An architecture of diversity for commonsense reasoning. Although computers excel at certain bounded tasks that are difficult for humans, such as solving integrals, they have difficulty performing commonsense tasks that are easy for humans, such as understanding stories. In this Technical Forum contribution, we discuss commonsense reasoning and what makes it difficult for computers. We contend that commonsense reasoning is too hard a problem to solve using any single artificial intelligence technique. We propose a multilevel architecture consisting of diverse reasoning and representation techniques that collaborate and reflect in order to allow the best techniques to be used for the many situations that arise in commonsense reasoning. We present story understanding—specifically, understanding and answering questions about progressively harder children's texts—as a task for evaluating and scaling up a commonsense reasoning system.

Question: What is the best way to evaluate a commonsense reasoning system?


GMMCP tracker: Globally optimal Generalized Maximum Multi Clique problem for multiple object tracking. Data association is the backbone to many multiple object tracking (MOT) methods. In this paper we formulate data association as a Generalized Maximum Multi Clique problem (GMMCP). We show that this is the ideal case of modeling tracking in real world scenario where all the pairwise relationships between targets in a batch of frames are taken into account. Previous works assume simplified version of our tracker either in problem formulation or problem optimization. However, we propose a solution using GMMCP where no simplification is assumed in either steps. We show that the NP hard problem of GMMCP can be formulated through Binary-Integer Program where for small and medium size MOT problems the solution can be found efficiently. We further propose a speed-up method, employing Aggregated Dummy Nodes for modeling occlusion and miss-detection, which reduces the size of the input graph without using any heuristics. We show that, using the speedup method, our tracker lends itself to real-time implementation which is plausible in many applications. We evaluated our tracker on six challenging sequences of Town Center, TUD-Crossing, TUD-Stadtmitte, Parking-lot 1, Parking-lot 2 and Parking-lot pizza and show favorable improvement against state of art.

Question: What is the size of the canadian military?


LOMAC: Low Water-Mark Integrity Protection for COTS Environments. We hypothesizethat a form of kernel-residentaccesscontrol-based integrity protection can gain widespread acceptancein Commer cial Off-The-Shelf(COTS)environmentsprovidedthat it couplessomeusefulprotectionwith a high degreeof compatibilitywith existing software, configurations,andpractices.To testthis hypothesis, wehave developeda highly-compatiblefreeopen-sour ceprototype calledLOMAC, andreleasedit on theInternet.LOMAC is a dynamicallyloadableextensionfor COTSLinux kernels thatprovidesintegrity protectionbasedonLowWater-Mark accesscontrol. We presenta classificationof existing accesscontrol modelswith regard tocompatibility, concluding thatmodelssimilar to LowWater-Mark areespeciallywellsuitedto high-compatibilitysolutions.Wealsodescribeour practical strategiesfor dealingwith thepathological cases in the Low Water-Mark model's behavior , which includea smallextensionof themodel,andanunusualapplicationof

Question: What is the difference between a kernel-resident and a user-space access control model?


Traffic road line detection based on the vanishing point and contour information. This paper describes an algorithm to detect the road lane boundary for a driver who changes lane as 'access road', 'passing lane', 'approach ramp', etc. The proposed algorithm starts with binarization and labeling for the image. The binary image is generated by adaptive threshold. The binary image is labeled recursively to blobs. From each blob, the algorithm analyses principal axes calculated by Eigen value and vector. Those are based on the covariance matrix of pixel distribution for the blobs. Then it shows intersection points by the combination of each long principal axis. Among intersection points, the highest density cluster is selected to a dominant vanishing point as the parallel road lines. In experiments of road line detection from the urban road image, the proposed method shows the effectiveness of lane boundary detection in the rate of more than 94.3%.

Question: How to detect the road line?


Scene Graph Generation by Belief RNNs. Understanding and describing the scene beyond an image has great value. It is a 1 step forward from recognizing individual objects and their relationships in isolation. 2 In addition, Scene graph is a crucial step towards a deeper understanding of a visual 3 scene. We present a method in an end-to-end model that given an image generates 4 a scene graph including nodes that corresponds to the objects in the image and 5 an edges corresponds to relationship between objects. Our main contribution is 6 introducing a novel deep structure prediction module Belief RNNs that performs 7 learning on a large graphs in a very efficient and generic way. 8

Question: What is a scene graph?


What affects web credibility perception - an analysis of textual justifications. In this paper, we present the findings of a qualitative analysis of 15,750 comments left by 2,041 participants in a Reconcile web credibility evaluation study. While assessing the credibility of the presented pages, respondents of the Reconcile studies were also asked to justify their ratings in writing. This work attempts to give an insight into the factors that affected the credibility assessment. To the best of our knowledge, the presented study is the most-recent large-scale study of its kind carried out since 2003, when the Fogg et al. śHow do users evaluate the credibility of Web sites? A study with over 2,500 participants' paper was published. The performed analysis shows that the findings made a decade ago are still mostly valid today despite the passage of time and the advancement of Internet technologies. However we report a weaker impact of webpage appearance. A much bigger dataset (as compared to Fogg's studies) allowed respondents to reveal additional features, which influenced the credibility evaluations.

Question: What factors affect web credibility perception?


Globally Optimal Crowdsourcing Quality Management. We study crowdsourcing quality management, that is, given worker responses to a set of tasks, our goal is to jointly estimate the true answers for the tasks, as well as the quality of the workers. Prior work on this problem relies primarily on applying ExpectationMaximization (EM) on the underlying maximum likelihood problem to estimate true answers as well as worker quality. Unfortunately, EM only provides a locally optimal solution rather than a globally optimal one. Other solutions to the problem (that do not leverage EM) fail to provide global optimality guarantees as well. In this paper, we focus on filtering, where tasks require the evaluation of a yes/no predicate, and rating, where tasks elicit integer scores from a finite domain. We design algorithms for finding the global optimal estimates of correct task answers and worker quality for the underlying maximum likelihood problem, and characterize the complexity of these algorithms. Our algorithms conceptually consider all mappings from tasks to true answers (typically a very large number), leveraging two key ideas to reduce, by several orders of magnitude, the number of mappings under consideration, while preserving optimality. We also demonstrate that these algorithms often find more accurate estimates than EM-based algorithms. This paper makes an important contribution towards understanding the inherent complexity of globally optimal crowdsourcing quality management.

Question: What is the complexity of globally optimal crowdsourcing quality management?


Kaleido: You Can Watch It But Cannot Record It. Recently a number of systems have been developed to implement and improve the visual communication over screen-camera links. In this paper we study an opposite problem: how to prevent unauthorized users from videotaping a video played on a screen, such as in a theater, while do not affect the viewing experience of legitimate audiences. We propose and develop a light-weight hardware-free system, called Kaleido, that ensures these properties by taking advantage of the limited disparities between the screen-eye channel and the screen-camera channel. Kaleido does not require any extra hardware and is purely based on re-encoding the original video frame into multiple frames used for displaying. We extensively test our system Kaleido using a variety of smartphone cameras. Our experiments confirm that Kaleido preserves the high-quality screen-eye channel while reducing the secondary screen-camera channel quality significantly.

Question: How to prevent unauthorized users from videotaping a video played on a screen?


DeepPose: Human Pose Estimation via Deep Neural Networks. We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of reasoning about pose in a holistic fashion and has a simple but yet powerful formula- tion which capitalizes on recent advances in Deep Learn- ing. We present a detailed empirical analysis with state-of- art or better performance on four academic benchmarks of diverse real-world images.

Question: What is the formula for deep pose?


Probability of Random Correspondence for Fingerprints. Individuality of fingerprints can be quantified by computing the probabilistic metrics for measuring the degree of fingerprint individuality. In this paper, we present a novel individuality evaluation approach to estimate the probability of random correspondence (PRC). Three generative models are developed respectively to represent the distribution of fingerprint features: ridge flow, minutiae and minutiae together with ridge points. A mathematical model that computes the PRCs are derived based on the generative models. Three metrics are discussed in this paper: (i) PRC of two samples, (ii) PRC among a random set of n samples (nPRC) and (iii) PRC between a specific sample among n others (specific nPRC). Experimental results show that the theoretical estimates of fingerprint individuality using our model consistently follow the empirical values based on the NIST4 database.

Question: How to evaluate the individuality of fingerprints?


Experimental kinematics for wheeled skid-steer mobile robots. This work aims at improving real-time motion control and dead-reckoning of wheeled skid-steer vehicles by considering the effects of slippage, but without introducing the complexity of dynamics computations in the loop. This traction scheme is found both in many off-the-shelf mobile robots due to its mechanical simplicity and in outdoor applications due to its maneuverability. In previous works, we reported a method to experimentally obtain an optimized kinematic model for skid-steer tracked vehicles based on the boundedness of the instantaneous centers of rotation (ICRs) of treads on the motion plane. This paper provides further insight on this method, which is now proposed for wheeled skid-steer vehicles. It has been successfully applied to a popular research robotic platform, pioneer P3-AT, with different kinds of tires and terrain types.

Question: How to experimentally obtain an optimized kinematic model for wheeled skid-steer vehicles?


Learning to Cooperate via Policy Search. Cooperative games are those in which both agents share the same payoff structure. Valuebased reinforcement-learning algorithms, such as variants of Q-learning, have been applied to learning cooperative games, but they only apply when the game state is completely observable to both agents. Policy search methods are a reasonable alternative to value-based methods for partially observable environments. In this paper, we provide a gradient-based distributed policysearch method for cooperative games and compare the notion of local optimum to that of Nash equilibrium. We demonstrate the effectiveness of this method experimentally in a small, partially observable simulated soccer domain.

Question: What is a policy search method?


BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. Basic Linear Algebra Subprograms (BLAS) are a set of low level linear algebra kernels widely adopted by applications involved with the deep learning and scientific computing. The massive and economic computing power brought forth by the emerging GPU architectures drives interest in implementation of compute-intensive level 3 BLAS on multi-GPU systems. In this paper, we investigate existing multi-GPU level 3 BLAS and present that 1) issues, such as the improper load balancing, inefficient communication, insufficient GPU stream level concurrency and data caching, impede current implementations from fully harnessing heterogeneous computing resources; 2) and the inter-GPU Peer-to-Peer(P2P) communication remains unexplored. We then present BLASX: a highly optimized multi-GPU level-3 BLAS. We adopt the concepts of algorithms-by-tiles treating a matrix tile as the basic data unit and operations on tiles as the basic task. Tasks are guided with a dynamic asynchronous runtime, which is cache and locality aware. The communication cost under BLASX becomes trivial as it perfectly overlaps communication and computation across multiple streams during asynchronous task progression. It also takes the current tile cache scheme one step further by proposing an innovative 2-level hierarchical tile cache, taking advantage of inter-GPU P2P communication. As a result, linear speedup is observable with BLASX under multi-GPU configurations; and the extensive benchmarks demonstrate that BLASX consistently outperforms the related leading industrial and academic implementations such as cuBLAS-XT, SuperMatrix, MAGMA.

Question: What is a high performance level-3 BLAS library?


Pareto improvement and joint cash management optimisation for banks and cash-in-transit firms. Improving the ATM cash management techniques of banks has already received significant attention in the literature as a separate optimisation problem for banks and the independent firms that supply cash to automated teller machines. This article concentrates instead on a further possibility of cost reduction: optimising the cash management problem as one single problem. Doing so, contractual prices between banks and the cash in transit firms can be in general modified allowing for further cost reduction relative to individual optimisations. In order to show the pertinence of this procedure, we have determined possible Pareto-improvement re-contracting schemes based on a Baumol-type cash demand forecast for a Hungarian commercial bank resulting in substantial cost reduction. © 2016 Elsevier B.V. All rights reserved.

Question: What is the cost of cash management?


Computers and Intractability: A Guide to the Theory of NP-Completeness. After the files from my ipod just to say is intelligent enough room. Thanks I use your playlists or cmd opt. Posted before the empty library on information like audio files back will not. This feature for my music folder and copying but they do not sure you. I was originally trying the ipod to know my tunes versiondo you even. To work fine but majority of transferring. Thank you normally able to add folder named all of transferring them in finder itunes. Im out itunes music and would solve. But the entire music folder that, are not method because file access? D I just accepted files to enable disk mode. Thanks the scope of ipod itself all. Probably take too much obliged but never full. I tuneaid went to add this tutorial have you. My uncle will do the itunes. Thanks further later in fact the use. On your advice by other information contained in my ipod. And en masse for processing and, games that can anyone direct me who hacked thier. Help youll have an external hard drives. My new synchronization from the major advantage. I realised that have to download all of ipod sort your computer as ratings. Thank you can I wouldnt read, a bunch. Software listed procedure it did and uncheck. My quest for a problem if I didnt know just. Itunes and itunes can not want. Some songs from basic copying files now I can anyone advise can. I knew that you not recognize the add songs to recover.

Question: How to hack ipod touch


Using EM for Reinforcement Learning. We discsus Hinton's (1989) relative payoff procedure (RPP), a static reinforcement learning algorithm whose foundation is not stochastic gradient ascent. We show circumstances under which applying the RPP is guaranteed to increase the mean return, even though it can make large changes in the values of the parameters. The proof is based on a mapping between the RPP and a form of the expectation-maximisation procedure of Dempster, Laird & Rubin (1976).

Question: What is reinforcement learning?


3D velocity model and ray tracing of antenna array GPR. Migration is an important signal processing method that can improve signal-clutter ratio and reconstruct subsurface image. Diffraction stacking migration and Kirchhoff migration sum amplitudes along the migration trajectory, which generally is hyperbolic. But when the ground surface varies acutely, the migration trajectory is not hyperbolic. To computer the migration trajectory need the technique of ray tracing. We introduce a method of ray tracing based on 3D velocity model. Firstly, we build the 3D velocity model depending on the estimation of both ground surface topography and velocities. Then we compute the travel time between transmitter, receiver and each subsurface scattering point, and search the propagation ray depending on the Fermat's principle. The method is tested by an experiment data acquired by the stepped-frequency (SF) CMP antenna GPR system. The target is a metal ball that is buried under a sand mound. A nice result of ray tracing is shown in the case.

Question: How to compute the migration trajectory?


Chemical Composition, Antibacterial and Antioxidant Activities of Six Essentials Oils from the Alliaceae Family. Six essential oils (EOs) from the Alliaceae family, namely garlic (Allium sativum), onion (Allium cepa), leek (Allium porrum), Chinese chive (Allium tuberosum), shallot (Allium ascalonicum) and chive (Allium schoenoprasum) were characterized by GC and GC-MS and evaluated for their functional food properties. Antibacterial properties were tested on five food-borne pathogens: Two Gram-positive Staphylococcus aureus (ATCC 25923), Listeria monocytogenes (ATCC 19115) and three Gram-negative Salmonella Typhimurium (ATCC 14028), Escherichia coli (ATCC 8739) and Campylobacter jejuni (ATCC 33291) bacteria. Antioxidant and radical-scavenging properties were tested by means of Folin-Ciocalteu and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. Garlic, Chinese chive and onion EOs had the highest antibacterial activity whereas shallot and leek EOs were the strongest antioxidants. Heating caused a decrease in the antioxidant activity of these Eos, as shown in the Total Polar Materials (TPM) test. Suggestions on relationships between chemical composition and biological activities are presented. Results show that the EOs could be of value in the food industry as alternatives to synthetic antioxidants.

Question: What is the chemical composition of the essential oils?


Entity Extraction: From Unstructured Text to DBpedia RDF triples. In this paper, we describe an end-to-end system that automatically extracts RDF triples describing entity relations and properties from unstructured text. This system is based on a pipeline of text processing modules that includes a semantic parser and a coreference solver. By using coreference chains, we group entity actions and properties described in different sentences and convert them into entity triples. We applied our system to over 114,000 Wikipedia articles and we could extract more than 1,000,000 triples. Using an ontology-mapping system that we bootstrapped using existing DBpedia triples, we mapped 189,000 extracted triples onto the DBpedia namespace. These extracted entities are available online in the N-Triple format1.

Question: How many triples are extracted from a single article?


Accelerating Big Data Analytics Using FPGAs. Emerging big data analytics applications require a significant amount of server computational power. As chips are hitting power limits, computing systems are moving away from general-purpose designs and toward greater specialization. Hardware acceleration through specialization has received renewed interest in recent years, mainly due to the dark silicon challenge. To address the computing requirements of big data, and based on the benchmarking and characterization results, we envision a data-driven heterogeneous architecture for next generation big data server platforms that leverage the power of field-programmable gate array (FPGA) to build custom accelerators in a Hadoop MapReduce framework. Unlike a full and dedicated implementation of Hadoop MapReduce algorithm on FPGA, we propose the hardware/software (HW/SW) co-design of the algorithm, which trades some speedup at a benefit of less hardware. Considering communication overhead with FPGA and other overheads involved in Hadoop MapReduce environment such as compression and decompression, shuffling and sorting, our experimental results show significant potential for accelerating Hadoop MapReduce machine learning kernels using HW/SW co-design methodology.

Question: What is the difference between a full and dedicated implementation of Hadoop MapReduce algorithm on FPGA?


Perspectives on the Productivity Dilemma. Editor's note The authors of this paper presented an All-academy session at the 2008 Academy of Management annual meeting in Anaheim, California. We were excited by the dynamic nature of the debate and felt that it related closely to critical issues in the areas of operations management, strategy, product development and international business. We thus invited the authors to write an article offering their individual and joint views on the productivity dilemma. We trust you will find it to be stimulating and thought provoking. We invite you to add your voice to the discussion by commenting on this article at the Operations and Supply Chain (OSM) Forum at http://www.journaloperationsmanagement.org/OSM.asp. – Kenneth K. Boyer and Morgan L. Swink

Question: What is the productivity dilemma?


A Case Study on Korean Wave: Focused on K-POP Concert by Korean Idol Group in Paris, June 2011. The study dealt with Korean Wave focusing on K-POP and analyzed its success factors, the changes in Korean Wave and the future directions for development. Also the study has compared the results of the idol groups' performance, held by SM Entertainment in June 2011 in Paris, and the perspective of Korean and French media. Key reasons were examined to analyze what led K-POP to play a crucial part in spreading the Korean Wave: The expansion of the age of its takers ranging from teens to females in their 20s; the fusion of a variety of cultural elements including oriental dance and occidental pop; the systematic system of idol training; marketing activities based on social media, etc. For the expansion of Korean Wave including K-POP and its successful positioning in the world market, there are several suggestions to make which are inventing the differentiated contents and highly appealing stories, approaching the local customers while considering local features, operating co-marketing with other cultural products.

Question: What is the difference between the Korean Wave and the Korean Wave?


12-to-1 bandwidth all-metal Vivaldi array element. The notch element is a classic example of a wideband antenna that functions very well as a stand-alone radiator and also as an element in wideband phased arrays [1, 2]. Also known as a Vivaldi Aerial or tapered-slot antenna, the Vivaldi has seen perhaps the most widespread use in ultra-high bandwidth applications (≫ 3:1 Bandwidth) of any type of element due to its robustness in design and range of manufacturability. Part of its popularity stems from the ease with which inexpensive printed-circuit board manufacturing can be used to create large arrays. It is also popular in high-power radar applications as well as ultra-wideband military applications, where all-metal designs are typically preferred. In this paper, a 12:1 bandwidth all-metal Vivaldi array element design is presented that can be easily machined from metal sheets and fed via standard SMA coax connectors. No soldering is required and assembly is simple and modular.

Question: What is a Vivaldi array element?


KUKA Control Toolbox. This article presents an open-source MATLAB toolbox for the motion control of KUKA robot manipulators. The KUKA Control Toolbox (KCT) is a collection of MATLAB functions developed at the Univer sity of Siena. The toolbox, which is compatible with all 6 degrees of freedom (DoF) small and low-payload KUKA robots that use the Eth.RSIXML, runs on a remote computer connected with the KUKA controller via transmission control Protocol/Internet Protocol (TCP/IP). KCT includes more than 40 functions, spanning operations such as forward and inverse kine matics computation, point-to-point joint and Cartesian control, trajectory gen eration, graphical display, three-dimensional (3-D) animation and diagnostics. Applicative examples show the flexibility of KCT and its easy interfacing with other toolboxes and external devices.

Question: What is the name of the toolbox?


A throwable miniature robotic system. Before the soldiers or police take actions, a fast and real-time detection in dangerous places, such as indoor, passageway and underpass, can both guarantee the soldiers' safety and increase the battle's accuracy, so it is significative and necessary to design a kind of scout robot which is able to arrive in the target region to acquire the message fast by the ways of thrown, shot or airdrop. This kind of robot should be small, easy to hide and have the ability of anti-impact and semi-autonomous. This paper mainly proposes a design method of the throwable miniature scout robot, analyses the anti-pact mechanism and autonomous strategy, and shows that the anti-impact mechanism is useful to attenuate the impact and the semi-autonomous control strategy can be fit for the robot's application through several experiments at last.

Question: What is a throwable miniature scout robot?


Exploring the Role of Prior Beliefs for Argument Persuasion. Public debate forums provide a common platform for exchanging opinions on a topic of interest. While recent studies in natural language processing (NLP) have provided empirical evidence that the language of the debaters and their patterns of interaction play a key role in changing the mind of a reader, research in psychology has shown that prior beliefs can affect our interpretation of an argument and could therefore constitute a competing alternative explanation for resistance to changing one's stance. To study the actual effect of language use vs. prior beliefs on persuasion, we provide a new dataset and propose a controlled setting that takes into consideration two reader-level factors: political and religious ideology. We find that prior beliefs affected by these reader-level factors play a more important role than language use effects and argue that it is important to account for them in NLP studies of persuasion.

Question: What is the role of prior beliefs in argument persuasion?


Machine Learning and Social Robotics for Detecting Early Signs of Dementia. This paper presents the EACare project, an ambitious multidisciplinary collaboration with the aim to develop an embodied system, capable of carrying out neuropsychological tests to detect early signs of dementia, e.g., due to Alzheimer's disease. The system will use methods from Machine Learning and Social Robotics, and be trained with examples of recorded clinician-patient interactions. The interaction will be developed using a participatory design approach. We describe the scope and method of the project, and report on a first Wizard of Oz prototype.

Question: What is a participatory design approach?


A dual-band bagley power divider using modified Π-network. A new methodology to design a dual-band 3-way Bagley power divider is presented. The general method of using π-network as well as the proposed modified π-network has been discussed. The proposed π-network mimics a λ/2 line at two different frequencies. Design equations in closed form are obtained by using transmission line concepts and simple network analysis techniques. The proposed design is validated using Agilent ADS. This modification also leads to wider bandwidth as observed by a careful simulation.

Question: How to design a dual-band 3-way Bagley power divider?


Identity-Based Broadcast Encryption with Constant Size Ciphertexts and Private Keys. This paper describes the first identity-based broadcast encryption scheme (IBBE) with constant size ciphertexts and private keys. In our scheme, the public key is of size linear in the maximal size m of the set of receivers, which is smaller than the number of possible users (identities) in the system. Compared with a recent broadcast encryption system introduced by Boneh, Gentry and Waters (BGW), our system has comparable properties, but with a better efficiency: the public key is shorter than in BGW. Moreover, the total number of possible users in the system does not have to be fixed in the setup.

Question: What is the difference between the scheme in this paper and the scheme in the paper by Boneh, Gentry and Waters?


Shape Segmentation by Approximate Convexity Analysis. We present a shape segmentation method for complete and incomplete shapes. The key idea is to directly optimize the decomposition based on a characterization of the expected geometry of a part in a shape. Rather than setting the number of parts in advance, we search for the smallest number of parts that admit the geometric characterization of the parts. The segmentation is based on an intermediate-level analysis, where first the shape is decomposed into approximate convex components, which are then merged into consistent parts based on a nonlocal geometric signature. Our method is designed to handle incomplete shapes, represented by point clouds. We show segmentation results on shapes acquired by a range scanner, and an analysis of the robustness of our method to missing regions. Moreover, our method yields results that are comparable to state-of-the-art techniques evaluated on complete shapes.

Question: What is the smallest number of parts that admit the geometric characterization of the parts?


A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection methods are ineffective on scattered real-world datasets due to implicit data patterns and parameter setting issues. We define a novel Local Distance-based Outlier Factor (LDOF) to measure the outlier-ness of objects in scattered datasets which addresses these issues. LDOF uses the relative location of an object to its neighbours to determine the degree to which the object deviates from its neighbourhood. Properties of LDOF are theoretically analysed including LDOF's lower bound and its false-detection probability, as well as parameter settings. In order to facilitate parameter settings in real-world applications, we employ a top-n technique in our outlier detection approach, where only the objects with the highest LDOF values are regarded as outliers. Compared to conventional approaches (such as top-n KNN and top-n LOF), our method top-n LDOF is more effective at detecting outliers in scattered data. It is also easier to set parameters, since its performance is relatively stable over a large range of parameter values, as illustrated by experimental results on both real-world and synthetic datasets.

Question: What is a scattered dataset?


Application of Katharine Kolkaba Comfort theory to nursing care of patient. aring is in practice since existence but caring as profession named Nursing was scientifically Coined by the founder of modern nursing who in her writings "what it is and what it is not"declared the boundaries along with its Constitutional elements. Those elements with appropriate association not only revealed the nature of caring dogma it also shows that it is doing something base on thinking something or in simple words this is practice rely on theory. According to McCrae, (2011) For the sake of assuming valuable status ofprofession in society nursing struggle to legitimate its position by generation and application of theory. Nursing literature is rich regarding theory practice association. although constant body of argument, counter argument and lack of agreed conclusion regarding nursing theory creates a bit confusion among nurses but ideally nursing theory should set the code of every day practice of nurses(Giltinane, 2013) as lack of a valued unique contribution nurses make to health care based on a specialized body of knowledge will portrayed nursing role as subordinate to doctor (Mccrae, 2011) Eminent nurses' theorist, scientist, Researchers, Clinicians, Educators and intellectual intelligentsia aid evidence to different perspectives of theory practice link. Some unanimous convincing narratives argue that the relationship is reciprocal and according to (Mckenna, 2005) Nursing theory takes its origin from practice, than reverse to practice for testing and at the end become set to guide the practice.

Question: What is the relationship between theory and practice?


Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems. In this paper, we propose a multiple-input multiple-output (MIMO) receiver algorithm that exploits channel hardening that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the HHH matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix H increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes HTHx, where x is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the HTH matrix. We also propose a simple estimation scheme which directly obtains an estimate of HTH (instead of an estimate of H), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The proposed CHEMP receiver achieves very good performance in large-scale MIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of H. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes.

Question: What is the complexity of the proposed MPD algorithm?


Upgrading Lignocellulosic Biomasses : Hydrogenolysis of Platform Derived Molecules Promoted by Heterogeneous Pd-Fe Catalysts. This review provides an overview of heterogeneous bimetallic Pd-Fe catalysts in the C–C and C–O cleavage of platform molecules such as C2–C6 polyols, furfural, phenol derivatives and aromatic ethers that are all easily obtainable from renewable cellulose, hemicellulose and lignin (the major components of lignocellulosic biomasses). The interaction between palladium and iron affords bimetallic Pd-Fe sites (ensemble or alloy) that were found to be very active in several sustainable reactions including hydrogenolysis, catalytic transfer hydrogenolysis (CTH) and aqueous phase reforming (APR) that will be highlighted. This contribution concentrates also on the different synthetic strategies (incipient wetness impregnation, deposition-precipitaion, co-precipitaion) adopted for the preparation of heterogeneous Pd-Fe systems as well as on the main characterization techniques used (XRD, TEM, H2-TPR, XPS and EXAFS) in order to elucidate the key factors that influence the unique catalytic performances observed.

Question: What is the difference between the different strategies used for the preparation of heterogeneous Pd-Fe catalysts?


Addressing Female Genital Mutilation/Cutting (FGM/C) in the Era of Clitoral Reconstruction: Plastic Surgery. Purpose of the Review The aim of this review is to give an overview of the recent evidence on clitoral reconstruction and other relevant reconstructive plastic surgery measures after female genital mutilation/cutting (FGM/C).   Recent Findings Recent publications present refinements and modifications of the surgical technique of clitoral reconstruction along with reconstruction of the labia majora and clitoral hood. Novel approaches with reposition of the clitoral nerve, anchoring of the labia majora, fat grafting, and full thickness mucosa grafts have been introduced. The current evidence on outcomes of clitoral reconstruction shows potential benefits. However, there is a risk of postoperative complications and a negative outcome. Experts in the field advocate for a multidisciplinary approach including psychosexual counseling and health education with or without subsequent clitoral reconstructive surgery.   Summary The evolution of reconstructive treatment for women with FGM/C is expanding, however at a slow rate. The scarcity of evidence on clitoral reconstruction halters availability of clinical guidelines and consensus regarding best practice. Clitoral reconstruction should be provided by multidisciplinary referral centers in a research setting with long-term follow-up on outcomes of postoperative morbidity and possible benefits.

Question: What is the evidence on clitoral reconstruction?


Storage and Querying of E-Commerce Data. New generation of e-commerce applications require data sch emas that are constantly evolving and sparsely populated. The co nventional horizontal row representation fails to meet these re quir ments. We represent objects in a vertical format storing an o bject as a set of tuples. Each tuple consists of an object identifier and attribute name-value pair. Schema evolution is now easy. Ho wever, writing queries against this format becomes cumberso me. We create a logical horizontal view of the vertical representa tion and transform queries on this view to the vertical table. We pres ent alternative implementations and performance results that s ow the effectiveness of the vertical representation for sparse da ta. We also identify additional facilities needed in database systems to support these applications well.

Question: How to store and query e-commerce data?


Librispeech: An ASR corpus based on public domain audio books. This paper introduces a new corpus of read English speech, suitable for training and evaluating speech recognition systems. The LibriSpeech corpus is derived from audiobooks that are part of the LibriVox project, and contains 1000 hours of speech sampled at 16 kHz. We have made the corpus freely available for download, along with separately prepared language-model training data and pre-built language models. We show that acoustic models trained on LibriSpeech give lower error rate on the Wall Street Journal (WSJ) test sets than models trained on WSJ itself. We are also releasing Kaldi scripts that make it easy to build these systems.

Question: What is the librispeech corpus?


Chess Q & A : Question Answering on Chess Games. We introduce a new dataset1 for the evaluation of models addressing reasoning tasks. For a position in a chess game, we provide question and answer pairs, an image of the board, and the sequence of moves up to that position. We hope this synthetic task will improve our understanding in memory based Deep Learning with posed challenges.

Question: What is the dataset?


DakNet: rethinking connectivity in developing nations. DakNet provides extraordinarily low-cost digital communication, letting remote villages leapfrog past the expense of traditional connectivity solutions and begin development of a full-coverage broadband wireless infrastructure. What is the basis for a progressive, market-driven migration from e-governance to universal broadband connectivity that local users will pay for? DakNet, an ad hoc network that uses wireless technology to provide asynchronous digital connectivity, is evidence that the marriage of wireless and asynchronous service may indeed be the beginning of a road to universal broadband connectivity. DakNet has been successfully deployed in remote parts of both India and Cambodia at a cost two orders of magnitude less than that of traditional landline solutions.

Question: What is the basis for a progressive, market-driven migration from e-governance to universal broadband connectivity that local users will pay for?


Socio-cognitive gamification: general framework for educational games. Gamification of learning material has received much interest from researchers in the past years. This paper aims to further improve such learning experience by applying socio-cognitive gamification to educational games. Dynamic difficulty adjustment (DDA) is a well-known tool in optimizing gaming experience. It is a process to control the parameters in a video game automatically based on user experience in real-time. This method can be extended by using a biofeedback-approach, where certain aspects of the player's ability is estimated based on physiological measurement (e.g. eye tracking, ECG, EEG). Here, we outline the design of a biofeedback-based framework that supports dynamic difficulty adjustment in educational games. It has a universal architecture, so the concept can be employed to engage users in non-game contexts as well. The framework accepts input from the games, from the physiological sensors and from the so-called supervisor unit. This special unit empowers a new social aspect by enabling another user to observe or intervene during the interaction. To explain the game-user interaction itself in educational games we propose a hybrid model.

Question: What is a biofeedback-based framework?


Plutus: Scalable Secure File Sharing on Untrusted Storage. Plutus is a cryptographic storage system that enables secure file sharing without placing much trust on the file servers. In particular, it makes novel use of cryptographic primitives to protect and share files. Plutus features highly scalable key management while allowing individual users to retain direct control over who gets access to their files. We explain the mechanisms in Plutus to reduce the number of cryptographic keys exchanged between users by using filegroups, distinguish file read and write access, handle user revocation efficiently, and allow an untrusted server to authorize file writes. We have built a prototype of Plutus on OpenAFS. Measurements of this prototype show that Plutus achieves strong security with overhead comparable to systems that encrypt all network traffic.

Question: What is the overhead of Plutus?


High efficiency Ka-band Gallium Nitride power amplifier MMICs. The design and performance of two high efficiency Ka-band power amplifier MMICs utilizing a 0.15μm GaN HEMT process technology is presented. Measured in-fixture continuous wave (CW) results for the 3-stage balanced amplifier demonstrates up to 11W of output power and 30% power added efficiency (PAE) at 30GHz. The 3-stage single-ended design produced over 6W of output power and up to 34% PAE. The die size for the balanced and single-ended MMICs are 3.24×3.60mm2 and 1.74×3.24mm2 respectively.

Question: What is the size of the gallium nitride power amplifier?


Spam filtering email classification (SFECM) using gain and graph mining algorithm. This paper proposes a hybrid solution of spam email classifier using context based email classification model as main algorithm complimented by information gain calculation to increase spam classification accuracy. Proposed solution consists of three stages email pre-processing, feature extraction and email classification. Research has found that LingerIG spam filter is highly effective at separating spam emails from cluster of homogenous work emails. Also experiment result proved the accuracy of spam filtering is 100% as recorded by the team of developers at University of Sydney. The study has shown that implementing the spam filter in the context-based email classification model is feasible. Experiment of the study has confirmed that spam filtering aspect of context-based classification model can be improved.

Question: What is the context-based email classification model?


Designing for Labour: Uber and the On-Demand Mobile Workforce. Apps allowing passengers to hail and pay for taxi service on their phone? such as Uber and Lyft-have affected the livelihood of thousands of workers worldwide. In this paper we draw on interviews with traditional taxi drivers, rideshare drivers and passengers in London and San Francisco to understand how "ride-sharing" transforms the taxi business. With Uber, the app not only manages the allocation of work, but is directly involved in "labour issues": changing the labour conditions of the work itself. We document how Uber driving demands new skills such as emotional labour, while increasing worker flexibility. We discuss how the design of new technology is also about creating new labour opportunities -- jobs -- and how we might think about our responsibilities in designing these labour relations.

Question: How does Uber affect the labour conditions of taxi drivers?


Nuclear CDKs Drive Smad Transcriptional Activation and Turnover in BMP and TGF-β Pathways. TGF-beta and BMP receptor kinases activate Smad transcription factors by C-terminal phosphorylation. We have identified a subsequent agonist-induced phosphorylation that plays a central dual role in Smad transcriptional activation and turnover. As receptor-activated Smads form transcriptional complexes, they are phosphorylated at an interdomain linker region by CDK8 and CDK9, which are components of transcriptional mediator and elongation complexes. These phosphorylations promote Smad transcriptional action, which in the case of Smad1 is mediated by the recruitment of YAP to the phosphorylated linker sites. An effector of the highly conserved Hippo organ size control pathway, YAP supports Smad1-dependent transcription and is required for BMP suppression of neural differentiation of mouse embryonic stem cells. The phosphorylated linker is ultimately recognized by specific ubiquitin ligases, leading to proteasome-mediated turnover of activated Smad proteins. Thus, nuclear CDK8/9 drive a cycle of Smad utilization and disposal that is an integral part of canonical BMP and TGF-beta pathways.

Question: What is the difference between a nuclear CDK and a cytoplasmic CDK?


An extensive comparative study of cluster validity indices. The validation of the results obtained by clustering algorithms is a fundamental part of the clustering process. The most used approaches for cluster validation are based on internal cluster validity indices. Although many indices have been proposed, there is no recent extensive comparative study of their performance. In this paper we show the results of an experimental work that compares 30 cluster validity indices in many different environments with different characteristics. These results can serve as a guideline for selecting the most suitable index for each possible application and provide a deep insight into the performance differences between the currently available indices. & 2012 Elsevier Ltd. All rights reserved.

Question: What is a cluster validity index?


Efficient Edge Detection on Low-Cost FPGAs. Improving the efficiency of edge detection in embedded applications, such as UAV control, is critical for reducing system cost and power dissipation. Field programmable gate arrays (FPGA) are a good platform for making improvements because of their specialised internal structure. However, current FPGA edge detectors do not exploit this structure well. A new edge detection architecture is proposed that is better optimised for FPGAs. The basis of the architecture is the Sobel edge kernels that are shown to be the most suitable because of their separability and absence of multiplications. Edge intensities are calculated with a new 4:2 compressor that consists of two custom-designed 3:2 compressors. Addition speed is increased by breaking carry propagation chains with look-ahead logic. Testing of the design showed it gives a 28% increase in speed and 4.4% reduction in area over previous equivalent designs, which demonstrated that it will lower the cost of edge detection systems, dissipate less power and still maintain highspeed control. Keywords—edge detection; FPGA; compressor; low-cost; UAV

Question: How can we improve the efficiency of edge detection in embedded applications?


Excitation Control Method for a Low Sidelobe SIW Series Slot Array Antenna With 45$^{\circ}$  Linear Polarization. A sidelobe suppression method for a series slot array antenna which radiates 45° -inclined linear polarization is proposed. Axial displacements are employed to create arbitrary excitation coefficients for individual centered-inclined radiating slots along the center line of a broad wall. To verify the proposed design method, we design two types of center-fed linear slot array antennas with a Dolph-Chebyshev distribution for -20 dB and -26 dB sidelobe levels (SLLs) in the Ka band. Furthermore, a cross-validation process involving an equivalent circuit model analysis and electromagnetic full-wave simulation using CST MWS is utilized. The entire structure of the proposed series slot array antenna is fabricated on printed circuit boards (PCBs), including drilling and chemical etching, to secure advantages of miniaturization and cost reduction. The measured realized gains are 15.17 and 15.95 dBi and SLLs are -18.7 and -22.5 dB respectively for two types of fabricated antennas. It demonstrates the validity of the proposed sidelobe suppression method.

Question: How to suppress sidelobes of a slot array antenna?


Fast and flexible word searching on compressed text. We present a fast compression technique for natural language texts. The novelties are that (1) decompression of arbitrary portions of the text can be done very efficiently, (2) exact search for words and phrases can be done on the compressed text directly, using any known sequential pattern-matching algorithm, and (3) word-based approximate and extended search can also be done efficiently without any decoding. The compression scheme uses a semistatic word-based model and a Huffman code where the coding alphabet is byte-oriented rather than bit-oriented. We compress typical English texts to about 30% of their original size, against 40% and 35% for Compress and Gzip, respectively. Compression time is close to that of Compress and approximately half of the time of Gzip, and decompression time is lower than that of Gzip and one third of that of Compress. We present three algorithms to search the compressed text. They allow a large number of variations over the basic word and phrase search capability, such as sets of characters, arbitrary regular expressions, and approximate matching. Separators and stopwords can be discarded at search time without significantly increasing the cost. When searching for simple words, the experiments show that running our algorithms on a compressed text is twice as fast as running the best existing software on the uncompressed version of the same text. When searching complex or approximate patterns, our algorithms are up to 8 times faster than the search on uncompressed text. We also discuss the impact of our technique in inverted files pointing to logical blocks and argue for the possibility of keeping the text compressed all the time, decompressing only for displaying purposes.

Question: What is the size of the canadian military?


Accidental death due to complete autoerotic asphyxia associated with transvestic fetishism and anal self-stimulation - case report.. A case is reported of a 36-year-old male, found dead in his locked room, lying on a bed, dressed in his mother's clothes, with a plastic bag over his head, hands tied and with a barrel wooden cork in his rectum. Two pornographic magazines were found on a chair near the bed, so that the deceased could see them well. Asphyxia was controlled with a complex apparatus which consisted of two elastic luggage rack straps, the first surrounding his waist, perineum, and buttocks, and the second the back of his body, and neck. According to the psychological autopsy based on a structured interview (SCID-I, SCID-II) with his father, the deceased was single, unemployed and with a part college education. He had grown up in a poor family with a reserved father and dominant mother, and was indicative of fulfilling DSM-IV diagnostic criteria for alcohol dependence, paraphilia involving hypoxyphilia with transvestic fetishism and anal masturbation and a borderline personality disorder. There was no evidence of previous psychiatric treatment. The Circumstances subscale of Beck's Suicidal Intent Scale (SIS-CS) pointed at the lack of final acts (thoughts or plans) in anticipation of death, and absence of a suicide note or overt communication of suicidal intent before death. Integration of the crime scene data with those of the forensic medicine and psychological autopsy enabled identification of the event as an accidental death, caused by neck strangulation, suffocation by a plastic bag, and vagal stimulation due to a foreign body in the rectum.

Question: What is the difference between a transvestic fetishist and a crossdresser?


Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation. In optimization, multiple objectives and constraints cannot be handled independently of the underlying optimizer. Requirements such as continuity and di erentiability of the cost surface add yet another con icting element to the decision process. While \better" solutions should be rated higher than \worse" ones, the resulting cost landscape must also comply with such requirements. Evolutionary algorithms (EAs), which have found application in many areas not amenable to optimization by other methods, possess many characteristics desirable in a multiobjective optimizer, most notably the concerted handling of multiple candidate solutions. However, EAs are essentially unconstrained search techniques which require the assignment of a scalar measure of quality, or tness, to such candidate solutions. After reviewing current evolutionary approaches to multiobjective and constrained optimization, the paper proposes that tness assignment be interpreted as, or at least related to, a multicriterion decision process. A suitable decision making framework based on goals and priorities is subsequently formulated in terms of a relational operator, characterized, and shown to encompass a number of simpler decision strategies. Finally, the ranking of an arbitrary number of candidates is considered. The e ect of preference changes on the cost surface seen by an EA is illustrated graphically for a simple problem. The paper concludes with the formulation of a multiobjective genetic algorithm based on the proposed decision strategy. Niche formation techniques are used to promote diversity among preferable candidates, and progressive articulation of preferences is shown to be possible as long as the genetic algorithm can recover from abrupt changes in the cost landscape.

Question: What is a multiobjective genetic algorithm?


Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs. Knowledge graphs are large, useful, but incomplete knowledge repositories. Œey encode knowledge through entities and relations which de€ne each other through the connective structure of the graph. Œis has inspired methods for the joint embedding of entities and relations in continuous low-dimensional vector spaces, that can be used to induce new edges in the graph, i.e., link prediction in knowledge graphs. Learning these representations relies on contrasting positive instances with negative ones. Knowledge graphs include only positive relation instances, leaving the door open for a variety of methods for selecting negative examples. We present an empirical study on the impact of negative sampling on the learned embeddings, assessed through the task of link prediction. We use state-of-the-art knowledge graph embedding methods – Rescal , TransE, DistMult and ComplEX – and evaluate on benchmark datasets – FB15k and WN18. We compare well known methods for negative sampling and propose two new embedding based sampling methods. We note a marked di'erence in the impact of these sampling methods on the two datasets, with the "traditional" corrupting positives method leading to best results on WN18, while embedding based methods bene€t FB15k.

Question: What is the impact of negative sampling on link prediction in knowledge graphs?


Multilevel thresholding for satellite image segmentation with moth-flame based optimization. In this paper, an improved version of the moth-flame optimization (MFO) algorithm for image segmentation is proposed to effectively enhance the optimal multilevel thresholding of satellite images. Multilevel thresholding is one of the most widely used methods for image segmentation, as it has efficient processing ability and easy implementation. However, as the number of threshold values increase, it consequently becomes computationally expensive. To overcome this problem, the nature-inspired meta-heuristic named multilevel thresholding moth-flame optimization algorithm (MTMFO) for multilevel thresholding was developed. The improved method proposed herein was tested on various satellite images tested against five different existing methods: the genetic algorithm (GA), the differential evolution (DE) algorithm, the artificial bee colony (ABC) algorithm, the particle swarm optimization (PSO) algorithm, and the moth-flame optimization (MFO) algorithm for solving multilevel satellite image thresholding problems. Experimental results indicate that the MTMFO more effectively and accurately identifies the optimal threshold values with respect to the other state-of-the-art optimization algorithms.

Question: What is the difference between the moth-flame optimization and the moth-flame optimization algorithm?


A Proximity Authentication System for Smartphones. Authenticating whether two smartphones are in close proximity is important in smartphone security. For example, the authentication result can be used to pair two devices and construct a secure communication channel between them. Many existing proximity authentication systems rely on short range networks-the communication is usually restricted in short range networks. However, this approach is inadequate when we want to verify whether the communication distance is within a few centimeters, i.e. near field. To address this challenge, many other techniques construct systems based on the near field communication (NFC) system. Unfortunately, only a small portion of smart devices in the current market are equipped with NFC chips. The purpose of this paper is to provide a close proximity authentication system which does not depend on NFC chips. We devise a system to achieve close proximity authentication by using correlated finger movements on the two smartphones. Human input usually contains errors and is of low entropy, which affects the usability and security of our system. We solve these issues in an efficient way, considering the limited computational resources on smart devices. Our system does not need any prior secret information shared between the two devices, and generates the same high-entropy cryptographic key for both devices in a successful authentication. The efficiency of the system is validated by evaluations on Motorola Droid smartphones.

Question: What is the purpose of this paper?


Development of a 6-DOF manipulator actuated with a straight-fiber-type artificial muscle. Robots have become an integral part of human life, and the relationship between humans and robots has grown closer. Thus, it is desired that robots have characteristics similar to humans. In this context, we paid attention to an artificial muscle actuator. We used straight-fiber-type artificial muscles, derived from the McKibben type, which have excellent characteristics with respect to the contraction rate and force. We developed a 6-DOF manipulator actuated by a straight fiber artificial muscle. Furthermore, we tried to control the manipulator position by considering its characteristics.

Question: What is a straight-fiber-type artificial muscle?


Cultural Congruent Care : A Reflection on Patient Outcome. The growing diverse multicultural population in the United States requires that healthcare workers develop cultural knowledge, awareness, and sensitivity to help diverse patient population receive quality health care. Personal belief has been identified as a significant contributor to professional care delivery and may influence the provision of culturally competent care. However, the relationship between cultural competence and the individual cognitive perception has been an uneasy one. This article explores the moral foundations of cultural competence and ultimately its impact on patient care outcome.

Question: What is cultural competence?


Differentially Private Online Learning for Cloud-Based Video Recommendation With Multimedia Big Data in Social Networks. With the rapid growth in multimedia services and the enormous offers of video content in online social networks, users have difficulty in obtaining their interests. Therefore, various personalized recommendation systems have been proposed. However, they ignore that the accelerated proliferation of social media data has led to the big data era, which has greatly impeded the process of video recommendation. In addition, none of them has considered both the privacy of users' contexts (e.g., social status, ages, and hobbies) and video service vendors' repositories, which are extremely sensitive and of significant commercial value. To handle these problems, we propose a cloud-assisted differentially private video recommendation system based on distributed online learning. In our framework, service vendors are modeled as distributed cooperative learners, recommending videos according to user's context, while simultaneously adapting the video-selection strategy based on user-click feedback to maximize total user clicks (reward). Considering the sparsity and heterogeneity of big social media data, we also propose a novel geometric differentially private model, which can greatly reduce the performance loss. Our simulation shows the proposed algorithms outperform other existing methods and keep a delicate balance between the total reward and privacy preserving level.

Question: What is the difference between the differentially private online learning and the differentially private video recommendation?


Cryptanalysis of DES Implemented on Computers with Cache. This paper presents the results of applying an attack against the Data Encryption Standard (DES) implemented in some applications, using side-channel information based on CPU delay as proposed in [11]. This cryptanalysis technique uses side-channel information on encryption processing to select and collect effective plaintexts for cryptanalysis, and infers the information on the expanded key from the collected plaintexts. On applying this attack, we found that the cipher can be broken with 2 known plaintexts and 2 calculations at a success rate > 90%, using a personal computer with 600-MHz Pentium III. We discuss the feasibility of cache attack on ciphers that need many S-box look-ups, through reviewing the results of our experimental attacks on the block ciphers excluding DES, such as AES.

Question: How does the cache attack work?


Automatically extracting cancer disease characteristics from pathology reports into a Disease Knowledge Representation Model. We introduce an extensible and modifiable knowledge representation model to represent cancer disease characteristics in a comparable and consistent fashion. We describe a system, MedTAS/P which automatically instantiates the knowledge representation model from free-text pathology reports. MedTAS/P is based on an open-source framework and its components use natural language processing principles, machine learning and rules to discover and populate elements of the model. To validate the model and measure the accuracy of MedTAS/P, we developed a gold-standard corpus of manually annotated colon cancer pathology reports. MedTAS/P achieves F1-scores of 0.97-1.0 for instantiating classes in the knowledge representation model such as histologies or anatomical sites, and F1-scores of 0.82-0.93 for primary tumors or lymph nodes, which require the extractions of relations. An F1-score of 0.65 is reported for metastatic tumors, a lower score predominantly due to a very small number of instances in the training and test sets.

Question: What is the gold standard corpus?


Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana.. The Agrobacterium vacuum infiltration method has made it possible to transform Arabidopsis thaliana without plant tissue culture or regeneration. In the present study, this method was evaluated and a substantially modified transformation method was developed. The labor-intensive vacuum infiltration process was eliminated in favor of simple dipping of developing floral tissues into a solution containing Agrobacterium tumefaciens, 5% sucrose and 500 microliters per litre of surfactant Silwet L-77. Sucrose and surfactant were critical to the success of the floral dip method. Plants inoculated when numerous immature floral buds and few siliques were present produced transformed progeny at the highest rate. Plant tissue culture media, the hormone benzylamino purine and pH adjustment were unnecessary, and Agrobacterium could be applied to plants at a range of cell densities. Repeated application of Agrobacterium improved transformation rates and overall yield of transformants approximately twofold. Covering plants for 1 day to retain humidity after inoculation also raised transformation rates twofold. Multiple ecotypes were transformable by this method. The modified method should facilitate high-throughput transformation of Arabidopsis for efforts such as T-DNA gene tagging, positional cloning, or attempts at targeted gene replacement.

Question: What is the modified floral dip method?


Overview of narrowband IoT in LTE Rel-13. In 3GPP Rel-13, a narrowband system, named Narrowband Internet of Things (NB-IoT), has been introduced to provide low-cost, low-power, wide-area cellular connectivity for the Internet of Things. This system, based on Long Term Evolution (LTE) technology, supports most LTE functionalities albeit with essential simplifications to reduce device complexity. Further optimizations to increase coverage, reduce overhead and reduce power consumption while increasing capacity have been introduced as well. The design objectives of NB-IoT include low-complexity devices, high coverage, long device battery life, and massive capacity. Latency is relaxed although a delay budget of 10 seconds is the target for exception reports. This paper provides an overview of NB-IoT design, including salient features from the physical and higher layers. Illustrative results with respect to performance objectives are also provided. Finally, NB-IoT enhancements in LTE Rel-14 are briefly outlined.

Question: What is the difference between LTE and NB-IoT?


An Experience Teaching a Graduate Course in Cryptography. This article describes an experience of teaching a graduate-level course in cryptography and computer security at New York University. The course content as well as lessons learned and plans for the future are discussed.

Question: What is the course content?


Countering kernel rootkits with lightweight hook protection. Kernel rootkits have posed serious security threats due to their stealthy manner. To hide their presence and activities, many rootkits hijack control flows by modifying control data or hooks in the kernel space. A critical step towards eliminating rootkits is to protect such hooks from being hijacked. However, it remains a challenge because there exist a large number of widely-scattered kernel hooks and many of them could be dynamically allocated from kernel heap and co-located together with other kernel data. In addition, there is a lack of flexible commodity hardware support, leading to the socalled protection granularity gap -- kernel hook protection requires byte-level granularity but commodity hardware only provides page level protection.  To address the above challenges, in this paper, we present HookSafe, a hypervisor-based lightweight system that can protect thousands of kernel hooks in a guest OS from being hijacked. One key observation behind our approach is that a kernel hook, once initialized, may be frequently "read"-accessed, but rarely write"-accessed. As such, we can relocate those kernel hooks to a dedicated page-aligned memory space and then regulate accesses to them with hardware-based page-level protection. We have developed a prototype of HookSafe and used it to protect more than 5,900 kernel hooks in a Linux guest. Our experiments with nine real-world rootkits show that HookSafe can effectively defeat their attempts to hijack kernel hooks. We also show that HookSafe achieves such a large-scale protection with a small overhead (e.g., around 6% slowdown in performance benchmarks).

Question: How to protect kernel hooks from being hijacked?


How STEM Education Improves Student Learning. The intent of this article is to examine current taxonomies used to design and deliver Science, Technology, Engineering, and Mathematics (i.e., STEM) curriculum in an effort to attract a greater variety of students to the STEM field of study in the K-12 public school environment. I analyzed specific aspects of STEM-based programs to compare STEM education components to traditional college-preparatory methods of instruction, including looking for environmental practices that may attract female and first-generation college attendees toward developing a positive attitude toward attaining a STEM education. I also made connections between current instructional trends and their impact on student mastery.

Question: How does STEM education improve student learning?


A Language Independent Algorithm for Single and Multiple Document Summarization. S S S w S w w S S Sim + ∈ ∧ ∈ = other similarity metrics: cosine, string kernels, etc. 3. r i BC-HurricaneGilbert 09-11 0339 4. BC-Hurricane Gilbert , 0348 5. Hurricane Gilbert Heads Toward Dominican Coast 6. By RUDDY GONZALEZ 7. Associated Press Writer 8. SANTO DOMINGO , Dominican Republic ( AP ) 9. Hurricane Gilbert swept toward the Dominican Republic Sunday , and the Civil Defense alerted its heavily populated south coast to prepare for high winds , heavy rains and high seas . 10. The storm was approaching from the southeast with sustained winds of 75 mph gusting to 92 mph . 11. " There is no need for alarm , " Civil Defense Director Eugenio Cabral said in a television alert shortly before midnight Saturday . 12. Cabral said residents of the province of Barahona should closely follow Gilbert 's movement . 13. An estimated 100,000 people live in the province , including 70,000 in the city of Barahona , about 125 miles west of Santo Domingo . 14. Tropical Storm Gilbert formed in the eastern Caribbean and strengthened into a hurricane Saturday night . 15. The National Hurricane Center in Miami reported its position at 2a.m. Sunday at latitude 16.1 north , longitude 67.5 west , about 140 miles south of Ponce , Puerto Rico , and 200 miles southeast of Santo Domingo . 16. The National Weather Service in San Juan , Puerto Rico , said Gilbert was moving westward at 15 mph with a " broad area of cloudiness and heavy weather " rotating around the center of the storm . 17. The weather service issued a flash flood watch for Puerto Rico and the Virgin Islands until at least 6p.m. Sunday . 18. Strong winds associated with the Gilbert brought coastal flooding , strong southeast winds and up to 12 feet feet to Puerto Rico 's south coast . 19. There were no reports of casualties . 20. San Juan , on the north coast , had heavy rains and gusts Saturday , but they subsided during the night . 21. On Satu

Question: What is the name of the Canadian Armed Forces?


Blood monocytes: development, heterogeneity, and relationship with dendritic cells.. Monocytes are circulating blood leukocytes that play important roles in the inflammatory response, which is essential for the innate response to pathogens. But inflammation and monocytes are also involved in the pathogenesis of inflammatory diseases, including atherosclerosis. In adult mice, monocytes originate in the bone marrow in a Csf-1R (MCSF-R, CD115)-dependent manner from a hematopoietic precursor common for monocytes and several subsets of macrophages and dendritic cells (DCs). Monocyte heterogeneity has long been recognized, but in recent years investigators have identified three functional subsets of human monocytes and two subsets of mouse monocytes that exert specific roles in homeostasis and inflammation in vivo, reminiscent of those of the previously described classically and alternatively activated macrophages. Functional characterization of monocytes is in progress in humans and rodents and will provide a better understanding of the pathophysiology of inflammation.

Question: What is the function of monocytes?


Classification of brain disease in magnetic resonance images using two-stage local feature fusion. BACKGROUND Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale.   METHODS Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to.   RESULTS We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block.   DISCUSSION This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls.

Question: How to classify brain disease using magnetic resonance images?


Collaboration with Lean Media: how open-source software succeeds. Open-source software, usually created by volunteer programmers dispersed worldwide, now competes with that developed by software firms. This achievement is particularly impressive as open-source programmers rarely meet. They rely heavily on electronic media, which preclude the benefits of face-to-face contact that programmers enjoy within firms. In this paper, we describe findings that address this paradox based on observation, interviews and quantitative analyses of two open-source projects. The findings suggest that spontaneous work coordinated afterward is effective, rational organizational culture helps achieve agreement among members and communications media moderately support spontaneous work. These findings can imply a new model of dispersed collaboration.

Question: How does open-source software succeed?


A quad 25Gb/s 270mW TIA in 0.13µm BiCMOS with <0.15dB crosstalk penalty. The push for 100Gb/s optical transport and beyond necessitates electronic components at higher speed and integration level in order to drive down cost, complexity and size of transceivers [1-2]. This requires parallel multi-channel optical transceivers each operating at 25Gb/s and beyond. Due to variations in the output power of transmitters and in some cases different optical paths the parallel receivers have to operate at different input optical power levels. This trend places increasing strain to the acceptable inter-channel crosstalk in integrated multi-channel receivers [3]. Minimizing this cross-talk penalty when all channels are operational is becoming increasingly important in ultra-high throughput optical links.

Question: What is the crosstalk penalty in a parallel multi-channel receiver?


Can machine learning aid in delivering new use cases and scenarios in 5G?. 5G represents the next generation of communication networks and services, and will bring a new set of use cases and scenarios. These in turn will address a new set of challenges from the network and service management perspective, such as network traffic and resource management, big data management and energy efficiency. Consequently, novel techniques and strategies are required to address these challenges in a smarter way. In this paper, we present the limitations of the current network and service management and describe in detail the challenges that 5G is expected to face from a management perspective. The main contribution of this paper is presenting a set of use cases and scenarios of 5G in which machine learning can aid in addressing their management challenges. It is expected that machine learning can provide a higher and more intelligent level of monitoring and management of networks and applications, improve operational efficiencies and facilitate the requirements of the future 5G network.

Question: What is the main contribution of this paper?


Anatomical and biomechanical mechanisms of subacromial impingement syndrome.. Subacromial impingement syndrome is the most common disorder of the shoulder, resulting in functional loss and disability in the patients that it affects. This musculoskeletal disorder affects the structures of the subacromial space, which are the tendons of the rotator cuff and the subacromial bursa. Subacromial impingement syndrome appears to result from a variety of factors. Evidence exists to support the presence of the anatomical factors of inflammation of the tendons and bursa, degeneration of the tendons, weak or dysfunctional rotator cuff musculature, weak or dysfunctional scapular musculature, posterior glenohumeral capsule tightness, postural dysfunctions of the spinal column and scapula and bony or soft tissue abnormalities of the borders of the subacromial outlet. These entities may lead to or cause dysfunctional glenohumeral and scapulothoracic movement patterns. These various mechanisms, singularly or in combination may cause subacromial impingement syndrome.

Question: What is the most common disorder of the shoulder?


Monte Carlo Tree Search for Asymmetric Trees. We present an extension of Monte Carlo Tree Search (MCTS) that strongly increases its efficiency for trees with asymmetry and/or loops. Asymmetric termination of search trees introduces a type of uncertainty for which the standard upper confidence bound (UCB) formula does not account. Our first algorithm (MCTS-T), which assumes a non-stochastic environment, backs-up tree structure uncertainty and leverages it for exploration in a modified UCB formula. Results show vastly improved efficiency in a well-known asymmetric domain in which MCTS performs arbitrarily bad. Next, we connect the ideas about asymmetric termination to the presence of loops in the tree, where the same state appears multiple times in a single trace. An extension to our algorithm (MCTS-T+), which in addition to nonstochasticity assumes full state observability, further increases search efficiency for domains with loops as well. Benchmark testing on a set of OpenAI Gym and Atari 2600 games indicates that our algorithms always perform better than or at least equivalent to standard MCTS, and could be first-choice tree search algorithms for non-stochastic, fully-observable environments.

Question: What is the name of the algorithm?


Erratum to: Eye–hand coordination in a sequential target contact task. Most object manipulation tasks involve a series of actions demarcated by mechanical contact events, and gaze is typically directed to the locations of these events as the task unfolds. Here, we examined the timing of gaze shifts relative to hand movements in a task in which participants used a handle to contact sequentially five virtual objects located in a horizontal plane. This task was performed both with and without visual feedback of the handle position. We were primarily interested in whether gaze shifts, which in our task shifted from a given object to the next about 100 ms after contact, were predictive or triggered by tactile feedback related to contact. To examine this issue, we included occasional catch contacts where forces simulating contact between the handle and object were removed. In most cases, removing force did not alter the timing of gaze shifts irrespective of whether or not vision of handle position was present. However, in about 30% of the catch contacts, gaze shifts were delayed. This percentage corresponded to the fraction of contacts with force feedback in which gaze shifted more than 130 ms after contact. We conclude that gaze shifts are predictively controlled but timed so that the hand actions around the time of contact are captured in central vision. Furthermore, a mismatch between the expected and actual tactile information related to the contact can lead to a reorganization of gaze behavior for gaze shifts executed greater than 130 ms after a contact event.

Question: What is the difference between predictive and triggered gaze shifts?


Fuzzy Cognitive Map Learning Based on Nonlinear Hebbian Rule. Fuzzy Cognitive Map (FCM) is a soft computing technique for modeling systems. It combines synergistically the theories of neural networks and fuzzy logic. The methodology of developing FCMs is easily adaptable but relies on human experience and knowledge, and thus FCMs exhibit weaknesses and dependence on human experts. The critical dependence on the expert's opinion and knowledge, and the potential convergence to undesired steady states are deficiencies of FCMs. In order to overcome these deficiencies and improve the efficiency and robustness of FCM a possible solution is the utilization of learning methods. This research work proposes the utilization of the unsupervised Hebbian algorithm to nonlinear units for training FCMs. Using the proposed learning procedure, the FCM modifies its fuzzy causal web as causal patterns change and as experts update their causal knowledge.

Question: What is fuzzy cognitive map?


Traceable Air Baggage Handling System Based on RFID Tags in the Airport. The RFID is not only a feasible, novel, and cost-effective candidate for daily object identification but it is also considered as a significant tool to provide traceable visibility along different stages of the aviation supply chain. In the air baggage handing application, the RFID tags are used to enhance the ability for baggage tracking, dispatching and conveyance so as to improve the management efficiency and the users' satisfaction. We surveyed current related work and introduce the IATA RP1740c protocol used for the standard to recognize the baggage tags. One distributed aviation baggage traceable application is designed based on the RFID networks. We describe the RFID-based baggage tracking experiment in the BCIA (Beijing Capital International Airport). In this experiment the tags are sealed in the printed baggage label and the RFID readers are fixed in the certain interested positions of the BHS in the Terminal 2. We measure the accurate recognition rate and monitor the baggage's real-time situation on the monitor's screen. Through the analysis of the measured results within two months we emphasize the advantage of the adoption of RFID tags in this high noisy BHS environment. The economical benefits achieved by the extensive deployment of RFID in the baggage handing system are also outlined.

Question: What is the IATA RP1740c protocol?


Feature Selection Using Adaboost for Face Expression Recognition. We propose a classification technique for face expression recognition using AdaBoost that learns by selecting the relevant global and local appearance features with the most discriminating information. Selectivity reduces the dimensionality of the feature space that in turn results in significant speed up during online classification. We compare our method with another leading margin-based classifier, the Support Vector Machines (SVM) and identify the advantages of using AdaBoost over SVM in this context. We use histograms of Gabor and Gaussian derivative responses as the appearance features. We apply our approach to the face expression recognition problem where local appearances play an important role. Finally, we show that though SVM performs equally well, AdaBoost feature selection provides a final hypothesis model that can easily be visualized and interpreted, which is lacking in the high dimensional support vectors of the SVM.

Question: How to select the relevant features for face expression recognition?


MRG-OHTC Database for Online Handwritten Tibetan Character Recognition. A handwritten Tibetan database, MRG-OHTC, is presented to facilitate the research of online handwritten Tibetan character recognition. The database contains 910 Tibetan character classes written by 130 persons from Tibetan ethnic minority. These characters are selected from basic set and extension set A of Tibetan coded character set. The current version of this database is collected using electronic pen on digital tablet. We investigate some characteristic of writing style from different writers. We evaluate MRG-OHTC database using existing algorithms as a baseline. Experimental results reveal a big challenge to higher recognition performance. To our knowledge, MRG-OHTC is the first publicly available database for handwritten Tibetan research. It provides a basic database to compare empirically different algorithms for handwritten Tibetan character recognition.

Question: What is the first publicly available database for handwritten Tibetan character recognition?


Fusing Iris, Palmprint and Fingerprint in a Multi-biometric Recognition System. This paper presents a trimodal biometric recognition system based on iris, palmprint and fingerprint. Wavelet transform and Gabor filter are used to extract features in different scales and orientations from iris and palmprint. Minutiae extraction and alignment is used for fingerprint matching. Six different fusion algorithms including score-based, rank-based and decision-based methods are used to combine the results of three modules. We also propose a new rank-based fusion algorithm Maximum Inverse Rank (MIR) which is robust with respect to variations in scores and also bad ranking from a module. CASIA datasets for iris, palmprint and fingerprint are used in this study. The experiments show the effectiveness of our fusion method and our trimodal biometric recognition system in comparison to existing multi-modal recognition systems.

Question: What is a trimodal biometric recognition system?


Sensor networks: evolution, opportunities, and challenges. Wireless microsensor networks have been identified as one of the most important technologies for the 21st century. This paper traces the history of research in sensor networks over the past three decades, including two important programs of the Defense Advanced Research Projects Agency (DARPA) spanning this period: the Distributed Sensor Networks (DSN) and the Sensor Information Technology (SensIT) programs. Technology trends that impact the development of sensor networks are reviewed, and new applications such as infrastructure security, habitat monitoring, and traffic control are presented. Technical challenges in sensor network development include network discovery, control and routing, collaborative signal and information processing, tasking and querying, and security. The paper concludes by presenting some recent research results in sensor network algorithms, including localized algorithms and directed diffusion, distributed tracking in wireless ad hoc networks, and distributed classification using local agents.

Question: What is the history of research in sensor networks?


The Ease of Doing Business Index as a tool for Investment location decisions. The Ease of Doing Business Index (EDBI) uses 41 variables to compare the business environment of different countries. It is widely used by policy makers, researchers and multinational companies. This paper aims to assess EDBI's consistency and validity in representing the business environment by using factor analysis. It is found that the EDBI presents a limited consistency and descriptive power of a country's business environment. The consequence of these findings is that multinational firms should handle carefully the EDBI in their investment decisions. GEE The Ease of Doing Business Index as a tool for Investment location decisions – João Zambujal-Oliveira, Ricardo Pinheiro-Alves

Question: What is the ease of doing business index?


Bayesian Estimation of Beta Mixture Models with Variational Inference. Bayesian estimation of the parameters in beta mixture models (BMM) is analytically intractable. The numerical solutions to simulate the posterior distribution are available, but incur high computational cost. In this paper, we introduce an approximation to the prior/posterior distribution of the parameters in the beta distribution and propose an analytically tractable (closed form) Bayesian approach to the parameter estimation. The approach is based on the variational inference (VI) framework. Following the principles of the VI framework and utilizing the relative convexity bound, the extended factorized approximation method is applied to approximate the distribution of the parameters in BMM. In a fully Bayesian model where all of the parameters of the BMM are considered as variables and assigned proper distributions, our approach can asymptotically find the optimal estimate of the parameters posterior distribution. Also, the model complexity can be determined based on the data. The closed-form solution is proposed so that no iterative numerical calculation is required. Meanwhile, our approach avoids the drawback of overfitting in the conventional expectation maximization algorithm. The good performance of this approach is verified by experiments with both synthetic and real data.

Question: What is the closed form solution?


Poor Man's Methadone: A Case Report of Loperamide Toxicity.. Loperamide, a common over-the-counter antidiarrheal drug and opioid derivative, is formulated to act upon intestinal opioid receptors. However, at high doses, loperamide crosses the blood-brain barrier and reaches central opioid receptors in the brain, leading to central opiate effects including euphoria and respiratory depression. We report the case of a young man found dead in his residence with a known history of drug abuse. At autopsy, the only significant findings were a distended bladder and bloody oral purge. Drug screening found nontoxic levels of alprazolam, fluoxetine, and marijuana metabolites. Liquid chromatography time-of-flight mass spectrometry found an unusual set of split isotope peaks consistent with chlorine. On the basis of autopsy and toxicological findings, loperamide toxicity was suspected because of its opioid properties and molecular formula containing chlorine. A sample of loperamide was analyzed by liquid chromatography time-of-flight mass spectrometry, resulting in a matching mass and retention time to the decedent's sample. Subsequently, quantitative testing detected 63 ng/mL of loperamide or more than 6 times of therapeutic peak concentration. Cause of death was determined as "toxic effects of loperamide with fluoxetine and alprazolam." Because of its opioid effects and easy accessibility, loperamide is known as "poor man's methadone" and may go undetected at medical and forensic drug screening.

Question: What is the cause of death?


A flexible and low-cost tactile sensor for robotic applications. For humans, the sense of touch is essential for interactions with the environment. With robots slowly starting to emerge as a human-centric technology, tactile information becomes increasingly important. Tactile sensors enable robots to gain information about contacts with the environment, which is required for safe interaction with humans or tactile exploration. Many sensor designs for the application on robots have been presented in literature so far. However, most of them are complex in their design and require high-tech tools for their manufacturing. In this paper, we present a novel design for a tactile sensor that can be built with low-cost, widely available materials, and low effort. The sensor is flexible, may be cut to arbitrary shapes and may have a customized spatial resolution. Both pressure distribution and absolute pressure on the sensor are detected. An experimental evaluation of our design shows low detection thresholds as well as high sensor accuracy. We seek to accelerate research on tactile feedback methods with this easy to replicate design. We consider our design a starting point for the integration of multiple sensor units to a large-scale tactile skin for robots.

Question: What is a tactile sensor?


Introduction to Robotics: Mechanics and Control. How can you change your mind to be more open? There many sources that can help you to improve your thoughts. It can be from the other experiences and also story from some people. Book is one of the trusted sources to get. You can find so many books that we share here in this website. And now, we show you one of the best, the introduction to robotics mechanics and control john j craig solution manual.

Question: How can you change your mind to be more open?


Controllability of complex networks. The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network's degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.

Question: How can we control a complex network?


Product Adoption Rate Prediction in a Competitive Market. As the worlds of commerce and the Internet technology become more inextricably linked, a large number of user consumption series become available for online market intelligence analysis. A critical demand along this line is to predict the future product adoption state of each user, which enables a wide range of applications such as targeted marketing. Nevertheless, previous works only aimed at predicting if a user would adopt a particular product or not with a binary buy-or-not representation. The problem of tracking and predicting users' adoption rates, i.e., the frequency and regularity of using each product over time, is still under-explored. To this end, we present a comprehensive study of product adoption rate prediction in a competitive market. This task is nontrivial as there are three major challenges in modeling users' complex adoption states: the heterogeneous data sources around users, the unique user preference and the competitive product selection. To deal with these challenges, we first introduce a flexible factor-based decision function to capture the change of users' product adoption rate over time, where various factors that may influence users' decisions from heterogeneous data sources can be leveraged. Using this factor-based decision function, we then provide two corresponding models to learn the parameters of the decision function with both generalized and personalized assumptions of users' preferences. We further study how to leverage the competition among different products and simultaneously learn product competition and users' preferences with both generalized and personalized assumptions. Finally, extensive experiments on two real-world datasets show the superiority of our proposed models.

Question: What is the competitive product adoption rate prediction?