Accurate Unlexicalized Parsing

We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. Indeed, its performance of 86.36% (LP/LR F 1) is better than that of earlylexicalizedPCFG models, and surprisingly close to the current state-of-theart. This result has potential uses beyond establishing a strong lower bound on the maximum possible accuracy of unlexicalized models: an unlexicalized PCFG is much more compact, easier to replicate, and easier to interpret than more complex lexical models, and the parsing algorithms are simpler, more widely understood, of lower asymptotic complexity, and easier to optimize. In the early 1990s, as probabilistic methods swept NLP, parsing work revived the investigation of probabilistic context-free grammars ( PCFGs) (Booth and Thomson, 1973; Baker, 1979). However, early results on the utility ofPCFGs for parse disambiguation and language modeling were somewhat disappointing. A conviction arose that lexicalizedPCFGs (where head words annotate phrasal nodes) were the key tool for high performancePCFG parsing. This approach was congruent with the great success of word n-gram models in speech recognition, and drew strength from a broader interest in lexicalized grammars, as well as demonstrations that lexical dependencies were a key tool for resolving ambiguities such asPPattachments (Ford et al., 1982; Hindle and Rooth, 1993). In the following decade, great success in terms of parse disambiguation and even language modeling was achieved by various lexicalized PCFG models (Magerman, 1995; Charniak, 1997; Collins, 1999; Charniak, 2000; Charniak, 2001). However, several results have brought into question how large a role lexicalization plays in such parsers. Johnson (1998) showed that the performance of anunlexicalizedPCFGover the Penn treebank could be improved enormously simply by annotating each node by its parent category. The Penn treebank coveringPCFGis a poor tool for parsing because the context-freedom assumptions it embodies are far too strong, and weakening them in this way makes the model much better. More recently, Gildea (2001) discusses how taking the bilexical probabilities out of a good current lexicalized PCFG parser hurts performance hardly at all: by at most 0.5% for test text from the same domain as the training data, and not at all for test text from a different domain. 1 But it is precisely these bilexical dependencies that backed the intuition that lexicalized PCFGs should be very successful, for example in Hindle and Rooth’s demonstration fromPPattachment. We take this as a reflection of the fundamental sparseness of the lexical dependency information available in the Penn Treebank. As a speech person would say, one million words of training data just isn’t enough. Even for topics central to the treebank’s Wall Street Journal text, such as stocks, many very plausible dependencies occur only once, for example stocks stabilized, while many others occur not at all, for example stocks skyrocketed .2 The best-performing lexicalized PCFGs have increasingly made use of subcategorization 3 of the 1There are minor differences, but all the current best-known lexicalized PCFGs employ bothmonolexicalstatistics, which describe the phrasal categories of arguments and adjuncts t hat appear around a head lexical item, and bilexicalstatistics, or dependencies, which describe the likelihood of a head word tak ing as a dependent a phrase headed by a certain other word. 2This observation motivates various classor similaritybased approaches to combating sparseness, and this remains a promising avenue of work, but success in this area has proven somewhat elusive, and, at any rate, current lexicalized PCFGs do simply use exact word matches if available, and interpola te with syntactic category-based estimates when they are not. 3In this paper we use the term subcategorizationin the original general sense of Chomsky (1965), for where a syntactic ca tcategories appearing in the Penn treebank. Charniak (2000) shows the value his parser gains from parentannotation of nodes, suggesting that this information is at least partly complementary to information derivable from lexicalization, and Collins (1999) uses a range of linguistically motivated and carefully hand-engineered subcategorizations to break down wrong context-freedom assumptions of the naive Penn treebank covering PCFG, such as differentiating “baseNPs” from noun phrases with phrasal modifiers, and distinguishing sentences with empty subjects from those where there is an overt subject NP. While he gives incomplete experimental results as to their efficacy, we can assume that these features were incorporated because of beneficial effects on parsing that were complementary to lexicalization. In this paper, we show that the parsing performance that can be achieved by an unlexicalized PCFG is far higher than has previously been demonstrated, and is, indeed, much higher than community wisdom has thought possible. We describe several simple, linguistically motivated annotations which do much to close the gap between a vanilla PCFG and state-of-the-art lexicalized models. Specifically, we construct anunlexicalizedPCFG which outperforms the lexicalized PCFGs of Magerman (1995) and Collins (1996) (though not more recent models, such as Charniak (1997) or Collins (1999)). One benefit of this result is a much-strengthened lower bound on the capacity of an unlexicalized PCFG. To the extent that no such strong baseline has been provided, the community has tended to greatly overestimate the beneficial effect of lexicalization in probabilistic parsing, rather than looking critically at where lexicalized probabilities are both neededto make the right decision and availablein the training data. Secondly, this result affirms the value of linguistic analysis for feature discovery. The result has other uses and advantages: an unlexicalized PCFGis easier to interpret, reason about, and improve than the more complex lexicalized models. The grammar representation is much more compact, no longer requiring large structures that store lexicalized probabilities. The parsing algorithms have lower asymptotic complexity4 and have much smaller grammar egory is divided into several subcategories, for example di viding verb phrases into finite and non-finite verb phrases, rath e than in the modern restricted usage where the term refers onl y to the syntactic argument frames of predicators. 4O(n3) vs. O(n5) for a naive implementation, or vs. O(n4) if using the clever approach of Eisner and Satta (1999). constants. An unlexicalizedPCFG parser is much simpler to build and optimize, including both standard code optimization techniques and the investigation of methods for search space pruning (Caraballo and Charniak, 1998; Charniak et al., 1998). It is not our goal to argue against the use of lexicalized probabilities in high-performance probabilistic parsing. It has been comprehensively demonstrated that lexical dependencies are useful in resolving major classes of sentence ambiguities, and a parser should make use of such information where possible. We focus here on using unlexicalized, tructural context because we feel that this information has been underexploited and underappreciated. We see this investigation as only one part of the foundation for state-of-the-art parsing which employsboth lexical and structural conditioning. 1 Experimental Setup To facilitate comparison with previous work, we trained our models on sections 2–21 of the WSJsection of the Penn treebank. We used the first 20 files (393 sentences) of section 22 as a development set (devset ). This set is small enough that there is noticeable variance in individual results, but it allowed rapid search for good features via continually reparsing the devset in a partially manual hill-climb. All of section 23 was used as a test set for the final model. For each model, input trees were annotated or transformed in some way, as in Johnson (1998). Given a set of transformed trees, we viewed the local trees as grammar rewrite rules in the standard way, and used (unsmoothed) maximum-likelihood estimates for rule probabilities. 5 To parse the grammar, we used a simple array-based Java implementation of a generalizedCKY parser, which, for our final best model, was able to exhaustively parse all sentences in section 23 in 1GB of memory, taking approximately 3 sec for average length sentences. 6 5The tagging probabilities were smoothed to accommodate unknown words. The quantityP(tag|word) was estimated as follows: words were split into one of several categories wordclass, based on capitalization, suffix, digit, and other character features. For each of these categories, we took th e maximum-likelihood estimate of P(tag|wordclass). This distribution was used as a prior against which observed tagging s, if any, were taken, givingP(tag|word) = [c(tag, word) + κ P(tag|wordclass)]/[c(word)+κ]. This was then inverted to give P(word|tag). The quality of this tagging model impacts all numbers; for example the raw treebank grammar’s devset F 1 is 72.62 with it and 72.09 without it. 6The parser is available for download as open source at: http://nlp.stanford.edu/downloads/lex-parser.shtml


TUNABLE AND SWITCHABLE BANDPASS FILTERS USING SLOT-LINE RESONATORS

In this paper, novel uniplanar tunable and switchable bandpass filters are designed by using the centrally-loaded slot-line resonator. From the voltage-wave distribution along the resonator, the appropriate location for the loading element is determined to be the center of the slot-line resonator, where the voltages of the fundamental signal and second harmonic are maximum and zero, respectively. As a result, the fundamental frequency can be tuned while the second harmonic remains almost unchanged. For the first time, the properties of the centrally-loaded slot-line resonator are analyzed by using the evenand odd-mode method, and their respective resonant frequencies are derived. The demonstrated tunable bandpass filter can give a 30.9% frequency tuning range with acceptable insertion loss when a varactor is used as the loading element. By replacing the loading varactors with PIN diodes, a switchable bandpass filter is realized in which the attenuation in the fundamental passband can be controlled. In experiments, the switchable bandpass filter exhibits a 2.13 dB insertion loss in the fundamental passband when the PIN diodes are off and more than 49 dB isolation across the passband when the PIN diodes are on. Received 8 October 2010, Accepted 5 November 2010, Scheduled 27 November 2010 Corresponding author: Zhi-Hua Bao (bao.zh@ntu.edu.cn).


ViziQuer: A Tool to Explore and Query SPARQL Endpoints

The presented tool uses a novel approach to explore and query a SPARQL endpoint. The tool is simple to use as a user needs only to enter an address of a SPARQL endpoint of one’s interest. The tool will extract and visualize graphically the data schema of the endpoint. The user will be able to overview the data schema and use it to construct a SPARQL query according to the data schema. The tool can be downloaded from http://viziquer.lumii.lv. There is also additional information and help on how to use it in practice.


Knowledge Discovery in Manufacturing Simulations

Discrete event simulation studies in a manufacturing context are a powerful instrument when modeling and evaluating processes of various industries. Usually simulation experts conduct simulation experiments for a predetermined system specification by manually varying parameters through educated assumptions and according to a prior defined goal. Moreover, simulation experts try to reduce complexity and number of simulation runs by excluding parameters that they consider as not influential regarding the simulation project scope. On the other hand, today's world of big data technology enables us to handle huge amounts of data. We therefore investigate the potential benefits of designing large scale experiments with a much broader coverage of possible system behavior. In this paper, we propose an approach for applying data mining methods on simulation data in combination with suitable visualization methods in order to uncover relationships in model behavior to discover knowledge that otherwise would have remained hidden. For a prototypical demonstration we used a clustering algorithm to divide large amounts of simulation output datasets into groups of similar performance values and depict those groups through visualizations to conduct a visual investigation process of the simulation data.


Toward Delay-Efficient Game-Aware Data Centers for Cloud Gaming

Gaming on demand is an emerging service that has recently started to garner prominence in the gaming industry. Cloud-based video games provide affordable, flexible, and high-performance solutions for end-users with constrained computing resources and enables them to play high-end graphic games on low-end thin clients. Despite its advantages, cloud gaming's Quality of Experience (QoE) suffers from high and varying end-to-end delay. Since the significant part of computational processing, including game rendering and video compression, is performed in data centers, controlling the transfer of information within the cloud has an important impact on the quality of cloud gaming services. In this article, a novel method for minimizing the end-to-end latency within a cloud gaming data center is proposed. We formulate an optimization problem for reducing delay, and propose a Lagrangian Relaxation (LR) time-efficient heuristic algorithm as a practical solution. Simulation results indicate that the heuristic method can provide close-to-optimal solutions. Also, the proposed model reduces end-to-end delay and delay variation by almost 11% and 13.5%, respectively, and outperforms the existing server-centric and network-centric models. As a byproduct, our proposed method also achieves better fairness among multiple competing players by almost 45%, on average, in comparison with existing methods.


The Application of Non-parametric Method and Time Series Analysis to Predict the Machine Repair Times

This study focuses on the utilization of non-parametric to assess the distribution of repair times of a machine part as well as the prediction of the future values. There are two folds of objectives, namely, the distribution assessment of the repair times. The diagnostic graph, i.e., histogram and normal probability plot, as well as a non-parametric test, Kolmogorov-Smirnov (KS) method, is utilized to assess the distribution of data. According to the KS test, it can be used effectively to test the distribution of the repair times of a machine which are selected as a case study. Another objective is the prediction of the future repair time required to fix a designated part. The time series analysis based on autoregressive integrated moving average (ARIMA) model is deployed in order to forecast the repair times. It turned out that one of the simplest models of ARIMA, ARIMA (0, 1, 0) or random walk, is the most appropriate model for the prediction and this indicates that the pattern of repair times is non-stationary.


Towards an automated system for intelligent screening of candidates for recruitment using ontology mapping (EXPERT)

Many e-recruitment tools for recruiting candidates for jobs have significantly spread in recent years. Companies often receive resumes from candidates using e-recruitment tools or via job portal for each job posting and manually short list qualified applicants. The existing e-recruitment tools have been mainly used for the storage of applicant contact data. In this paper, we present EXPERT, an intelligent tool for screening candidates for recruitment using ontology mapping. EXPERT has three phases in screening candidates for recruitment. In first phase, the system collects candidates’ resumes and constructs ontology document for the features of the candidates. Job openings/job requirements are represented as ontology in the second phase and in third phase, EXPERT maps the job requirement ontology onto the candidate ontology document and retrieves the eligible candidates. Experiment results show that this model improves the accuracy of matching candidates with job requirement.


Social Internet of Things: The Potential of the Internet of Things for Defining Human Behaviours

The potential of the artificial intelligence, data mining and the so-called Big Data to build solutions based on the understanding of human behaviours is being extended with the capabilities of the Future Internet and the Internet of Things (IoT). The described potential of data and networks have been analyzed by the complex network theory, offering a specialized branch, the defined as Human Dynamics. The goal with the Internet of Things in the social area is to describe in real-time the human behaviours and activities. These goals are starting to be feasible through the quantity of data provided by the personal devices such as smart phone, and the smart environments such as Smart cities that makes more intelligent the environment and offer a smart space that sense our movements, actions, and the evolution of the ecosystem. This work analyses the ecosystem defined through the triangle formed by Big Data, Smart Cities and Personal/Wearable Computing to determinate human behaviours and human dynamics. For this purpose, the life-cycle of human dynamics determinations in Smart Cities have been analysed in order to determinate the current status of the technology, challenges, and opportunities.


The State of Solving Large Incomplete-Information Games, and Application to Poker

ion algorithms take as input a description of the game and output a smaller but strategically similar — or even equivalent — game. The abstraction algorithms discussed here work with any finite number of players and do not assume a zerosum game. Information Abstraction The most popular kind of abstraction is information abstraction. The game is abstracted so that the agents cannot distinguish some of the states that they can distinguish in the actual game. For example in an abstracted poker hand, an agent is not able to observe all the nuances of the cards that she would normally observe. Lossless Information Abstraction. It turns out that it is possible to do lossless information abstraction, which may seem like an oxymoron at first. The method I will describe (Gilpin and Sandholm 2007b) is for a class of games that we call games with ordered signals. It is structured, but still general enough to capture a wide range of strategic situations. A game with ordered signals consists of a finite number of rounds. Within a round, the players play a game on a directed tree (the tree can be different in different rounds). The only uncertainty players face stems from private signals the other players have received and from the unknown future signals. In other words, players observe each Articles 14 AI MAGAZINE Nash equilibrium Nash equilibrium Original game


A case study on propagating and updating provenance information using the CIDOC CRM

Provenance information of digital objects maintained by digital libraries and archives is crucial for authenticity assessment, reproducibility and accountability. Such information is commonly stored on metadata placed in various Metadata Repositories (MRs) or Knowledge Bases (KBs). Nevertheless, in various settings it is prohibitive to store the provenance of each digital object due to the high storage space requirements that are needed for having complete provenance. In this paper, we introduce provenance-based inference rules as a means to complete the provenance information, to reduce the amount of provenance information that has to be stored, and to ease quality control (e.g., corrections). Roughly, we show how provenance information can be propagated by identifying a number of basic inference rules over a core conceptual model for representing provenance. The propagation of provenance concerns fundamental modelling concepts such as actors, activities, events, devices and information objects, and their associations. However, since a MR/KB is not static but changes over time due to several factors, the question that arises is how we can satisfy update requests while still supporting the aforementioned inference rules. Towards this end, we elaborate on the specification of the required add/delete operations, consider two different semantics for deletion of information, and provide the corresponding update algorithms. Finally, we report extensive comparative results for different repository policies regarding the derivation of new knowledge, in datasets containing up to one million RDF triples. The results allow us to understand the tradeoffs related to the use of inference rules on storage space and performance of queries and updates.


Development of a Whole-Sensitive Teleoperated Robot Arm using Torque Sensing Technique

In this paper, we concentrate on the design of a new whole-sensitive robot arm enabling torque measurement in each joint by means of developed optical torque sensors. When the contact of arm with an object occurs, local impedance algorithm provides active compliance of corresponding robot arm joint. Thus, the whole structure of the manipulator can safely interact with unstructured environment. The detailed design procedure of the 4-DOF robot arm and optical torque sensors is described in the paper. The gravity compensation algorithm was elaborated and verified by implementation of the local impedance control of a simple two-link arm manipulator


The kNN-TD Reinforcement Learning Algorithm

A reinforcement learning algorithm called kNN-TD is introduced. This algorithm has been developed using the classical formulation of temporal difference methods and a k-nearest neighbors scheme as its expectations memory. By means of this kind of memory the algorithm is able to generalize properly over continuous state spaces and also take benefits from collective action selection and learning processes. Furthermore, with the addition of probability traces, we obtain the kNN-TD(λ) algorithm which exhibits a state of the art performance. Finally the proposed algorithm has been tested on a series of well known reinforcement learning problems and also at the Second Annual RL Competition with excellent results.


The Evolution and Future of National Customer Satisfaction Index Models

A number of both national and international customer satisfaction barometers or indices have been introduced in the last decade. For the most part, these satisfaction indices are embedded within a system of cause and effect relationships or satisfaction model. Yet there has been little in the way of model development. Of critical importance to the validity and reliability of such indices is that the models and methods used to measure customer satisfaction and related constructs continue to learn, adapt, and improve over time. The primary goal of this research is to propose and test a number of modifications and improvements to the national index models. Using survey data from the Norwegian Customer Satisfaction Barometer (NCSB), we find general support for the proposed modifications.


Virtual Reality Exposure Therapy for Anxiety and Specific Phobias

There is a growing body of research indicating the multiple ways that affective dysregulation (e.g., anxiety disorders, specific phobias, panic disorder, and posttraumatic stress disorder (PTSD)) may lead to significant impairments in normal life functioning. Anxiety and fear are concentrated emotional experiences that serve critical functions in organizing necessary survival responses (Fendt & Fanselow, 1999). In properly functioning affective systems, the responses are adaptive. LeDoux (2012a) posits survival circuits that enable humans to adapt to feared stimuli by organizing brain functions. The fear induced arousal and activation of survival circuits allows for adaptive responses to take priority and other responses are inhibited. Further, attentional processing focuses on pertinent environmental stimuli and learning occurs (Scherer, 2000; LeDoux, 2012b). Hence, adaptive survival circuits are optimized to detect threatening stimuli and relay the information as environmental challenges and opportunities. The adaptive survival circuits use this information to adjust behavioral and psychophysiological responses for appropriate adaptation and resolution. Excessive fear responses, however, can be restrictive and may be a sign of dysregulated anxiety. When exposure to stress occurs early in development and is repeated in persons with a particular genetic disposition, a decreased threshold for developing anxiety may result (Heim & Nemeroff, 1999). Further, over-excitation and deprivation can influence the affective system and may induce changes in the emotional circuitry of the brain that can contribute to stress-related psychopathology (Davidson, Jackson, & Kalin, 2000). A good deal of research has shown that exposure therapy is effective for reducing negative affective symptoms (Rothbaum & Schwartz, 2002). In vivo exposure therapy has been found to have greater efficacy when compared to imaginal exposure, especially in the treatment of specific phobias (Emmelkamp, 2003). Exposure to emotional situations and prolonged rehearsal result in the regular activation of cerebral metabolism in brain areas associated with inhibition of maladaptive associative processes (Schwartz, 1998). Identical neural circuits have been found to be involved in affective regulation across affective disorders (De Raedt, 2006; Mineka, Watson, & Clark, 1998). Systematic and controlled therapeutic exposure to phobic stimuli may enhance emotional regulation through adjustments of inhibitory processes on the amygdala by the medial prefrontal cortex during exposure and structural changes in the hippocampus after successful therapy (Hariri, Bookheimer, & Mazziotta, 2000). A novel tool for conducting exposure therapy is virtual reality exposure therapy (VRET), in which users are immersed within a computer-generated simulation or virtual environment (VE) that updates in a natural way to the user’s psychophysiological arousal, head and/ or body motion (Parsons and Courtney, 2011, Parsons and Reinebold, 2012). Virtual environment applications that focus on treatment of affective (see Powers & Emmelkamp, 2008; Parsons et al., 2008a; Opris et al., 2012) and cognitive disorders (see Rose et al., 2005; Parsons 2009a) as well as assessment of component cognitive processes are now being developed and tested: attention (Parsons, et al., 2007, 2011) spatial abilities (Beck et al., 2010; Goodrich-Hunsaker and Hopkins, 2010; Parsons, et al., 2013), memory (Moffat, 2009; Parsons & Rizzo, 2008b; Parsons et al., 2013; Knight & Titov, 2009), spatial memory (Parsons et al., 2013); and executive functions (Armstrong et al., 2013; Henry et al., 2012; Parsons et al., 2012, 2013, 2014). The increased ecological validity of virtual scenarios may aid differential diagnosis and treatment planning. Within a virtual world, it is possible to systematically present cognitive tasks targeting neuropsychological performance beyond what are currently available using traditional methods (Parsons, 2011, 2012). Thomas D. Parsons University of North Texas, USA


BYOD security challenges: control and protect your most sensitive data

According to a recent survey by Harris Interactive and ESET, more than 80% of employed adults use some kind of personally owned electronic device for work-related functions.1 One of the primary advantages in allowing employees to bring and use their personal devices for work is that it increases efficiency and flexibility. By giving access to the corporate network, and therefore corporate information via unmanaged devices, work can be done from anywhere, at any time, using any endpoint. It also provides cost savings to organisations, since personal device usage means they don’t need to provide or manage mobile devices for their employees. The Harris survey also determined that 47% of employees use personal desktop computers to access or store company information, while 41% do this with personal laptops, 24% with smartphones and 10% with tablets. However, with less than half of these devices being protected by basic security measures, some organisations may start to worry that the security challenges associated with BYOD far outweigh the benefits.


Enabling the IoT Paradigm in E-health Solutions through the VIRTUS Middleware

In Europe, in a context of growing population and decreasing resources, ageing related diseases represent one of the most relevant challenges in terms of healthcare organization complexity, plus care levels and system financing balancing. Nowadays there are several researches that are studying the application of the IoT (Internet of Things) paradigm in the e-health field. This paper explains how a solution, built on the top of the VIRTUS IoT middleware, provides a valid alternative to current IoT solutions, which are mainly based on SOA (Service Oriented Architecture). VIRTUS leverage an Instant Messaging protocol (XMPP) to guarantee a (near) real-time, secure and reliable communication channel among heterogeneous devices. The presented development has been exploited in a healthcare case study: an implementation of a cost-savvy remote body movement monitoring system, aimed at classify daily patients' activities, designed as a modular architecture and deployed in a large scale scenario. The paper analyzes the features offered by the VIRTUS middleware, if used within a e-health solution, providing a comparison with other well-known systems.


Feasibility Study on the Use of Biometrics in an Entitlement Scheme

This report examines the feasibility of using biometrics as a means of establishing a unique identity, to support the proposed entitlement scheme under development by the United Kingdom Passport Service (UKPS) and Driver and Vehicle Licensing Agency (DVLA). Biometrics identification systems measure physiological and behavioural characteristics of a person, and use these measurements to reliably distinguish one person from another. The main examples considered in this study are fingerprint, iris and face image recognition. Biometric identification can assist in the issue of entitlement cards, passports, driving licences and other identity documents in two ways. On the initial issue of such documents, biometrics can be used to check that applicants are not erroneously issued documents using two different identity details; this is the main focus of this study. Secondly, when an entitlement card, passport or driving licence is being used, biometrics can help confirm that it is being used by the correct person. The purpose of the study is to assess the feasibility of fingerprint, iris and face recognition technologies for these applications, to identify unknowns and the risks associated with the use of biometrics in such a national identity scheme, and to make recommendations for how some of these risks might be addressed should such a scheme proceed. Biometric methods do not offer 100% certainty of authentication of individuals. The success of any deployment of a system using biometric methods depends, therefore, on many factors such as: the degree of the 'uniqueness' of the biometric measure, technical and social factors, user interfaces, and provision of secure backup systems for those situations and individual s where the biometric will not work effectively. The main findings of the study are: a In principle, fingerprint or iris recognition can provide the identification performance required for unique identification over the entire UK adult population. In the case of fingerprint recognition, the system would require the enrolment of at least four fingers, whereas for iris recognition both irises should be registered. However, the practicalities of deploying either iris or fingerprint recognition in such a scheme are far from straightforward. b Such a system would be a groundbreaking deployment for this kind of biometric application. Not only would it be one of the largest deployments to date, but aspects of its performance would be far more demanding than those of similarly sized systems; such existing systems are either not applied in the civil sector, or operate …


Model predictive hovering-translation control of an unmanned Tri-TiltRotor

The experimental translational hovering control of a Tri-TiltRotor Unmanned Aerial Vehicle is the subject of this paper. This novel UAV is developed to possess the capability to perform autonomous conversion between the Vertical Take-Off and Landing, and the Fixed-Wing flight modes. Via this design's implemented features however, the capability for additional control authority on the UAV's longitudinal translational motion arises: The rotor-tilting servos are utilized in performing thrust vectoring of the main rotors, thus exploiting their fast response characteristics in directly providing translation-controlling forces. The system's hovering translation is handled by a Model Predictive Control scheme, following the aforementioned actuation principles. While performing experimental studies of the overall controlled system's efficiency, the advantageous effects of this novel control authority are clearly noted. Additionally, in this article the considerations and requirements for operational autonomy-related on-board-only state estimation are addressed.


Regularized Off-Policy TD-Learning

We present a novel l1 regularized off-policy convergent TD-learning method (termed RO-TD), which is able to learn sparse representations of value functions with low computational complexity. The algorithmic framework underlying ROTD integrates two key ideas: off-policy convergent gradient TD methods, such as TDC, and a convex-concave saddle-point formulation of non-smooth convex optimization, which enables first-order solvers and feature selection using online convex regularization. A detailed theoretical and experimental analysis of RO-TD is presented. A variety of experiments are presented to illustrate the off-policy convergence, sparse feature selection capability and low computational cost of the RO-TD algorithm.


Understanding neurocognitive developmental disorders can improve education for all.

Specific learning disabilities (SLDs) are estimated to affect up to 10% of the population, and they co-occur far more often than would be expected, given their prevalences. We need to understand the complex etiology of SLDs and their co-occurrences in order to underpin the training of teachers, school psychologists, and clinicians, so that they can reliably recognize SLDs and optimize the learning contexts for individual learners.


An efficient k-means clustering algorithm

In this paper, we present a novel algorithm for performing k-means clustering. It organizes all the patterns in a k-d tree structure such that one can find all the patterns which are closest to a given prototype efficiently. The main intuition behind our approach is as follows. All the prototypes are potential candidates for the closest prototype at the root level. However, for the children of the root node, we may be able to prune the candidate set by using simple geometrical constraints. This approach can be applied recursively until the size of the candidate set is one for each node. Our experimental results demonstrate that our scheme can improve the computational speed of the direct k-means algorithm by an order to two orders of magnitude in the total number of distance calculations and the overall time of computation.


Miniaturized Wilkinson power dividers utilizing capacitive loading

The authors report the miniaturization of a planar Wilkinson power divider by capacitive loading of the quarter wave transmission lines employed in conventional Wilkinson power dividers. Reduction of the transmission line segments from /spl lambda//4 to between /spl lambda//5 and /spl lambda//12 are reported here. The input and output lines at the three ports and the lines comprising the divider itself are coplanar waveguide (CPW) and asymmetric coplanar stripline (ACPS), respectively. The 10 GHz power dividers are fabricated on high resistivity silicon (HRS) and alumina wafers. These miniaturized dividers are 74% smaller than conventional Wilkinson power dividers, and have a return loss better than +30 dB and an insertion loss less than 0.55 dB. Design equations and a discussion about the effect of parasitic reactance on the isolation are presented for the first time.


A Randomized Singular Value Decomposition Algorithm for Image Processing Applications

The main contribution of this paper is to demonstrate that a new randomized SVD algorithm, proposed by Drineas et. al. in [4], is not only of theoretical interest but also a viable and fast alternative to traditional SVD algorithms in applications (e.g. image processing). This algorithm samples a constant number of rows (or columns) of the matrix, scales them appropriately to form a small matrix, say S, and then computes the SVD of S (which is a good approximation to the SVD of the original matrix). We experimentally evaluate the accuracy and speed of this algorithm for image matrices, using various probability distributions to perform the sampling.


Design and experimental evaluation of the hydraulically actuated prototype leg of the HyQ robot

This paper focuses on the design and experimental evaluation of a hydraulically actuated robot leg. The evaluation of the leg prototype is an important milestone in the development of HyQ, a Hydraulically actuated Quadruped robot. The prototype features two rotary joints actuated by hydraulic cylinders and has a mass of 4.5kg. We performed several experiments with the leg prototype attached to a vertical slider to tests the robustness of the mechanical design and the hydraulic actuation system. Besides the experimental evaluation of the hydraulic components, we also extensively studied the sensor data of the leg during periodic hopping. The results show that hydraulic actuation is suitable for legged robots because of its high power-to-weight ratio, fast response and ability to cope with high impact force peaks. Furthermore, we compare the cylinder force data obtained by the load cell with the calculated value based on the cylinder pressures to analyze if it is possible to eliminate this sensory system redundancy in the future. Through these studies, weaknesses of the design were identified and suggestions on how to improve them are presented.


Cortical coordination dynamics and cognition

New imaging techniques in cognitive neuroscience have produced a deluge of information correlating cognitive and neural phenomena. Yet our understanding of the inter-relationship between brain and mind remains hampered by the lack of a theoretical language for expressing cognitive functions in neural terms. We propose an approach to understanding operational laws in cognition based on principles of coordination dynamics that are derived from a simple and experimentally verified theoretical model. When applied to the dynamical properties of cortical areas and their coordination, these principles support a mechanism of adaptive inter-area pattern constraint that we postulate underlies cognitive operations generally.


Cerebral mechanisms of word masking and unconscious repetition priming

We used functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) to visualize the cerebral processing of unseen masked words. Within the areas associated with conscious reading, masked words activated left extrastriate, fusiform and precentral areas. Furthermore, masked words reduced the amount of activation evoked by a subsequent conscious presentation of the same word. In the left fusiform gyrus, this repetition suppression phenomenon was independent of whether the prime and target shared the same case, indicating that case-independent information about letter strings was extracted unconsciously. In comparison to an unmasked situation, however, the activation evoked by masked words was drastically reduced and was undetectable in prefrontal and parietal areas, correlating with participants' inability to report the masked words.


Neural Darwinism and consciousness

Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.


An information integration theory of consciousness

Consciousness poses two main problems. The first is understanding the conditions that determine to what extent a system has conscious experience. For instance, why is our consciousness generated by certain parts of our brain, such as the thalamocortical system, and not by other parts, such as the cerebellum? And why are we conscious during wakefulness and much less so during dreamless sleep? The second problem is understanding the conditions that determine what kind of consciousness a system has. For example, why do specific parts of the brain contribute specific qualities to our conscious experience, such as vision and audition? This paper presents a theory about what consciousness is and how it can be measured. According to the theory, consciousness corresponds to the capacity of a system to integrate information. This claim is motivated by two key phenomenological properties of consciousness: differentiation – the availability of a very large number of conscious experiences; and integration – the unity of each such experience. The theory states that the quantity of consciousness available to a system can be measured as the Φ value of a complex of elements. Φ is the amount of causally effective information that can be integrated across the informational weakest link of a subset of elements. A complex is a subset of elements with Φ>0 that is not part of a subset of higher Φ. The theory also claims that the quality of consciousness is determined by the informational relationships among the elements of a complex, which are specified by the values of effective information among them. Finally, each particular conscious experience is specified by the value, at any given time, of the variables mediating informational interactions among the elements of a complex. The information integration theory accounts, in a principled manner, for several neurobiological observations concerning consciousness. As shown here, these include the association of consciousness with certain neural systems rather than with others; the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; the reduction of consciousness during dreamless sleep and generalized seizures; and the time requirements on neural interactions that support consciousness. The theory entails that consciousness is a fundamental quantity, that it is graded, that it is present in infants and animals, and that it should be possible to build conscious artifacts.


Interaction as performance : cases of configuring physical interfaces in mixed media

Mixed media, as artful assemblages of digital objects and physical artefacts, provide distinctive opportunities for experiential, presentational and representational interaction. In project-based learning of architecture design, participants staged spatial narratives with multiple projections, performed mixed objects and artefacts, and exploited bodily movements in mixed representations. These cases show how physical interfaces in mixed media acquire a spatial dimension, integrate physical artefacts and bodily movements and propose configurability as a central feature. A perspective based on anthropological concepts of performance makes it possible to address these aspects in a coherent way, pointing to sense experience, the individuality and collective emergence of expression and its diachronic and event-like character. From this perspective, interaction is part of expressive events aimed at generating new insights for participants (interchangeable performers and spectators) privileging sense experience. Events are the outcome of configurations of space, artefacts and digital media, and are characterised by a simultaneousness of doing and undergoing, of bodily presence and representation. More importantly, the performance perspective suggests a particular temporal view of interaction, based on the concept of event, addressing a neglected granularity of analysis between the moment-by-moment unfolding of interaction and the longer term co-evolution of technology and practice. Implications of interaction as performance contribute to a wider program of interaction design, thereby providing alternatives to established human-computer interaction tenets: the notion of event is an alternative to the notion of task; perception in Dewey's terms replaces recognition proposing expression as an alternative to accountability and usability. Implications include looking at how space can be configured and staged instead of measured or simulated, and how situations can be staged instead of sensed and recognised, privileging the sensing human over the


Driver Gaze Region Estimation Without Using Eye Movement

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Controlling privacy in recommender systems

Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferences. In this paper, we explore a two-tiered notion of privacy where there is a small set of “public” users who are willing to share their preferences openly, and a large set of “private” users who require privacy guarantees. We show theoretically and demonstrate empirically that a moderate number of public users with no access to private user information already suffices for reasonable accuracy. Moreover, we introduce a new privacy concept for gleaning relational information from private users while maintaining a first order deniability. We demonstrate gains from controlled access to private user preferences.


On fast surface reconstruction methods for large and noisy point clouds

In this paper we present a method for fast surface reconstruction from large noisy datasets. Given an unorganized 3D point cloud, our algorithm recreates the underlying surface's geometrical properties using data resampling and a robust triangulation algorithm in near realtime. For resulting smooth surfaces, the data is resampled with variable densities according to previously estimated surface curvatures. Incremental scans are easily incorporated into an existing surface mesh, by determining the respective overlapping area and reconstructing only the updated part of the surface mesh. The proposed framework is flexible enough to be integrated with additional point label information, where groups of points sharing the same label are clustered together and can be reconstructed separately, thus allowing fast updates via triangular mesh decoupling. To validate our approach, we present results obtained from laser scans acquired in both indoor and outdoor environments.


Distant Supervision for Relation Extraction with Hierarchical Attention and Entity Descriptions

Distant supervision for relation extraction is an effective method to find novel relational facts from plain text. However, distant supervision inevitably suffers from wrong label problem, and most existing methods generally focus on direct sentences containing entity pairs, but ignore massive information from background knowledge. To tackle these problems, we propose a novel hierarchical attention model to select valid instances and capture vital semantic information in them. Furthermore, we incorporate entity descriptions extracted from Wikipedia into the hierarchical attention model to provide supplementary background knowledge. The proposed architecture can not only combat the noise introduced by distant supervision, but also adequately extract latent and helpful background information. The experimental results on both Chinese and English datasets show that the proposed approach consistently achieves significant improvements on relation extraction as compared with strong baselines.


2018 Low-Power Image Recognition Challenge

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technologies that can classify and detect objects in images efficiently (short execution time and low energy consumption) and accurately (high precision). Over the four years, the winners’ scores have improved more than 24 times. As computer vision is widely used in many battery-powered systems (such as drones and mobile phones), the need for low-power computer vision will become increasingly important. This paper summarizes LPIRC 2018 by describing the three different tracks and the winners’ solutions.


A layered naming architecture for the internet

Currently the Internet has only one level of name resolution, DNS, which converts user-level domain names into IP addresses. In this paper we borrow liberally from the literature to argue that there should be three levels of name resolution: from user-level descriptors to service identifiers; from service identifiers to endpoint identifiers; and from endpoint identifiers to IP addresses. These additional levels of naming and resolution (1) allow services and data to be first class Internet objects (in that they can be directly and persistently named), (2) seamlessly accommodate mobility and multi-homing and (3) integrate middleboxes (such as NATs and firewalls) into the Internet architecture. We further argue that flat names are a natural choice for the service and endpoint identifiers. Hence, this architecture requires scalable resolution of flat names, a capability that distributed hash tables (DHTs) can provide.


Pathophysiology of human visceral obesity: an update.

Excess intra-abdominal adipose tissue accumulation, often termed visceral obesity, is part of a phenotype including dysfunctional subcutaneous adipose tissue expansion and ectopic triglyceride storage closely related to clustering cardiometabolic risk factors. Hypertriglyceridemia; increased free fatty acid availability; adipose tissue release of proinflammatory cytokines; liver insulin resistance and inflammation; increased liver VLDL synthesis and secretion; reduced clearance of triglyceride-rich lipoproteins; presence of small, dense LDL particles; and reduced HDL cholesterol levels are among the many metabolic alterations closely related to this condition. Age, gender, genetics, and ethnicity are broad etiological factors contributing to variation in visceral adipose tissue accumulation. Specific mechanisms responsible for proportionally increased visceral fat storage when facing positive energy balance and weight gain may involve sex hormones, local cortisol production in abdominal adipose tissues, endocannabinoids, growth hormone, and dietary fructose. Physiological characteristics of abdominal adipose tissues such as adipocyte size and number, lipolytic responsiveness, lipid storage capacity, and inflammatory cytokine production are significant correlates and even possible determinants of the increased cardiometabolic risk associated with visceral obesity. Thiazolidinediones, estrogen replacement in postmenopausal women, and testosterone replacement in androgen-deficient men have been shown to favorably modulate body fat distribution and cardiometabolic risk to various degrees. However, some of these therapies must now be considered in the context of their serious side effects. Lifestyle interventions leading to weight loss generally induce preferential mobilization of visceral fat. In clinical practice, measuring waist circumference in addition to the body mass index could be helpful for the identification and management of a subgroup of overweight or obese patients at high cardiometabolic risk.


Linked Data and multimedia: the state of affairs

Linked Data is a way of exposing and sharing data as resources on the Web and interlinking them with semantically related resources. In the last three years significant amounts of data have been generated, increasingly forming a globally connected, distributed data space. For multimedia content, metadata are a key factor for efficient management, organization, and retrieval. However, the relationship between multimedia and Linked Data has been rarely studied, leading to a lack of mutual awareness and, as a consequence thereof, technological deficiencies. This article introduces the basic concepts of Linked Data in the context of multimedia metadata, and discusses techniques to generate, expose, discover, and consume Linked Data. It shows that a large amount of data sources exist, which are ready to be exploited by multimedia applications. The benefit of Linked Data in two multimedia-related applications is discussed and open research issues are outlined with the goal of bringing the research fields of multimedia and Linked Data closer together in order to facilitate mutual benefit.


Cheek defects.

The challenge surgeons face when reconstructing cheek defects varies significantly depending on the location and depth of the defect and the distensibility of the surrounding tissues. The cheek is a large aesthetic unit characterized in most areas with a convex surface and inherent transitions in color and texture. These characteristics demand the surgeon's attention to achieve superior results during reconstruction. Surgeons must also recognize the free margins of the adjacent structures, including the lower eyelid, nasal ala, and lip, to minimize distortion of these areas during healing. With these challenges in mind, this article discusses several approaches to reconstruction of various types of cheek defects.


Role of self-care in management of diabetes mellitus

Diabetes mellitus (DM) is a chronic progressive metabolic disorder characterized by hyperglycemia mainly due to absolute (Type 1 DM) or relative (Type 2 DM) deficiency of insulin hormone. World Health Organization estimates that more than 346 million people worldwide have DM. This number is likely to more than double by 2030 without any intervention. The needs of diabetic patients are not only limited to adequate glycemic control but also correspond with preventing complications; disability limitation and rehabilitation. There are seven essential self-care behaviors in people with diabetes which predict good outcomes namely healthy eating, being physically active, monitoring of blood sugar, compliant with medications, good problem-solving skills, healthy coping skills and risk-reduction behaviors. All these seven behaviors have been found to be positively correlated with good glycemic control, reduction of complications and improvement in quality of life. Individuals with diabetes have been shown to make a dramatic impact on the progression and development of their disease by participating in their own care. Despite this fact, compliance or adherence to these activities has been found to be low, especially when looking at long-term changes. Though multiple demographic, socio-economic and social support factors can be considered as positive contributors in facilitating self-care activities in diabetic patients, role of clinicians in promoting self-care is vital and has to be emphasized. Realizing the multi-faceted nature of the problem, a systematic, multi-pronged and an integrated approach is required for promoting self-care practices among diabetic patients to avert any long-term complications.


Improving the Accuracy and Speed of Support Vector Machines

Bernhard Scholkopf" Max-Planck-Institut fur biologische Kybernetik , Spemannstr. 38 72076 Tubingen, Germany bs@mpik-tueb.mpg.de Support Vector Learning Machines (SVM) are finding application in pattern recognition , regression estimation , and operator inversion for ill-posed problems. Against this very general backdrop , any methods for improving the generalization performance, or for improving the speed in test phase, of SVMs are of increasing interest. In this paper we combine two such techniques on a pattern recognition problem. The method for improving generalization performance (the "virtual support vector" method) does so by incorporating known invariances of the problem. This method achieves a drop in the error rate on 10,000 NIST test digit images of 1.4% to 1.0%. The method for improving the speed (the "reduced set" method) does so by approximating the support vector decision surface. We apply this method to achieve a factor of fifty speedup in test phase over the virtual support vector machine. The combined approach yields a machine which is both 22 times faster than the original machine, and which has better generalization performance, achieving 1.1 % error. The virtual support vector method is applicable to any SVM problem with known invariances. The reduced set method is applicable to any support vector machine.


Online continuous stereo extrinsic parameter estimation

Stereo visual odometry and dense scene reconstruction depend critically on accurate calibration of the extrinsic (relative) stereo camera poses. We present an algorithm for continuous, online stereo extrinsic re-calibration operating only on sparse stereo correspondences on a per-frame basis. We obtain the 5 degree of freedom extrinsic pose for each frame, with a fixed baseline, making it possible to model time-dependent variations. The initial extrinsic estimates are found by minimizing epipolar errors, and are refined via a Kalman Filter (KF). Observation covariances are derived from the Cramer-Rao lower bound of the solution uncertainty. The algorithm operates at frame rate with unoptimized Matlab code with over 1000 correspondences per frame. We validate its performance using a variety of real stereo datasets and simulations.


ActiveStereoNet: End-to-End Self-supervised Learning for Active Stereo Systems

In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. Due to the lack of ground truth, our method is fully self-supervised, yet it produces precise depth with a subpixel precision of 1/30th of a pixel; it does not suffer from the common over-smoothing issues; it preserves the edges; and it explicitly handles occlusions. We introduce a novel reconstruction loss that is more robust to noise and texture-less patches, and is invariant to illumination changes. The proposed loss is optimized using a window-based cost aggregation with an adaptive support weight scheme. This cost aggregation is edge-preserving and smooths the loss function, which is key to allow the network to reach compelling results. Finally we show how the task of predicting invalid regions, such as occlusions, can be trained end-toend without ground-truth. This component is crucial to reduce blur and particularly improves predictions along depth discontinuities. Extensive quantitatively and qualitatively evaluations on real and synthetic data demonstrate state of the art results in many challenging scenes.


Towards 5G Security

This paper discusses potential security requirements and mechanisms for 5G mobile networks. It does not intend to do so exhaustively, but rather aims at initiating and spurring the work towards a 5G security architecture.


Cyclic codes over the ring 𝔽p[u, v] / 〈uk, v2, uv-vu〉

Article history: Received 4 June 2014 Received in revised form 29 December 2014 Accepted 13 January 2015 Available online xxxx Communicated by W. Cary Huffman


The internet of energy: a web-enabled smart grid system

The quest for sustainable energy models is the main factor driving research on smart grid technology. SGs represent the bridging paradigm to enable highly efficient energy production, transport, and consumption along the whole chain, from the source to the user. Although this concept promises to be very fruitful, the research on how to deploy it in the real world has just begun. A discussion on the enabling technologies for SGs and a possible roadmap for the profitable evolution thereof is the focus of this article. After introducing the recent trends that are pushing the SG paradigm, we will discuss various key scenarios for the SG, and briefly introduce some of its key requirements. We will then provide an analysis of how current and future standard solutions in the areas of communications and networking can be engineered into a system that fulfills the needs of the SG vision. We advocate the use of small, cheap, and resource-constrained devices with pervasive computing capabilities as the key component to deploy a ubiquitous energy control system. To this end, the recent efforts carried out by Internet standardization bodies such as the IETF and W3C toward the vision of the Internet of Things (IoT) are especially relevant. The various components of the proposed solution have been successfully showcased in real-world implementations, and relevant actors such as ETSI, ZigBee, and IPSO are already evaluating their potential for future IoT applications, making the Internet-based smart grid vision considered in this article practically achievable in the not too distant future.


Power laws , Pareto distributions and Zipf ’ s law

When the probability of measuring a particular value of some quantity varies inversely as a power of that value, the quantity is said to follow a power law, also known variously as Zipf’s law or the Pareto distribution. Power laws appear widely in physics, biology, earth and planetary sciences, economics and finance, computer science, demography and the social sciences. For instance, the distributions of the sizes of cities, earthquakes, forest fires, solar flares, moon craters and people’s personal fortunes all appear to follow power laws. The origin of power-law behaviour has been a topic of debate in the scientific community for more than a century. Here we review some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them.


LED driver circuit with inherent PFC

A buck-boost topology operating in discontinuous conduction mode (DCM) is used as an off line LED driver for lighting applications. Operating from a full wave rectified ac-voltage with minimum input capacitance, with a constant switching frequency and constant on-time, the utility current has near unity power factor. This LED driver is suitable for cost sensitive applications because this circuit has a minimal parts count and a very simple control circuit. Disadvantages are that the LED drive current is modulated at twice the utility frequency and DCM operation increases component stress levels.


Retargeting Semantically-Rich Photos

Semantically-rich photos contain a rich variety of semantic objects (e.g., pedestrians and bicycles). Retargeting these photos is a challenging task since each semantic object has fixed geometric characteristics. Shrinking these objects simultaneously during retargeting is prone to distortion. In this paper, we propose to retarget semantically-rich photos by detecting photo semantics from image tags, which are predicted by a multi-label SVM. The key technique is a generative model termed latent stability discovery (LSD). It can robustly localize various semantic objects in a photo by making use of the predicted noisy image tags. Based on LSD, a feature fusion algorithm is proposed to detect salient regions at both the low-level and high-level. These salient regions are linked into a path sequentially to simulate human visual perception . Finally, we learn the prior distribution of such paths from aesthetically pleasing training photos. The prior enforces the path of a retargeted photo to be maximally similar to those from the training photos. In the experiment, we collect 217 1600 ×1200 photos, each containing over seven salient objects. Comprehensive user studies demonstrate the competitiveness of our method.


Euler Number and Connectivity Indexes of a Three Dimensional Digital Picture

Fundamental properties of topological structure of a 3D digitized picture are presented including the concept of neighborhood and connectivity among volume cells (voxels) of 3D digitized binary pictures defined on a cubic grid, the concept of simplicial decomposition of a 3D digitized object, and two algorithms for calculating the Euler number (genus). First we define four types of connectivity. Second we present two algorithms to calculate the Euler number of a 3D figure. Thirdly we introduce new local features called the connectivity number (CN) and the connectivity index to study topological properties of a 3D object in a 3D digitized picture. The CN at a 1-voxel (=a voxel with the value 1) x is defined as the change in the Euler number of the object caused by changing the value of x into zero, that is, caused by deleting x. Finally, by using them, we prove a necessary and sufficient condition that a 1-voxel is deletable. A 1-voxel x is said to be deletable if deletion of x causes no decrease and no increase in the numbers of connected components, holes and cavities in a given 3D picture.


Necessary Conditions for Existence of Some Designs in Polynomial Metric Spaces

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


On Maximal Spherical Codes I

We investigate the possibilities for attaining two Levenshtein upper bounds for spherical codes. We find the distance distributions of all codes meeting these bounds. Then we show that the fourth Levenshtein bound can be attained in some very special cases only. We prove that no codes with an irrational maximal scalar product meet the third Levenshtein bound. So in dimensions 3 ≤ n ≤ 100 exactly seven codes are known to attain this bound and ten cases remain undecided. Moreover, the first two codes (in dimensions 5 and 6) are unique up to isometry. Nonexistence of maximal codes in all dimensions n with cardinalities between 2n+1 and 2n+ [7 √ n ] is shown as well. We prove nonexistence of several infinite families of maximal codes whose maximal scalar product is rational. The distance distributions of the only known nontrivial infinite family of maximal codes (due to Levenshtein) are given.


Interpolation and approximation in L2(gamma)

Assume a standard Brownian motion W = (Wt )t∈[0,1], a Borel function f : R → R such that f (W1) ∈ L2, and the standard Gaussian measure on the real line. We characterize that f belongs to the Besov space B 2,q ( ) := (L2( ), D1,2( )) ,q , obtained via the real interpolation method, by the behavior of aX(f (X1); ) := ‖f (W1)−P Xf (W1)‖L2 , where =(ti )ni=0 is a deterministic time net and P X : L2 → L2 the orthogonal projection onto a subspace of ‘discrete’stochastic integrals x0+ ∑n i=1 vi−1(Xti −Xti−1) with X being the Brownian motion or the geometric Brownian motion. By using Hermite polynomial expansions the problem is reduced to a deterministic one. The approximation numbers aX(f (X1); ) can be used to describe the L2-error in discrete time simulations of the martingale generated by f (W1) and (in stochastic finance) to describe the minimal quadratic hedging error of certain discretely adjusted portfolios. © 2006 Elsevier Inc. All rights reserved.


On Maximal Codes in Polynominal Metric Spaces


Nonexistence of Certain Spherical Designs of Odd Strengths and Cardinalities

A sphericalτ -design onSn−1 is a finite set such that, for all polynomials f of degree at most τ , the average of over the set is equal to the average of f over the sphere Sn−1. In this paper we obtain some necessary conditions for the existence of designs of odd strengths and cardinalities. This gives nonexistence results in many cases. Asymptotically, we derive a bound which is better than the corresponding estimation ensured by the Delsarte– Goethals–Seidel bound. We consider in detail the strengths τ = 3 andτ = 5 and obtain further nonexistence results in these cases. When the nonexistence argument does not work, we obtain bounds on the minimum distance of such designs.


Image Steganography based on a Parameterized Canny Edge Detection Algorithm

Steganography is the science of hiding digital information in such a way that no one can suspect its existence. Unlike cryptography which may arouse suspicions, steganography is a stealthy method that enables data communication in total secrecy. Steganography has many requirements, the foremost one is irrecoverability which refers to how hard it is for someone apart from the original communicating parties to detect and recover the hidden data out of the secret communication. A good strategy to guaranteeirrecoverability is to cover the secret data not usinga trivial method based on a predictable algorithm, but using a specific random pattern based on a mathematical algorithm. This paper proposes an image steganography technique based on theCanny edge detection algorithm. It is designed to hide secret data into a digital image within the pixels that make up the boundaries of objects detected in the image. More specifically, bits of the secret data replace the three LSBs of every color channel of the pixels detected by the Canny edge detection algorithm as part of the edges in the carrier image. Besides, the algorithm is parameterized by three parameters: The size of the Gaussian filter, a low threshold value, and a high threshold value. These parameters can yield to different outputs for the same input image and secret data. As a result, discovering the inner-workings of the algorithm would be considerably ambiguous, misguiding steganalysts from the exact location of the covert data. Experiments showed a simulation tool codenamed GhostBit, meant to cover and uncover secret data using the proposed algorithm. As future work, examining how other image processing techniques such as brightness and contrast adjustment can be taken


Comparative analysis of master-slave latches and flip-flops for high-performance and low-power systems

In this paper, we propose a set of rules for consistent estimation of the real performance and power features of the flip-flop and master–slave latch structures. A new simulation and optimization approach is presented, targeting both highperformance and power budget issues. The analysis approach reveals the sources of performance and power-consumption bottlenecks in different design styles. Certain misleading parameters have been properly modified and weighted to reflect the real properties of the compared structures. Furthermore, the results of the comparison of representative master–slave latches and flipflops illustrate the advantages of our approach and the suitability of different design styles for high-performance and low-power applications.


Dual-band microstrip antenna for WiMAX applications using complementary split ring resonators

A new design of dual-band microstrip antenna is presented in this paper using metamaterial concept. By etching a metamaterial unit cells that have a resonance frequency of 5.3 GHz within the ground plane of a conventional patch resonates at 3.6 GHz, a dual resonance response is created to satisfy the requirement of covering the middle and upper bands of Wi-MAX.A detailed study of the placement of the unit cell is introduced and the most suitable one is chosen to be the place of our unit cell. Multi-unit cell concept is used for performance enhancement of the fabricated design to achieve a good matching with the simulated one.


A Two-Level Investigation of Information Systems Outsourcing

O UTSOURCING is the contracting of various systems to outside information systems (IS) vendors. Ever since the Eastman Kodak--IBM partnership was reported in 1989 [15], outsourcing has emerged and has been recognized as a key method of managing IS. In previous studies of outsourcing [4, 5, 12, 15, 17, 20], two gaps are noticeable. The first relates to the fact that requirements for outsourcing are not uniform, and managers have different approaches to the process. Yet most previous research studies have phrased their inquiries unidimensionally in terms of the extent or degree of outsourcing: either as a binary variable or as size of contract in terms of the percentage of total IS budget [5, 15]. Neither unidimensional gauge is sufficiently expressive; neither allows representation of diverse patterns of outsourcing. Second, even though the IS industry had not used the term “outsourcing” explicitly in the past, outsourcing is not a new concept and has existed for many years in one form or another. Even though firms have repetitively used outside vendors for years, researchers have neither considered prior relationships in their studies of IS outsourcing nor studied the intentions of client firms to continue the partnership with the outsourcing vendors in the future. In this study, IS outsourcing decisions are investigated at two levels. The first level deals with the initial outsourcing decision of client firms. The second level pertains to the intention to continue the relationships with current outsourcing vendors in the future. The following three research questions are explored at these two levels (in contrast to the singlelevel approach taken by most researchers): • What are the dimensions of outsourcing decisions? Two dimensions, extent of substitution by vendors and strategic impact of IS applications, are proposed in order to conceptualize the diverse types of outsourcing relationships between clients and vendors. Based on these two dimensions, four types of outsourcing relationships are proposed. • What are the determinants that affect the dimensions of outsourcing decisions at the first level? The concepts derived from incomplete contracts [2, 9] and transactions cost economics [23, 24] theory are used with information technology (IT) organizational contexts and processes as a foundation to study the determinants of the two dimensions of outsourcing decisions. Information Syst


Design of Low Actuation Voltage RF MEMS Switch

Low-loss microwave microelectromechanical systems (MEMS) shunt switches are reported that utilize highly compliant serpentine spring folded suspensions together with large area capacitive actuators to achieve low actuation voltages while maintaining sufficient off-state isolation. The RF MEMS switches were fabricated via a surface micromachining process using PI2545 Polyimide 1 as the sacrificial layer. The switch structure was composed of electroplated nickel and the serpentine folded suspensions had varying number of meanders from 1 to 5. DC measurements indicate actuation voltages as low as 9 V with an on-to-off capacitance ratio of 48. Power handling measurement results showed no ”selfbiasing” or failure of the MEMS switches for power levels up to 6.6W. RF measurements demonstrate an isolation of -26 dB at 40 GHz.


Comparison of different methods to cancel offset capacitance in capacitive displacement sensors

This paper presents a comparative study of the power consumption of two methods to cancel the offset capacitance in high-resolution capacitive displacement sensors. One method is applied based on correlated-double-sampling (CDS) technique and the other method is applied using oversampling technique. The analytical comparison predicts similar power consumption, if the same resolution for the same conversion time need to be reached. Experimental results with implementations of the two methods confirmed the analytical prediction.


From IT Addiction to Discontinued Use: A Cognitive Dissonance Perspective

One of the main topics discussed within the realm of the dark side of IT is addiction. IT addiction has been found to bring adverse consequences on users’ lives. In order to overcome the difficulties associated with IT addiction, interrupting and quitting addiction has become an important research agenda. Recent research findings have shown that IT addicts do not always feel guilty about their usage, and in many cases, they do not even perceive their usage as problematic. In this study, we draw on cognitive dissonance theory to theorize and propose a model showing that the degree of users’ cognitive dissonance can make a difference in their willingness to quit their IT addiction. We tested the model using data collected from 226 social network sites users. The analysis provided empirical support for our model and shed light on the mediation and moderation effects of cognitive dissonance in this process. 1


Comparison of Internet addicts and non-addicts in Taiwanese high school

This study investigated the difference between Internet addicts and non-addicts in Taiwanese high schools, and focused specifically on their Internet usage patterns, and gratification and communication pleasures. A total of 1708 valid data samples of high school adolescents were collected. Among this sample, 236 subjects (13.8%) were identified as addicts using the eight-item Internet addiction Diagnostic Questionnaire designed by Young [Internet addiction survey [Online]. Available: http://www.pitt.edu/_ksy/survey.htm]. The analytical results revealed that Internet addicts spent almost twice as many hours on line on average than the non-addicts. Notably, surfing with a social/entertainment motivation and gratification was positively correlated with Internet addiction. Furthermore, Internet addicts obtained markedly higher overall PIUST scores and scored higher than non-addicts on four subscales (tolerance; compulsive use and withdrawal; related problems, including family, school, health, and other problems; interpersonal and financial problems). While Internet addicts perceived the Internet to have significantly more negative influences on daily routines, school performance, teacher and parental relation than non-addicts, both Internet addicts and non-addicts viewed Internet use as enhancing peer relations. Moreover, students with personalities characterized by dependence, shyness, depression and low self-esteem had a high tendency to become addicted. 2004 Elsevier Ltd. All rights reserved.


Scheduling in the Dark ( Improved Result )

We considered non-clairvoyant multiprocessor scheduling of jobs with arbitrary arrival times and changing execution characteristics. The problem has been studied extensively when either the jobs all arrive at time zero, or when all the jobs are fully parallelizable, or when the scheduler has considerable knowledge about the jobs. This paper considers for the first time this problem without any of these three restrictions yet when our algorithm is given more resources than the adversary. We provide new upper and lower bound techniques applicable in this more difficult scenario. The results are of both theoretical and practical interest. In our model, a job can arrive at any arbitrary time and its execution characteristics can change through the life of the job from being anywhere from fully parallelizable to completely sequential. We assume that the scheduler has no knowledge about the jobs except for knowing when a job arrives and knowing when it completes. (This is why we say that the scheduler is completely in the dark.) Given all this, we prove that the scheduler algorithm Equi-partition, though simple, performs within a constant factor as well as the optimal scheduler as long as it is given at least twice as many processors. More over, we prove that if none of the jobs are ”strictly” fully parallelizable, then Equi-partition performs competitively with no extra processors. Author is supported by NSERC Canada.


Optimal Lower Bounds on Regular Expression Size Using Communication Complexity

The problem of converting deterministic finite automata into (short) regular expressions is considered. It is known that the required expression size is 2 in the worst case for infinite languages, and for finite languages it is n log n) and n , if the alphabet size grows with the number of states n of the given automaton. A new lower bound method based on communication complexity for regular expression size is developed to show that the required size is indeed n . For constant alphabet size the best lower bound known to date is Ω(n), even when allowing infinite languages and nondeterministic finite automata. As the technique developed here works equally well for deterministic finite automata over binary alphabets, the lower bound is improved to n .


Quantifying the Security Posture of Containerized Mission Critical Systems

Determining the security posture of containerized mission-critical systems is difficult given the vast number of parameters that determine a system's ability to withstand cyber-attacks. In many cases, technical audits can be performed to determine a system's security posture and to evaluate how well they are configured to protect against known cyber-threats. Properly configuring systems can lead to higher security, however, the configuration and auditing process can be time-consuming and error-prone. In addition, the results obtained from these audits can be difficult to summarize into one meaningful metric that accurately characterizes system's security posture as guided by customer needs. In this work, we propose an approach for computing a security-posture metric for containerized systems that supports operators during the sense-making process that follows traditional security audits. The results of this work can be used on a per-deployment case, taking into account what matters to operators of containerized mission-critical systems.


Intelligent Heart Disease Prediction System Using Probabilistic Neural Network

The diagnosis of diseases is a crucial and difficult job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by hasty effects [1]. Thus an attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a great challenge. The healthcare industry gathers enormous amounts of heart disease data that unfortunately, are not mined to determine concealed information for effective diagnosing [2]. In this paper, an efficient approach for the intelligent heart disease prediction based on Probabilistic Neural Network (PNN) technique is proposed. Initially, the data set containing 13 medical attributes were obtained from the Cleveland heart disease database. The dataset is clustered with the aid of k-means clustering algorithm. The PNN with radial basis function is trained using the selected data sets. The comparison between existing approaches and proposed approach with respect to accuracy of prediction, sensitivity and specificity is recorded in this paper. The results from experiments returned with diminishing fact that there is considerable improvement in classification and prediction. The proposed PNN works as promising tool for prediction of heart disease.


Requirements for Safe Robots : Measurements , Analysis and New Insights

Physical human–robot interaction and cooperation has become a topic of increasing importance and of major focus in robotics research. An essential requirement of a robot designed for high mobility and direct interaction with human users or uncertain environments is that it must in no case pose a threat to the human. Until recently, quite a few attempts were made to investigate real-world threats via collision tests and use the outcome to considerably improve safety during physical human–robot interaction. In this paper, we give an overview of our systematic evaluation of safety in human–robot interaction, covering various aspects of the most significant injury mechanisms. In order to quantify the potential injury risk emanating from such a manipulator, impact tests with the DLR-Lightweight Robot III were carried out using standard automobile crash test facilities at the German Automobile Club (ADAC). Based on these tests, several industrial robots of different weight have been evaluated and the influence of the robot mass and velocity have been investigated. The evaluated non-constrained impacts would only partially capture the nature of human–robot safety. A possibly constrained environment and its effect on the resulting human injuries are discussed and evaluated from different perspectives. As well as such impact tests and simulations, we have analyzed the problem of the quasi-static constrained impact, which could pose a serious threat to the human even for low-inertia robots under certain circumstances. Finally, possible injuries relevant in robotics are summarized and systematically classified. KEY WORDS—Physical Human-Robot Interaction, Simulation, Flexible Arms, Mechanics, Design and Control, Force Control The International Journal of Robotics Research Vol. 00, No. 00, Xxxxxxxx 2009, pp. 000–000 DOI: 10.1177/0278364909343970 c The Author(s), 2009. Reprints and permissions: http://www.sagepub.co.uk/journalsPermissions.nav Figures 1–10, 12–18 appear in color online: http://ijr.sagepub.com


Sego: Pervasive Trusted Metadata for Efficiently Verified Untrusted System Services

Sego is a hypervisor-based system that gives strong privacy and integrity guarantees to trusted applications, even when the guest operating system is compromised or hostile. Sego verifies operating system services, like the file system, instead of replacing them. By associating trusted metadata with user data across all system devices, Sego verifies system services more efficiently than previous systems, especially services that depend on data contents. We extensively evaluate Sego's performance on real workloads and implement a kernel fault injector to validate Sego's file system-agnostic crash consistency and recovery protocol.


A Data Driven Approach for Algebraic Loop Invariants

We describe a new algorithm GUESS-AND-CHECK for computing algebraic equation invariants. These invariants are of the form ∧ifi(x1, . . . , xn) = 0, where each fi is a polynomial over the variables x1, . . . , xn of the program. Two novel features of our algorithm are:(1) it is data driven, that is, invariants are derived from data generated from concrete executions of the program, and (2) it is sound and complete, that is, the algorithm terminates with the correct invariant if it exists. The GUESS-AND-CHECK algorithm proceeds iteratively in two phases. The “guess” phase uses linear algebra techniques to efficiently derive a candidate invariant from data. This candidate invariant is subsequently validated in a “check” phase. If the check phase fails to validate the candidate invariant, then the proof of invalidity is used to generate more data and this is used to find better candidate invariants in a subsequent guess phase. Therefore, GUESS-AND-CHECK iteratively invokes the guess and check phases until it finds the desired invariant. In terms of implementation, off-the-shelf linear algebra solvers are used to implement the guess phase, and off-the-shelf decision procedures are used to implement the check phase. We have evaluated our technique on a number of benchmark programs from recent papers on invariant generation. Our results are encouraging – we are able to efficiently compute algebraic invariants in all cases.


Nanowire Ultraviolet Photodetectors and Optical Switches

Nanowires and nanotubes may become important building blocks for nanoscale optoelectronics, since they can function as miniaturized devices as well as electrical interconnects. Nano-devices such as field-effect transistors, single-electron transistors, metal±semiconductor junctions, and intermolecular crossed junctions have been demonstrated. Many of these devices rely on binary switching, which is critical for important applications such as memory storage and logic circuits. Switching on the nanometer and molecular level has been predominantly achieved through proper electrical gating, as exemplified by nanotube transistors. However, no attention has been given to the photoconducting properties of nanowires despite the exciting possibilities for use in optoelectronic circuits. Here, we show the possibility of creating highly sensitive nanowire switches by exploring the photoconducting properties of individual semiconductor nanowires. The conductivity of the ZnO nanowires is extremely sensitive to ultraviolet light exposure. The light-induced conductivity increase allows us to reversibly switch the nanowires between aOFFo and aONo states, an optical gating phenomenon analogous to the commonly used electrical gating. The ZnO nanowires used in the experiments were grown by a vapor phase transport process developed in our lab. The diameters of these wires range from 50 to 300 nm. To characterize their photoconducting properties, the nanowires were dispersed directly on pre-fabricated gold electrodes. Alternatively, electron-beam lithography was used to fabricate gold electrodes on top of the nanowires. Field-emission scanning electron microscopy (FE-SEM) was used to image the ZnO nanowire devices. Electrical resistivity measurements were performed in a four-terminal configuration in air, nitrogen, or vacuum environments. Four-terminal measurements of individual ZnO nanowires indicate that they are highly insulating in the dark with a resistivity above 3.5 MX cm. When the nanowires are exposed to ultraviolet (UV)-light with wavelengths below 380 nm (handheld UV-lamp, 0.3 mW cm, 365 nm), the nanowire resistivity decreases by typically 4 to 6 orders of magnitude. Figure 1 compares the current±voltage (I±V) curves measured on a 60 nm nanowire in the dark and upon UV-light exposure. A larger photoresponse was detected at higher bias. We notice that the I±V curve for the UV-exposed nanowire exhibits nonlinear behavior. The same nonlinear I±V has been observed for both the wire-on-electrode and electrode-on-wire configurations. The four-terminal and two-terminal measurements show essentially identical resistivity values, which suggests that the Au/ZnO contacts may not contribute to the I±V nonlinearity. The exact reason for this nonlinearity remains unknown at this stage. The high sensitivity of the nanowire photoconductors can be seen in Figure 2, which shows the power dependence of the photoresponse. The third harmonic of a Nd:YAG laser was used as the UV light source. Neutral density filters were used to change the incident UV light power. It was found that the photoresponse (Ipc) can be expressed by a simple power law


The Dual-State Theory of Prefrontal Cortex Dopamine Function with Relevance to Catechol-<ce:italic>O</ce:italic>-Methyltransferase Genotypes and Schizophrenia

There is now general consensus that at least some of the cognitive deficits in schizophrenia are related to dysfunctions in the prefrontal cortex (PFC) dopamine (DA) system. At the cellular and synaptic level, the effects of DA in PFC via D1- and D2-class receptors are highly complex, often apparently opposing, and hence difficult to understand with regard to their functional implications. Biophysically realistic computational models have provided valuable insights into how the effects of DA on PFC neurons and synaptic currents as measured in vitro link up to the neural network and cognitive levels. They suggest the existence of two discrete dynamical regimes, a D1-dominated state characterized by a high energy barrier among different network patterns that favors robust online maintenance of information and a D2-dominated state characterized by a low energy barrier that is beneficial for flexible and fast switching among representational states. These predictions are consistent with a variety of electrophysiological, neuroimaging, and behavioral results in humans and nonhuman species. Moreover, these biophysically based models predict that imbalanced D1:D2 receptor activation causing extremely low or extremely high energy barriers among activity states could lead to the emergence of cognitive, positive, and negative symptoms observed in schizophrenia. Thus, combined experimental and computational approaches hold the promise of allowing a detailed mechanistic understanding of how DA alters information processing in normal and pathological conditions, thereby potentially providing new routes for the development of pharmacological treatments for schizophrenia.


KEEPING YOUR HEADCOUNT WHEN ALL ABOUT YOU ARE LOSING THEIRS : DOWNSIZING , VOLUNTARY TURNOVER RATES , AND THE MODERATING ROLE OF HR PRACTICES

Although both downsizing and voluntary turnover have been topics of great interest in the organizational literature, little research has addressed the possible relationship between the two. Using organization-level data from multiple industries, we first investigate whether downsizing predicts voluntary turnover rates. Second, to lend support to our causal model, we examine whether this relationship is mediated by aggregated levels of organizational commitment. Third, we test whether the downsizing-turnover rate relationship: (1) is mitigated by HR practices that tend to embed employees in the organization or convey procedural fairness; and (2) is strengthened by HR practices that enhance career development. Results support the hypothesized main, mediated, and moderated effects.


Bias in Wikipedia

While studies have shown that Wikipedia articles exhibit quality that is comparable to conventional encyclopedias, research still proves that Wikipedia, overall, is prone to many different types of Neutral Point of View (NPOV) violations that are explicitly or implicitly caused by bias from its editors. Related work focuses on political, cultural and gender bias. We are developing an approach for detecting both explicit and implicit bias in Wikipedia articles and observing its evolution over time. Our approach is based on different factors of bias, with the most important ones being language style, editors, and citations. In this paper we present the approach, methodology and a first analysis.


Touching the void: direct-touch interaction for intangible displays

In this paper, we explore the challenges in applying and investigate methodologies to improve direct-touch interaction on intangible displays. Direct-touch interaction simplifies object manipulation, because it combines the input and display into a single integrated interface. While traditional tangible display-based direct-touch technology is commonplace, similar direct-touch interaction within an intangible display paradigm presents many challenges. Given the lack of tactile feedback, direct-touch interaction on an intangible display may show poor performance even on the simplest of target acquisition tasks. In order to study this problem, we have created a prototype of an intangible display. In the initial study, we collected user discrepancy data corresponding to the interpretation of 3D location of targets shown on our intangible display. The result showed that participants performed poorly in determining the z-coordinate of the targets and were imprecise in their execution of screen touches within the system. Thirty percent of positioning operations showed errors larger than 30mm from the actual surface. This finding triggered our interest to design a second study, in which we quantified task time in the presence of visual and audio feedback. The pseudo-shadow visual feedback was shown to be helpful both in improving user performance and satisfaction.