title: Development and experiment of CSM-based industrial robot servoing control system

abstract: Vision-based without camera calibration control of uncalibrated industrial robots is a challenging research problem. To address the issue, a vision-based industrial robot servoing control system has been developed with the CSM algorithm being adopted in this paper. The software and hardware of this system as well as the direct and inverse kinematics equations which map joint space into “camera space” have been described. The control strategy has been proposed and applied to the CSM-based industrial robot servoing control system. The experiments of robot positioning were performed on the developed CSM-based robot control system without camera calibration to validate the accuracy and real-time performance of the system. Experimental results show that the accuracy can reach approximately 0.3mm in 3-dimensional robot space, and the real-time performance of the system can satisfy the requirements of most industrial applications.


title: Resolution Reconstruction of Climate Data with Pixel Recursive Model

abstract: Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramatically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.


Sample Path Generation for Probabilistic Demand Forecasting


title: A Comparison of Affine Region Detectors

abstract: The paper gives a snapshot of the state of the art in affine covariant region detectors, and compares their performance on a set of test images under varying imaging conditions. Six types of detectors are included: detectors based on affine normalization around Harris (Mikolajczyk and Schmid, 2002; Schaffalitzky and Zisserman, 2002) and Hessian points (Mikolajczyk and Schmid, 2002), a detector of `maximally stable extremal regions', proposed by Matas et al. (2002); an edge-based region detector (Tuytelaars and Van Gool, 1999) and a detector based on intensity extrema (Tuytelaars and Van Gool, 2000), and a detector of `salient regions', proposed by Kadir, Zisserman and Brady (2004). The performance is measured against changes in viewpoint, scale, illumination, defocus and image compression. ::: ::: The objective of this paper is also to establish a reference test set of images and performance software, so that future detectors can be evaluated in the same framework.


title: Dual-Band Omnidirectional Circularly Polarized Antenna Using Zeroth- and First-Order Modes

abstract: This letter discusses the development of a dual-band omnidirectional circularly polarized (CP) antenna using the zeroth- and the first-order resonance modes of epsilon-negative (ENG) transmission lines (TLs). The antenna is based on a circular mushroom structure with curved branches and designed without additional feeding parts for a 90 ° phase difference between two orthogonal modes as well as additional radiators for dual-band operations. A left-hand CP (LHCP) and a right-hand CP (RHCP) are obtained at the zeroth- and the first-order resonance modes, respectively, because the current direction of the curved branch, which is related to a horizontal polarization, at the zeroth-order resonance (ZOR) mode is opposite to that at the first-order resonance (FOR) mode. The measured average axial ratios at the resonance modes in the azimuthal plane are 1.57 and 0.86 dB, respectively. The measured average LHCP and RHCP gains are - 0.24 dBic at the ZOR mode and -0.51 dBic at the FOR mode, respectively. These results are congruent with simulated data.


title: 3.2 A 320mW 32Gb/s 8b ADC-based PAM-4 analog front-end with programmable gain control and analog peaking in 28nm CMOS

abstract: Multilevel modulation formats, such as PAM-4, have been introduced in recent years for next generation wireline communication systems for more efficient use of the available link bandwidth. High-speed ADCs with digital signal processing (DSP) can provide robust performance for such systems to compensate for the severe channel impairment as the data rate continues to increase.


title: Roots of two transcendental equations determining the frequency spectra of standing spherical electromagnetic waves

abstract: Roots of the transcendental equations j/sub l/(lambda)/y/sub l/(lambda) =j/sub l/(..cap alpha..lambda) i/sub l/ (a)/i/sub j/(a)-j/sub l/(..cap alpha..lambda)/..sqrt..vertical-barepsilonvertical-bar)/(y/sub l/ (..cap alpha..lambda) i/sub l/(a)/i/sub l/(a)-y/sub l/ (..cap alpha..lambda)/..sqrt..vertical-barepsilonvertical-bar)/a=..cap alpha..lambda..sqrt..vertical-barepsilonvertical-bar and (etaj/sub l/(eta)-lj/sub l/(eta))/(etay/sub l/ (eta)-ly/sub l/(eta))=vertical-barepsilonvertical-bar..beta..j/sub l/(..beta..)/(1+vertical-barepsilonvertical-bar) -lj/sub l/(..beta..)+..sqrt..vertical-barepsilonvertical-bar..beta..j/sub l/(..beta..) i/sub l/ (b)/(1+vertical-barepsilonvertical-bar) i/sub l/(b))/(vertical-barepsilonvertical-bar..beta..y/sub l/ (..beta..)/(1+vertical-barepsilonvertical-bar)-ly/sub l/(..beta..)+..sqrt..vertical-barepsilonvertical-bar..beta..y/sub l/(..beta..) i/sub l/(b)/(1+vertical-barepsilonvertical-bar) i/sub l/(b))/..beta.. =..cap alpha..eta/b=..beta sqrt..vertical-barepsilonvertical-bar for the spherical Bessel functions of the first and second kind, j/sub l/(x) and y/sub l/(x), and for the modified spherical Bessel functions of the first kind, i/sub l/(x), have been computed. The ranges for the parameters ..sqrt..vertical-barepsilonvertical-bar and ..cap alpha.., the order l and the root index n are: ..sqrt..vertical-barepsilonvertical-bar=1.0, 10.0 100.0, 500.0; ..cap alpha..=0.1(0.1)0.7; lambda=1(1)15; n=1(1)30.


title: Security without identification: transaction systems to make big brother obsolete

abstract: The large-scale automated transaction systems of the near future can be designed to protect the privacy and maintain the security of both individuals and organizations.


title: Voice-selective areas in human auditory cortex

abstract: The human voice contains in its acoustic structure a wealth of information on the speaker's identity and emotional state which we perceive with remarkable ease and accuracy1,2,3. Although the perception of speaker-related features of voice plays a major role in human communication, little is known about its neural basis4,5,6,7. Here we show, using functional magnetic resonance imaging in human volunteers, that voice-selective regions can be found bilaterally along the upper bank of the superior temporal sulcus (STS). These regions showed greater neuronal activity when subjects listened passively to vocal sounds, whether speech or non-speech, than to non-vocal environmental sounds. Central STS regions also displayed a high degree of selectivity by responding significantly more to vocal sounds than to matched control stimuli, including scrambled voices and amplitude-modulated noise. Moreover, their response to stimuli degraded by frequency filtering paralleled the subjects' behavioural performance in voice-perception tasks that used these stimuli. The voice-selective areas in the STS may represent the counterpart of the face-selective areas in human visual cortex8,9; their existence sheds new light on the functional architecture of the human auditory cortex.


title: Semantic based Document Clustering: A Detailed Review

abstract: Document clustering, one of the traditional data mining techniques, is an unsupervised learning paradigm where clustering methods try to identify inherent groupings of the text documents, so that a set of clusters is produced in which clusters exhibit high intra-cluster similarity and low intercluster similarity. The importance of document clustering emerges from the massive volumes of textual documents created. Although numerous document clustering methods have been extensively studied in these years, there still exist several challenges for increasing the clustering quality. Particularly, most of the current document clustering algorithms does not consider the semantic relationships which produce unsatisfactory clustering results. Since last three-four years efforts have been seen in applying semantics to document clustering. Here, an exhaustive and detailed review of more than thirty semantic driven document clustering methods is presented. After an introduction to the document clustering and its basic requirements for improvement, traditional algorithms are overviewed. Also, semantic similarity measures are explained. The article then discusses algorithms that make semantic interpretation of documents for clustering. The semantic approach applied, datasets used, evaluation parameters applied, limitations and future work of all these approaches is presented in tabular format for easy and quick interpretation.


title: False Positives, False Negatives, and False Analyses: A Rejoinder to "Machine Bias: There's Software Used across the Country to Predict Future Criminals. and It's Biased against Blacks"

abstract: The validity and intellectual honesty of conducting and reporting analysis are critical, since the ramifications of published data, accurate or misleading, may have consequences for years to come.-Marco and Larkin, 2000, p. 692PROPUBLICA RECENTLY RELEASED a much-heralded investigative report claiming that a risk assessment tool (known as the COMPAS) used in criminal justice is biased against black defendants.12 The report heavily implied that such bias is inherent in all actuarial risk assessment instruments (ARAIs).We think ProPublica's report was based on faulty statistics and data analysis, and that the report failed to show that the COMPAS itself is racially biased, let alone that other risk instruments are biased. Not only do ProPublica's results contradict several comprehensive existing studies concluding that actuarial risk can be predicted free of racial and/or gender bias, a correct analysis of the underlying data (which we provide below) sharply undermines ProPublicas approach.Our reasons for writing are simple. It might be that the existing justice system is biased against poor minorities due to a wide variety of reasons (including economic factors, policing patterns, prosecutorial behavior, and judicial biases), and therefore, regardless of the degree of bias, risk assessment tools informed by objective data can help reduce racial bias from its current level. It would be a shame if policymakers mistakenly thought that risk assessment tools were somehow worse than the status quo. Because we are at a time in history when there appears to be bipartisan political support for criminal justice reform, one poorly executed study that makes such absolute claims of bias should not go unchallenged. The gravity of this study's erroneous conclusions is exacerbated by the large-market outlet in which it was published (ProPublica).Before we expand further into our criticisms of the ProPublica piece, we describe some context and characteristics of the American criminal justice system and risk assessments.Mass Incarceration and ARAIsThe United States is clearly the worldwide leader in imprisonment. The prison population in the United States has declined by small percentages in recent years and at year-end 2014 the prison population was the smallest it had been since 2004. Yet, we still incarcerated 1,561,500 individuals in federal and state correctional facilities (Carson, 2015). By sheer numbers, or rates per 100,000 inhabitants, the United States incarcerates more people than just about any country in the world that reports reliable incarceration statistics (Wagner & Walsh, 2016).Further, it appears that there is a fair amount of racial disproportion when comparing the composition of the general population with the composition of the prison population. The 2014 United States Census population projection estimates that, across the U.S., the racial breakdown of the 318 million residents comprised 62.1 percent white, 13.2 percent black or African American, and 17.4 percent Hispanic. In comparison, 37 percent of the prison population was categorized as black, 32 percent was categorized as white, and 22 percent as Hispanic (Carson, 2015). Carson (2015:15) states that, "As a percentage of residents of all ages at yearend 2014, 2.7 percent of black males (or 2,724 per 100,000 black male residents) and 1.1 percent of Hispanic males (1,090 per 100,000 Hispanic males) were serving sentences of at least 1 year in prison, compared to less than 0.5 percent of white males (465 per 100,000 white male residents)."Aside from the negative effects caused by imprisonment, there is a massive financial cost that extends beyond official correctional budgets. A recent report by The Vera Institute of Justice (Henrichson & Delaney, 2012) indicated that the cost of prison operations (including such things as pension and insurance contributions, capital costs, legal fees, and administrative fees) in 40 states participating in their study was 39. …


title: Quaternion Based Inverse Kinematics for Industrial Robot Manipulators with Euler Wrist

abstract: The major complications of inverse kinematics problem for serial robot manipulators are singularities and nonlinearities. In this context, it is important to formulize the inverse problem in a compact closed form. In this paper, we present closed form solutions of the 6-DOF industrial robot manipulators with Euler wrist using dual quaternions. The successive screw displacements in dual quaternions reduce sine/cosine-type nonlinearities, resulting in a very compact formulation. The RS, RN, and NS robot manipulators are considered as the examples of the employed method.


Adversarial Training for Unsupervised Bilingual Lexicon Induction


BooViews : Aspect-based Sentiment Analysis on Product Reviews combining SVM and CRF in Portuguese


Opleiding Informatica Anomaly Detection with Deep Belief Networks


title: FATAUVA-Net: An Integrated Deep Learning Framework for Facial Attribute Recognition, Action Unit Detection, and Valence-Arousal Estimation

abstract: Facial expression recognition has been investigated for many years, and there are two popular models: Action Units (AUs) and the Valence-Arousal space (V-A space) that have been widely used. However, most of the databases for estimating V-A intensity are captured in laboratory settings, and the benchmarks "in-the-wild" do not exist. Thus, the First Affect-In-The-Wild Challenge released a database for V-A estimation while the videos were captured in wild condition. In this paper, we propose an integrated deep learning framework for facial attribute recognition, AU detection, and V-A estimation. The key idea is to apply AUs to estimate the V-A intensity since both AUs and V-A space could be utilized to recognize some emotion categories. Besides, the AU detector is trained based on the convolutional neural network (CNN) for facial attribute recognition. In experiments, we will show the results of the above three tasks to verify the performances of our proposed network framework.


title: Improving Interactional Organizational Research: A Model of Person-Organization Fit.

abstract: In order for researchers to understand and predict behavior, they must consider both person and situation factors and how these factors interact. Even though organization researchers have developed interactional models, many have overemphasized either person or situation components, and most have failed to consider the effects that persons have on situations. This paper presents criteria for improving interactional models and a model of person-organization fit, which satisfies these criteria. Using a Q-sort methodology, individual value profiles are compared to organizational value profiles to determine fit and to predict changes in values, norms, and behaviors.


title: Clustering Traces Using Sequence Alignment

abstract: Process mining discovers process models from event logs. Logs containing heterogeneous sets of traces can lead to complex process models that try to account for very different behaviour in a single model. Trace clustering identifies homogeneous sets of traces within a heterogeneous log and allows for the discovery of multiple, simpler process models. In this paper, we present a trace clustering method based on local alignment of sequences, subsequent multidimensional scaling, and k-means clustering. We describe its implementation and show that its performance compares favourably to state-of-the-art clustering approaches on two evaluation problems.


title: International Journal of Innovations in Engineering and Technology (IJIET) Comparison of Jaccard, Dice, Cosine Similarity Coefficient To Find Best Fitness Value for Web Retrieved Documents Using Genetic Algorithm

abstract: A similarity coefficient represents the similarity between two documents, two queries, or one document and one query. The retrieved documents can also be ranked in the order of presumed importance. A similarity coefficient is a function which computes the degree of similarity between a pair of text objects. There are a large number of similarity coefficients proposed in the literature, because the best similarity measure doesn't exist (yet !). In this paper we do a comparative analysis for finding out the most relevant document for the given set of keyword by using three similarity coefficients viz Jaccard, Dice and Cosine coefficients. This we perform using genetic algorithm approach. Due to the randomized nature of genetic algorithm the best fitness value is the average of 10 runs of the same code for a fixed number of iterations.The similarity coefficient for a set of documents retrieved for a given query from Google are find out then average relevancy in terms of fitness values using similarity coefficients is calculated. In this paper we have averaged 10 different generations for each query by running the program 10 times for the fixed value of Probability of Crossover Pc=0.7 and Probability of Mutation Pm=0.01. The same experiment was conducted for 10 queries.


title: Bridging the partisan divide: Self-affirmation reduces ideological closed-mindedness and inflexibility in negotiation

abstract: Three studies link resistance to probative information and intransigence in negotiation to concerns of identity maintenance. Each shows that affirmations of personal integrity (vs. nonaffirmation or threat) can reduce resistance and intransigence but that this effect occurs only when individuals’ partisan identity and/or identity-related convictions are made salient. Affirmation made participants’ assessment of a report critical of U.S. foreign policy less dependent on their political views, but only when the identity relevance of the issue rather than the goal of rationality was salient (Study 1). Affirmation increased concession making in a negotiation over abortion policy, but again this effect was moderated by identity salience (Studies 2 and 3). Indeed, although affirmed negotiators proved relatively more open to compromise when either the salience of their true convictions or the importance of remaining faithful to those convictions was heightened, the reverse was true when the salient goal was compromise. The theoretical and applied significance of these findings are discussed.


eview multi-targeted approach to suppress tumor-promoting nflammation


title: INCREASED OIL PRODUCTION BY ADVANCED CONTROL OF RECEIVING FACILITIES

abstract: Abstract Slug flow from wells or multiphase flow lines from subsea satellite fields is one major disturbance at offshore oil and gas processing facilities. Slugging is an undesirable flow pattern with liquid blockages that can occur in multiphase flow lines transporting both gas and liquid. The original contribution in this paper is the successful application of advanced control for the inlet facilities, where active slug control for two 11.7 km long multiphase flow lines is combined with model predictive control to handle slugs entering the inlet separators.


title: Loss Functions for Neural Networks for Image Processing

abstract: Neural networks are becoming central in several areas of computer vision and image processing and different architectures have been proposed to solve specific problems. The impact of the loss layer of neural networks, however, has not received much attention in the context of image processing: the default and virtually only choice is L2. In this paper, we bring attention to alternative choices for image restoration. In particular, we show the importance of perceptually-motivated losses when the resulting image is to be evaluated by a human observer. We compare the performance of several losses, and propose a novel, differentiable error function. We show that the quality of the results improves significantly with better loss functions, even when the network architecture is left unchanged.


title: The Cambridge Face Tracker: Accurate, Low Cost Measurement of Head Posture Using Computer Vision and Face Recognition Software

abstract: PURPOSE ::: We validate a video-based method of head posture measurement. ::: ::: ::: METHODS ::: The Cambridge Face Tracker uses neural networks (constrained local neural fields) to recognize facial features in video. The relative position of these facial features is used to calculate head posture. First, we assess the accuracy of this approach against videos in three research databases where each frame is tagged with a precisely measured head posture. Second, we compare our method to a commercially available mechanical device, the Cervical Range of Motion device: four subjects each adopted 43 distinct head postures that were measured using both methods. ::: ::: ::: RESULTS ::: The Cambridge Face Tracker achieved confident facial recognition in 92% of the approximately 38,000 frames of video from the three databases. The respective mean error in absolute head posture was 3.34°, 3.86°, and 2.81°, with a median error of 1.97°, 2.16°, and 1.96°. The accuracy decreased with more extreme head posture. Comparing The Cambridge Face Tracker to the Cervical Range of Motion Device gave correlation coefficients of 0.99 (P < 0.0001), 0.96 (P < 0.0001), and 0.99 (P < 0.0001) for yaw, pitch, and roll, respectively. ::: ::: ::: CONCLUSIONS ::: The Cambridge Face Tracker performs well under real-world conditions and within the range of normally-encountered head posture. It allows useful quantification of head posture in real time or from precaptured video. Its performance is similar to that of a clinically validated mechanical device. It has significant advantages over other approaches in that subjects do not need to wear any apparatus, and it requires only low cost, easy-to-setup consumer electronics. ::: ::: ::: TRANSLATIONAL RELEVANCE ::: Noncontact assessment of head posture allows more complete clinical assessment of patients, and could benefit surgical planning in future.


title: The health benefits and constraints of exercise therapy for wheelchair users: A clinical commentary

abstract: BACKGROUND ::: There are approximately 1 billion people living with chronic lower limb disability, many of whom are wheelchair users. ::: ::: ::: OBJECTIVES ::: Review cardiometabolic and neuromuscular risk profiles of wheelchair users, benefits of regular exercise and the causes of neuromuscular upper limb and hip injuries that hinder regular adherence. ::: ::: ::: METHOD ::: Literature published between 2013 and 2017 was adopted according to the standard practices for systematic reviews (PRISMA) through Crossref Metadata and Google Scholar searches. Individual paper quality was evaluated using a modified Downs and Black Appraisal Scale. ::: ::: ::: RESULTS ::: The literature search identified 16 600 papers which were excluded if they were non-English, non-peer-reviewed or published before 2013. Finally, 25 papers were accepted, indicating that sedentary wheelchair users have poor cardiometabolic risk profiles (PCMRP) because of a lack of physical activity, limiting their quality of life, characterised by low self-esteem, social isolation and depression. Their predominant mode of physical activity is through upper limb exercises, which not only improves their cardiometabolic risk profiles but also precipitates neuromuscular upper limb overuse injuries. The primary cause of upper limb injuries was attributed to poor wheelchair propulsion related to incorrect chair setup and poor cardiorespiratory fitness. ::: ::: ::: CONCLUSION ::: Wheelchair users have a high body mass index, body fat percentage and serum lipid, cholesterol and blood glucose concentrations. Empirical investigations illustrate exercise improves their PCMRP and cardiorespiratory fitness levels. Although literature encourages regular exercise, none discusses the need to individualise chair setup in order to eliminate wheelchair pathomechanics and upper limb neuromuscular injuries. Wheelchair users must be encouraged to consult a biokineticist or physiotherapist to review their wheelchair setup so as to eliminate possible incorrect manual wheelchair propulsion biomechanics and consequent overuse injuries.


title: One-Shot Learning for Real-Time Action Recognition

abstract: The goal of the paper is to develop a one-shot real-time learning and recognition system for 3D actions. We use RGBD images, combine motion and appearance cues, and map them into a new overcomplete space. The proposed method relies on descriptors based on 3D Histogram of Flow (3DHOF) and on Global Histogram of Oriented Gradient (GHOG); adaptive sparse coding (SC) is further applied to capture high-level patterns. We add effective on-line video segmentation and finally the recognition of actions through linear SVMs. The main contribution of the paper is a real-time system for one-shot action modeling; moreover we highlight the effectiveness of sparse coding techniques to represent 3D actions. We obtain very good results on the ChaLearn Gesture Dataset and with a Kinect sensor.


title: Detecting and Estimating Signals in Noisy Cable Structures, I: Neuronal Noise Sources

abstract: In recent theoretical approaches addressing the problem of neural coding, tools from statistical estimation and information theory have been applied to quantify the ability of neurons to transmit information through their spike outputs. These techniques, though fairly general, ignore the specific nature of neuronal processing in terms of its known biophysical properties. However, a systematic study of processing at various stages in a biophysically faithful model of a single neuron can identify the role of each stage in information transfer. Toward this end, we carry out a theoretical analysis of the information loss of a synaptic signal propagating along a linear, one-dimensional, weakly active cable due to neuronal noise sources along the way, using both a signal reconstruction and a signal detection paradigm. Here we begin such an analysis by quantitatively characterizing three sources of membrane noise: (1) thermal noise due to the passive membrane resistance, (2) noise due to stochastic openings and closings of voltage-gated membrane channels (NA+ and K+), and (3) noise due to random, background synaptic activity. Using analytical expressions for the power spectral densities of these noise sources, we compare their magnitudes in the case of a patch of membrane from a cortical pyramidal cell and explore their dependence on different biophysical parameters.


Exploring the Influence of Parental Involvement and Socioeconomic Status on Teen Digital Citizenship: A Path Modeling Approach


title: The Report of Three Rare Cases of the Niemann-pick Disease in Birjand, South Khorasan, Eastern Iran

abstract: Niemann-Pick disease type C (NP-C) is a rare neurovisceral and irreversible disease leading to premature death and disabling neurological signs. This autosomal recessive disease with incidence rate of 1:120000 is caused by mutations in either the NPC1 or the NPC2 gene, which leads to accumulation of cholesterol in body tissues especially brain and progressive neurological symptoms. NP-C is characterized by nonspecific visceral, neurological and psychiatric manifestations in infants. The neurological involvement is typically proceeded by systemic signs (cholestatic jaundice in the neonatal period or isolated spleno-or hepatosplenomegaly in infancy or childhood). Early detection of NPC is important so that therapy with miglustat can delay onset of neurological symptoms and prolong survival. We describe here three infants from Birjand, South Khorasan, eastern Iran in 2016 with splenomegaly and different neurological signs that diagnosis was confirmed by genetic study. In all of them, NPC-509 was pathologically increased. They also had an unreported homozygous mutation (c.1415T>C, p.Leu472Pro) in exon 9 of the NPC1 gene. We found unreported homozygous mutation in NPC gene. Knowing this mutation is significant to our people. Genotype-phenotype correlations for this specific mutation needs to be further studied.


Proposing A new Design Approach for M-learning Applications


title: Design of anelectrically small meander antenna for LTE mobile terminals in the 800 MHz band

abstract: Fourth generation mobile networks (also called Long Term Evolution — LTE) will make use of multiple-input-multiple-output (MIMO) technology to achieve very high data rates in both the uplink and downlink. MIMO is based on the use of multiple antenna systems within the mobile terminal as well as the base station. The small size of the mobile terminal poses series integration and antenna miniaturization challenges. In this work, we propose an electrically small antenna (ESA) that is based on the meander antenna structure that operates in the 800 MHz band of LTE and 3G cellular standards. The antenna has a measured center frequency of 897 MHz, bandwidth of 185 MHz and total size of 23.5 × 43 mm2. Both simulation and experiment results are presented. A study on the effect of the various antenna parameters that will aid the designer fine tune his structure is also discussed.


title: Recursive self-organizing network models

abstract: Self-organizing models constitute valuable tools for data visualization, clustering, and data mining. Here, we focus on extensions of basic vector-based models by recursive computation in such a way that sequential and tree-structured data can be processed directly. The aim of this article is to give a unified review of important models recently proposed in literature, to investigate fundamental mathematical properties of these models, and to compare the approaches by experiments. We first review several models proposed in literature from a unifying perspective, thereby making use of an underlying general framework which also includes supervised recurrent and recursive models as special cases. We shortly discuss how the models can be related to different neuron lattices. Then, we investigate theoretical properties of the models in detail: we explicitly formalize how structures are internally stored in different context models and which similarity measures are induced by the recursive mapping onto the structures. We assess the representational capabilities of the models, and we shortly discuss the issues of topology preservation and noise tolerance. The models are compared in an experiment with time series data. Finally, we add an experiment for one context model for tree-structured data to demonstrate the capability to process complex structures.


title: A Collection of Definitions of Intelligence

abstract: This chapter is a survey of a large number of informal definitions of “intelligence” that the authors have collected over the years. Naturally, compiling a complete list would be impossible as many definitions of intelligence are buried deep inside articles and books. Nevertheless, the 70 odd definitions presented here are, to the authors' knowledge, the largest and most well referenced collection there is.


title: Comparison of the Modular Multilevel DC Converter and the Dual-Active Bridge Converter for Power Conversion in HVDC and MVDC Grids

abstract: It is expected that in the near future the use of high-voltage dc (HVDC) transmission and medium-voltage dc (MVDC) distribution technology will expand. This development is driven by the growing share of electrical power generation by renewable energy sources that are located far from load centers and the increased use of distributed power generators in the distribution grid. Power converters that transfer the electric energy between voltage levels and control the power flow in dc grids will be key components in these systems. The recently presented modular multilevel dc converter (M2DC) and the three-phase dual-active bridge converter (DAB) are benchmarked for this task. Three scenarios are examined: a 15 MW converter for power conversion from an HVDC grid to an MVDC grid of a university campus, a gigawatt converter for feeding the energy from an MVDC collector grid of a wind farm into the HVDC grid, and a converter that acts as a power controller between two HVDC grids with the same nominal voltage level. The operation and degrees of freedom of the M2DC are investigated in detail aiming for an optimal design of this converter. The M2DC and the DAB converter are thoroughly compared for the given scenarios in terms of efficiency, amount of semiconductor devices, and expense on capacitive storage and magnetic components.


title: An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination

abstract: This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.


title: OntoKhoj: a semantic web portal for ontology searching, ranking and classification

abstract: The goal of the next generation Web is to build virtual communities, wherein software agents and people can work in cooperation by sharing knowledge. To achieve this goal, the emerging Semantic Web community has proposed ontologies to express knowledge in a machine understandable way. The process of building and maintaining ontologies, which is known as Ontology Engineering, presents unique challenges. These challenges are related to lack of trustworthy and authoritative knowledge sources and absence of a centralized repository to locate ontologies to be reused. In this paper, we propose a Semantic Web portal, called OntoKhoj that is designed to simplify the Ontology Engineering process. The methodology in developing OntoKhoj is based on algorithms used for searching, aggregating, ranking and classifying ontologies in Semantic Web. The proposed OntoKhoj would 1) allow agents and ontology engineers to retrieve trustworthy, authoritative knowledge, and 2) expedite the process of ontology engineering through extensive reuse of ontologies. We have implemented the OntoKhoj portal and further validated our system on the real ontological data in the Semantic Web.


title: Exploring the Scientific Impact of Information Systems Design Science Research: A Scientometric Study

abstract: Design science is a fundamental research stream that contends its position in the information systems discipline. While ongoing debates address the relative importance of design science contributions in the information systems community, insights into the scientific impact of design science research (DSR) are missing and this lack of understanding arguably poses challenges to an informed discourse. To identify the most influential papers and those factors that explain their scientific impact, this paper presents an exploratory study of the scientific impact of DSR papers published in the AIS Senior Scholars' Basket of Journals. We uncover the current DSR landscape by taking stock of influential papers and theories and develop a model to explain the scientific impact of DSR papers. Our findings show that scientific impact is significantly explained by theorization and novelty. We discuss how the implications of our work can be projected on the overarching discourse on DSR.


Neural Networks for Language Modeling


title: A Cascaded Approach to Efficient Detection of OFDM Signals Based on Energy and Autocorrelation Detection

abstract: Spectrum sensing is one of the most important parts of the cognitive radio system. In order to detect the primary user signal, the robust sensing method is required. In this paper, we propose a combination of the energy detection method and the autocorrelation-based detection method with a cascaded architecture to improve the probability of detection. Energy detection involves lower complexity and energy consumption, but it is unreliable at low signal-to-noise ratios (SNRs). Orthogonal frequency division multiplexing signal property is used by an autocorrelation-based detector, which involves more complexity and is more robust at low SNRs. We build the cascaded design of both energy detection and autocorrelation-based detection to take advantage of each technique. The performance of a cascaded detector is then presented. It is shown that the probability of detection of the cascaded design is always better than the probability of detection of a single detector. The design of the cascaded detector has been implemented which does not require additional sensing time. The complexity and utilization of each detector design is then presented to show the efficiency of the proposed design.


title: The ART of practical synchronization

abstract: The performance of transactional database systems is critically dependent on the efficient synchronization of in-memory data structures. The traditional approach, fine-grained locking, does not scale on modern hardware. Lock-free data structures, in contrast, scale very well but are extremely difficult to implement and often require additional indirections. In this work, we argue for a middle ground, i.e., synchronization protocols that use locking, but only sparingly. We synchronize the Adaptive Radix Tree (ART) using two such protocols, Optimistic Lock Coupling and Read-Optimized Write EXclusion (ROWEX). Both perform and scale very well while being much easier to implement than lock-free techniques.


title: Visual Recognition of American Sign Language Using Hidden Markov Models

abstract: Abstract : Using hidden Markov models (HMM's), an unobstrusive single view camera system is developed that can recognize hand gestures, namely, a subset of American Sign Language (ASL). Previous systems have concentrated on finger spelling or isolated word recognition, often using tethered electronic gloves for input. We achieve high recognition rates for full sentence ASL using only visual cues. A forty word lexicon consisting of personal pronouns, verbs, nouns, and adjectives is used to create 494 randomly constructed five word sentences that are signed by the subject to the computer. The data is separated into a 395 sentence training set and an independent 99 sentence test set. While signing, the 2D position, orientation, and eccentricity of bounding ellipses of the hands are tracked in real time with the assistance of solidly colored gloves. Simultaneous recognition and segmentation of the resultant stream of feature vectors occurs five times faster than real time on an HP 735. With a strong grammar, the system achieves an accuracy of 97%; with no grammar, an accuracy of 91% is reached (95% correct).


title: Security Patterns from Intelligent Data: A Map of Software Vulnerability Analysis

abstract: A significant milestone is reached when the field of software vulnerability research matures to a point warranting related security patterns represented by intelligent data. A substantial research material of empirical findings, distinctive taxonomy, theoretical models, and a set of novel or adapted detection methods justify a unifying research map. The growth interest in software vulnerability is evident from a large number of works done during the last several decades. This article briefly reviews research works in vulnerability enumeration, taxonomy, models and detection methods from the perspective of intelligent data processing and analysis. This article also draws the map which associated with specific characteristics and challenges of vulnerability research, such as vulnerability patterns representation and problem-solving strategies.


title: Impact of extreme high temperature on mortality and regional level definition of heat wave: a multi-city study in China.

abstract: BACKGROUND ::: Few multi-city studies have been conducted to explore the regional level definition of heat wave and examine the association between extreme high temperature and mortality in developing countries. ::: ::: ::: OBJECTIVES ::: The purpose of the present study was to investigate the impact of extreme high temperature on mortality and to explore the local definition of heat wave in five Chinese cities. ::: ::: ::: METHODS ::: We first used a distributed lag non-linear model to characterize the effects of daily mean temperature on non-accidental mortality. We then employed a generalized additive model to explore the city-specific definition of heat wave. Finally, we performed a comparative analysis to evaluate the effectiveness of the definition. ::: ::: ::: RESULTS ::: For each city, we found a positive non-linear association between extreme high temperature and mortality, with the highest effects appearing within 3 days of extreme heat event onset. Specifically, we defined individual heat waves of Beijing and Tianjin as being two or more consecutive days with daily mean temperatures exceeding 30.2 °C and 29.5 °C, respectively, and Nanjing, Shanghai and Changsha heat waves as ≥3 consecutive days with daily mean temperatures higher than 32.9 °C, 32.3 °C and 34.5 °C, respectively. Comparative analysis generally supported the definition. ::: ::: ::: CONCLUSIONS ::: We found extreme high temperatures were associated with increased mortality, after a short lag period, when temperatures exceeded obvious threshold levels. The city-specific definition of heat wave developed in our study may provide guidance for the establishment and implementation of early heat-health response systems for local government to deal with the projected negative health outcomes due to heat waves.


title: Using Reflexivity to Optimize Teamwork in Qualitative Research

abstract: Reflexivity is often described as an individual activity. The authors propose that reflexivity employed as a team activity, through the sharing of reflexive writing (accounts of personal agendas, hidden assumptions, and theoretical definitions) and group discussions about arising issues, can improve the productivity and functioning of qualitative teams and the rigor and quality of the research. The authors review the literature on teamwork, highlighting benefits and pitfalls, and define and discuss the role for reflexivity. They describe their own team and detail how they work together on a project investigating doctor-patient communication about prescribing. The authors present two reflexive tools they have used and show through examples how they have influenced the effectiveness of their team in terms of process, quality, and outcome.


title: Realizing human rights for women.

abstract: The Vienna Conference not only marked an acceptance of the importance of asserting the indivisibility of human rights for women but also of strengthening the enforcement mechanisms for protecting womens human rights. As a reconceptualization of human rights has begun to take place the agenda is shifting toward the challenge of ensuring the effective enjoyment of these rights. A number of recent developments of the Committee on the Elimination of All Forms of Discrimination Against Women (CEDAW) are designed to enhance the effectiveness of the Womens Convention. In particular the state reporting procedure under the Womens Convention which is the principal means by which the CEDAW monitors implementation of the Convention is under scrutiny and a proposal for the establishment of an individual complaints procedure is currently approaching its final stages of consultation. Both steps represent a serious effort to counteract the operational difficulties that have impaired the effective enjoyment of womens human rights and to breathe life into the embryonic right to be free from violence in the public and private sphere. These developments illustrate how far the human rights movement has shifted toward embracing womens issues fifty years after the Universal Declaration of Human Rights 8 first asserted that "[a]ll human beings are born free and equal in dignity and rights." This article aims to describe and evaluate the progress that has ensued. Section II will briefly explain why the human rights community has been so slow to respond to womens issues. Section III will then trace the development of the international communitys response to the issue of violence against women. Next Section IV will explain why the international instruments dealing with violence against women mark a reconceptualization of human rights law and assess their wider significance. Section V will then set out some of the recent operational developments in enforcing womens human rights. In conclusion Section VI will suggest with reference to recent jurisprudence on state responsibility how these developments might be exploited. (excerpt)


title: Soft Switching Isolated Sepic Converter with the Buck-Boost Type of Active Clamp

abstract: A zero voltage switching (ZVS) isolated Sepic converter with active clamp topology is presented. The buck-boost type of active clamp is connected in parallel with the primary side of the transformer to absorb all the energy stored in the transformer leakage inductance and to limit the peak voltage on the switching device. During the transition interval between the main and auxiliary switches, the resonance based on the output capacitor of switch and the transformer leakage inductor can achieve ZVS for both switches. The operational principle, steady state analysis and design consideration of the proposed converter are presented. Finally, the proposed converter is verified by the experimental results based on an 180 W prototype circuit.


title: Flow-Based detection of DNS tunnels

abstract: DNS tunnels allow circumventing access and security policies in firewalled networks. Such a security breach can be misused for activities like free web browsing, but also for command & control traffic or cyber espionage, thus motivating the search for effective automated DNS tunnel detection techniques. In this paper we develop such a technique, based on the monitoring and analysis of network flows. Our methodology combines flow information with statistical methods for anomaly detection. The contribution of our paper is twofold. Firstly, based on flow-derived variables that we identified as indicative of DNS tunnelling activities, we identify and evaluate a set of non-parametrical statistical tests that are particularly useful in this context. Secondly, the efficacy of the resulting tests is demonstrated by extensive validation experiments in an operational environment, covering many different usage scenarios.


title: Sobolev GAN

abstract: We propose a new Integral Probability Metric (IPM) between distributions: the Sobolev IPM. The Sobolev IPM compares the mean discrepancy of two distributions for functions (critic) restricted to a Sobolev ball defined with respect to a dominant measure $\mu$. We show that the Sobolev IPM compares two distributions in high dimensions based on weighted conditional Cumulative Distribution Functions (CDF) of each coordinate on a leave one out basis. The Dominant measure $\mu$ plays a crucial role as it defines the support on which conditional CDFs are compared. Sobolev IPM can be seen as an extension of the one dimensional Von-Mises Cram\'er statistics to high dimensional distributions. We show how Sobolev IPM can be used to train Generative Adversarial Networks (GANs). We then exploit the intrinsic conditioning implied by Sobolev IPM in text generation. Finally we show that a variant of Sobolev GAN achieves competitive results in semi-supervised learning on CIFAR-10, thanks to the smoothness enforced on the critic by Sobolev GAN which relates to Laplacian regularization.


title: A review of fuzzy set aggregation connectives

abstract: Abstract One of the most attractive features of fuzzy set theory is to provide a mathematical setting for the integration of subjective categories represented by membership functions. Indeed, a body of aggregation operations is already available, which may be useful in decision analysis, quantitative psychology and information processing. This paper provides an extensive survey on fuzzy set-theoretic operations, and emphasizes the relevance of the theory of functional equations in the axiomatical construction of classes of such operations and the derivation of functional representations. The second part is devoted to the application of fuzzy set theory to multifactorial evaluation. Some links between this approach and multiattribute utility theory are explored. Problems of modeling the importance of criteria, as well as of choosing a proper aggregation connective in a given situation, are also discussed.


title: Symbol detection using the differential evolution algorithm in MIMO-OFDM systems

abstract: Channel estimation and symbol detection in multiple-input and multiple-output (MIMO)-orthogonal fre- quency division multiplexing (OFDM) systems are essential tasks. Although the maximum likelihood (ML) detector reveals excellent performance for symbol detection, the computational complexity of this algorithm is extremely high in systems with more transmitter antennas and high-order constellation size. In this paper, we propose the differential evolution (DE) algorithm in order to reduce the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems. The DE algorithm is also compared to some heuristic approaches, such as the genetic algorithm and particle swarm optimization. According to the simulation results, the DE has the advantage of significantly less complexity and is closer to the optimal solution.


title: Protestant Disillusionment with the Northern Ireland Peace Agreement

abstract: The period since the 1998 Good Friday Agreement has witnessed a degree of electoral polarisation that dwarfs any previous period during the current Troubles in scale and intensity. This has been attributed to Protestant disillusionment with the Agreement and the political institutions it established. The results presented here using a wide range of public opinion polls support this view. Protestants are much more pessimistic of both current and future relations between the two communities than are Catholics. The increasingly negative view of Protestants, particularly in terms of future community relations, is reflected in declining support for the Agreement. Protestants who believe that relations between the two religious communities in five years time will be worse than they are now are significantly more likely to vote against the Agreement. This is the case even among previous Protestant supporters of the Agreement.


title: A Hierarchical Security Framework for Defending Against Sophisticated Attacks on Wireless Sensor Networks in Smart Cities

abstract: In smart cities, wireless sensor networks (WSNs) act as a type of core infrastructure that collects data from the city to implement smart services. The security of WSNs is one of the key issues of smart cities. In resource-restrained WSNs, dynamic ongoing or unknown attacks usually steer clear of isolated defense components. Therefore, to resolve this problem, we propose a hierarchical framework based on chance discovery and usage control (UCON) technologies to improve the security of WSNs while still taking the low-complexity and high security requirements of WSNs into account. The features of continuous decision and dynamic attributes in UCON can address ongoing attacks using advanced persistent threat detection. In addition, we use a dynamic adaptive chance discovery mechanism to detect unknown attacks. To design and implement a system using the mechanism described above, a unified framework is proposed in which low-level attack detection with simple rules is performed in sensors, and high-level attack detection with complex rules is performed in sinks and at the base station. Moreover, software-defined networking and network function virtualization technologies are used to perform attack mitigation when either low-level or high-level attacks are detected. An experiment was performed to acquire an attack data set for evaluation. Then, a simulation was created to evaluate the resource consumption and attack detection rate. The results demonstrate the feasibility and efficiency of the proposed scheme.


title: A 5.9nV/√Hz chopper operational amplifier with 0.78μV maximum offset and 28.3nV/°C offset drift

abstract: Many auto-zero or chopper operational amplifiers have been reported with low offset and low-offset drift. The resulting baseband noise can also be a significant error source, and thus reducing the total error down to sub μV levels at DC and low frequencies has been targeted. Chopping is more suitable to lower the baseband noise PSD, as it is primarily determined by the broad-band thermal noise floor and not aliased by the high frequency noise [1]. Reducing the thermal noise floor requires higher value of input transconductance [1]. Consequently, more capacitance or higher output transconductance is required to stabilize the overall feedback loop with regular Miller compensation. A 6.5nV/√Hz conditionally stable chopper operational amplifier has been reported, using multi-pole feedforward compensation techniques [2]. Unconditionally stable chopper operational amplifiers presented so far exhibit more than 10nV/√Hz noise PSD [1,3–5]. This paper reports a 5.9nV/√Hz unconditionally stable chopper operational amplifier with 1.47mA supply current and 1.26mm2 die area, achieved by phase compensation using current attenuation. In addition, adaptive clock level shift and backgate biasing for the input chopping allows optimization for noise and offset, realizing 0.78μV maximum offset with a worst-case 28.3nV/°C drift.


title: Design And Optimization Of Planar Waveguide Magic Tee At W-band

abstract: Conventionally, the sum and difference signals of a tracking system are fixed up by sum and difference network and the network is often composed of four or more magic tees whose arms direct at four different directions, which give inconveniences to assemble. In this paper, a waveguide side-wall slot directional coupler and a double dielectric slab filled waveguide phase shifter is used to form a planar magic tee with four arms in the same H-plane. Four planar magic tees can be used to construct the W-band planar monopulse comparator. The planar magic tee is analyzed exactly with Ansoft HFSS software, and is optimized by genetic algorithm. Simulation results are presented, which show good performance.


title: Holographic artificial impedance surfaces for conformal antennas

abstract: We have developed a method for generating arbitrary radiation patterns from antennas on complex objects. The object is coated with an artificial impedance surface consisting of a lattice of sub-wavelength metal patches on a grounded dielectric substrate. The effective surface impedance depends on the size of the patches, and can be varied as a function of position. Using holography, the surface impedance is designed to generate any desired radiation pattern from currents in the surface. With this technique we can create antennas with novel properties such as radiation toward angles that would otherwise be shadowed


title: Instance-Aware Hashing for Multi-Label Image Retrieval

abstract: Similarity-preserving hashing is a commonly used method for nearest neighbor search in large-scale image retrieval. For image retrieval, deep-network-based hashing methods are appealing, since they can simultaneously learn effective image representations and compact hash codes. This paper focuses on deep-network-based hashing for multi-label images, each of which may contain objects of multiple categories. In most existing hashing methods, each image is represented by one piece of hash code, which is referred to as semantic hashing. This setting may be suboptimal for multi-label image retrieval. To solve this problem, we propose a deep architecture that learns instance-aware image representations for multi-label image data, which are organized in multiple groups, with each group containing the features for one category. The instance-aware representations not only bring advantages to semantic hashing but also can be used in category-aware hashing, in which an image is represented by multiple pieces of hash codes and each piece of code corresponds to a category. Extensive evaluations conducted on several benchmark data sets demonstrate that for both the semantic hashing and the category-aware hashing, the proposed method shows substantial improvement over the state-of-the-art supervised and unsupervised hashing methods.


Practical challenges related to point of care testing


title: Content preserving text generation with attribute controls

abstract: In this work, we address the problem of modifying textual attributes of sentences. Given an input sentence and a set of attribute labels, we attempt to generate sentences that are compatible with the conditioning information. To ensure that the model generates content compatible sentences, we introduce a reconstruction loss which interpolates between auto-encoding and back-translation loss components. We propose an adversarial loss to enforce generated samples to be attribute compatible and realistic. Through quantitative, qualitative and human evaluations we demonstrate that our model is capable of generating fluent sentences that better reflect the conditioning information compared to prior methods. We further demonstrate that the model is capable of simultaneously controlling multiple attributes.


title: Poor water quality suppresses the cortisol response of salmonid fish to handling and confinement

abstract: Confinement of brown trout in small troughs of static water for 1 h at a density of six fish per 25L stimulated the hypothalamic-pituitary-interrenal axis and resulted in an elevation of plasma cortisol from basal levels (less than 2 ng/ml) to about 100 ng/ml, the degree of stimulation being dependent upon water temperature. Confinement at a density of 30 fish per 25L resulted in a 50% suppression of this response. It is demonstrated that this effect is mediated by changes in water chemistry and not by crowding per se. Experimental manipulation of the water chemistry showed that reduced pH (7.1 to 6.3), elevated free CO2 (63 to 520 μmol/L) or elevated ammonia (8 to 1300 μg/L as total ammonia nitrogen) had no individual effects on the interrenal response to acute confinement. Elevated ammonia in combination with reduced pH significantly increased the plasma cortisol levels in response to acute confinement, whereas a combination of reduced oxygen (100 to 20% saturation), elevated free CO2 and elevated ammonia markedly suppressed (∼ 50%) the cortisol response of both brown trout and rainbow trout to acute confinement in a manner similar to that observed with trout at high densities. A compensatory increase in plasma cortisol levels was observed during the subsequent recovery of fish which had been confined for 1 h in water of poor quality. These findings are discussed in relation to the exposure of fish to multiple stresses and to the role of corticosteroids in the stress response.


title: Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks

abstract: Traffic flow forecasting is an important application domain of machine learning. How to use the information provided by adjacent links more efficiently is a key to improving the performance of Intelligent Transportation Systems (ITS). In this paper, we build a sparse graphical model for multi-link traffic flow through the Graphical Lasso (GL) algorithm and then implement the forecasting with Neural Networks. Through a large number of experiments, we find that network-scale traffic forecasting with modeling by Graphical Lasso performs much better than previous research. Traditional approaches considered the information provided by adjacent links but did not extract the information. Thus, although they improved the performance to some extent, they did not make good use of the information. Furthermore, we summarize the theoretical analysis of Graphical Lasso algorithm. From theoretical and practical points of view, we fully verify the superiority of Graphical Lasso used in modeling for multi-link traffic flow forecasting.


Towards a hybrid approach to Netflix Challenge


An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming


title: Dimensionality-reduced subspace clustering

abstract: Subspace clustering refers to the problem of clustering unlabeled high-dimensional data points into a union of low-dimensional linear subspaces, whose number, orientations, and dimensions are all unknown. In practice one may have access to dimensionality-reduced observations of the data only, resulting, e.g., from undersampling due to complexity and speed constraints on the acquisition device or mechanism. More pertinently, even if the high-dimensional data set is available it is often desirable to first project the data points into a lower-dimensional space and to perform clustering there; this reduces storage requirements and computational cost. The purpose of this paper is to quantify the impact of dimensionality reduction through random projection on the performance of three subspace clustering algorithms, all of which are based on principles from sparse signal recovery. Specifically, we analyze the thresholding based subspace clustering (TSC) algorithm, the sparse subspace clustering (SSC) algorithm, and an orthogonal matching pursuit variant thereof (SSC-OMP). We find, for all three algorithms, that dimensionality reduction down to the order of the subspace dimensions is possible without incurring significant performance degradation. The mathematical engine behind our theory is a result quantifying how the affinities between subspaces change under random projections. Experiments on synthetic and real data complement our theoretical results.


title: Probiotics, prebiotics and synbiotics- a review

abstract: The health benefits imparted by probiotics and prebiotics as well as synbiotics have been the subject of extensive research in the past few decades. These food supplements termed as functional foods have been demonstrated to alter, modify and reinstate the pre-existing intestinal flora. They also facilitate smooth functions of the intestinal environment. Most commonly used probiotic strains are: Bifidobacterium, Lactobacilli, S. boulardii, B. coagulans. Prebiotics like FOS, GOS, XOS, Inulin; fructans are the most commonly used fibers which when used together with probiotics are termed synbiotics and are able to improve the viability of the probiotics. Present review focuses on composition and roles of Probiotics, Prebiotics and Synbiotics in human health. Furthermore, additional health benefits like immune-modulation, cancer prevention, inflammatory bowel disease etc. are also discussed. Graphical abstractPictorial summary of health benefits imparted by probiotics, prebiotics and synbiotics.


title: Differences in energy expenditure during high-speed versus standard-speed yoga: A randomized sequence crossover trial

abstract: Abstract Objectives To compare energy expenditure and volume of oxygen consumption and carbon dioxide production during a high-speed yoga and a standard-speed yoga program. Design Randomized repeated measures controlled trial. Setting A laboratory of neuromuscular research and active aging. Interventions Sun-Salutation B was performed, for eight minutes, at a high speed versus and a standard-speed separately while oxygen consumption was recorded. Caloric expenditure was calculated using volume of oxygen consumption and carbon dioxide production. Main outcome measures Difference in energy expenditure (kcal) of HSY and SSY. Results Significant differences were observed in energy expenditure between yoga speeds with high-speed yoga producing significantly higher energy expenditure than standard-speed yoga (MD = 18.55, SE = 1.86, p Conclusions High-speed yoga results in a significantly greater caloric expenditure than standard-speed yoga. High-speed yoga may be an effective alternative program for those targeting cardiometabolic markers.


title: Peripheral Nerve Injuries: Electrophysiology for the Neurosurgeon

abstract: Peripheral nerve injuries are a heterogeneous and distinct group of disorders that are secondary to various causes commonly including motor vehicle accidents, falls, industrial accidents, household accidents, and penetrating trauma. The earliest classification of nerve injuries was given by Seddon and Sunderland, which holds true till date and is commonly used. Neuropraxia, axonotmesis, and neurotmesis are the three main types of nerve injuries. The electrophysiological studies including nerve conduction studies (NCS) and electromyography (EMG) play a key role and are now considered an extension of the clinical examination in patients with peripheral nerve injuries. The electrophysiological results should be interpreted in the light of clinical examination. These studies help in localizing the site of lesion, determine the type and severity of lesion, and help in prognosticating. In neuropraxia, the compound muscle action potential (CMAP) and sensory nerve action potential (SNAP) are elicitable on stimulating the nerve distal to the site of the lesion but demonstrate conduction block on proximal stimulation. The electrodiagnostic findings in axonotmesis and neurotmesis are similar. After few days of injury, Wallerian degeneration sets in with failure to record CMAP and SNAP. Intraoperative technique involves recording from the peripheral nerves during the intraoperative period and has proved useful in the surgical management of nerve injuries and helps in identifying the injured nerve, to determine whether the nerve is in continuity and in localizing the site of lesion. Intraoperative monitoring also helps in identifying the nerve close to an ongoing surgery so that surgical damage to the nerve can be prevented.


title: Terabus: Terabit/Second-Class Card-Level Optical Interconnect Technologies

abstract: In the "Terabus" optical interconnect program, optical data bus technologies are developed that will support terabit/second chip-to-chip data transfers over organic cards within high-performance servers, switch routers, and other intensive computing systems. A complete technology set is developed for this purpose, based on a chip-like optoelectronic packaging structure (Optochip), assembled directly onto an organic card (Optocard). Vertical-cavity surface emitting laser (VCSEL) and photodiode arrays (4times12) are flip-chip bonded to the driver and receiver IC arrays implemented in 0.13-mum CMOS. The IC arrays are in turn flip-chip assembled onto a 1.2-cm2 silicon carrier interposer to complete the transmitter and receiver Optochips. The organic Optocard incorporates 48 parallel multimode optical waveguides on a 62.5-mum pitch. A simple scheme for optical coupling between the Optochip and the Optocard is developed, based on a single-lens array etched onto the backside of the optoelectronic arrays and on 45deg mirrors in the waveguides. Transmitter and receiver operation is demonstrated up to 20 and 14 Gb/s per channel, respectively. The power dissipation of 10-Gb/s single-channel links over multimode fiber is as low as 50 mW


title: The 1st DDIExtraction-2011 challenge task: Extraction of Drug-Drug Interactions from biomedical texts Challenge Task on Drug-Drug Interaction Extraction

abstract: We present an evaluation task designed to provide a frame- work for comparing different approaches to extracting drug-drug interac- tions from biomedical texts. We define the task, describe the training/test data, list the participating systems and discuss their results. There were 10 teams who submitted a total of 40 runs.


title: Clin Soc Work J DOI 10.1007/s10615-007-0111-7 ORIGINAL PAPER Modern Attachment Theory: The Central Role of Affect Regulation in Development and Treatment

abstract: Over the past decade attachment theory has undergone an intense expansion of both its original scientific foundations as well as its applications to clinical work. Bowlby’s original description occurred during a period of behaviorism and an emphasis on the strange situation and secure base behaviors, which then gave way to a dominance of cognition and an emphasis on attachment narratives and reflective capacities. We will argue that in line with Bowlby’s fundamental goal of the integration of psychological and biological models of human development, the current interest in affective bodily-based processes, interactive regulation, early experience-dependent brain maturation, stress, and nonconscious relational transactions has shifted attachment theory to a regulation theory. This emphasis on the right brain systems that underlie attachment and developmental change has in turn forged deeper connections with clinical models of psychotherapeutic change, all of which are consonant with psychoanalytic understandings. Modern attachment theory can thus be incorporated into the core of social work theory, research, and practice.


title: RNA epigenetics--chemical messages for posttranscriptional gene regulation.

abstract: Chemical modifications in cellular RNA are diverse and abundant. Commonly found in ribosomal RNA (rRNA), transfer RNA (tRNA), long-noncoding RNA (lncRNA), and small nuclear (snRNA), these components play various structural and functional roles. Until recently, the roles of chemical modifications within messenger RNA (mRNA) have been understudied. Recent maps of several mRNA modifications have suggested regulatory functions for these marks. This review summarizes recent advances in identifying and understanding biological roles of posttranscriptional mRNA modification, or 'RNA epigenetics', with an emphasis on the most common internal modification of eukaryotic mRNA, N(6)-methyladenosine (m(6)A). We also discuss YTH proteins as direct mediators of m(6)A function and the emerging role of this mark in a new layer of gene expression regulation.


title: Fingerprint enhancement for direct grayscale minutiae extraction by combining MFRAT and Gabor filters

abstract: Minutiae are important features in the fingerprints matching. The effective of minutiae extraction depends greatly on the results of fingerprint enhancement. This paper proposes a novel fingerprint enhancement method for direct gray scale extracting minutiae based on combining Gabor filters with the Adaptive Modified Finite Radon Transform (AMFRAT) filters. First, the proposed method uses Gabor filters as band-pass filters for deleting the noise and clarifying ridges. Next, AMFRAT filters are applied for connecting broken ridges together, filling the created holes and clarifying linear symmetry of ridges quickly. AMFRAT is the MFRAT filter, the window size of which is adaptively adjusted according to the coherence values. The small window size is for high curvature ridge areas (small coherence value), and vice versa. As the result, the ridges are the linear symmetry areas, and more suitable for direct gray scale minutiae extraction. Finally, linear symmetry filter is only used for locating minutiae in an inverse model, as "lack of linear symmetry" occurs at minutiae points. Experimental results on FVC2004 databases DB4 (set A) shows that the proposed method is capable of improving the goodness index (GI).


title: Self-Compassion and PTSD Symptom Severity

abstract: Neff ’s (2003a, 2003b) notion of self-compassion emphasizes kindness towards one’s self, a feeling of connectedness with others, and mindful awareness of distressing experiences. Because exposure to trauma and subsequent posttraumatic stress symptoms (PSS) may be associated with self-criticism and avoidance of internal experiences, the authors examined the relationship between self-compassion and PSS. Out of a sample of 210 university students, 100 endorsed experiencing a Criterion A trauma. Avoidance symptoms significantly correlated with self-compassion, but reexperiencing and hyperarousal did not. Individuals high in self-compassion may engage in less avoidance strategies following trauma exposure, allowing for a natural exposure process. Neff (2003a, 2003b) developed her construct self-compassion based on the larger Buddhist notion of compassion (Pali: karuna) and on what is often translated as loving-kindness (Pali: matta; K. Neff, personal communication, June 13, 2005). Karuna refers to a feeling of compassion towards all beings and an awareness of our shared experience as human beings, whereas metta involves conscious goodwill towards others. Self-compassion consists of three components: (a) an attitude of kindness and understanding to one’s self as opposed to harsh judgment; (b) perceiving one’s experiences as part of the larger human condition instead of feeling separate and isolated; (c) being mindfully aware of painful experiences without overidentifying with them (Neff, 2003a). Researchers have already begun to incorporate compassionbased practices into treatment. In Mindfulness-Based Stress Reduction (MBSR), loving-kindness is introduced during an allday meditation (Kabat-Zinn, 1990), and health care professionals exhibited significant increases in self-compassion at the end of an 8-week MBSR program (Shapiro, Astin, Bishop, & Cordova, 2005). An 8-week program emphasizing loving-kindness meditation found a reduction in pain and anger in a sample of patients with chronic lower back pain (Carson et al., 2005), and it has been suggested that this program may be helpful in reducing anger in survivors of childhood sexual abuse (Bowman, 2005). More recently, Gilbert and Proctor (2006) developed a program aimed at fostering compassion and decreasing shame and self-criticism in patients with personality and/or mood disorders attending a hospital day treatment program. Research on the Self-Compassion Scale has found that higher self-compassion is associated with greater psychological well-being: less depression, anxiety, rumination, and thought suppression, and with greater life satisfaction and social relatedness (Neff, 2003b). Increases in self-compassion over a one-month period were


title: Addressing the selective role of distinct prefrontal areas in response suppression: A study with brain tumor patients

abstract: Abstract The diverging evidence for functional localization of response inhibition within the prefrontal cortex might be justified by the still unclear involvement of other intrinsically related cognitive processes like response selection and sustained attention. In this study, the main aim was to understand whether inhibitory impairments, previously found in patients with both left and right frontal lesions, could be better accounted for by assessing these potentially related cognitive processes. We tested 37 brain tumor patients with left prefrontal, right prefrontal and non-prefrontal lesions and a healthy control group on Go/No-Go and Foreperiod tasks. In both types of tasks inhibitory impairments are likely to cause false alarms, although additionally the former task requires response selection and the latter target detection abilities. Irrespective of the task context, patients with right prefrontal damage showed frequent Go and target omissions, probably due to sustained attention lapses. Left prefrontal patients, on the other hand, showed both Go and target omissions and high false alarm rates to No-Go and warning stimuli, suggesting a decisional rather than an inhibitory impairment. An exploratory whole-brain voxel-based lesion-symptom mapping analysis confirmed the association of left ventrolateral and dorsolateral prefrontal lesions with target discrimination failure, and right ventrolateral and medial prefrontal lesions with target detection failure. Results from this study show how left and right prefrontal areas, which previous research has linked to response inhibition, underlie broader cognitive control processes, particularly involved in response selection and target detection. Based on these findings, we suggest that successful inhibitory control relies on more than one functionally distinct process which, if assessed appropriately, might help us to better understand inhibitory impairments across different pathologies.


title: Evaluating the Vegetation Recovery in the Damage Area of Wenchuan Earthquake Using MODIS Data

abstract: The catastrophic 8.0 Richter magnitude earthquake that occurred on 12 May 2008 in Wenchuan, China caused extensive damage to vegetation due to widespread landslides and debris flows. In the past five years, the Chinese government has implemented a series of measures to restore the vegetation in the severely afflicted area. How is the vegetation recovering? It is necessary and important to evaluate the vegetation recovery effect in earthquake-stricken areas. Based on MODIS NDVI data from 2005 to 2013, the vegetation damage area was extracted by the quantified threshold detection method. The vegetation recovery rate after five years following the earthquake was evaluated with respect to counties, altitude, fault zones, earthquake intensity, soil texture and vegetation types, and assessed over time. We have proposed a new method to obtain the threshold with vegetation damage quantitatively, and have concluded that: (1) The threshold with vegetation damage was 13.47%, and 62.09% of the field points were located in the extracted damaged area; (2) The total vegetation damage area was 475,688 ha, which accounts for 14.34% of the study area and was primarily distributed in the central fault zone, the southwest mountainous areas and along rivers in the Midwest region of the study area; (3) Vegetation recovery in the damaged area was better in the northeast regions of the study area, and in the western portion of the Wenchuan-Maoxian fracture; vegetation recovery was better with increasing altitude; there is no obvious relationship between clay content in the topsoil and vegetation recovery; (4) Meadows recovered best and the worst recovery was in mixed coniferous broad-leaved forest; (5) 81,338 ha of vegetation in the damage area is currently undergoing degradation and the main vegetation types in the degradation area are coniferous forest (31.39%) and scrub (34.17%); (6) From 2009 to 2013, 41% has been restored to the level before the earthquake, 9% has not returned but 50% will continue to recover. The Chinese government usually requires five years as a period for post-disaster reconstruction. This paper could be regarded as a guidance for Chinese government departments, whereby additional investment is encouraged for vegetation recovery.


Learning Gamification Design - An Usability First Approach for the Enterprise Infoboard Experiment


title: Max-min fair allocation of indivisible goods

abstract: We consider the problem of fairly allocating a set of m indivisible goods to n agents, given the agents’ utilities for each good. Fair allocations in this context are those maximizing the minimum utility received by any agent. We give hardness results and polynomial time approximation algorithms for several variants of this problem. Our main result is a bicriteria approximation in the model with additive utilities, in which a (1− 1 k ) fraction of the agents receive utility at least OPT/k, for any integer k. This result is obtained from rounding a suitable linear programming relaxation of the problem, and is the best possible result for our LP. We also give an O( √ n) approximation for a special case with only two classes of goods, an (m − n + 1) approximation for instances with submodular utilities, and extreme inapproximability results for the most general model with monotone utilities. This research is supported by NSF ITR grants CCR-0122581 and IIS-0121678.


title: Is Fecal Carriage of Extended-Spectrum-β-Lactamase-Producing Escherichia coli in Urban Rats a Risk for Public Health?

abstract: Brown rats (Rattus norvegicus) are synanthropic and inhabit urban infrastructures. Therefore, they might be involved in transmission pathways of zoonotic bacteria, including multiresistant “superbugs” like extended-spectrum beta-lactamase-producing (ESBL) Escherichia coli ([1][1]). According to


title: Lightning-Induced Voltages on Overhead Distribution Lines: Theoretical and Experimental Investigation of Related Problems and their Impact on Power Quality

abstract: Recent power quality studies have been focused on the source-identification of voltage disturbances at distribution network busses. This paper describes a method aimed at correlating indirect-lightning events with power systems relay operations, associated with voltage dips. The proposed method, based on the coordinated use of the Italian lightning location system CESI-SIRF, the Italian monitoring system of protection manoeuvres CESI-SAM, and the availability of an advanced simulation tool for the accurate simulation of lightning-induced voltages on complex power networks, namely the LIOVEMTP code, is applied to the real case of an Italian distribution system. The LIOV-EMTP code is also employed along with a statistical procedure based on the Monte Carlo method to carry out a statistical analysis aimed at assessing the lightning performance of a typical Italian distribution line.


title: An Application of HodgeRank to Online Peer Assessment

abstract: Bias and heterogeneity in peer assessment can lead to the issue of unfair scoring in the educational field. To deal with this problem, we propose a reference ranking method for an online peer assessment system using HodgeRank. Such a scheme provides instructors with an objective scoring reference based on mathematics.


title: Wearable Flexible Reconfigurable Antenna Integrated With Artificial Magnetic Conductor

abstract: This letter presents a wearable flexible reconfigurable folded slot antenna. The antenna is composed of a folded slot and a stub where the reconfigurability is achieved by turning a p-i-n diode on and off , which alters the radiation characteristics of the stub. The operating frequency and polarization of the slot and stub are different. Hence, a polarization-dependent dual-band artificial magnetic conductor (AMC) surface is integrated with the antenna to improve its radiation performance and to reduce the specific absorption rate (SAR). The antenna is designed and fabricated on a flexible substrate, and its performance is measured for both flat and curved configurations. The measurements show an excellent agreement with the simulations. To examine its performance as a wearable antenna, it is measured on a human body. Simulations show that the SAR level is reduced when the AMC surface is used as an isolator. The proposed wearable antenna structure can be used for wireless body area network (WBAN) and Worldwide Interoperability for Microwave Access (WiMAX) body-worn wireless devices.


title: Learning speaker-specific pronunciations of disordered speech

abstract: One of the main clinical applications of speech technology is in voice-enabled assistive technology for people with disordered speech. Progress in this area is hampered by a sparseness in suitable data and recent research have focused on ways of incorporating knowledge about typical (i.e., un-impaired) speech through the use of e.g., deep belief neural networks. This paper presents a new way of using deep belief neural networks trained on typical speech, namely to improve pronunciations for individual speakers. Analysis of the posterior probabilities show a clear correlation between measured pronunciation ‘disorderedness’ and the overall speech recognition performance of the full system. Based on this, we propose a method to use deep belief network outputs to i) identify which words are pronounced differently than what would be expected from a typical pronunciation, and ii) subsequently generate new pronunciations. We investigate different methods for pronunciation generation as well as what is the best way of using the modified pronunciations to inform the system development stages. Using the UAspeech database of disordered speech, we demonstrate improvement in average accuracy of 69.76% to 70.51%, with some speakers showing individual improvements of up to 10%. Index Terms: dysarthric speech recognition, learning speakerspecific pronunciations


ABSTRACT A Visual Lexicon


title: Real-Time Artistic Silhouettes Rendering for 3D Models

abstract: In line drawings, the line thickness is an important element for artists to depict shape and express emotion. In this paper, we proposed an approach for the real-time rendering of artistic silhouette outlines, based on the inherent aesthetic law of line thickness. We adopted the triangle shell technique as the basis of our silhouette outlines rendering method. By shifting the vertex of the back-facing mesh along its vertex normal under the aesthetic law, we recovered the variation of line thickness that artists often use when creating line drawings, and obtained aesthetically pleasing rendering results. Our method is implemented on GPU, and is suitable for real-time applications such as 3D games.


title: Forensics investigation challenges in cloud computing environments

abstract: Cloud computing discusses about sharing any imaginable entity such as process units, storage devices or software. The provided service is utterly economical and expandable. Cloud computing attractive benefits entice huge interest of both business owners and cyber thefts. Consequently, the “computer forensic investigation” step into the play to find evidences against criminals. As a result of the new technology and methods used in cloud computing, the forensic investigation techniques face different types of issues while inspecting the case. The most profound challenges are difficulties to deal with different rulings obliged on variety of data saved in different locations, limited access to obtain evidences from cloud and even the issue of seizing the physical evidence for the sake of integrity validation or evidence presentation. This paper suggests a simple yet very useful solution to conquer the aforementioned issues in forensic investigation of cloud systems. Utilizing TPM in hypervisor, implementing multi-factor authentication and updating the cloud service provider policy to provide persistent storage devices are some of the recommended solutions. Utilizing the proposed solutions, the cloud service will be compatible to the current digital forensic investigation practices; alongside it brings the great advantage of being investigable and consequently the trust of the client.


title: Life-Cycle Cost Based Optimal Retrofitting of Structures by Fluid Dampers

abstract: A simulation-based, probabilistic framework is discussed in this paper for design of viscous dampers based on life-cycle cost criteria. This framework allows for explicit consideration in the design process of all important nonlinearities for both the dampers and the structural behavior, as well as of all sources of uncertainty related to the seismic hazard. It is based on an assembly-based vulnerability approach for estimating earthquake losses, and on description of the earthquake hazard through stochastic ground motion models. In this setting, the life-cycle cost is quantified by its expected value over the space of the uncertain parameters for the structural and excitation models, and is estimated through stochastic simulation. For the design-optimization an algorithm appropriate for costly global optimization problems is adopted. An illustrative example is presented that considers the optimal life-cycle based design of fluid viscous dampers for retrofitting a three-story concrete structure.


title: Towards highly reliable enterprise network services via inference of multi-level dependencies

abstract: Localizing the sources of performance problems in large enterprise networks is extremely challenging. Dependencies are numerous, complex and inherently multi-level, spanning hardware and software components across the network and the computing infrastructure. To exploit these dependencies for fast, accurate problem localization, we introduce an Inference Graph model, which is well-adapted to user-perceptible problems rooted in conditions giving rise to both partial service degradation and hard faults. Further, we introduce the Sherlock system to discover Inference Graphs in the operational enterprise, infer critical attributes, and then leverage the result to automatically detect and localize problems. To illuminate strengths and limitations of the approach, we provide results from a prototype deployment in a large enterprise network, as well as from testbed emulations and simulations. In particular, we find that taking into account multi-level structure leads to a 30% improvement in fault localization, as compared to two-level approaches.


title: Flexible isosurfaces: Simplifying and displaying scalar topology using the contour tree

abstract: The contour tree is an abstraction of a scalar field that encodes the nesting relationships of isosurfaces. We show how to use the contour tree to represent individual contours of a scalar field, how to simplify both the contour tree and the topology of the scalar field, how to compute and store geometric properties for all possible contours in the contour tree, and how to use the simplified contour tree as an interface for exploratory visualization.


title: Search Result Diversification in Short Text Streams

abstract: We consider the problem of search result diversification for streams of short texts. Diversifying search results in short text streams is more challenging than in the case of long documents, as it is difficult to capture the latent topics of short documents. To capture the changes of topics and the probabilities of documents for a given query at a specific time in a short text stream, we propose a dynamic Dirichlet multinomial mixture topic model, called D2M3, as well as a Gibbs sampling algorithm for the inference. We also propose a streaming diversification algorithm, SDA, that integrates the information captured by D2M3 with our proposed modified version of the PM-2 (Proportionality-based diversification Method -- second version) diversification algorithm. We conduct experiments on a Twitter dataset and find that SDA statistically significantly outperforms state-of-the-art non-streaming retrieval methods, plain streaming retrieval methods, as well as streaming diversification methods that use other dynamic topic models.


title: Wideband Bandstop Filter With Cross-Coupling

abstract: A general circuit configuration for cross-coupled wideband bandstop filters is proposed. The distinct filtering characteristics of this new type of transmission line filter are investigated theoretically and experimentally. It is shown that a ripple stopband can be created, leading to a quasi-elliptic function response that enhances the rejection bandwidth. A demonstrator with approximately 80% fractional bandwidth at a mid-stopband frequency of 4 GHz is developed and presented. The proposed filter is successfully realized in theory and verified by full-wave electromagnetic simulation and the experiment. Theoretical, simulated, and measured results are in excellent agreement.


title: Minimum entropy-based acoustic source localization with Laplace Distribution

abstract: Accurate and fast localization of acoustic sources is a problem that is of significant interest in applications such as conference systems, gunshot localization systems. Recently, approaches that based on the time difference of arrival(TDOA) are becoming popular, despite the computational expenses. The TDOA localization algorithms contain two parts: the time delay estimation(TDE) algorithms and space search algorithms. The most important TDE algorithms are based on the generalized cross-correlation(GCC) method. These algorithms perform reasonably well when reverberation or noise is not too high. Lots of improved algorithms are proposed, such as SRP-PHAT. In this article, we show that acoustic source localization with Laplace Distribution can be developed on a basis of minimum entropy (ME). For traditional grid search is too expensive for a real-time system, we propose using stochastic region contraction(SRC) to make computing the ME practical. Results from simulation experiences show excellent accuracy of the ME-SRC algorithm.


title: Modofoed Skyhook Control of Semi-Active Suspensions: A New Model, Gain Scheduling, and . . .

abstract: In this paper, a road adaptive modified skyhook control for the semi-active Macpherson strut suspension system of hydraulic type is investigated. A new control-oriented model, which incorporates the rotational motion of the unsprung mass, is introduced. The control law extends the conventional skyhook-groundhook control scheme and schedules its gains for various road conditions. Using the vertical acceleration data measured, the road conditions are estimated by using the linearized new model developed. Two filters for estimating the absolute velocity of the sprung mass and the relative velocity in the rattle space are also designed. The hydraulic semi-active actuator dynamics are incorporated in the hardware-in-the-loop tuning stage of the control algorithm developed. The optimal gains for the ISO road classes are discussed. Experimental results are included. @DOI: 10.1115/1.1434265#


title: Computing Modular Exponentiation for Fixed-Exponent

abstract: Exponentiation is computing ge, where g is an element of a group G and e is a positive integer. In modular exponentiation the underlying group is Zn or Z*n. This paper describe the methods to compute exponentiation where a fixed-exponent e is raised to several bases g of a group G. We describe modular exponentiation based on Bernstein's algorithm for multiplication by constant. We also present a modified approach to modular exponentiation based on k-ary String Replacement (SR(k)) representation.


title: A three-fingered cable-driven gripper for underwater applications

abstract: In this paper, the design and experimental evaluation of a cable driven robotic gripper for underwater applications is presented. The gripper has three fingers and is characterised by a large workspace if compared with other similar devices reported in literature. Its kinematic configuration allows to execute both parallel and precision grasps on objects with very different dimensions. The gripper has 8 degrees of freedom actuated by only three motors by means of a suitable coupling of the joints obtained through the cable transmission. Moreover, in order to facilitate the execution of complex tasks, special force/torque sensors are mounted on the fingertips. The paper reports the main specifications deriving from the particular tasks in which the gripper is involved, and illustrates the proposed design solutions. Results obtained from real underwater experiments are provided as well, in order to demonstrate the capabilities of the gripper.


title: VoxNet: A 3D Convolutional Neural Network for real-time object recognition

abstract: Robust object recognition is a crucial skill for robots operating autonomously in real world environments. Range sensors such as LiDAR and RGBD cameras are increasingly found in modern robotic systems, providing a rich source of 3D information that can aid in this task. However, many current systems do not fully utilize this information and have trouble efficiently dealing with large amounts of point cloud data. In this paper, we propose VoxNet, an architecture to tackle this problem by integrating a volumetric Occupancy Grid representation with a supervised 3D Convolutional Neural Network (3D CNN). We evaluate our approach on publicly available benchmarks using LiDAR, RGBD, and CAD data. VoxNet achieves accuracy beyond the state of the art while labeling hundreds of instances per second.