A flame detection algorithm based on Bag-of-Features in the YUV color space. Computer vision-based fire detection involves flame detection and smoke detection. This paper proposes a new flame detection algorithm, which is based on a Bag-of-Features technique in the YUV color space. Inspired by that the color of flame in image and video will fall in certain regions in the color space, models of flame pixels and non-flame pixels are established based on code book in the training phase in our proposal. In the testing phase, the input image is split into some N×N blocks and each block is classified respectively. In each N×N block, the pixels values in the YUV color space are extracted as features, just as in the training phase. According to the experimental results, our proposed method can reduce the number of false alarms greatly compared with an alternative algorithm, while it also ensures the accurate classification of positive samples. The classification performance of our proposed method is better than that of alternative algorithms.

Question: What is a bag of features?


Twitter Sentiment Classification on Sanders Data using Hybrid Approach. Sentiment analysis is very perplexing and massive issue in the field of social data mining. Twitter is one of the mostly used social media where people discuss on various issues in a dense way. The tweets about a particular topic give peoples' views, opinions, orientations, inclinations about that topic. In this work, we have used pre-labeled (with positive, negative and neutral opinion) tweets on particular topics for sentiment classification. Opinion score of each tweet is calculated using feature vectors. These opinion score is used to classify the tweets into positive, negative and neutral classes. Then using various machine learning classifiers the accuracy of predicted classification with respect to actual classification is being calculated and compared using supervised learning model. Along with building a sentiment classification model, analysis of tweets is being carried out by visualizing the wordcloud of tweets using R.

Question: What is the difference between supervised and unsupervised learning?


Discrete Delaunay: Boundary extraction from voxel objects. We present a discrete approach for boundary extraction from 3D image data. The proposed technique is based on the duality between the Voronoi graph computed accross the digital boundary and the Delaunay triangulation. The originality of the approach is that algorithms perform only integer arithmetic and the method does not suffer from standard round problems and numerical instabilities in the case of floating point computations. This method has been applied both on segmented anatomical structures and on manufactured objects presenting corners and edges. The experimental results show that the method allows to produce a polygonal boundary representation which is guaranteed to be a 2-manifold. This representation is successfully transformed into a triangular quality mesh which meets all topological and geometrical requirements of applications such as augmented reality or simulation.

Question: What is discrete delaunay triangulation?


X-Ray PoseNet: 6 DoF Pose Estimation for Mobile X-Ray Devices. Precise reconstruction of 3D volumes from X-ray projections requires precisely pre-calibrated systems where accurate knowledge of the systems geometric parameters is known ahead. However, when dealing with mobile X-ray devices such calibration parameters are unknown. Joint estimation of the systems calibration parameters and 3d reconstruction is a heavily unconstrained problem, especially when the projections are arbitrary. In industrial applications, that we target here, nominal CAD models of the object to be reconstructed are usually available. We rely on this prior information and employ Deep Learning to learn the mapping between simulated X-ray projections and its pose. Moreover, we introduce the reconstruction loss in addition to the pose loss to further improve the reconstruction quality. Finally, we demonstrate the generalization capabilities of our method in case where poses can be learned on instances of the objects belonging to the same class, allowing pose estimation of unseen objects from the same category, thus eliminating the need for the actual CAD model. We performed exhaustive evaluation demonstrating the quality of our results on both synthetic and real data.

Question: How do you estimate the pose of an object from an x-ray?


A developmental, mentalization-based approach to the understanding and treatment of borderline personality disorder.. The precise nature and etiopathogenesis of borderline personality disorder (BPD) continues to elude researchers and clinicians. Yet, increasing evidence from various strands of research converges to suggest that affect dysregulation, impulsivity, and unstable relationships constitute the core features of BPD. Over the last two decades, the mentalization-based approach to BPD has attempted to provide a theoretically consistent way of conceptualizing the interrelationship between these core features of BPD, with the aim of providing clinicians with a conceptually sound and empirically supported approach to BPD and its treatment. This paper presents an extended version of this approach to BPD based on recently accumulated data. In particular, we suggest that the core features of BPD reflect impairments in different facets of mentalization, each related to impairments in relatively distinct neural circuits underlying these facets. Hence, we provide a comprehensive account of BPD by showing how its core features are related to each other in theoretically meaningful ways. More specifically, we argue that BPD is primarily associated with a low threshold for the activation of the attachment system and deactivation of controlled mentalization, linked to impairments in the ability to differentiate mental states of self and other, which lead to hypersensitivity and increased susceptibility to contagion by other people's mental states, and poor integration of cognitive and affective aspects of mentalization. The combination of these impairments may explain BPD patients' propensity for vicious interpersonal cycles, and their high levels of affect dysregulation and impulsivity. Finally, the implications of this expanded mentalization-based approach to BPD for mentalization-based treatment and treatment of BPD more generally are discussed.

Question: What is borderline personality disorder?


Robust Subspace Segmentation by Low-Rank Representation. We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank representation among all the candidates that represent all vectors as the linear combination of the bases in a dictionary. Unlike the well-known sparse representation (SR), which computes the sparsest representation of each data vector individually, LRR aims at finding the lowest-rank representation of a collection of vectors jointly. LRR better captures the global structure of data, giving a more effective tool for robust subspace segmentation from corrupted data. Both theoretical and experimental results show that LRR is a promising tool for subspace segmentation.

Question: What is robust subspace segmentation?


Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: a meta-analysis.. Virtual reality exposure therapy (VRET) is an increasingly common treatment for anxiety and specific phobias. Lacking is a quantitative meta-analysis that enhances understanding of the variability and clinical significance of anxiety reduction outcomes after VRET. Searches of electronic databases yielded 52 studies, and of these, 21 studies (300 subjects) met inclusion criteria. Although meta-analysis revealed large declines in anxiety symptoms following VRET, moderator analyses were limited due to inconsistent reporting in the VRET literature. This highlights the need for future research studies that report uniform and detailed information regarding presence, immersion, anxiety and/or phobia duration, and demographics.

Question: What is the effect of virtual reality exposure therapy on anxiety?


Decision quality and satisfaction: the effects of online information sources and self-efficacy. Purpose – Digital libraries and social media are two sources of online information with different characteristics. This study integrates self-efficacy into the analysis of the relationship between information sources and decision-making, with the aim of exploring the effect of self-efficacy on decision-making, as well as the interacting effect of self-efficacy and information sources on decision-making. Design/methodology/approach –Survey data were collected and the partial least squares (PLS) structural equation modelling (SEM) was employed to verify the research model. Findings – The effect of digital library usage for acquiring information on perceived decision quality is larger than that of social media usage for acquiring information on perceived decision quality. Self-efficacy in acquiring information stands out as the key determinant for perceived decision quality. The effect of social media usage for acquiring information on perceived decision quality is positively moderated by self-efficacy in acquiring information. Practical implications – Decision-making is a fundamental activity for individuals, but human decision-making is often subject to biases. The findings of this study provide useful insights into decision quality improvement, highlighting the importance of self-efficacy in acquiring information in the face of information overload. Originality/value – This study integrates self-efficacy into the analysis of the relationship between information sources and decision-making, presenting a new perspective for decision-making research and practice alike.

Question: What is the difference between a digital library and a social media?


Towards subjective quality of experience assessment for omnidirectional video streaming. Currently, we witness dramatically increasing interest in immersive media technologies like Virtual Reality (VR), particularly in omnidirectional video (OV) streaming. Omnidirectional (also called 360-degree) videos are panoramic spherical videos in which the user can look around during playback and which therefore can be understood as hybrids between traditional movie streaming and interactive VR worlds. Unfortunately, streaming this kind of content is extremely bandwidth intensive (compared to traditional 2D video) and therefore, Quality of Experience (QoE) tends to deteriorate significantly in absence of continuous optimal bandwidth conditions. In this paper, we present a first approach towards subjective QoE assessment for omnidirectional video (OV) streaming. We present the results of a lab study on the QoE impact of stalling in the context of OV streaming using head-mounted displays (HMDs). Our findings show that subjective testing for immersive media like OV is not trivial, with even simple cases like stalling leading to unexpected results. After a discussion of characteristic pitfalls and lessons learned, we provide a a set of recommendations for upcoming OV assessment studies.

Question: What is the quality of experience of a 360 degree video?


Emotion control in collaborative learning situations: do students regulate emotions evoked by social challenges?. BACKGROUND During recent decades, self-regulated learning (SRL) has become a major research field. SRL successfully integrates the cognitive and motivational components of learning. Self-regulation is usually seen as an individual process, with the social aspects of regulation conceptualized as one aspect of the context. However, recent research has begun to investigate whether self-regulation processes are complemented by socially shared regulation processes.   AIMS The presented study investigated what kind of socio-emotional challenges students experience during collaborative learning and whether the students regulate the emotions evoked during these situations. The interplay of the emotion regulation processes between the individual and the group was also studied.   SAMPLE The sample for this study was 63 teacher education students who studied in groups of three to five during three collaborative learning tasks.   METHOD Students' interpretations of experienced social challenges and their attempts to regulate emotions evoked by these challenges were collected following each task using the Adaptive Instrument for the Regulation of Emotions.   RESULTS The results indicated that students experienced a variety of social challenges. Students also reported the use of shared regulation in addition to self-regulation. Finally, the results suggested that intrinsic group dynamics are derived from both individual and social elements of collaborative situations.   CONCLUSION The findings of the study support the assumption that students can regulate emotions collaboratively as well as individually. The study contributes to our understanding of the social aspects of emotional regulation in collaborative learning contexts.

Question: How can we regulate emotions collaboratively?


2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for Clinical Records presented three tasks: a concept extraction task focused on the extraction of medical concepts from patient reports; an assertion classification task focused on assigning assertion types for medical problem concepts; and a relation classification task focused on assigning relation types that hold between medical problems, tests, and treatments. i2b2 and the VA provided an annotated reference standard corpus for the three tasks. Using this reference standard, 22 systems were developed for concept extraction, 21 for assertion classification, and 16 for relation classification. These systems showed that machine learning approaches could be augmented with rule-based systems to determine concepts, assertions, and relations. Depending on the task, the rule-based systems can either provide input for machine learning or post-process the output of machine learning. Ensembles of classifiers, information from unlabeled data, and external knowledge sources can help when the training data are inadequate.

Question: What is the 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text?


The Traveling Salesman Problem for Cubic Graphs. We show how to find a Hamiltonian cycle in a graph of degree at most three with n vertices, in time O(2) ≈ 1.260 and linear space. Our algorithm can find the minimum weight Hamiltonian cycle (traveling salesman problem), in the same time bound. We can also count or list all Hamiltonian cycles in a degree three graph in time O(2) ≈ 1.297. We also solve the traveling salesman problem in graphs of degree at most four, by randomized and deterministic algorithms with runtime O((27/4)) ≈ 1.890 and O((27/4+ ǫ)) respectively. Our algorithms allow the input to specify a set of forced edges which must be part of any generated cycle. Our cycle listing algorithm shows that every degree three graph has O(2) Hamiltonian cycles; we also exhibit a family of graphs with 2 Hamiltonian cycles per graph. Article Type Communicated by Submitted Revised Regular paper J. S. B. Mitchell April 2004 Work supported in part by NSF grant CCR-9912338. A preliminary version of this paper appeared at the 8th Annual Workshop on Algorithms and Data Structures,

Question: What is the minimum weight Hamiltonian cycle in a cubic graph?


Fusion of Keypoint Tracking and Facial Landmark Detection for Real-Time Head Pose Estimation. In this paper, we address the problem of extreme head pose estimation from intensity images, in a monocular setup. We introduce a novel fusion pipeline to integrate into a dedicated Kalman Filter the pose estimated from a tracking scheme in the prediction stage and the pose estimated from a detection scheme in the correction stage. To that end, the measurement covariance of the Kalman Filter is updated in every frame. The tracking scheme is performed using a set of keypoints extracted in the area of the head along with a simple 3D geometric model. The detection scheme, on the other hand, relies on the alignment of facial landmarks in each frame combined with 3D features extracted on a head mesh. The head pose in each scheme is estimated by minimizing the reprojection error from the 3D-2D correspondences. By combining both frameworks, we extend the applicability of head pose estimation from facial landmarks to cases where these features are no longer visible. We compared the proposed method to other related approaches, showing that it can achieve state-of-the-art performance. We also demonstrate that our approach is suitable for cases with extreme head rotations and (self-) occlusions, besides being suitable for real time applications.

Question: How to estimate the head pose from facial landmarks?


Adhesive capsulitis: review of imaging findings, pathophysiology, clinical presentation, and treatment options. Adhesive capsulitis, commonly referred to as "frozen shoulder," is a debilitating condition characterized by progressive pain and limited range of motion about the glenohumeral joint. It is a condition that typically affects middle-aged women, with some evidence for an association with endocrinological, rheumatological, and autoimmune disease states. Management tends to be conservative, as most cases resolve spontaneously, although a subset of patients progress to permanent disability. Conventional arthrographic findings include decreased capsular distension and volume of the axillary recess when compared with the normal glenohumeral joint, in spite of the fact that fluoroscopic visualization alone is rarely carried out today in favor of magnetic resonance imaging (MRI). MRI and MR arthrography (MRA) have, in recent years, allowed for the visualization of several characteristic signs seen with this condition, including thickening of the coracohumeral ligament, axillary pouch and rotator interval joint capsule, in addition to the obliteration of the subcoracoid fat triangle. Additional findings include T2 signal hyperintensity and post-contrast enhancement of the joint capsule. Similar changes are observable on ultrasound. However, the use of ultrasound is most clearly established for image-guided injection therapy. More aggressive therapies, including arthroscopic release and open capsulotomy, may be indicated for refractory disease, with arthroscopic procedures favored because of their less invasive nature and relatively high success rate.

Question: What is the treatment for adhesive capsulitis?


Deep motion features for visual tracking. Robust visual tracking is a challenging computer vision problem, with many real-world applications. Most existing approaches employ hand-crafted appearance features, such as HOG or Color Names. Recently, deep RGB features extracted from convolutional neural networks have been successfully applied for tracking. Despite their success, these features only capture appearance information. On the other hand, motion cues provide discriminative and complementary information that can improve tracking performance. Contrary to visual tracking, deep motion features have been successfully applied for action recognition and video classification tasks. Typically, the motion features are learned by training a CNN on optical flow images extracted from large amounts of labeled videos. This paper presents an investigation of the impact of deep motion features in a tracking-by-detection framework. We further show that hand-crafted, deep RGB, and deep motion features contain complementary information. To the best of our knowledge, we are the first to propose fusing appearance information with deep motion features for visual tracking. Comprehensive experiments clearly suggest that our fusion approach with deep motion features outperforms standard methods relying on appearance information alone.

Question: What is a tracking-by-detection framework?


High performance active gate drive for high power IGBTs. This paper deals with an active gate drive (AGD) technology for high power IGBTs. It is based on an optimal combination of several requirements necessary for good switching performance under hard switching conditions. The scheme specifically combines together the slow drive requirements for low noise and switching stress and the fast drive requirements for high speed switching and low switching energy loss. The gate drive can also effectively dampen oscillations during low current turn-on transients in the IGBT. This paper looks at the conflicting requirements of the conventional gate drive circuit design and demonstrates, using experimental results, that the proposed three-stage active gate drive technique can be an effective solution.

Question: What is the difference between a gate drive and a gate drive circuit?


PH2 - A dermoscopic image database for research and benchmarking. The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images. Unfortunately, the performance of such systems cannot be compared since they are evaluated in different sets of images by their authors and there are no public databases available to perform a fair evaluation of multiple systems. In this paper, a dermoscopic image database, called PH2, is presented. The PH2 database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images. The PH2 database will be made freely available for research and benchmarking purposes.

Question: What is a dermoscopic image database?


Constant Communication ORAM with Small Blocksize. There have been several attempts recently at using homomorphic encryption to increase the efficiency of Oblivious RAM protocols. One of the most successful has been Onion ORAM, which achieves O(1) communication overhead with polylogarithmic server computation. However, it has two drawbacks. It requires a large block size of B = Ω(log6 N) with large constants. Moreover, while it only needs polylogarithmic computation complexity, that computation consists mostly of expensive homomorphic multiplications. In this work, we address these problems and reduce the required block size to Ω(log4 N). We remove most of the homomorphic multiplications while maintaining O(1) communication complexity. Our idea is to replace their homomorphic eviction routine with a new, much cheaper permute-and-merge eviction which eliminates homomorphic multiplications and maintains the same level of security. In turn, this removes the need for layered encryption that Onion ORAM relies on and reduces both the minimum block size and server computation.

Question: What is the minimum block size for onion oram?


Wideband Circularly Polarized Patch Antennas on Reactive Impedance Substrates. A reduced-size wideband single-feed circularly polarized patch antenna is introduced for telemetry applications in S-band around 2300 MHz. The proposed structure consists of a slot-loaded patch antenna printed over an optimized metamaterial-inspired reactive impedance substrate (RIS). We demonstrate, step by step, the main role of each antenna element by comparing numerically and experimentally the performance of various antenna configurations: antenna over a single- or dual-layer substrate, standard patch or slot-loaded patch, antenna with or without RIS. The final optimized structure exhibits an axial-ratio bandwidth of about 15% and an impedance bandwidth better than 11%, which is much wider than the conventional printed antenna on the same materials.

Question: What is a reactive impedance substrate?


Engagement in Multimedia Training Systems. Two studies examined user engagement in two type multimedia training systems -a more passive medium, videotape, and a less passive medium, interactive softw Each study compared engagement in three formats: the Text format contained text and still images, the Audio format contained audio and still images, and the Video format contained audio and video images. In both studies, engagement was lower in the Text condition than in the Video condition. However, there were no differences in engagement between Text and Audio in the videotapebased training, and no differences between Audio and Video in the computer-based training.

Question: What is the difference between the text and audio formats?


Design, simulation and implementation of a self-oscillating control circuit to drive series resonant inverter feeding a brazing induction furnace. This research deals with the design and simulation of induction furnace power source (inverter) using MATLAB package. This source designed to lock on the resonant frequency of the load by using self-oscillating technique, also it has the capability to control the power supplied to the load using phase shift pulse width modulation (PSPWM) technique. These characteristics used to overcome the load nonlinear behavior during the brazing process and to achieve soft switching of the inverter elements. Also, the inverter has the capability to operate with or without load (workpiece). The implemented prototype operates at a frequency range (50-100)kHz and 10kW was successfully used for brazing two copper workpieces.

Question: How to design a self-oscillating control circuit to drive series resonant inverter feeding a brazing induction furnace?


Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood.. We directly sequenced cell-free DNA with high-throughput shotgun sequencing technology from plasma of pregnant women, obtaining, on average, 5 million sequence tags per patient sample. This enabled us to measure the over- and underrepresentation of chromosomes from an aneuploid fetus. The sequencing approach is polymorphism-independent and therefore universally applicable for the noninvasive detection of fetal aneuploidy. Using this method, we successfully identified all nine cases of trisomy 21 (Down syndrome), two cases of trisomy 18 (Edward syndrome), and one case of trisomy 13 (Patau syndrome) in a cohort of 18 normal and aneuploid pregnancies; trisomy was detected at gestational ages as early as the 14th week. Direct sequencing also allowed us to study the characteristics of cell-free plasma DNA, and we found evidence that this DNA is enriched for sequences from nucleosomes.

Question: How can we detect fetal aneuploidy?


Question: What is the canadian military?


Architecture for an Intelligent Tutoring System that Considers Learning Styles. In this paper we propose the architecture of an Intelligent Tutoring System that considers the student's learning style and the competency-based education. We also describe the processes that have been implemented so far. Our architecture presents innovations in the representation of the tutor module and in the knowledge module; the tutor module incorporates a selector agent, which will choose the content to show, considering the teaching strategies that support the student's learning style.

Question: What is the architecture of an intelligent tutoring system?


Fibonacci heaps and their uses in improved network optimization algorithms. In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, <italic>Fibonacci heaps</italic> (abbreviated <italic>F-heaps</italic>), extends the binomial queues proposed by Vuillemin and studied further by Brown. F-heaps support arbitrary deletion from an <italic>n</italic>-item heap in <italic>O</italic>(log <italic>n</italic>) amortized time and all other standard heap operations in <italic>O</italic>(1) amortized time. Using F-heaps we are able to obtain improved running times for several network optimization algorithms. In particular, we obtain the following worst-case bounds, where <italic>n</italic> is the number of vertices and <italic>m</italic> the number of edges in the problem graph:<list><item><italic>O</italic>(<italic>n</italic> log <italic>n</italic> + <italic>m</italic>) for the single-source shortest path problem with nonnegative edge lengths, improved from <italic>O</italic>(<italic>m</italic>log<subscrpt>(<italic>m/n</italic>+2)</subscrpt><italic>n</italic>); </item><item><italic>O</italic>(<italic>n</italic><supscrpt>2</supscrpt>log <italic>n</italic> + <italic>nm</italic>) for the all-pairs shortest path problem, improved from <italic>O</italic>(<italic>nm</italic> log<subscrpt>(<italic>m/n</italic>+2)</subscrpt><italic>n</italic>); </item><item><italic>O</italic>(<italic>n</italic><supscrpt>2</supscrpt>log <italic>n</italic> + <italic>nm</italic>) for the assignment problem (weighted bipartite matching), improved from <italic>O</italic>(<italic>nm</italic>log<subscrpt>(<italic>m/n</italic>+2)</subscrpt><italic>n</italic>); </item><item><italic>O</italic>(<italic>mβ</italic>(<italic>m, n</italic>)) for the minimum spanning tree problem, improved from <italic>O</italic>(<italic>m</italic>log log<subscrpt>(<italic>m/n</italic>+2)</subscrpt><italic>n</italic>); where <italic>β</italic>(<italic>m, n</italic>) = min {<italic>i</itali

Question: What is the minimum spanning tree problem?


Occupational risks and challenges of seafaring.. UNLABELLED Seafarers are exposed to a high diversity of occupational health hazards onboard ships.   OBJECTIVE The aim of this article is to present a survey of the current, most important hazards in seafaring including recommendations on measures how to deal with these problems.   METHODS The review is based on maritime expert opinions as well a PubMed analysis related to the occupational risks of seafaring.   RESULTS Despite recent advances in injury prevention, accidents due to harmful working and living conditions at sea and of non-observance of safety rules remain a main cause of injury and death. Mortality in seafaring from cardiovascular diseases (CVD) is mainly caused by increased risks and impaired treatment options of CVD at sea. Further, shipboard stress and high demand may lead to fatigue and isolation which have an impact on the health of onboard seafarers. Communicable diseases in seafaring remain an occupational problem. Exposures to hazardous substances and UV-light are important health risks onboard ships. Because of harsh working conditions onboard including environmental conditions, sufficient recreational activities are needed for the seafarers' compensation both onboard and ashore. However, in reality there is often a lack of leisure time possibilities.   DISCUSSION Seafaring is still an occupation with specific work-related risks. Thus, a further reduction of occupational hazards aboard ships is needed and poses a challenge for maritime health specialists and stakeholders. Nowadays, maritime medicine encompasses a broad field of workplaces with different job-related challenges.

Question: What are the occupational risks of seafaring?


A Risk Management Approach to the "Insider Threat". Recent surveys indicate that the financial impact and operating losses due to insider intrusions are increasing. But these studies often disagree on what constitutes an "insider;" indeed, many define it only implicitly. In theory, appropriate selection of, and enforcement of, properly specified security policies should prevent legitimate users from abusing their access to computer systems, information, and other resources. However, even if policies could be expressed precisely, the natural mapping between the natural language expression of a security policy, and the expression of that policy in a form that can be implemented on a computer system or network, creates gaps in enforcement. This paper defines "insider" precisely, in terms of these gaps, and explores an access-based model for analyzing threats that include those usually termed "insider threats." This model enables an organization Matt Bishop Matt Bishop, Dept. of Computer Science, University of California at Davis e-mail: bishop@cs.

Question: What is the definition of insider?


Fog computing: Security issues, solutions and robust practices. Fog Computing (FC) has extended the services of cloud computing to the edge of the network. It inherits some of the characteristics from cloud computing but FC also have some distinguished features such as geo-distribution, location awareness and low latency. Along with the inherited characteristics, it also inherits the issues and problems of cloud computing like energy efficiency, resource management and security issues. This paper presents the critical analysis of the fog architecture with respect to security. The state of the art work done since 2012 is critical analyzed on the bases of security techniques and security threats. We grouped the existing security techniques on the bases of security goals achieved by each. It will provide a clear and comprehensive distinction between the security areas explored and those, which still need researchers' attention.

Question: What is fog computing?


Proposal of millimeter-wave holographic radar with antenna switching. This paper proposes a millimeter-wave holographic radar with a simple structure for automotive applications. The simplicity can be realized by switching both transmitting antennas and receiving antennas. Also, a super resolution technique is introduced for the detection of angular positions in the proposed radar. The radar developed experimentally has accomplished an azimuthal angular resolution of less than 2 degrees and an azimuthal field of view (FoV) of more than 20 degrees simultaneously.

Question: What is the resolution of the radar?


PENS-wheel (one-wheeled self balancing vehicle) balancing control using PID controller. Pens-Wheel is an electric vehicle which uses one wheel that able to balance itself so the rider does not fall forward or backward while riding it. This vehicle uses one brushless DC motor as actuator which capable to rotate in both directions symmetrically. The vehicle uses a combination of accelerometer and gyroscope contained in IMU (Inertial Measurement Unit) for balancing sensor. The controlled motion on the vehicle occurs only on the x-axis (pitch angle), in forward and backward directions. The PID (Proportional Integral Derivative) control algorithm is used to maintain the balance and movement of the vehicle. From the simulation and application in the real vehicle, the use of PID control is capable driving the vehicle in maintaining the balance condition within ±10° tilt angle boundary on flat surface, bumpy road, and inclining road up to 15° slope.

Question: How to control the balance of a vehicle?


A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure.. A theory was proposed to reconcile paradoxical findings on the invariance of personality and the variability of behavior across situations. For this purpose, individuals were assumed to differ in (a) the accessibility of cognitive-affective mediating units (such as encodings, expectancies and beliefs, affects, and goals) and (b) the organization of relationships through which these units interact with each other and with psychological features of situations. The theory accounts for individual differences in predictable patterns of variability across situations (e.g., if A then she X, but if B then she Y), as well as for overall average levels of behavior, as essential expressions or behavioral signatures of the same underlying personality system. Situations, personality dispositions, dynamics, and structure were reconceptualized from this perspective.

Question: What is a cognitive-affective system theory of personality?


Chapter 2 Depression and a Stepped Care Model. Given the public health significance of depression and the limited resources available for providing evidence-based treatment, there is a need to develop effective models of care to reduce the personal and societal costs of the disorder. Within stepped care service provisions, all patients presenting with symptoms of depression generally are first offered the lowest intensity and least intrusive intervention deemed necessary following assessment and triage. Only when patients do not show improvement do they move to higher, more intensive levels of care. However, stepped care models also provide information to aid clinicians in decision making regarding selection of treatment strategies that are most appropriate for an individual patient. For some individuals, lower levels of care would never be appropriate or may not be preferred by the consumer. Thus, stepped interventions offer a variety of treatment options to match the intensity of the patient's presenting problem as well as potential patient preference. In this chapter, we discuss various strategies for treating depression consistent with a stepped model of care beginning with least intensive treatment and then moving up through the hierarchy of steps of care. While this is not a comprehensive review of all available treatments for depression, the chapter is designed to make clinicians aware of specific strategies for addressing depressive symptoms and to provide guidance about resources available at the various levels of care.

Question: What is the lowest intensity treatment for depression?


Synaptic patterning and the timescales of cortical dynamics. Neocortical circuits, as large heterogeneous recurrent networks, can potentially operate and process signals at multiple timescales, but appear to be differentially tuned to operate within certain temporal receptive windows. The modular and hierarchical organization of this selectivity mirrors anatomical and physiological relations throughout the cortex and is likely determined by the regional electrochemical composition. Being consistently patterned and actively regulated, the expression of molecules involved in synaptic transmission constitutes the most significant source of laminar and regional variability. Due to their complex kinetics and adaptability, synapses form a natural primary candidate underlying this regional temporal selectivity. The ability of cortical networks to reflect the temporal structure of the sensory environment can thus be regulated by evolutionary and experience-dependent processes.

Question: What is the timescale of cortical dynamics?


PLUG: flexible lookup modules for rapid deployment of new protocols in high-speed routers. New protocols for the data link and network layer are being proposed to address limitations of current protocols in terms of scalability, security, and manageability. High-speed routers and switches that implement these protocols traditionally perform packet processing using ASICs which offer high speed, low chip area, and low power. But with inflexible custom hardware, the deployment of new protocols could happen only through equipment upgrades. While newer routers use more flexible network processors for data plane processing, due to power and area constraints lookups in forwarding tables are done with custom lookup modules. Thus most of the proposed protocols can only be deployed with equipment upgrades. To speed up the deployment of new protocols, we propose a flexible lookup module, PLUG (Pipelined Lookup Grid). We can achieve generality without loosing efficiency because various custom lookup modules have the same fundamental features we retain: area dominated by memories, simple processing, and strict access patterns defined by the data structure. We implemented IPv4, Ethernet, Ethane, and SEATTLE in our dataflow-based programming model for the PLUG and mapped them to the PLUG hardware which consists of a grid of tiles. Throughput, area, power, and latency of PLUGs are close to those of specialized lookup modules.

Question: What is the area of a PLUG?


Current and Emerging Topics in Sports Video Processing. Sports video processing is an interesting topic for research, since the clearly defined game rules in sports provide the rich domain knowledge for analysis. Moreover, it is interesting because many specialized applications for sports video processing are emerging. This paper gives an overview of sports video research, where we describe both basic algorithmic techniques and applications.

Question: What is the difference between sports video processing and sports video analysis?


Multiview Clustering via Adaptively Weighted Procrustes. In this paper, we make a multiview extension of the spectral rotation technique raised in single view spectral clustering research. Since spectral rotation is closely related to the Procrustes Analysis for points matching, we point out that classical Procrustes Average approach can be used for multiview clustering. Besides, we show that direct applying Procrustes Average (PA) in multiview tasks may not be optimal theoretically and empirically, since it does not take the clustering capacity differences of different views into consideration. Other than that, we propose an Adaptively Weighted Procrustes (AWP) approach to overcome the aforementioned deficiency. Our new AWP weights views with their clustering capacities and forms a weighted Procrustes Average problem accordingly. The optimization algorithm to solve the new model is computational complexity analyzed and convergence guaranteed. Experiments on five real-world datasets demonstrate the effectiveness and efficiency of the new models.

Question: How to cluster data with different views?


HCI Education: Innovation, Creativity and Design Thinking. Human-Computer Interaction (HCI) education needs re-thinking. In this paper, we explore how and what creativity and design thinking could contribute with, if included as a part of the HCI curriculum. The findings from courses where design thinking was included, indicate that design thinking contributed to increased focus on innovation and creativity, as well as prevented too early fixation on a single solution in the initial phases of HCI design processes, fostering increased flexibility and adaptability in learning processes. The creativity and adaptability may be the best long-term foci that HCI education can add to its curriculums and offer to students when preparing them for future work

Question: What is design thinking?


Human Postures Recognition Based on D-S Evidence Theory and Multi-sensor Data Fusion. Body Sensor Networks (BSNs) are conveying notable attention due to their capabilities in supporting humans in their daily life. In particular, real-time and noninvasive monitoring of assisted livings is having great potential in many application domains, such as health care, sport/fitness, e-entertainment, social interaction and e-factory. And the basic as well as crucial feature characterizing such systems is the ability of detecting human actions and behaviors. In this paper, a novel approach for human posture recognition is proposed. Our BSN system relies on an information fusion method based on the D-S Evidence Theory, which is applied on the accelerometer data coming from multiple wearable sensors. Experimental results demonstrate that the developed prototype system is able to achieve a recognition accuracy between 98.5% and 100% for basic postures (standing, sitting, lying, squatting).

Question: What is the difference between a sensor network and a body sensor network?


A 0.5-V bulk-input fully differential operational transconductance amplifier. We present a fully differential two-stage Miller op-amp operating from a 0.5 V power supply. The input signal is applied to the bulk nodes of the input devices. A prototype was designed in a standard 0.18 /spl mu/m CMOS process using standard 0.5 V V/sub T/ devices. It has a measured 52 dB DC gain, a 2.5 MHz gain-bandwidth and consumes 110 /spl mu/W.

Question: What is a 0.5-V fully differential operational transconductance amplifier?


Sentiment-Based Features for Predicting Election Polls: A Case Study on the Brazilian Scenario. The success of opinion mining for automatically processing vast amounts of opinionated content available on the Internet has been demonstrated as a less expensive and lower latency solution for gathering public opinion. In this paper, we investigate whether it is possible to predict variations in vote intention based on sentiment time series extracted from news comments, using three Brazilian elections as case study. The contributions of this case study are: a) the comparison of two approaches for opinion mining in user-generated content in Brazilian Portuguese, b) the proposition of two types of features to represent sentiment behavior towards political candidates that can be used for prediction, c) an approach to predict polls vote intention variations that is adequate for scenarios of sparse data. We developed experiments to assess the influence on the forecasting accuracy of the proposed features, and their respective preparation. Our results display an accuracy of 70% in predicting positive and negative variations. These are important contributions towards a more general framework that is able to blend opinions from several different sources to find representativeness of the target population, and make more reliable predictions.

Question: What is the difference between the two approaches for opinion mining in user-generated content in Brazilian Portuguese?


Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. Multimedia content is dominating today's Web information. The nature of multimedia user-item interactions is 1/0 binary implicit feedback (e.g., photo likes, video views, song downloads, etc.), which can be collected at a larger scale with a much lower cost than explicit feedback (e.g., product ratings). However, the majority of existing collaborative filtering (CF) systems are not well-designed for multimedia recommendation, since they ignore the implicitness in users' interactions with multimedia content. We argue that, in multimedia recommendation, there exists item- and component-level implicitness which blurs the underlying users' preferences. The item-level implicitness means that users' preferences on items (e.g. photos, videos, songs, etc.) are unknown, while the component-level implicitness means that inside each item users' preferences on different components (e.g. regions in an image, frames of a video, etc.) are unknown. For example, a 'view'' on a video does not provide any specific information about how the user likes the video (i.e.item-level) and which parts of the video the user is interested in (i.e.component-level). In this paper, we introduce a novel attention mechanism in CF to address the challenging item- and component-level implicit feedback in multimedia recommendation, dubbed Attentive Collaborative Filtering (ACF). Specifically, our attention model is a neural network that consists of two attention modules: the component-level attention module, starting from any content feature extraction network (e.g. CNN for images/videos), which learns to select informative components of multimedia items, and the item-level attention module, which learns to score the item preferences. ACF can be seamlessly incorporated into classic CF models with implicit feedback, such as BPR and SVD++, and efficiently trained using SGD. Through extensive experiments

Question: What is the difference between a neural network and a neural network?


Cluster validity functions for categorical data: a solution-space perspective. For categorical data, there are three widely-used internal validity functions: the $$k$$ k -modes objective function, the category utility function and the information entropy function, which are defined based on within-cluster information only. Many clustering algorithms have been developed to use them as objective functions and find their optimal solutions. In this paper, we study the generalization, effectiveness and normalization of the three validity functions from a solution-space perspective. First, we present a generalized validity function for categorical data. Based on it, we analyze the generality and difference of the three validity functions in the solution space. Furthermore, we address the problem whether the between-cluster information is ignored when these validity functions are used to evaluate clustering results. To the end, we analyze the upper and lower bounds of the three validity functions for a given data set, which can help us estimate the clustering difficulty on a data set and compare the performance of a clustering algorithm on different data sets.

Question: What is the difference between the three validity functions?


An integrated approach to testing complex systems. The increasing complexity of today's testing scenarios for complex systems demands an integrated, open, and flexible approach to support the management of the overall test process. "Classical" model-based testing approaches, where a complete and precise formal specification serves as a reference for automatic test generation, are often impractical. Reasons are, on the one hand, the absence of a suitable formal specification. As complex systems are composed of several components, either hardware or software, often pre-built and third party, it is unrealistic to assume that a formal specification exists a priori. On the other hand, a sophisticated test execution environment is needed that can handle distributed test cases. This is because the test actions and observations can take place on different subsystems of the overall system. This thesis presents a novel approach to the integrated testing of complex systems. Our approach offers a coarse grained test environment, realized in terms of a component-based test design on top of a library of elementary but intuitively understandable test case fragments. The relations between the fragments are treated orthogonally, delivering a test design and execution environment enhanced by means of light-weight formal verification methods. In this way we are able to shift the test design issues from total experts of the system and the used test tools to experts of the system's logic only. We illustrate the practical usability of our approach by means of industrial case studies in two different application domains: Computer Telephony Integrated solutions and Web-based applications. As an enhancement of our integrated test approach we provide an algorithm for generating approximate models for complex systems a posteriori. This is done by optimizing a standard machine learning algorithm according to domain-specific structural properties, i.e. properties like prefix-closeness, input-de

Question: What is the difference between a model-based testing approach and a model-free testing approach?


Adaptive sequential Monte Carlo by means of mixture of experts. Selecting appropriately the proposal kernel of particle filters is an issue of significant importance, since a bad choice may lead to deterioration of the particle sample and, consequently, waste of computational power. In this paper we introduce a novel algorithm approximating adaptively the so-called optimal proposal kernel by a mixture of integrated curved exponential distributions with logistic weights. This family of distributions, referred to as mixtures of experts, is broad enough to be used in the presence of multi-modality or strongly skewed distributions. The mixtures are fitted, via Monte Carlo EM or online-EM methods, to the optimal kernel through minimization of the Kullback-Leibler divergence between the auxiliary target and instrumental distributions of the particle filter. At each iteration of the particle filter, the algorithm is required to solve only a single optimization problem for the whole particle sample, as opposed to existing methods solving one problem per particle. In addition, we illustrate in a simulation study how the method can be successfully applied to optimal filtering in nonlinear state-space models.

Question: What is the difference between a mixture of experts and a mixture of Gaussians?


A Rule-Based Approach For Effective Sentiment Analysis. The success of Web 2.0 applications has made online social media websites tremendous assets for supporting critical business intelligence applications. The knowledge gained from social media can potentially lead to the development of novel services that are better tailored to users' needs and at the same time meet the objectives of businesses offering them. Online consumer reviews are one of the critical social media contents. Proper analysis of consumer reviews not only provides valuable information to facilitate the purchase decisions of customers but also helps merchants or product manufacturers better understand general responses of customers on their products for marketing campaign improvement. This study aims at designing an approach for supporting the effective analysis of the huge volume of online consumer reviews and, at the same time, settling the major limitations of existing approaches. Specifically, the proposed rule-based sentiment analysis (R-SA) technique employs the class association rule mining algorithm to automatically discover interesting and effective rules capable of extracting product features or opinion sentences for a specific product feature interested. According to our preliminary evaluation results, the R-SA technique performs well in comparison with its benchmark technique.

Question: What is the rule-based sentiment analysis?


Review on Machine Learning Techniques for Automatic Segmentation of Liver Images. The segmentation of liver from abdominal images has gained huge importance in medical imaging field since it is fundamental step to diagnose liver tumor and other liver diseases, liver volume measurement and 3D liver volume rendering. In this paper, recent automatic methods for liver image segmentation proposed in literature are reviewed. Generally, Liver image segmentation techniques can be semi-automatic and fully automatic. Under fully automatic segmentation category, various methods, approaches, recent advances and related problems has been explained. Brief summary of all discussed methods has been provided. Finally it is concluded that liver image segmentation is still an open problem since various drawbacks of proposed methods can be addressed. Keywords— Liver image Segmentation, Automatic Segmentation, Neural Network, Support Vector Machine, Clustering, Hybrid, Review.

Question: What is the size of the liver?


A11y Attacks: Exploiting Accessibility in Operating Systems. Driven in part by federal law, accessibility (a11y) support for disabled users is becoming ubiquitous in commodity OSs. Some assistive technologies such as natural language user interfaces in mobile devices are welcomed by the general user population. Unfortunately, adding new features in modern, complex OSs usually introduces new security vulnerabilities. Accessibility support is no exception. Assistive technologies can be defined as computing subsystems that either transform user input into interaction requests for other applications and the underlying OS, or transform application and OS output for display on alternative devices. Inadequate security checks on these new I/O paths make it possible to launch attacks from accessibility interfaces. In this paper, we present the first security evaluation of accessibility support for four of the most popular computing platforms: Microsoft Windows, Ubuntu Linux, iOS, and Android. We identify twelve attacks that can bypass state-of-the-art defense mechanisms deployed on these OSs, including UAC, the Yama security module, the iOS sandbox, and the Android sandbox. Further analysis of the identified vulnerabilities shows that their root cause is that the design and implementation of accessibility support involves inevitable trade-offs among compatibility, usability, security, and (economic) cost. These trade-offs make it difficult to secure a system against misuse of accessibility support. Based on our findings, we propose a number of recommendations to either make the implementation of all necessary security checks easier and more intuitive, or to alleviate the impact of missing/incorrect checks. We also point out open problems and challenges in automatically analyzing accessibility support and identifying security vulnerabilities.

Question: What is the first large-scale Canadian peacekeeping mission?


Comparing software and hardware schemes for reducing the cost of branches. Pipelining has become a common technique to increase throughput of the instruction fetch, instruction decode, and instruction execution portions of modern computers. Branch instructions disrupt the flow of instructions through the pipeline, increasing the overall execution cost of branch instructions. Three schemes to reduce the cost of branches are presented in the context of a general pipeline model. Ten realistic Unix domain programs are used to directly compare the cost and performance of the three schemes and the results are in favor of the software-based scheme. For example, the software-based scheme has a cost of 1.65 cycles/branch vs. a cost of 1.68 cycles/branch of the best hardware scheme for a highly pipelined processor (11-stage pipeline). The results are 1.19 (software scheme) vs. 1.23 cycles/branch (best hardware scheme) for a moderately pipelined processor (5-stage pipeline).

Question: How to compare software and hardware schemes for reducing the cost of branches?


Message authentication in driverless cars. Driverless cars and driver-assisted vehicles are becoming prevalent in today's transportation systems. Companies like TESLA, Audi, and Google are among the leaders in this new era of the automotive industry. Modern vehicles, equipped with sophisticated navigation devices, complex driver-assisted systems, and a whole lot of safety features, bring broader impacts to our quality of life, economic development, and environmental sustainability. Instant safety messages such as pre-collision warnings, blind-spot detection, pedestrian and object awareness significantly improve the safety for drivers, passengers, and pedestrians. As a result, vehicles would be able to travel closely yet safely together, forming a platoon, thus resulting in a reduction of traffic congestion and fuel consumption. Driverless cars also have non-safety-related applications: which are used to facilitate traffic management and infotainment dissemination for drivers and passengers. Vehicular Ad hoc Network (VANET), the wireless communication technology enabling driverless cars, features not only dynamic topology but also high mobility. The vehicle nodes move rapidly on streets and highways. Their movements also depend on but not limited to road traffic, speed limits, and behavior of nearby vehicles. With massive amount of messages exchanged among driverless cars that command the cars' movements at high speeds and in close distances, any malicious alternation could lead to disastrous accidents. Message authentication to ensure data integrity is paramount to attack preparation. This paper presents a novel message authentication scheme that protects cars from bogus messages and makes VANET resilient to Denial-of-Service (DoS) attacks. The work includes a simulation framework that integrates vehicle and data traffic models to validate the effectiveness of the proposed message authentication scheme.

Question: What is the difference between a driverless car and a driver-assisted car?


Usefulness of altmetrics for measuring the broader impact of research: A case study using data from PLOS and F1000Prime. Purpose: The present case study investigates the usefulness of altmetrics for measuring the broad impact of research. Methods: This case study is based on a sample of 1,082 PLOS (the Public Library of Science) journal articles recommended in F1000. The dataset includes altmetrics which were provided by PLOS. The F1000 dataset contains tags on papers which were assigned by experts to characterise them. Findings: Results from the Facebook and Twitter models show higher predicted numbers of counts for "good for teaching" papers than for those papers where the tag is not set. Further model estimations show that saves by Mendeley users are particularly to be expected when a paper introduces a new practical/ theoretical technique (tag: "technical advance"). The tag "New finding" is statistically significant in the model with which the Facebook counts are evaluated. Conclusions: The "good for teaching" is assigned to papers which could be of interest to a wider circle of readers than the peers in a specialized area. Thus, the results of the current study indicate that Facebook and Twitter, but not Figshare or Mendeley, might provide an indication of which papers are of interest to a broader circle of readers (and not only for the peers in a specialist area), and could therefore be useful for the measurement of the social impact of research.

Question: What is the usefulness of altmetrics for measuring the broader impact of research?


Cost Models for Future Software Life Cycle Processes: COCOMO 2.0. Current software cost estimation models, such as the 1981 Constructive Cost Model (COCOMO) for software cost estimation and its 1987 Ada COCOMO update, have been experiencing increasing difficulties in estimating the costs of software developed to new life cycle processes and capabilities. These include non-sequential and rapid-development process models; reuse-driven approaches involving commercial off the shelf (COTS) packages, reengineering, applications composition, and applications generation capabilities; object-oriented approaches supported by distributed middleware; and software process maturity initiatives. This paper summarizes research in deriving a baseline COCOMO 2.0 model tailored to these new forms of software development, including rationales for the model decisions. The major new modeling capabilities of COCOMO 2.0 are a tailorable family of software sizing models, involving Object Points, Function Points, and Source Lines of Code; nonlinear models for software reuse and reengineering; an exponent-driver approach for modeling relative software diseconomies of scale; and several additions, deletions, and updates to previous COCOMO effort-multiplier cost drivers. This model is serving as a framework for an extensive current data collection and analysis effort to further refine and calibrate the model's estimation capabilities.

Question: What is the cost of software development?


The effect of five prosthetic feet on the gait and loading of the sound limb in dysvascular below-knee amputees.. The purpose of this study was to determine the effects of prosthetic foot design on the vertical ground reaction forces experienced by the sound and amputated limbs in a group of persons with dysvascular below-knee amputations. Stride characteristics, joint motion, and ground reaction forces were recorded simultaneously during a self-selected free walking velocity in seven subjects wearing five different prosthetic feet (SACH, Flex-Foot, Carbon Copy II, Seattle, Quantum). Subjects used each foot for one month prior to testing. Results indicated that the sound limb was exposed to higher vertical ground reaction forces than normal despite a reduced walking velocity. Use of the Flex-Foot resulted in the lowest sound limb vertical forces, which appears to be related to its large arc of dorsiflexion motion. In addition, there was increased loading response knee flexion of the sound limb indicating an attempt by these subjects to modulate floor impact. These results suggest that the intact lower extremity is susceptible to excessive floor impact, and that prosthetic foot design can have an effect on the magnitude of the vertical forces experienced by the limb.

Question: What is the effect of prosthetic foot design on the gait and loading of the sound limb in dysvascular below-knee amputees?


The spread of behavior in an online social network experiment.. How do social networks affect the spread of behavior? A popular hypothesis states that networks with many clustered ties and a high degree of separation will be less effective for behavioral diffusion than networks in which locally redundant ties are rewired to provide shortcuts across the social space. A competing hypothesis argues that when behaviors require social reinforcement, a network with more clustering may be more advantageous, even if the network as a whole has a larger diameter. I investigated the effects of network structure on diffusion by studying the spread of health behavior through artificially structured online communities. Individual adoption was much more likely when participants received social reinforcement from multiple neighbors in the social network. The behavior spread farther and faster across clustered-lattice networks than across corresponding random networks.

Question: How do social networks affect the spread of behavior?


A dynamic core loss model for soft ferromagnetic and power ferrite materials in transient finite element analysis. A dynamic core loss model is proposed to estimate core loss in both soft ferromagnetic and power ferrite materials with arbitrary flux waveforms. The required parameters are the standard core loss coefficients that are either directly provided by manufacturers or extracted from the loss curve associated with sinusoidal excitation. The model is applied to calculating core loss in both two-dimensional and three-dimensional transient finite element analysis, and the results are compared with measured data.

Question: What is the dynamic core loss model?


Latent Aspect Mining via Exploring Sparsity and Intrinsic Information. We investigate latent aspect mining problem that aims at automatically discovering aspect information from a collection of review texts in a domain in an unsupervised manner. One goal is to discover a set of aspects which are previously unknown for the domain, and predict the user's ratings on each aspect for each review. Another goal is to detect key terms for each aspect. Existing works on predicting aspect ratings fail to handle the aspect sparsity problem in the review texts leading to unreliable prediction. We propose a new generative model to tackle the latent aspect mining problem in an unsupervised manner. By considering the user and item side information of review texts, we introduce two latent variables, namely, user intrinsic aspect interest and item intrinsic aspect quality facilitating better modeling of aspect generation leading to improvement on the accuracy and reliability of predicted aspect ratings. Furthermore, we provide an analytical investigation on the Maximum A Posterior (MAP) optimization problem used in our proposed model and develop a new block coordinate gradient descent algorithm to efficiently solve the optimization with closed-form updating formulas. We also study its convergence analysis. Experimental results on the two real-world product review corpora demonstrate that our proposed model outperforms existing state-of-the-art models.

Question: What is the difference between aspect mining and aspect extraction?


Optimal detection of fetal chromosomal abnormalities by massively parallel DNA sequencing of cell-free fetal DNA from maternal blood.. BACKGROUND Massively parallel DNA sequencing of cell-free fetal DNA from maternal blood can detect fetal chromosomal abnormalities. Although existing algorithms focus on the detection of fetal trisomy 21 (T21), these same algorithms have difficulty detecting trisomy 18 (T18).   METHODS Blood samples were collected from 1014 patients at 13 US clinic locations before they underwent an invasive prenatal procedure. All samples were processed to plasma, and the DNA extracted from 119 samples underwent massively parallel DNA sequencing. Fifty-three sequenced samples came from women with an abnormal fetal karyotype. To minimize the intra- and interrun sequencing variation, we developed an optimized algorithm by using normalized chromosome values (NCVs) from the sequencing data on a training set of 71 samples with 26 abnormal karyotypes. The classification process was then evaluated on an independent test set of 48 samples with 27 abnormal karyotypes.   RESULTS Mapped sites for chromosomes of interest in the sequencing data from the training set were normalized individually by calculating the ratio of the number of sites on the specified chromosome to the number of sites observed on an optimized normalizing chromosome (or chromosome set). Threshold values for trisomy or sex chromosome classification were then established for all chromosomes of interest, and a classification schema was defined. Sequencing of the independent test set led to 100% correct classification of T21 (13 of 13) and T18 (8 of 8) samples. Other chromosomal abnormalities were also identified.   CONCLUSION Massively parallel sequencing is capable of detecting multiple fetal chromosomal abnormalities from maternal plasma when an optimized algorithm is used.

Question: What is the optimal detection of fetal chromosomal abnormalities by massively parallel DNA sequencing of cell-free fetal DNA from maternal blood?


A Low-Bandwidth Network File System. Users rarely consider running network file systems over slow or wide-area networks, as the performance would be unacceptable and the bandwidth consumption too high. Nonetheless, efficient remote file access would often be desirable over such networks---particularly when high latency makes remote login sessions unresponsive. Rather than run interactive programs such as editors remotely, users could run the programs locally and manipulate remote files through the file system. To do so, however, would require a network file system that consumes less bandwidth than most current file systems.This paper presents LBFS, a network file system designed for low-bandwidth networks. LBFS exploits similarities between files or versions of the same file to save bandwidth. It avoids sending data over the network when the same data can already be found in the server's file system or the client's cache. Using this technique in conjunction with conventional compression and caching, LBFS consumes over an order of magnitude less bandwidth than traditional network file systems on common workloads.

Question: What is a low-bandwidth network file system?


Ovariohysterectomy versus ovariectomy for elective sterilization of female dogs and cats: is removal of the uterus necessary?. Views: Commentary 1409 E sterilization of female dogs and cats is one of the most common procedures performed in veterinary practice and is considered by private veterinary practitioners as one of the most important skills required of new graduates. Potential benefits of sterilization include population control, prevention of diseases of the reproductive tract, and elimination of undesirable behaviors associated with hormonal cycling. The AVMA and the Association of Shelter Veterinarians both promote elective sterilization of female dogs and cats as integral to reducing euthanasia of unwanted dogs and cats. Sterilization of female dogs and cats can be accomplished by removing both the ovaries and uterus (ovariohysterectomy) or by removing the ovaries alone (ovariectomy). Ovariohysterectomy has historically been recommended in the United States and Canada and is currently emphasized at schools and colleges of veterinary medicine in these countries. To our knowledge, only one of the most frequently used surgical textbooks in the United States and Canada describes ovariectomy, and ovariectomy is generally not taught to veterinary students during their surgical laboratories. The Clinical Proficiency Examination, which is the final step in the Educational Commission for Foreign Veterinary Graduates' program for establishing the educational equivalence of graduates of nonaccredited veterinary schools seeking licensure in the United States or Canada, requires "complete removal of both ovaries and removal of the majority of the uterus" to obtain a passing grade. Despite the apparent preference for ovariohysterectomy in the United States and Canada, ovariectomy appears to have become the standard of care in many European countries. In addition, with the development of minimally invasive surgical techniques, laparoscopic ovariectomy has gained popular

Question: What is the difference between ovariohysterectomy and ovariectomy?


Evaluating question answering over linked data. The availability of large amounts of open, distributed and structured semantic data on the web has no precedent in the history of computer science. In recent years, there have been important advances in semantic search and question answering over RDF data. In particular, natural language interfaces to online semantic data have the advantage that they can exploit the expressive power of Semantic Web data models and query languages, while at the same time hiding their complexity from the user. However, despite the increasing interest in this area, there are no evaluations so far that systematically evaluate this kind of systems, in contrast to traditional question answering and search interfaces to document spaces. To address this gap, we have set up a series of evaluation challenges for question answering over linked data. The main goal of the challenge was to get insight into the strengths, capabilities and current shortcomings of question answering systems as interfaces to query linked data sources, as well as benchmarking how these interaction paradigms can deal with the fact that the amount of RDF data available on the web is very large and heterogeneous with respect to the vocabularies and schemas used. Here we report on the results from the first and second of such evaluation campaigns. We also discuss how the second evaluation addressed some of the issues and limitations which arose from the first one, as well as the open issues to be addressed in future competitions.

Question: What is the first large-scale Canadian peacekeeping mission?


10 An Empirical Approach for the Evaluation of Voice User Interfaces. Nowadays, the convergence of devices, electronic computing, and massive media produces huge volumes of information, which demands the need for faster and more efficient interaction between users and information. How to make information access manageable, efficient, and easy becomes the major challenge for Human-Computer Interaction (HCI) researchers. The different types of computing devices, such as PDAs (personal digital assistants), tablet PCs, desktops, game consoles, and the next generation phones, provide many different modalities for information access. This makes it possible to dynamically adapt application user interfaces to the changing context. However, as applications go more and more pervasive, these devices show theirs limited input/output capacity caused by small visual displays, use of hands to operate buttons and the lack of an alphanumeric keyboard and mouse (Gu & Gilbert, 2004). Voice User Interface (VUI) systems are capable of, besides recognizing the voice of their users, to understand voice commands, and to provide responses to them, usually, in real time. The state-of-the-art in speech technology already allows the development of automatic systems designed to work in real conditions. VUI is perhaps the most critical factor in the success of any automated speech recognition (ASR) system, determining whether the user experience will be satisfying or frustrating, or even whether the customer will remain one. This chapter describes a practical methodology for creating an effective VUI design. The methodology is scientifically based on principles in linguistics, psychology, and language technology (Cohen et al. 2004; San-Segundo et al., 2005). Given the limited input/output capabilities of mobile devices, speech presents an excellent way to enter and retrieve information either alone or in combination with other modalities. Furthermore, people with disabilities should be provided

Question: What is the difference between a voice user interface and a speech user interface?


Sensorized Garments and Textrode-Enabled Measurement Instrumentation for Ambulatory Assessment of the Autonomic Nervous System Response in the ATREC Project. Advances in textile materials, technology and miniaturization of electronics for measurement instrumentation has boosted the development of wearable measurement systems. In several projects sensorized garments and non-invasive instrumentation have been integrated to assess on emotional, cognitive responses as well as physical arousal and status of mental stress through the study of the autonomous nervous system. Assessing the mental state of workers under stressful conditions is critical to identify which workers are in the proper state of mind and which are not ready to undertake a mission, which might consequently risk their own life and the lives of others. The project Assessment in Real Time of the Stress in Combatants (ATREC) aims to enable real time assessment of mental stress of the Spanish Armed Forces during military activities using a wearable measurement system containing sensorized garments and textile-enabled non-invasive instrumentation. This work describes the multiparametric sensorized garments and measurement instrumentation implemented in the first phase of the project required to evaluate physiological indicators and recording candidates that can be useful for detection of mental stress. For such purpose different sensorized garments have been constructed: a textrode chest-strap system with six repositionable textrodes, a sensorized glove and an upper-arm strap. The implemented textile-enabled instrumentation contains one skin galvanometer, two temperature sensors for skin and environmental temperature and an impedance pneumographer containing a 1-channel ECG amplifier to record cardiogenic biopotentials. With such combinations of garments and non-invasive measurement devices, a multiparametric wearable measurement system has been implemented able to record the following physiological paramet

Question: What is the ATREC project?


Convolutional Neural Network for Brain MR Imaging Extraction Using Silver-Standards Masks. Convolutional neural networks (CNN) for medical imaging are constrained by the number of annotated data required for the training stage. Usually, manual annotation is considered to be the "gold-standard'. However, medical imaging datasets with expert manual segmentation are scarce as this step is time-consuming and expensive. Moreover, the single-rater manual annotation is often used in data-driven approaches making the algorithm optimal for one guideline only. In this work, we propose a convolutional neural network (CNN) for brain magnetic resonance (MR) imaging extraction, fully trained with what we refer to as silver-standard masks. To the best of our knowledge, our approach is the first deep learning approach that is fully trained using silver-standards masks, having an optimal generalization. Furthermore, regarding the Dice coefficient, we outperform the current skull-stripping (SS) state-of-the-art method in three datasets. Our method consists of 1) a dataset with silver-standard masks as input, 2) a tri-planar method using parallel 2D U-Net-based CNNs, which we refer to as CONSNet, and 3) an auto-context implementation of CONSNet. CONSNet refers to our integrated approach, i.e., training with silver-standard masks and us∗Corresponding author Email address: oeslle@dca.fee.unicamp.br (Oeslle Lucena) URL: miclab.fee.unicamp.br (Oeslle Lucena) Preprint submitted to Medical Image Analysis April 13, 2018 ar X iv :1 80 4. 04 98 8v 1 [ cs .C V ] 1 3 A pr 2 01 8 ing a CNN architecture. Masks are generated by forming a consensus from a set of publicly available automatic segmentation methods using the simultaneous truth and performance level estimation (STAPLE) algorithm. The CNN architecture is robust, with dropout and batch normalization as regularizers. It was inspired by the 2D U-Net model published by the RECOD group. We conducted our analysis using three publicly available

Question: What is the difference between a convolutional neural network and a deep learning model?


77 GHz radar transceiver with dual integrated antenna elements. A complete radar transceiver for 77 GHz with two integrated antenna elements is presented. Based on a previously published design [1], two of the transmit and receive channels of the transceiver are supplemented with integrated antenna elements. The antennas exhibit a well defined antenna pattern with an efficiency of better than 50%.

Question: What is the antenna pattern of the 77 GHz radar transceiver?


Resilient packet delivery through software defined redundancy: An experimental study. Mission-critical applications that use computer networks require guaranteed communication with bounds on the time needed to deliver packets, even if hardware along a path fails or congestion occurs. Current networking technologies follow a reactive approach in which retransmission mechanisms and routing update protocols respond once packet loss occurs. We present a proactive approach that pre-builds and monitors redundant paths to ensure timely delivery with no recovery latency, even in the case of a single-link failure. The paper outlines the approach, describes a new mechanism we call a redundancy controller, and explains the use of SDN to establish and change paths. The paper also reports on a prototype system and gives experimental measurements.

Question: How does a packet delivery system work?


Alike people, alike interests? Inferring interest similarity in online social networks. Understanding how much two individuals are alike in their interests (i.e., interest similarity) has become virtually essential for many applications and services in Online Social Networks (OSNs). Since users do not always explicitly elaborate their interests in OSNs like Facebook, how to determine users' interest similarity without fully knowing their interests is a practical problem. In this paper, we investigate how users' interest similarity relates to various social features (e.g. geographic distance); and accordingly infer whether the interests of two users are alike or unalike where one of the users' interests are unknown. Relying on a large Facebook dataset, which contains 479, 048 users and 5, 263, 351 user-generated interests, we present comprehensive empirical studies and verify the homophily of interest similarity across three interest domains (movies, music and TV shows). The homophily reveals that people tend to exhibit more similar tastes if they have similar demographic information (e.g., age, location), or if they are friends. It also shows that the individuals with a higher interest entropy usually share more interests with others. Based on these results, we provide a practical prediction model under a real OSN environment. For a given user with no interest information, this model can select some individuals who not only exhibit many interests but also probably achieve high interest similarities with the given user. Eventually, we illustrate a use case to demonstrate that the proposed prediction model could facilitate decision-making for OSN applications and services.

Question: How to infer interest similarity in online social networks?


Adolescent development and the regulation of youth crime.. Elizabeth Scott and Laurence Steinberg explore the dramatic changes in the law's conception of young offenders between the end of the nineteenth century and the beginning of the twenty-first. At the dawn of the juvenile court era, they note, most youths were tried and punished as if they were adults. Early juvenile court reformers argued strongly against such a view, believing that the justice system should offer young offenders treatment that would cure them of their antisocial ways. That rehabilitative model of juvenile justice held sway until a sharp upswing in youth violence at the end of the twentieth century led both public opinion and public policy toward a view that youths should be held to the same standard of criminal accountability as adults. Lawmakers seemed to lose sight of developmental differences between adolescents and adults. But Scott and Steinberg note that lawmakers and the public appear now to be rethinking their views once more. A justice system that operates on the principle of "adult time for adult crime" now seems to many to take too little note of age and immaturity in calculating criminal punishment. In 2005 the United States Supreme Court abolished the juvenile death penalty as cruel and unusual punishment, emphasizing that the immaturity of adolescents made them less culpable than adult criminals. In addition, state legislatures recently have repealed or moderated some of the punitive laws they recently enacted. Meanwhile, observe the authors, public anger has abated and attitudes toward young offenders have softened somewhat. In response to these changes, Scott and Steinberg argue that it is appropriate to reexamine juvenile justice policy and to devise a new model for the twenty-first century. In this article, they propose what they call a developmental model. They observe that substantial new scientific evidence about adolescence and criminal activity by adolescents provides

Question: What is the difference between a juvenile and an adult?


SURVEY ON REVIEW SPAM DETECTION. The proliferation of E-commerce sites has made web an excellent source of gathering customer reviews about products; as there is no quality control anyone one can write anything which leads to review spam. This paper previews and reviews the substantial research on Review Spam detection technique. Further it provides state of art depicting some previous attempt to study review spam detection. KeywordsNatural language processing, reviews centric spam detection, reviewer centric spam detection

Question: What is review spam?


A Sparse Matrix Library in C + + for High PerformanceArchitectures. We describe an object oriented sparse matrix library in C++ built upon the Level 3 Sparse BLAS proposal [5] for portability and performance across a wide class of machine architectures. The C++ library includes algorithms for various iterative methods and supports the most common sparse data storage formats used in practice. Besides simplifying the subroutine interface, the object oriented design allows the same driving code to be used for various sparse matrix formats, thus addressing many of the di culties encountered with the typical approach to sparse matrix libraries. We emphasize the fundamental design issues of the C++ sparse matrix classes and illustrate their usage with the preconditioned conjugate gradient (PCG) method as an example. Performance results illustrate that these codes are competitive with optimized Fortran 77. We discuss the impact of our design on elegance, performance, maintainability, portability, and robustness.

Question: What is the preconditioned conjugate gradient method?


Handbook of genetic algorithms. In this paper, the effect of Genetic algorithm (GA) on the enhancement of the texture and quality of plants visual L. Davis, The handbook of Genetic Algorithms. Genetic Algorithm is one of many methods that can be used to create a schedule. This method Davis, L.: Handbook on Genetic Algorithms. Van Nostrand. In this research, genetic algorithm approach has been applied for solving exam (18) Davis L., Handbook of Genetic Algorithms, New York, Van Nostrand.

Question: What is genetic algorithm?


Expressive speech-driven facial animation. Speech-driven facial motion synthesis is a well explored research topic. However, little has been done to model expressive visual behavior during speech. We address this issue using a machine learning approach that relies on a database of speech-related high-fidelity facial motions. From this training set, we derive a generative model of expressive facial motion that incorporates emotion control, while maintaining accurate lip-synching. The emotional content of the input speech can be manually specified by the user or automatically extracted from the audio signal using a Support Vector Machine classifier.

Question: How to model expressive facial behavior during speech?


Efficient Support Vector Classifiers for Named Entity Recognition. NamedEntity (NE) recognitionis a task in which proper nouns and numerical information are extractedfrom documentsandareclassifiedinto categoriessuchas person,organization,and date. It is a key technologyof InformationExtractionand Open-DomainQuestionAnswering.First,weshow thatanNE recognizerbasedonSupportVectorMachines(SVMs)givesbetterscoresthanconventional systems.However, off-the-shelfSVM classifiersare too inefficient for this task.Therefore,we presenta methodthat makes the systemsubstantiallyfaster . This approachcan also be applied to other similar taskssuchaschunkingandpart-of-speechtagging. We alsopresentanSVM-basedfeatureselection methodandanefficient trainingmethod.

Question: What is the name of the paper?


Deep HyperNEAT : Evolving the Size and Depth of the Substrate Evolutionary. This report describes DeepHyperNEAT, an extension of HyperNEAT to allow it to alter the topology of its indirectlyencoded neural network (called the substrate) so that it can continue to grow and increase in complexity over evolution. This aim is accomplished by augmenting HyperNEAT's compositional pattern producing networks (CPPNs) with new information that allows them to represent substrate topology, and by adding three novel mutations to HyperNEAT that exploit this new information. The purpose of this report is to detail the method and validate its ability to evolve, which is shown through a simple XOR-based test. Significantly more work will be needed to analyze the algorithmic and scientific implications of these new capabilities, but by releasing this report it becomes possible for others also to explore the opportunities that such an extension opens up. A link to associated source code is also provided at the end of this document. Introduction HyperNEAT [1; 2; 3] (Hypercube-based NeuroEvolution of Augmenting Topologies) is a method for evolving neural networks (NNs) through an indirect encoding based on the NEAT method [4] that came before it. The main idea in HyperNEAT is that a special genetic representation called a compositional pattern producing network (CPPN) [5] that is evolved by NEAT generates a pattern of weights that connect a fixed set of neurons positioned within a two-dimensional or three-dimensional space called the substrate. A longstanding limitation of the conventional HyperNEAT algorithm is that while the CPPN can increase in size, the number of neurons and layers in the substrate remains fixed from the beginning of evolution. While there exists one method called evolvable substrate HyperNEAT (ES-HyperNEAT) [6] that allows HyperNEAT to increase the complexity of its substrate that indeed offers opportunities not available in the original HyperNEAT, the new method pr

Question: What is the difference between hyperNEAT and deep hyperNEAT?


Modeling of magnetically biased graphene patch frequency selective surface (FSS). A free-standing magnetically biased graphene patch frequency selective surface (FSS) is modelled in this paper. Its transmission coefficients of co- and cross-polarizations can be obtained with an equivalent tensorial surface conductivity. Then, the rotation angle for normal incidence is explored with different values of biasing magnetic field B0. The maximum rotation angle provided by the magnetically biased graphene patch FSS is 43° at 4.7 THz with B0=2.5 T, which is much larger than the rotation angle provided by a graphene sheet. This is very promising for THz nano-devices based on the giant Faraday rotation of graphenes.

Question: How large is the rotation angle provided by the magnetically biased graphene patch FSS?


A UWB based Localization System for Indoor Robot Navigation. For robots to become more popular for domestic applications, the short comings of current indoor navigation technologies have to be overcome. In this paper, we propose the use of UWB-IR for indoor robot navigation. Various parts of an actual implementation of a UWB-IR based robot navigation system such as system architecture, RF sub-system design, antennas and localization algorithms are discussed. It is shown that by properly addressing the various issues, a localization error of less than 25 cm can be achieved at all points within a realistic indoor localization space.

Question: How does a robot navigate indoors?


Matroids and the greedy algorithm. (0) Many discrete programming algorithms are being proposed. One thing most of them have in common is that they do not work very well. Solving problems that are a priori finite, astronomically finite, is preferably a matter of finding algorithms that are s o m e h o w better than finite. These considerations prompt looking for good algorithms and trying to understand how and why at least a few combinatorial problems have them. (1) Let H be a finite (for convenience) set of real-valued vectors , x = [xj] , ] ~ E. Often all the members of H will be integer-valued; often they will all be {0, 1}-valued. The index-set, E, is any finite set of elements. Let c = [cj], ] ~ E, be any real vector on E, called the objective or weighting of E. The problem of finding a member o f H which maximizes (or minimizes) cx = iN cjx/, j ~ E, we call a loco problem or loco programming. "Loco" stands for "linear-objective combinatorial". (2) In order for a loco problem to be a completely defined problem, the way H is given must of course be specified. There are various ways to describe implicitly very large sets H so tha t it is relatively easy to determine whether or not any particular vector is a member of H. One well-known:way is in linear programming, where H is the set of extreme points of the solution-set of a given finite system, L, of linear equations and <_ type linear inequalities in the variables xj (briefly, a

Question: What is a loco problem?


The Evolution of the Peer-to-Peer File Sharing Industry and the Security Risks for Users. Peer-to-peer file sharing is a growing security risk for firms and individuals. Users who participate in these networks to share music, pictures, and video are subject to many security risks including inadvertent publishing of private information, exposure to viruses and worms, and the consequences of spyware. In this paper, we examine the peer-to-peer file sharing phenomena, including an overview of the industry, its business models, and evolution. We describe the information security risks users' face including personal identification disclosure and leakage of proprietary business information. We illustrate those risks through honey-pot experiments and discuss how peer-to-peer industry dynamics are contributing to the security problem.

Question: What is the peer-to-peer file sharing industry?


Dynamic simultaneous fare proration for large-scale network revenue management. Network revenue management is concerned with managing demand for products that require inventory from one or several resources by controlling product availability and/or prices in order to maximize expected revenues subject to the available resource capacities. One can tackle this problem by decomposing it into resource-level subproblems that can be solved efficiently, e.g. by dynamic programming (DP). We propose a new dynamic fare proration method specifically having large-scale applications in mind. It decomposes the network problem by fare proration and solves the resource-level dynamic programs simultaneously using simple, endogenously obtained dynamic marginal capacity value estimates to update fare prorations over time. An extensive numerical simulation study demonstrates that the method results in tightened upper bounds on the optimal expected revenue, and that the obtained policies are very effective with regard to achieved revenues and required runtime.

Question: What is the dynamic fare proration method?


Women " Take Care , " Men " Take Charge " : Managers ' Stereotypic Perceptions of Women and Men Leaders. This study explored possible underpinnings of findings from earlier research in which women's overall leadership competence was less favorably evaluated than men's. The authors examined perceptions held by senior managers, 34% of whom were CEOs, of women's and men's effectiveness at 10 key leadership behaviors. Respondents generally perceived that women were more effective than men at caretaking leader behaviors; and that men were more effective than women at actionoriented, "take-charge" leader behaviors. Notably, male respondents perceived that the behavior at which men leaders most outperformed women was problemsolving. The authors propose that this perception could potentially undermine the influence of women leaders.

Question: What is the difference between caretaking and actionoriented leader behaviors?


Pseudo Random Pulse Driven Advanced In-Cell Touch Screen Panel for Spectrum Spread Electromagnetic Interference. For the first time, we analyze the mechanism of electromagnetic interference (EMI) in an advanced in-cell touch (AIT) panel, which is a state-of-the-art in-cell touch screen panel technology. The AIT panel has stronger EMI generation at a specific frequency band (0.15 ~ 30 MHz) due to a load free driving (LFD) method. The LFD is adopted to overcome the structural vulnerability of in-cell touch panel, which incurs large parasitic capacitance due to the touch electrodes within the display panel. In order to overcome the EMI problem, we present a novel driving method using pseudo random pulse (PRP). The power spectrum of PRP is well spread over the frequency band, resulting in a lower EMI. We measured the EMI level with a near-field probe, and the proposed driving method shows the EMI reduction of 6.5 dB. This EMI reduction is accomplished without structural reconfiguration, as well as the touch performance remains the same as that before PRP is applied. Therefore, the proposed driving method can be utilized in the field of automotive, military, and aviation industries as a user interface which requires high touch performance and low EMI generation due to the peculiarities.

Question: What is the mechanism of electromagnetic interference in an advanced in-cell touch (AIT) panel?