Miracle-dz/UniFAR-FTUs huggingface dataset:
Random neighbour-based fault localization

In the large-scale network, the router acts an increasingly important role but the malicious behaviours including packets dropping and corruption of the malicious routers harm the performance of the network. Actually, many work has been proposed to locate the potential failure nodes but they all suffer from some issues of performance and scalability, which are not practical for the network environment. To deal with these problems, we introduce random neighbour-based fault localization (RNFL). It utilizes neighbourhood nodes and message authentication code (MAC) to check the integrity of packets so that RNFL can detect the malicious nodes. Besides, it supports dynamic routing and the experiment shows that it only puts small extra computing burden (less than 10%) on the network routers.
Reading Statistics and Research (5th ed.)

The users of this book can be teachers of measurement, research, and statistics courses. Also, this book can be valuable to researchers and consumers of research as a reference. The book is written with an easy-to-understand explanation of a variety of topics and techniques used in research. There are no formulas or computational examples to confuse a person who just wants to know what a technique is or the basic information about a topic. There are review terms, items in the companion website, and exercises inside Research Navigator at the end of each chapter. Chapter 1 explains the typical format of a journal article. This chapter familiarizes the reader with what to expect to see in any journal article. To some degree, Chapter 1 lays the ground work for the rest of the book. Chapters 2 and 3 are about descriptive statistics and bivariate correlation. Graphs, measures of central tendency, measures of variability, standard scores, the correlation coefficient, and different kinds of correlational procedures are covered in these chapters. Chapter 4 is on reliability and validity. Both terms are well-defined, and different approaches to estimating reliability and validity are presented. The author’s comments at the end of the chapter are excellent and quite practical. Chapter 5 covers foundations of inferential statistics. Here is where the concept of inference and sampling techniques is presented. Some common problems in sampling are addressed, such as low response rate and attrition. This chapter lays the groundwork for many of the later chapters.
A Comparative Study of Real-Time Implementable Cooperative Aerial Manipulation Systems

This survey paper focuses on quadrotor- and multirotor- based cooperative aerial manipulation. Emphasis is first given on comparing and evaluating prototype systems that have been implemented and tested in real-time in diverse application environments. Underlying modeling and control approaches are also discussed and compared. The outcome of the survey allows for understanding the motivation and rationale to develop such systems, their applicability and implementability in diverse applications and also challenges that need to be addressed and overcome. Moreover, the survey provides a guide to develop the next generation of prototype systems based on preferred characteristics, functionality, operability and application domain.
Optimal Transport for Domain Adaptation through Gaussian Mixture Models

In this paper we explore domain adaptation through optimal transport. We propose a novel approach, where we model the data distributions through Gaussian mixture models. This strategy allows us to solve continuous optimal transport through an equivalent discrete problem. The optimal transport solution gives us a matching between source and target domain mixture components. From this matching, we can map data points between domains, or transfer the labels from the source domain components towards the target domain. We experiment with 2 domain adaptation benchmarks in fault diagnosis, showing that our methods have state-of-the-art performance.
XMapGen and XMapSiG results for OAEI 2013

The XMapGen and XMapSig systems are flexible and self-configuring matching tools using different strategies for combining multiple similarity measures into a single aggregated metric with the final aim of improving the ontology alignment quality of large scale ontologies. XMapGen and XMapSig are two variants of XMap++. The results obtained by the two ontology matching tools within the 9th edition of the Ontology Alignment Evaluation Initiative (OAEI 2013) campaign are therefore presented.
T Cell-Mediated Beta Cell Destruction: Autoimmunity and Alloimmunity in the Context of Type 1 Diabetes

Type 1 diabetes (T1D) results from destruction of pancreatic beta cells by T cells of the immune system. Despite improvements in insulin analogs and continuous blood glucose level monitoring, there is no cure for T1D, and some individuals develop life-threatening complications. Pancreas and islet transplantation have been attractive therapeutic approaches; however, transplants containing insulin-producing cells are vulnerable to both recurrent autoimmunity and conventional allograft rejection. Current immune suppression treatments subdue the immune system, but not without complications. Ideally a successful approach would target only the destructive immune cells and leave the remaining immune system intact to fight foreign pathogens. This review discusses the autoimmune diabetes disease process, diabetic complications that warrant a transplant, and alloimmunity. First, we describe the current understanding of autoimmune destruction of beta cells including the roles of CD4 and CD8 T cells and several possibilities for antigen-specific tolerance induction. Second, we outline diabetic complications necessitating beta cell replacement. Third, we discuss transplant recognition, potential sources for beta cell replacement, and tolerance-promoting therapies under development. We hypothesize that a better understanding of autoreactive T cell targets during disease pathogenesis and alloimmunity following transplant destruction could enhance attempts to re-establish tolerance to beta cells.
Effects of Metformin on Body Weight and Body Composition in Obese Insulin-Resistant Children

OBJECTIVE Metformin can decrease adiposity and ameliorate obesity-related comorbid conditions, including abnormalities in glucose homeostasis in adolescents, but there are few data evaluating the efficacy of metformin among younger children. Our objective was to determine whether metformin treatment causes weight loss and improves obesity-related comorbidities in obese children, who are insulin-resistant. RESEARCH DESIGN AND METHODS This study was a randomized double-blind placebo-controlled trial consisting of 100 severely obese (mean BMI 34.6 ± 6.6 kg/m2) insulin-resistant children aged 6–12 years, randomized to 1,000 mg metformin (n = 53) or placebo (n = 47) twice daily for 6 months, followed by open-label metformin treatment for 6 months. All children and their parents participated in a monthly dietitian-administered weight-reduction program. RESULTS Eighty-five percent completed the 6-month randomized phase. Children prescribed metformin had significantly greater decreases in BMI (difference −1.09 kg/m2, CI −1.87 to −0.31, P = 0.006), body weight (difference −3.38 kg, CI −5.2 to −1.57, P < 0.001), BMI Z score (difference between metformin and placebo groups −0.07, CI −0.12 to −0.01, P = 0.02), and fat mass (difference −1.40 kg, CI −2.74 to −0.06, P = 0.04). Fasting plasma glucose (P = 0.007) and homeostasis model assessment (HOMA) insulin resistance index (P = 0.006) also improved more in metformin-treated children than in placebo-treated children. Gastrointestinal symptoms were significantly more prevalent in metformin-treated children, which limited maximal tolerated dosage in 17%. During the 6-month open-label phase, children treated previously with placebo decreased their BMI Z score; those treated continuously with metformin did not significantly change BMI Z score further. CONCLUSIONS Metformin had modest but favorable effects on body weight, body composition, and glucose homeostasis in obese insulin-resistant children participating in a low-intensity weight-reduction program.
Ray Theory of Waves

In order to deal with the interaction of an electromagnetic wave with large homogeneous objects of arbitrary shape with smooth surface we develop the ray theory of waves (RTW) which is composed of the vectorial complex ray model (VCRM) and VCRM based singularity theory. By introducing the wavefront curvature as an intrinsic property of rays, VCRM permits to predict the amplitude and the phase of field at any point rigorously in the sense of ray model. Its combination with the singularity theory remedies the discontinuity in the ray model. In this letter, the wavefront equation, key physical law of VCRM describing the relation between the wavefront curvatures of the incident wave and the refracted/reflected wave, is derived for the most general case of three dimension scattering. The strategy of the calculation scheme in RTW is described. Typical applications to the prediction of the rainbow patterns of a spheroidal drop are presented. The comparison to a rigorous numerical method, multilevel fast multipole algorithm, shows that RTW can predict very fast and precisely the scattered field even in the vicinity of caustics.
Deriving Interventions on the Basis of Factors Influencing Behavioral Intentions for Waste Recycling, Composting, and Reuse in Cuba

In this article the authors study existing waste-disposal intentions and behavior-influencing factors at the household level in Santiago de Cuba. The authors analyze the perceived reputation of the behavior, two different attitude components (sentiment and cost-value ratio), and perceived difficulties. Our focus is to compare three types of waste-disposal behaviors and derive specific interventions. The behaviors most suitable to Cuba are recycling, composting, and reuse. Analysis with structural equation modeling (SEM) reveals relevant differences in factor influence for attitude components and perceived reputation. Recycling and composting are most strongly influenced by affective aspects of attitude, whereas the general attitude toward reuse seems to have a more rational basis. The influence of perceived reputation on recycling is strong, that on composting is moderate, and no influence at all is found for reuse. The authors combine the SEM results with those of the qualitative data analysis of problems and incentives assessed from the participants and suggest behavior-specific interventions.
Evolution of Strategies for ResourceProtection ProblemsWilliam

The objective of this project is to develop eeective nite-state machine (FSM) strategies for winning against an adversary in a Competition for Resources simulation. To achieve this goal, we evolve these strategies in a simulated environment and compare a variety of evolutionary methods in this context. Key empirical questions are addressed, such as how many FSM states are optimal, how eeective is it to use an evolutionary algorithm that adapts the number of states, and how can one reduce the variance in tness evaluation? Some of our experimental answers to these questions are quite intriguing. This paper also explores and evaluates novel algorithms for detecting and repairing deleterious cycles in the evolved FSMs.
Gesture as model enactment: the role of gesture in mental model construction and inference making when learning from text

The question of the relationship between gesture production and mental models was explored in three experiments focusing on inference making when learning from reading a scientific text. Participants engaged in one-on-one interviews after reading an illustrated tutorial on the human circulatory system. Participants gestured more frequently when responding to mental model-based inference test questions (Experiment 1; N = 22) than textbase or general knowledge questions. Learning from a text lacking illustrations resulted in comparable inference making (Experiment 2; N = 48) but elevated gest ure production. Restricting gesture production with hand tapping led to inferior inference making (Experiment 3; N = 79). Results support an embodied cognition view of mental model formation where inference making stimulates gesture production, and restricting gestures selectively impairs inference making. The results are interpreted within the Gesture as Model Enactment (GAME) framework. Activation of motor control systems via gesture support simulated actions that contribute to mental model formation. Implications for learning and assessing knowledge are explored.
Mobile offloading game against smart attacks

Mobile cloud computing enables mobile devices such as smartphones to offload data to clouds via access points or base stations to reduce energy consumption and improve their user experience. However, mobile offloading is vulnerable to smart attackers that can exploit software defined radios to perform multiple types of attacks, such as spoofing and jamming, based on the status of radio environments and the offloading process. In this paper, a mobile offloading game against smart attacks, in which a mobile device chooses its offloading rate, a smart attacker chooses the type of its attack, and a security agent decides whether to initiate full data protection for the offloading, is investigated. The interactions among a mobile device, a smart attacker and a security agent are formulated as a secure mobile offloading game. The Nash equilibrium (NE) and its existence conditions are provided for the static secure offloading game. A Q-learning based mobile offloading strategy is proposed for dynamic environments to address smart attacks, in which the mobile device is unaware of the system parameters. Simulation results show that the proposed offloading strategy improves both the offloading rate and the security performance.
Stability of ferromagnetism in the half-metallic pnictides and similar compounds: a first-principles study

Based on first-principles electron structure calculations and employing the frozen-magnon approximation, we study the exchange interactions in a series of transition-metal binary alloys crystallizing in the zinc-blende structure and calculate the Curie temperature within both the mean-field approximation and random-phase approximation. We study two Cr compounds, CrAs and CrSe, and four Mn compounds, MnSi, MnGe, MnAs and MnC. MnC, MnSi and MnGe are isovalent to CrAs and MnAs is isoelectronic to CrSe. Ferromagnetism is particular stable for CrAs, MnSi and MnGe: all three compounds show Curie temperatures around 1000 K. On the other hand, CrSe and MnAs show a tendency to antiferromagnetism when compressing the lattice. In MnC the half-metallic gap is located in the majority-spin channel, in contrast to the other five compounds. The large half-metallic gaps, very high Curie temperatures, the stability of the ferromagnetism with respect to the variation of the lattice parameter and a coherent growth on semiconductors make MnSi and CrAs the most promising candidates for use in spintronics devices.
On secure outsourcing of cryptographic computations to cloud

For the past few years, research works on the topic of secure outsourcing of cryptographic computations has drawn significant attention from academics in security and cryptology disciplines as well as information security practitioners. One main reason for this interest is their application for resource constrained devices such as RFID tags. While there has been significant progress in this domain since Hohenberger and Lysyanskaya have provided formal security notions for secure computation delegation, there are some interesting challenges that need to be solved that can be useful towards a wider deployment of cryptographic protocols that enable secure outsourcing of cryptographic computations. This position paper brings out these challenging problems with RFID technology as the use case together with our ideas, where applicable, that can provide a direction towards solving the problems.
Traditional Mediterranean diet and longevity in the elderly: a review

Abstract Objective: To review the evidence that the traditional Mediterranean diet is associated with longevity. Setting: Elderly persons of both genders in Greece, Spain, Denmark and Australia studied by different groups of investigators. Methods: Adherence to the principles of the Mediterranean diet was operationalised through a score devised a priori, and study participants were followed up until death or the end of the study. Proportional hazard models were used. Results: Closer adherence to the Mediterranean diet was associated with a significant decrease in general mortality among the elderly persons studied. Conclusion: The Mediterranean diet is positively associated with longevity among the elderly. If the assumption holds that there is no interaction between age and diet with respect to general mortality, it can be inferred that the traditional Mediterranean diet represents a healthy nutritional pattern.
1-bit Hamming compressed sensing

Compressed sensing (CS) and 1-bit CS cannot directly recover quantized signals preferred in digital systems and require time consuming recovery. In this paper, we introduce 1-bit Hamming compressed sensing (HCS) that directly recovers a k-bit quantized signal of dimension n from its 1-bit measurements via invoking n times of Kullback-Leibler divergence based nearest neighbor search. Compared to CS and 1-bit CS, 1-bit HCS allows the signal to be dense, takes considerably less (linear and non-iterative) recovery time and requires substantially less measurements. Moreover, 1-bit HCS can accelerate 1bit CS recover. We study a quantized recovery error bound of 1-bit HCS for general signals. Extensive numerical simulations verify the appealing accuracy, robustness, efficiency and consistency of 1-bit HCS.
A Mathematical Formalization of Hierarchical Temporal Memory Cortical Learning Algorithm's Spatial Pooler

Hierarchical temporal memory (HTM) is an emerging machine learning algorithm, with the potential to provide a means to perform predictions on spatiotemporal data. The algorithm, inspired by the neocortex, currently does not have a comprehensive mathematical framework. This work brings together all aspects of the spatial pooler (SP), a critical learning component in HTM, under a single unifying framework. The primary learning mechanism is explored, where a maximum likelihood estimator for determining the degree of permanence update is proposed. The boosting mechanisms are studied and found to be only relevant during the initial few iterations of the network. Observations are made relating HTM to well known algorithms such as competitive learning and attribute bagging. Methods are provided for using the SP for classification as well as dimensionality reduction. Empirical evidence verifies that given the proper parameterizations, the SP may be used for feature learning.
Formation control of unicycle mobile robots: a virtual structure approach

In this paper, the formation control problem for unicycle mobile robots is studied. A virtual structure control strategy with mutual coupling between the robots is proposed. The rationale behind the introduction of the coupling terms is the fact that these introduce additional robustness with respect to perturbations as compared to typical leader-follower approaches. The applicability of the proposed approach is shown in experiments with a group of mobile robots controlled over a wireless communication network.
Assessment of Spectral Band Impact on Intercalibration Over Desert Sites Using Simulation Based on EO-1 Hyperion Data

Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.
Image sensor data fusion using factorized Kalman filter

This paper presents image sensor data fusion strategy using factorized Kalman filter algorithm which has wide range of aerospace applications. This involves locating the target from the images obtained from the two sensors using Centroid tracking Factorized Kalman filter and then fusing the sensor data to get much better information of the target position and velocity. Factorized Kalman filter or UD filter (UDF) is used for predicting the upcoming position and other variables of the target. Fusion is used to reduce the error that occurs due to clutters in image data taken from sensors. Performance of two fusion algorithms that is measurement or data level fusion and state vector fusion are carried out and good results are obtained regarding the position and velocity estimation of the target. Image sensor data fusion (ISDF) is realized using MATLAB tool. The sensor images are synthesized and added with different noise levels in order to represent sensor data obtained in the presence of different atmospheric clutter. Segmentation process and nearest neighbor technique is used to extract the target details from the sensor images.
UIR-PKU: Twitter-OpinMiner System for Sentiment Analysis in Twitter at SemEval 2015

Microblogs are considered as We-Media information with many real-time opinions. This paper presents a Twitter-OpinMiner system for Twitter sentiment analysis evaluation at SemEval 2015. Our approach stems from two different angles: topic detection for discovering the sentiment distribution on different topics and sentiment analysis based on a variety of features. Moreover, we also implemented intra-sentence discourse relations for polarity identification. We divided the discourse relations into 4 predefined categories, including continuation, contrast, condition, and cause. These relations could facilitate us to eliminate polarity ambiguities in compound sentences where both positive and negative sentiments are appearing. Based on the SemEval 2014 and SemEval 2015 Twitter sentiment analysis task datasets, the experimental results show that the performance of Twitter-OpinMiner could effectively recognize opinionated messages and identify the polarities.