Passing a Hide-and-Seek Third-Person Turing Test. Hiding and seeking are cognitive abilities frequently demonstrated by humans in both real life and video games. To determine to which extent these abilities can be replicated with AI, we introduce a specialized version of the Turing test for hiding and seeking. We then develop a computer agent that passes the test by appearing indistinguishable from human behavior to a panel of human judges. We analyze the AI techniques that enable the agent to imitate human hide-and-seek behavior and their relative contribution to the agent's performance.

Question: What is a hide-and-seek Turing test?


Good Features to Correlate for Visual Tracking. During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in this family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize the robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks, which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.

Question: What is the difference between correlation filter based and correlation filter based visual tracking?


Active Learning with Feedback on Both Features and Instances. We extend the traditional active learning framework to include feedback on features in addition to labeling instances, and we execute a careful study of the effects of feature selection and human feedback on features in the setting of text categorization. Our experiments on a variety of categorization tasks indicate that there is significant potential in improving classifier performance by feature re-weighting, beyond that achieved via membership queries alone (traditional active learning) if we have access to an oracle that can point to the important (most predictive) features. Our experiments on human subjects indicate that human feedback on feature relevance can identify a sufficient proportion of the most relevant features (over 50% in our experiments). We find that on average, labeling a feature takes much less time than labeling a document. We devise an algorithm that interleaves labeling features and documents which significantly accelerates standard active learning in our simulation experiments. Feature feedback can complement traditional active learning in applications such as news filtering, e-mail classification, and personalization, where the human teacher can have significant knowledge on the relevance of features.

Question: What is the difference between active learning and traditional active learning?


Discrete Dynamic Shortest Path Problems in Transportation Applications: Complexity and Algorithms with Optimal Run Time. This paper solves what appears to be a 30 years old problem dealing with the discovery of most effi algorithms possible to compute all-to-one shortest paths in discrete dynamic networks. This problem lies at th of efficient solution approaches to dynamic network models that arise in dynamic transportation systems, suc Intelligent Transportation Systems (ITS) applications. While the main objective of this paper is the study of the one dynamic shortest paths problem, one-to-all fastest paths problems are studied as well. Early results are and new properties are established. We establish the exact complexity of these problems and develop optima run time sense, solution algorithms. A new and simple solution algorithm is proposed for all-to-one all departur intervals shortest path problems. It is proved, theoretically, that the new solution algorithm has an optimal run complexity that equals the complexity of the problem. Computer implementations and experimental evaluatio various solution algorithms support the theoretical findings and demonstrate the efficiency of the proposed so algorithm. We expect our findings to be of major benefit to research and development activities in the field of dynamic, in particular real-time, management and control of large-scale Intelligent Transportation Systems (I

Question: What is the complexity of the shortest path problem?


Constituency Parsing with a Self-Attentive Encoder. We demonstrate that replacing an LSTM encoder with a self-attentive architecture can lead to improvements to a state-ofthe-art discriminative constituency parser. The use of attention makes explicit the manner in which information is propagated between different locations in the sentence, which we use to both analyze our model and propose potential improvements. For example, we find that separating positional and content information in the encoder can lead to improved parsing accuracy. Additionally, we evaluate different approaches for lexical representation. Our parser achieves new state-ofthe-art results for single models trained on the Penn Treebank: 93.55 F1 without the use of any external data, and 95.13 F1 when using pre-trained word representations. Our parser also outperforms the previous best-published accuracy figures on 8 of the 9 languages in the SPMRL dataset.

Question: How does a self-attentive encoder improve constituency parsing?


Web evolution and Web Science. This paper examines the evolution of the World Wide Web as a network of networks and discusses the emergence of Web Science as an interdisciplinary area that can provide us with insights on how the Web developed, and how it has affected and is affected by society. Through its different stages of evolution, the Web has gradually changed from a technological network of documents to a network where documents, data, people and organisations are interlinked in various and often unexpected ways. It has developed from a technological artefact separate from people to an integral part of human activity that is having an increasingly significant impact on the world. This paper outlines the lessons from this retrospective examination of the evolution of the Web, presents the main outcomes of Web Science activities and discusses directions along which future developments could be anticipated.

Question: What is the web?


Spinal Instability Neoplastic Score (SINS): Reliability Among Spine Fellows and Resident Physicians in Orthopedic Surgery and Neurosurgery. Study Design Reliability analysis.   Objectives The Spinal Instability Neoplastic Score (SINS) was developed for assessing patients with spinal neoplasia. It identifies patients who may benefit from surgical consultation or intervention. It also acts as a prognostic tool for surgical decision making. Reliability of SINS has been established for spine surgeons, radiologists, and radiation oncologists, but not yet among spine surgery trainees. The purpose of our study is to determine the reliability of SINS among spine residents and fellows, and its role as an educational tool.   Methods Twenty-three residents and 2 spine fellows independently scored 30 de-identified spine tumor cases on 2 occasions, at least 6 weeks apart. Intraclass correlation coefficient (ICC) measured interobserver and intraobserver agreement for total SINS scores. Fleiss's kappa and Cohen's kappa analysis evaluated interobserver and intraobserver agreement of 6 component subscores (location, pain, bone lesion quality, spinal alignment, vertebral body collapse, and posterolateral involvement of spinal elements).   Results Total SINS scores showed near perfect interobserver (0.990) and intraobserver (0.907) agreement. Fleiss's kappa statistics revealed near perfect agreement for location; substantial for pain; moderate for alignment, vertebral body collapse, and posterolateral involvement; and fair for bone quality (0.948, 0.739, 0.427, 0.550, 0.435, and 0.382). Cohen's kappa statistics revealed near perfect agreement for location and pain, substantial for alignment and vertebral body collapse, and moderate for bone quality and posterolateral involvement (0.954, 0.814, 0.610, 0.671, 0.576, and 0.561, respectively).   Conclusions The SINS is a reliable and valuable educational tool for spine fellows and residents learning to judge spinal instability.

Question: What is the reliability of the spinal instability neoplastic score?


A Novel Driving and Protection Circuit for Reverse-Blocking IGBT Used in Matrix Converter. A novel drive and protection circuit for reverse-blocking insulated gate bipolar transistor (RB-IGBT) is proposed in this paper. For the drive circuit, a dynamic current source is introduced to reduce the turn-on and turn-off transients. Meanwhile, the di/dt of the collector current and the dv/dt of the collector-emitter voltage are strictly restricted, so do the respective stresses. The drive circuit consists of a conventional push-pull driver and two controllable current sources-a current generator and a current sink. These two current sources work in switching transitions. For the protection circuit, a novel collector current detecting circuit suitable for RB-IGBT is proposed. This method detects the collector current by sensing collector-emitter voltage of the device. Further study shows that this method can be used to acquire the current signs in commutation transitions of matrix converter. A series of experiments has been carried out concerning the proposed drive and protection circuit and the experimental setup; results as well as detailed analysis are presented

Question: What is a matrix converter?


Smart vehicle accident detection and alarming system using a smartphone. Vehicle accident is the paramount thread for the people's life which causes a serious wound or even dead. The automotive companies have made lots of progress in alleviating this thread, but still the probability of detrimental effect due to an accident is not reduced. Infringement of spFieed is one of the elementary reasons for a vehicle accident. Therewithal, external pressure and change of tilt angle with road surface blameworthy for this mishap. As soon as the emergency service could divulge about an accident, the more the effect would be mitigated. For this purpose, we developed an Android based application that detects an accidental situation and sends emergency alert message to the nearest police station and health care center. This application is integrated with an external pressure sensor to extract the outward force of the vehicle body. It measures speed and change of tilt angle with GPS and accelerometer sensors respectively on Android phone. By checking conditions, this application also capable of reducing the rate of false alarm.

Question: How to detect vehicle accident?


Energy Management of Fuel Cell/Battery/Supercapacitor Hybrid Power Sources Using Model Predictive Control. Well known as an efficient and eco-friendly power source, fuel cell, unfortunately, offers slow dynamics. When attached as primary energy source in a vehicle, fuel cell would not be able to respond to abrupt load variations. Supplementing battery and/or supercapacitor to the system will provide a solution to this shortcoming. On the other hand, a current regulation that is vital for lengthening time span of the energy storage system is needed. This can be accomplished by keeping fuel cell's and batteries' current slope in reference to certain values, as well as attaining a stable dc output voltage. For that purpose, a feedback control system for regulating the hybrid of fuel cell, batteries, and supercapacitor was constructed for this study. Output voltage of the studied hybrid power sources (HPS) was administered by assembling three dc-dc converters comprising two bidirectional converters and one boost converter. Current/voltage output of fuel cell was regulated by boost converter, whereas the bidirectional converters regulated battery and supercapacitor. Reference current for each converter was produced using Model Predictive Control (MPC) and subsequently tracked using hysteresis control. These functions were done on a controller board of a dSPACE DS1104. Subsequently, on a test bench made up from 6 V, 4.5 Ah battery and 7.5 V, 120 F supercapacitor together with a fuel cell of 50 W, 10 A, experiment was conducted. Results show that constructing a control system to restrict fuel cell's and batteries' current slope and maintaining dc bus voltage in accordance with the reference values using MPC was feasible and effectively done.

Question: How to regulate the hybrid of fuel cell, batteries, and supercapacitor?


GENIA corpus - a semantically annotated corpus for bio-textmining. MOTIVATION Natural language processing (NLP) methods are regarded as being useful to raise the potential of text mining from biological literature. The lack of an extensively annotated corpus of this literature, however, causes a major bottleneck for applying NLP techniques. GENIA corpus is being developed to provide reference materials to let NLP techniques work for bio-textmining.   RESULTS GENIA corpus version 3.0 consisting of 2000 MEDLINE abstracts has been released with more than 400,000 words and almost 100,000 annotations for biological terms.

Question: What is the motivation for developing the GENIA corpus?


Low-Power and Area-Efficient Carry Select Adder. Carry Select Adder (CSLA) is one of the fastest adders used in many data-processing processors to perform fast arithmetic functions. From the structure of the CSLA, it is clear that there is scope for reducing the area and power consumption in the CSLA. This work uses a simple and efficient gate-level modification to significantly reduce the area and power of the CSLA. Based on this modification 8-, 16-, 32-, and 64-b square-root CSLA (SQRT CSLA) architecture have been developed and compared with the regular SQRT CSLA architecture. The proposed design has reduced area and power as compared with the regular SQRT CSLA with only a slight increase in the delay. This work evaluates the performance of the proposed designs in terms of delay, area, power, and their products by hand with logical effort and through custom design and layout in 0.18-μm CMOS process technology. The results analysis shows that the proposed CSLA structure is better than the regular SQRT CSLA.

Question: What is the area of the proposed design?


An Introduction to Locally Linear Embedding. Many problemsin informationprocessinginvolvesomeform of dimensionality reduction.Herewe describelocally linearembedding(LLE), anunsupervisedlearningalgorithmthat computeslow dimensional,neighborhood preservingembeddingsof high dimensionaldata.LLE attemptsto discover nonlinearstructurein high dimensionaldataby exploiting thelocal symmetries of linear reconstructions.Notably, LLE mapsits inputs into a single global coordinatesystemof lower dimensionality, and its optimizations— thoughcapableof generatinghighly nonlinearembeddings—donot involve localminima.We illustratethemethodon imagesof lips usedin audiovisual speechsynthesis.

Question: What is locally linear embedding?


Lane detection and tracking using B-Snake. In this paper, we proposed a B-Snake based lane detection and tracking algorithm without any cameras' parameters. Compared with other lane models, the B-Snake based lane model is able to describe a wider range of lane structures since B-Spline can form any arbitrary shape by a set of control points. The problems of detecting both sides of lane markings (or boundaries) have been merged here as the problem of detecting the mid-line of the lane, by using the knowledge of the perspective parallel lines. Furthermore, a robust algorithm, called CHEVP, is presented for providing a good initial position for the B-Snake. Also, a minimum error method by Minimum Mean Square Error (MMSE) is proposed to determine the control points of the B-Snake model by the overall image forces on two sides of lane. Experimental results show that the proposed method is robust against noise, shadows, and illumination variations in the captured road images. It is also applicable to the marked and the unmarked roads, as well as the dash and the solid paint line roads. q 2003 Elsevier B.V. All rights reserved.

Question: What is the difference between a dash and a solid paint line?


Chat Speed OP : Practices of Coherence in Massive Twitch Chat. Paste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced in a sans-serif 7 point font. Every submission will be assigned their own unique DOI string to be included here. Abstract Twitch.tv, a streaming platform known for video game content, has grown tremendously since its inception in 2011. We examine communication practices in Twitch chats for the popular game Hearthstone, comparing massive chats with at least 10,000 concurrent viewers and small chats with fewer than 2,000 concurrent viewers. Due to the large scale and fast pace of massive chats, communication patterns no longer follow models developed in previous studies of computer-mediated communication. Rather than what other studies have described as communication breakdowns and information overload, participants in massive chats communicate in what we call "crowdspeak."

Question: What is crowdspeak?


Analysis of a microstrip patch array fed cylindric lens antenna for 77GHz automotive radar. Regarding gain and SLL, the new lens antenna concept has better focusing abilities compared to the column antenna. Pattern perturbations due to lens edge effects were analyzed with regard to digital array processing. They can be confined either with an appropriate choice for the lens length L and the xlscr,i of the radar sensorpsilas receiving ULA or with narrower feeding beams in the H-plane.

Question: What is the difference between a lens antenna and a patch antenna?


New Direct Torque Control Scheme for BLDC Motor Drives Suitable for EV Applications. This paper proposes a simple and effective scheme for Direct Torque Control (DTC) of Brushless DC Motor. Unlike the traditional DTC where both the torque and flux must to be employed in order to deliver the switching table for the inverter, the proposed DTC scheme utilizes only the torque information. By considering the particular operating principle of the motor, the instantaneous torque can be estimated only by using back EMF ratio in an unified differential equation. The simulation results have shown the good performance of the proposed scheme. It can be seen thus a very suitable technique for EV drives which need fast and precise torque response.

Question: What is the difference between the traditional DTC and the proposed DTC?


Medical Sentiment Analysis using Social Media: Towards building a Patient Assisted System. With the enormous growth of Internet, more users have engaged in health communities such as medical forums to gather health-related information, to share experiences about drugs, treatments, diagnosis or to interact with other users with similar condition in communities. Monitoring social media platforms has recently fascinated medical natural language processing researchers to detect various medical abnormalities such as adverse drug reaction. In this paper, we present a benchmark setup for analyzing the sentiment with respect to users' medical condition considering the information, available in social media in particular. To this end, we have crawled the medical forum website 'patient.info' with opinions about medical condition self narrated by the users. We constrained ourselves to some of the popular domains such as depression, anxiety, asthma, and allergy. The focus is given on the identification of multiple forms of medical sentiments which can be inferred from users' medical condition, treatment, and medication. Thereafter, a deep Convolutional Neural Network (CNN) based medical sentiment analysis system is developed for the purpose of evaluation. The resources are made available to the community through LRE map for further research.

Question: What is the medical sentiment analysis?


Image contrast enhancement by automatic multi-histogram equalization for satellite images. In this paper, a new automatic histogram equalization algorithm which is based on Bi-Histogram Equalization (BHE) is proposed. The proposed method preserves the brightness and also improves the contrast. Mean value of the intensity is used for selecting the thresholds to avoid over enhancement also improving contrast of the image. The calculated mean limits the valley points to divide the histogram into small parts which guarantee equal input and output mean brightness. In addition, normalization of image brightness is applied to assure less Absolute Mean Brightness Error (AMBE). The performances of proposed algorithm, Global Histogram equalization algorithm and Bi-Histogram equalization algorithm are measured by calculating another validity parameter called Peak Signal to Noise Ratio (PSNR). The proposed method confirms the improvement in qualitative parameters as compared with the other two algorithms considered.

Question: How to improve the contrast of satellite images?


Private Release of Graph Statistics using Ladder Functions. Protecting the privacy of individuals in graph structured data while making accurate versions of the data available is one of the most challenging problems in data privacy. Most efforts to date to perform this data release end up mired in complexity, overwhelm the signal with noise, and are not effective for use in practice. In this paper, we introduce a new method which guarantees differential privacy. It specifies a probability distribution over possible outputs that is carefully defined to maximize the utility for the given input, while still providing the required privacy level. The distribution is designed to form a 'ladder', so that each output achieves the highest 'rung' (maximum probability) compared to less preferable outputs. We show how our ladder framework can be applied to problems of counting the number of occurrences of subgraphs, a vital objective in graph analysis, and give algorithms whose cost is comparable to that of computing the count exactly. Our experimental study confirms that our method outperforms existing methods for counting triangles and stars in terms of accuracy, and provides solutions for some problems for which no effective method was previously known. The results of our algorithms can be used to estimate the parameters of suitable graph models, allowing synthetic graphs to be sampled.

Question: How to count triangles in a graph?


[Botulinum toxin injection techniques in the lower third and middle of the face, the neck and the décolleté: the "Nefertiti lift"].. Although correction of the dynamic wrinkles of the upper part of the face is the major indication for botulinum toxin, there are also many possibilities for the middle and lower thirds of the face and neck. However, these injections are more delicate and require an experienced operator who has excellent knowledge of the muscles of these regions, their functions, the antagonist actions exercised on other muscles, particularly in terms of the complex equilibrium of the mouth. An excessive dose, an inappropriate injection point, or a centering mistake can all easily be responsible for undesirable side effects. However, the results obtained, often with lower doses than in the superior part of the face, can be highly satisfactory, notably in erasing bunny lines, improvement of marionette lines, peau d'orange chin, attenuation of peribuccal lines, melomental folds, correction of a gummy smile, and facial asymmetries. In the neck it is possible to reduce platysmal bands, horizontal lines, and diagonal lines of the neck and décolleté. The face contours can also be improved by the Nefertiti lift. In the mid and lower regions of the face, botulinum toxin is often a complement to other esthetic techniques, particularly filling procedures.

Question: What is the "Nefertiti lift"?


Predictive analytics with surveillance big data. In this paper, we describe a novel analytics system that enables query processing and predictive analytics over streams of aviation data. As part of an Internal Research and Development project, Boeing Research and Technology (BR&T) Advanced Air Traffic Management (AATM) built a system that makes predictions based upon descriptive patterns of archived aviation data. Boeing AATM has been receiving live Aircraft Situation Display to Industry (ASDI) data and archiving it for over two years. At the present time, there is not an easy mechanism to perform analytics on the data. The incoming ASDI data is large, compressed, and requires correlation with other flight data before it can be analyzed.  The service exposes this data once it has been uncompressed, correlated, and stored in a data warehouse for further analysis using a variety of descriptive, predictive, and possibly prescriptive analytics tools. The service is being built partially in response to requests from Boeing Commercial Aviation (BCA) for analysis of capacity and flow in the US National Airspace System (NAS). The service utilizes a custom tool for correlating the raw ASDI feed, IBM Warehouse with DB2 for data management, WebSphere Message Broker for real-time message brokering, SPSS Modeler for statistical analysis, and Cognos BI for front-end business intelligence (BI) visualization. This paper describes a scalable service architecture, implementation and the value it adds to the aviation domain.

Question: What is the value of predictive analytics with surveillance big data?


Exploring the role of robotic kissing "Kissenger" in digital communication through alan turing's imitation game. With advances in robotics and artificial intelligence, and increasing prevalence of commercial social robots and chatbots, humans are communicating with artificially intelligent machines for various applications in a wide range of settings. Intimate touch is crucial to relationships forming and emotional bonding, however it remains as a missing element in digital communication between humans, as well as humans and machines. A kissing machine, Kissenger, is built to transmit haptic kissing sensations in a communication network. In order to investigate the role of robotic kissing using the Kissenger device in digital communication, we conducted a modified version of the Imitation Game described by Alan Turing by including the use of the kissing machine. The study consists of 4 rounds, in which participants communicate with two players, a male and a female, using online chatrooms with the goal to identify the female player. In the last two rounds, the male player is replaced with a chatbot with female personas. Participants are told to remotely kiss the players using the kissing device at least once during the chat in the second and fourth round, but not in the first and third round. Results show that robotic kissing has no effect on the winning rates of the male and female players during human-human communication, but it increases the winning rate of the female player when a chatbot is involved in the game.

Question: What is the role of robotic kissing in digital communication?


A Virtual Feedback Assistance System for Remote Operation of a 3DOF Micromanipulator in Micro-Nanorobotic Manipulation. Manipulation in micro or nanoscale with robotic manipulators under observation of electron microscopes is a widely used strategy for fabrication of nanodevices and nanoscale material property characterization. These types of manipulation systems can handle the relatively larger scale of objects. However, the complexity of manipulation increases highly for 3D manipulation. Since the manipulation system consists of multiple components including manipulator, microscope, and also some end-effector tools, a proper offline visualization of the system is necessary for operation. Therefore, we propose a web-based virtual interface between the user and the actual manipulator operated under digital microscope initially. It gives the operator 3D positional feedback from the virtual model by mapping data read during remote operation. The same interface is used for remote operation of the manipulator within the SEM chamber and a manipulation task is performed.

Question: How to manipulate a 3D object in a SEM?


Energy Management Based on Frequency Approach for Hybrid Electric Vehicle Applications: Fuel-Cell/Lithium-Battery and Ultracapacitors. This paper presents the ultracapacitors (U) and fuel-cell/lithium-battery connection with an original energy management method for hybrid electric vehicle (HEV) applications. The proposed method is focused on the frequency approach to meet the load energy requirement. The ultracapacitors are connected to the dc link through a buck-boost converter, and the fuel cell is connected to the dc link via a boost converter for the first topology. In the second topology, the lithium battery is connected to the dc link without a converter to avoid the dc-link voltage control. An asynchronous machine is used like the traction motor; it is related to the dc link through a dc/ac converter (inverter). The main contribution of this paper is focused on HEV energy management according to the dynamics (frequency) of the hybrid sources using polynomial correctors. The performances of the proposed method are evaluated through some simulations and the experimental tests, using the New European Driving Cycle (NEDC). This study is extended to an aggressive test cycle, such as the U.S. driving cycle (USDC), to understand the system response and the control performances.

Question: How to manage the energy of a hybrid electric vehicle?


Scaling Distributed Machine Learning with System and Algorithm Co-design. Due to the rapid growth of data and the ever increasing model complexity, which often manifests itself in the large number of model parameters, today, many important machine learning problems cannot be efficiently solved by a single machine. Distributed optimization and inference is becoming more and more inevitable for solving large scale machine learning problems in both academia and industry. However, obtaining an efficient distributed implementation of an algorithm, is far from trivial. Both intensive computational workloads and the volume of data communication demand careful design of distributed computation systems and distributed machine learning algorithms. In this thesis, we focus on the co-design of distributed computing systems and distributed optimization algorithms that are specialized for large machine learning problems. In the first part, we propose two distributed computing frameworks: Parameter Server, a distributed machine learning framework that features efficient data communication between the machines; MXNet, a multi-language library that aims to simplify the development of deep neural network algorithms. We have witnessed the wide adoption of the two proposed systems in the past two years. They have enabled and will continue to enable more people to harness the power of distributed computing to design efficient large-scale machine learning applications. In the second part, we examine a number of distributed optimization problems in machine learning, leveraging the two computing platforms. We present new methods to accelerate the training process, such as data partitioning with better locality properties, communication friendly optimization methods, and more compact statistical models. We implement the new algorithms on the two systems and test on large scale real data sets. We successfully demonstrate that careful co-design of computing systems and learning algorithms can

Question: What is the difference between a distributed computing framework and a distributed machine learning framework?


DB2 Design Advisor: Integrated Automatic Physical Database Design. The DB2 Design Advisor in IBM® DB2® Universal DatabaseTM (DB2 UDB) Version 8.2 for Linux®, UNIX® and Windows® is a tool that, for a given workload, automatically recommends physical design features that are any subset of indexes, materialized query tables (also called materialized views), shared-nothing database partitionings, and multidimensional clustering of tables. Our work is the very first industrial-strength tool that covers the design of as many as four different features, a significant advance to existing tools, which support no more than just indexes and materialized views. Building such a tool is challenging, because of not only the large search space introduced by the interactions among features, but also the extensibility needed by the tool to support additional features in the future. We adopt a novel "hybrid" approach in the Design Advisor that allows us to take important interdependencies into account as well as to encapsulate design features as separate components to lower the reengineering cost. The Design Advisor also features a built-in module that automatically reduces the given workload, and therefore provides great scalability for the tool. Our experimental results demonstrate that our tool can quickly provide good physical design recommendations that satisfy users' requirements.

Question: What is the DB2 Design Advisor?


The qualitative interview in IS research: Examining the craft. The qualitative interview is one of the most important data gathering tools in qualitative research, yet it has remained an unexamined craft in IS research. This paper discusses the potential difficulties, pitfalls and problems of the qualitative interview in IS research. Building on Goffman's seminal work on social life, the paper proposes a dramaturgical model as a useful way of conceptualizing the qualitative interview. Based on this model the authors suggest guidelines for the conduct of qualitative interviews. 2006 Elsevier Ltd. All rights reserved.

Question: What is the qualitative interview?


Immuno-inspired autonomic system for cyber defense. The biological immune system is an autonomic system for self-protection, which has evolved over millions of years probably through extensive redesigning, testing, tuning and optimization process. The powerful information processing capabilities of the immune system, such as feature extraction, pattern recognition, learning, memory, and its distributive nature provide rich metaphors for its artificial counterpart. Our study focuses on building an autonomic defense system, using some immunological metaphors for information gathering, analyzing, decision making and launching threat and attack responses. This on-going research effort is not to mimic the nature but to explore and learn valuable lessons useful for self-adaptive cyber defense systems.

Question: What is an autonomic system?


Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. Human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. We explore the use of Amazon's Mechanical Turk system, a significantly cheaper and faster method for collecting annotations from a broad base of paid non-expert contributors over the Web. We investigate five tasks: affect recognition, word similarity, recognizing textual entailment, event temporal ordering, and word sense disambiguation. For all five, we show high agreement between Mechanical Turk non-expert annotations and existing gold standard labels provided by expert labelers. For the task of affect recognition, we also show that using non-expert labels for training machine learning algorithms can be as effective as using gold standard annotations from experts. We propose a technique for bias correction that significantly improves annotation quality on two tasks. We conclude that many large labeling tasks can be effectively designed and carried out in this method at a fraction of the usual expense.

Question: What is the canadian military?


Multitechnique paraphrase alignment: A contribution to pinpointing sub-sentential paraphrases. This work uses parallel monolingual corpora for a detailed study of the task of sub-sentential paraphrase acquisition. We argue that the scarcity of this type of resource is compensated by the fact that it is the most suited type for studies on paraphrasing. We propose a large exploration of this task with experiments on two languages with five different acquisition techniques, selected for their complementarity, their combinations, as well as four monolingual corpus types of varying comparability. We report, under all conditions, a significant improvement over all techniques by validating candidate paraphrases using a maximum entropy classifier. An important result of our study is the identification of difficult-to-acquire paraphrase pairs, which are classified and quantified in a bilingual typology.

Question: What is the largest monolingual corpus?


Dynamic Behaviour of an Electronically Commutated ( Brushless DC ) Motor Drive with Back-emf Sensing. Conventionally, BLDC motors are commutated in six-step pattern with commutation controlled by position sensors. To reduce cost and complexity of the drive system, sensorless drive is preferred. The existing sensorless control scheme with the conventional back EMF sensing based on motor neutral voltage for BLDC has certain drawbacks, which limit its applications. This paper presents the dynamic behaviour of an analytical and circuit model of a Brushless DC (BLDC) motors with back emf sensing. The circuit model was simulated using LTspice and the results obtained were compared with the experimental results. The value of the motor constant and the back emf measured from the experiment agreed with the simulated model. The starting behaviour of the motor, changing of load torque when current are varied and disturbance of sensing method at peak load shows that the dynamic behaviour results of the experiment obtained from oscilloscope are similar to the simulated value.

Question: What is the back emf of a BLDC motor?


Software developers' perceptions of productivity. The better the software development community becomes at creating software, the more software the world seems to demand. Although there is a large body of research about measuring and investigating productivity from an organizational point of view, there is a paucity of research about how software developers, those at the front-line of software construction, think about, assess and try to improve their productivity. To investigate software developers' perceptions of software development productivity, we conducted two studies: a survey with 379 professional software developers to help elicit themes and an observational study with 11 professional software developers to investigate emergent themes in more detail. In both studies, we found that developers perceive their days as productive when they complete many or big tasks without significant interruptions or context switches. Yet, the observational data we collected shows our participants performed significant task and activity switching while still feeling productive. We analyze such apparent contradictions in our findings and use the analysis to propose ways to better support software developers in a retrospection and improvement of their productivity through the development of new tools and the sharing of best practices.

Question: How do software developers perceive their productivity?


Formalizing agility, part 2: how an agile organization embraced the CMMI. Most large IT organizations need the best of both worlds - working software that supports ever-changing business needs, and a process for delivering software that is predictable, trainable, and auditable. Organizations with agile software teams often receive timely, cost-effective solutions of sufficient quality. Organizations with formal processes often benefit from industry-recognized certifications and robust process improvement mechanisms. Rarely does a single, large IT organization achieve both. DTE Energy has such a combination: its lightweight yet CMMI-compatible methodology is now used within its 600+ person IT organization to deliver and support working software. Its small teams embrace core agile principles as they provide "just enough" solutions that satisfy maturing business needs. Yet they passed two SCAMPI appraisals toward formal CMMI Level III accreditation, scheduled for mid-2006. This report extends the Agile 2005 experience report on DTE Energy's agile IT organization's journey toward CMMI staged maturity accreditation. This report briefly recaps their seven years of agile experience, presents governance mechanisms and change management techniques, and highlights their four-release, one-year plan for CMMI Level III accreditation. Finally, this report offers suggestions on embracing a formal process framework that are applicable to any organization

Question: How to formalize agility?


Open circuit fault detection in PWM voltage source inverter for PMSM drive system. In this paper, a simple and low-cost open-circuit fault detection and identification method for a pulse-width modulated (PWM) voltage-source inverter (VSI) employing a permanent magnet synchronous motor is proposed. An open-circuit fault of a power switch in the PWM VSI changes the corresponding terminal voltage and introduces the voltage distortions to each phase voltage. The proposed open-circuit fault diagnosis method employs the model reference adaptive system techniques and requires no additional sensors or electrical devices to detect the fault condition and identify the faulty switch. The proposed method has the features of fast diagnosis time, simple structure, and being easily inserted to the existing control algorithms as a subroutine without major modifications. The simulations and experiments are carried out and the results show the effectiveness of the proposed method.

Question: How to detect open circuit fault in PWM VSI?


Novel high efficiency broadband Ku band power combiner. High power solid-state power amplifiers require a high efficiency power dividing/combining structure to keep the power loss as low as possible. The heat sinking capability of the divider/combiner also limits its maximum output power with continues wave (CW) configuration. In this paper, we introduce a novel 8-way Ku band power divider/combiner system, it demonstrate advantages of low loss, broadband and good heat sinking capability simultaneously. As its sub-components, low loss probes for waveguide-to-microstrip transition and low loss broadband 1-to-2 power combiners are designed and fabricated. The measured back-to-back insertion loss of the whole 8-way power combiner is lower than 0.5dB in the whole Ku band, and the corresponding combining efficiency is as high as 94.5%. The simulated thermal resistance of the system is as low as 0.21°C/W, indicating the proposed power combiner is able to produce 50W of CW output power with commercial available Monolithic Microwave Integrated Circuits (MMICs).

Question: What is the power of the combiner?


Impact of research on practice in the field of inspections, reviews and walkthroughs: learning from successful industrial uses. Software inspections, reviews, and walkthroughs have become a standard process component in many software development domains. Maturity level 3 of the CMM-I requires establishment of peer reviews [12] and substantial sustained improvements in quality and productivity have been reported as a result of using reviews ([16], [21], [22], [27]). The NSF Impact project identifies the degree to which these industrial success cases have been instigated and improved by research in software engineering.  This research identifies that there is widespread adoption of inspections, reviews or walkthroughs but that companies do not generally exploit their full potential. However there exist sustained industrial success cases with respect to the wide-spread and measurably successful application of them. It also identifies research in software engineering that can be credibly documented as having influenced the industrial success cases. Credible documentation may exist in the form of publications or documented reports by witnesses. Due to the semi-formal nature of inspections, reviews, and walkthroughs, a specific focus is given to empirical research results as motivators for adoption. Through the examination of one detailed case study, it is shown that software engineering research has had a significant impact on practice and that the impact can be traced in this case from research to that practice. The case study chosen provides evidence of both success and failure regarding sustained application in practice.  Thus the analysis of historic impact chains of research reveals a clear impact of software engineering research on sustained industrial success for inspections, reviews and walkthroughs. More importantly, in impact chains where the empirical results have not been established, we conclude that success has not been achieved or has not been sustained.

Question: What is the impact of research on practice in the field of inspections, reviews and walkthroughs?


Study of battery modeling using mathematical and circuit oriented approaches. Energy storage improves the efficiency and reliability of the electric utility system. The most common device used for storing electrical energy is batteries. To investigate power converter-based charge and discharge control of a battery storage device, effective battery models are critically needed. This paper presents a comparison study of mathematical and circuit-oriented battery models with a focus on lead-acid batteries that are normally used for large power storage applications. The paper shows how mathematical and circuit-oriented battery models are developed to reflect typical battery electrochemical properties. The relation between mathematical and circuit-oriented battery models is analyzed in the paper. Comparison study is made to investigate the difference and complexity in parameter extraction using the two different modeling approaches. The paper shows that the fundamental battery electromechanical relationship is usually built into the battery mathematical model but is not directly available in the circuit-oriented model. In terms of the computational complexity, the circuit-oriented battery model requires much expensive computing resources. Performance study is conducted to evaluate various factors that may affect the behavior of the mathematical battery models.

Question: What is the difference between mathematical and circuit-oriented battery models?


Information Fusion for Diabetic Retinopathy CAD in Digital Color Fundus Photographs. The purpose of computer-aided detection or diagnosis (CAD) technology has so far been to serve as a second reader. If, however, all relevant lesions in an image can be detected by CAD algorithms, use of CAD for automatic reading or prescreening may become feasible. This work addresses the question how to fuse information from multiple CAD algorithms, operating on multiple images that comprise an exam, to determine a likelihood that the exam is normal and would not require further inspection by human operators. We focus on retinal image screening for diabetic retinopathy, a common complication of diabetes. Current CAD systems are not designed to automatically evaluate complete exams consisting of multiple images for which several detection algorithm output sets are available. Information fusion will potentially play a crucial role in enabling the application of CAD technology to the automatic screening problem. Several different fusion methods are proposed and their effect on the performance of a complete comprehensive automatic diabetic retinopathy screening system is evaluated. Experiments show that the choice of fusion method can have a large impact on system performance. The complete system was evaluated on a set of 15 000 exams (60 000 images). The best performing fusion method obtained an area under the receiver operator characteristic curve of 0.881. This indicates that automated prescreening could be applied in diabetic retinopathy screening programs.

Question: How to fuse information from multiple CAD algorithms, operating on multiple images that comprise an exam, to determine a likelihood that the exam is normal and would not require further inspection by human operators.


Agent-Based Modeling of the Spread of Influenza-Like Illness in an Emergency Department: A Simulation Study. The objective of this paper was to develop an agent based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C + + using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that be came infected in one day within the simulation was the dependent variable. The results suggest that within the given instance con text, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Question: What is agent-based modeling?


Compact Rep-Rate GW Pulsed Generator Based on Forming Line With Built-In High-Coupling Transformer. In this paper, a compact rep-rate GW pulsed power generator is developed. First, its three key subsystems are theoretically analyzed, engineering designed, and experimentally investigated, respectively. The emphases are put on these four problems: the theoretical analysis of the voltage distribution across the conical secondary windings of the high-coupling transformer, the investigation of the high energy storage density dielectric used in the pulse forming line, the choice of the gas flow velocity of the gas blowing system, and theoretical analysis of the passive stability of the pulsed power generator operated in rep-rate mode. Second, the developed pulsed power generator is described in detail. It has a 0.2-m diameter, a 1.0-m length, and a 20- Ω wave impedance. Across a 100- Ω resistive dummy load, it can steadily operate at a 300-kV output voltage in 50-Hz rep-rate and 250 kV in 150 Hz without gas blowing system. The average power is ~ 1 kW. Finally, the pulsed power generator is applied to drive a relativistic backward-wave oscillator, generating a high-power microwave with peak output power of 200 MW and duration (full-width at half-maximum) of 5 ns in 150-Hz rep-rate. These efforts set a good foundation for the development of a compact rep-rate pulsed power generator and show a promising application for the future.

Question: What is the difference between a pulsed power generator and a pulsed power source?


Order-Preserving Encryption for Numeric Data. Encryption is a well established technology for protecting sensitive data. However, once encrypted, data can no longer be easily queried aside from exact matches. We present an order-preserving encryption scheme for numeric data that allows any comparison operation to be directly applied on encrypted data. Query results produced are sound (no false hits) and complete (no false drops). Our scheme handles updates gracefully and new values can be added without requiring changes in the encryption of other values. It allows standard databse indexes to be built over encrypted tables and can easily be integrated with existing database systems. The proposed scheme has been designed to be deployed in application environments in which the intruder can get access to the encrypted database, but does not have prior domain information such as the distribution of values and annot encrypt or decrypt arbitrary values of his choice. The encryption is robust against estimation of the true value in such environments.

Question: What is the order-preserving encryption for numeric data?


Learning to Segment Instances in Videos with Spatial Propagation Network. We propose a deep learning-based framework for instance-level object segmentation. Our method mainly consists of three steps. First, We train a generic model based on ResNet-101 for foreground/background segmentations. Second, based on this generic model, we fine-tune it to learn instance-level models and segment individual objects by using augmented object annotations in first frames of test videos. To distinguish different instances in the same video, we compute a pixel-level score map for each object from these instance-level models. Each score map indicates the objectness likelihood and is only computed within the foreground mask obtained in the first step. To further refine this per frame score map, we learn a spatial propagation network. This network aims to learn how to propagate a coarse segmentation mask spatially based on the pairwise similarities in each frame. In addition, we apply a filter on the refined score map that aims to recognize the best connected region using spatial and temporal consistencies in the video. Finally, we decide the instance-level object segmentation in each video by comparing score maps of different instances.

Question: How to segment instances in videos?


Towards Contactless, Low-Cost and Accurate 3D Fingerprint Identification. Human identification using fingerprint impressions has been widely studied and employed for more than 2000 years. Despite new advancements in the 3D imaging technologies, widely accepted representation of 3D fingerprint features and matching methodology is yet to emerge. This paper investigates 3D representation of widely employed 2D minutiae features by recovering and incorporating (i) minutiae height z and (ii) its 3D orientation φ information and illustrates an effective matching strategy for matching popular minutiae features extended in 3D space. One of the obstacles of the emerging 3D fingerprint identification systems to replace the conventional 2D fingerprint system lies in their bulk and high cost, which is mainly contributed from the usage of structured lighting system or multiple cameras. This paper attempts to addresses such key limitations of the current 3D fingerprint technologies bydeveloping the single camera-based 3D fingerprint identification system. We develop a generalized 3D minutiae matching model and recover extended 3D fingerprint features from the reconstructed 3D fingerprints. 2D fingerprint images acquired for the 3D fingerprint reconstruction can themselves be employed for the performance improvement and have been illustrated in the work detailed in this paper. This paper also attempts to answer one of the most fundamental questions on the availability of inherent discriminableinformation from 3D fingerprints. The experimental results are presented on a database of 240 clients 3D fingerprints, which is made publicly available to further research efforts in this area, and illustrate the discriminant power of 3D minutiae representation andmatching to achieve performance improvement.

Question: How to improve the performance of 3D fingerprint identification?


Introducing Entity-Based Concepts to Business Process Modeling. The so-called Internet of Things (IoT) that comprises interconnected physical devices such as sensor networks and its technologies like Radio Frequency Identification (RFID) is increasingly adopted in many industries and thus becomes highly relevant for process modeling and execution. As BPMN 2.0 does not yet consider the idiosyncrasies of real-world entities we suggest new modeling concepts for a physical entity as well as a sensing task and an actuation task to make BPMN IoT-aware.

Question: What is the Internet of Things?


Goubau-Line Leaky-Wave Antenna for Wide-Angle Beam Scanning From Backfire to Endfire. A Goubau-line leaky-wave antenna (LWA) with a large scanning angle is presented in this letter. In contrast to the conventional Goubau-line leaky wave with a small scanning angle range, this letter employed a periodically bending Goubau line, which not only brings in a periodic perturbation for leaky-wave radiation, but also enhances the scanning range due to the increased delay for each line element. The simulation and experimental results show that the proposed LWA provides $90\%$ radiation efficiency and 7–10 dBi radiation gain from backfire to endfire through broadside as frequency changes. The proposed antenna features good radiation performance and has a compact and low-profile configuration.

Question: What is a Goubau-line leaky-wave antenna?


Evaluation of machine learning techniques for network intrusion detection. Network traffic anomaly may indicate a possible intrusion in the network and therefore anomaly detection is important to detect and prevent the security attacks. The early research work in this area and commercially available Intrusion Detection Systems (IDS) are mostly signature-based. The problem of signature based method is that the database signature needs to be updated as new attack signatures become available and therefore it is not suitable for the real-time network anomaly detection. The recent trend in anomaly detection is based on machine learning classification techniques. We apply seven different machine learning techniques with information entropy calculation to Kyoto 2006+ data set and evaluate the performance of these techniques. Our findings show that, for this particular data set, most machine learning techniques provide higher than 90% precision, recall and accuracy. However, using area under the Receiver Operating Curve (ROC) metric, we find that Radial Basis Function (RBF) performs the best among the seven algorithms studied in this work.

Question: What is the difference between a signature and a classifier?


River flow estimation using adaptive neuro fuzzy inference system. Accurate estimation of River flow changes is a quite important problem for a wise and sustainable use. Such a problem is crucial to the works and decisions related to the water resources and management. In this study, an adaptive network-based fuzzy inference system (ANFIS) approach was used to construct a River flow forecasting system. In particular, the applicability of ANFIS as an estimation model for River flow was investigated. To illustrate the applicability and capability of the ANFIS, the River Great Menderes, located the west of Turkey and the most important water resource of Great Menderes Catchment's, was chosen as a case study area. The advantage of this method is that it uses the input–output data sets. Totally 5844 daily data sets collected in 1985–2000 years were used to estimate the River flow. The models having various input structures were constructed and the best structure was investigated. In addition four various training/testing data sets were constructed by cross validation methods and the best data set was investigated. The performance of the ANFIS models in training and testing sets were compared with the observations and also evaluated. The results indicated that the ANFIS can be applied successfully and provide high accuracy and reliability for River flow estimation. © 2006 IMACS. Published by Elsevier B.V. All rights reserved.

Question: What is the advantage of using an adaptive neuro fuzzy inference system?


Big Data , Digital Media , and Computational Social Science : Possibilities and Perils. We live life in the network. We check our e-mails regularly, make mobile phone calls from almost any location ... make purchases with credit cards ... [and] maintain friendships through online social networks. ... These transactions leave digital traces that can be compiled into comprehensive pictures of both individual and group behavior, with the potential to transform our understanding of our lives, organizations, and societies.

Question: What is the potential of big data?


The habitual consumer. Consumers sometimes act like creatures of habit, automatically repeating past behavior with little regard to current goals and valued outcomes. To explain this phenomenon, we show that habits are a specific form of automaticity in which responses are directly cued by the contexts (e.g., locations, preceding actions) that consistently covaried with past performance. Habits are prepotent responses that are quick to activate in memory over alternatives and that have a slow-to-modify memory trace. In daily life, the tendency to act on habits is compounded by everyday demands, including time pressures, distraction, and self-control depletion. However, habits are not immune to deliberative processes. Habits are learned largely as people pursue goals in daily life, and habits are broken through the strategic deployment of effortful self-control. Also, habits influence the post hoc inferences that people make about their behavior. © 2009 Society for Consumer Psychology. Published by Elsevier Inc. All rights reserved.

Question: What is the difference between habits and automaticity?


Semantic Framework for Comparison Structures in Natural Language. Comparison is one of the most important phenomena in language for expressing objective and subjective facts about various entities. Systems that can understand and reason over comparative structure can play a major role in the applications which require deeper understanding of language. In this paper we present a novel semantic framework for representing the meaning of comparative structures in natural language, which models comparisons as predicate-argument pairs interconnected with semantic roles. Our framework supports not only adjectival, but also adverbial, nominal, and verbal comparatives. With this paper, we provide a novel dataset of gold-standard comparison structures annotated according to our semantic framework.

Question: What is the meaning of the word "comparative"?


Neonatal Abstinence Syndrome and High School Performance.. BACKGROUND AND OBJECTIVES Little is known of the long-term, including school, outcomes of children diagnosed with Neonatal abstinence syndrome (NAS) (International Statistical Classification of Disease and Related Problems [10th Edition], Australian Modification, P96.1).   METHODS Linked analysis of health and curriculum-based test data for all children born in the state of New South Wales (NSW), Australia, between 2000 and 2006. Children with NAS (n = 2234) were compared with a control group matched for gestation, socioeconomic status, and gender (n = 4330, control) and with other NSW children (n = 598 265, population) for results on the National Assessment Program: Literacy and Numeracy, in grades 3, 5, and 7.   RESULTS Mean test scores (range 0-1000) for children with NAS were significantly lower in grade 3 (359 vs control: 410 vs population: 421). The deficit was progressive. By grade 7, children with NAS scored lower than other children in grade 5. The risk of not meeting minimum standards was independently associated with NAS (adjusted odds ratio [aOR], 2.5; 95% confidence interval [CI], 2.2-2.7), indigenous status (aOR, 2.2; 95% CI, 2.2-2.3), male gender (aOR, 1.3; 95% CI, 1.3-1.4), and low parental education (aOR, 1.5; 95% CI, 1.1-1.6), with all Ps < .001.   CONCLUSIONS A neonatal diagnostic code of NAS is strongly associated with poor and deteriorating school performance. Parental education may decrease the risk of failure. Children with NAS and their families must be identified early and provided with support to minimize the consequences of poor educational outcomes.

Question: What is the risk of not meeting minimum standards?


Cloud RAN for Mobile Networks—A Technology Overview. Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user's needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and possible cost savings on baseband resources. Furthermore, it improves network capacity by performing load balancing and cooperative processing of signals originating from several base stations. This paper surveys the state-of-the-art literature on C-RAN. It can serve as a starting point for anyone willing to understand C-RAN architecture and advance the research on C-RAN.

Question: What is the state of the art on cloud radio access network?


A scoping review of scoping reviews: advancing the approach and enhancing the consistency. BACKGROUND The scoping review has become an increasingly popular approach for synthesizing research evidence. It is a relatively new approach for which a universal study definition or definitive procedure has not been established. The purpose of this scoping review was to provide an overview of scoping reviews in the literature.   METHODS A scoping review was conducted using the Arksey and O'Malley framework. A search was conducted in four bibliographic databases and the gray literature to identify scoping review studies. Review selection and characterization were performed by two independent reviewers using pretested forms.   RESULTS The search identified 344 scoping reviews published from 1999 to October 2012. The reviews varied in terms of purpose, methodology, and detail of reporting. Nearly three-quarter of reviews (74.1%) addressed a health topic. Study completion times varied from 2 weeks to 20 months, and 51% utilized a published methodological framework. Quality assessment of included studies was infrequently performed (22.38%).   CONCLUSIONS Scoping reviews are a relatively new but increasingly common approach for mapping broad topics. Because of variability in their conduct, there is a need for their methodological standardization to ensure the utility and strength of evidence.

Question: What is a scoping review?


Continuous Electrowetting of Non-toxic Liquid Metal for RF Applications. Continuous electrowetting (CEW) is demonstrated to be an effective actuation mechanism for reconfigurable radio frequency (RF) devices that use non-toxic liquid-metal tuning elements. Previous research has shown CEW is an efficient means of electrically inducing motion in a liquid-metal slug, but precise control of the slug's position within fluidic channels has not been demonstrated. Here, the precise positioning of liquid-metal slugs is achieved using CEW actuation in conjunction with channels designed to minimize the liquid-metal surface energy at discrete locations. This approach leverages the high surface tension of liquid metal to control its resting position with submillimeter accuracy. The CEW actuation and fluidic channel design were optimized to create reconfigurable RF devices. In addition, solutions for the reliable actuation of a gallium-based, non-toxic liquid-metal alloy (Galinstan) are presented that mitigate the tendency of the alloy to form a surface oxide layer capable of wetting to the channel walls, inhibiting motion. A reconfigurable slot antenna utilizing these techniques to achieve a 15.2% tunable frequency bandwidth is demonstrated.

Question: How does electrowetting work?


Recognizing Abnormal Heart Sounds Using Deep Learning. The work presented here applies deep learning to the task of automated cardiac auscultation, i.e. recognizing abnormalities in heart sounds. We describe an automated heart sound classification algorithm that combines the use of time-frequency heat map representations with a deep convolutional neural network (CNN). Given the cost-sensitive nature of misclassification, our CNN architecture is trained using a modified loss function that directly optimizes the trade-off between sensitivity and specificity. We evaluated our algorithm at the 2016 PhysioNet Computing in Cardiology challenge where the objective was to accurately classify normal and abnormal heart sounds from single, short, potentially noisy recordings. Our entry to the challenge achieved a final specificity of 0.95, sensitivity of 0.73 and overall score of 0.84. We achieved the greatest specificity score out of all challenge entries and, using just a single CNN, our algorithm differed in overall score by only 0.02 compared to the top place finisher, which used an ensemble approach.

Question: How does deep learning work?


Probabilistic Similarity Logic. Many machine learning applications require the ability to learn from and reason about noisy multi-relational data. To address this, several effective representations have been developed that provide both a language for expressing the structural regularities of a domain, and principled support for probabilistic inference. In addition to these two aspects, however, many applications also involve a third aspect–the need to reason about similarities–which has not been directly supported in existing frameworks. This paper introduces probabilistic similarity logic (PSL), a general-purpose framework for joint reasoning about similarity in relational domains that incorporates probabilistic reasoning about similarities and relational structure in a principled way. PSL can integrate any existing domainspecific similarity measures and also supports reasoning about similarities between sets of entities. We provide efficient inference and learning techniques for PSL and demonstrate its effectiveness both in common relational tasks and in settings that require reasoning about similarity.

Question: What is the difference between probabilistic similarity logic and probabilistic logic?


Algorithm 799: revolve: an implementation of checkpointing for the reverse or adjoint mode of computational differentiation. In its basic form, the reverse mode of computational differentiation yields the gradient of a scalar-valued function at a cost that is a small multiple of the computational work needed to evaluate the function itself. However, the corresponding memory requirement is proportional to the run-time of the evaluation program. Therefore, the practical applicability of the reverse mode in its original formulation is limited despite the availability of ever larger memory systems. This observation leads to the development of checkpointing schedules to reduce the storage requirements. This article presents the function revolve, which generates checkpointing schedules that are provably optimal with regard to a primary and a secondary criterion. This routine is intended to be used as an explicit "controller" for running a time-dependent applications program.

Question: What is the cost of the reverse mode of computational differentiation?


met*: A Method for Discriminating Matonymy and Metaphor by Computer. The met* method distinguishes selected examples of metonymy from metaphor and from literalness and anomaly in short English sentences. In the met* method, literalness is distinguished because it satisfies contextual constraints that the nonliteral others all violate. Metonymy is discriminated from metaphor and anomaly in a way that [1] supports Lakoff and Johnson's (1980) view that in metonymy one entity stands for another whereas in metaphor one entity is viewed as another, [2] permits chains of metonymies (Reddy 1979), and [3] allows metonymies to co-occur with instances of either literalness, metaphor, or anomaly. Metaphor is distinguished from anomaly because the former contains a relevant analogy, unlike the latter. The met* method is part of Collative Semantics, a semantics for natural language processing, and has been implemented in a computer program called meta5. Some examples of meta5's analysis of metaphor and metonymy are given. The met* method is compared with approaches from artificial intelligence, linguistics, philosophy, and psychology.

Question: What is the met* method?


A Surgical Palpation Probe With 6-Axis Force/Torque Sensing Capability for Minimally Invasive Surgery. A novel surgical palpation probe installing a miniature 6-axis force/torque (F/T) sensor is presented for robot-assisted minimally invasive surgery. The 6-axis F/T sensor is developed by using the capacitive transduction principle and a novel capacitance sensing method. The sensor consists of only three parts, namely a sensing printed circuit board, a deformable part, and a base part. The simple configuration leads to simpler manufacturing and assembly processes in conjunction with high durability and low weight. In this study, a surgical instrument installed with a surgical palpation probe is implemented. The 6-axis F/T sensing capability of the probe has been experimentally validated by comparing it with a reference 6-axis F/T sensor. Finally, a vivo tissue palpation task is performed in a simulated surgical environment with an animal organ and a relatively hard simulated cancer buried under the surface of the organ.

Question: What is a surgical palpation probe?


Reduction in gravitational torques of an industrial robot equipped with 2 DOF passive counterbalance mechanisms. In most 6 DOF robot arms, considerable amounts of gravitational torques due to the robot's own weight are applied to pitch joints of the robot, which causes most arms to use high capacity motors and speed reducers. A spring-based counterbalance mechanism can compensate for this gravitational torque, thus leading to a significant reduction in the effect of gravity. However, a simple installation of counterbalance mechanisms at each pitch joint does not work properly because the gravitational torque at each joint is dependent also on the other joints. To achieve multi-DOF counterbalancing, we propose a parallelogram linkage combined with dual counterbalance mechanisms, each being composed of a slider-crank mechanism and springs. Simulations and experimental results showed that the counterbalance robot arm based on the proposed counterbalance mechanisms effectively reduced the torques required to support the robot mass, thus allowing the prospective use of much smaller motors and speed reducers than traditional industrial robots.

Question: How can we reduce the gravitational torque of a robot?


A printed 16 ports massive MIMO antenna system with directive port beams. The design of a massive multiple-input-multiple-output (mMIMO) antenna system based on patch antennas is presented in this paper. The array consists of 16 ports, each port consists of a 2×2 patch antenna array with different phase excitation at each element to tilt the beam toward different directions to provide lower correlation coefficient values. A fixed progressive phase feed network is designed to provide the beam tilts. The proposed antenna system is designed using a 3-layer FR4 substrate with total size of 33.33×33.33×0.16 cm3.

Question: What is a massive MIMO antenna system?


A Clinical Study of 35 Cases of Pincer Nails. BACKGROUND Pincer nail is a nail deformity characterized by transverse overcurvature of the nail plate. Pincer nail can affect a patient's quality of life due to its chronic, recurrent course; however, there have been no clinical studies on the pincer nail condition in Korean patients.   OBJECTIVE The purpose of this study was to characterize the clinical findings and treatment of pincer nail. In addition, possible etiological factors were considered, and treatment efficacy was evaluated.   METHODS The medical records and clinical photographs of 35 patients (12 males, 23 females) who were diagnosed with pincer nail between August 1, 2005 and July 31, 2009 were studied.   RESULTS Patient age ranged from 10 to 77 (52.09±17.26) years, and there was a predominance of female (23 out of 35 patients, F:M=2:1). The mean duration of the disorder was 7.45 years (range 0.25~40); 85% had pincer nail for at least 1 year. In addition, 40% had a history of previous treatment and recurrence. There were 82.8% patients with the common type of pincer nails. The most commonly involved nails were both great toenails. Among 35 patients, nail grinding was started in 30 patients, and 25 patients showed clinical improvement with nail grinding. The width index increased and the height index decreased after treatment. The mean follow up period was 8.42 months (range 1~27), and 7 patients showed recurrence after 8.8 months (range 2~20). Among 35 patients, 5 patients were treated with nail extraction with matricectomy, and the symptoms resolved immediately. The mean follow up period was 7.6 months (range 0~19), and recurrence was not observed. Onychomycosis was also present in 37.1% of patients, and itraconazole pulse therapy for 3 months was added.   CONCLUSION The results of this study demonstrate the clinical features of pincer nail in Korean patients. The findings show that the common type of pincer nail was most common, and nail grinding as a c

Question: What is the most common type of pincer nail?


FPGA implementations of fast fourier transforms for real-time signal and image processing. Applications based on Fast Fourier Transform (FFT) such as signal and image processing require high computational power, plus the ability to experiment with algorithms. Reconfigurable hardware devices in the form of Field Programmable Gate Arrays (FPGAs) have been proposed as a way of obtaining high performance at an economical price. At present, however, users must program FPGAs at a very low level and have a detailed knowledge of the architecture of the device being used. To try to reconcile the dual requirements of high performance and ease of development, this paper reports on the design and realisation of a High Level framework for the implementation of 1-D and 2-D FFTs for real-time applications. Results show that the parallel implementation of 2-D FFT achieves virtually linear speed-up and real-time performance for large matrix sizes. Finally, an FPGA-based parametrisable environment based on the developed parallel 2-D FFT architecture is presented as a solution for frequencydomain image filtering application.

Question: What is a high level framework?


Help from the Sky: Leveraging UAVs for Disaster Management. This article presents a vision for future unmanned aerial vehicles (UAV)-assisted disaster management, considering the holistic functions of disaster prediction, assessment, and response. Here, UAVs not only survey the affected area but also assist in establishing vital wireless communication links between the survivors and nearest available cellular infrastructure. A perspective of different classes of geophysical, climate-induced, and meteorological disasters based on the extent of interaction between the UAV and terrestrially deployed wireless sensors is presented in this work, with suitable network architectures designed for each of these cases. The authors outline unique research challenges and possible solutions for maintaining connected aerial meshes for handoff between UAVs and for systems-specific, security- and energy-related issues. This article is part of a special issue on drones.

Question: What is the difference between a drone and a UAV?


Health-related rumour detection on Twitter. In the last years social networks have emerged as a critical mean for information spreading. In spite of all the positive consequences this phenomenon brings, unverified and instrumentally relevant information statements in circulation, named as rumours, are becoming a potential threat to the society. Recently, there have been several studies on topic-independent rumour detection on Twitter. In this paper we present a novel rumour detection system which focuses on a specific topic, that is health-related rumours on Twitter. To this aim, we constructed a new subset of features including influence potential and network characteristics features. We tested our approach on a real dataset observing promising results, as it is able to correctly detect about 89% of rumours, with acceptable levels of precision.

Question: What is a rumour?


Existence and Stability of Equilibrium of DC Microgrid With Constant Power Loads. Constant power loads (CPLs) are often the cause of instability and no equilibrium of dc microgrids. In this study, we analyze the existence and stability of equilibrium of dc microgirds with CPLs and the sufficient conditions for them are provided. To derive the existence of system equilibrium, we transform the problem of quadratic equation solvability into the existence of a fixed point for an increasing fractional mapping. Then, the sufficient condition based on the Tarski fixed-point theorem is derived. It is less conservative compared with the existing results. Moreover, we adopt the small-signal model to predict the system qualitative behavior around equilibrium. The analytic conditions of robust stability are determined by analyzing quadratic eigenvalue. Overall, the obtained conditions provide the references for building reliable dc microgrids. The simulation results verify the correctness of the proposed conditions.

Question: How to solve a quadratic equation?


Generating entangled photon pairs in a parallel crystal geometry. We present recent findings towards developing brighter entangled photon sources in critically phase matched (CPM) nonlinear crystals. Specifically, we use type-I collinear phase matching at non-degenerate wavelengths in parallel β-Barium Borate (BBO) crystals to generate pairs of polarization entangled photons for free-space quantum key distribution (QKD). We first review the entangled source configuration and then discuss ways to further improve the source brightness by means of tailoring the pump and collection modes. We present preliminary results that may lead to brighter entangled photon sources that are intrinsically robust to changes in their environment.

Question: How to generate entangled photon pairs in a parallel crystal geometry?


New developments in our understanding of acne pathogenesis and treatment.. Interest in sebaceous gland physiology and its diseases is rapidly increasing. We provide a summarized update of the current knowledge of the pathobiology of acne vulgaris and new treatment concepts that have emerged in the last 3 years (2005-2008). We have tried to answer questions arising from the exploration of sebaceous gland biology, hormonal factors, hyperkeratinization, role of bacteria, sebum, nutrition, cytokines and toll-like receptors (TLRs). Sebaceous glands play an important role as active participants in the innate immunity of the skin. They produce neuropeptides, excrete antimicrobial peptides and exhibit characteristics of stem cells. Androgens affect sebocytes and infundibular keratinocytes in a complex manner influencing cellular differentiation, proliferation, lipogenesis and comedogenesis. Retention hyperkeratosis in closed comedones and inflammatory papules is attributable to a disorder of terminal keratinocyte differentiation. Propionibacterium acnes, by acting on TLR-2, may stimulate the secretion of cytokines, such as interleukin (IL)-6 and IL-8 by follicular keratinocytes and IL-8 and -12 in macrophages, giving rise to inflammation. Certain P. acnes species may induce an immunological reaction by stimulating the production of sebocyte and keratinocyte antimicrobial peptides, which play an important role in the innate immunity of the follicle. Qualitative changes of sebum lipids induce alteration of keratinocyte differentiation and induce IL-1 secretion, contributing to the development of follicular hyperkeratosis. High glycemic load food and milk may induce increased tissue levels of 5alpha-dihydrotestosterone. These new aspects of acne pathogenesis lead to the considerations of possible customized therapeutic regimens. Current research is expected to lead to innovative treatments in the near future.

Question: What is acne?


Semantic Similarity Strategies for Job Title Classification. Automatic and accurate classification of items enables numerous downstream applications in many domains. These applications can range from faceted browsing of items to product recommendations and big data analytics. In the online recruitment domain, we refer to classifying job ads to pre-defined or custom occupation categories as job title classification. A large-scale job title classification system can power various downstream applications such as semantic search, job recommendations and labor market analytics. In this paper, we discuss experiments conducted to improve our in-house job title classification system. The classification component of the system is composed of a two-stage coarse and fine level classifier cascade that classifies input text such as job title and/or job ads to one of the thousands of job titles in our taxonomy. To improve classification accuracy and effectiveness, we experiment with various semantic representation strategies such as average W2V vectors and document similarity measures such as Word Movers Distance (WMD). Our initial results show an overall improvement in accuracy of Carotene[1].

Question: How to improve the accuracy of job title classification?


How to practice person‐centred care: A conceptual framework. BACKGROUND Globally, health-care systems and organizations are looking to improve health system performance through the implementation of a person-centred care (PCC) model. While numerous conceptual frameworks for PCC exist, a gap remains in practical guidance on PCC implementation.   METHODS Based on a narrative review of the PCC literature, a generic conceptual framework was developed in collaboration with a patient partner, which synthesizes evidence, recommendations and best practice from existing frameworks and implementation case studies. The Donabedian model for health-care improvement was used to classify PCC domains into the categories of "Structure," "Process" and "Outcome" for health-care quality improvement.   DISCUSSION The framework emphasizes the structural domain, which relates to the health-care system or context in which care is delivered, providing the foundation for PCC, and influencing the processes and outcomes of care. Structural domains identified include: the creation of a PCC culture across the continuum of care; co-designing educational programs, as well as health promotion and prevention programs with patients; providing a supportive and accommodating environment; and developing and integrating structures to support health information technology and to measure and monitor PCC performance. Process domains describe the importance of cultivating communication and respectful and compassionate care; engaging patients in managing their care; and integration of care. Outcome domains identified include: access to care and Patient-Reported Outcomes.   CONCLUSION This conceptual framework provides a step-wise roadmap to guide health-care systems and organizations in the provision PCC across various health-care sectors.

Question: How to practice person-centred care: A conceptual framework


Measuring the Physical in Physical Attractiveness : Quasi-Experiments on the Sociobiology of Female Facial Beauty. Two quasi-experiments investigated the relation between specific adult female facial features and the attraction, attribution, and altruistic responses of adult males. Precise measurements were obtained of the relative size of 24 facial features in an international sample of photographs of 50 females. Male subjects provided ratings of the attractiveness of each of the females. Positively correlated with attractiveness ratings were the neonate features of large eyes, small nose, and small chin; the maturity features of prominent cheekbones and narrow cheeks; and the expressive features of high eyebrows, large pupils, and large smile. A second study asked males to rate the personal characteristics of 16 previously measured females. The males were also asked to indicate the females for whom they would be most inclined to perform altruistic behaviors, and select for dating, sexual behavior, and childrearing. The second study replicated the correlations of feature measurements with attractiveness. Facial features also predicted personality attributions, altruistic inclinations, and reproductive interest. Sociobiological interpretations are discussed.

Question: What is the relation between facial features and attractiveness?


The FaceSketchID System: Matching Facial Composites to Mugshots. Facial composites are widely used by law enforcement agencies to assist in the identification and apprehension of suspects involved in criminal activities. These composites, generated from witness descriptions, are posted in public places and media with the hope that some viewers will provide tips about the identity of the suspect. This method of identifying suspects is slow, tedious, and may not lead to the timely apprehension of a suspect. Hence, there is a need for a method that can automatically and efficiently match facial composites to large police mugshot databases. Because of this requirement, facial composite recognition is an important topic for biometrics researchers. While substantial progress has been made in nonforensic facial composite (or viewed composite) recognition over the past decade, very little work has been done using operational composites relevant to law enforcement agencies. Furthermore, no facial composite to mugshot matching systems have been documented that are readily deployable as standalone software. Thus, the contributions of this paper include: 1) an exploration of composite recognition use cases involving multiple forms of facial composites; 2) the FaceSketchID System, a scalable, and operationally deployable software system that achieves state-of-the-art matching accuracy on facial composites using two algorithms (holistic and component based); and 3) a study of the effects of training data on algorithm performance. We present experimental results using a large mugshot gallery that is representative of a law enforcement agency's mugshot database. All results are compared against three state-of-the-art commercial-off-the-shelf face recognition systems.

Question: How does the face sketch id system work?


A Dual-Polarized Dual-Band Antenna With High Gain for 2G/3G/LTE Indoor Communications. A compact dual-polarized dual-band omnidirectional antenna with high gain is presented for 2G/3G/LTE communications, which comprise two horizontal polarization (HP) and a vertical polarization (VP) elements. The upper HP element consists of four pairs of modified printed magneto-electric (ME) dipoles that are fed by a four-way power divider feeding network, and eight pieces of arc-shaped parasitic patches that are printed on both sides of the circular printed circuit board alternately. The four-way power divider feeding network together with the four pairs of ME dipoles mainly provide a stable 360° radiation pattern and high gain, while the eight pieces of patches are used to enhance the bandwidth. The lower HP element is similar to the upper one except that it do not have the parasitic patches. The VP element consists of four pairs of cone-shaped patches. Different from the HP element, the upper VP element provides the lower frequency band while the lower VP one yields the upper frequency band. The VP element and the HP element are perpendicularly arranged to obtain the compact and dual-polarized features. Measured results show that a bandwidth of 39.6% (0.77–1.15 GHz) with a gain of about 2.6 dBi and another bandwidth of 55.3% (1.66–2.93 GHz) with a gain of about 4.5 dBi can be achieved for the HP direction, while a bandwidth of 128% (0.7–3.2 GHz) with a gain of around 4.4 dBi can be acquired for the VP direction. Port isolation larger than 20 dB and low-gain variation levels within 2 dBi are also obtained. Hence, the proposed antenna is suitable for 2G/3G/LTE indoor communications.

Question: What is the gain of the antenna?


Single Shot Text Detector with Regional Attention. We present a novel single-shot text detector that directly outputs word-level bounding boxes in a natural image. We propose an attention mechanism which roughly identifies text regions via an automatically learned attentional map. This substantially suppresses background interference in the convolutional features, which is the key to producing accurate inference of words, particularly at extremely small sizes. This results in a single model that essentially works in a coarse-to-fine manner. It departs from recent FCN-based text detectors which cascade multiple FCN models to achieve an accurate prediction. Furthermore, we develop a hierarchical inception module which efficiently aggregates multi-scale inception features. This enhances local details, and also encodes strong context information, allowing the detector to work reliably on multi-scale and multi-orientation text with single-scale images. Our text detector achieves an F-measure of 77% on the ICDAR 2015 benchmark, advancing the state-of-the-art results in [18, 28]. Demo is available at: http://sstd.whuang.org/.

Question: What is the name of the text detector?


FlowTime: Dynamic Scheduling of Deadline-Aware Workflows and Ad-Hoc Jobs. With rapidly increasing volumes of data to be processed in modern data analytics, it is commonplace to run multiple data processing jobs with inter-job dependencies in a datacenter cluster, typically as recurring data processing workloads. Such a group of inter-dependent data analytic jobs is referred to as a workflow, and may have a deadline due to its mission-critical nature. In contrast, non-recurring ad-hoc jobs are typically best-effort in nature, and rather than meeting deadlines, it is desirable to minimize their average job turnaround time. The state-of-the-art scheduling mechanisms focused on meeting deadlines for individual jobs only, and are oblivious to workflow deadlines. In this paper, we present FlowTime, a new system framework designed to make scheduling decisions for workflows so that their deadlines are met, while simultaneously optimizing the performance of ad-hoc jobs. To achieve this objective, we first adopt a divide-and-conquer strategy to transform the problem of workflow scheduling to a deadline-aware job scheduling problem, and then design an efficient algorithm that tackles the scheduling problem with both deadline-aware jobs and ad-hoc jobs by solving its corresponding optimization problem directly using a linear program solver. Our experimental results have clearly demonstrated that FlowTime achieves the lowest deadline-miss rates for deadline-aware workflows and 2-10 times shorter average job turnaround time, as compared to the state-of-the-art scheduling algorithms.

Question: What is the deadline-aware scheduling algorithm?


The Effectiveness of Intrinsic and Extrinsic Motivations : A Study of Malaysian Amway Company ' s Direct Sales Forces. This research utilizes the survey questionnaire data collected in May/June 2010 from 200 Amway Company's direct sales forces in Klang Valley areas (Malaysia) to analyze the effectiveness of intrinsic and extrinsic motivation in influencing job satisfaction. The research will be analyzed using the well-established correlation analysis, regression analysis, independent sample t-test, and one-way ANOVA. There are four major findings. First, there is a relationship between intrinsic and extrinsic motivations with job satisfaction. According to the correlation value, intrinsic motivation compared to extrinsic motivation tends to contribute more in job satisfaction. Second, there are significant and positive relationship between intrinsic and extrinsic motivations and job satisfaction. Both of the intrinsic and extrinsic motivation is identified as the predictor for job satisfaction. In other words, they are both significantly contribute in better job satisfaction. Third, there is no difference between gender and intrinsic and extrinsic motivations. Hence, gender is not a factor that affects both of the intrinsic and extrinsic motivations. Lastly, the result indicates that there is a difference between age and intrinsic and extrinsic motivations. Therefore, age is the factor that influences on both intrinsic and extrinsic motivations. Last but not least, the results have demonstrated the effectiveness of intrinsic and extrinsic motivations in influencing job satisfaction among the Amway Company's direct sales forces, as well as establishing appropriate intrinsic motivations may promote higher job satisfaction.

Question: What is the difference between intrinsic and extrinsic motivation?