Occlusion horizons for driving through urban scenery. Wepresentarapidocclusioncullingalgorithmspecificallydesigned for urbanenvironments. For eachframe,an occlusionhorizonis beingbuilt on-the-flyduring a hierarchicalfront-to-backtraversal of the scene.All conservatively hiddenobjectsareculled, while all theoccludingimpostorsof all conservatively visibleobjectsare addedto the  D occlusionhorizon.Our framework alsosupports levels-of-detail(LOD) renderingby estimatingthe visible areaof the projectionof an objectin orderto selecttheappropriateLOD for eachobject.This algorithmrequiresno substantial preprocessing andnoexcessi ve storage. In a test sceneof 10,000buildings, the cull phasetook 11 ms on a PentiumII333 MHz and45 ms on an SGI Octaneper frame on average. In typical views, the occlusionhorizonculled away 80-90%of theobjectsthatwerewithin theview frustum,giving a 10 timesspeedupover view frustumculling alone.Combiningthe occlusionhorizonwith LOD renderinggavea17 timesspeedupon anSGIOctane,and23 timeson aPII. CR Categoriesand SubjectDescriptors: I.3.7[ComputerGraphics]: I.3.7 Three-Dimensional GraphicsandRealism.

Question: What is the difference between a LOD and a LOD rendering?


Conservation cores: reducing the energy of mature computations. Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. In this regime, specialized, energy-efficient processors can increase parallelism by reducing the per-computation power requirements and allowing more computations to execute under the same power budget. To pursue this goal, this paper introduces conservation cores. Conservation cores, or c-cores, are specialized processors that focus on reducing energy and energy-delay instead of increasing performance. This focus on energy makes c-cores an excellent match for many applications that would be poor candidates for hardware acceleration (e.g., irregular integer codes). We present a toolchain for automatically synthesizing c-cores from application source code and demonstrate that they can significantly reduce energy and energy-delay for a wide range of applications. The c-cores support patching, a form of targeted reconfigurability, that allows them to adapt to new versions of the software they target. Our results show that conservation cores can reduce energy consumption by up to 16.0x for functions and by up to 2.1x for whole applications, while patching can extend the useful lifetime of individual c-cores to match that of conventional processors.

Question: What is a conservation core?


Data Preparation for Mining World Wide Web Browsing Patterns. The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. The complexity of tasks such as Web site design, Web server design, and of simply navigating through a Web site have increased along with this growth. An important input to these design tasks is the analysis of how a Web site is being used. Usage analysis includes straightforward statistics, such as page access frequency, as well as more sophisticated forms of analysis, such as finding the common traversal paths through a Web site. Web Usage Mining is the application of data mining techniques to usage logs of large Web data repositories in order to produce results that can be used in the design tasks mentioned above. However, there are several preprocessing tasks that must be performed prior to applying data mining algorithms to the data collected from server logs. This paper presents several data preparation techniques in order to identify unique users and user sessions. Also, a method to divide user sessions into semantically meaningful transactions is defined and successfully tested against two other methods. Transactions identified by the proposed methods are used to discover association rules from real world data using the WEBMINER system [15].

Question: How to divide user sessions into semantically meaningful transactions?


Sparse code multiple access. Multicarrier CDMA is a multiplexing approach in which modulated QAM symbols are spread over multiple OFDMA tones by using a generally complex spreading sequence. Effectively, a QAM symbol is repeated over multiple tones. Low density signature (LDS) is a version of CDMA with low density spreading sequence allowing us to take advantage of a near optimal ML receiver with practically feasible complexity. In this paper, we propose a new multiple access scheme so called sparse code multiple access (SCMA) which still enjoys the low complexity reception technique but with better performance compared to LDS. In SCMA, the procedure of bit to QAM symbol mapping and spreading are combined together and incoming bits are directly mapped to a multidimensional codeword of an SCMA codebook set. Each layer or user has its dedicated codebook. Shaping gain of a multidimensional constellation is the main source of the performance improvement in comparison to the simple repetition of QAM symbols in LDS. In general, SCMA codebook design is an optimization problem. A systematic sub-optimal approach is proposed here for SCMA codebook design.

Question: What is sparse code multiple access?


Architectures for Natural Language Generation: Problems and Perspectives. Current research in natural language generation is situated in a computational linguistics tradition that was founded several decades ago. We critically analyse some of the architectural assumptions underlying existing systems and point out some problems in the domains of text planning and lexicalization. Guided by the identification of major generation challenges viewed from the angles of knowledge-based systems and cognitive psychology, we sketch some new directions for future research.

Question: What is the difference between knowledge-based systems and cognitive psychology?


Hardware Accelerated Per-Pixel Displacement Mapping. In this paper we present an algorithm capable of rendering a displacement mapped triangle mesh interactively on latest GPUs. The algorithm uses only pixel shaders and does not rely on adaptively adding geometry. All sampling of the displacement map takes place in the pixel shader and bior trilinear filtering can be applied to it, and at the same time as the calculations are done per pixel in the shader, the algorithm has automatic level of detail control. The triangles of the base mesh are extruded along the respective normal directions and then the resulting prisms are rendered by casting rays inside and intersecting them with the displaced surface. Two different implementations are discussed in detail.

Question: How to render a displacement mapped triangle mesh interactively on latest GPUs?


SlowFast Networks for Video Recognition. We present SlowFast networks for video recognition. Our model involves (i) a Slow pathway, operating at low frame rate, to capture spatial semantics, and (ii) a Fast pathway, operating at high frame rate, to capture motion at fine temporal resolution. The Fast pathway can be made very lightweight by reducing its channel capacity, yet can learn useful temporal information for video recognition. Our models achieve strong performance for both action classification and detection in video, and large improvements are pin-pointed as contributions by our SlowFast concept. We report 79.0% accuracy on the Kinetics dataset without using any pre-training, largely surpassing the previous best results of this kind. On AVA action detection we achieve a new stateof-the-art of 28.3 mAP. Code will be made publicly available.

Question: What is the slowfast network for video recognition?


Comparison of Longley-Rice, ITM and ITWOM propagation models for DTV and FM broadcasting. With the rapid deployment of digital TV, there is an increasing need for accurate point-to-area prediction tools. There is a great deal of propagation models for coverage prediction of DTV. Some of them are pure empirical models, and others are mixed, empirical-analytical models, based on measurement campaigns and electromagnetic theory. The aim of this paper is to compare accurate measurements taken by a Rohde & Schwarz FSH-3 portable spectrum analyzer and precision antennas (biconical and log-periodic), with simulation results derived from coverage prediction models, like the NTIA-ITS Longley-Rice model, the ITM (Irregular Terrain Model) using the 3-arc-second SRTM (Satellite Radar Topography Mission) data that is available freely, and the newer ITWOM (Irregular Terrain with Obstructions Model) model which combines equations from ITU-R P.1546 model with Beer's law and Snell's law. Furthermore, measurements for analog FM broadcasting are compared to predictions from the above mentioned models.

Question: What is the difference between the longley-rice model and the ITM model?


Rapid Graph Layout Using Space Filling Curves. Network data frequently arises in a wide variety of fields, and node-link diagrams are a very natural and intuitive representation of such data. In order for a node-link diagram to be effective, the nodes must be arranged well on the screen. While many graph layout algorithms exist for this purpose, they often have limitations such as high computational complexity or node colocation. This paper proposes a new approach to graph layout through the use of space filling curves which is very fast and guarantees that there will be no nodes that are colocated. The resulting layout is also aesthetic and satisfies several criteria for graph layout effectiveness.

Question: What is a space filling curve?


Bayesian Compressive Sensing. The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be reconstructed accurately using only a small number M Lt N of basis-function coefficients associated with B. Compressive sensing is a framework whereby one does not measure one of the aforementioned N-dimensional signals directly, but rather a set of related measurements, with the new measurements a linear combination of the original underlying N-dimensional signal. The number of required compressive-sensing measurements is typically much smaller than N, offering the potential to simplify the sensing system. Let f denote the unknown underlying N-dimensional signal, and g a vector of compressive-sensing measurements, then one may approximate f accurately by utilizing knowledge of the (under-determined) linear relationship between f and g, in addition to knowledge of the fact that f is compressible in B. In this paper we employ a Bayesian formalism for estimating the underlying signal f based on compressive-sensing measurements g. The proposed framework has the following properties: i) in addition to estimating the underlying signal f, "error bars" are also estimated, these giving a measure of confidence in the inverted signal; ii) using knowledge of the error bars, a principled means is provided for determining when a sufficient number of compressive-sensing measurements have been performed; iii) this setting lends itself naturally to a framework whereby the compressive sensing measurements are optimized adaptively and hence not determined randomly; and iv) the framework accounts for additive noise in the compressive-sensing measurements and provides an estimate of the noise variance. In this paper we present the underlying theory, an associated algorithm, example results, and provide comparisons to other compressive-sensing inversion algorithms in the literature.

Question: What is Bayesian Compressive Sensing?


"No-Touch" Technique for Lip Enhancement.. BACKGROUND The purpose of this study was to examine the anatomical principles of lip structure as they relate to individualized lip enhancement procedures and to describe a technique that does not violate lip mucosa during injection.   METHODS A retrospective analysis of patients undergoing lip enhancement procedures between 2001 and 2014 was performed. Preprocedural and postprocedural photographs were analyzed for lip subunit changes. A stepwise treatment algorithm targeting specific anatomical subunits of lip is described.   RESULTS Four hundred ten patients were treated with a "no-touch" technique for lip enhancement. Lip profile is determined by the position of the white roll. The white roll is accessed by a 30-gauge needle at a point 5 mm lateral to the oral commissure and at the base of the philtral columns. Lip projection is established by vermilion formation contributing to the arc of the Cupid's bow. To improve projection, the labial commissure is entered with a 25-gauge cannula and tunneled into the submucosal space between the white and red rolls. Lip augmentation is a direct reflection of the prominence of the red line and can be approached in a perpendicular fashion with a needle or cannula descending to the level of the wet-dry junction.   CONCLUSIONS Accurate assessment of the white and red rolls, arc of Cupid's bow, philtrum, and gingival show can guide the injector on the proper enhancement that individual patients require. The no-touch technique minimizes mucosal trauma. Tailoring treatment toward lip profile, projection, and/or augmentation can yield predictable and reproducible outcomes in this commonly performed cosmetic procedure.

Question: What is the no-touch technique for lip enhancement?


Vishleshan: Performance Comparison and Programming Process Mining Algorithms in Graph-Oriented and Relational Database Query Languages. Process-Aware Information System (PAIS) are IT systems that manages, supports business processes and generate large event logs from execution of business processes. Process Mining consists of analyzing event logs generated by PAISs and discover business process models and check for conformance between the discovered and actual models. The large volume of event logs generated are stored in databases. Relational databases perform well for certain class of applications. However, there are certain class of applications for which relational databases are not able to scale. Several NoSQL databases have emerged to encounter the challenges of scalability in traditional databases. Discovering social network from event logs is one of the most challenging and important Process Mining task. Similar-Task algorithm is one of the most widely used Organizational Mining techniques. Our objective is to investigate which of the databases (Relational or Graph) perform better for Organizational Mining under Process Mining. We implement Similar-Task algorithm on relational and NoSQL (graph oriented) databases using only query language constructs. We conduct empirical analysis on a large real world data set to compare the performance of row-oriented database and NoSQL graph-oriented database.

Question: What is the difference between a relational database and a graph database?


Step negotiation with wheel traction: a strategy for a wheel-legged robot. This paper presents a quasi-static step climbing behaviour for a minimal sensing wheel-legged quadruped robot called PAW. In the quasi-static climbing maneuver, the robot benefits from wheel traction and uses its legs to reconfigure itself with respect to the step during the climb. The control methodology with the corresponding controller parameters is determined and the state machine for the maneuver is developed. With this controller, PAW is able to climb steps higher than its body clearance. Furthermore, any step height up to this maximum achievable height can be negotiated autonomously with a single set of controller parameters, without knowledge of the step height or distance to the step.

Question: How to negotiate a step?


A framework for consciousness. Here we summarize our present approach to the problem of consciousness. After an introduction outlining our general strategy, we describe what is meant by the term 'framework' and set it out under ten headings. This framework offers a coherent scheme for explaining the neural correlates of (visual) consciousness in terms of competing cellular assemblies. Most of the ideas we favor have been suggested before, but their combination is original. We also outline some general experimental approaches to the problem and, finally, acknowledge some relevant aspects of the brain that have been left out of the proposed framework.

Question: What is the framework for consciousness?


Use of Design Patterns in PHP-Based Web Application Frameworks. It is known that design patterns of object-oriented programming are used in the design of Web applications, but there is no sufficient information which data patterns are used, how often they are used, and the level of quality at which they are used. This paper describes the results concerning the use of design patterns in projects which develop PHP-based Web application frameworks. Documentation and source code were analysed for 10 frameworks, finding that design patterns are used in the development of Web applications, but not too much and without much consistency. The results and conclusions can be of use when planning and developing new projects because the existing experience can be taken into account. The paper also offers information which design patterns are not used because they may be artificial or hard-to-use in real projects. Alternatively, developers may simply lack information on the existence of the design patterns.

Question: What are design patterns?


Educational data mining and its role in determining factors affecting students academic performance: A systematic review. Education helps people develop as individuals. It not only helps build social skills but also enhances the problem solving and decision making skills of individuals. With the growing number of schools, colleges and universities around the globe, education now has taken new dimension. The main focus of higher Educational Institutes is to improve the overall quality and effectiveness of education. Predicting the performance of student and Predicting the Future in this world of Big Data is the need of Today in Education. The crude data from educational organizations act as a gold mine which facilitate the analysts and designers to make a system that will improve the overall teaching and learning process. This new field coined as Educational Data mining helps in Predicting the Future and Changing the Future. In this paper we have studied what is Educational Data Mining and what are the Application areas of EDM, various techniques of EDM and the factors affecting the students' Academic Performance and the Teaching-Learning process.

Question: What is Educational Data Mining?


Gender identity disorder in twins: a review of the case report literature.. INTRODUCTION The etiology of gender identity disorder (GID) remains largely unknown. In recent literature, increased attention has been attributed to possible biological factors in addition to psychological variables.   AIM To review the current literature on case studies of twins concordant or discordant for GID.   METHODS A systematic, comprehensive literature review.   RESULTS Of 23 monozygotic female and male twins, nine (39.1%) were concordant for GID; in contrast, none of the 21 same-sex dizygotic female and male twins were concordant for GID, a statistically significant difference (P=0.005). Of the seven opposite-sex twins, all were discordant for GID.   CONCLUSIONS These findings suggest a role for genetic factors in the development of GID.

Question: What is the etiology of gender identity disorder?


The five-factor model of personality and managerial performance: validity gains through the use of 360 degree performance ratings.. This study investigated the usefulness of the five-factor model (FFM) of personality in predicting two aspects of managerial performance (task vs. contextual) assessed by utilizing the 360 degree performance rating system. The authors speculated that one reason for the low validity of the FFM might be the failure of single-source (e.g., supervisor) ratings to comprehensively capture the construct of managerial performance. The operational validity of personality was found to increase substantially (50%-74%) across all of the FFM personality traits when both peer and subordinate ratings were added to supervisor ratings according to the multitrait-multimethod approach. Furthermore, the authors responded to the recent calls to validate tests via a multivariate (e.g., multitrait-multimethod) approach by decomposing overall managerial performance into task and contextual performance criteria and by using multiple rating perspectives (sources). Overall, this study contributes to the evidence that personality may be even more useful in predicting managerial performance if the performance criteria are less deficient.

Question: What is the five-factor model of personality?


Challenges in Autonomous Vehicle Testing and Validation. Software testing is all too often simply a bug hunt rather than a wellconsidered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles. This paper identifies five major challenge areas in testing according to the V model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and failoperational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively relaxed operational scenarios, use of a monitor/actuator pair architecture to separate the most complex autonomy functions from simpler safety functions, and fault injection as a way to perform more efficient edge case testing. While significant challenges remain in safety-certifying the type of algorithms that provide high-level autonomy themselves, it seems within reach to instead architect the system and its accompanying design process to be able to employ existing software safety approaches.

Question: What is the difference between a monitor and an actuator?


Wideband Circularly Polarized Patch Antenna Using Broadband Baluns. A novel 90deg broadband balun comprising a broadband 90deg Schiffman phase shifter is introduced as a means of enhancing the wideband circular polarization performance of dual-fed type microstrip antennas. The proposed 90deg broadband balun delivers good impedance matching, balanced power splitting and consistent 90deg (plusmn5deg) phase shifting, across a wide bandwidth (~57.5%). A circular patch antenna utilizing the proposed 90deg broadband balun is shown to attain measured impedance(S11< -10 dB) and axial ratio (AR < 3 dB) bandwidths of 60.24% and 37.7%, respectively, for the dual L-probe case; and 71.28% and 81.6% respectively, for the quadruple L-probe case.

Question: What is a broadband balun?


Enabling ∼100fps detection on a landing unmanned aircraft for its on-ground vision-based recovery. In this paper, a deep learning inspired solution is proposed and developed to enable timeliness and practicality of the pre-existing ground stereo vision guidance system for flxed-wing UAVs' safe landing. Since the ground guidance prototype was restricted within applications due to its untimeliness, eventually the vision-based detection less than 15 fps (frame per second). Under such circumstances, we employ a regression based deep learning algorithm into automatic detection on the flying aircraft in the landing sequential images. The system architecture is upgraded so as to be compatible with the novel deep learning requests, and furthermore, annotated datasets are conducted to support training and testing of the regression-based learning detection algorithm. Experimental results validate that the detection attaches 100 fps or more while the localization accuracy is kept in the same level.

Question: How to enable ∼100fps detection on a landing unmanned aircraft for its on-ground vision-based recovery.


Columbia-IBM news video story segmentation in trecvid 2004. In this technical report, we give an overview our technical developments in the story segmentation task in TRECVID 2004. Among them, we propose an information-theoretic framework, visual cue cluster construction (VC), to automatically discover adequate mid-level features. The problem is posed as mutual information maximization, through which optimal cue clusters are discovered to preserve the highest information about the semantic labels. We extend the Information Bottleneck framework to high-dimensional continuous features and further propose a projection method to map each video into probabilistic memberships over all the cue clusters. The biggest advantage of the proposed approach is to remove the dependence on the manual process in choosing the mid-level features and the huge labor cost involved in annotating the training corpus for training the detector of each mid-level feature. When tested in TRECVID 2004 news video story segmentation, the proposed approach achieves promising performance gain over representations derived from conventional clustering techniques and even the mid-level features selected manually; meanwhile, it achieved one of the top performances, F1=0.65, close to the highest performance, F1=0.69, by other groups. We also experiment with other promising visual features and continue investigating effective prosody features. The introduction of post-processing also provides practical improvements. Furthermore, the fusion from other modalities, such as speech prosody features and ASR-based segmentation scores are significant and have been confirmed again in this experiment.

Question: How to segment a video into segments?


HHCART: An Oblique Decision Tree. Decision trees are a popular technique in statistical data classification. They recursively partition the feature space into disjoint sub-regions until each sub-region becomes homogeneous with respect to a particular class. The basic Classification and Regression Tree (CART) algorithm partitions the feature space using axis parallel splits. When the true decision boundaries are not aligned with the feature axes, this approach can produce a complicated boundary structure. Oblique decision trees use oblique decision boundaries to potentially simplify the boundary structure. The major limitation of this approach is that the tree induction algorithm is computationally expensive. In this article we present a new decision tree algorithm, called HHCART. The method utilizes a series of Householder matrices to reflect the training data at each node during the tree construction. Each reflection is based on the directions of the eigenvectors from each classes' covariance matrix. Considering axis parallel splits in the reflected training data provides an efficient way of finding oblique splits in the unreflected training data. Experimental results show that the accuracy and size of the HHCART trees are comparable with some benchmark methods in the literature. The appealing feature of HHCART is that it can handle both qualitative and quantitative features in the same oblique split.

Question: What is an oblique decision tree?


An integrated theory of the mind.. Adaptive control of thought-rational (ACT-R; J. R. Anderson & C. Lebiere, 1998) has evolved into a theory that consists of multiple modules but also explains how these modules are integrated to produce coherent cognition. The perceptual-motor modules, the goal module, and the declarative memory module are presented as examples of specialized systems in ACT-R. These modules are associated with distinct cortical regions. These modules place chunks in buffers where they can be detected by a production system that responds to patterns of information in the buffers. At any point in time, a single production rule is selected to respond to the current pattern. Subsymbolic processes serve to guide the selection of rules to fire as well as the internal operations of some modules. Much of learning involves tuning of these subsymbolic processes. A number of simple and complex empirical examples are described to illustrate how these modules function singly and in concert.

Question: What is the theory of the mind?


Software engineering for security: a roadmap. doesn't need to be secure? Almost every softwarecontrolled system faces threats from potential adversaries, from Internet-aware client applications running on PCs, to complex telecommunications and power systems accessible over the Internet, to commodity software with copy protection mechanisms. Software engineers must be cognizant of these threats and engineer systems with credible defenses, while still delivering value to customers. In this paper, we present our perspectives on the research issues that arise in the interactions between software engineering and security.

Question: What is the difference between software engineering and software security?


Beyond Doctors: Future Health Prediction from Multimedia and Multimodal Observations. Although chronic diseases cannot be cured, they can be effectively controlled as long as we understand their progressions based on the current observational health records, which is often in the form of multimedia data. A large and growing body of literature has investigated the disease progression problem. However, far too little attention to date has been paid to jointly consider the following three observations of the chronic disease progression: 1) the health statuses at different time points are chronologically similar; 2) the future health statuses of each patient can be comprehensively revealed from the current multimedia and multimodal observations, such as visual scans, digital measurements and textual medical histories; and 3) the discriminative capabilities of different modalities vary significantly in accordance to specific diseases. In the light of these, we propose an adaptive multimodal multi-task learning model to co-regularize the modality agreement, temporal progression and discriminative capabilities of different modalities. We theoretically show that our proposed model is a linear system. Before training our model, we address the data missing problem via the matrix factorization approach. Extensive evaluations on a real-world Alzheimer's disease dataset well verify our proposed model. It should be noted that our model is also applicable to other chronic diseases.

Question: What is the difference between a chronic disease and a chronic disease?


Overweight among primary school-age children in Malaysia.. This study is a secondary data analysis from the National Health Morbidity Survey III, a population-based study conducted in 2006. A total of 7,749 children between 7 and 12 years old were recruited into the study. This study seeks to report the prevalence of overweight (including obesity) children in Malaysia using international cut-off point and identify its associated key social determinants. The results show that the overall prevalence of overweight children in Malaysia was 19.9%. The urban residents, males, Chinese, those who are wealthy, have overweight or educated guardians showed higher prevalence of overweight. In multivariable analysis, higher likelihood of being overweight was observed among those with advancing age (OR=1.15), urban residents (OR=1.16, 95% CI: 1.01-1.36), the Chinese (OR=1.45, 95% CI: 1.19-1.77), boys (OR=1.23, 95% CI: 1.08-1.41), and those who came from higher income family. In conclusion, one out of five of 7-12 year-old-children in Malaysia were overweight. Locality of residence, ethnicity, gender, guardian education, and overweight guardian were likely to be the predictors of this alarming issue. Societal and public health efforts are needed in order to reduce the burden of disease associated with obesity.

Question: What is the prevalence of overweight among primary school-age children in Malaysia?


Introduction: Hybrid intelligent adaptive systems. This issue of International Journal of Intelligent Systems includes extended versions of selected papers from the 4th International Conference on Soft Computing, held in Iizuka, Japan, September 30]October 5, 1996. The topic of the special issue is ''Hybrid Intelligent Adaptive Systems.'' Research on hybrid systems is one of the key issues of developing intelligent systems and it can apply a wide range of tools, including artificial neural networks, fuzzy logic, knowledge-based systems, genetic algorithms, evolutionary computation, and chaos models. The papers in this issue have been carefully reviewed and modified to give the readers a comprehensive overview of theoretical aspects, design, and implementation issues of hybrid intelligent adaptive systems. In the first paper by Kasabov and Kozma, a general framework of developing hybrid, intelligent, and adaptive systems is given. This work develops multimodular, fuzzy neural network systems and applies it to phoneme-based speech recognition. The second paper by Miyata, Furuhashi, and Uchikawa proposes fuzzy abductive inference with degrees of manifestations. This method infers irredundant combinations of candidates with degrees of belief for the manifestations. It is also demonstrated that the results of the inference method are applicable to medical diagnosis and system fault detection. Cho adopts ideas of artificial life in his work to develop evolutionary neural networks. The introduced modular neural network can evole its structure autonomously using a structural genetic code. The effectiveness of the method is demonstrated on the example of handwritten digit recognition. Feuring and Lippe study theoretical aspects of fuzzy neural networks. They propose a training algorithm for fuzzy neural networks that satisfies a certain goodness criterion. The second part of the special issue contains articles related to time series analysis and systems control. Yamazaki, Ka

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


Analytical and Practical Analysis of Switched-Capacitor DC-DC Converters. Switched-capacitor DC-DC converters are useful alternatives to inductor-based converters in many lowpower and medium-power applications. This work develops a straightforward analysis method to determine a switched-capacitor converter's output impedance (a measure of performance and power loss). This resistive impedance is a function of frequency and has two asymptotic limits, one corresponding to very high switching frequency where resistive paths dominate the impedance, and one corresponding to very low switching frequency where charge transfers among idealized capacitors dominate the impedance. An optimization method is developed to improve the performance of these converters through component sizing based on practical constraints. Several switched-capacitor converter topologies are compared in the two asymptotic limits. Switched-capacitor converter performance (based on conduction loss) is compared with that of two magnetics-based DC-DC converters. At moderate to high conversion ratios, the switchedcapacitor converter has significantly less conduction loss than an inductor-based buck converter. Some aspects of converter implementation are discussed, including the power loss due to device parasitics and methods for transistor control. Implementation using both integrated and discrete devices is discussed. With the correct analysis methods, switched-capacitor DC-DC converters can provide an attractive alternative to conventional power converters.

Question: What is the difference between switched-capacitor and inductor-based converters?


IoTScanner: Detecting and Classifying Privacy Threats in IoT Neighborhoods. In the context of the emerging Internet of Things (IoT), a proliferation of wireless connectivity can be expected. That ubiquitous wireless communication will be hard to centrally manage and control, and can be expected to be opaque to end users. As a result, owners and users of physical space are threatened to lose control over their digital environments. In this work, we propose the idea of an IoTScanner. The IoTScanner integrates a range of radios to allow local reconnaissance of existing wireless infrastructure and participating nodes. It enumerates such devices, identifies connection patterns, and provides valuable insights for technical support and home users alike. Using our IoTScanner, we attempt to classify actively streaming IP cameras from other non-camera devices using simple heuristics. We show that our classification approach achieves a high accuracy in an IoT setting consisting of a large number of IoT devices. While related work usually focuses on detecting either the infrastructure, or eavesdropping on traffic from a specific node, we focus on providing a general overview of operations in all observed networks. We do not assume prior knowledge of used SSIDs, preshared passwords, or similar.

Question: What is the difference between a range scanner and a range finder?


Compressive sensing. 1 Scope The Shannon/Nyquist sampling theorem tells us that in order to not lose information when uniformly sampling a signal we must sample at least two times faster than its bandwidth. In many applications, including digital image and video cameras, the Nyquist rate can be so high that we end up with too many samples and must compress in order to store or transmit them. In other applications, including imaging systems (medical scanners, radars) and high-speed analog-to-digital converters, increasing the sampling rate or density beyond the current state-of-the-art is very expensive. In this lecture, we will learn about a new technique that tackles these issues using compressive sensing [1, 2]. We will replace the conventional sampling and reconstruction operations with a more general linear measurement scheme coupled with an optimization in order to acquire certain kinds of signals at a rate significantly below Nyquist.

Question: What is compressive sensing?


A Laminated Waveguide Magic-T With Bandpass Filter Response in Multilayer LTCC. A laminated waveguide magic-T with imbedded Chebyshev filter response is developed in a multilayer low-temperature co-fired ceramic technology by vertically stacked rectangular cavity resonators with highly symmetric coupling structures. The cavities provide even- and odd-symmetric field distributions by simultaneously resonating TE102 and TE201 modes at the center frequency of the magic-T. Thus, the in-phase and out-of-phase responses of the magic-T function are accomplished according to the induced mode. Meanwhile, the filter frequency response is realized by the cascaded cavities with proper coupling strengths according to the filter specification. With the degenerate, but orthogonal cavity modes, a fewer number of cavities are required and the circuit size is further reduced. A third-order bandpass magic-T is designed and fabricated to operate at 24 GHz with 6% fractional bandwidth. The highly symmetric structure of the implemented magic-T provides a low in-band magnitude imbalance ( ±0.25 dB) and phase imbalance (0°-6°). The sum and difference ports also provide an isolation greater than 30 dB in the operation frequency range. Measurement and simulated results are in good agreement, both validating the design concept.

Question: What is a magic-T?


Question: What is AES?


A Fractional-N Sub-Sampling PLL using a Pipelined Phase-Interpolator With an FoM of -250 dB. A fractional-N sub-sampling PLL architecture based on pipelined phase-interpolator and Digital-to-Time-Converter (DTC) is presented in this paper. The combination of pipelined phase-interpolator and DTC enables efficient design of the multi-phase generation mechanism required for the fractional operation. This technique can be used for designing a fractional-N PLL with low in-band phase noise and low spurious tones with low power consumption. The short-current-free pipelined phase-interpolator used in this work is capable of achieving high-linearity with low-power while minimizing the intrinsic jitter. A number of other circuit techniques and layout techniques are also employed in this design for ensuring high-performance operation with minimal chip area and power consumption. The proposed fractional-N PLL is implemented in standard 65 nm CMOS technology. The PLL has an operating range of 600 MHz from 4.34 GHz to 4.94 GHz. In fractional-N mode, the proposed PLL achieves -249.5 dB FoM and less than -59 dBc fractional spurs.

Question: What is a fractional-N PLL?


Wristband-Type Driver Vigilance Monitoring System Using Smartwatch. Studies have presented that the driver vigilance level has serious implication in the causation of road accidents. This paper focuses on integrating both the vehicle-based control behavior and physiological state to predict the driver vigilance index which is evaluated by using a smartwatch. The vehicle control behavior can be observed from the steering wheel movement. Our study utilized the smartwatch motion sensors to study the steering wheel behavior. Meanwhile, physiological state of driver reflects the driver capability of safety alert driving which is estimated by photoplethysmogram (PPG) and respiration signals in this paper. The PPG sensor is integrated in a sport wristband with a Bluetooth low energy module, transmitted the PPG signals to smartwatch in real time. The steering angle is derived by the reading from smartwatch built-in accelerometer and gyroscope sensors. On the other hand, the respiration is derived using the PPG peak baseline method. In order to utterly investigate the sleepiness-induced factors, the time, spectral, and phase space domain features are calculated. Considering the smartwatch processing capability, mutual-information technique is applied to designate the ten most descriptive features. Then, the extracted descriptive features are serve as parameters to a classifier to determine the driver aptitude status. The features are analyzed for their correlation with the subjective Koralinska sleepiness scale and through recorded video observations. The experimental results reveal that our system is capable of estimating driver hypervigilance at average of 96.5% accuracy rate by evaluating on both driving behavior and driver physiological state, provided a novel and low-cost implementation.

Question: How to predict driver vigilance level using smartwatch?


The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity. We describe a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives. The model is based on a probabilistic factor decomposition and allows identifying principal topics of the collection as well as authoritative documents within those topics. Furthermore, the relationships between topics is mapped out in order to build a predictive model of link content. Among the many applications of this approach are information retrieval and search, topic identification, query disambiguation, focused web crawling, web authoring, and bibliometric analysis.

Question: What is a probabilistic model of document content and hypertext connectivity?


Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †. Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Question: What is the relationship between base station power consumption and traffic load?


An Operational Amplifier with Recycling Folded Cascode Topology and Adaptive Biasing. This paper presents a highly adaptive operational amplifier with high gain, high bandwidth, high speed and low power consumption. By adopting the recycling folded cascode topology along with an adaptivebiasing circuit, this design achieves high performance in terms of gain-bandwidth product (GBW) and slew rate (SR). This single stage op-amp has been designed in 0.18μm technology with a power supply of 1.8V and a 5pF load. The simulation results show that the amplifier achieved a GBW of 335.5MHz, Unity Gain Bandwidth of 247.1MHz and a slew rate of 92.8V/μs.

Question: What is the GBW of an op-amp?


Management patterns: SDN-enabled network resilience management. Software-defined networking provides abstractions and a flexible architecture for the easy configuration of network devices, based on the decoupling of the data and control planes. This separation has the potential to considerably simplify the implementation of resilience functionality (e.g., traffic classification, anomaly detection, traffic shaping) in future networks. Although software-defined networking in general, and OpenFlow as its primary realisation, provide such abstractions, support is still needed for orchestrating a collection of OpenFlow-enabled services that must cooperate to implement network-wide resilience. In this paper, we describe a resilience management framework that can be readily applied to this problem. An important part of the framework are policy-controlled management patterns that describe how to orchestrate individual resilience services, implemented as OpenFlow applications.

Question: What is a management pattern?


Smart Societies, Infrastructure, Technologies and Applications. We describe a new approach to building high performance nonstop infrastructure for scalable AI and cloud computing. With AI as the technological driving force behind future smart cities and smart societies, we will need powerful new nonstop AI infrastructures at both the cloud level and at the edge.

Question: What is a smart society?


Indra: A Word Embedding and Semantic Relatedness Server. In recent years word embedding/distributional semantic models evolved to become a fundamental component in many natural language processing (NLP) architectures due to their ability of capturing and quantifying semantic associations at scale. Word embedding models can be used to satisfy recurrent tasks in NLP such as lexical and semantic generalisation in machine learning tasks, finding similar or related words and computing semantic relatedness of terms. However, building and consuming specific word embedding models require the setting of a large set of configurations, such as corpus-dependant parameters, distance measures as well as compositional models. Despite their increasing relevance as a component in NLP architectures, existing frameworks provide limited options in their ability to systematically build, parametrise, compare and evaluate different models. To answer this demand, this paper describes INDRA, a multi-lingual word embedding/distributional semantics framework which supports the creation, use and evaluation of word embedding models. In addition to the tool, INDRA also shares more than 65 pre-computed models in 14 languages.

Question: What is a word embedding model?


A tensor-based deep learning framework. This paper presents an unsupervised deep learning framework that derives spatio-temporal features for human-robot interaction. The respective models extract high-level features from low-level ones through a hierarchical network, viz. the Hierarchical Temporal Memory (HTM), providing at the same time a solution to the curse of dimensionality in shallow techniques. The presented work incorporates the tensor-based framework within the operation of the nodes and, thus, enhances the feature derivation procedure. This is due to the fact that tensors allow the preservation of the initial data format and their respective correlation and, moreover, attain more compact representations. The computational nodes form spatial and temporal groups by exploiting the multilinear algebra, subsequently express the samples according to those groups in terms of proximity. This generic framework may be applied in a diverse of visual data, whilst it has been examined on sequences of color and depth images, exhibiting remarkable performance.

Question: What is a tensor?


Large-Scale Training of Shadow Detectors with Noisily-Annotated Shadow Examples. This paper introduces training of shadow detectors under the large-scale dataset paradigm. This was previously impossible due to the high cost of precise shadow annotation. Instead, we advocate the use of quickly but imperfectly labeled images. Our novel label recovery method automatically corrects a portion of the erroneous annotations such that the trained classifiers perform at state-of-the-art level. We apply our method to improve the accuracy of the labels of a new dataset that is 20 times larger than existing datasets and contains a large variety of scenes and image types. Naturally, such a large dataset is appropriate for training deep learning methods. Thus, we propose a semantic-aware patch level Convolutional Neural Network architecture that efficiently trains on patch level shadow examples while incorporating image level semantic information. This means that the detected shadow patches are refined based on image semantics. Our proposed pipeline can be a useful baseline for future advances in shadow detection.

Question: How large is the dataset?


Parametric Shape-from-Shading by Radial Basis Functions. In this paper, we present a new method of shape from shading by using radial basis functions to parameterize the object depth. The radial basis functions are deformed by adjusting their centers, widths, and weights such that the intensity errors are minimized. The initial centers and widths are arranged hierarchically to speed up convergence and to stabilize the solution. Although the smoothness constraint is used, it can be eventually dropped out without causing instabilities in the solution. An important feature of our parametric shape-from-shading method is that it offers a unified framework for integration of multiple sensory information. We show that knowledge about surface depth and/or surface normals anywhere in the image can be easily incorporated into the shape from shading process. It is further demonstrated that even qualitative knowledge can be used in shape from shading to improve 3D reconstruction. Experimental comparisons of our method with several existing ones are made by using both synthetic and real images. Results show that our solution is more accurate than the others.

Question: What is the difference between parametric shape-from-shading and shape-from-shading?


An empirical evaluation of internet latency expansion. The Internet's latency expansion determines the asymptotic performance of large-scale distributed systems (such as Peer-to-Peer systems), but previous studies on the Internet have defined expansion in terms of router-level hops. In this paper, we empirically determine the Internet's latency expansion characteristics using measurements from two different Internet topology datasets. Our results show that the Internet router-level topology exhibits a power-law latency expansion, in contrast to its exponential expansion rate in terms of hops.

Question: What is the asymptotic performance of large-scale distributed systems?


Two-dimensional Disjunctively Constrained Knapsack Problem: Heuristic and exact approaches.

Question: What is the two-dimensional disjunctively constrained knapsack problem?


TechMiner: Extracting Technologies from Academic Publications. In recent years we have seen the emergence of a variety of scholarly datasets. Typically these capture 'standard' scholarly entities and their connections, such as authors, affiliations, venues, publications, citations, and others. However, as the repositories grow and the technology improves, researchers are adding new entities to these repositories to develop a richer model of the scholarly domain. In this paper, we introduce TechMiner, a new approach, which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support a number of tasks, such as: richer semantic search, which can exploit the technology dimension to support better retrieval of publications; richer expert search; monitoring the emergence and impact of new technologies, both within and across scientific fields; studying the scholarly dynamics associated with the emergence of new technologies; and others. TechMiner was evaluated on a manually annotated gold standard and the results indicate that it significantly outperforms alternative NLP approaches and that its semantic features improve performance significantly with respect to both recall and precision.

Question: What is the difference between a gold standard and a gold standard?


Message in a Sealed Bottle: Privacy Preserving Friending in Social Networks. Many proximity-based mobile social networks are developed to facilitate connections between any two people, or to help a user to find people with a matched profile within a certain distance. A challenging task in these applications is to protect the privacy of the participants' profiles and personal interests. In this paper, we design novel mechanisms, when given a preference-profile submitted by a user, that search persons with matching-profile in decentralized multi-hop mobile social networks. Our mechanisms also establish a secure communication channel between the initiator and matching users at the time when the matching user is found. Our rigorous analysis shows that our mechanism is privacy-preserving (no participants' profile and the submitted preference-profile are exposed), verifiable (both the initiator and the unmatched user cannot cheat each other to pretend to be matched), and efficient in both communication and computation. Extensive evaluations using real social network data, and actual system implementation on smart phones show that our mechanisms are significantly more efficient than existing solutions.

Question: What is the privacy preserving friending in social networks?


A quick MST-based algorithm to obtain Pathfinder networks (∞,n-1). Network scaling algorithms such as the Pathfinder algorithm are used to prunemany different kinds of networks, including citation networks, randomnetworks, and social networks. However, this algorithm suffers from run time problems for large networks and online processing due to its O(n4) time complexity. In this article, we introduce a new alternative, the MST-Pathfinder algorithm, which will allow us to prune the original network to get its PFNET(∞, n −1) in justO(n2 · logn) time.Theunderlying idea comes from the fact that the union (superposition) of all the Minimum Spanning Trees extracted from a given network is equivalent to the PFNET resulting from the Pathfinder algorithmparameterized by a specific set of values (r = ∞ and q = n −1), those usually considered in many different applications. Although this property is well-known in the literature, it seems that no algorithm based on it has been proposed, up to now, to decrease the high computational cost of the original Pathfinder algorithm.We also present a mathematical proof of the correctness of this new alternative and test its good efficiency in two different case studies: one dedicated to the post-processing of large random graphs, and the other one to a real world case in which medium networks obtained by a cocitation analysis of the scientific domains in different countries are pruned.

Question: What is the time complexity of the MST-Pathfinder algorithm?


An Organizational Theoretic Review of Green Supply Chain Management Literature. Green supply chain management (GSCM) has gained increasing attention within both academia and industry. As the literature grows, finding new directions by critically evaluating the research and identifying future directions becomes important in advancing knowledge for the field. Using organizational theories to help categorize the literature provides opportunities to address both the objectives of understanding where the field currently stands and identifying research opportunities and directions. After providing a background discussion on GSCM we categorize and review recent GSCM literature under nine broad organizational theories. Within this review framework, we also identify GSCM research questions that are worthy of investigation. Additional organizational theories which are considered valuable for future GSCM research are also identified with a conclusion for this review.

Question: What is the green supply chain management?


Harmonic Resonance Evaluation for Hub Traction Substation Consisting of Multiple High-Speed Railways. In many hub traction power-supply systems (TPSSs), the 27.5 kV busbars in the traction substation (TSS) have supplied several railway lines in a local area for reducing the number of TSSs. However, the multiple railway lines connected to the busbar may affect the resonance behaviors of the entire system. It is therefore necessary to investigate the resonance behaviors under such hub TPSS conditions since the harmonic current collection of all railway lines will aggravate the resonance problem. Thus, resonance-mode assessment and its sensitivity method is adopted for investigating the resonance behaviors of hub TPSS affected by different numbers of connected lines, lengths of supply lines, system capacities, etc. The numerical results of modal sensitivity indices are compared to investigate and quantify the harmonic resonance issue caused by multiple electrical railway lines. In addition, the resonance frequency-shift technique and modal impedance sensitivity index-based method are also employed to mitigate the critical harmonic resonances. The results illustrate that it is effective to analyze resonance issues by adopting the harmonic model and modal methods in this paper. The two types of resonance behaviors (i.e., primary resonance and resonance band) caused from the hub TPSS have been fully investigated, and the resulting harmonic distortion of hub TPSS is suppressed.

Question: What is the harmonic resonance evaluation for hub traction substation consisting of multiple high-speed railways?


Scalable triangulation-based logo recognition. We propose a scalable logo recognition approach that extends the common bag-of-words model and incorporates local geometry in the indexing process. Given a query image and a large logo database, the goal is to recognize the logo contained in the query, if any. We locally group features in triples using multi-scale Delaunay triangulation and represent triangles by signatures capturing both visual appearance and local geometry. Each class is represented by the union of such signatures over all instances in the class. We see large scale recognition as a sub-linear search problem where signatures of the query image are looked up in an inverted index structure of the class models. We evaluate our approach on a large-scale logo recognition dataset with more than four thousand classes.

Question: What is the largest logo recognition dataset?


DESIGNING A LAYOUT USING THE MODIFIED TRIANGLE METHOD , AND GENETIC ALGORITHMS. This paper describes the use of genetic algorithms (GA) for solving the facility layout problem (FLP) within manufacturing systems' design. The paper considers a specific heuristic layout planning method, known as the modified triangle method. This method seeks for an optimal layout solution based on the degrees of flows between workstations. The search for an optimal solution is extremely time-consuming and not suitable for larger systems; therefore we have developed a system based on evolutionary computation. Our paper presents a system, based on GA, and the results obtained regarding several numerical cases from the literature. We propose the usage of this system by presenting numerous advantages over other methods of solving FLP for problem representation and evolutionary computation for solution search. (Received in September 2012, accepted in June 2013. This paper was with the authors 2 months for 2 revisions.)

Question: How to design a layout using the modified triangle method?


Cell-Balancing Techniques: Theory and Implementation. In the safety chapter we briefly discussed the issue that when multiple cells are connected in series, the cell voltage is not always equal to the pack voltage divided by the number of cells. How does this happen? This chapter explores that question in detail, but the first question to answer is this: Why do we care? The first reason is safety. Remember, when lithium ion cell voltage exceeds 4.2V by a few hundred millivolts, it can undergo thermal runaway, melting the battery pack and device it is powering. It can even blow up as a big ball of fire. Although a well-designed pack has an overvoltage protection circuit that will prevent such an event (usually even two independent circuits!), it is better not to tempt fate by triggering this protection unnecessarily. The second reason is longevity. If the maximal recommended charging voltage is exceeded even a little, it will cause very accelerated degradation. Just increasing the charging voltage from 4.2 to 4.25V causes the degradation rate to increase by 30%. For this reason, the misbehaving cell that has higher than its due share of voltage will degrade faster. The third reason is incomplete charging of the pack. Let's assume the protector circuit does its job and that charging stops when just one cell gets close to unsafe conditions. Now we have successfully prevented thermal runaway, but all of the other cells now have lower voltages and are not fully charged. If we look at the pack voltage, it will be much less than 4.2V multiplied by the

Question: What is the difference between a cell and a battery?


Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms. Find the secret to improve the quality of life by reading this evolutionary algorithms in theory and practice evolution strategies evolutionary programming genetic algorithms. This is a kind of book that you need now. Besides, it can be your favorite book to read after having this book. Do you ask why? Well, this is a book that has different characteristic with others. You may not need to know who the author is, how well-known the work is. As wise word, never judge the words from who speaks, but make the words as your good value to your life.

Question: What is the author of this book?


SPECTRE : Serialization of Proof-of-work Events : Confirming Transactions via Recursive Elections. Bitcoin utilizes Nakamoto Consensus to achieve agreement on a consistent set of transactions, in the permissionless setting, where anyone can participate in the protocol anonymously. Since its rise, many other permissionless consensus protocols have been proposed. We present SPECTRE, a new protocol for the consensus core of cryptocurrencies that remains secure even under high throughput and fast confirmation times. At any throughput, SPECTRE is resilient to attackers with up to 50% of the computational power (reaching the limit defined by network congestion and bandwidth constraints). SPECTRE can operate at arbitrarily high block creation rates, which implies that its transactions confirm in mere seconds (limited mostly by the round-trip-time in the network). SPECTRE's underlying model falls into the category of partial synchronous networks: its security depends on the existence of some bound on the delivery time of messages between honest participants, but the protocol itself does not contain any parameter that depends on this bound. Hence, while other protocols that do encode such parameters must operate with extreme safety margins, SPECTRE converges according to the actual network delay. Key to SPECTRE's achievements is the fact that it satisfies weaker properties than classic consensus requires. In the conventional paradigm, the order between any two transactions must be decided and agreed upon by all non-corrupt nodes. In contrast, SPECTRE only satisfies this with respect to transactions performed by honest users. We observe that in the context of money, two conflicting payments that are published concurrently could only have been created by a dishonest user, hence we can afford to delay the acceptance of such transactions without harming the usability of the system. Our framework formalizes this weaker set of requirements for a cryptocurrency's distributed ledger

Question: What is the difference between Nakamoto Consensus and SPECTRE?


Scalable pseudo-random noise radar. This paper describes the implementation of a pseudo-random noise radar system on a scalable sensor platform that consists of several multi-purpose 61- and 122-GHz transceivers in a Silicon-Germanium BiCMOS technology. The multi-band transceivers are equipped with a frequency multiplier to generate the 61- and 122-GHz carrier signals from a single 30.5-GHz LO signal and can be cascaded to build a MIMO radar system with 2 different frequency bands. The implemented scalable sensor system is suitable for various radar and communication applications by using the same transceiver chips with integrated binary phase-shift keying modulators and I/Q receiver. A suitable pseudo-random binary sequence was used in a radar measurement to demonstrate the applicability of the developed chips.

Question: What is a scalable pseudo-random noise radar?


Nanowire dye-sensitized solar cells.. Excitonic solar cells-including organic, hybrid organic-inorganic and dye-sensitized cells (DSCs)-are promising devices for inexpensive, large-scale solar energy conversion. The DSC is currently the most efficient and stable excitonic photocell. Central to this device is a thick nanoparticle film that provides a large surface area for the adsorption of light-harvesting molecules. However, nanoparticle DSCs rely on trap-limited diffusion for electron transport, a slow mechanism that can limit device efficiency, especially at longer wavelengths. Here we introduce a version of the dye-sensitized cell in which the traditional nanoparticle film is replaced by a dense array of oriented, crystalline ZnO nanowires. The nanowire anode is synthesized by mild aqueous chemistry and features a surface area up to one-fifth as large as a nanoparticle cell. The direct electrical pathways provided by the nanowires ensure the rapid collection of carriers generated throughout the device, and a full Sun efficiency of 1.5% is demonstrated, limited primarily by the surface area of the nanowire array.

Question: What is the efficiency of the dye-sensitized solar cell?


ROBHAZ-rescue: rough-terrain negotiable teleoperated mobile robot for rescue mission. This paper presents design and integration of the ROBHAZ-DT3, which is a newly developed mobile robot system with chained double-track mechanisms. It is designed to carry out military and civilian missions in various hazardous environments. A passive adaptation mechanism equipped between the front and rear body enables the ROBHAZ-DT3 to have good adaptability to uneven terrains including stairs. The passive adaptation mechanism reduces energy consumption when moving on uneven terrain as well as its simplicity in design and remote control, since no actuator is necessary for adaptation. Based on this novel mobile platform, a rescue version of the ROBHAZ-DT3 with appropriate sensors and a semi-autonomous mapping and localization algorithm is developed to participate in the RoboCup2004 US-Open: Urban Search and Rescue Competition. From the various experiments in the realistic rescue arena, we can verify that the ROBHAZ-DT3 is reliable in travelling rugged terrain and the proposed mapping and localization algorithm are effective in the unstructured environment with uneven ground.

Question: What is the ROBHAZ-rescue?


The Lone-Actor Terrorist and the TRAP-18. An open source sample of 111 lone-actor terrorists from the United States and Europe were studied through the lens of the Terrorist Radicalization Assessment Protocol (TRAP-18). This investigative template consists of 8 proximal warning behaviors and 10 distal characteristics for active risk management or active monitoring, respectively, by national security threat assessors. Several aspects of criterion validity were tested in this known outcome sample. Seventy percent of the terrorists were positive for at least half or more of the indicators. When the sample was divided into Islamic extremists, right-wing extremists, and single-issue terrorists, there were no significant differences across all 18 indicators except for 4. When the sample was divided according to successful versus thwarted attackers, the successful attackers were significantly more fixated, creative, and innovative, and failed to have a prior sexually intimate pair bond. They were significantly less likely to have displayed pathway warning behavior and be dependent on a virtual community of likeminded true believers. Effect sizes were small to medium (! " 0.190–0.317). The TRAP-18 appears to have promise as an eventual structured professional judgment risk assessment instrument according to some of the individual terrorist content domains outlined by Monahan (2012, 2016).

Question: What is the TRAP-18?


Measurements revealing Challenges in Radar Sensor Modeling for Virtual Validation of Autonomous Driving. The virtual validation of automated driving functions requires meaningful simulation models of environment perception sensors such as radar, lidar, and cameras. There does not yet exist an unrivaled standard for perception sensor models, and radar especially lacks modeling approaches that consistently produce realistic results. In this paper, we present measurements that exemplify challenges in the development of meaningful radar sensor models. We highlight three major challenges: multi-path propagation, separability, and sensitivity of radar cross section to the aspect angle. We also review previous work addressing these challenges and suggest further research directions towards meaningful automotive radar simulation models.

Question: What is the radar cross section?


Learning to Detect Rooftops in Aerial Images. In this paper, we examine the use of machine learning to improve the robustness of systems for image analysis on the task of roof detection. We review the problem of analyzing aerial photographs, and describe an existing vision system that attempts to automate the identiication of buildings in aerial images. After this, we brieey review several well-known learning algorithms that represent a wide variety of inductive biases. We report three experiments designed to illuminate facets of applying machine learning methods to the image analysis task; one experiment focuses on within-image learning, another deals with the cost of diierent errors, and a third addresses between-image learning. Experimental results demonstrate that machine-learned classiiers meet or exceed the accuracy of handcrafted solutions and that useful generalization occurs when training and testing on data derived from diierent images.

Question: How to detect roofs in aerial images?


Learner Modeling for Integration Skills. Complex skill mastery requires not only acquiring individual basic component skills, but also practicing integrating such basic skills. However, traditional approaches to knowledge modeling, such as Bayesian knowledge tracing, only trace knowledge of each decomposed basic component skill. This risks early assertion of mastery or ineffective remediation failing to address skill integration. We introduce a novel integration-level approach to model learners' knowledge and provide fine-grained diagnosis: a Bayesian network based on a new kind of knowledge graph with progressive integration skills. We assess the value of such a model from multifaceted aspects: performance prediction, parameter plausibility, expected instructional effectiveness, and real-world recommendation helpfulness. Our experiments based on a Java programming tutor show that proposed model significantly improves two popular multiple-skill knowledge tracing models on all these four aspects.

Question: What is a knowledge graph?


Forwarding metamorphosis: fast programmable match-action processing in hardware for SDN. In Software Defined Networking (SDN) the control plane is physically separate from the forwarding plane. Control software programs the forwarding plane (e.g., switches and routers) using an open interface, such as OpenFlow. This paper aims to overcomes two limitations in current switching chips and the OpenFlow protocol: i) current hardware switches are quite rigid, allowing ``Match-Action'' processing on only a fixed set of fields, and ii) the OpenFlow specification only defines a limited repertoire of packet processing actions. We propose the RMT (reconfigurable match tables) model, a new RISC-inspired pipelined architecture for switching chips, and we identify the essential minimal set of action primitives to specify how headers are processed in hardware. RMT allows the forwarding plane to be changed in the field without modifying hardware. As in OpenFlow, the programmer can specify multiple match tables of arbitrary width and depth, subject only to an overall resource limit, with each table configurable for matching on arbitrary fields. However, RMT allows the programmer to modify all header fields much more comprehensively than in OpenFlow. Our paper describes the design of a 64 port by 10 Gb/s switch chip implementing the RMT model. Our concrete design demonstrates, contrary to concerns within the community, that flexible OpenFlow hardware switch implementations are feasible at almost no additional cost or power.

Question: What is the difference between a switch and a router?


Design of hybrid resistive-capacitive DAC for SAR A/D converters. While hybrid capacitive-resistive D/A Converter (DAC) has been known for many years, its potential for energy-efficient operation is sometimes overlooked. This paper investigates the utilization of hybrid DACs in successive-approximation register A/D converters. To improve energy efficiency of SAR ADCs, a new hybrid DAC is introduced. In an exemplar 10-bit 100-MS/s ADC, simulation results show that the energy efficiency and chip area (of passive devices) can be improved by more than an order of magnitude.

Question: How to design a hybrid DAC?


Transaction-Cost Economics: The Governance of Contractual Relations. Transaction-Cost Economics: The Governance of Contractual Relations Author(s): Oliver E. Williamson Reviewed work(s): Source: Journal of Law and Economics, Vol. 22, No. 2 (Oct., 1979), pp. 233-261 Published by: The University of Chicago Press for The Booth School of Business of the University of Chicago and The University of Chicago Law School Stable URL: http://www.jstor.org/stable/725118 . Accessed: 07/01/2013 16:49

Question: What is the governance of contractual relations?


ReTiCaM: Real-time Human Performance Capture from Monocular Video. We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage analysis-by-synthesis optimization whose formulation and implementation are designed for high performance. In the first stage, a skinned templatemodel is jointly fitted to background subtracted input video, 2D and 3D skeleton joint positions found using a deep neural network, and a set of sparse facial landmark detections. In the second stage, dense non-rigid 3D deformations of skin and even loose apparel are captured based on a novel real-time capable algorithm for non-rigid tracking using dense photometric and silhouette constraints. Our novel energy formulation leverages automatically identified material regions on the template to model the differing non-rigid deformation behavior of skin and apparel. The two resulting nonlinear optimization problems per-frame are solved with specially-tailored data-parallel Gauss-Newton solvers. In order to achieve real-time performance of over 25Hz, we design a pipelined parallel architecture using the CPU and two commodity GPUs. Our method is the first real-time monocular approach for full-body performance capture. Our method yields comparable accuracy with off-line performance capture techniques, while being orders of magnitude faster.

Question: What is the first real-time human performance capture approach?


Cannabis use and psychosis: a longitudinal population-based study.. Cannabis use may increase the risk of psychotic disorders and result in a poor prognosis for those with an established vulnerability to psychosis. A 3-year follow-up (1997-1999) is reported of a general population of 4,045 psychosis-free persons and of 59 subjects in the Netherlands with a baseline diagnosis of psychotic disorder. Substance use was assessed at baseline, 1-year follow-up, and 3-year follow-up. Baseline cannabis use predicted the presence at follow-up of any level of psychotic symptoms (adjusted odds ratio (OR) = 2.76, 95% confidence interval (CI): 1.18, 6.47), as well as a severe level of psychotic symptoms (OR = 24.17, 95% CI: 5.44, 107.46), and clinician assessment of the need for care for psychotic symptoms (OR = 12.01, 95% CI: 2.24, 64.34). The effect of baseline cannabis use was stronger than the effect at 1-year and 3-year follow-up, and more than 50% of the psychosis diagnoses could be attributed to cannabis use. On the additive scale, the effect of cannabis use was much stronger in those with a baseline diagnosis of psychotic disorder (risk difference, 54.7%) than in those without (risk difference, 2.2%; p for interaction = 0.001). Results confirm previous suggestions that cannabis use increases the risk of both the incidence of psychosis in psychosis-free persons and a poor prognosis for those with an established vulnerability to psychotic disorder.

Question: What is the effect of cannabis use on psychosis?


Low Drop-Out Voltage Regulators: Capacitor-less Architecture Comparison. Demand for system-on-chip solutions has increased the interest in low drop-out (LDO) voltage regulators which do not require a bulky off-chip capacitor to achieve stability, also called capacitor-less LDO (CL-LDO) regulators. Several architectures have been proposed; however comparing these reported architectures proves difficult, as each has a distinct process technology and specifications. This paper compares CL-LDOs in a unified matter. We designed, fabricated, and tested five illustrative CL-LDO regulator topologies under common design conditions using 0.6?m CMOS technology. We compare the architectures in terms of (1) line/load regulation, (2) power supply rejection, (3) line/load transient, (4) total on-chip compensation capacitance, (5) noise, and (6) quiescent power consumption. Insights on what optimal topology to choose to meet particular LDO specifications are provided.

Question: What is the difference between a capacitor-less LDO and a capacitor LDO?


Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces. This paper proposes an effective framework of human-humanoid robot physical interaction. Its key component is a new control technique for full-body balancing in the presence of external forces, which is presented and then validated empirically. We have adopted an integrated system approach to develop humanoid robots. Herein, we describe the importance of replicating human-like capabilities and responses during human-robot interaction in this context. Our balancing controller provides gravity compensation, making the robot passive and thereby facilitating safe physical interactions. The method operates by setting an appropriate ground reaction force and transforming these forces into full-body joint torques. It handles an arbitrary number of force interaction points on the robot. It does not require force measurement at interested contact points. It requires neither inverse kinematics nor inverse dynamics. It can adapt to uneven ground surfaces. It operates as a force control process, and can therefore, accommodate simultaneous control processes using force-, velocity-, or position-based control. Forces are distributed over supporting contact points in an optimal manner. Joint redundancy is resolved by damping injection in the context of passivity. We present various force interaction experiments using our full-sized bipedal humanoid platform, including compliant balance, even when affected by unknown external forces, which demonstrates the effectiveness of the method.

Question: How to balance a humanoid robot?


Rectangular patch antenna with inset feed and modified ground-plane for wideband antenna. This paper presents the technique for increasing bandwidth of rectangular patch antenna from 0.88 GHz (7.76 - 8.64 GHz) to 6.75 GHz (3.49 - 10.24 GHz). This technique use inset feed patch antenna with modified ground plane for achieved widest bandwidth. We will propose three types of rectangular patch antenna: the simple rectangular patch fed by microstrip line, inset feed rectangular patch and inset feed rectangular patch with modifies ground plane. The final simulation result show that the lower edge of frequency is moved down from 7.76 GHz to 3.49 GHz and the higher edge of frequency is shifted up from 8.64 GHz to 10.24 GHz, which is the one selection for increasing bandwidth of rectangular patch antenna for wideband. Details of the increasing bandwidth of microstrip patch antenna are described, and simulation results for obtained wideband performance are presented by using IE3D Zeland software.

Question: How to increase the bandwidth of a rectangular patch antenna?


ESD protection circuit schemes for DDR3 DQ drivers. The high-speed interface of DQ pins in DDR3 DRAM requires special ESD considerations. During ESD characterization testing, high voltages from the power rail could pass through the pre-driver PMOSFET to damage the pull-down NMOSFET gate oxide. Special circuit design of the pre-driver circuit is required to eliminate this ESD failure mechanism.

Question: What is the ESD protection circuit scheme for DDR3 DQ drivers?


RECOGNITION AND RETRIEVAL PROCESSES IN FREE RECALL. A model of free recall is described which identifies two processes in free recall: a retrieval process by which the subject accesses the words, and a recognition process by which the subject decides whether an implicitly retrieved word is a to-be-recalled word. Submodels for the recognition process and the retrieval process are described. The recognition model assumes that during the study phase, the subject associates "list markers" to the to-be-recalled words. The establishment of such associates is postulated to be an all-or-none stochastic process. In the test phase, the subject recognizes to-be-recalled words by deciding which words have relevant list markers as associates. A signal detectability model is developed for this decision process. The retrieval model is introduced as a computer program that tags associative paths between list words. In several experiments, subjects studied and were tested on a sequence of overlapping sublists sampled from a master set of common nouns. The twoprocess model predicts that the subject's ability to retrieve the words should increase as more overlapping sublists are studied, but his ability to differentiate the words on the most recent list should deteriorate. Experiments confirmed this predicted dissociation of recognition and retrieval. Further predictions derived from the free recall model were also supported.

Question: What is a free recall model?


Cowden syndrome.. BACKGROUND Cowden syndrome is a rare genodermatosis charactarized by presence of multiple hamartomas. The aim of the study was to specify the clinical, therapeutic and prognostic aspects of Cowden syndrome.   CASES REPORT Our study included 4 patients with Cowden syndrome, 2 males and 2 females between 14 and 46 years old. Clinical examination of the skin revealed facials papules (4 cases), acral keratosis (1 case), translucent keratotic papules (2 cases). Oral examination revealed papules (4 cases), papillomatosis (4 cases), gingival hypertrophy (4 cases) and scrotal tongue (2 cases). Investigations revealed thyroid lesions (2 cases), fibrocystic disease and lipoma of the breast in 1 case, "glycogenic acanthosis" (1 case), macrocephaly (2 cases), dysmorphic face (1 case) and lichen nitidus (1 case). Oral etretinate and acitretine were temporary efficient in 2 patients. Topical treatment with tretinoin lotion resulted in some improvement in cutaneous, but not mucosal lesions in one patient. No cancer was revealed.   CONCLUSION The pathognomonic mucocutaneous lesions were found in all patients. However, no degenerative lesions have been revealed. A new association of Cowden syndrome with lichen nitidus was found. Treatment with oral retinoids was efficient on cutaneous lesions.

Question: What is the pathognomonic mucocutaneous lesions?


Architecture decisions: demystifying architecture. We believe that a key to demystifying architecture products lies in the architecture decisions concept. We can make the architecture more transparent and clarify its rationale for all stakeholders by explicitly documenting major architecture decisions.

Question: What is the architecture decisions concept?


gNUFFTW : Auto-Tuning for High-Performance GPU-Accelerated Non-Uniform Fast Fourier Transforms by Teresa. Non-uniform sampling of the Fourier transform appears in many important applications such as magnetic resonance imaging (MRI), optics, tomography and radio interferometry. Computing the inverse often requires fast application of the non-uniform discrete Fourier transform (NUDFT) and its adjoint operation. Non-Uniform Fast Fourier Transform (NUFFT) methods, such as gridding/regridding, are approximate algorithms which often leverage the highly-optimized Fast Fourier Transform (FFT) and localized interpolations. These approaches require selecting several parameters, such as interpolation and FFT grid sizes, which affect both the accuracy and runtime. In addition, different implementations lie on a spectrum of precomputation levels, which can further speed up repeated computations, with various trade-offs in planning time, execution time and memory usage. Choosing the optimal parameters and implementations is important for performance speed, but difficult to do manually since the performance of NUFFT is not well-understood for modern parallel processors. Inspired by the FFTW library, we demonstrate an empirical auto-tuning approach for the NUFFT on General Purpose Graphics Processors Units (GPGPU). We demonstrate order-of-magnitude speed improvements with autotuning compared to typical default choices. Our auto-tuning is implemented in an easy to use proof-of-concept library called gNUFFTW, which leverages existing open-source NUFFT packages, cuFFT and cuSPARSE libraries, as well as our own NUFFT implementations for high performance. Keywords—non-uniform, non-Cartesian, FFT, NUFFT, GPU, auto-tuning, image processing.

Question: How to auto-tune the NUFFT parameters?


Collision-free object movement using vector fields. The topics of computer animation and object collision detection and resolution have become increasingly desirable in a wide range of applications including autonomous vehicle navigation, robotics, and the movie industry. However, the techniques currently available are typically difficult to use or are restricted to a particular domain. This paper presents a technique for providing automatic animation and collision avoidance of arbitrary objects in a computer graphics system. The underlying construct used in this process is a surrounding volume octree vector field. The system automatically generates these structures around objects in the scene. By judicious creation and use of these vector fields, objects in the scene move and interact, but do not collide. The manner in which these vector fields are created is given. Two applications cloud movement over terrain and autonomous aircraft navigation are presented which show typical usage of this technique.

Question: How to create a vector field?


Tobler ' s First Law of Geography , Self Similarity , and Perlin Noise : A Large Scale Analysis of Gradient Distribution in Southern Utah with Application to Procedural Terrain Generation. A statistical analysis finds that in a 160,000 square kilometer region of southern Utah gradients appear to be exponentially distributed at resolutions from 5m up to 1km. A simple modification to the Perlin noise generator changing the gradient distribution in each octave to an exponential distribution results in realistic and interesting procedurally generated terrain. The inverse transform sampling method is used in the amortized noise algorithm to achieve an exponential distribution in each octave, resulting in the generation of infinite non-repeating terrain with the same characteristics.

Question: How to generate procedural terrain?


Extracting lines of curvature from noisy point clouds. We present a robust framework for extracting lines of curvature from point clouds. First, we show a novel approach to denoising the input point cloud using robust statistical estimates of surface normal and curvature which automatically rejects outliers and corrects points by energy minimization. Then the lines of curvature are constructed on the point cloud with controllable density. Our approach is applicable to surfaces of arbitrary genus, with or without boundaries, and is statistically robust to noise and outliers while preserving sharp surface features. We show our approach to be effective over a range of synthetic and real-world input datasets with varying amounts of noise and outliers. The extraction of curvature information can benefit many applications in CAD, computer vision and graphics for point cloud shape analysis, recognition and segmentation. Here, we show the possibility of using the lines of curvature for feature-preserving mesh construction directly from noisy point clouds.

Question: How to extract lines of curvature from noisy point clouds?


An Overview on XML Semantic Disambiguation from Unstructured Text to Semi-Structured Data : Background , Applications , and Ongoing Challenges. Since the last two decades, XML has gained momentum as the standard for Web information management and complex data representation. Also, collaboratively built semi-structured information resources, such as Wikipedia, have become prevalent on the Web and can be inherently encoded in XML. Yet most methods for processing XML and semi-structured information handle mainly the syntactic properties of the data, while ignoring the semantics involved. To devise more intelligent applications, one needs to augment syntactic features with machine-readable semantic meaning. This can be achieved through the computational identification of the meaning of data in context, also known as (a.k.a.) automated semantic analysis and disambiguation, which is nowadays one of the main challenges at the core of the Semantic Web. This survey paper provides a concise and comprehensive review of the methods related to XML-based semi-structured semantic analysis and disambiguation. It is made of four logical parts. First, we briefly cover traditional word sense disambiguation methods for processing flat textual data. Second, we describe and categorize disambiguation techniques developed and extended to handle semi-structured and XML data. Third, we describe current and potential application scenarios that can benefit from XML semantic analysis, including: data clustering and semantic-aware indexing, data integration and selective dissemination, semantic-aware and temporal querying, Web and Mobile Services matching and composition, blog and social semantic network analysis, and ontology learning. Fourth, we describe and discuss ongoing challenges and future directions, including: the quantification of semantic ambiguity, expanding XML disambiguation context, combining structure and content, using collaborative/social information sources, integrating expli

Question: What is the size of the canadian military?


Inferring activities from interactions with objects. A key aspect of pervasive computing is using computers and sensor networks to effectively and unobtrusively infer users' behavior in their environment. This includes inferring which activity users are performing, how they're performing it, and its current stage. Recognizing and recording activities of daily living is a significant problem in elder care. A new paradigm for ADL inferencing leverages radio-frequency-identification technology, data mining, and a probabilistic inference engine to recognize ADLs, based on the objects people use. We propose an approach that addresses these challenges and shows promise in automating some types of ADL monitoring. Our key observation is that the sequence of objects a person uses while performing an ADL robustly characterizes both the ADL's identity and the quality of its execution. So, we have developed Proactive Activity Toolkit (PROACT).

Question: What is the name of the toolkit?


A virtual reality intervention to improve the understanding and empathy for people with dementia in informal caregivers: results of a pilot study.. OBJECTIVE Informal caregivers often experience psychological distress due to the changing functioning of the person with dementia they care for. Improved understanding of the person with dementia reduces psychological distress. To enhance understanding and empathy in caregivers, an innovative technology virtual reality intervention Through the D'mentia Lens (TDL) was developed to experience dementia, consisting of a virtual reality simulation movie and e-course. A pilot study of TDL was conducted.   METHODS A pre-test-post-test design was used. Informal caregivers filled out questionnaires assessing person-centeredness, empathy, perceived pressure from informal care, perceived competence and quality of the relationship. At post-test, additional questions about TDL's feasibility were asked.   RESULTS Thirty-five caregivers completed the pre-test and post-test. Most participants were satisfied with TDL and stated that TDL gave more insight in the perception of the person with dementia. The simulation movie was graded 8.03 out of 10 and the e-course 7.66. Participants significantly improved in empathy, confidence in caring for the person with dementia, and positive interactions with the person with dementia.   CONCLUSION TDL is feasible for informal caregivers and seems to lead to understanding of and insight in the experience of people with dementia. Therefore, TDL could support informal caregivers in their caregiving role.

Question: What is the difference between informal and formal caregivers?


Entity resolution using inferred relationships and behavior. We present a method for entity resolution that infers relationships between observed identities and uses those relationships to aid in mapping identities to underlying entities. We also introduce the idea of using graphlets for entity resolution. Graphlets are collections of small graphs that can be used to characterize the "role" of a node in a graph. The idea is that graphlets can provide a richer set of features to characterize identities. We validate our method on standard author datasets, and we further evaluate our method using data collected from Twitter. We find that inferred relationships and graphlets are useful for entity resolution.

Question: How to resolve entities using graphlets?


An Optimal Algorithm for Mutual Exclusion in Computer Networks. An algorithm is proposed that creates mutual exclusion in a computer network whose nodes communicate only by messages and do not share memory. The algorithm sends only 2*(N 1) messages, where N is the number of nodes in the network per critical section invocation. This number of messages is at a minimum if parallel, distributed, symmetric control is used; hence, the algorithm is optimal in this respect. The time needed to achieve mutual exclusion is also minimal under some general assumptions. As in Lamport's "bakery algorithm," unbounded sequence numbers are used to provide first-come firstserved priority into the critical section. It is shown that the number can be contained in a fixed amount of memory by storing it as the residue of a modulus. The number of messages required to implement the exclusion can be reduced by using sequential node-by-node processing, by using broadcast message techniques, or by sending information through timing channels. The "readers and writers" problem is solved by a simple modification of the algorithm and the modifications necessary to make the algorithm robust are described.

Question: What is the optimal algorithm for mutual exclusion in computer networks?