Combined ivermectin and doxycycline treatment has microfilaricidal and adulticidal activity against Dirofilaria immitis in experimentally infected dogs.. There is still a pressing need for effective adulticide treatment for human and animal filarial infections. Like many filarial nematodes, Dirofilaria immitis, the causative agent of canine heartworm disease, harbours the bacterial endosymbiont Wolbachia, which has been shown to be essential for worm development, fecundity and survival. Here the authors report the effect of different treatment regimens in dogs experimentally infected with adult D. immitis on microfilariemia, antigenemia, worm recovery and Wolbachia content. Treatment with ivermectin (IVM; 6 microg/kg per os weekly) combined with doxycycline (DOXY; 10 mg/kg/day orally from Weeks 0-6, 10-12, 16-18, 22-26 and 28-34) resulted in a significantly faster decrease of circulating microfilariae and higher adulticidal activity compared with either IVM or DOXY alone. Quantitative PCR analysis of ftsZ (Wolbachia DNA) and 18S rDNA (nematode DNA) absolute copy numbers showed significant decreases in Wolbachia content compared with controls in worms recovered from DOXY-treated dogs that were not, however, associated with worm death. Worms from IVM/DOXY-treated dogs, on the other hand, had Wolbachia/nematode DNA ratios similar to those of control worms, suggesting a loss of both Wolbachia and nematode DNA as indicated by absolute copy number values. Histology and transmission electron microscopy of worms recovered from the IVM/DOXY combination group showed complete loss of uterine content in females and immunohistochemistry for Wolbachia was negative. Results indicate that the combination of these two drugs causes adult worm death. This could have important implications for control of human and animal filarial infections.

Question: What is the effect of the combination of ivermectin and doxycycline on adult worms?


Effective resource management for enhancing performance of 2D and 3D stencils on GPUs. GPUs are an attractive target for data parallel stencil computations prevalent in scientific computing and image processing applications. Many tiling schemes, such as overlapped tiling and split tiling, have been proposed in past to improve the performance of stencil computations. While effective for 2D stencils, these techniques do not achieve the desired improvements for 3D stencils due to the hardware constraints of GPU.  A major challenge in optimizing stencil computations is to effectively utilize all resources available on the GPU. In this paper we develop a tiling strategy that makes better use of resources like shared memory and register file available on the hardware. We present a systematic methodology to reason about which strategy should be employed for a given stencil and also discuss implementation choices that have a significant effect on the achieved performance. Applying these techniques to various 2D and 3D stencils gives a performance improvement of 200-400% over existing tools that target such computations.

Question: What is a stencil?


Face recognition using PCA-based method. The objective of this paper is to develop the image processing and recognize the faces using PCA-based face recognition technique. MATLAB based programs are implemented to identify the faces using Indian databases and the Face recognition data, University of Essex, UK. For matching unknown images with known images, different techniques like sum of absolute difference (SAD), sum of squared difference (SSD), normalized cross correlation (NCC) etc. can be used which has been shown in this paper. Finally, it has been shown that the performance of PCA-based face recognition system is quite satisfactory instead of having some shortcomings of the system. (Abstract)

Question: What is PCA-based face recognition?


Anime Artist Analysis based on CNN. Artist recognition is not easy for human beings if the artworks are general and 1 share many similarities, but modern machine learning or deep learning models may 2 help people identify the artwork authors. In this project, we trained Convolutional 3 Neural Networks (CNN) identifying Japanese anime artists. Our dataset was 4 crawled from Pixiv, a well-known Japanese website containing lots of fine anime 5 artworks. Specifically, the dataset has 9 authors and each one has 200 paintings. 6 We trained different kinds of networks, from a very basic Conv2D net to more 7 advanced networks, in order to carry out the identification. It turned out that 8 traditional neural networks can in some way identify different authors, but the 9 accuracy could be improved to a better level by tuning hyperparameters or using 10 more advanced networks such as ResNet and VGGNet. 11

Question: How to identify anime artists?


Modeling and Verification of a Six-Phase Interior Permanent Magnet Synchronous Motor. In this paper, a new mathematical modeling for a six-phase interior permanent magnet synchronous motor (IPMSM) is presented. The proposed model utilizes two synchronous reference frames. First, the flux model in the <inline-formula> <tex-math notation="LaTeX">$abcxyz$</tex-math></inline-formula> frame is mapped into the stationary <inline-formula> <tex-math notation="LaTeX">$dq$</tex-math></inline-formula> frames and then to two synchronous rotating frames. Then, differentiating the flux models, voltage equations are derived in rotating frames. Through this analysis, the interaction between the <inline-formula><tex-math notation="LaTeX">$abc$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$xyz$</tex-math></inline-formula> subsystems is properly described by a coupling matrix. The torque equation is also derived using the two reference current variables. Flux model was verified through FEM analysis. Experiments were done using a 100 kW six-phase IPMSM in a dynamo system. The validity of the torque equation was checked with some experimental results under a shorted condition on an <inline-formula><tex-math notation="LaTeX">$xyz$</tex-math></inline-formula> subsystem.

Question: How to model a six-phase IPMSM?


Head Pose and Expression Transfer Using Facial Status Score. We propose a method to transfer both head poseand facial expression of a source person in a video to the faceof a target person in an output video. Our method models theentire 2D frame instead of the 3D face, and it generates outputresults using a status score, which includes the relative facialstatus about the head pose and expression in a frame. From thetarget video, the learning process obtains frame features neededfor moving to each frame from the neutral frame for all frames,and generates the basis of these features via principal componentanalysis (PCA). Then, it learns to generate these features from agiven status score sequentially. In the transfer process, it obtainsa status score from a source frame of the video and generatesthe features from the given status score. Then, it generates theoutput frame using the reconstructed features. An output videois generated by repeating these steps for each source frame.Our method generates output results on the trajectory of thetarget video by using the advantage of PCA. Therefore, in theoutput results generated by our methods, both head pose andexpression are transferred correctly while the non-face regionsof the frames are supported. Finally, we experimentally comparethe effectiveness of our method and conventional methods.

Question: How to transfer head pose and expression?


Using grid for accelerating density-based clustering. Clustering analysis is a primary method for data mining. The ever increasing volumes of data in different applications forces clustering algorithms to cope with it. DBSCAN is a well-known algorithm for density-based clustering. It is both effective so it can detect arbitrary shaped clusters of dense regions and efficient especially in existence of spatial indexes to perform the neighborhood queries efficiently. In this paper we introduce a new algorithm GriDBSCAN to enhance the performance of DBSCAN using grid partitioning and merging, yielding a high performance with the advantage of high degree of parallelism. We verified the correctness of the algorithm theoretically and experimentally, studied the performance theoretically and using experiments on both real and synthetic data. It proved to run much faster than original DBSCAN. We compared the algorithm with a similar algorithm, EnhancedDBSCAN, which is also an enhancement to DBSCAN using partitioning. Experiments showed the new algorithm's superiority in performance and degree of parallelism.

Question: How to accelerate density-based clustering?


Detecting and Tracking Political Abuse in Social Media. We study astroturf political campaigns on microblogging platforms: politically-motivated individuals and organizations that use multiple centrally-controlled accounts to create the appearance of widespread support for a candidate or opinion. We describe a machine learning framework that combines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation. We present promising preliminary results with better than 96% accuracy in the detection of astroturf content in the run-up to the 2010 U.S. midterm elections.

Question: What is astroturf?


Bare bones differential evolution. Article history: Received 22 August 2007 Accepted 29 February 2008 Available online xxxx

Question: What is the history of differential evolution?


Design and control of a GaN-based, 13-level, flying capacitor multilevel inverter. Multilevel topologies are an appealing method to achieve higher power density inverters for both mobile and stationary systems. This work discusses the design and development of a 13-level, flying capacitor multilevel (FCML) inverter. Operating from an 800 V bus, this inverter requires switches with a voltage blocking capability of less than 80 V. A 120 kHz switching frequency is enabled through the use of GaN FETs and the development of custom integrated switching cells, which reduce commutation loop inductance and allow for a modular design. Additionally, the frequency multiplication effect of FCML inverters allows the output inductor of the inverter to be made exceptionally small (4.7 μH) while maintaining a 0.7 % THD due to the 1.44 MHz effective inductor ripple frequency.

Question: What is a flying capacitor multilevel inverter?


Dialogue-act-driven Conversation Model : An Experimental Study. The utility of additional semantic information for the task of next utterance selection in an automated dialogue system is the focus of study in this paper. In particular, we show that additional information available in the form of dialogue acts –when used along with context given in the form of dialogue history– improves the performance irrespective of the underlying model being generative or discriminative. In order to show the model agnostic behavior of dialogue acts, we experiment with several well-known models such as sequence-to-sequence encoder-decoder model, hierarchical encoder-decoder model, and Siamese-based models with and without hierarchy; and show that in all models, incorporating dialogue acts improves the performance by a significant margin. We, furthermore, propose a novel way of encoding dialogue act information, and use it along with hierarchical encoder to build a model that can use the sequential dialogue act information in a natural way. Our proposed model achieves an MRR of about 84.8% for the task of next utterance selection on a newly introduced DailyDialog dataset, and outperform the baseline models. We also provide a detailed analysis of results including key insights that explain the improvement in MRR because of dialogue act information.

Question: What is the utility of dialogue acts in an automated dialogue system?


Multilevel Converters as a Utility Interface for Renewable Energy Systems. Electric power production in the 21 Century will see dramatic changes in both the physical infrastructure and the control and information infrastructure. A shift will take place from a relatively few large, concentrated generation centers and the transmission of electricity over mostly a high voltage ac grid (Fig. 1) to a more diverse and dispersed generation infrastructure that also has a higher percentage of dc transmission lines (Fig. 2) [1]. In the United States, generation capacity has not kept up with power demands, as over the last decade the reserve margins declined from 22% in 1990 to 16% in 1997. This declining margin trend is expected to continue over the next decade partly because of the uncertainty of how the future deregulated electrical environment will function. Less reserve margins will lead to less peaking capacity on highdemand days and more volatile energy prices [2]. This change in a physical infrastructure combined with a more deregulated electric power industry will result in more parties generating power – or distributed generation. Some of the distributed generation power sources that are expected to increase greatly their market share of the total power produced in the United States and abroad include renewable energy sources such as photovoltaics, wind, low-head hydro, and geothermal [3]. Fuel cell technology is also nearing the development point where it could start to supply a significant share of the power needs [4]. The advent of high power electronic modules has also encouraged the use of more dc transmission and made the prospects of interfacing dc power sources such as fuel cells and photovoltaics more easily attainable. A modular, scalable power electronics technology that is ideal for these types of utility applications is the transformerless multilevel converter [5].

Question: What is a multilevel converter?


Anti-steganalysis for image on convolutional neural networks. Nowadays, convolutional neural network (CNN) based steganalysis methods achieved great performance. While those methods are also facing security problems. In this paper, we proposed an attack scheme aiming at CNN based steganalyzer including two different attack methods 1) the LSB-Jstego Gradient Based Attack; 2) LSB-Jstego Evolutionary Algorithms Based Attack. The experiment results show that the attack strategies could achieve 96.02% and 90.25% success ratio separately on the target CNN. The proposed attack scheme is an effective way to fool the CNN based steganalyzer and in addition demonstrates the vulnerability of the neural networks in steganalysis.

Question: How to attack CNN based steganalyzer?


ABF + + : Fast and Robust Angle Based Flattening Temporary version-In print. Conformal parameterization of mesh models has numerous applications in geometry processing. Conformality is desirable for remeshing, surface reconstruction, and many other mesh processing applications. Subject to the conformality requirement, these applications typically bene t from parameterizations with smaller stretch. The Angle Based Flattening (ABF) method, presented a few years ago, generates provably valid conformal parameterizations with low stretch. However, it is quite time consuming and becomes error prone for large meshes due to numerical error accumulation. This work presents ABF++, a highly e cient extension of the ABF method that overcomes these drawbacks, while maintaining all the advantages of ABF. ABF++ robustly parameterizes meshes of hundreds of thousands and millions of triangles within minutes. It is based on two main components: (1) a new numerical solution technique that dramatically reduces the dimension of the linear systems solved at each iteration, speeding up the solution; (2) an e cient hierarchical solution technique. The speedup with (1) does not come at the expense of greater distortion. The hierarchical technique (2) enables parameterization of models with millions of faces in seconds, at the expense of a minor increase in parametric distortion. The parameterization computed by ABF++ are provably valid, i.e. they contain no ipped triangles. As a result of these extensions, the ABF++ method is extremely suitable for robustly and e ciently parameterizing models for geometry processing applications.

Question: What is the ABF++ method?


Real-time object classification in 3D point clouds using point feature histograms. This paper describes a LIDAR-based perception system for ground robot mobility, consisting of 3D object detection, classification and tracking. The presented system was demonstrated on-board our autonomous ground vehicle MuCAR-3, enabling it to safely navigate in urban traffic-like scenarios as well as in off-road convoy scenarios. The efficiency of our approach stems from the unique combination of 2D and 3D data processing techniques. Whereas fast segmentation of point clouds into objects is done in a 2 D occupancy grid, classifying the objects is done on raw 3D point clouds. For fast object feature extraction, we advocate the use of statistics of local point cloud properties, captured by histograms over point features. In contrast to most existing work on 3D point cloud classification, where real-time operation is often impossible, this combination allows our system to perform in real-time at 0.1s frame-rate.

Question: What is a LIDAR?


Demand Side Management in Smart Grids. Smart grids are considered to be the next generation electric grids. Drivers for this development are among others: an increased electricity demand, an ageing network infrastructure and an increased share of renewable energy sources. Sustainability and the European 20/20/20 climate and energy targets are also main drivers for this development. Some of the important aspects of smart grids are that they allow two-way communication between the actors in the grid and enable optimisation of electricity use and production and customer participation. Demand side management is associated to smart grids and means adapting the electricity demand to the electricity production and the available electricity in the grid. It is considered that smart grids and demand side management hold potential to facilitate an increased share of renewable energy sources and to reduce the need for the current power reserve, which is based on fossil energy sources. The aim of this study was to compile and analyse some of the work that has been done and is being implemented around the world concerning demand side management in smart grids with a focus on market rules and business models in relation to Swedish conditions. The study includes a review of selected research and demonstration projects. Success factors and knowledge gaps have been identified through an analysis of the project findings and recommendations. A description of the current Nordic market conditions is also given. The conclusions regarding the conditions on the Swedish electricity market is that it appears to be relatively well adjusted to demand side management with the possibility for hourly meter readings and a full deployment of smart meters. The Nord Pool electricity market allows both day-ahead trading and intra-day trading on the elspot and the elbas markets. The review of the projects show that there is a potential for achieving flexible load from private customers. Hourly metering

Question: What is the Nord Pool electricity market?


Event Detection in Social Media Detecting. The proliferation of social media and user-generated content in the Web has opened new opportunities for detecting and disseminating information quickly. The Twitter stream is one large source of information, but the magnitude of tweets posted and the noisy nature of its content makes the harvesting of knowledge from Twitter very hard. Aiming at overcoming some of the challenges and extract some of the hidden information, this thesis proposes a system for real-time detection of news events from the Twitter stream. The first step of our approach is to let a classifier, based on an Artificial Neural Network and deep learning, detect news relevant tweets from the stream. Next, a novel streaming data clustering algorithm is applied to the detected news tweets to form news events. Finally, the events of highest interest is retrieved based on events' sizes and rapid growth in tweet frequencies, before the news events are presented and visualized in a web user interface. We evaluate the proposed system on a large, publicly available corpus of annotated news events from Twitter. As part of the evaluation, we compare our approach with a related state-of-the-art solution. Overall, our experiments and user-based evaluation show that our approach on detecting current (real) news events delivers state-of-the-art performance.

Question: How to detect news events from Twitter?


Predicting Movie Sales from Blogger Sentiment. The volume of discussion about a product in weblogs has recently been shown to correlate with the product's financial performance. In this paper, we study whether applying sentiment analysis methods to weblog data results in better correlation than volume only, in the domain of movies. Our main finding is that positive sentiment is indeed a better predictor for movie success when applied to a limited context around references to the movie in weblogs, posted prior to its release. If my film makes one more person miserable, I've done my job.

Question: How to predict movie sales from weblogs?


SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery. In this paper we present the novel SD-Map algorithm for exhaustive but efficient subgroup discovery. SD-Map guarantees to identify all interesting subgroup patterns contained in a data set, in contrast to heuristic or samplingbased methods. The SD-Map algorithm utilizes the well-known FP-growth method for mining association rules with adaptations for the subgroup discovery task. We show how SD-Map can handle missing values, and provide an experimental evaluation of the performance of the algorithm using synthetic data.

Question: What is the SD-Map algorithm?


Minoxidil-induced trichostasis spinulosa of terminal hair.. depression after pressure application to the skin and a fold after stretching of the skin are clinical signs of CL. To our knowledge, the exclusive acral involvement of CL has been reported in only 7 patients, and 4 of them also had multiple myeloma amyloidosis. Unlike those 4 patients, our patient manifested elastolytic cutaneous lesions as the only clinical sign of his multiple myeloma. The histopathologic findings were the clue for the diagnosis of underlying monoclonal gammopathy. Destruction of elastic fibers could be immune mediated by deposition of abnormal proteins. Wewould like toemphasize the importanceof recognizing cutaneous laxity on fingertips associated with temporary dimpling of the skin for minutes after pressure is applied, which can be the clue for the diagnosis of a monoclonalgammopathy.Clinicopathologiccorrelationisessential; demonstration of amyloid deposits with monotypic expression of light chains and diminution of dermal elastic fibers are the histopathologic clues of these forms of acrolocalized acquired CL associated with multiple myeloma.

Question: What is the clinical clue for the diagnosis of a monoclonalgammopathy?


CiteSeer: An Automatic Citation Indexing System. We presentCiteSeer : an autonomous citation indexing system which indexes academic literature in electronic format (e.g. Postscript files on the Web). CiteSeer understands how to parse citations, identify citations to the same paper in d ifferent formats, and identify the context of citations in the body of articles. CiteSeer provides most of the advantages o f traditional (manually constructed) citation indexes (e.g . the ISI citation indexes), including: literature retrieval by following citation links (e.g. by providing a list of papers tha cite a given paper), the evaluation and ranking of papers, au thors, journals, etc. based on the number of citations, and t he identification of research trends. CiteSeer has many advantages over traditional citation indexes, including the abi lity to create more up-to-date databases which are not limited to a preselected set of journals or restricted by journal public ation delays, completely autonomous operation with a correspond ing reduction in cost, and powerful interactive browsing of the literature using the context of citations. Given a parti cular paper of interest, CiteSeer can display the context of ho w the paper is cited in subsequent publications. This context may contain a brief summary of the paper, another author's response to the paper, or subsequent work which builds upon the original article. CiteSeer allows the location of paper s by keyword search or by citation links. Papers related to a give n paper can be located using common citation information or word vector similarity. CiteSeer will soon be available for public use.

Question: What is the context of a paper?


Combining Textual Entailment and Argumentation Theory for Supporting Online Debates Interactions. Blogs and forums are widely adopted by online communities to debate about various issues. However, a user that wants to cut in on a debate may experience some difficulties in extracting the current accepted positions, and can be discouraged from interacting through these applications. In our paper, we combine textual entailment with argumentation theory to automatically extract the arguments from debates and to evaluate their acceptability.

Question: How to extract arguments from debates?


Euthanasia and physician-assisted suicide: focus on the data.. 1 MBritain and the United States began in the late 19th century. Legislation was periodically proposed only to be defeated until, in 1942, Switzerland decriminalised assistance in suicide for cases when there were no "selfish motives". In 2002, euthanasia was legalised in the Netherlands and Belgium, then in Luxembourg in 2009, and most recently, in 2015 in Colombia and in 2016 in Canada. PAS, but not euthanasia, has been legalised in five US states. In Oregon, PAS was legalised by popular referendum in 1997. In addition, in 2009, Washington State legalised PAS by referendum and Montana by court ruling; Vermont in 2013 and California in 2015 also legalised PAS by legislation.

Question: What is euthanasia?


Avoiding Confusing Features in Place Recognition. We seek to recognize the place depicted in a query image using a database of "street side" images annotated with geolocation information. This is a challenging task due to changes in scale, viewpoint and lighting between the query and the images in the database. One of the key problems in place recognition is the presence of objects such as trees or road markings, which frequently occur in the database and hence cause significant confusion between different places. As the main contribution, we show how to avoid features leading to confusion of particular places by using geotags attached to database images as a form of supervision. We develop a method for automatic detection of image-specific and spatially-localized groups of confusing features, and demonstrate that suppressing them significantly improves place recognition performance while reducing the database size. We show the method combines well with the state of the art bag-of-features model including query expansion, and demonstrate place recognition that generalizes over wide range of viewpoints and lighting conditions. Results are shown on a geotagged database of over 17K images of Paris downloaded from Google Street View.

Question: How to avoid confusing features in place recognition?


Client-Side Defense Against Web-Based Identity Theft. Web spoofing is a significant problem involving fraudulent email and web sites that trick unsuspecting users into revealing private information. We discuss some aspects of common attacks and propose a framework for client-side defense: a browser plug-in that examines web pages and warns the user when requests for data may be part of a spoof attack. While the plugin, SpoofGuard, has been tested using actual sites obtained through government agencies concerned about the problem, we expect that web spoofing and other forms of identity theft will be continuing problems in

Question: What is client-side defense against web-based identity theft?


Competency based management: a review of systems and approaches. Purpose – Aims to review the key concepts of competency management (CM) and to propose method for developing competency method. Design/methodology/approach – Examines the CM features of 22 CM systems and 18 learning management systems. Findings – Finds that the areas of open standard (XML, web services, RDF), semantic technologies (ontologies and the semantic web) and portals with self-service technologies are going to play a significant part in the evolution of CM systems. Originality/value – Emphasizes the beneficial attributes of CM for private and public organizations.

Question: What is the purpose of competency based management?


Analysis of Load Balancing Techniques in Cloud Computing. Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. So, the amount of data storage increases quickly. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is necessary to utilize resources efficiently. This paper discusses some of the existing load balancing algorithms in cloud computing and also their challenges.

Question: What is cloud computing?


Lessons from the journey: a query log analysis of within-session learning. The Internet is the largest source of information in the world. Search engines help people navigate the huge space of available data in order to acquire new skills and knowledge. In this paper, we present an in-depth analysis of sessions in which people explicitly search for new knowledge on the Web based on the log files of a popular search engine. We investigate within-session and cross-session developments of expertise, focusing on how the language and search behavior of a user on a topic evolves over time. In this way, we identify those sessions and page visits that appear to significantly boost the learning process. Our experiments demonstrate a strong connection between clicks and several metrics related to expertise. Based on models of the user and their specific context, we present a method capable of automatically predicting, with good accuracy, which clicks will lead to enhanced learning. Our findings provide insight into how search engines might better help users learn as they search.

Question: How to predict which clicks will lead to enhanced learning?


A deep reinforcement learning based framework for power-efficient resource allocation in cloud RANs. Cloud Radio Access Networks (RANs) have become a key enabling technique for the next generation (5G) wireless communications, which can meet requirements of massively growing wireless data traffic. However, resource allocation in cloud RANs still needs to be further improved in order to reach the objective of minimizing power consumption and meeting demands of wireless users over a long operational period. Inspired by the success of Deep Reinforcement Learning (DRL) on solving complicated control problems, we present a novel DRL-based framework for power-efficient resource allocation in cloud RANs. Specifically, we define the state space, action space and reward function for the DRL agent, apply a Deep Neural Network (DNN) to approximate the action-value function, and formally formulate the resource allocation problem (in each decision epoch) as a convex optimization problem. We evaluate the performance of the proposed framework by comparing it with two widely-used baselines via simulation. The simulation results show it can achieve significant power savings while meeting user demands, and it can well handle highly dynamic cases.

Question: What is the power consumption of a cloud radio access network?


Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach. Despite the popularity, the tuning aspect of proportional–integral-derivative (PID) controllers is a challenge for researchers and plant operators. Various controllers tuning methodologies have been proposed in the literature such as auto-tuning, self-tuning, pattern recognition, artificial intelligence, and optimization methods. Chaotic optimization algorithms as an emergent method of global optimization have attracted much attention in engineering applications. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool for engineering applications. In this paper, a tuning method for determining the parameters of PID control for an automatic regulator voltage (AVR) system using a chaotic optimization approach based on Lozi map is proposed. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Simulation results are promising and show the effectiveness of the proposed approach. Numerical simulations based on proposed PID control of an AVR system for nominal system parameters and step reference voltage input demonstrate the good performance of chaotic optimization. 2007 Elsevier Ltd. All rights reserved.

Question: Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach.


VeriCon: towards verifying controller programs in software-defined networks. Software-defined networking (SDN) is a new paradigm for operating and managing computer networks. SDN enables logically-centralized control over network devices through a "controller" software that operates independently from the network hardware, and can be viewed as the network operating system. Network operators can run both inhouse and third-party SDN programs (often called applications) on top of the controller, e.g., to specify routing and access control policies. SDN opens up the possibility of applying formal methods to prove the correctness of computer networks. Indeed, recently much effort has been invested in applying finite state model checking to check that SDN programs behave correctly. However, in general, scaling these methods to large networks is challenging and, moreover, they cannot guarantee the absence of errors.  We present VeriCon, the first system for verifying that an SDN program is correct on all admissible topologies and for all possible (infinite) sequences of network events. VeriCon either confirms the correctness of the controller program on all admissible network topologies or outputs a concrete counterexample. VeriCon uses first-order logic to specify admissible network topologies and desired network-wide invariants, and then implements classical Floyd-Hoare-Dijkstra deductive verification using Z3. Our preliminary experience indicates that VeriCon is able to rapidly verify correctness, or identify bugs, for a large repertoire of simple core SDN programs. VeriCon is compositional, in the sense that it verifies the correctness of execution of any single network event w.r.t. the specified invariant, and can thus scale to handle large programs. To relieve the burden of specifying inductive invariants from the programmer, VeriCon includes a separate procedure for inferring invariants, which is shown to be effective on simple controller programs. We view VeriCon a

Question: What is software-defined networking?


One-Class Convolutional Neural Network. We present a novel convolutional neural network (CNN) based approach for one-class classification. The idea is to use a zero centered Gaussian noise in the latent space as the pseudo-negative class and train the network using the cross-entropy loss to learn a good representation as well as the decision boundary for the given class. A key feature of the proposed approach is that any pre-trained CNN can be used as the base network for one-class classification. The proposed one-class CNN is evaluated on the UMDAA-02 Face, Abnormality-1001, and FounderType-200 datasets. These datasets are related to a variety of one-class application problems such as user authentication, abnormality detection, and novelty detection. Extensive experiments demonstrate that the proposed method achieves significant improvements over the recent state-of-the-art methods. The source code is available at: github.com/otkupjnoz/oc-cnn.

Question: What is the source code for the one-class convolutional neural network?


Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning. A heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavation site. An approach is presented to the automatic estimation of mathematical models of such pots from 3D measurements of sherds. A Bayesian approach is formulated beginning with a description of the complete set of geometric parameters that determine the distribution of the sherd measurement data. Matching of fragments and aligning them geometrically into configurations is based on matching break-curves (curves on a pot surface separating fragments), estimated axis and profile curve pairs for individual fragments and configurations of fragments, and a number of features of groups of break-curves. Pot assembly is a bottom-up maximum likelihood performance-based search. Experiments are illustrated on pots which were broken for the purpose, and on sherds from an archaeological dig located in Petra, Jordan. The performance measure can also be aposteriori probability, and many other types of information can be included, e.g., pot wall thickness, surface color, patterns on the surface, etc. This can also be viewed as the problem of learning a geometric object from an unorganized set of free-form fragments of the object and of clutter, or as a problem of perceptual grouping.

Question: How to assemble pots from sherds?


Combined Phase-Shift and Frequency Modulation of a Dual-Active-Bridge AC–DC Converter With PFC. This paper presents a combined phase-shift and frequency modulation scheme of a dual-active-bridge (DAB) ac- dc converter with power factor correction (PFC) to achieve zero voltage switching (ZVS) over the full range of the ac mains voltage. The DAB consists of a half bridge with bidirectional switches on the ac side and a full bridge on the dc side of the isolation transformer to accomplish single-stage power conversion. The modulation scheme is described by means of analytical formulas, which are used in an optimization procedure to determine the optimal control variables for minimum switch commutation currents. Furthermore, an ac current controller suitable for the proposed modulation scheme is described. A loss model and measurements on a 3.3-kW electric vehicle battery charger to connect to the 230 Vrms / 50-Hz mains considering a battery voltage range of 280-420 V validate the theoretical analysis.

Question: What is the difference between a phase-shift and a frequency modulation scheme?


Information Gain-based Exploration Using Rao-Blackwellized Particle Filters. This paper presents an integrated approach to exploration, mapping, and localization. Our algorithm uses a highly efficient Rao-Blackwellized particle filter to represent the posterior about maps and poses. It applies a decision-theoretic framework which simultaneously considers the uncertainty in the map and in the pose of the vehicle to evaluate potential actions. Thereby, it trades off the cost of executing an action with the expected information gain and takes into account possible sensor measurements gathered along the path taken by the robot. We furthermore describe how to utilize the properties of the Rao-Blackwellization to efficiently compute the expected information gain. We present experimental results obtained in the real world and in simulation to demonstrate the effectiveness of our approach.

Question: What is the information gain?


Dispositional Factors in Internet Use: Personality Versus Cognitive Style. This study directly tests the effect of personality and cognitive style on three measures of Internet use. The results support the use of personality—but not cognitive style—as an antecedent variable. After controlling for computer anxiety, selfefficacy, and gender, including the "Big Five" personality factors in the analysis significantly adds to the predictive capabilities of the dependent variables. Including cognitive style does not. The results are discussed in terms of the role of personality and cognitive style in models of technology adoption and use.

Question: What is the effect of personality on internet use?


Risks and benefits of social media for children and adolescents.. Resources • AAP Internet safety resources site, http:// safetynet.aap.org • CDC Social Media Tools Guidelines & Best Practices site, http://www.cdc.gov/ SocialMedia/Tools/ guidelines/ • Common Sense Media (2009). Is technology changing childhood? A national poll on teens and social networking. R e t r i e v e d f r om http://www.commonsensemedia.org/teensocial-media. FACEBOOK, TWITTER, AND YouTube bring benefits to children and teenagers, including enhancing communication, broadening social connections, and learning technical skills, but can also expose them to risks, such as cyberbullying, "Facebook depression," and "sexting," according to a new report by the American Academy of Pediatrics (AAP; O'Keeffe, Clarke-Pearson, & Council on Communications and Media, 2011). The new report outlines the latest research on one of the most common activities among today's children and teenagers and describes how health care providers can help families understand these sites and encourage their healthy use. The report considers any site that allows social interaction as a social media site, including social networking sites such as Facebook, MySpace, and Twitter; gaming sites and virtual worlds such as Club Penguin, Second Life, and the Sims; video sites such as YouTube; and blogs. The abundance of these sites has grown exponentially in recent years. According to a poll cited in the report, more than half of American teenagers log onto their favorite social media site at least once a day, whereas 22% do so at least 10 times a day; 75% of teenagers now own cell phones, with 54% of them using them for texting, 24% for instant messaging, and 25% for social media access. According to the authors of the new report, increase in social media has been so rapid and their presence in children's everyday life is now so pervasive that, for some teens, social media is the primary way they interact socially, and a large part of

Question: What is the difference between social media and social networking?


Adwords management for third-parties in SEM: An optimisation model and the potential of Twitter. In Search Engine Marketing (SEM), "third-party" partners play an important intermediate role by bridging the gap between search engines and advertisers in order to optimise advertisers' campaigns in exchange of a service fee. In this paper, we present an economic analysis of the market involving a third-party broker in Google AdWords and the broker's customers. We show that in order to optimise his profit, a third-party broker should minimise the weighted average Cost Per Click (CPC) of the portfolio of keywords attached to customer's ads while still satisfying the negotiated customer's demand. To help the broker build and manage such portfolio of keywords, we develop an optimisation framework inspired from the classical Markowitz portfolio management which integrates the customer's demand constraint and enables the broker to manage the tradeoff between return on investment and risk through a single risk aversion parameter. We then propose a method to augment the keywords portfolio with relevant keywords extracted from trending and popular topics on Twitter. Our evaluation shows that such a keywords-augmented strategy is very promising and enables the broker to achieve, on average, four folds larger return on investment than with a non-augmented strategy, while still maintaining the same level of risk.

Question: What is the cost of adwords management for third-parties?


Characterization of the Impact of Hardware Islands on OLTP. Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database systems mostly assume that all processing cores are the same and that microarchitecture differences are not significant enough to appear in critical database execution paths. As we demonstrate in this paper, however, non-uniform core topology does appear in the critical path and conventional database architectures achieve suboptimal and even worse, unpredictable performance. We perform a detailed performance analysis of OLTP deployments in servers with multiple cores per CPU (multicore) and multiple CPUs per server (multisocket). We compare different database deployment strategies where we vary the number and size of independent database instances running on a single server, from a single shared-everything instance to fine-grained shared-nothing configurations. We quantify the impact of non-uniform hardware on various deployments by (a) examining how efficiently each deployment uses the available hardware resources and (b) measuring the impact of distributed transactions and skewed requests on different workloads. We show that no strategy is optimal for all cases and that the best choice depends on the combination of hardware topology and workload characteristics. Finally, we argue that transaction processing systems must be aware of the hardware topology in order to achieve predictably high performance.

Question: How to characterize the impact of hardware islands on OLTP.


Older adults' views of "successful aging"--how do they compare with researchers' definitions?. OBJECTIVES To determine whether older adults have thought about aging and aging successfully and to compare their perceptions of successful aging with attributes of successful aging identified in the published literature.   DESIGN A cross-sectional, mailed survey.   SETTING King County, Washington.   PARTICIPANTS Nondemented participants from two cohorts. The first cohort, referred to as Kame, which means turtle, a symbol of longevity for Japanese, enrolled 1,985 Japanese Americans aged 65 and older and was established in 1992-94. The second cohort, Adult Changes in Thought, enrolled 2,581 white men and women aged 65 and older from a health maintenance organization and was established in 1994-96.   MEASUREMENTS Respondents were asked whether they had ever thought about aging and aging successfully and whether these thoughts had changed over the previous 20 years and about how important specific attributes, originating from the published literature, were in characterizing successful aging.   RESULTS Overall, 90% had previously thought about aging and aging successfully, and approximately 60% said their thoughts had changed over the previous 20 years. The Japanese-American group rated 13 attributes as important to successful aging; the white group rated the same 13 as important and added one additional attribute, learning new things.   CONCLUSION Older adults' definition of successful aging is multidimensional, encompassing physical, functional, psychological, and social health. In contrast, none of the published work describing attributes of successful aging includes all four dimensions. Future work would benefit from an expanded definition to adequately reflect the perceptions of older adults.

Question: What are the attributes of successful aging?


Biomedical Event Extraction using Abstract Meaning Representation. We propose a novel, Abstract Meaning Representation (AMR) based approach to identifying molecular events/interactions in biomedical text. Our key contributions are: (1) an empirical validation of our hypothesis that an event is a subgraph of the AMR graph, (2) a neural network-based model that identifies such an event subgraph given an AMR, and (3) a distant supervision based approach to gather additional training data. We evaluate our approach on the 2013 Genia Event Extraction dataset1 (Kim et al., 2013) and show promising results.

Question: What is the 2013 Genia Event Extraction dataset?


A Tlreshold Selection Method from Gray-Level Histograms. A nonparametric and unsupervised method ofautomatic threshold selection for picture segmentation is presented. An optimal threshold is selected by the discriminant criterion, namely, so as to maximize the separability of the resultant classes in gray levels. The procedure is very simple, utilizing only the zerothand the first-order cumulative moments of the gray-level histogram. It is straightforward to extend the method to multithreshold problems. Several experimental results are also presented to support the validity of the method.

Question: What is a gray-level histogram?


Smart agent based prepaid wireless energy meter. Prepaid meter (PM) is getting very popular especially in developing countries. There are many advantages to use prepaid meter as opposed to postpaid meter both to the utility provider and to the consumer. Brunei Darussalam has adopted PM but it is not intelligent and not wireless enabled. Reading meters and topping up balance are still done manually. Utility provider does not have information on the usage statistics and has only limited functionalities in the grid control. So accordingly a novel software agent based wireless prepaid energy meter was developed using Java Agent Development Environment (JADE-LEAP) allowing agent from utility provider to query wireless energy meter for energy values of every household. These statistics can be used for statistical computation of the power consumed and for policy and future planning.

Question: What is the advantage of using prepaid meter?


Suppression by Selecting Wavelets for Feature Compression in Distributed Speech Recognition. Distributed speech recognition DSR splits the processing of data between a mobile device and a network server. In the front-end, features are extracted and compressed to transmit over a wireless channel to a back-end server, where the incoming stream is received and reconstructed for recognition tasks. In this paper, we propose a feature compression algorithm termed suppression by selecting wavelets SSW to achieve the two main goals of DSR: Minimizing memory and device requirements while also maintaining or even improving the recognition performance. The SSW approach first applies the discrete wavelet transform DWT to filter the incoming speech feature sequence into two temporal subsequences at the client terminal. Feature compression is achieved by keeping the low modulation frequency subsequence while discarding the high frequency counterpart. The low-frequency subsequence is then transmitted across the remote network for specific feature statistics normalization. Wavelets are favorable for resolving the temporal properties of the feature sequence, and the down-sampling process in DWT achieves data compression by reducing the amount of data at the terminal prior to transmission across the network. Once the compressed features have arrived at the server, the feature sequence can be enhanced by statistics normalization, reconstructed with inverse DWT, and compensated with a simple post filter to alleviate any over-smoothing effects from the compression stage. Results on a standard robustness task Aurora-4 and on a Mandarin Chinese news corpus showed SSW outperforms conventional noise-robustness techniques while also providing nearly a 50% compression rate during the transmission stage of DSR systems.

Question: What is the difference between a speech recognition system and a speech recognition system?


Exploiting the Data Redundancy Locality to Improve the Performance of Deduplication-Based Storage Systems. The chunk-lookup disk bottleneck and the read amplification problems are two great challenges for deduplication-based storage systems and restrict the applicability of data deduplication for large-scale data volumes. Previous studies and our experimental evaluations have shown that the amount of redundant data shared among different types of applications is negligible. Based on the observations, we propose AA-Plus which effectively groups the hash index of the same application together and divides the whole hash index into different groups based on the application types. Moreover, it groups the data chunks of the same application together on the disks. The extensive trace-driven experiments conducted on our lightweight prototype implementation of AA-Plus show that compared with AA-Dedupe, AA-Plus significantly speeds up the write throughput by a factor of up to 6.9 and with an average of 3.1, and speeds up the read throughput by a factor of up to 3.3 and with an average of 1.9.

Question: How does data deduplication work?


Finding unusual review patterns using unexpected rules. In recent years, opinion mining attracted a great deal of research attention. However, limited work has been done on detecting opinion spam (or fake reviews). The problem is analogous to spam in Web search [1, 9 11]. However, review spam is harder to detect because it is very hard, if not impossible, to recognize fake reviews by manually reading them [2]. This paper deals with a restricted problem, i.e., identifying unusual review patterns which can represent suspicious behaviors of reviewers. We formulate the problem as finding unexpected rules. The technique is domain independent. Using the technique, we analyzed an Amazon.com review dataset and found many unexpected rules and rule groups which indicate spam activities.

Question: What is the problem of detecting opinion spam?


Suitable MLP Network Activation Functions for Breast Cancer and Thyroid Disease Detection. This paper compared various MLP activation functions for classification problems. The most well-known (Artificial Neural Network) ANN architecture is the Multilayer Perceptron (MLP) network which is widely used for solving problems related to data classifications. Selection of the activation functions in the MLP network plays an essential role on the network performance. A lot of studies have been conducted by reseachers to investigate special activation function to solve different kind of problems. Therefore, this paper intends to investigate the activation functions in MLP networks in terms of the accuracy performances. The activation functions under investigation are sigmoid, hyperbolic tangent, neuronal, logarithmic, sinusoidal and exponential. Medical diagnosis data from two case studies, thyroid disease classification and breast cancer classification, have been used to test the performance of the MLP network. The MLP networks are trained using Back Propagation learning algorithm. The performance of the MLP networks are calculated based on the percentage of correct classificition. The results show that the hyperbolic tangent function in MLP network had the capability to produce the highest accuracy for classifying breast cancer data. Meanwhile, for thyroid disease classification, neuronal function is the most suitable function that performed the highest accuracy in MLP network.

Question: What is the most suitable activation function for MLP network?


Using plane + parallax for calibrating dense camera arrays. A light field consists of images of a scene taken from different viewpoints. Light fields are used in computer graphics for image-based rendering and synthetic aperture photography, and in vision for recovering shape. In this paper, we describe a simple procedure to calibrate camera arrays used to capture light fields using a plane + parallax framework. Specifically, for the case when the cameras lie on a plane, we show (i) how to estimate camera positions up to an affine ambiguity, and (ii) how to reproject light field images onto a family of planes using only knowledge of planar parallax for one point in the scene. While planar parallax does not completely describe the geometry of the light field, it is adequate for the first two applications which, it turns out, do not depend on having a metric calibration of the light field. Experiments on acquired light fields indicate that our method yields better results than full metric calibration.

Question: How to calibrate dense camera arrays using plane + parallax


A Study on Watermarking Schemes for Image Authentication. The digital revolution in digital image processing has made it possible to create, manipulate and transmit digital images in a simple and fast manner. The adverse affect of this is that the same image processing techniques can be used by hackers to tamper with any image and use it illegally. This has made digital image safety and integrity the top prioritized issue in today's information explosion. Watermarking is a popular technique that is used for copyright protection and authentication. This paper presents an overview of the various concepts and research works in the field of image watermark authentication. In particular, the concept of content-based image watermarking is reviewed in details.

Question: What is the difference between watermarking and watermarking?


Towards a taxonomy of intrusion-detection systems. Intrusion-detection systems aim at detecting attacks against computer systems and networks, or against information systems in general, as it is difficult to provide provably secure information systems and maintain them in such a secure state for their entire lifetime and for every utilization. Sometimes, legacy or operational constraints do not even allow a fully secure information system to be realized at all. Therefore, the task of intrusion-detection systems is to monitor the usage of such systems and to detect the apparition of insecure states. They detect attempts and active misuse by legitimate users of the information systems or external parties to abuse their privileges or exploit security vulnerabilities. In this paper, we introduce a taxonomy of intrusion-detection systems that highlights the various aspects of this area. This taxonomy defines families of intrusion-detection systems according to their properties. It is illustrated by numerous examples from past and current projects. q 1999 Elsevier Science B.V. All rights reserved.

Question: What is a taxonomy of intrusion-detection systems?


A stepped-carrier 77-GHz OFDM MIMO radar system with 4 GHz bandwidth. This paper presents a 77-GHz orthogonal frequency-division multiplexing (OFDM) multiple-input multiple-output (MIMO) radar system with 4 GHz bandwidth. Due to the limited bandwidth of the analog-to-digital and digital-to-analog converters a stepped-carrier approach is used. OFDM radar measurements with a bandwidth of 200MHz at 20 different carrier frequencies are combined in signal processing to achieve a high range resolution OFDM MIMO radar. Spectrally-interleaved OFDM signals are used to allow for simultaneous transmission and thus MIMO operation. The proposed approach is verified in practical measurements of a static target scenario and a slowly moving target scenario. Therefore a self-developed software defined radar evaluation platform with four transmitters and four receivers is used. The expected high range resolution could be achieved and range/angle/velocity measurements show the suitability for detecting slowly moving targets like pedestrians.

Question: What is a stepped-carrier 77-GHz OFDM MIMO radar system with 4 GHz bandwidth?


Summarizing sporting events using twitter. The status updates posted to social networks, such as Twitter and Facebook, contain a myriad of information about what people are doing and watching. During events, such as sports games, many updates are sent describing and expressing opinions about the event. In this paper, we describe an algorithm that generates a journalistic summary of an event using only status updates from Twitter as a source. Temporal cues, such as spikes in the volume of status updates, are used to identify the important moments within an event, and a sentence ranking method is used to extract relevant sentences from the corpus of status updates describing each important moment within an event. We evaluate our algorithm compared to human-generated summaries and the previous best summarization algorithm, and find that the results of our method are superior to the previous algorithm and approach the readability and grammaticality of the human-generated summaries.

Question: How to summarize a sporting event using twitter?


Biomimetic walking robot SCORPION: Control and modeling. We present the biomimetic control scheme for the walking robot SCORPION. We used a concept of Basic Motion Patterns, which can be combined in a very flexible manner. In addition our modeling and simulation approach is described, which has been done based on the ADAMS(TM) simulator. Especially the motion patterns of real scorpions were analyzed and used for walking patterns and acceleration of the robot.

Question: How to control a robot?


A multidisciplinary approach towards computational thinking for science majors. This paper describes the development and initial evaluation of a new course ``Introduction to Computational Thinking'' taken by science majors to fulfill a college computing requirement. The course was developed by computer science faculty in collaboration with science faculty and it focuses on the role of computing and computational principles in scientific inquiry. It uses Python and Python libraries to teach computational thinking via basic programming concepts, data management concepts, simulation, and visualization. Problems with a computational aspect are drawn from different scientific disciplines and are complemented with lectures from faculty in those areas. Our initial evaluation indicates that the problem-driven approach focused on scientific discovery and computational principles increases the student's interest in computing.

Question: What is a multidisciplinary approach?


Thermal management and cooling of windings in electrical machines for electric vehicle and traction application. Conventional electrical machine cooling includes housing fins, shaft-mounted fan, and water jacket. In these cases, heat from the copper loss of windings needs to pass through either the stator core or the air between windings and the housing. Because of the large thermal resistance in the path, these methods are sometimes not efficient enough for high torque density machines. Overheat in windings causes failure in the insulation and damages the machine. Many technologies that facilitate winding cooling have been investigated in the literature, such as winding topologies with more efficient heat dissipation capability, impregnation material with high thermal conductivity, and advanced direct winding. This paper reviews and classifies thermal management and cooling methods to provide a guideline for high torque density electrical machine design for a better winding thermal management.

Question: What is the thermal management and cooling of windings in electrical machines for electric vehicle and traction application?


Atanassov's Intuitionistic Fuzzy Programming Method for Heterogeneous Multiattribute Group Decision Making With Atanassov's Intuitionistic Fuzzy Truth Degrees. The aim of this paper is to develop a new Atanassov's intuitionistic fuzzy (A-IF) programming method to solve heterogeneous multiattribute group decision-making problems with A-IF truth degrees in which there are several types of attribute values such as A-IF sets (A-IFSs), trapezoidal fuzzy numbers, intervals, and real numbers. In this method, preference relations in comparisons of alternatives with hesitancy degrees are expressed by A-IFSs. Hereby, A-IF group consistency and inconsistency indices are defined on the basis of preference relations between alternatives. To estimate the fuzzy ideal solution (IS) and weights, a new A-IF programming model is constructed on the concept that the A-IF group inconsistency index should be minimized and must be not larger than the A-IF group consistency index by some fixed A-IFS. An effective method is developed to solve the new derived model. The distances of the alternatives to the fuzzy IS are calculated to determine their ranking order. Moreover, some generalizations or specializations of the derived model are discussed. Applicability of the proposed methodology is illustrated with a real supplier selection example.

Question: What is the difference between intuitionistic fuzzy sets and fuzzy sets?


13C-NMR-Based Metabolomic Profiling of Typical Asian Soy Sauces. It has been a strong consumer interest to choose high quality food products with clear information about their origin and composition. In the present study, a total of 22 Asian soy sauce samples have been analyzed in terms of (13)C-NMR spectroscopy. Spectral data were analyzed by multivariate statistical methods in order to find out the important metabolites causing the discrimination among typical soy sauces from different Asian regions. It was found that significantly higher concentrations of glutamate in Chinese red cooking (CR) soy sauce may be the result of the manual addition of monosodium glutamate (MSG) in the final soy sauce product. Whereas lower concentrations of amino acids, like leucine, isoleucine and valine, observed in CR indicate the different fermentation period used in production of CR soy sauce, on the other hand, the concentration of some fermentation cycle metabolites, such as acetate and sucrose, can be divided into two groups. The concentrations of these fermentation cycle metabolites were lower in CR and Singapore Kikkoman (SK), whereas much higher in Japanese shoyu (JS) and Taiwan (China) light (TL), which depict the influence of climatic conditions. Therefore, the results of our study directly indicate the influences of traditional ways of fermentation, climatic conditions and the selection of raw materials and can be helpful for consumers to choose their desired soy sauce products, as well as for researchers in further authentication studies about soy sauce.

Question: What is the difference between the typical Asian soy sauces?


A High Gain Input-Parallel Output-Series DC/DC Converter With Dual Coupled Inductors. High voltage gain dc-dc converters are required in many industrial applications such as photovoltaic and fuel cell energy systems, high-intensity discharge lamp (HID), dc back-up energy systems, and electric vehicles. This paper presents a novel input-parallel output-series boost converter with dual coupled inductors and a voltage multiplier module. On the one hand, the primary windings of two coupled inductors are connected in parallel to share the input current and reduce the current ripple at the input. On the other hand, the proposed converter inherits the merits of interleaved series-connected output capacitors for high voltage gain, low output voltage ripple, and low switch voltage stress. Moreover, the secondary sides of two coupled inductors are connected in series to a regenerative capacitor by a diode for extending the voltage gain and balancing the primary-parallel currents. In addition, the active switches are turned on at zero current and the reverse recovery problem of diodes is alleviated by reasonable leakage inductances of the coupled inductors. Besides, the energy of leakage inductances can be recycled. A prototype circuit rated 500-W output power is implemented in the laboratory, and the experimental results shows satisfactory agreement with the theoretical analysis.

Question: What is the purpose of the voltage multiplier module?


A study of smoothing methods for language models applied to information retrieval. Language modeling approaches to information retrieval are attractive and promising because they connect the problem of retrieval with that of language model estimation, which has been studied extensively in other application areas such as speech recognition. The basic idea of these approaches is to estimate a language model for each document, and to then rank documents by the likelihood of the query according to the estimated language model. A central issue in language model estimation is smoothing, the problem of adjusting the maximum likelihood estimator to compensate for data sparseness. In this article, we study the problem of language model smoothing and its influence on retrieval performance. We examine the sensitivity of retrieval performance to the smoothing parameters and compare several popular smoothing methods on different test collections. Experimental results show that not only is the retrieval performance generally sensitive to the smoothing parameters, but also the sensitivity pattern is affected by the query type, with performance being more sensitive to smoothing for verbose queries than for keyword queries. Verbose queries also generally require more aggressive smoothing to achieve optimal performance. This suggests that smoothing plays two different role---to make the estimated document language model more accurate and to "explain" the noninformative words in the query. In order to decouple these two distinct roles of smoothing, we propose a two-stage smoothing strategy, which yields better sensitivity patterns and facilitates the setting of smoothing parameters automatically. We further propose methods for estimating the smoothing parameters automatically. Evaluation on five different databases and four types of queries indicates that the two-stage smoothing method with the proposed parameter estimation methods consistently gives retrieval performance that is clos

Question: What is the difference between a language model and a language model?


A 1-V, 16.9 ppm/$^{\circ}$C, 250 nA Switched-Capacitor CMOS Voltage Reference. An ultra low-power, precise voltage reference using a switched-capacitor technique in 0.35-μm CMOS is presented in this paper. The temperature dependence of the carrier mobility and channel length modulation effect can be effectively minimized by using 3.3 and 5 V N-type transistors to operate in the saturation and subthreshold regions, respectively. In place of resistors, a precise reference voltage with flexible trimming capability is achieved by using capacitors. When the supply voltage is 1 V and the temperature is 80°C, the supply current is 250 nA. The line sensitivity is 0.76%/V; the PSRR is -41 dB at 100 Hz and -17 dB at 10 MHz. Moreover, the occupied die area is 0.049 mm2.

Question: What is the temperature dependence of the carrier mobility and channel length modulation effect?


Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model. Urban land use information plays an essential role in a wide variety of urban planning and environmental monitoring processes. During the past few decades, with the rapid technological development of remote sensing (RS), geographic information systems (GIS) and geospatial big data, numerous methods have been developed to identify urban land use at a fine scale. Points-of-interest (POIs) have been widely used to extract information pertaining to urban land use types and functional zones. However, it is difficult to quantify the relationship between spatial distributions of POIs and regional land use types due to a lack of reliable models. Previous methods may ignore abundant spatial features that can be extracted from POIs. In this study, we establish an innovative framework that detects urban land use distributions at the scale of traffic analysis zones (TAZs) by integrating Baidu POIs and a Word2Vec model. This framework was implemented using a Google open-source model of a deep-learning language in 2013. First, data for the Pearl River Delta (PRD) are transformed into a TAZ-POI corpus using a greedy algorithmby considering the spatial distributions of TAZs and inner POIs. Then, high-dimensional characteristic vectors of POIs and TAZs are extracted using the Word2Vec model. Finally, to validate the reliability of the POI/TAZ vectors, we implement a K-Means-based clustering model to analyze correlations between the POI/TAZ vectors and deploy TAZ vectors to identify urban land use types using a random forest algorithm (RFA) model. Compared with some state-of-the-art probabilistic topic models (PTMs), the proposed method can efficiently obtain the highest accuracy (OA = 0.8728, kappa = 0.8399). Moreover, the results can be used to help urban planners to monitor dynamic urban land use and evaluate the impact of urban planning schemes. ARTICLE HISTORY Received 21

Question: How to detect urban land use types using a Word2Vec model?


A biomimetic soft fingertip applicable to haptic feedback systems for texture identification. Humans recognize textures using the tactile data obtained from the human somatosensory system. Recognition of textures allows humans discriminate objects and materials. Moreover, by understanding the object's or material's texture, the human intuitively estimates roughness and the friction properties of the object or the material. This ability is necessary for object manipulative tasks. Likewise artificial haptic systems too, should have the ability to encode textures and feedback those data to haptic applications such as haptic displays. In this paper a biomimetic soft fingertip sensor that can be used in above haptic systems is introduced. The fingertip has the ability to detect force and vibration modalities. We propose three features calculated from the covariance signal of two adjacent accelerometers in the fingertip to use in texture identification. The covariance signal is transformed using Discrete Wavelet Transform (DWT) and the three features mentioned below are calculated. The mean and variance of the approximate signal, and the energies of the detailed signal are chosen as features. Then, the proposed features were validate by using those in an Artificial Neural Network (ANN) to classify seven wood samples. The results showed a 65% success rate in classifying wood samples and that the proposed features are acceptable to encode textures.

Question: What is a biomimetic soft fingertip?


Building Natural Language Interfaces to Web APIs. As the Web evolves towards a service-oriented architecture, application program interfaces (APIs) are becoming an increasingly important way to provide access to data, services, and devices. We study the problem of natural language interface to APIs (NL2APIs), with a focus on web APIs for web services. Such NL2APIs have many potential benefits, for example, facilitating the integration of web services into virtual assistants.  We propose the first end-to-end framework to build an NL2API for a given web API. A key challenge is to collect training data, i.e., NL command-API call pairs, from which an NL2API can learn the semantic mapping from ambiguous, informal NL commands to formal API calls. We propose a novel approach to collect training data for NL2API via crowdsourcing, where crowd workers are employed to generate diversified NL commands. We optimize the crowdsourcing process to further reduce the cost. More specifically, we propose a novel hierarchical probabilistic model for the crowdsourcing process, which guides us to allocate budget to those API calls that have a high value for training NL2APIs. We apply our framework to real-world APIs, and show that it can collect high-quality training data at a low cost, and build NL2APIs with good performance from scratch. We also show that our modeling of the crowdsourcing process can improve its effectiveness, such that the training data collected via our approach leads to better performance of NL2APIs than a strong baseline.

Question: How to build a natural language interface to a web api?


From Manual to Semi-Automatic Semantic Annotation: About Ontology-Based Text Annotation Tools. Semantic Annotation is a basic technology for intelligent content and is bene cial in a wide range of content-oriented intelligent applications, esp. in the area of the Semantic Web. In this paper we present our work in ontology-based semantic annotation, which is embedded in a scenario of a knowledge portal application. Starting with seemingly good and bad manual semantic annotation, we describe our experiences made within the KAinitiative. The experiences gave us the starting point for developing an ergonomic and knowledge base-supported annotation tool. Furthermore, the annotation tool described are currently extended with mechanisms for semi-automatic information-extraction based annotation. Supporting the evolving nature of semantic content we additionally describe our idea of evolving ontologies supporting semantic annotation. This paper has been presented at the COLING-2000 Workshop on Semantic Annotation and Intelligent Content, Centre Universitaire, Luxembourg, 5.-6. August, 2000.

Question: What is the ontology-based semantic annotation?


Novel paradigms for advanced distribution grid energy management. The electricity distribution grid was not designed to cope with load dynamics imposed by high penetration of electric vehicles, neither to deal with the increasing deployment of distributed Renewable Energy Sources. Distribution System Operators (DSO) will increasingly rely on flexible Distributed Energy Resources (flexible loads, controllable generation and storage) to keep the grid stable and to ensure quality of supply. In order to properly integrate demand-side flexibility, DSOs need new energy management architectures, capable of fostering collaboration with wholesale market actors and prosumers. We propose the creation of Virtual Distribution Grids (VDG) over a common physical infrastructure, to cope with heterogeneity of resources and actors, and with the increasing complexity of distribution grid management and related resources allocation problems. Focusing on residential VDG, we propose an agent-based hierarchical architecture for providing Demand-Side Management services through a market-based approach, where households transact their surplus/lack of energy and their flexibility with neighbours, aggregators, utilities and DSOs. For implementing the overall solution, we consider fine-grained control of smart homes based on Internet of Things technology. Homes seamlessly transact self-enforcing smart contracts over a blockchainbased generic platform. Finally, we extend the architecture to solve existing problems on smart home control, beyond energy management.

Question: How to implement a virtual distribution grid?


How does EMDR work ?. Eye movement desensitisation and reprocessing (EMDR) is an effective treatment for alleviating trauma symptoms, and the positive effects of this treatment have been scientifically confirmed under wellcontrolled conditions. This has provided an opportunity to explore how EMDR works. The present paper reports on the findings of a long series of experiments that disproved the hypothesis that eye movements or other 'dual tasks' are unnecessary. These experiments also disproved the idea that 'bilateral stimulation' is needed; moving the eyes up and down produces the same effect as horizontal eye movement, and so do tasks that require no eye movement at all. However, it is important that the dual task taxes working memory. Several predictions can be derived from the working memory explanation for eye movements in EMDR. These seem to hold up extremely well in critical experimental tests, and create a solid explanation on how eye movements work. This paper discusses the implications that this theory and the empirical findings may have for the EMDR technique. © Copyright 2012 Textrum Ltd. All rights reserved.

Question: How does EMDR work?


Mining and analyzing the enterprise knowledge graph. Today's enterprises hold ever-growing amounts of public data, stemming from different organizational systems, such as development environments, CRM systems, business intelligence systems, and enterprise social media. This data unlocks rich and diverse information about entities, people, terms, and the relationships among them. A lot of insight can be gained through analyzing this knowledge graph, both by individual employees and by the organization as a whole. In this talk, I will review recent work done by the Social Technologies & Analytics group at IBM Research-Haifa to mine these relationships, represent them in a generalized model, and use the model for different aims within the enterprise, including social search [5], expertise location [1], social recommendation [2, 3], and network analysis [4].

Question: What is the enterprise knowledge graph?


Handcrafted features with convolutional neural networks for detection of tumor cells in histology images. Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional neural networks (CNNs) to detect cells in H&E stained images. However, all such methods use some form of raw pixel intensities as input and rely on the CNN to learn the deep features. In this work, we extend a recently proposed spatially constrained CNN (SC-CNN) by proposing features that capture texture characteristics and show that although CNN produces good results on automatically learned features, it can perform better if the input consists of a combination of handcrafted features and the raw data. The handcrafted features are computed through the scattering transform which gives non-linear invariant texture features. The combination of handcrafted features with raw data produces sharp proximity maps and better detection results than the results of raw intensities with a similar kind of CNN architecture.

Question: How to detect tumor nuclei in cancer histology images?


Dioxin characterisation , formation and minimisation during municipal solid waste ( MSW ) incineration : review. The present review discusses the current views on methods to minimise dioxins, namely polychlorinated dibenzodioxins (PCDDs) and dibenzofurans (PCDFs), formation in MSW incineration systems. The structure of this group of compounds is discussed initially and then the toxic equivalence scale is presented for the most common isomers and congeners in the dioxin family. The current status on dioxin limits imposed in various countries and by various organisations is presented. A detailed analysis of the theories leading to dioxin formation in MSW incineration is given, since, this has been one of the most controversial areas of dioxin chemistry for the past 20 years. Three dioxin formation theories were considered possible for a long time; (i) from PCDD/PCDFs originally present in the furnace feedstock; (ii) from precursor compounds (foundation formatting molecules which could react rapidly with other groups in the system to form dioxins) in the MSW feed; (iii) from de novo synthesis of smaller, relatively innocuous chemical molecules combining together to form the dioxins. Methods (ii) and (iii) are based on heterogeneously catalysed reactions. Some researchers are considering possible homogeneous thermal reaction formation of dioxin. This review demonstrates that with the advanced modern MSW combustion systems, option (i) is a most unlikely route and also methods (ii) and (iii) are quite feasible. Based on thermodynamic and kinetic data in the literature, the rate and extent of the formation of dioxins and their precursors by certain mechanisms can definitely be contributing to routes (ii) and (iii). Since even the most advanced MSW combustion systems do not produce complete combustion, predominantly because of inadequate feed preparation and turbulence, some de novo synthesis of precursors can also take place. These 'de novo precursors' could be carried thr

Question: What is the dioxin characterisation, formation and minimisation during municipal solid waste ( MSW ) incineration : review?


Choice of intra-articular injection in treatment of knee osteoarthritis: platelet-rich plasma, hyaluronic acid or ozone options. This study was performed to compare the efficacy of treatment in three groups of patients with knee osteoarthritis (OA) given an intra-articular injection of platelet-rich plasma (PRP), hyaluronic acid (HA) or ozone gas. A total of 102 patients with mild–moderate and moderate knee OA who presented at the polyclinic with at least a 1-year history of knee pain and VAS score ≥4 were randomly separated into three groups. Group 1 (PRP group) received intra-articular injection of PRP × 2 doses, Group 2 (HA group) received a single dose of HA, and Group 3 (Ozone group) received ozone × four doses. Weight-bearing anteroposterior–lateral and Merchant's radiographs of both knees were evaluated. WOMAC and VAS scores were applied to all patients on first presentation and at 1, 3, 6 and 12 months. At the end of the 1st month after injection, significant improvements were seen in all groups. In the 3rd month, the improvements in WOMAC and VAS scores were similar in Groups 1 and 2, while those in Group 3 were lower (p < 0.001). At the 6th month, while the clinical efficacies of PRP and HA were similar and continued, the clinical effect of ozone had disappeared (p < 0.001). At the end of the 12th month, PRP was determined to be both statistically and clinically superior to HA (p < 0.001). In the treatment of mild–moderate knee OA, PRP was more successful than HA and ozone injections, as the application alone was sufficient to provide at least 12 months of pain-free daily living activities. Therapeutic study, Level I.

Question: What is the difference between PRP and HA?


Recognition with Local Features: the Kernel Recipe. Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have been established as powerful learning algorithms with good generalization capabilities. In this paper, we combine these two approaches and propose a general kernel method for recognition with local features. We show that the proposed kernel satisfies the Mercer condition and that it is suitable for many established local feature frameworks. Large-scale recognition results are presented on three different databases, which demonstrate that SVMs with the proposed kernel perform better than standard matching techniques on local features. In addition, experiments on noisy and occluded images show that local feature representations significantly outperform global approaches.

Question: What is the kernel method for recognition with local features?


Penile septoplasty for congenital ventral penile curvature: results in 51 patients.. PURPOSE The technique most widely used to correct congenital ventral penile curvature is still corporoplasty as originally described by Nesbit. We present results in patients treated with a variation of Nesbit corporoplasty used specifically for congenital ventral penile curvature.   MATERIALS AND METHODS From June 2000 to June 2007 we treated 51 patients with congenital ventral penile curvature using modified corporoplasty (septoplasty), consisting of accessing the bed of the penile dorsal vein and excising 1 or more diamonds of tunica albuginea from it, extending in wedge-like formation 4 to 5 mm deep into the septum, until the penis is completely straightened. Patient history, clinical findings, self-photography results and the International Index of Erectile Function score were assessed. Curvature grade is expressed using the equation, 180 degrees - X, where X represents the deviation in degrees from the penis axis. Mean preoperative ventral curvature was 131.4 degrees (median 135, range 145 to 110). Of the patients 13 also had erectile dysfunction.   RESULTS At followup postoperative mean ventral curvature was 178.3 degrees (median 179.1, range 180 to 175). A total of 49 stated that they were completely satisfied. Penile shortening was 5 to 15 mm. Compared to preoperative values there were marked improvements in the International Index of Erectile Function score in the various groups. No major postoperative complications developed. In 4 patients wound healing occurred by secondary intent.   CONCLUSIONS This technique provides excellent straightening of the curved penis. By avoiding isolation of the whole dorsal neurovascular bundle there is no risk of neurovascular lesions. Suture perception is minimized.

Question: What is the purpose of the penile septoplasty?


Empathy circuits. The social neuroscientific investigation of empathy has revealed that the same neural networks engaged during first-hand experience of affect subserve empathic responses. Recent meta-analyses focusing on empathy for pain for example reliably identified a network comprising anterior insula and anterior midcingulate cortex. Moreover, recent studies suggest that the generation of empathy is flexibly supported by networks involved in action simulation and mentalizing depending on the information available in the environment. Further, empathic responses are modulated by many factors including the context they occur in. Recent work shows how this modulation can be afforded by the engagement of antagonistic motivational systems or by cognitive control circuits, and these modulatory systems can also be employed in efforts to regulate one's empathic responses.

Question: What is the social neuroscientific investigation of empathy?


Dynamic Adaptive Streaming over HTTP/2.0. MPEG Dynamic Adaptive Streaming over HTTP (DASH) is a new streaming standard that has been recently ratified as an international standard (IS). In comparison to other streaming systems, e.g., HTTP progressive download, DASH is able to handle varying bandwidth conditions providing smooth streaming. Furthermore, it enables NAT and Firewall traversal, flexible and scalable deployment as well as reduced infrastructure costs due to the reuse of existing Internet infrastructure components, e.g., proxies, caches, and Content Distribution Networks (CDN). Recently, the Hypertext Transfer Protocol Bis (httpbis) working group of the IETF has officially started the development of HTTP 2.0. Initially three major proposals have been submitted to the IETF i.e., Googles' SPDY, Microsofts' HTTP Speed+Mobility and Network-Friendly HTTP Upgrade, but SPDY has been chosen as working draft for HTTP 2.0. In this paper we implemented MPEG-DASH over HTTP 2.0 (i.e., SPDY), demonstrating its potential benefits and drawbacks. Moreover, several experimental evaluations have been performed that compare HTTP 2.0 with HTTP 1.1 and HTTP 1.0 in the context of DASH. In particular, the protocol overhead, the performance for different round trip times, and DASH with HTTP 2.0 in a lab test scenario has been evaluated in detail.

Question: What is the difference between HTTP 1.0 and HTTP 2.0?


PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.. The newly inaugurated Research Resource for Complex Physiologic Signals, which was created under the auspices of the National Center for Research Resources of the National Institutes of Health, is intended to stimulate current research and new investigations in the study of cardiovascular and other complex biomedical signals. The resource has 3 interdependent components. PhysioBank is a large and growing archive of well-characterized digital recordings of physiological signals and related data for use by the biomedical research community. It currently includes databases of multiparameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and from patients with a variety of conditions with major public health implications, including life-threatening arrhythmias, congestive heart failure, sleep apnea, neurological disorders, and aging. PhysioToolkit is a library of open-source software for physiological signal processing and analysis, the detection of physiologically significant events using both classic techniques and novel methods based on statistical physics and nonlinear dynamics, the interactive display and characterization of signals, the creation of new databases, the simulation of physiological and other signals, the quantitative evaluation and comparison of analysis methods, and the analysis of nonstationary processes. PhysioNet is an on-line forum for the dissemination and exchange of recorded biomedical signals and open-source software for analyzing them. It provides facilities for the cooperative analysis of data and the evaluation of proposed new algorithms. In addition to providing free electronic access to PhysioBank data and PhysioToolkit software via the World Wide Web (http://www.physionet. org), PhysioNet offers services and training via on-line tutorials to assist users with varying levels of expertise.

Question: What is the difference between the Canadian Armed Forces and the Canadian Army?


Real-time super-resolution Sound Source Localization for robots. Sound Source Localization (SSL) is an essential function for robot audition and yields the location and number of sound sources, which are utilized for post-processes such as sound source separation. SSL for a robot in a real environment mainly requires noise-robustness, high resolution and real-time processing. A technique using microphone array processing, that is, Multiple Signal Classification based on Standard EigenValue Decomposition (SEVD-MUSIC) is commonly used for localization. We improved its robustness against noise with high power by incorporating Generalized EigenValue Decomposition (GEVD). However, GEVD-based MUSIC (GEVD-MUSIC) has mainly two issues: 1) the resolution of pre-measured Transfer Functions (TFs) determines the resolution of SSL, 2) its computational cost is expensive for real-time processing. For the first issue, we propose a TF interpolation method integrating time-domain-based and frequency-domain-based interpolation. The interpolation achieves super-resolution SSL, whose resolution is higher than that of the pre-measured TFs. For the second issue, we propose two methods, MUSIC based on Generalized Singular Value Decomposition (GSVD-MUSIC), and Hierarchical SSL (H-SSL). GSVD-MUSIC drastically reduces the computational cost while maintaining noise-robustness in localization. H-SSL also reduces the computational cost by introducing a hierarchical search algorithm instead of using greedy search in localization. These techniques are integrated into an SSL system using a robot embedded microphone array. The experimental result showed: the proposed interpolation achieved approximately 1 degree resolution although we have only TFs at 30 degree intervals, GSVD-MUSIC attained 46.4% and 40.6% of the computational cost compared to SEVD-MUSIC and GEVD-MUSIC, respectively, H-SSL reduces 59.2% computational cost in localization of a single sound source.

Question: How to improve the resolution of SSL?


Towards the Next Generation of Tabletop Gaming Experiences. In this paper we present a novel hardware and software platform (STARS) to realize computer augmented tabletop games that unify the strengths of traditional board games and computer games. STARS game applications preserve the social situation of traditional board games and provide a tangible interface with physical playing pieces to facilitate natural interaction. The virtual game components offer exciting new opportunities for game design and provide richer gaming experiences impossible to realize with traditional media. This paper describes STARS in terms of the hardware setup and the software platform used to develop and play STARS games. The interaction design within STARS is discussed and sample games are presented with regard to their contributions to enhancing user experience. Finally, realworld experiences with the platform are reported.

Question: What is the next generation of tabletop gaming experiences?


Final Project : Entangled Photons and Quantum Teleportation. This paper contains an overview of the concept of photon entanglement and discusses generating EPR photon pairs and performing Bell state measurements on them. The procedure of quantum teleportation, or transferring the quantum state of a particle onto another particle, is described in detail. The experimental progress in performing such operations is reviewed in relationship to the developing field of quantum communication.

Question: What is the difference between a photon and a photon?


Efficient Genome-Wide, Privacy-Preserving Similar Patient Query based on Private Edit Distance. Edit distance has been proven to be an important and frequently-used metric in many human genomic research, with Similar Patient Query (SPQ) being a particularly promising and attractive example. However, due to the widespread privacy concerns on revealing personal genomic data, the scope and scale of many novel use of genome edit distance are substantially limited. While the problem of private genomic edit distance has been studied by the research community for over a decade [6], the state-of-the-art solution [31] is far from even close to be applicable to real genome sequences. In this paper, we propose several private edit distance protocols that feature unprecedentedly high efficiency and precision. Our construction is a combination of a novel genomic edit distance ap- proximation algorithm and new construction of private set difference size protocols. With the private edit distance based secure SPQ primitive, we propose GENSETS, a genome-wide, privacy- preserving similar patient query system. It is able to support search- ing large-scale, distributed genome databases across the nation. We have implemented a prototype of GENSETS. The experimental results show that, with 100 Mbps network connection, it would take GENSETS less than 200 minutes to search through 1 million breast cancer patients (distributed nation-wide in 250 hospitals, each having 4000 patients), based on edit distances between their genomes of lengths about 75 million nucleotides each.

Question: What is the largest genome database?