From piecemeal to configurational representation of faces.. Unlike older children and adults, children of less than about 10 years of age remember photographs of faces presented upside down almost as well as those shown upright and are easily fooled by simple disguises. The development at age 10 of the ability to encode orientation-specific configurational aspects of a face may reflect completion of certain maturational changes in the right cerebral hemisphere.

Question: How do children remember faces?


Providing device integration with OPC UA. OPC UA allows the company wide access and integration of information. One important part of this information system is the automation system and its automation devices. The important issue for presenting devices in such an enterprise system is standardization of device representation. This document provides a proposal on how to standardize the presentation of devices based on a comparison of existing device integration technologies.

Question: What is OPC UA?


Necessary Conditions for Existence of Some Designs in Polynomial Metric Spaces. Let M be a metric space with a finite diameter D and a finite normalized measure μM. Let the Hilbert space L2(M) of complex-valued functions be decomposed into a countable (whenM is infinite) or finite (with D+ 1 members whenM is finite) direct sum of mutually orthogonal subspaces L2(M) = V0 ⊕ V1 ⊕ · · · (V0 is the space of constant functions). We denote N = D + 1 ifM is finite and N = ∞ otherwise. In definition and description of the notion of polynomial metric spaces we follow [26, 27].

Question: What is the diameter of a metric space?


Computationally efficient leakage inductance calculation for a high-frequency core-type transformer. Leakage inductance is a critical design attribute of high-frequency transformers. In this paper, a new method to estimate core-type transformer leakage inductance is proposed. The magnetic analysis uses a combination of analytical and numerical analysis. A two-dimensional magnetic analysis using Biot-Savart law and the method of images is introduced. Using the same field analysis, expressions for mean squared field intensity values necessary for estimating proximity effect loss in the windings are also derived.

Question: How to calculate leakage inductance of a core-type transformer?


Small Discrete Fourier Transforms on GPUs. Efficient implementations of the Discrete Fourier Transform (DFT) for GPUs provide good performance with large data sizes, but are not competitive with CPU code for small data sizes. On the other hand, several applications perform multiple DFTs on small data sizes. In fact, even algorithms for large data sizes use a divide-and-conquer approach, where eventually small DFTs need to be performed. We discuss our DFT implementation, which is efficient for multiple small DFTs. One feature of our implementation is the use of the asymptotically slow matrix multiplication approach for small data sizes, which improves performance on the GPU due to its regular memory access and computational patterns. We combine this algorithm with the mixed radix algorithm for 1-D, 2-D, and 3-D complex DFTs. We also demonstrate the effect of different optimization techniques. When GPUs are used to accelerate a component of an application running on the host, it is important that decisions taken to optimize the GPU performance not affect the performance of the rest of the application on the host. One feature of our implementation is that we use a data layout that is not optimal for the GPU so that the overall effect on the application is better. Our implementation performs up to two orders of magnitude faster than cuFFT on an NVIDIA GeForce 9800 GTX GPU and up to one to two orders of magnitude faster than FFTW on a CPU for multiple small DFTs. Furthermore, we show that our implementation can accelerate the performance of a Quantum Monte Carlo application for which cuFFT is not effective. The primary contributions of this work lie in demonstrating the utility of the matrix multiplication approach and also in providing an implementation that is efficient for small DFTs when a GPU is used to accelerate an application running on the host.

Question: How to implement a discrete fourier transform on a GPU?


Prediction and Simulation of Human Mobility Following Natural Disasters. In recent decades, the frequency and intensity of natural disasters has increased significantly, and this trend is expected to continue. Therefore, understanding and predicting human behavior and mobility during a disaster will play a vital role in planning effective humanitarian relief, disaster management, and long-term societal reconstruction. However, such research is very difficult to perform owing to the uniqueness of various disasters and the unavailability of reliable and large-scale human mobility data. In this study, we collect big and heterogeneous data (e.g., GPS records of 1.6 million users1 over 3 years, data on earthquakes that have occurred in Japan over 4 years, news report data, and transportation network data) to study human mobility following natural disasters. An empirical analysis is conducted to explore the basic laws governing human mobility following disasters, and an effective human mobility model is developed to predict and simulate population movements. The experimental results demonstrate the efficiency of our model, and they suggest that human mobility following disasters can be significantly more predictable and be more easily simulated than previously thought.

Question: What is the difference between prediction and simulation?


Fashioning with Networks: Neural Style Transfer to Design Clothes. Convolutional Neural Networks have been highly successful in performing a host of computer vision tasks such as object recognition, object detection, image segmentation and texture synthesis. In 2015, Gatys et. al [7] show how the style of a painter can be extracted from an image of the painting and applied to another normal photograph, thus recreating the photo in the style of the painter. The method has been successfully applied to a wide range of images and has since spawned multiple applications and mobile apps. In this paper, the neural style transfer algorithm is applied to fashion so as to synthesize new custom clothes. We construct an approach to personalize and generate new custom clothes based on a user's preference and by learning the user's fashion choices from a limited set of clothes from their closet. The approach is evaluated by analyzing the generated images of clothes and how well they align with the user's fashion style.

Question: How to design clothes?


Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. While social media empowers freedom of expression and individual voices, it also enables anti-social behavior, online harassment, cyberbullying, and hate speech. In this paper, we deepen our understanding of online hate speech by focusing on a largely neglected but crucial aspect of hate speech – its target: either directed towards a specific person or entity, or generalized towards a group of people sharing a common protected characteristic. We perform the first linguistic and psycholinguistic analysis of these two forms of hate speech and reveal the presence of interesting markers that distinguish these types of hate speech. Our analysis reveals that Directed hate speech, in addition to being more personal and directed, is more informal, angrier, and often explicitly attacks the target (via name calling) with fewer analytic words and more words suggesting authority and influence. Generalized hate speech, on the other hand, is dominated by religious hate, is characterized by the use of lethal words such as murder, exterminate, and kill; and quantity words such as million and many. Altogether, our work provides a data-driven analysis of the nuances of online-hate speech that enables not only a deepened understanding of hate speech and its social implications, but also its detection.

Question: What is the difference between hate speech and hate speech?


Characterizing Taxi Flows in New York City. We present an analysis of taxi flows in Manhattan (NYC) using a variety of data mining approaches. The methods presented here can aid in development of representative and accurate models of large-scale traffic flows with applications to many areas, including outlier detection and characterization.

Question: What is a taxi flow?


Implementation of a fuzzy logic speed controller for a permanent magnet dc motor using a low-cost Arduino platform. Implementation of a Fuzzy Logic speed controller for a Permanent Magnet DC (PMDC) motor using a low-cost Arduino interfaced with a standard xPC Target MATLAB environment is demonstrated. The Arduino solution is acceptable at kHz sampling frequencies. The study of speed control of PMDC motor based on Arduino and L298N H-Bridge using an artificial intelligence control method, such as Fuzzy PID with only four rules, has been validated by experiments on the physical system.

Question: How to implement a fuzzy logic speed controller for a permanent magnet dc motor using a low-cost Arduino platform?


Stereo HDR Disparity Map Computation Using Structured Light. In this paper, we present work in progress towards the generation of a ground truth data set for High Dynamic Range (HDR) stereo matching. The development and evaluation of novel stereo matching algorithms that are tailored to the characteristics of HDR images would greatly benefit from the availability of such reference data. We describe our laboratory setup and processing steps for acquiring multi-exposed stereo images along with a corresponding reference disparity map computed by a structured light approach. We discuss the special requirements and challenges which HDR test scenes impose on the computation of the reference disparities and show some preliminary results.

Question: How to generate a ground truth data set for HDR stereo matching?


Web services and business process management. Web services based on the service-oriented architecture framework provide a suitable technical foundation for making business processes accessible within enterprises and across enterprises. But to appropriately support dynamic business processes and their management, more is needed, namely, the ability to prescribe how Web services are used to implement activities within a business process, how business processes are represented as Web services, and also which business partners perform what parts of the actual business process. In this paper, the relationship between Web services and the management of business processes is worked out and presented in a tutorial-like manner.

Question: What is the relationship between web services and business process management?


Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. This paper presents a variant of particle swarm optimizers (PSOs) that we call the comprehensive learning particle swarm optimizer (CLPSO), which uses a novel learning strategy whereby all other particles' historical best information is used to update a particle's velocity. This strategy enables the diversity of the swarm to be preserved to discourage premature convergence. Experiments were conducted (using codes available from http://www.ntu.edu.sg/home/epnsugan) on multimodal test functions such as Rosenbrock, Griewank, Rastrigin, Ackley, and Schwefel and composition functions both with and without coordinate rotation. The results demonstrate good performance of the CLPSO in solving multimodal problems when compared with eight other recent variants of the PSO.

Question: What is a particle swarm optimizer?


Li-Fi technology in traffic light. Wireless communication has become a basic utility in personal and business life such that it becomes a fundamental of our lives and this communication uses the radio spectrum for data transfer. There are issues in using the radio spectrum further, they are, capacity, efficiency, availability and security. The defects of Wi-Fi technology has given birth to the concept of Li-Fi (Light Fidelity) technology. Li-Fi can be defined as a light based Wi-Fi. This technology mainly serves the purpose of transmitting data using retrofitting of LED Bulbs that has high efficiency, durability and reliability.This technology emerged by 1990s in a lot of countries like Japan, German and Korea. The proposed paper aims in using the Wi-Fi technology and enabling communication of vehicles with the traffic light system in order to prioritize the vehicles and change the signals accordingly rather than by a process of pre-defined order or by manual order. Traffic lights already use LED lighting, so that this proposed system may seem easy to implement. Sending data through siren lights in an ambulance and fire extinguishers to a traffic light control system and switching the signal in order to allow faster and non-interrupted transport. Here is already a kind of system in play for GPS navigational systems, but the traffic lights can be used in updating drivers using basic information or streaming video directly from news broadcasts i.e, about the accidents or delays up ahead.

Question: What is the difference between Li-Fi and Wi-Fi?


Evolutionary timeline summarization: a balanced optimization framework via iterative substitution. Classic news summarization plays an important role with the exponential document growth on the Web. Many approaches are proposed to generate summaries but seldom simultaneously consider evolutionary characteristics of news plus to traditional summary elements. Therefore, we present a novel framework for the web mining problem named Evolutionary Timeline Summarization (ETS). Given the massive collection of time-stamped web documents related to a general news query, ETS aims to return the evolution trajectory along the timeline, consisting of individual but correlated summaries of each date, emphasizing relevance, coverage, coherence and cross-date diversity. ETS greatly facilitates fast news browsing and knowledge comprehension and hence is a necessity. We formally formulate the task as an optimization problem via iterative substitution from a set of sentences to a subset of sentences that satisfies the above requirements, balancing coherence/diversity measurement and local/global summary quality. The optimized substitution is iteratively conducted by incorporating several constraints until convergence. We develop experimental systems to evaluate on 6 instinctively different datasets which amount to 10251 documents. Performance comparisons between different system-generated timelines and manually created ones by human editors demonstrate the effectiveness of our proposed framework in terms of ROUGE metrics.

Question: What is the evolution timeline summarization?


Mining term association patterns from search logs for effective query reformulation. Search engine logs are an emerging new type of data that offers interesting opportunities for data mining. Existing work on mining such data has mostly attempted to discover knowledge at the level of queries (e.g., query clusters). In this paper, we propose to mine search engine logs for patterns at the level of terms through analyzing the relations of terms inside a query. We define two novel term association patterns (i.e., context-sensitive term substitutions and term additions) and propose new methods for mining such patterns from search engine logs. These two patterns can be used to address the mis-specification and under-specification problems of ineffective queries. Experiment results on real search engine logs show that the mined context-sensitive term substitutions can be used to effectively reword queries and improve their accuracy, while the mined context-sensitive term addition patterns can be used to support query refinement in a more effective way.

Question: What is the difference between mining term association patterns from search engine logs for effective query reformulation and mining term association patterns from search engine logs for effective query reformulation?


Comparative Study on Generative Adversarial Networks. In recent years, there have been tremendous advancements in the field of machine learning. These advancements have been made through both academic as well as industrial research. Lately, a fair amount of research has been dedicated to the usage of generative models in the field of computer vision and image classification. These generative models have been popularized through a new framework called Generative Adversarial Networks. Moreover, many modified versions of this framework have been proposed in the last two years. We study the original model proposed by Goodfellow et al. (2014) as well as modifications over the original model and provide a comparative analysis of these models.

Question: What is a generative adversarial network?


A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization. Text categorization has become a key research field in the NLP community. However, most works in this area are focused on Western languages ignoring other Semitic languages like Arabic. These languages are of immense political and social importance necessitating robust categorization techniques. In this paper, we present a novel three-stage technique to efficiently classify Arabic documents into different categories based on the words they contain. We leverage the significance of root-words in Arabic and incorporate a combination of Markov clustering and Deep Belief Networks to classify Arabic words into separate groups (clusters). Our approach is tested on two public datasets giving a F-Measure of 91.02%.

Question: What is the significance of root-words in Arabic?


Terahertz band communications: Applications, research challenges, and standardization activities. Terahertz frequency band, 0.1–10THz, is envisioned as one of the possible resources to be utilized for wireless communications in networks beyond 5G. Communications over this band will be feature a number of attractive properties, including potentially terabit-per-second link capacities, miniature transceivers and, potentially, high energy efficiency. Meanwhile, a number of specific research challenges have to be addressed to convert the theoretical estimations into commercially attractive solutions. Due to the diversity of the challenges, the research on THz communications at its early stages was mostly performed by independent communities from different areas. Therefore, the existing knowledge in the field is substantially fragmented. In this paper, an attempt to address this issue and provide a clear and easy to follow introduction to the THz communications is performed. A review on the state-of-the-art in THz communications research is given by identifying the target applications and major open research challenges as well as the recent achievements by industry, academia, and the standardization bodies. The potential of the THz communications is presented by illustrating the basic tradeoffs in typical use cases. Based on the given summary, certain prospective research directions in the field are identified.

Question: What is the terahertz band?


Object Detection with Active Sample Harvesting. The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between populations of samples. In practice, all the samples are not equally important: some examples are trivially classified and do not bring much to the training, while others close to the boundary or misclassified are the ones that truly matter. Similarly, images where the samples originate from are not all rich in informative samples. However, most training procedures select samples and images uniformly or weigh them equally. The common thread of this dissertation is how to efficiently find the informative samples/images for training. Although we never consider all the possible samples "in the world", our purpose is to select the samples in a smarter manner, without looking at all the available ones. The framework adopted in this work consists in organising the data (samples or images) in a tree to reflect the statistical regularities of the training samples, by putting "similar" samples in the same branch. Each leaf carries a sample and a weight related to the "importance" of the corresponding sample, and each internal node carries statistics about the weights below. The tree is used to select the next sample/image for training, by applying a sampling policy, and the "importance" weights are updated accordingly, to bias the sampling towards informative samples/images in future iterations. Our experiments show that, in the various applications, properly focusing on informative images or informative samples improves the learning phase by either reaching better performances faster or by reducing the training loss faster.

Question: What is the difference between a tree and a graph?


Polarization imaging reflectometry in the wild. We present a novel approach for on-site acquisition of surface reflectance for planar, spatially varying, isotropic samples in uncontrolled outdoor environments. Our method exploits the naturally occurring linear polarization of incident and reflected illumination for this purpose. By rotating a linear polarizing filter in front of a camera at three different orientations, we measure the polarization reflected off the sample and combine this information with multi-view analysis and inverse rendering in order to recover per-pixel, high resolution reflectance and surface normal maps. Specifically, we employ polarization imaging from two near orthogonal views close to the Brewster angle of incidence in order to maximize polarization cues for surface reflectance estimation. To the best of our knowledge, our method is the first to successfully extract a complete set of reflectance parameters with passive capture in completely uncontrolled outdoor settings. To this end, we analyze our approach under the general, but previously unstudied, case of incident partial linear polarization (due to the sky) in order to identify the strengths and weaknesses of the method under various outdoor conditions. We provide practical guidelines for on-site acquisition based on our analysis, and demonstrate high quality results with an entry level DSLR as well as a mobile phone.

Question: How to measure polarization in the wild?


Wafer-scale VLSI implementations of pulse coupled neural networks. In this paper, we present a system architecture currently under development that will allow very large (>10 neurons, >10 synapses) reconfigurable networks to be built, in the form of interlinked dies on a single wafer. Reconfigurable routing and complex adaptation/plasticity across several timescales in neurons and synapses allow for the implementation of large-scale biologically realistic neuronal networks and behaviors. Compared to biology the network dynamics will be about 10 to 10 times faster, so that developmental plasticity can be studied in detail. Keywords—neural VLSI hardware, system simulation, mapping algorithms, parallelization.

Question: What is the size of a wafer?


The real-time video stabilization for the rescue robot. When rescue robots navigate in a rough terrain, significant vibration of the video occurs unavoidably and a video stabilization system is proposed in this paper to reduce the disturbance on the visual system of the present rescue robots. The Kalman filter is applied to estimate the motion vector of the robot and the false estimation occurrence can be thus greatly reduced by applying analysis of correlation and variance of the motion vector estimation. With a hierarchical searching algorithm implemented on the TI DSP 6437, the frame rate can be improved from 10 fps to 28 fps to realize the real-time video stabilization and furthermore, the cooperative mission of multiple rescue robots has been achieved by applying the developed visual servo technique. The proposed virtual bounded motion control algorithm further leads the robots approaching the target precisely with cooperation of multiple rescue robots. The demo video is available at: http://lab816.cn.nctu.edu.tw/DemoVideo/. video stabilization

Question: How to stabilize a video?


Morsel-driven parallelism: a NUMA-aware query evaluation framework for the many-core age. With modern computer architecture evolving, two problems conspire against the state-of-the-art approaches in parallel query execution: (i) to take advantage of many-cores, all query work must be distributed evenly among (soon) hundreds of threads in order to achieve good speedup, yet (ii) dividing the work evenly is difficult even with accurate data statistics due to the complexity of modern out-of-order cores. As a result, the existing approaches for plan-driven parallelism run into load balancing and context-switching bottlenecks, and therefore no longer scale. A third problem faced by many-core architectures is the decentralization of memory controllers, which leads to Non-Uniform Memory Access (NUMA). In response, we present the morsel-driven query execution framework, where scheduling becomes a fine-grained run-time task that is NUMA-aware. Morsel-driven query processing takes small fragments of input data (morsels) and schedules these to worker threads that run entire operator pipelines until the next pipeline breaker. The degree of parallelism is not baked into the plan but can elastically change during query execution, so the dispatcher can react to execution speed of different morsels but also adjust resources dynamically in response to newly arriving queries in the workload. Further, the dispatcher is aware of data locality of the NUMA-local morsels and operator state, such that the great majority of executions takes place on NUMA-local memory. Our evaluation on the TPC-H and SSB benchmarks shows extremely high absolute performance and an average speedup of over 30 with 32 cores.

Question: What is the average speedup of the morsel-driven framework?


Spatial Transformer Networks. Convolutional Neural Networks define an exceptionally powerful class of models, but are still limited by the lack of ability to be spatially invariant to the input data in a computationally and parameter efficient manner. In this work we introduce a new learnable module, the Spatial Transformer, which explicitly allows the spatial manipulation of data within the network. This differentiable module can be inserted into existing convolutional architectures, giving neural networks the ability to actively spatially transform feature maps, conditional on the feature map itself, without any extra training supervision or modification to the optimisation process. We show that the use of spatial transformers results in models which learn invariance to translation, scale, rotation and more generic warping, resulting in state-of-the-art performance on several benchmarks, and for a number of classes of transformations.

Question: What is a convolutional neural network?


Weaknesses in the Key Scheduling Algorithm of RC4. In this paper we present several weaknesses in the key scheduling algorithm of RC4, and describe their cryptanalytic signi cance. We identify a large number of weak keys, in which knowledge of a small number of key bits su ces to determine many state and output bits with non-negligible probability. We use these weak keys to construct new distinguishers for RC4, and to mount related key attacks with practical complexities. Finally, we show that RC4 is completely insecure in a common mode of operation which is used in the widely deployed Wired Equivalent Privacy protocol (WEP, which is part of the 802.11 standard), in which a xed secret key is concatenated with known IV modi ers in order to encrypt di erent messages. Our new passive ciphertext-only attack on this mode can recover an arbitrarily long key in a negligible amount of time which grows only linearly with its size, both for 24 and 128 bit IV modi ers.

Question: What is the weakness in the key scheduling algorithm of RC4?


Physical experience enhances science learning.. Three laboratory experiments involving students' behavior and brain imaging and one randomized field experiment in a college physics class explored the importance of physical experience in science learning. We reasoned that students' understanding of science concepts such as torque and angular momentum is aided by activation of sensorimotor brain systems that add kinetic detail and meaning to students' thinking. We tested whether physical experience with angular momentum increases involvement of sensorimotor brain systems during students' subsequent reasoning and whether this involvement aids their understanding. The physical experience, a brief exposure to forces associated with angular momentum, significantly improved quiz scores. Moreover, improved performance was explained by activation of sensorimotor brain regions when students later reasoned about angular momentum. This finding specifies a mechanism underlying the value of physical experience in science education and leads the way for classroom practices in which experience with the physical world is an integral part of learning.

Question: How does physical experience enhance science learning?


A Survey of Augmented Reality. This paper surveys the field of augmented reality (AR), in which 3D virtual objects are integrated into a 3D real environment in real time. It describes the medical, manufacturing, visualization, path planning, entertainment, and military applications that have been explored. This paper describes the characteristics of augmented reality systems, including a detailed discussion of the tradeoffs between optical and video blending approaches. Registration and sensing errors are two of the biggest problems in building effective augmented reality systems, so this paper summarizes current efforts to overcome these problems. Future directions and areas requiring further research are discussed. This survey provides a starting point for anyone interested in researching or using augmented reality.

Question: What is augmented reality?


Design of fully printable chipless RFID tag on flexible substrate for secure banknote applications. A fully printable, passive and planar chipless RFID tag on thin flexible substrate is presented. The chipless tag encodes data into the spectral signature using a multiresonating circuit. Both amplitude and phase components of the spectral signature are used for data encoding. The tag comprises of a microstrip multiresonating circuit with 6 multi-spiral resonators and two cross-polarized UWB disc loaded monopole transmitting and receiving antennas. The chipless tag is designed to be printed on the Australian banknote and provide an extra layer of security against counterfeiting.

Question: What is a chipless RFID tag?


Scene Text Localization and Recognition with Oriented Stroke Detection. An unconstrained end-to-end text localization and recognition method is presented. The method introduces a novel approach for character detection and recognition which combines the advantages of sliding-window and connected component methods. Characters are detected and recognized as image regions which contain strokes of specific orientations in a specific relative position, where the strokes are efficiently detected by convolving the image gradient field with a set of oriented bar filters. Additionally, a novel character representation efficiently calculated from the values obtained in the stroke detection phase is introduced. The representation is robust to shift at the stroke level, which makes it less sensitive to intra-class variations and the noise induced by normalizing character size and positioning. The effectiveness of the representation is demonstrated by the results achieved in the classification of real-world characters using an euclidian nearest-neighbor classifier trained on synthetic data in a plain form. The method was evaluated on a standard dataset, where it achieves state-of-the-art results in both text localization and recognition.

Question: What is the nearest neighbor classifier?


HUmanoid Robotic Leg via pneumatic muscle actuators : implementation and control. In this article, a HUmanoid Robotic Leg (HURL) via the utilization of pneumatic muscle actuators (PMAs) is presented. PMAs are a pneumatic form of actuation possessing crucial attributes for the implementation of a design that mimics the motion characteristics of a human ankle. HURL acts as a feasibility study in the conceptual goal of developing a 10 degree-of-freedom (DoF) lower-limb humanoid for compliance and postural control, while serving as a knowledge basis for its future alternative use in prosthetic robotics. HURL's design properties are described in detail, while its 2-DoF motion capabilities (dorsiflexion–plantar flexion, eversion–inversion) are experimentally evaluated via an advanced nonlinear PID-based control algorithm.

Question: What is a pneumatic muscle actuator?


Face to Face Collaborative AR on Mobile Phones. Mobile phones are an ideal platform for augmented reality. In this paper we describe how they can also be used to support face to face collaborative AR gaming. We have created a custom port of the ARToolKit library to the Symbian mobile phone operating system and then developed a sample collaborative AR game based on this. We describe the game in detail and user feedback from people who have played the game. We also provide general design guidelines that could be useful for others who are developing mobile phone collaborative AR applications.

Question: What is a collaborative AR game?


Survey of Consistent Network Updates. Computer networks have become a critical infrastructure. As such, networks should not only meet strict requirements in terms of correctness, availability, and performance, but they should also be very flexible and support fast updates, e.g., due to a change in the security policy, increasing traffic, or failures. In this paper, we present a structured survey of mechanisms and protocols to update computer networks in a fast and consistent manner. In particular, we identify and discuss the different desirable consistency properties that should be provided throughout a network update, the algorithmic techniques which are needed to meet these consistency properties, and the implications on the speed and costs at which updates can be performed. We also explain the relationship between consistent network update problems and classic algorithmic optimization ones. While our survey is mainly motivated by the advent of Software-Defined Networks (SDNs) and their primary need for correct and efficient update techniques, the fundamental underlying problems are not new, and we provide a historical perspective of the subject as well. CCS Concepts: rGeneral and reference → Surveys and overviews; rNetworks → Network algorithms; rComputer systems organization→ Distributed architectures;

Question: What is the difference between a network and a computer system?


CBR: Strengths and Weaknesses. There is considerable enthusiasm about Case-Based Reasoning as a means of developing knowledge-based systems. There are two broad reasons for this enthusiasm. First, it is evident that much of human expert competence is experience based and it makes sense to adopt a reuse-based methodology for developing knowledge based systems. The other reason is the expectation that using Case-Based Reasoning to develop knowledge based systems will i nvolve less knowledge engineering than alternative ' first-principles' based approaches. In this paper I explore the veracity of this assertion and outline the types of situation in which it will be true. CBR is perceived to have this knowledge engineering advantage because it allows the development of knowledge based systems in weak theory domains. If CBR can work without formalising a domain theory then there is a question about the quality of solutions produced by case-based systems. This is the other issue discussed in this paper and situations where CBR will and will not produce good quality solutions are outlined.

Question: What is the difference between a knowledge-based system and a case-based system?


Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user comprehensibility of the results, non-presumption of any canonical data distribution, and insensitivity to the order of input records. We present CLIQUE, a clustering algorithm that satisfies each of these requirements. CLIQUE identifies dense clusters in subspaces of maximum dimensionality. It generates cluster descriptions in the form of DNF expressions that are minimized for ease of comprehension. It produces identical results irrespective of the order in which input records are presented and does not presume any specific mathematical form for data distribution. Through experiments, we show that CLIQUE efficiently finds accurate cluster in large high dimensional datasets.

Question: What is a clustering algorithm?


Timing to Perfection: The Biology of Central and Peripheral Circadian Clocks. The mammalian circadian system, which is comprised of multiple cellular clocks located in the organs and tissues, orchestrates their regulation in a hierarchical manner throughout the 24 hr of the day. At the top of the hierarchy are the suprachiasmatic nuclei, which synchronize subordinate organ and tissue clocks using electrical, endocrine, and metabolic signaling pathways that impact the molecular mechanisms of cellular clocks. The interplay between the central neural and peripheral tissue clocks is not fully understood and remains a major challenge in determining how neurological and metabolic homeostasis is achieved across the sleep-wake cycle. Disturbances in the communication between the plethora of body clocks can desynchronize the circadian system, which is believed to contribute to the development of diseases such as obesity and neuropsychiatric disorders. This review will highlight the relationship between clocks and metabolism, and describe how cues such as light, food, and reward mediate entrainment of the circadian system.

Question: What is the relationship between the circadian system and metabolism?


Static and dynamic 3D facial expression recognition: A comprehensive survey. a r t i c l e i n f o Keywords: Facial behaviour analysis Facial expression recognition 3D facial surface 3D facial surface sequences (4D faces) Automatic facial expression recognition constitutes an active research field due to the latest advances in computing technology that make the user's experience a clear priority. The majority of work conducted in this area involves 2D imagery, despite the problems this presents due to inherent pose and illumination variations. In order to deal with these problems, 3D and 4D (dynamic 3D) recordings are increasingly used in expression analysis research. In this paper we survey the recent advances in 3D and 4D facial expression recognition. We discuss developments in 3D facial data acquisition and tracking, and present currently available 3D/4D face databases suitable for 3D/4D facial expressions analysis as well as the existing facial expression recognition systems that exploit either 3D or 4D data in detail. Finally, challenges that have to be addressed if 3D facial expression recognition systems are to become a part of future applications are extensively discussed. Automatic human behaviour understanding has attracted a great deal of interest over the past two decades, mainly because of its many applications spanning various fields such as psychology, computer technology , medicine and security. It can be regarded as the essence of next-generation computing systems as it plays a crucial role in affective computing technologies (i.e. proactive and affective user interfaces), learner-adaptive tutoring systems, patient-profiled personal wellbeing technologies, etc. [1]. Facial expression is the most cogent, naturally preeminent means for humans to communicate emotions, to clarify and give emphasis, to signal comprehension disagreement, to express intentions and, more generally, to regulate interactions with the environment and other people [2]. These f

Question: What is the difference between facial expression and facial behaviour?


A Comprehensive Data Quality Methodology for Web and Structured Data. Measuring and improving data quality in an organization or in a group of interacting organizations is a complex task. Several methodologies have been developed in the past providing a basis for the definition of a complete data quality program applying assessment and improvement techniques in order to guarantee high data quality levels. Since the main limitation of existing approaches is their specialization on specific issues or contexts, this paper presents the comprehensive data quality (CDQ) methodology that aims at integrating and enhancing the phases, techniques and tools proposed by previous approaches. CDQ methodology is conceived to be at the same time complete, flexible and simple to apply. Completeness is achieved by considering existing techniques and tools and integrating them in a framework that can work in both intra and inter organizational contexts, and can be applied to all types of data. The methodology is flexible since it supports the user in the selection of the most suitable techniques and tools within each phase and in any context. Finally, CDQ is simple since it is organized in phases and each phase is characterized by a specific goal and techniques to apply. The methodology is explained by means of a running example.

Question: What is a comprehensive data quality methodology?


Adaptive Parser-Centric Text Normalization. Text normalization is an important first step towards enabling many Natural Language Processing (NLP) tasks over informal text. While many of these tasks, such as parsing, perform the best over fully grammatically correct text, most existing text normalization approaches narrowly define the task in the word-to-word sense; that is, the task is seen as that of mapping all out-of-vocabulary non-standard words to their in-vocabulary standard forms. In this paper, we take a parser-centric view of normalization that aims to convert raw informal text into grammatically correct text. To understand the real effect of normalization on the parser, we tie normalization performance directly to parser performance. Additionally, we design a customizable framework to address the often overlooked concept of domain adaptability, and illustrate that the system allows for transfer to new domains with a minimal amount of data and effort. Our experimental study over datasets from three domains demonstrates that our approach outperforms not only the state-of-the-art wordto-word normalization techniques, but also manual word-to-word annotations.

Question: What is the difference between a parser and a normalizer?


A Multi-ESD-Path Low-Noise Amplifier With a 4.3-A TLP Current Level in 65-nm CMOS. This paper studies the electrostatic discharge (ESD)-protected RF low-noise amplifiers (LNAs) in 65-nm CMOS technology. Three different ESD designs, including double-diode, modified silicon-controlled rectifier (SCR), and modified-SCR with double-diode configurations, are employed to realize ESD-protected LNAs at 5.8 GHz. By using the modified-SCR in conjunction with double-diode, a 5.8-GHz LNA with multiple ESD current paths demonstrates a 4.3-A transmission line pulse (TLP) failure level, corresponding to a ~ 6.5-kV Human-Body-Mode (HBM) ESD protection level. Under a supply voltage of 1.2 V and a drain current of 6.5 mA, the proposed ESD-protected LNA demonstrates a noise figure of 2.57 dB with an associated power gain of 16.7 dB. The input third-order intercept point (IIP3) is - 11 dBm, the input and output return losses are greater than 15.9 and 20 dB, respectively.

Question: What is the noise figure of a LNA?


Question: What is the name of the book?


Content Centric Networking in tactical and emergency MANETs. Reliable and secure content distribution in a disruptive environment is a critical challenge due to high mobile and lossy channels. Traditional IP networking and wireless protocols tend to perform poorly. In this paper, we propose Content Centric Networking (CCN) for emergency wireless ad hoc environments. CCN is a novel communication architecture capable to access and retrieve content by name. This new approach achieves scalability, security, and efficient network resource management in large scale disaster recovery and battlefield networks. Existing Internet CCN schemes cannot be directly applied to wireless mobile ad hoc networks due to different environments and specific limitations. Thus, we must extend the CCN architecture by introducing features and requirements especially designed for disruptive networks. We prove feasibility and performance gain of the new design via implementation and experimentation.

Question: What is a disruptive environment?


IoT security: A layered approach for attacks & defenses. Internet of Things (IoT) has been a massive advancement in the Information and Communication Technology (ICT). It is projected that over 50 billion devices will become part of the IoT in the next few years. Security of the IoT network should be the foremost priority. In this paper, we evaluate the security challenges in the four layers of the IoT architecture and their solutions proposed from 2010 to 2016. Furthermore, important security technologies like encryption are also analyzed in the IoT context. Finally, we discuss countermeasures of the security attacks on different layers of IoT and highlight the future research directions within the IoT architecture.

Question: What is the future of IoT?


The Sensemaking-Coevolution-Implementation Theory of software design. Understanding software design practice is critical to understanding modern information systems development. New developments in empirical software engineering, information systems design science and the interdisciplinary design literature combined with recent advances in process theory and testability have created a situation ripe for innovation. Consequently, this paper utilizes these breakthroughs to formulate a process theory of software design practice: SensemakingCoevolution-Implementation Theory explains how complex software systems are created by collocated software development teams in organizations. It posits that an independent agent (design team) creates a software system by alternating between three activities: organizing their perceptions about the context, mutually refining their understandings of the context and design space, and manifesting their understanding of the design space in a technological artifact. This theory development paper defines and illustrates Sensemaking-Coevolution-Implementation Theory, grounds its concepts and relationships in existing literature, conceptually evaluates the theory and situates it in the broader context of information systems development.

Question: What is the sensemaking-coevolution-implementation theory of software design?


Conjunctive representation of position, direction, and velocity in entorhinal cortex.. Grid cells in the medial entorhinal cortex (MEC) are part of an environment-independent spatial coordinate system. To determine how information about location, direction, and distance is integrated in the grid-cell network, we recorded from each principal cell layer of MEC in rats that explored two-dimensional environments. Whereas layer II was predominated by grid cells, grid cells colocalized with head-direction cells and conjunctive grid x head-direction cells in the deeper layers. All cell types were modulated by running speed. The conjunction of positional, directional, and translational information in a single MEC cell type may enable grid coordinates to be updated during self-motion-based navigation.

Question: How do grid cells work?


Efficiently indexing shortest paths by exploiting symmetry in graphs. Shortest path queries (SPQ) are essential in many graph analysis and mining tasks. However, answering shortest path queries on-the-fly on large graphs is costly. To online answer shortest path queries, we may materialize and index shortest paths. However, a straightforward index of all shortest paths in a graph of N vertices takes O(N2) space. In this paper, we tackle the problem of indexing shortest paths and online answering shortest path queries. As many large real graphs are shown richly symmetric, the central idea of our approach is to use graph symmetry to reduce the index size while retaining the correctness and the efficiency of shortest path query answering. Technically, we develop a framework to index a large graph at the orbit level instead of the vertex level so that the number of breadth-first search trees materialized is reduced from O(N) to O(|Δ|), where |Δ| ≤ N is the number of orbits in the graph. We explore orbit adjacency and local symmetry to obtain compact breadth-first-search trees (compact BFS-trees). An extensive empirical study using both synthetic data and real data shows that compact BFS-trees can be built efficiently and the space cost can be reduced substantially. Moreover, online shortest path query answering can be achieved using compact BFS-trees.

Question: How to efficiently index shortest paths?


The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation.

Question: What is the nature and role of feedback text comments in online marketplaces?


The contribution of sleep to hippocampus-dependent memory consolidation. There is now compelling evidence that sleep promotes the long-term consolidation of declarative and procedural memories. Behavioral studies suggest that sleep preferentially consolidates explicit aspects of these memories, which during encoding are possibly associated with activation in prefrontal-hippocampal circuitry. Hippocampus-dependent declarative memory benefits particularly from slow-wave sleep (SWS), whereas rapid-eye-movement (REM) sleep seems to benefit procedural aspects of memory. Consolidation of hippocampus-dependent memories relies on a dialog between the neocortex and hippocampus. Crucial features of this dialog are the neuronal reactivation of new memories in the hippocampus during SWS, which stimulates the redistribution of memory representations to neocortical networks; and the neocortical slow (<1Hz) oscillation that synchronizes hippocampal-to-neocortical information transfer to activity in other brain structures.

Question: What is the contribution of sleep to hippocampus-dependent memory consolidation?


Filter technologies for wireless base stations. Phenomenal growth in the telecommunication industry in recent years has brought significant advances in filter technology as new communication systems emerged, demanding more stringent filter characteristics. In particular, the growth of the wireless communication industry has spurred tremendous activity in the area of microwave filter miniaturization and has been responsible for many advances made in this field. The filters that are currently being used in wireless base stations can be divided into two main categories: coaxial cavity resonator filters and dielectric resonator (DR) filters. While coaxial cavity filters have limited quality factor (Q) values, they offer the lowest cost design and are still being widely employed, particularly in wide bandwidth applications. With increased demands for high performance wireless systems, dielectric resonator filters are emerging as the baseline design for wireless base stations. Over the next five years, dielectric resonator filters are expected to have a significant share of the overall wireless base station filter market. High-temperature superconductor (HTS) filters are also expected to have a share of this market, particularly for systems, which have very stringent requirements for out-of-band interference. In this article, we begin by reviewing the main filter requirements, highlighting the technologies that are being currently employed. Emerging filter technologies that have the potential to replace the existing technologies are then described.

Question: What technologies are being used in wireless base stations?


Low-Power High-Efficiency Class D Audio Power Amplifiers. The architecture, design, and implementation of two clock-free analog class D audio power amplifiers using 0.5 ¿m CMOS standard technology are introduced. The amplifiers are designed to consume significantly less power than former implementations. Both designs operate with a 2.7 V single voltage supply and deliver a maximum output power of 250 mW into an 8 ¿ speaker. The two class-D amplifiers are based on a hysteretic sliding mode controller, which avoids the complex task of generating the highly linear triangle carrier signal used in conventional architectures. The first design generates a two-level modulated signal, known as binary modulated amplifier (BMA); the second topology implements a three-level modulated signal, also called ternary modulated amplifier (TMA). The architectures and implementations are simple and compact, providing very low quiescent power consumption. Experimental results of the BMA/TMA yield an efficiency of 89/90% and a total harmonic distortion plus noise (THD+N) of 0.02/0.03%, respectively. The efficiency and linearity is comparable to state-of-the-art amplifiers but the static power consumption is less than one tenth of previous proposed architectures. Both class D amplifiers achieve a power supply rejection ratio greater than 75 dB at 217 Hz, and a signal-to-noise ratio (SNR) higher than 90 dB within the whole audio band. Each amplifier occupies less than 1.5 mm2.

Question: What is the difference between binary and ternary modulation?


KEEL: a software tool to assess evolutionary algorithms for data mining problems. This paper introduces a software tool named KEEL, which is a software tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based on different approaches: Pittsburgh, Michigan and IRL, as well as the integration of evolutionary learning techniques with different pre-processing techniques, allowing it to perform a complete analysis of any learning model in comparison to existing software tools. Moreover, KEEL has been designed with a double goal: research and educational.

Question: What is the name of the software tool?


Noise adaptive soft-switching median filter. Existing state-of-the-art switching-based median filters are commonly found to be nonadaptive to noise density variations and prone to misclassifying pixel characteristics at high noise density interference. This reveals the critical need of having a sophisticated switching scheme and an adaptive weighted median filter. We propose a novel switching-based median filter with incorporation of fuzzy-set concept, called the noise adaptive soft-switching median (NASM) filter, to achieve much improved filtering performance in terms of effectiveness in removing impulse noise while preserving signal details and robustness in combating noise density variations. The proposed NASM filter consists of two stages. A soft-switching noise-detection scheme is developed to classify each pixel to be uncorrupted pixel, isolated impulse noise, nonisolated impulse noise or image object's edge pixel. "No filtering" (or identity filter), standard median (SM) filter or our developed fuzzy weighted median (FWM) filter will then be employed according to the respective characteristic type identified. Experimental results show that our NASM filter impressively outperforms other techniques by achieving fairly close performance to that of ideal-switching median filter across a wide range of noise densities, ranging from 10% to 70%

Question: What is the noise adaptive soft-switching median filter?


KP-Miner: A keyphrase extraction system for English and Arabic documents. Automatic key phrase extraction has many important applications including but not limited to summarization, cataloging/indexing, feature extraction for clustering and classification, and data mining. This paper presents the KP-Miner system, and demonstrates through experimentation and comparison with existing systems that the it is effective in extracting keyphrases from both English and Arabic documents of varied length. Unlike other existing keyphrase extraction systems, the KP-Miner system has the advantage of being configurable as the rules and heuristics adopted by the system are related to the general nature of documents and keyphrase. This implies that the users of this system can use their understanding of the document(s) being input into the system, to fine tune it to their particular needs.

Question: What is a keyphrase extraction system?


A conceptual model of client-driven agile requirements prioritization: results of a case study. Requirements (re)prioritization is an essential mechanism of agile development approaches to maximize the value for the clients and to accommodate changing requirements. Yet, in the agile Requirements Engineering (RE) literature, very little is known about how agile (re)prioritization happens in practice. Conceptual models about this process are missing, which, in turn, makes it difficult for both practitioners and researchers to reason about requirements decision-making at inter-iteration time. We did a multiple case study on agile requirements prioritization methods to yield a conceptual model for understanding the inter-iteration prioritization process. The model is derived by using interview data from practitioners in 8 development organizations. Such a model makes explicit the concepts that are used tacitly in the agile requirements prioritization practice and can be used for structuring future empirical investigations about this topic, and for analyzing, supporting, and improving the process in real-life projects.

Question: What is a conceptual model?


Contributions of the prefrontal cortex to the neural basis of human decision making. The neural basis of decision making has been an elusive concept largely due to the many subprocesses associated with it. Recent efforts involving neuroimaging, neuropsychological studies, and animal work indicate that the prefrontal cortex plays a central role in several of these subprocesses. The frontal lobes are involved in tasks ranging from making binary choices to making multi-attribute decisions that require explicit deliberation and integration of diverse sources of information. In categorizing different aspects of decision making, a division of the prefrontal cortex into three primary regions is proposed. (1) The orbitofrontal and ventromedial areas are most relevant to deciding based on reward values and contribute affective information regarding decision attributes and options. (2) Dorsolateral prefrontal cortex is critical in making decisions that call for the consideration of multiple sources of information, and may recruit separable areas when making well defined versus poorly defined decisions. (3) The anterior and ventral cingulate cortex appear especially relevant in sorting among conflicting options, as well as signaling outcome-relevant information. This topic is broadly relevant to cognitive neuroscience as a discipline, as it generally comprises several aspects of cognition and may involve numerous brain regions depending on the situation. The review concludes with a summary of how these regions may interact in deciding and possible future research directions for the field.

Question: What is the neural basis of decision making?


POSTER: Watch Out Your Smart Watch When Paired. We coin a new term called \textit{data transfusion} as a phenomenon that a user experiences when pairing a wearable device with the host device. A large amount of data stored in the host device (e.g., a smartphone) is forcibly copied to the wearable device (e.g., a smart watch) due to pairing while the wearable device is usually less attended. To the best of knowledge, there is no previous work that manipulates how sensitive data is transfused even without user's consent and how users perceive and behave regarding such a phenomenon for smart watches. We tackle this problem by conducting an experimental study of data extraction from commodity devices, such as in Android Wear, watchOS, and Tizen platforms, and a following survey study with 205 smart watch users, in two folds. The experimental studies have shown that a large amount of sensitive data was transfused, but there was not enough user notification. The survey results have shown that users have lower perception on smart watches for security and privacy than smartphones, but they tend to set the same passcode on both devices when needed. Based on the results, we perform risk assessment and discuss possible mitigation that involves volatile transfusion.

Question: What is the difference between data transfusion and data extraction?


The BOBYQA algorithm for bound constrained optimization without derivatives. BOBYQA is an iterative algorithm for finding a minimum of a function F (x), x∈R, subject to bounds a≤x≤b on the variables, F being specified by a "black box" that returns the value F (x) for any feasible x. Each iteration employs a quadratic approximation Q to F that satisfies Q(y j ) = F (y j ), j = 1, 2, . . . , m, the interpolation points y j being chosen and adjusted automatically, but m is a prescribed constant, the value m= 2n+1 being typical. These conditions leave much freedom in Q, taken up when the model is updated by the highly successful technique of minimizing the Frobenius norm of the change to the second derivative matrix of Q. Thus no first derivatives of F are required explicitly. Most changes to the variables are an approximate solution to a trust region subproblem, using the current quadratic model, with a lower bound on the trust region radius that is reduced cautiously, in order to keep the interpolation points well separated until late in the calculation, which lessens damage from computer rounding errors. Some other changes to the variables are designed to improve the model without reducing F . These techniques are described. Other topics include the starting procedure that is given an initial vector of variables, the value of m and the initial trust region radius. There is also a new device called RESCUE that tries to restore normality if severe loss of accuracy occurs in the matrix calculations of the updating of the model. Numerical results are reported and discussed for two test problems, the numbers of variables being between 10 and 320. Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, England.

Question: What is the name of the algorithm?


Efficient Object Category Recognition Using Classemes. We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the output of a large number of weakly trained object category classifiers on the image. The trained categories are selected from an ontology of visual concepts, but the intention is not to encode an explicit decomposition of the scene. Rather, we accept that existing object category classifiers often encode not the category per se but ancillary image characteristics; and that these ancillary characteristics can combine to represent visual classes unrelated to the constituent categories' semantic meanings. The advantage of this descriptor is that it allows object-category queries to be made against image databases using efficient classifiers (efficient at test time) such as linear support vector machines, and allows these queries to be for novel categories. Even when the representation is reduced to 200 bytes per image, classification accuracy on object category recognition is comparable with the state of the art (36% versus 42%), but at orders of magnitude lower computational cost.

Question: What is the state of the art in object category recognition?


Ground-Penetrating Radar Theory and Application of Thin-Bed Offset-Dependent Reflectivity. Offset-dependent reflectivity or amplitude-variationwith-offset AVO analysis of ground-penetrating radar GPR data may improve the resolution of subsurface dielectric permittivity estimates. A horizontally stratified medium has a limiting layer thickness below which thin-bed AVO analysis is necessary. For a typical GPR signal, this limit is approximately 0.75 of the characteristic wavelength of the signal. Our approach to modeling the GPR thin-bed response is a broadband, frequency-dependent computation that utilizes an analytical solution to the three-interface reflectivity and is easy to implement for either transverse electric TE or transverse magnetic TM polarizations. The AVO curves for TE and TM modes differ significantly. In some cases, constraining the interpretation using both TE and TM data is critical. In two field examples taken from contaminated-site characterization data, we find quantitative thin-bed modeling agrees with the GPR field data and available characterization data.

Question: How do you model the thin-bed response of a GPR signal?


Efficient Hierarchical Identity-Based Signature With Batch Verification for Automatic Dependent Surveillance-Broadcast System. The automatic-dependent surveillance-broad-cast (ADS-B) is generally regarded as the most important module in air traffic surveillance technology. To obtain better airline security, ADS-B system will be deployed in most airspace by 2020, where aircraft will be equipped with an ADS-B device that periodically broadcasts messages to other aircraft and ground station controllers. Due to the open communication environment, the ADS-B system is subject to a broad range of attacks. To simultaneously implement both integrity and authenticity of messages transmitted in the ADS-B system, Yang et al. proposed a new authentication frame based on the three-level hierarchical identity-based signature (TLHIBS) scheme with batch verification, as well as constructing two schemes for the ADS-B system. However, neither TLHIBS schemes are sufficiently lightweight for practical deployment due to the need for complex hash-to-point operation or expensive certification management. In this paper, we construct an efficient TLHIBS scheme with batch verification for the ADS-B system. Our scheme does not require hash-to-point operation or (expensive) certification management. We then prove the TLHIBS scheme secure in the random oracle model. We also demonstrate the practicality of the scheme using experiments, whose findings indicate that the TLHIBS scheme supports attributes required by the ADS-B system without the computation cost in Chow et al.'s scheme and Yang et al.'s TLHIBS schemes.

Question: What is the ADS-B system?


Bidding algorithms for simultaneous auctions. This paper introduces RoxyBot, one of the top-scoring agents in the First International Trading Agent Competition. A TAC agent simulates one vision of future travel agents: it represents a set of clients in simultaneous auctions, trading complementary (e.g., airline tickets and hotel reservations) and substitutable (e.g., symphony and theater tickets) goods. RoxyBot faced two key technical challenges in TAC: (i) allocation---assigning purchased goods to clients at the end of a game instance so as to maximize total client utility, and (ii) completion---determining the optimal quantity of each resource to buy and sell given client preferences, current holdings, and market prices. For the dimensions of TAC, an optimal solution to the allocation problem is tractable, and RoxyBot uses a search algorithm based on A* to produce optimal allocations. An optimal solution to the completion problem is also tractable, but in the interest of minimizing bidding cycle time, RoxyBot solves the completion problem using beam search, producing approximately optimal completions. RoxyBot's completer relies on an innovative data structure called a priceline.

Question: What is a priceline?


Towards a questionnaire for measuring affective benefits and costs of communication technologies. As CSCW creates and investigates technologies for social communication, it is important to understand the emotional benefits and costs of these systems. We propose the Affec-tive Benefits and Costs of Communication Technologies (ABCCT) questionnaire to supplement traditional qualita-tive methods of understanding communication media. We discuss the pilots of this survey with 45 children and 110 adults measuring the inter-item reliability of this instru-ment. We present the results of interviews with 14 children and 14 adults, which help confirm that the ABCCT measures the same constructs that may emerge through interview investigations. Finally, we demonstrate that the ABCCT is sensitive enough to discriminate between differ-ent communication technologies and has shown promise in some of its early adoption. Though the ABCCT is not with-out limitations, it may provide a way to compare technolo-gies in field deployments, draw findings across investiga-tions, and quantify the impact of specific design decisions.

Question: What is the purpose of the ABCCT?


An energy-efficient unequal clustering mechanism for wireless sensor networks. Clustering provides an effective way for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spots problem in multihop wireless sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavy relay traffic and tend to die early, leaving areas of the network uncovered and causing network partition. To address the problem, we propose an energy-efficient unequal clustering (EEUC) mechanism for periodical data gathering in wireless sensor networks. It partitions the nodes into clusters of unequal size, and clusters closer to the base station have smaller sizes than those farther away from the base station. Thus cluster heads closer to the base station can preserve some energy for the inter-cluster data forwarding. We also propose an energy-aware multihop routing protocol for the inter-cluster communication. Simulation results show that our unequal clustering mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime

Question: How does the unequal clustering mechanism work?


AskWorld: Budget-Sensitive Query Evaluation for Knowledge-on-Demand. Recently, several Web-scale knowledge harvesting systems have been built, each of which is competent at extracting information from certain types of data (e.g., unstructured text, structured tables on the web, etc.). In order to determine the response to a new query posed to such systems (e.g., is sugar a healthy food?), it is useful to integrate opinions from multiple systems. If a response is desired within a specific time budget (e.g., in less than 2 seconds), then maybe only a subset of these resources can be queried. In this paper, we address the problem of knowledge integration for on-demand time-budgeted query answering. We propose a new method, AskWorld, which learns a policy that chooses which queries to send to which resources, by accommodating varying budget constraints that are available only at query (test) time. Through extensive experiments on real world datasets, we demonstrate AskWorld's capability in selecting most informative resources to query within test-time constraints, resulting in improved performance compared to competitive baselines.

Question: What is the budget-sensitive query evaluation for knowledge-on-demand?


Google and the scholar: the role of Google in scientists' information-seeking behaviour. Purpose – This paper aims to demonstrate the role that the Google general search engine plays in the information-seeking behaviour of scientists, particularly physicists and astronomers. Design/methodology/approach – The paper is based on a mixed-methods study including 56 semi-structured interviews, a questionnaire survey of 114 respondents (47 per cent response rate) and the use of information-event cards to collect critical incident data. The study was conducted at the Department of Physics and Astronomy at University College, London. Findings – The results show that Google is the tool most used for problem-specific information seeking. The results also show the growing reliance of scientists on general search engines, particularly Google, for finding scholarly articles. Initially, finding scholarly articles was a by-product of general searching for information rather than focused searches for papers. However, a growing number of articles read by scientists are identified through the Google general search engine and, as scientists are becoming more aware of the quantity of scholarly papers searchable by Google, they are increasingly relying on Google for finding scholarly literature. Research limitations/implications – As the only fields covered in the study were physics and astronomy, and the research participants were sourced from just one department of one institution, caution should be taken in generalising the findings. Originality/value – The data are based on a mixed-methods in-depth study of scientists' information-seeking behaviour which sheds some light on a question raised in past studies relating to the reason for the high number of articles identified through Google.

Question: What is the role of google in scientists' information seeking behaviour?


Increased human intestinal barrier permeability plasma biomarkers zonulin and FABP2 correlated with plasma LPS and altered gut microbiome in anxiety or depression.. We read with interest the recent work by Uhde et al, which demonstrated that physically asymptomatic non-coeliac gluten/ wheat sensitivity involves compromised intestinal epithelium barrier dysfunction in conjunction with systemic immune activation events. We also read with interest the recent work by Marchesi et al, which comprehensively reviewed the role of microbiota in physical disorders of the gut and extra-gut organs. But common to these Gut papers was the lack of accounting for anxiety and depression, comorbidities often experienced in gastroenterology clinics. Patients who are otherwise physically asymptomatic often do not explicitly divulge these mental disorders, or the disorders are unintentionally overlooked, yet they report 'diminished quality of life'. In response to this gap, we explored roles of dysbiosis and gut barrier integrity in individuals physically asymptomatic for gastrointestinal distress, yet nonetheless experiencing mental distress. We hypothesised that anxiety and depressive disorders are linked to human gut dysbiosis with microbiota that secrete lipopolysaccharide (LPS) endotoxin into plasma, which in conjunction with compromised gut barrier integrity has systemic manifestations including the brain. We further hypothesised that this correlates with altered intestinal epithelium paracellular integrity molecules discharged into blood as biomarkers, namely zonulin and intestinal fatty acidbinding protein-2 (FABP2). Zonulin is the master regulator of endothelial and epithelium tight junctions, modulating both gut and blood–brain barriers. We analysed stool faecal microbiota and plasma in 50 subjects who self-reported to be asymptomatic for gastrointestinal physical disorders; 22 volunteers met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for a de

Question: What is the difference between anxiety and depression?


Robust and fast visual tracking via spatial kernel phase correlation filter. In this paper, we present a novel robust and fast object tracker called spatial kernel phase correlation based Tracker (SPC). Compared with classical correlation tracking which occupies all spectrums (including both phase spectrum and magnitude spectrum) in frequency domain, our SPC tracker only adopts the phase spectrum by implementing using phase correlation filter to estimate the object's translation. Thanks to circulant structure and kernel trick, we can implement dense sampling in order to train a high-quality phase correlation filter. Meanwhile, SPC learns the object's spatial context model by using new spatial response distribution, achieving superior performance. Given all these elaborate configurations, SPC is more robust to noise and cluster, and achieves more competitive performance in visual tracking. The framework of SPC can be briefly summarized as: firstly, phase correlation filter is well trained with all subwindows and is convoluted with a new image patch; then, the object's translation is calculated by maximizing spatial response; finally, to adapt to changing object, phase correlation filter is updated by reliable image patches. Tracking performance is evaluated by Peak-to-Sidelobe Ratio (PSR), aiming to resolve drifting problem by adaptive model updating. Owing to Fast Fourier Transform (FFT), the proposed tracker can track the object at about 50 frames/s. Numerical experiments demonstrate the proposed algorithm performs favorably against several state-of-the-art trackers in speed, accuracy and robustness. & 2016 Elsevier B.V. All rights reserved.

Question: What is the difference between correlation and phase correlation?


Laser hair removal.. The extended theory of selective photothermolysis enables the laser surgeon to target and destroy hair follicles, thereby leading to hair removal. Today, laser hair removal (LHR) is the most commonly requested cosmetic procedure in the world and is routinely performed by dermatologists, other physicians, and non-physician personnel with variable efficacy. The ideal candidate for LHR is fair skinned with dark terminal hair; however, LHR can today be successfully performed in all skin types. Knowledge of hair follicle anatomy and physiology, proper patient selection and preoperative preparation, principles of laser safety, familiarity with the various laser/light devices, and a thorough understanding of laser-tissue interactions are vital to optimizing treatment efficacy while minimizing complications and side effects.

Question: What is the ideal candidate for laser hair removal?


Clause Restructuring for Statistical Machine Translation. We describe a method for incorporating syntactic information in statistical machine translation systems. The first step of the method is to parse the source language string that is being translated. The second step is to apply a series of transformations to the parse tree, effectively reordering the surface string on the source language side of the translation system. The goal of this step is to recover an underlying word order that is closer to the target language word-order than the original string. The reordering approach is applied as a pre-processing step in both the training and decoding phases of a phrase-based statistical MT system. We describe experiments on translation from German to English, showing an improvement from 25.2% Bleu score for a baseline system to 26.8% Bleu score for the system with reordering, a statistically significant improvement.

Question: What is a statistical machine translation system?


Tensegrity II. How structural networks influence cellular information processing networks.. The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

Question: How does tensegrity architecture influence cell behavior?


AP3: cooperative, decentralized anonymous communication. This paper describes a cooperative overlay network that provides anonymous communication services for participating users. The Anonymizing Peer-to-Peer Proxy (AP3) system provides clients with three primitives: (i) anonymous message delivery, (ii) anonymous channels, and (iii) secure pseudonyms. AP3 is designed to be lightweight, low-cost and provides "probable innocence" anonymity to participating users, even under a large-scale coordinated attack by a limited fraction of malicious overlay nodes. Additionally, we use AP3's primitives to build novel anonymous group communication facilities (multicast and anycast), which shield the identity of both publishers and subscribers.

Question: What is the difference between AP3 and Tor?


Acquisition and analysis of volatile memory from android devices. The Android operating system for mobile phones, which is still relatively new, is rapidly gaining market share, with dozens of smartphones and tablets either released or set to be released. In this paper, we present the first methodology and toolset for acquisition and deep analysis of volatile physical memory from Android devices. The paper discusses some of the challenges in performing Android memory acquisition, discusses our new kernel module for dumping memory, named dmd, and specifically addresses the difficulties in developing device-independent acquisition tools. Our acquisition tool supports dumping memory to either the SD on the phone or via the network. We also present analysis of kernel structures using newly developed Volatility functionality. The results of this work illustrate the potential that deep memory analysis offers to digital forensics investigators. a 2011 Elsevier Ltd. All rights reserved.

Question: How to dump memory from android devices?


Application Protocols and Wireless Communication for IoT: A Simulation Case Study Proposal. The current Internet of Things (IoT) solutions require support at different network layers, from higher level applications to lower level media-based support. This paper presents some of the main application requirements for IoT, characterizing architecture, Quality of Service (QoS) features, security mechanisms, discovery service resources and web integration options and the protocols that can be used to provide them (e.g. CoAP, XMPP, DDS, MQTT-SN, AMQP). As examples of lower-level requirements and protocols, several wireless network characteristics (e.g. ZigBee, Z-Wave, BLE, LoRaWAN, SigFox, IEEE 802.11af, NB-IoT) are presented. The variety of possible applications scenarios and the heterogeneity of enabling technologies combined with a large number of sensors and devices, suggests the need for simulation and modeling tactics to describe how the previous requirements can be met. As a potential solution, the creation of simulation models and the usage of the OMNET++ simulation tool to enable meaningful IoT simulation is discussed. The analysis of the behavior of IoT applications is proposed for two use cases: Wireless Sensor Networks (WSN) for home and industrial automation, and Low Power Wide Area (LPWA) networks for smart meters, smart buildings, and smart cities.

Question: What is the difference between ZigBee and Z-Wave?


Let's stop trying to be "sexy" - preparing managers for the (big) data-driven business era. Let's stop trying to be 'sexy' – preparing managers for the (big) data-driven business era Kevin Daniel André Carillo, Article information: To cite this document: Kevin Daniel André Carillo, (2017) "Let's stop trying to be 'sexy' – preparing managers for the (big) data-driven business era", Business Process Management Journal, Vol. 23 Issue: 3, doi: 10.1108/BPMJ-09-2016-0188 Permanent link to this document: http://dx.doi.org/10.1108/BPMJ-09-2016-0188

Question: Let's stop trying to be "sexy" - preparing managers for the (big) data-driven business era


Pharmaceutical cold chain management: Platform based on a distributed ledger. In the process of distributing pharmaceutical products multiple stages are involved until products are delivered to patient. A reliable way for validating and verifying that products had been maintained within a licensed range is required. The paper presents a solution for pharmaceutical cold chain management using distributed ledger technologies. An application framework is proposed for shipment tracking which will deliver information to all stakeholders during the distribution phase of pharmaceutical products. The solution is based on Hyperledger Sawtooth distributed ledger framework, which has been extended with a custom transactions family and a sensors gateway for automatically collecting data from temperature tracking devices. The focus of the paper is to describe the data model and how entities of the system communicate.

Question: What is a distributed ledger?


Magnetic integration of LCC compensated resonant converter for inductive power transfer applications. The aim of this paper is to present a novel magnetic integrated LCC series-parallel compensation topology for the design of both the primary and pickup pads in inductive power transfer (IPT) applications. A more compact structure can be realized by integrating the inductors of the compensation circuit into the coupled power-transmitting coils. The impact of the extra coupling between the compensated coils (inductors) and the power-transferring coils is modeled and analyzed. The basic characteristics of the proposed topology are studied based on the first harmonic approximation (FHA). High-order harmonics are taken into account to derive an analytical solution for the current at the switching instant, which is helpful for the design of soft-switching operation. An IPT system with up to 5.6kW output power for electric vehicles (EV) charger has been built to verify the validity of the proposed magnetic integrated compensation topology. A peak efficiency of 95.36% from DC power source to the battery load is achieved at rated operation condition.

Question: How to design a magnetic integrated LCC series-parallel compensation topology for inductive power transfer applications?


Object volume estimation based on 3D point cloud. An approach to estimating the volume of an object based on 3D point cloud is proposed in this paper. Firstly, 3D point cloud is cut into slices of equal thickness along the z-axis. Bisect each slice along the y-axis and cut each slice into sub-intervals along the x-axis. Using the minimum and maximum coordinates in each sub-interval, two surface curve functions can be fitted accordingly for the bisected slices. Then, the curves are integrated to estimate the area of each slice and further integrated along the z-axis for an estimated volume of the object.

Question: How to estimate the volume of an object based on 3D point cloud?


Integrated microstrip and rectangular waveguide in planar form. Usually transitions from microstrip line to rectangular waveguide are made with three-dimensional complex mounting structures. In this paper, a new planar platform is developed in which the microstrip line and rectangular waveguide are fully integrated on the same substrate, and they are interconnected via a simple taper. Our experiments at 28 GHz show that an effective bandwidth of 12% at 20 dB return loss is obtained with an in-band insertion loss better than 0.3 dB. The new transition allows a complete integration of waveguide components on substrate with MICs and MMICs.

Question: What is the difference between microstrip and rectangular waveguide?


A user's guide to tabu search. We describe the main features of tabu search, emphasizing a perspective for guiding a user to understand basic implementation principles for solving combinatorial or nonlinear problems. We also identify recent developments and extensions that have contributed to increasing the efficiency of the method. One of the useful aspects of tabu search is the ability to adapt a rudimentary prototype implementation to encompass additional model elements, such as new types of constraints and objective functions. Similarly, the method itself can be evolved to varying levels of sophistication. We provide several examples of discrete optimization problems to illustrate the strategic concerns of tabu search, and to show how they may be exploited in various contexts. Our presentation is motivated by the emergence of an extensive literature of computational results, which demonstrates that a well-tuned implementation makes it possible to obtain solutions of high quality for difficult problems, yielding outcomes in some settings that have not been matched by other known techniques.

Question: What is tabu search?


Crop disease classification using texture analysis. With the Agriculture Sector being the backbone of not only a large number of industries but also society as a whole, there is a rising need to grow good quality crops which in turn will give a high yield. For this to happen, it is crucial to monitor the crops throughout their growth period. In this paper, Image processing is used to detect and classify sunflower crop diseases based on the image of their leaf. The images are taken through a high resolution digital camera and after preprocessing, are subjected to k-means clustering to get the diseased part of the leaf. These are then run through the various machine learning algorithms and classified based on their color and texture features. A comparison based on accuracy between various machine learning algorithms is done namely K-Nearest Neighbors, Multi-Class Support Vector Machine, Naive Bayes and Multinomial Logistic Regression to achieve maximum accuracy. The implementation has been done using MATLAB.

Question: How to classify crop diseases using image processing?


The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder.. One hundred children, ages 6-19, who were diagnosed with attention-deficit/hyperactivity disorder (ADHD), either inattentive or combined types, participated in a study examining the effects of Ritalin, EEG biofeedback, and parenting style on the primary symptoms of ADHD. All of the patients participated in a 1-year, multimodal, outpatient program that included Ritalin, parent counseling, and academic support at school (either a 504 Plan or an IEP). Fifty-one of the participants also received EEG biofeedback therapy. Posttreatment assessments were conducted both with and without stimulant therapy. Significant improvement was noted on the Test of Variables of Attention (TOVA; L. M. Greenberg, 1996) and the Attention Deficit Disorders Evaluation Scale (ADDES; S. B. McCarney, 1995) when participants were tested while using Ritalin. However, only those who had received EEG biofeedback sustained these gains when tested without Ritalin. The results of a Quantitative Electroencephalographic Scanning Process (QEEG-Scan; V. J. Monastra et al., 1999) revealed significant reduction in cortical slowing only in patients who had received EEG biofeedback. Behavioral measures indicated that parenting style exerted a significant moderating effect on the expression of behavioral symptoms at home but not at school.

Question: What is the effect of stimulant therapy on the primary symptoms of attention-deficit/hyperactivity disorder?


An Efficient Method for Traffic Sign Recognition Based on Extreme Learning Machine. This paper proposes a computationally efficient method for traffic sign recognition (TSR). This proposed method consists of two modules: 1) extraction of histogram of oriented gradient variant (HOGv) feature and 2) a single classifier trained by extreme learning machine (ELM) algorithm. The presented HOGv feature keeps a good balance between redundancy and local details such that it can represent distinctive shapes better. The classifier is a single-hidden-layer feedforward network. Based on ELM algorithm, the connection between input and hidden layers realizes the random feature mapping while only the weights between hidden and output layers are trained. As a result, layer-by-layer tuning is not required. Meanwhile, the norm of output weights is included in the cost function. Therefore, the ELM-based classifier can achieve an optimal and generalized solution for multiclass TSR. Furthermore, it can balance the recognition accuracy and computational cost. Three datasets, including the German TSR benchmark dataset, the Belgium traffic sign classification dataset and the revised mapping and assessing the state of traffic infrastructure (revised MASTIF) dataset, are used to evaluate this proposed method. Experimental results have shown that this proposed method obtains not only high recognition accuracy but also extremely high computational efficiency in both training and recognition processes in these three datasets.

Question: What is the difference between the ELM and the backpropagation algorithm?


Secondary Load-Frequency Control for MicroGrids in Islanded Operation. The objective of this paper is to present novel control strategies for MicroGrid operation, especially in islanded mode. The control strategies involve mainly the coordination of secondary load-frequency control by a MicroGrid Central Controller that heads a hierarchical control system able to assure stable and secure operation when the islanding of the MicroGrid occurs and in load-following situations in islanded mode.

Question: What is the objective of this paper?


Rethinking project management : A structured literature review with a critical look at the brave new world. This paper presents the results of a structured review of the rethinking project management (RPM) literature based on the classification and analysis of 74 contributions and in addition takes a critical look at this brave new world. Through the analysis, a total of 6 overarching categories emerged: contextualization, social and political aspects, rethinking practice, complexity and uncertainty, actuality of projects and broader conceptualization. These categories cover a broad range of different contributions with diverse and alternative perspectives on project management. The early RPM literature dates back to the 1980s, while the majority was published in 2006 onwards, and the research stream appears to be still active. A critical look at this brave new world exhibits the overall challenge for RPM to become much more diffused and accepted. © 2014 Elsevier Ltd. APM and IPMA. All rights reserved.

Question: What is the brave new world?


Efficient High-Quality Volume Rendering of SPH Data. High quality volume rendering of SPH data requires a complex order-dependent resampling of particle quantities along the view rays. In this paper we present an efficient approach to perform this task using a novel view-space discretization of the simulation domain. Our method draws upon recent work on GPU-based particle voxelization for the efficient resampling of particles into uniform grids. We propose a new technique that leverages a perspective grid to adaptively discretize the view-volume, giving rise to a continuous level-of-detail sampling structure and reducing memory requirements compared to a uniform grid. In combination with a level-of-detail representation of the particle set, the perspective grid allows effectively reducing the amount of primitives to be processed at run-time. We demonstrate the quality and performance of our method for the rendering of fluid and gas dynamics SPH simulations consisting of many millions of particles.

Question: How to efficiently render SPH data?


Intelligent stereo camera mobile platform for indoor service robot research. Stereo vision is an active research topic in computer vision. Point Grey® Bumblebee® and digital single-lens reflex camera (DSLR) are normally found in the stereo vision research, they are robust but expensive. Open source electronic prototyping platforms such as Arduino and Raspberry Pi are interesting products, which allows students or researchers to custom made inexpensive experimental equipment for their research projects. This paper describes the intelligent stereo camera mobile platform developed in our research using Pi and camera modules and presents the concept of using inexpensive open source parts for robotic stereo vision research work in details.

Question: What is the concept of using inexpensive open source parts for robotic stereo vision research?