title: CRITICAL SUCCESS FACTORS FOR THE IMPLEMENTATION OF ENTERPRISE RESOURCE PLANNING ( ERP ) : EMPIRICAL VALIDATION

abstract: Implementing an Enterprise Resource Planning (ERP) system project is a difficult and high cost proposition as it places tremendous demands on organization’s time and resources. The ERP implementation literature contains many case studies of organizations that have implemented ERP systems successfully. However, many organizations do not achieve success in their ERP implementation projects. Much has been written about implementation and the critical success factors for ERP implementation projects. But there very few studies have scientifically developed and tested constructs that represent critical success factors of ERP implementation projects. Based on a survey of 53 organizations in Australia, the results suggest that a 65 item instrument that measures seven dimensions of ERP implementation is well validated. It is argued that model proposed in the paper is valuable to researchers and practitioners interested in implementing Enterprise Resource Planning systems.


title: Front and rear vehicle detection and tracking in the day and night times using vision and sonar sensor fusion

abstract: Active research into vehicle detection and tracking using a vision sensor are done for driver assistance systems (DAS) - collision warning and avoidance, vision enhancement, etc. The vehicle detection and tracking algorithm for DAS requires a robust feature extraction and tracking method regardless of the light and road conditions and an exact estimation of vehicle position and velocity regardless of the distance from the ego-vehicle. But most research was carried out in the day time with good lighting conditions and the little research done so far in the night time assumed no interference of headlights from other vehicles. This paper proposes a new robust vehicle detection and tracking method regardless of the light and road conditions at any distance using vision and sonar sensors. We use the sonar sensor for detection and distance estimation within 10 m and the image sensor over 10 m. First, this paper proposes a simple method that can determine the light condition by observing several images and this light condition is used by selecting one of several detection methods. The proposed vehicle detection method in the day time image can extract the shadow region represented by the boundary between a vehicle and the road and further verify using other vehicle features, such as symmetry rate, vertical edge, and lane information. The vehicle tracking method in the day time uses online template matching using the mean image created by several consecutive detection results. The vehicle detection method in the night time extracts bright regions caused by the headlights, taillights, brake lights, etc. and these candidates are verified by observing several consecutive frames.


title: The case for research in game engine architecture

abstract: This paper is a call for research in the field of game engine architecture and design, a more comprehensive and thorough understanding of which we consider to be essential for its development. We present a number of key aspects that may help to define the problem space and provide a catalogue of questions that we believe identify areas of interest for future investigation.


title: Dynamic Control of Receiver Buffers in Mobile Video Streaming Systems

abstract: We propose a novel algorithm to efficiently transmit multiple Variable-Bit-Rate (VBR) video streams from a base station to mobile receivers in wide-area wireless networks. The algorithm multicasts video streams in bursts to save the energy of mobile devices. In addition, the algorithm adaptively controls the buffer levels of mobile devices receiving different video streams according to the bit rate of the video stream being received by each device. Compared to previous algorithms, the new algorithm enables dynamic control of the wireless channel and allows the base station to transmit more video data on time to mobile receivers. This is done by providing finer control over the bandwidth allocation of the wireless channel. The problem of optimizing energy saving has been shown to be NP-Complete. We prove that our algorithm finds a feasible schedule if one exists and always produces a correct schedule even when dropped frames are unavoidable. We analytically bound the gap between the energy saving resulting from our algorithm and the optimal energy saving and show that our results are close to optimal. We analyze the tradeoff between the fine control over bandwidth allocation and energy saving and demonstrate that in practical situations, flexible and finer control of bandwidth allocation will result in significantly lower frame loss rates while achieving higher energy saving. We have implemented the proposed algorithm as well as two other recent algorithms in a mobile video streaming testbed. Our extensive analysis and results demonstrate that the proposed algorithm outperforms the other two algorithms; it results in higher energy saving for mobile devices and fewer dropped video frames.


A Proposal of the AdaBoost-Based Detection of


title: Discovering Browser Extensions via Web Accessible Resources

abstract: Browser extensions provide a powerful platform to enrich browsing experience. At the same time, they raise important security questions. From the point of view of a website, some browser extensions are invasive, removing intended features and adding unintended ones, e.g. extensions that hijack Facebook likes. Conversely, from the point of view of extensions, some websites are invasive, e.g. websites that bypass ad blockers. Motivated by security goals at clash, this paper explores browser extension discovery, through a non-behavioral technique, based on detecting extensions' web accessible resources. We report on an empirical study with free Chrome and Firefox extensions, being able to detect over 50% of the top 1,000 free Chrome extensions, including popular security- and privacy-critical extensions such as AdBlock, LastPass, Avast Online Security, and Ghostery. We also conduct an empirical study of non-behavioral extension detection on the Alexa top 100,000 websites. We present the dual measures of making extension detection easier in the interest of websites and making extension detection more difficult in the interest of extensions. Finally, we discuss a browser architecture that allows a user to take control in arbitrating the conflicting security goals.


title: Distributed Storage Allocations for Optimal Delay

abstract: We examine the problem of creating an encoded distributed storage representation of a data object for a network of mobile storage nodes so as to achieve the optimal recovery delay. A source node creates a single data object and disseminates an encoded representation of it to other nodes for storage, subject to a given total storage budget. A data collector node subsequently attempts to recover the original data object by contacting other nodes and accessing the data stored in them. By using an appropriate code, successful recovery is achieved when the total amount of data accessed is at least the size of the original data object. The goal is to find an allocation of the given budget over the nodes that optimizes the recovery delay incurred by the data collector; two objectives are considered: (i) maximization of the probability of successful recovery by a given deadline, and (ii) minimization of the expected recovery delay. We solve the problem completely for the second objective in the case of symmetric allocations (in which all nonempty nodes store the same amount of data), and show that the optimal symmetric allocation for the two objectives can be quite different. A simple data dissemination and storage protocol for a mobile delay-tolerant network is evaluated under various scenarios via simulations. Our results show that the choice of storage allocation can have a significant impact on the recovery delay performance, and that coding may or may not be beneficial depending on the circumstances.


title: Copy-move forgery detection based on scaled ORB

abstract: To solve the problem of the false matching and low robustness in detecting copy-move forgeries, a new method was proposed in this study. It involves the following steps: first, establish a Gaussian scale space; second, extract the orientated FAST key points and the ORB features in each scale space; thirdly, revert the coordinates of the orientated FAST key points to the original image and match the ORB features between every two different key points using the hamming distance; finally, remove the false matched key points using the RANSAC algorithm and then detect the resulting copy-move regions. The experimental results indicate that the new algorithm is effective for geometric transformation, such as scaling and rotation, and exhibits high robustness even when an image is distorted by Gaussian blur, Gaussian white noise and JPEG recompression; the new algorithm even has great detection on the type of hiding object forgery.


title: Improving IT management at the BMW Group by integrating existing IT management processes

abstract: The management of IT landscapes consisting of thousands of business applications, different middleware systems, and supporting various business processes is a challenge for modern IT management. The BMW Group has addressed this challenge by establishing an integrated IT management process which covers strategy, architecture, planning and controlling. The BMW Group integrates the following preexisting IT processes in a continuous management process: "architecture and standardization" defines blueprints in terms of architectural patterns; "landscape management" maintains an overall model of the (present and future) IT landscape; "portfolio management" coordinates, evaluates and prioritizes action items with IT impact; "synchronization management" manages ongoing (IT) projects, their dependencies and the cross functions; "strategy and objectives" generates action items, defines guidelines for the other processes and adjusts strategies based on feedback from the other processes. This paper describes the problems that arise if such an integrated, continuous management process is lacking.


title: Consumed endurance: a metric to quantify arm fatigue of mid-air interactions

abstract: Mid-air interactions are prone to fatigue and lead to a feeling of heaviness in the upper limbs, a condition casually termed as the gorilla-arm effect. Designers have often associated limitations of their mid-air interactions with arm fatigue, but do not possess a quantitative method to assess and therefore mitigate it. In this paper we propose a novel metric, Consumed Endurance (CE), derived from the biomechanical structure of the upper arm and aimed at characterizing the gorilla-arm effect. We present a method to capture CE in a non-intrusive manner using an off-the-shelf camera-based skeleton tracking system, and demonstrate that CE correlates strongly with the Borg CR10 scale of perceived exertion. We show how designers can use CE as a complementary metric for evaluating existing and designing novel mid-air interactions, including tasks with repetitive input such as mid-air text-entry. Finally, we propose a series of guidelines for the design of fatigue-efficient mid-air interfaces.


title: Photo Aesthetics Ranking Network with Attributes and Content Adaptation

abstract: Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis have primarily focused on the coarse, binary categorization of images into high- or low-aesthetic categories. In this work, we propose to learn a deep convolutional neural network to rank photo aesthetics in which the relative ranking of photo aesthetics are directly modeled in the loss function. Our model incorporates joint learning of meaningful photographic attributes and image content information which can help regularize the complicated photo aesthetics rating problem.


title: Comparing Cortical Plasticity Induced by Conventional and High-Definition 4 × 1 Ring tDCS: A Neurophysiological Study

abstract: Abstract Background Transcranial direct current stimulation (tDCS) induces long-lasting NMDA receptor-dependent cortical plasticity via persistent subthreshold polarization of neuronal membranes. Conventional bipolar tDCS is applied with two large (35 cm 2 ) rectangular electrodes, resulting in directional modulation of neuronal excitability. Recently a newly designed 4 × 1 high-definition (HD) tDCS protocol was proposed for more focal stimulation according to the results of computational modeling. HD tDCS utilizes small disc electrodes deployed in 4 × 1 ring configuration whereby the physiological effects of the induced electric field are thought to be grossly constrained to the cortical area circumscribed by the ring. Objective We aim to compare the physiological effects of both tDCS electrode arrangements on motor cortex excitability. Methods tDCS was applied with 2 mA for 10 min. Fourteen healthy subjects participated, and motor cortex excitability was monitored by transcranial magnetic stimulation (TMS) before and after tDCS. Results Excitability enhancement following anodal and a respective reduction after cathodal stimulation occurred in both, conventional and HD tDCS. However, the plastic changes showed a more delayed peak at 30 min and longer lasting after-effects for more than 2 h after HD tDCS for both polarities, as compared to conventional tDCS. Conclusion The results show that this new electrode arrangement is efficient for the induction of neuroplasticity in the primary motor cortex. The pattern of aftereffects might be compatible with the concept of GABA-mediated surround inhibition, which should be explored in future studies directly.


title: Term frequency with average term occurrences for textual information retrieval

abstract: In the context of information retrieval (IR) from text documents, the term weighting scheme (TWS) is a key component of the matching mechanism when using the vector space model. In this paper, we propose a new TWS that is based on computing the average term occurrences of terms in documents and it also uses a discriminative approach based on the document centroid vector to remove less significant weights from the documents. We call our approach Term Frequency With Average Term Occurrence (TF-ATO). An analysis of commonly used document collections shows that test collections are not fully judged as achieving that is expensive and maybe infeasible for large collections. A document collection being fully judged means that every document in the collection acts as a relevant document to a specific query or a group of queries. The discriminative approach used in our proposed approach is a heuristic method for improving the IR effectiveness and performance and it has the advantage of not requiring previous knowledge about relevance judgements. We compare the performance of the proposed TF-ATO to the well-known TF-IDF approach and show that using TF-ATO results in better effectiveness in both static and dynamic document collections. In addition, this paper investigates the impact that stop-words removal and our discriminative approach have on TF-IDF and TF-ATO. The results show that both, stop-words removal and the discriminative approach, have a positive effect on both term-weighting schemes. More importantly, it is shown that using the proposed discriminative approach is beneficial for improving IR effectiveness and performance with no information on the relevance judgement for the collection.


title: A userstudy of visualization effectiveness using EEG and cognitive load. Computer Graphics Forum 30

abstract: Effectively evaluating visualization techniques is a difficult task often assessed through feedback from user studies and expert evaluations. This work presents an alternative approach to visualization evaluation in which brain activity is passively recorded using electroencephalography (EEG). These measurements are used to compare different visualization techniques in terms of the burden they place on a viewer's cognitive resources. In this paper, EEG signals and response times are recorded while users interpret different representations of data distributions. This information is processed to provide insight into the cognitive load imposed on the viewer. This paper describes the design of the user study performed, the extraction of cognitive load measures from EEG data, and how those measures are used to quantitatively evaluate the effectiveness of visualizations.


title: Design and Performance Evaluation of Image Processing Algorithms on GPUs

abstract: In this paper, we construe key factors in design and evaluation of image processing algorithms on the massive parallel graphics processing units (GPUs) using the compute unified device architecture (CUDA) programming model. A set of metrics, customized for image processing, is proposed to quantitatively evaluate algorithm characteristics. In addition, we show that a range of image processing algorithms map readily to CUDA using multiview stereo matching, linear feature extraction, JPEG2000 image encoding, and nonphotorealistic rendering (NPR) as our example applications. The algorithms are carefully selected from major domains of image processing, so they inherently contain a variety of subalgorithms with diverse characteristics when implemented on the GPU. Performance is evaluated in terms of execution time and is compared to the fastest host-only version implemented using OpenMP. It is shown that the observed speedup varies extensively depending on the characteristics of each algorithm. Intensive analysis is conducted to show the appropriateness of the proposed metrics in predicting the effectiveness of an application for parallel implementation.


title: Learning Profiles in Duplicate Question Detection

abstract: This paper presents the results of systematic and comparative experimentation with major types of methodologies for automatic duplicate question detection when these are applied to datasets of progressively larger sizes, thus allowing to study the learning profiles of this task under these different approaches and evaluate their merits. This study was made possible by resorting to the recent release for research purposes, by the Quora online question answering engine, of a new dataset with over 400,000 pairs labeled with respect to their elements being duplicate interrogative segments.


title: Management and Education of the Risk of Insider Threat ( MERIT ) : System Dynamics Modeling of Computer System Sabotage

abstract: Abstract : The Insider Threat Study, conducted by the U.S. Secret Service and Carnegie Mellon University's Software Engineering Institute CERT Program, analyzed insider cyber crimes across U.S. critical infrastructure sectors. The study indicates that management decisions related to organizational and employee performance sometimes yield unintended consequences magnifying risk of insider attack. Lack of tools for understanding insider threat, analyzing risk mitigation alternatives, and communicating results exacerbates the problem. The goal of Carnegie Mellon University's MERIT (Management and Education of the Risk of Insider Threat) project is to develop such tools.4 MERIT uses system dynamics to model and analyze insider threats and produce interactive learning environments. These tools can be used by policy makers, security officers, information technology, human resources, and management to understand the problem and assess risk from insiders based on simulations of policies, cultural, technical, and procedural factors. This paper describes the MERIT insider threat model and simulation results.


title: Prostaglandin E2 selectively increases interferon gamma receptor expression on human CD8+ lymphocytes.

abstract: We previously reported that prostaglandin E2 (PGE2) at a physiologic concentration (10(-8) M) and interferon gamma (IFN gamma), acting sequentially, were required for the differentiation of suppressor cells in mitogen-stimulated cultures. The present study was designed to test whether PGE2 might mediate IFN gamma-dependent effects on CD8+ cells by altering the number and/or affinity of their IFN gamma receptors. CD8+ and CD4+ cells when cultured for 18 h expressed comparable numbers of IFN gamma receptors of a single high affinity. Incubation with 10(-8) M PGE2 for 18 h, however, increased the number of IFN gamma receptors on CD8+ cells without affecting the binding affinity. Similar effects were not observed with CD4+ cells, nor when CD8+ cells were cultured in 10(-8) M PGD2. Concentrations of PGE2, which were ineffective in the induction of IFN gamma-dependent suppressor cell differentiation, also did not affect IFN gamma receptor expression on CD8+ cells. This observation of a specific stimulatory effect of PGE2 on the display of IFN gamma receptors of CD8+ cells suggests a novel mechanism for eicosanoid function through tissue-specific regulation of hormone receptors.


1 Experiments with Unit Selection Speech Databases for Indian Languages


title: Consumer Attitude towards Cosmetic Products

abstract: The world wide annual expenditures for cosmetics is estimated at U.S.$18 billion, and many players in the field are competing aggressively to capture more and more market. Hence, companies are interested to know about consumer’s attitude towards cosmetics so as to devise strategies to win over competition. The main purpose of this article is to investigate the influence of attitude on cosmetics buying behaviour. The research question is “what kind of attitudes do the customers have towards buying behaviour of cosmetic products?” A questionnaire was developed and distributed to female consumers in Bangalore city by using convenience sampling method. 118 completed questionnaires were returned and then 100 valid were analyzed by using ANOVA, mean and standard deviation. The result of the study confirms that age, occupation, marital status have positive influence towards cosmetic products. But income does not have any influence on the attitude towards cosmetic products.


title: Open information extraction based on lexical semantics

abstract: Open Information Extraction (Open IE) aims to obtain not predefined, domain-independent relations from text. This article introduces the Open IE research field, thoroughly discussing the main ideas and systems in the area as well as its main challenges and open issues. The paper describes an open extractor elaborated from the belief that it is not necessary to have an enormous list of patterns or several types of linguistic labels to better perform Open IE. The extractor is based on generic patterns that identify relations not previously specified, including rules corresponding to Cimiano and Wenderoth proposal to learn Qualia structure. Named LSOE (Lexical-Syntactic pattern-based Open Extractor) and designed to validate such strategy, this extractor is presented and its performance is compared with two Open IE systems. The results demonstrate that LSOE extracts relations that are not learned by other extractors and achieves compatible precision. The work reported here contributes with a new Open IE approach based on pattern matching, demonstrating the feasibility of an extractor based on simple lexical-syntactic patterns.


title: Latent Fingerprint Enhancement via Multi-Scale Patch Based Sparse Representation

abstract: Latent fingerprint identification plays an important role for identifying and convicting criminals in law enforcement agencies. Latent fingerprint images are usually of poor quality with unclear ridge structure and various overlapping patterns. Although significant advances have been achieved on developing automated fingerprint identification system, it is still challenging to achieve reliable feature extraction and identification for latent fingerprints due to the poor image quality. Prior to feature extraction, fingerprint enhancement is necessary to suppress various noises, and improve the clarity of ridge structures in latent fingerprints. Motivated by the recent success of sparse representation in image denoising, this paper proposes a latent fingerprint enhancement algorithm by combining the total variation model and multiscale patch-based sparse representation. First, the total variation model is applied to decompose the latent fingerprint into cartoon and texture components. The cartoon component with most of the nonfingerprint patterns is removed as the structured noise, whereas the texture component consisting of the weak latent fingerprint is enhanced in the next stage. Second, we propose a multiscale patch-based sparse representation method for the enhancement of the texture component. Dictionaries are constructed with a set of Gabor elementary functions to capture the characteristics of fingerprint ridge structure, and multiscale patch-based sparse representation is iteratively applied to reconstruct high-quality fingerprint image. The proposed algorithm cannot only remove the overlapping structured noises, but also restore and enhance the corrupted ridge structures. In addition, we present an automatic method to segment the foreground of latent image with the sparse coefficients and orientation coherence. Experimental results and comparisons on NIST SD27 latent fingerprint database are presented to show the effectiveness of the proposed algorithm and its superiority over existing algorithms.


title: Automatic search for related-key differential characteristics in byte-oriented block ciphers: application to AES, Camellia, Khazad and others

abstract: While differential behavior of modern ciphers in a single secret key scenario is relatively well understood, and simple techniques for computation of security lower bounds are readily available, the security of modern block ciphers against related-key attacks is still very ad hoc. In this paper we make a first step towards provable security of block ciphers against related-key attacks by presenting an efficient search tool for finding differential characteristics both in the state and in the key (note that due to similarities between block ciphers and hash functions such tool will be useful in analysis of hash functions as well). We use this tool to search for the best possible (in terms of the number of rounds) related-key differential characteristics in AES, byte-Camellia, Khazad, FOX, and Anubis. We show the best related-key differential characteristics for 5, 11, and 14 rounds of AES-128, AES-192, and AES-256 respectively. We use the optimal differential characteristics to design the best related-key and chosen key attacks on AES-128 (7 out of 10 rounds), AES-192 (full 12 rounds), byte-Camellia (full 18 rounds) and Khazad (7 and 8 out of 8 rounds). We also show that ciphers FOX and Anubis have no related-key attacks on more than 4-5 rounds.


title: A compact 110 kVA, 140°C ambient, 105°C liquid cooled, all-SiC inverter for electric vehicle traction drives

abstract: Wide bandgap materials are having a transformational impact on the electrical, thermal, and mechanical performance of military, industrial, and commercial power electronic systems where silicon (Si) power semiconductors are the present material technology of choice. This paper reports on the design, analysis, and experimental verification of a compact allsilicon carbide (SiC)-based inverter to meet the inhospitable environmental demands of hybrid, plug-in hybrid, extended-range electrified vehicles, and fuel cell vehicle architectures. The compact 4.8 L, 6.6 kg inverter achieves a volumetric and gravimetric power density of 23.1 kVA/L and 16.8 kVA/kg, respectively. Three 1200 V, 3.6 mΩ, half-bridge power modules, each containing seven 25 mΩ SiC MOSFETs and six 50 A Schottky barrier diodes (SBDs) per switch position, comprise the power stage. Significant improvement in conduction, switching, and reverse-recovery losses allowed this SiC MOSFET-based inverter to achieve 96.3% average efficiency and 98.9% average peak efficiency over all experiments. This is superior to Si IGBT-based inverters throughout the entire range of torques, speeds, and bus voltages — and especially at light load operating points typical of electric vehicles. Dynamometer experiments used a 20 kHz switching frequency, double-update space-vector modulation, thermal controls for ambient and coolant temperatures, custom data acquisition, and a commercial three-phase power meter to collect performance data over 500 to 6000 RPM, 5 to 180 N-m, four bus voltages, and six thermal cases.


title: Current practice of waste management system in Malaysia: towards sustainable waste management

abstract: Nowadays, the increasing quantity of municipal solid waste has causes serious environmental problem which requires a better solution in handling the wastes that generate. Construction waste is considered as part of the municipal solid waste. Construction wastes that produce in the construction process contributes a large amount to municipal solid waste. For that reason, a proper way of handling construction wastes is significance in reducing the negative impacts towards the environment, social, and economy. Sustainable waste management is introduced to maintain the balance between the environment, social and economic aspects through several ways such as acts implementation, and techniques in managing waste. Therefore, it is essential to identify current waste management system adopted by industry in order to make adjustment and improvement in moving towards sustainable waste management. This paper highlights the current waste management system implemented in Malaysia and the challenges in applying the concept of sustainability into waste management through reviewing past similar researches. This research has conducted an exploratory interview to six industry practitioners in both private and government sector in Malaysia. The results obtained show the current waste management systems applied in Malaysia and factors that hinder the concept of sustainability into waste management. It allows a major shift in Malaysia waste management by improvise current waste management technology into more sustainable way.


title: Characterization of hydrometeor scattering effects and experimental measurements using near-infrared free-space urban links

abstract: The improvements of the instrumentation available within the free space optics (FSO) link set up in the Roman area (Italy) is illustrated together with FSO channel physical modelling activity. The wireless optical link at 1550 nm is 1.650 km long and has a transmission rate up to 1.5 Gbps. This link is intended to be, in the next future, the trunk sector of a convergent passive optical network (G-PON). Among particle scattering effects affecting the capacity of the optical channel, a focus is placed on raindrop and fog droplets. An evaluation of these atmospheric effects is illustrated and a comparison with measurements is carried out for some case studies of moderate and heavy rainfall. This becomes fundamental to evaluate the feasibility of such an approach in real telecommunications access scenarios, where the quality of service (QoS) and the quality of experience (QoE) must be always guaranteed.


title: Functional Capacity of Children with Leukemia

abstract: The purpose of this study was to determine if the functional capacity and quality of life of children receiving treatment against acute lymphoblastic leukemia (ALL) is decreased compared to healthy age and gender-matched children. Functional capacity was assessed with a number of measurements as the peak oxygen uptake (V·O 2peak ) and ventilatory threshold determined during a ramp treadmill test, functional mobility (Timed Up and Down Stairs test [TUDS]) and ankle dorsiflexion passive and active range of motion (passive and active DF-ROM, respectively). Quality of life (QOL) was determined with the Spanish version of the Child Report Form of the Child Health and Illness Profile-Child Edition (CHIP-CE/CRF). Fifteen children (9 boys, 6 girls; mean [SD] age: 6.8 ± 3.1 years) receiving maintenance therapy against ALL were studied and fifteen, nonathletic healthy children (9 boys, 6 girls; 6.9 ± 3.3 years) were selected as controls. The mean values of V·O 2peak and active DF-ROM were significantly (p < 0.05) lower in patients (25.3 ± 6.5 ml · kg -1 · min -1 vs. 31.9 ± 6.8 ml · kg -1 · min -1 in controls and 19.6 ± 8.0° vs. 24.1 ± 5.0°, respectively). Children's self report of satisfaction (with self and health) (p < 0.05), comfort (concerning emotional and physical symptoms and limitations) (p < 0.01) and resilience (positive activities that promote health) (p < 0.01) were significantly decreased in patients with ALL. In summary, children receiving treatment against ALL have overall lower functional capacity and QOL than healthy children. However, their physical condition and health status are sufficiently high to allow them to participate in physical activities and supervised exercise programs.


title: Risk of recurarization during retransfusion of autologous blood withdrawn after injection of muscle relaxants: a comparison of rocuronium and mivacurium.

abstract: STUDY OBJECTIVES ::: In the context of acute normovolemic hemodilution (ANH) recurarization, defined as significant decrease of train-of-four ratio (TOFR) during retransfusion of autologous blood withdrawn after induction of anesthesia, has been described for vecuronium and atracurium. The present study for the first time examined this risk for rocuronium and mivacurium. ::: ::: ::: DESIGN ::: Prospective, randomized, unblinded clinical study. ::: ::: ::: SETTING ::: University Hospital in Zurich/Switzerland. ::: ::: ::: PATIENTS ::: 20 ASA physical status I and II patients undergoing general anesthesia for major maxillofacial surgery. ::: ::: ::: INTERVENTIONS ::: Anesthesia was induced and maintained with propofol and remifentanil, and rocuronium (0.9 mg kg(-1)) or mivacurium (0.25 mg kg(-1)) was given to facilitate intubation. Thereafter, ANH was started with the removal of 500 mL autologous blood and the subsequent replacement by the same amount of 6% hydroxyethyl starch. The withdrawn blood was stored at 4 degrees C until retransfusion at the end of surgery. ::: ::: ::: MEASUREMENTS ::: To estimate the risk of recurarization during retransfusion, the degree of recurarization during retransfusion of the autologous blood was assessed mechanomyographically. Plasma levels of rocuronium and mivacurium in the patients' plasma and the autologous blood were determined after its removal and before retransfusion. ::: ::: ::: MAIN RESULTS ::: The TOFR before retransfusion was 0.97 (range: 0.96 to 0.98) for rocuronium (n = 10) and 0.98 (range: 0.96 to 1.0) for mivacurium (n = 8); n.s. During retransfusion, a slight, but statistically significant reduction of TOFR occurred in one patient in each group. In the mivacurium group, this recurarization occurred 10 minutes after the start of retransfusion; in the rocuronium group, it occurred 20 minutes after retransfusion. The plasma levels of rocuronium and mivacurium in the autologous blood did not change during storage. The plasma concentration of mivacurium in the autologous blood after its removal was 420 +/- 142 microg/L; before retransfusion, it was 384 +/- 147 microg/L. The respective concentrations for rocuronium were 2930 +/- 516 microg/L and 2660 +/- 464 microg/L. ::: ::: ::: CONCLUSIONS ::: Recurarization during retransfusion may occur with both neuromuscular blocking drugs, mivacurium and rocuronium, when these drugs were injected before the removal of the autologous blood.


title: YACCLAB - Yet Another Connected Components Labeling Benchmark

abstract: The problem of labeling the connected components (CCL) of a binary image is well-defined and several proposals have been presented in the past. Since an exact solution to the problem exists and should be mandatory provided as output, algorithms mainly differ on their execution speed. In this paper, we propose and describe YACCLAB, Yet Another Connected Components Labeling Benchmark. Together with a rich and varied dataset, YACCLAB contains an open source platform to test new proposals and to compare them with publicly available competitors. Textual and graphical outputs are automatically generated for three kinds of test, which analyze the methods from different perspectives. The fairness of the comparisons is guaranteed by running on the same system and over the same datasets. Examples of usage and the corresponding comparisons among state-of-the-art techniques are reported to confirm the potentiality of the benchmark.


title: MRI of progressive supranuclear palsy, corticobasal degeneration and multiple system atrophy

abstract: ■ Abstract The characteristics of progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and multiple system atrophy (MSA) on routine magnetic resonance imaging (MRI) are reviewed. In PSP, atrophy of the midbrain tegmentum, truncus of corpus callosum and anterior cingulate cortex was seen on midsagittal plane MRI. These findings probably relate to supranuclear gaze palsy, motor programming dysfunction and emotional dysfunction. In CBD, asymmetric frontoparietal atrophy is usually seen, which could be the basis of focal signs. In MSA, putaminal and pontine involvements are represented by the hyperintense rim and,hot-cross bun' signs on MRI. These would be closely linked via the premotor and motor cortex, which supervise motor execution. MRI findings mirror the clinical signs and symptoms in atypical parkinsonism.


title: Ant colony optimization based enhanced dynamic source routing algorithm for mobile Ad-hoc network

abstract: Due to the dynamic nature of the Mobile Ad-hoc Network (MANET), routing in MANET becomes challenging especially when certain QoS requirements (like high data packet delivery ratio, low end to end delay, low routing overhead, and low energy consumption) are to be satisfied. Though a number of routing protocols have been proposed aiming to fulfill some of these QoS requirements but none of them can support all these requirements at the same time. In this paper, we propose an enhanced version of the well-known Dynamic Source Routing (DSR) scheme based on the Ant Colony Optimization (ACO) algorithm, which can produce a high data packet delivery ratio in low end to end delay with low routing overhead and low energy consumption. In our scheme, when a node needs to send a packet to another node, like DSR, it first checks the cache for existing routes. When no routes are known, the sender node locally broadcasts the Route Request control packets (called the Req.Ant packets) to find out the routes. This is similar to the biological ants initially spreading out in all directions from their colony in search of food. Now, the ants, after finding the food source, come back to the colony and deposit pheromone on their way so that other ants get informed about the paths. Similarly, in our routing scheme, the Req.Ant packets propagate through the network according to our novel route discovery scheme and gathers information of the route (i.e. total length of the route, congestion along the route and end to end path reliability of the route), till it reaches the destination node. When the destination node receives a Req.Ant packet, it sends back Rep.Ant (Route Reply control packet) which consists the route information of the corresponding Req.Ant to the source node through the same route. On receiving such Rep.Ant packets from different routes, the source node comes to know about those routes. Under the ant colony framework, the best route is selected by the pheromone level of the route. Similarly, here we calculate the pheromone level of a route based on the number of hops in the route, the congestion along the route and end to end path reliability of the route.The route with the highest pheromone count will be selected for data packet delivery. We also propose a novel pheromone decay technique for route maintenance. The simulation results show that our ACO based Enhanced DSR (E-Ant-DSR) outperforms the original DSR and other ACO based routing algorithms.


title: A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization

abstract: In modern data science problems, techniques for extracting value from big data require performing large-scale optimization over heterogenous, irregularly structured data. Much of this data is best represented as multi-relational graphs, making vertex-programming abstractions such as those of Pregel and GraphLab ideal fits for modern large-scale data analysis. In this paper, we describe a vertex-programming implementation of a popular consensus optimization technique known as the alternating direction method of multipliers (ADMM) [1]. ADMM consensus optimization allows the elegant solution of complex objectives such as inference in rich probabilistic models. We also introduce a novel hypergraph partitioning technique that improves over the state-of-the-art vertex programming framework and significantly reduces the communication cost by reducing the number of replicated nodes by an order of magnitude. We implement our algorithm in GraphLab and measure scaling performance on a variety of realistic bipartite graphs and a large synthetic voter-opinion analysis application. We show a 50% improvement in running time over the current GraphLab partitioning scheme.


title: A hardware Gaussian noise generator for channel code evaluation

abstract: Hardware simulation of channel codes offers the potential of improving code evaluation speed by orders of magnitude over workstation of PC-based simulation. We describe a hardware-based Gaussian noise generator used as a key component in a hardware simulation system, for exploring channel code behavior at very low bit error rates (BERs) in the range of 10/sup -9/ to 10/sup -10/. The main novelty is the design and use of nonuniform piecewise linear approximations in computing trigonometric and logarithmic functions. The parameters of the approximation are chosen carefully to enable rapid computation of coefficients from the inputs, while still retaining extremely high fidelity to the modeled functions. The output of the noise generator accurately models a true Gaussian PDF even at very high /spl sigma/ values. Its properties are explored using: (a) several different statistical tests, including the chi-square test and the Kolmogorov-Smirnov test, and (b) an application for decoding of low density parity check (LDPC) codes. An implementation at 133MHz on a Xilinx Virtex-II XC2V4000-6 FPGA produces 133 million samples per second, which is 40 times faster than a 2.13GHz PC; another implementation on a Xilinx Spartan-IIE XC2S300E-7 FPGA at 62MHz is capable of a 20 times speedup. The performance can be improved by exploiting parallelism: an XC2V4000-6 FPGA with three parallel instances of the noise generator at 126 MHz can run 100 times faster than a 2.13GHz PC. We illustrate the deterioration of clock speed with the increase in the number of instances.


title: Enhanced K Strange Points Clustering Algorithm

abstract: The algorithm proposed in this paper enhances the K Strange points clustering algorithm by selecting the first of unchanging K strange points as the minimum of the dataset and then finds the next strange point as the point which is farthest from the minimum and continues this process till it finds the K points which are farthest and almost equally spaced from each other. It then assigns the remaining points in the dataset into clusters formed by these K farthest or Strange points. The algorithm presented in this paper successfully addresses the issues related to longer execution time and formation of inaccurate clusters seen in the K Strange points clustering algorithm.


title: Big Data Validation and Quality Assurance -- Issuses, Challenges, and Needs

abstract: With the fast advance of big data technology and analytics solutions, big data computing and service is becoming a very hot research and application subject in academic research, industry community, and government services. Nevertheless, there are increasing data quality problems resulting in erroneous data costs in enterprises and businesses. Current research seldom discusses how to effectively validate big data to ensure data quality. This paper provides informative discussions for big data validation and quality assurance, including the essential concepts, focuses, and validation process. Moreover, the paper presents a comparison among big data validation tools and several major players in industry are discussed. Furthermore, the primary issues, challenges, and needs are discussed.


title: Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)

abstract: Recommendation and review sites offer a wealth of information beyond ratings. For instance, on IMDb users leave reviews, commenting on different aspects of a movie (e.g. actors, plot, visual effects), and expressing their sentiments (positive or negative) on these aspects in their reviews. This suggests that uncovering aspects and sentiments will allow us to gain a better understanding of users, movies, and the process involved in generating ratings. The ability to answer questions such as "Does this user care more about the plot or about the special effects?" or "What is the quality of the movie in terms of acting?" helps us to understand why certain ratings are generated. This can be used to provide more meaningful recommendations. In this work we propose a probabilistic model based on collaborative filtering and topic modeling. It allows us to capture the interest distribution of users and the content distribution for movies; it provides a link between interest and relevance on a per-aspect basis and it allows us to differentiate between positive and negative sentiments on a per-aspect basis. Unlike prior work our approach is entirely unsupervised and does not require knowledge of the aspect specific ratings or genres for inference. We evaluate our model on a live copy crawled from IMDb. Our model offers superior performance by joint modeling. Moreover, we are able to address the cold start problem -- by utilizing the information inherent in reviews our model demonstrates improvement for new users and movies.


title: 16K Cinematic VR Streaming

abstract: We present an end-to-end system for streaming Cinematic Virtual Reality (VR) content (also called 360 or omnidirectional content). Content is captured and ingested at a resolution of 16K at 25Hz and streamed towards untethered mobile VR devices. Besides the usual navigation interactions such as panning and tilting offered by common VR systems, we also provide a zooming interactivity. This allows the VR client to fetch high quality pixels captured at a spatial resolution of 16K that greatly increase perceived quality compared to a 4K VR streaming solution. Since current client devices are not capable of receiving and decoding a 16K video, several optimizations are provided to only stream the required pixels for the current viewport of the user, while meeting strict latency and bandwidth requirements for a qualitative VR immersive experience.


title: One-handed gesture recognition using ultrasonic Doppler sonar

abstract: This paper presents a new device based on ultrasonic sensors to recognize one-handed gestures. The device uses three ultrasonic receivers and a single transmitter. Gestures are characterized through the Doppler frequency shifts they generate in reflections of an ultrasonic tone emitted by the transmitter. We show that this setup can be used to classify simple one-handed gestures with high accuracy. The ultrasonic doppler based device is very inexpensive - $20 USD for the whole setup including the acquisition system, and computationally efficient as compared to most traditional devices (e.g. video). These gestures, could potentially be used to control and drive a device.


title: Real-Time Long-Range Lane Detection and Tracking for Intelligent Vehicle

abstract: This paper presents a real-time long-range lane detection and tracking approach to meet the requirements of the high-speed intelligent vehicles running on highway roads. Based on a linear-parabolic two-lane highway road model and a novel strong lane marking feature named Lane Marking Segmentation, the maximal lane detection distance of this approach is up to 120 meters. Then the lane lines are selected and tracked by estimating the ego vehicle lateral offset with a Kalman filter. Experiment results with test dataset extracted from real traffic scenes on highway roads show that the approaches proposed in this paper can achieve a high detection rate with a low time cost.


title: Quantitative Classification of Near-Fault Ground Motions Using Wavelet Analysis

abstract: A method is described for quantitatively identifying ground motions containing strong velocity pulses, such as those caused by near-fault directivity. The approach uses wavelet analysis to extract the largest velocity pulse from a given ground motion. The size of the extracted pulse relative to the original ground motion is used to develop a quantitative criterion for classifying a ground motion as “pulselike.” The criterion is calibrated by using a training data set of manually classified ground motions. To identify the subset of these pulselike records of greatest engineering interest, two additional criteria are applied: the pulse arrives early in the ground motion and the absolute amplitude of the velocity pulse is large. The period of the velocity pulse (a quantity of interest to engineers) is easily determined as part of the procedure, using the pseudoperiods of the basis wavelets. This classification approach is useful for a variety of seismology and engineering topics where pulselike ground motions are of interest, such as probabilistic seismic hazard analysis, ground- motion prediction (“attenuation”) models, and nonlinear dynamic analysis of structures. The Next Generation Attenuation (nga) project ground motion library was processed using this approach, and 91 large-velocity pulses were found in the fault- normal components of the approximately 3500 strong ground motion recordings considered. It is believed that many of the identified pulses are caused by near-fault directivity effects. The procedure can be used as a stand-alone classification criterion or as a filter to identify ground motions deserving more careful study.


title: Quantitative Genomics of Aggressive Behavior in Drosophila melanogaster

abstract: Aggressive behavior is important for animal survival and reproduction, and excessive aggression is an enormous social and economic burden for human society. Although the role of biogenic amines in modulating aggressive behavior is well characterized, other genetic mechanisms affecting this complex behavior remain elusive. Here, we developed an assay to rapidly quantify aggressive behavior in Drosophila melanogaster, and generated replicate selection lines with divergent levels of aggression. The realized heritability of aggressive behavior was approximately 0.10, and the phenotypic response to selection specifically affected aggression. We used whole-genome expression analysis to identify 1,539 probe sets with different expression levels between the selection lines when pooled across replicates, at a false discovery rate of 0.001. We quantified the aggressive behavior of 19 mutations in candidate genes that were generated in a common co-isogenic background, and identified 15 novel genes affecting aggressive behavior. Expression profiling of genetically divergent lines is an effective strategy for identifying genes affecting complex traits. Citation: Edwards AC, Rollmann SM, Morgan TJ, Mackay TFC (2006) Quantitative genomics of aggressive behavior in Drosophila melanogaster. PLoS Genet 2(9): e154. DOI: 10. 1371/journal.pgen.0020154


title: Monte Carlo Tree Search for games with Hidden Information and Uncertainty

abstract: Monte Carlo Tree Search (MCTS) is an AI technique ::: that has been successfully applied to many deterministic games ::: of perfect information, leading to large advances in a number of domains, ::: such as Go and General Game Playing. ::: Imperfect information games are less well studied in the field of AI ::: despite being popular and of significant commercial interest, ::: for example in the case of computer and mobile adaptations of turn based board and card games. ::: This is largely because hidden information and uncertainty ::: leads to a large increase in complexity compared to perfect information games. ::: ::: In this thesis MCTS is extended to games with hidden information and uncertainty ::: through the introduction of the Information Set MCTS (ISMCTS) family of algorithms. ::: It is demonstrated that ISMCTS can handle hidden information and uncertainty ::: in a variety of complex board and card games. ::: This is achieved whilst preserving the general applicability of MCTS ::: and using computational budgets appropriate for use in a commercial game. ::: The ISMCTS algorithm is shown to outperform the existing approach of Perfect Information Monte Carlo (PIMC) search. ::: Additionally it is shown that ISMCTS can be used to solve two known issues with PIMC search, ::: namely strategy fusion and non-locality. ::: ISMCTS has been integrated into a commercial game, Spades by AI Factory, ::: with over 2.5 million downloads. ::: ::: The Information Capture And ReUSe (ICARUS) framework is also introduced in this thesis. ::: The ICARUS framework generalises MCTS enhancements in terms of information capture (from MCTS simulations) ::: and reuse (to improve MCTS tree and simulation policies). ::: The ICARUS framework is used to express existing enhancements, ::: to provide a tool to design new ones, ::: and to rigorously define how MCTS enhancements can be combined. ::: The ICARUS framework is tested across a wide variety of games.


title: A Survey of Using Vocal Prosody to Convey Emotion in Robot Speech

abstract: The use of speech for robots to communicate with their human users has been facilitated by improvements in speech synthesis technology. Now that the intelligibility of synthetic speech has advanced to the point that speech synthesizers are a widely accepted and used technology, what are other aspects of speech synthesis that can be used to improve the quality of human-robot interaction? The communication of emotions through changes in vocal prosody is one way to make synthesized speech sound more natural. This article reviews the use of vocal prosody to convey emotions between humans, the use of vocal prosody by agents and avatars to convey emotions to their human users, and previous work within the human–robot interaction (HRI) community addressing the use of vocal prosody in robot speech. The goals of this article are (1) to highlight the ability and importance of using vocal prosody to convey emotions within robot speech and (2) to identify experimental design issues when using emotional robot speech in user studies.


PROC OF THE IEEE NOVEMBER Gradient Based Learning Applied to Document Recognition


title: WISER: A Semantic Approach for Expert Finding in Academia based on Entity Linking

abstract: Abstract We present Wiser , a new semantic search engine for expert finding in academia. Our system is unsupervised and it jointly combines classical language modeling techniques, based on text evidences, with the Wikipedia Knowledge Graph, via entity linking. Wiser indexes each academic author through a novel profiling technique which models her expertise with a small, labeled and weighted graph drawn from Wikipedia. Nodes in this graph are the Wikipedia entities mentioned in the author’s publications, whereas the weighted edges express the semantic relatedness among these entities computed via textual and graph-based relatedness functions. Every node is also labeled with a relevance score which models the pertinence of the corresponding entity to author’s expertise, and is computed by means of a proper random-walk calculation over that graph; and with a latent vector representation which is learned via entity and other kinds of structural embeddings derived from Wikipedia. At query time, experts are retrieved by combining classic document-centric approaches, which exploit the occurrences of query terms in the author’s documents, with a novel set of profile-centric scoring strategies, which compute the semantic relatedness between the author’s expertise and the query topic via the above graph-based profiles. The effectiveness of our system is established over a large-scale experimental test on a standard dataset for this task. We show that Wiser achieves better performance than all the other competitors, thus proving the effectiveness of modeling author’s profile via our “semantic” graph of entities. Finally, we comment on the use of Wiser for indexing and profiling the whole research community within the University of Pisa, and its application to technology transfer in our University.


title: Pattern-Reconfigurable Unidirectional Dipole Antenna Array Fed by SIW Coupler for Millimeter Wave Application

abstract: A directional two-element mm-wave dipole antenna array with reconfigurable patterns is presented in this paper. An substrate integrated waveguide (SIW) 90° coupler is used to realize reconfigurable patterns of the antenna array. The two dipole elements are parallel in space, and there is a distance of $\lambda _{0}$ /4 ( $\lambda _{0}$ is the wavelength of the free space) between them. When the two inputs of the 90° coupler are excited, respectively, two completely opposite radiation patterns are able to be achieved. In order to further enhance the directivity of the proposed antenna, two groups of novel zero-index metamaterials and three metallic strips are introduced. As a consequence, a 0.7–1.2 dBi gain enhancement and reduced back lobe are obtained within the working frequencies. The measured amplitudes of S11 and S22 are below −10 dB from 45.5 to 49.5 GHz, and the measured gain is all great than 5 dBi within this band.


title: Driver assist system for human–machine interaction

abstract: A haptic driver–vehicle steering interface is introduced that interacts with the driver through environmentally mediated torque and stiffness changes, thereby communicating the vehicle’s proximity to constraints in the driving environment. The system design is based on principles of distributed cognition, which are used to shape the force characteristics to provide the driver with a tangible, rich, distributed representation of the task constraints. This mapping of the task constraints aids the human operator in satisfying a variety of needs, including managing risk, maintaining contextual awareness and achieving a satisfactory level of performance. The proposed design philosophy was applied to implement a haptic steering system in a real-world test vehicle to assist drivers in navigating through an experimental course with tight passages. In tests conducted with 12 participants, not only did most drivers show improved performance, but activities identified as epistemic behaviors were also observed; in the context of driving, epistemic behaviors are actions through which a driver probes the environment to maintain contextual awareness for the purpose of actively maintaining a satisfactory balance between performance and risk. These findings indicate that the proposed system design allows humans to actively integrate the haptic interface system into their cognitive loops and that the resulting human–machine system achieves higher performance than the human alone. The observed human–machine system interaction is interpreted as achieving improved resilience against variations in environmentally imposed risks.


H 5 Spark : Bridging the I / O Gap between Spark and Scientific Data Formats on HPC Systems


title: Phylogenetics of Vicia (Fabaceae) based on morphological data

abstract: The phylogenetic relationships among 67 Vicia species from Eurasia were studied in relation to Trifolium montanum on the basis of 91 morphological characters. The characters were coded as multistate, 17 were treated as ordered. In subgenus Vicia, V. sepium and V. oroboides form a separate taxon, section Sepium, into which V. grandiflora should be included. Separation of V. lathyroides and V. cuspidata into a distinct section Lathyroides is supported. Placement of V. mollis into section Hypechusa is supported, however, treatment of V. hyrcanica and V. noeana in a separate taxon, series Hyrcanicae, is not supported and needs further study. Joining of V. faba to the Narbonensis group is well supported. In subgenus Cracca, sections Vicilla and Cassubicae appear monophyletic when V. amoena is moved from section Vicilla to section Cassubicae. Section Variegatae does not appear monophyletic, as V. argentea and V. canescens, although closely connected, belong to section Cracca. ::: ::: The present analysis supports separation of the Ervoid group (V. tetrasperma, V. tenuissima, V. pubescens, and V. caesarea) into an independent subgenus, subgenus Ervum; the position of V. hirsuta remains disputable. Therefore, division of Vicia into three subgenera is supported. (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)


title: Analyzing and labeling telecom communities using structural properties

abstract: Social network analysis and mining has been highly influenced by the online social web sites, telecom consumer data and instant messaging systems and has widely analyzed the presence of dense communities using graph theory and machine learning techniques. Mobile social network analysis is the mapping and measuring of interactions and flows between people, groups, and organizations based on the usage of their mobile communication services. Community identification and mining is one of the recent major directions in social network analysis. In this paper we find the communities in the network based on a modularity factor. Then we propose a graph theory-based algorithm for further split of communities resulting in smaller sized and closely knit sub-units, to drill down and understand consumer behavior in a comprehensive manner. These sub-units are then analyzed and labeled based on their group behavior pattern. The analysis is done using two approaches:—rule-based, and cluster-based, for comparison and the able usage of information for suitable labeling of groups. Moreover, we measured and analyzed the uniqueness of the structural properties for each small unit; it is another quick and dynamic way to assign suitable labels for each distinct group. We have mapped the behavior-based labeling with unique structural properties of each group. It reduces considerably the time taken for processing and identifying smaller sub-communities for effective targeted marketing. The efficiency of the employed algorithms was evaluated on a large telecom dataset in three different stages of our work.


title: An integrity-based mechanism for accessing keys in a mobile trusted module

abstract: The data encryption is a good method to hide the original contents of data from hackers. The main components of the cryptography are keys and passwords. In recent, to protect the keys from the hackers, the keys are stored into hardware modules that are independent on a user terminal. Otherwise, the passwords are easily exposed by a variety of password hacking techniques. Moreover, to access keys in the hardware module, users also have to input the password of key or hardware module every time. To solve these problems, we propose a mechanism to access keys in the hardware module without any password. The mechanism was implemented on our prototype with new MTM and management daemons in android environment.


title: Faulty Loop Data Analysis/Correction and Loop Fault Detection

abstract: Inductive Loops are widely used in California for traffic detection and monitoring. This paper reviews previous work on faulty loop data analysis for correction and faulty loop diagnosis. The authors emphasize that it is necessary to distinguish faulty loop data analysis and loop fault detection according to the data level. According to the level of data used, they divide the work in three levels: the macroscopic level as in TMC (Transportation Management Center) or PeMS (Performance Measurement System) in California, which uses highly aggregated data to look at loop problems related wide range; the mesoscopic level, which involves synchronized data for a section of freeways involving several control cabinet such as Berkeley Highway Lab (BHL); and the microscopic level or control cabinet level including all the loop stations involved. They also review the corresponding data correction methods. The authors conclude that higher level data analysis could be effective for systematic errors which are caused by communication system and power outage. Data analysis in the highway section/corridor level could be used to locate suspicious loop stations if the communication system can be made reliable. Those two methods can only be called indirect since they are affected by the communication system for data passing.


title: Universal Haptic Drive: A Robot for Arm and Wrist Rehabilitation

abstract: In this paper we present a universal haptic drive (UHD), a device that enables rehabilitation of either arm ("ARM" mode) or wrist ("WRIST" mode) movement in two degrees-of-freedom. The mode of training depends on the selected mechanical configuration, which depends on locking/unlocking of a passive universal joint. Actuation of the device is accomplished by utilizing a series elastic actuation principle, which enables use of off-the-shelf mechanical and actuation components. A proportional force control scheme, needed for implementation of impedance control based movement training, was implemented. The device performance in terms of achievable lower and upper bound of viable impedance range was evaluated through adequately chosen sinusoidal movement in eight directions of a planar movement for the "ARM" mode and in eight directions of a combined wrist flexion/extension and forearm pronation/supination movement for the "WRIST" mode. Additionally, suitability of the universal haptic drive for movement training was tested in a series of training sessions conducted with a chronic stroke subject. The results have shown that reliable and repeatable performance can be achieved in both modes of operation for all tested directions.


title: Changes in the prevalence of alcohol in rap music lyrics 1979-2009

abstract: This study examines the prevalence and context of alcohol references in rap music lyrics from 1979 through 2009. Four hundred nine top-ranked rap music songs released were sampled from Billboard magazine rating charts. Songs were analyzed using systematic content analysis and were coded for alcohol beverage types and brand names, drinking behaviors, drinking contexts, attitudes towards alcohol, and consequences of drinking. Trends were analyzed using regression analyses. The results of the study reveal significant increases in the presence of alcohol in rap songs; a decline in negative attitudes towards alcohol; decreases in consequences attributed to alcohol; increases in the association of alcohol with glamour and wealth, drugs, and nightclubs; and increases in references to liquor and champagne.


title: Influence of customer engagement with company social networks on stickiness: Mediating effect of customer value creation

abstract: Customer engagement on CSN comprises three dimensions: conscious participation, enthusiasm, social interaction.Customer engagement has a direct and significant influence on stickiness.Customer value co-creation mediates the relationship between customer engagement and stickiness.CSN managers should take actions to strengthen customer engagement for better business promotion. Company social networks have become an important means for the socialized marketing of a company, forming a new challenge to companies on how to attract customers. Based on such theories as customer engagement, value co-creation, and relationship marketing, this paper presents a model of the influence of customer engagement on stickiness. Data collected from 260 valid questionnaires from Sinas enterprise microblog users were analyzed by structural equation modeling. Empirical results show that customer engagement has a direct and positive influence on customer stickiness as well as an indirect influence through customer value creation. This study enriches previous researches on existing theories of customer engagement, value co-creation, and stickiness, and gives practical guidance for companies to encourage customer engagement and enhance the stickiness of company social networks.


title: Anatomical and Functional Findings in Female‐to‐Male Transsexuals: Testing a New Hypothesis

abstract: Gender dysphoria (GD) is characterized by incongruence between ones gender assigned at birth and the gender that one identifies with. The biological mechanisms of GD are unclear, especially in female-to-male transsexuals (FtM-TR). Here, we investigate whether distinct structural and functional patterns along cerebral midline networks processing own-body perception may constitute a biological correlate.MRI of functional connectivity, cortical thickness, surface area, and gray matter volume was carried out in 28 female-to-male transsexuals (FtM-TR) and 68 cis-sexual controls (34 male). FtM-TR displayed thicker mid-frontal, precuneal-parietal, and lingual cortex than both male and female controls, whereas, in regions with reported anatomical sex differences among the controls, FtM-TR followed patterns of the gender assigned at their birth. FtM-TR also displayed weaker functional connections from the pregenual anterior cingulate to the insular cortex, and the temporo parietal junction compared with both control groups. Distinct structural and functional pattern in the own-body image network may represent biological markers for the dysphoric own-body perception in transgender individuals.


title: IEEE 802.11ax: Challenges and Requirements for Future High Efficiency WiFi

abstract: The popularity of IEEE 802.11 based wireless local area networks (WLANs) has increased significantly in recent years because of their ability to provide increased mobility, flexibility, and ease of use, with reduced cost of installation and maintenance. This has resulted in massive WLAN deployment in geographically limited environments that encompass multiple overlapping basic service sets (OBSSs). In this article, we introduce IEEE 802.11ax, a new standard being developed by the IEEE 802.11 Working Group, which will enable efficient usage of spectrum along with an enhanced user experience. We expose advanced technological enhancements proposed to improve the efficiency within high density WLAN networks and explore the key challenges to the upcoming amendment.


title: Clickthrough-based latent semantic models for web search

abstract: This paper presents two new document ranking models for Web search based upon the methods of semantic representation and the statistical translation-based approach to information retrieval (IR). Assuming that a query is parallel to the titles of the documents clicked on for that query, large amounts of query-title pairs are constructed from clickthrough data; two latent semantic models are learned from this data. One is a bilingual topic model within the language modeling framework. It ranks documents for a query by the likelihood of the query being a semantics-based translation of the documents. The semantic representation is language independent and learned from query-title pairs, with the assumption that a query and its paired titles share the same distribution over semantic topics. The other is a discriminative projection model within the vector space modeling framework. Unlike Latent Semantic Analysis and its variants, the projection matrix in our model, which is used to map from term vectors into sematic space, is learned discriminatively such that the distance between a query and its paired title, both represented as vectors in the projected semantic space, is smaller than that between the query and the titles of other documents which have no clicks for that query. These models are evaluated on the Web search task using a real world data set. Results show that they significantly outperform their corresponding baseline models, which are state-of-the-art.


title: Design of a wireless miniature low cost EMG sensor using gold plated dry electrodes for biomechanics research

abstract: EMG sensors for biomechanics research and portable applications need to be small, wireless and power efficient. This imposes several constraints on the design methodology of such sensors. There are many commercially available devices which are expensive and have proprietary communication protocols. It is difficult to synchronize them with other devices. Furthermore, using gel-based electrodes for signal acquisition increases setup time and running costs. Hence we present the design of a miniaturized, wireless, low-cost and non-invasive dry-electrode EMG sensor that was prototyped in our lab and dubbed the `WB-EMG' Sensor. We demonstrate its working being fitted with a gold plated copper core electrode. By mounting the sensor on the extensor carpiulnaris and recording data during some simple exercises, we were able to show that its envelope in the frequency domain was similar to the expected EMG Pattern.


Collaborative Filtering on Very Sparse Graphs A Recommendation System for Yelp


title: Trace-driven simulation of multithreaded applications

abstract: Over the past few years, computer architecture research has moved towards execution-driven simulation, due to the inability of traces to capture timing-dependent thread execution interleaving. However, trace-driven simulation has many advantages over execution-driven that are being missed in multithreaded application simulations. We present a methodology to properly simulate multithreaded applications using trace-driven environments. We distinguish the intrinsic application behavior from the computation for managing parallelism. Application traces capture the intrinsic behavior in the sections of code that are independent from the dynamic multithreaded nature, and the points where parallelism-management computation occurs. The simulation framework is composed of a trace-driven simulation engine and a dynamic-behavior component that implements the parallelism-management operations for the application. Then, at simulation time, these operations are reproduced by invoking their implementation in the dynamic-behavior component. The decisions made by these operations are based on the simulated architecture, allowing to dynamically reschedule sections of code taken from the trace to the target simulated components. As the captured sections of code are independent from the parallel state of the application, they can be simulated on the trace-driven engine, while the parallelism-management operations, that require to be re-executed, are carried out by the execution-driven component, thus achieving the best of both trace- and execution-driven worlds. This simulation methodology creates several new research opportunities, including research on scheduling and other parallelism-management techniques for future architectures, and hardware support for programming models.


Bayesian Optimization Algorithm


title: Inferring User Political Preferences from Streaming Communications

abstract: Existing models for social media personal analytics assume access to thousands of messages per user, even though most users author content only sporadically over time. Given this sparsity, we: (i) leverage content from the local neighborhood of a user; (ii) evaluate batch models as a function of size and the amount of messages in various types of neighborhoods; and (iii) estimate the amount of time and tweets required for a dynamic model to predict user preferences. We show that even when limited or no selfauthored data is available, language from friend, retweet and user mention communications provide sufficient evidence for prediction. When updating models over time based on Twitter, we find that political preference can be often be predicted using roughly 100 tweets, depending on the context of user selection, where this could mean hours, or weeks, based on the author’s tweeting frequency.


title: A comprehensive overview of methodologies and performance evaluation frameworks in 3D mesh segmentation

abstract: An overview of the state-of-the-art in 3D mesh segmentation.An overview of performance evaluation frameworks for 3D mesh segmentation.New categorization for 3D mesh segmentation methodologies.Pros and cons in performance evaluation frameworks. 3D mesh segmentation has become a crucial part of many applications in 3D shape analysis. In this paper, a comprehensive survey on 3D mesh segmentation methods is presented. Analysis of the existing methodologies is addressed taking into account a new categorization along with the performance evaluation frameworks which aim to support meaningful benchmarks not only qualitatively but also in a quantitative manner. This survey aims to capture the essence of current trends in 3D mesh segmentation.


title: Code Recommendation with Natural Language Tags and Other Heterogeneous Data

abstract: Recommender systems solve the problem of information overload by efficiently utilizing huge quantities of data and trying its best to predict potential preference which aims at a certain user. They are widely applied in numerous fields. However, hardly can we see a code recommender system for programmers though it is desperately expected. Raw data of the code are not so convenient to handle for the difference in structure and lack of relevance. Fortunately, in real world, there are abundant data affiliated to the code, such as context, tags, social relations of users and view histories. In this paper, we firstly formulate a new task of code recommendation. Then, we propose a hybrid linear algorithm for recommending source codes, in which we maximize the utility of multivariate heterogeneous auxiliary data with code. Experiments on the dataset from Code Review Community show that our proposed method works for the new code recommendation task. Our system is hopefully designed to be adaptive to new source of heterogeneous information, and hopefully performs better with more significant data and new inspired components.


title: TRUST AND DISTRUST IN ORGANIZATIONS: Emerging Perspectives, Enduring Questions

abstract: Scholarly interest in the study of trust and distrust in organizations has grown dramatically over the past five years. This interest has been fueled, at least in part, by accumulating evidence that trust has a number of important benefits for organizations and their members. A primary aim of this review is to assess the state of this rapidly growing literature. The review examines recent progress in conceptualizing trust and distrust in organizational theory, and also summarizes evidence regarding the myriad benefits of trust within organizational systems. The review also describes different forms of trust found in organizations, and the antecedent conditions that produce them. Although the benefits of trust are well-documented, creating and sustaining trust is often difficult. Accordingly, the chapter concludes by examining some of the psychological, social, and institutional barriers to the production of trust. CONTENTS


title: Shape-based hand recognition

abstract: The problem of person recognition and verification based on their hand images has been addressed. The system is based on the images of the right hands of the subjects, captured by a flatbed scanner in an unconstrained pose at 45 dpi. In a preprocessing stage of the algorithm, the silhouettes of hand images are registered to a fixed pose, which involves both rotation and translation of the hand and, separately, of the individual fingers. Two feature sets have been comparatively assessed, Hausdorff distance of the hand contours and independent component features of the hand silhouette images. Both the classification and the verification performances are found to be very satisfactory as it was shown that, at least for groups of about five hundred subjects, hand-based recognition is a viable secure access control scheme.


title: Accelerating t-SNE using tree-based algorithms

abstract: The paper investigates the acceleration of t-SNE--an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots--using two tree-based algorithms. In particular, the paper develops variants of the Barnes-Hut algorithm and of the dual-tree algorithm that approximate the gradient used for learning t-SNE embeddings in O(N log N). Our experiments show that the resulting algorithms substantially accelerate t-SNE, and that they make it possible to learn embeddings of data sets with millions of objects. Somewhat counterintuitively, the Barnes-Hut variant of t-SNE appears to outperform the dual-tree variant.


Cascade Subspace Clustering


title: From Brexit to Trump: Social Media’s Role in Democracy

abstract: The ability to share, access, and connect facts and opinions among like-minded (and not so) citizens has encouraged wholesale political adoption of platforms like Twitter and Facebook. Yet our ability to understand the impact that social networks have had on the democratic process is currently very limited. The authors analyze the role social media played in the outcome of the 2016 US presidential election and the Brexit referendum.


title: Regular expressions for decoding of neural network outputs

abstract: Abstract This article proposes a convenient tool for decoding the output of neural networks trained by Connectionist Temporal Classification (CTC) for handwritten text recognition. We use regular expressions to describe the complex structures expected in the writing. The corresponding finite automata are employed to build a decoder. We analyze theoretically which calculations are relevant and which can be avoided. A great speed-up results from an approximation. We conclude that the approximation most likely fails if the regular expression does not match the ground truth which is not harmful for many applications since the low probability will be even underestimated. The proposed decoder is very efficient compared to other decoding methods. The variety of applications reaches from information retrieval to full text recognition. We refer to applications where we integrated the proposed decoder successfully.


title: Visualizando 15 anos de IHC

abstract: This paper presents a visual exploration of the field of Human Computer Interaction in Brazil from a fifteen-year analysis of paper production in Brazilian Symposium on Human Factors in Computing Systems (IHC). Our analysis is based on data-driven visual exploration, and it can help to get insights from the data and identify topics evolution, central authors and institutions, and important trends.


title: Energy efficiency in industry 4.0 using SDN

abstract: Industry 4.0 is a new concept that has emerged from the use of new technologies, which brings great improvements to industries. Consequently, several challenges have been launched for this new concept to become consolidated and will become an industry standard. Software Defined Networking (SDN) is a technology that comes with a proposal of flexibility and agility for the communication networks, which fits with the challenges of Industry 4.0, it searches for these requirements throughout the manufacturing process of its products. While industrial evolution is a worldwide trend, Energy Efficiency in industry plays a key role in environmental sustainability and economic performance of the industry. This article presents the APIs using the SDN paradigm to achieve Energy Efficiency applied to Industry 4.0. Simulation results validate and show the benefits of using SDN APIs in Industry 4.0.


title: Antecedents of User Stickiness and Loyalty and Their Effects on Users' Group-Buying Repurchase Intention

abstract: Intense competition among a vast number of group-buying websites leads to higher product homogeneity, which allows customers to switch to alternative websites easily and reduce their website stickiness and loyalty. This study explores the antecedents of user stickiness and loyalty and their effects on consumers’ group-buying repurchase intention. Results indicate that systems quality, information quality, service quality, and alternative system quality each has a positive relationship with user loyalty through user stickiness. Meanwhile, information quality directly impacts user loyalty. Thereafter, user stickiness and loyalty each has a positive relationship with consumers’ repurchase intention. Theoretical and managerial implications are also discussed.


title: Quadrilateral mesh simplification

abstract: We introduce a simplification algorithm for meshes composed of quadrilateral elements. It is reminiscent of edge-collapse based methods for triangle meshes, but takes a novel approach to the challenging problem of maintaining the quadrilateral connectivity during level-of-detail creation. The method consists of a set of unit operations applied to the dual of the mesh, each designed to improve mesh structure and maintain topological genus. Geometric shape is maintained by an extension of a quadric error metric to quad meshes. The technique is straightforward to implement and efficient enough to be applied to real-world models. Our technique can handle models with sharp features, and can be used to re-mesh general polygonal, i.e. tri- and quad-dominant, meshes into quadonly meshes.


title: A review energy-efficient task scheduling algorithms in cloud computing

abstract: Cloud computing is a model for delivering information technology services, wherein resources are retrieved from the Internet through web-based tools and applications instead of a direct connection to a server. The capability to provision and release cloud computing resources with minimal management effort or service provider interaction led to the rapid increase of the use of cloud computing. Therefore, balancing cloud computing resources to provide better performance and services to end users is important. Load balancing in cloud computing means balancing three important stages through which a request is processed. The three stages are data center selection, virtual machine scheduling, and task scheduling at a selected data center. User task scheduling plays a significant role in improving the performance of cloud services. This paper presents a review of various energy-efficient task scheduling methods in a cloud environment. A brief analysis of various scheduling parameters considered in these methods is also presented. The results show that the best power-saving percentage level can be achieved by using both DVFS and DNS.


title: A Feature Model of Actor, Agent, Functional, Object, and Procedural Programming Languages

abstract: Abstract The number of programming languages is large and steadily increasing. However, little structured information and empirical evidence is available to help software engineers assess the suitability of a language for a particular development project or software architecture. We argue that these shortages are partly due to a lack of high-level, objective programming language feature assessment criteria: existing advice to practitioners is often based on ill-defined notions of ‘paradigms’ [3, p. xiii] and ‘orientation’, while researchers lack a shared common basis for generalisation and synthesis of empirical results. This paper presents a feature model constructed from the programmer's perspective, which can be used to precisely compare general-purpose programming languages in the actor-oriented, agent-oriented, functional, object-oriented, and procedural categories. The feature model is derived from the existing literature on general concepts of programming, and validated with concrete mappings of well-known languages in each of these categories. The model is intended to act as a tool for both practitioners and researchers, to facilitate both further high-level comparative studies of programming languages, and detailed investigations of feature usage and efficacy in specific development contexts.


title: Health Literacy in Taiwan: A Population-Based Study

abstract: Data on health literacy (HL) in the population is limited for Asian countries. This study aimed to test the validity of the Mandarin version of the European Health Literacy Survey Questionnaire (HLS-EU-Q) for use in the general public in Taiwan. Multistage stratiﬁcation random sampling resulted in a sample of 2989 people aged 15 years and above. The HLS-EU-Q was validated by confirmatory factor analysis with excellent model data fit indices. The general HL of the Taiwanese population was 34.4 ± 6.6 on a scale of 50. Multivariate regression analysis showed that higher general HL is significantly associated with the higher ability to pay for medication, higher self-perceived social status, higher frequency of watching health-related TV, and community involvement but associated with younger age. HL is also associated with health status, health behaviors, and health care accessibility and use. The HLS-EU-Q was found to be a useful tool to assess HL and its associated factors in the general population.


title: Internet banking adoption among young intellectuals

abstract: The aim of this paper is to study technology acceptance of internet banking among undergraduate students in Malaysia. Thus, the theoretical framework of the paper is based on modified version of Technology Acceptance Model (TAM). This paper develops a technology acceptance model for internet banking, a conceptual framework to explain the factors influencing undergraduate students' acceptance of internet banking. The model employs perceived usefulness (PU), perceived ease of use (PEOU), perceived credibility (PC) and computer self-efficacy (CSE). The first two are two initial constructs for TAM model. The rest are new constructs to be included in the model in order to have an extension of TAM model that better reflects the students’ view. The results suggest that PU, PEOU and PC had a significant relationship with behavioral intention. Further, these measures are good determinant for undergraduate acceptance for internet banking. Results also suggest that PU and PEOU had a significant relationship with CSE. On the contrary, CSE did not associate with PC. Also, PEOU had a significant relationship with PU and PC that indicate these scales are related to PEOU in explaining undergraduate preference. The paper is useful in providing the understanding of the TAM among undergraduate from Malaysians’ perspective.


title: Design of a Parallel Actuated Exoskeleton for Adaptive and Safe Robotic Shoulder Rehabilitation

abstract: Powered exoskeletons can facilitate after-stroke rehabilitation of patients with shoulder disabilities. Designs using serial mechanisms usually result in complicated and bulky exoskeletons. This paper presents a new parallel actuated shoulder exoskeleton that consists of two spherical mechanisms, two slider crank mechanisms, and a gravity balancing mechanism. The actuators are grounded and placed side-by-side. Thus, better inertia properties can be achieved while lightweight and compactness are maintained. An adaptive mechanism with only passive joints is introduced to compensate for the exoskeleton–limb misalignment and size variation among different subjects. Linear series elastic actuators (SEAs) are proposed to obtain accurate force and impedance control at the exoskeleton–limb interface. The total number of force sensors and actuators is minimized using the adaptive mechanism and SEAs. An exoskeleton prototype is shown to provide bidirectional actuation between the exoskeleton and upper limb, which is required for various rehabilitation processes. We expect this design can provide a means of shoulder rehabilitation.


title: A metasurface isoflux antenna and potential beam reconfigurability

abstract: Artificial surfaces for antenna applications are discussed. The paper is focused on antennas for LEO satellite application and a circularly polarized isoflux shaped beam antenna based on metasurface is presented with numerical results. Potentialities of application of the metasurfing concept to reconfigurable surfaces are also discussed.


title: Premarital Sex, Premarital Cohabitation, and the Risk of Subsequent Marital Dissolution Among Women

abstract: Using nationally representative data from the 1995 National Survey of Family Growth, I estimate the association between intimate premarital relationships (premarital sex and premarital cohabitation) and subsequent marital dissolution. I extend previous research by considering relationship histories pertaining to both premarital sex and premarital cohabitation. I find that premarital sex or premarital cohabitation that is limited to a woman's husband is not associated with an elevated risk of marital disruption. However, women who have more than one intimate premarital relationship have an increased risk of marital dissolution. These results suggest that neither premarital sex nor premarital cohabitation by itself indicate either preexisting characteristics or subsequent relationship environments that weaken marriages. Indeed, the findings are consistent with the notion that premarital sex and cohabitation limited to one's future spouse has become part of the normal courtship process for marriage.


title: ScAlN MEMS Cantilevers for Vibrational Energy Harvesting Purposes

abstract: Piezoelectric energy harvesting offers the possibility to make use of ambient vibrations most beneficially to feed low power sensor nodes. This paper demonstrates the fabrication and characterization of piezoelectric cantilevers with AlN and ScxAl1-xN (x = 27%) thin films for the evaluations of their energy harvesting performance. The characterization mainly focuses on the measurement of the output power at variable load resistance to achieve maximum power output. Superior properties of ScAlN thin films for energy harvesting compared with AlN films are confirmed. Furthermore, an analytical model is employed to extract material parameters for ScAlN. High piezoelectric coefficients e31 = 1.6 C/m2 and d31 = 6.9 pm/V are determined for ScAlN. Finally, a proof mass is attached to further increase the output power at optimized load resistance.


Mesh Generation


title: An IoT System for Remote Monitoring of Patients at Home

abstract: Application areas that utilize the concept of IoT can be broadened to healthcare or remote monitoring areas. In this paper, a remote monitoring system for patients at home in IoT environments is proposed, constructed, and evaluated through several experiments. To make it operable in IoT environments, a protocol conversion scheme between ISO/IEEE 11073 protocol and oneM2M protocol, and a Multiclass Q-learning scheduling algorithm based on the urgency of biomedical data delivery to medical staff are proposed. In addition, for the sake of patients’ privacy, two security schemes are proposed—the separate storage scheme of data in parts and the Buddy-ACK authorization scheme. The experiment on the constructed system showed that the system worked well and the Multiclass Q-learning scheduling algorithm performs better than the Multiclass Based Dynamic Priority scheduling algorithm. We also found that the throughputs of the Multiclass Q-learning scheduling algorithm increase almost linearly as the measurement time increases, whereas the throughputs of the Multiclass Based Dynamic Priority algorithm increase with decreases in the increasing ratio.


title: Exceptions that prove the rule: Using a theory of motivated social cognition to account for ideological incongruities and political anomalies

abstract: A meta-analysis by J. T. Jost, J. Glaser, A. W. Kruglanski, and F. J. Sulloway (2003) concluded that political conservatism is partially motivated by the management of uncertainty and threat. In this reply to J. Greenberg and E. Jonas (2003), conceptual issues are clarified, numerous political anomalies are explained, and alleged counterexamples are incorporated with a dynamic model that takes into account differences between “young” and “old” movements. Studies directly pitting the rigidity-of-the-right hypothesis against the ideological extremity hypothesis demonstrate strong support for the former. Medium to large effect sizes describe relations between political conservatism and dogmatism and intolerance of ambiguity; lack of openness to experience; uncertainty avoidance; personal needs for order, structure, and closure; fear of death; and system threat.


title: When grandiosity and vulnerability collide: Implicit and explicit self-esteem in patientswith Narcissistic Personality Disorder

abstract: Abstract Background and objectives Narcissistic personality disorder (NPD) is characterized by reports of grandiosity including exaggerated illusions of superiority and entitlement (DSM-IV-TR, APA, 2000 ). Based on clinical theories (e.g., Kernberg, 1975 ), many researchers argue that high explicit self-esteem in narcissists masks underlying implicit vulnerability (low implicit self-esteem). Conversely, based on social learning theories (i.e., Millon, 1981 ), people with NPD are characterized by implicit grandiosity (high implicit self-esteem). We test these competing hypotheses in patients diagnosed with NPD. Methods The present study examined implicit self-esteem (using an Implicit Association Test) and explicit self-esteem (using a self-report questionnaire) in patients with NPD in comparison to non-clinical and clinical, non-NPD (Borderline Personality Disorder, BPD) control groups. Results Patients with NPD scored lower on explicit self-esteem than non-clinical controls. In comparison to patients with BPD, NPD patients scored higher on explicit and implicit self-esteem. Moreover, within the group of NPD patients, damaged self-esteem (i.e., low explicit, high implicit) was associated with higher narcissistic psychopathology. Limitations In both clinical groups we included participants seeking psychiatric treatment, which might influence explicit self-esteem. Longitudinal studies are needed to further assess self-esteem stability in NPD patients in comparison to the control groups. Conclusions Our findings are indicative of vulnerable facets in patients with NPD (i.e., low explicit self-esteem). Furthermore, damaged self-esteem is connected to specific psychopathology within the NPD group. Implications for research on NPD are discussed.