Miracle-dz/UniFAR-FTUs huggingface dataset:
Reverse link erlang capacity of multiclass CDMA cellular system considering nonideal antenna sectorization

In this paper, the effect of antenna sectorization in the reverse link erlang capacity of a multiclass code-division multiple-access (CDMA) cellular system is studied. Traditionally, it has been considered that the capacity is multiplied by a factor equal to the number of sectors introduced. This is true only in the ideal antenna sectored system. However, due to the nonideal antenna radiation pattern, the sectorization gain is smaller than the number of sectors. Our contribution is the analytical study of the effect of nonideal antenna patterns on the capacity of a multiclass CDMA system. We also present an approximated analysis of the erlang capacity, considering that blocking in CDMA occurs when the interference reaches a predetermined level above the background noise level of mainly thermal origin. The analysis also includes the effects of imperfect power control and service activity detection. We found that the capacity losses due to the consideration of antenna sectorization are about 20.20% for the nonideal antenna radiation pattern and 30.32% for the evaluated commercial radiation pattern. This percentage loss implies that the sectorization gain is approximately 2.39 for a nonideal antenna pattern and 2.09 for a commercial antenna pattern in typical conditions, /spl mu/=4 and /spl alpha/=8 dB.
Supporting mobile applications with information centric networking: the case of P2Plive adaptive video streaming

This paper briefly presents a P2P application for the live streaming of video contents encoded at multiple bit-rates, enabling neighboring cellular devices to increase the quality of video playback, by cooperatively using their cellular (e.g. HSDPA) and proximity (e.g. Wi-Fi Direct) wireless connections. The application is designed to exploit key functionalities of an Information Centric Network: routing-by-name, in-network caching and multicasting. We implemented a prototype of the application and assessed its performance in a test-bed based on Linux, the CCNx tool and real cellular connections.
Social Capital: One or Many? Definition and Measurement

Three families of social capital concepts are discussed: (fa1) trust, (fa2) ease of cooperation, and (fa3) network. In the language of game theory, social capital is the excess propensity to play cooperative solutions in prisoners' dilemma games. The three families lead to different definitions, and thus to different measurement methods. Some measures are theory-near, while others are easy-to-use proxies. It is shown that all definitions and measures are related. The "social capital dream" is that all definitions try to catch aspects of the same phenomenon, so that all measures tap the same latent variable. It is discussed whether this dream is likely to come true. Copyright 2000 by Blackwell Publishers Ltd
High resolution automotive radar measurements of vulnerable road users – pedestrians & cyclists

Several years after successful entry into automotive market radar sensors conquers more and more complex fields of automotive applications like Lane Change Assist or Automatic Emergency Braking systems. Future sensor generations will be challenged by constantly demanding resolution requirements not only determined by consumer rating organizations like EuroNCAP, but also by the challenges induced by highly automated driving features. To satisfy these needs detailed and more accurate information of objects in the vehicle's surrounding and their multi-dimensional extent will be mandatory. To gain information about radar characteristics of pedestrians and cyclists this paper provides measurements captured with a high resolution experimental radar setup. The results are analyzed and the found radar characteristics are discussed in detail, to serve as a basis for future development of sensor hardware and signal processing algorithms.
Loop flexibility in human telomeric quadruplex small-molecule complexes

Quadruplex nucleic acids can be formed at the ends of eukaryotic chromosomes. Their formation and stabilisation by appropriate small molecules can be used as a means of inhibiting the telomere maintenance functions of telomerase in human cancer cells. The crystal structures have been determined for a number of complexes between these small molecules and human telomeric DNA and RNA quadruplexes. The detailed structural characteristics of these complexes have been surveyed here and the variations in conformation for the TTA and UUA loops have been explored. Loop conformations have been classified in terms of a number of discrete types and their distribution among the crystal structures. Sugar conformation and backbone angles have also been examined and trends highlighted. One particular loop class has been found to be most prevalent. Implications for in particular, rational drug design, are discussed.
Journal of Theoretical and Applied Information Technology Frequency Domain Technique for Fault Diagnosis in Analog Circuits-software and Hardware Implementation

In this paper, we present a fault diagnosis system for analog circuit testing based on the Simulation Before Test (SBT) approach. The circuit under test is subjected to a frequency response analysis, from which parameters are extracted such that they give unique values for every configuration of the circuit. This uniqueness makes them ideally suitable for utilization as signatures that may be used to characterize the state of the circuit. Software implementation has been done using MATLAB and SIMULINK, whereas, for the hardware implementation of the system, we have chosen the NI ELVIS platform. In both cases, signatures have been extracted from the frequency response of the circuit (Sallen-Key band pass filter). As most signature values obtained are unique, successful classification of faults is made feasible.
Deterministic versus Stochastic Volatility ∗

This paper provides a testing procedure to discriminate between the classes of deterministic and stochastic volatility models, under minimal assumptions. In particular, apart from standard regularity conditions, no assumptions are made on the functional forms of either the drift or the variance term. Our test is constructed by comparing two estimators of integrated volatility: one is a kernel estimator of the instantaneous variance, averaged over the sample realization on a fixed time span; the other is realized volatility. Under the null hypothesis of a deterministic volatility model, the statistics have a mixed normal limiting distribution, under the alternative diverge at an appropriate rate. Versions of the test robust to jumps and to microstructure noise are also provided. The findings from a Monte Carlo study indicate that the suggested tests have good finite sample properties. An empirical illustration to short term rates is included. Finally, the economic effect on bond pricing of incorrectly choosing deterministic volatility models is quantified.
Tactile interfaces: a state-of-the-art survey

Virtual reality techniques allow one to interact with synthetic worlds, i.e. virtual environments. Tactile feedback means conveying parameters such as roughness, rigidity, and temperature. These information and many others are obtained thanks to the sense of touch. Tactile feedback is of prime importance in many applications. In this paper we examine the state-of-the-art in tactile interfaces design. Thorough reviews of the literature reveal a significant amount of publications concerning tactile human- machine interfaces, especially onwards the ~1990. This paper reports the progress in tactile interfaces technology in the following areas: teleoperation, telepresence, sensory substitution, 3D surface generation, Braille systems, laboratory prototypes, and games. Different parameters and specifications required to generate and feed back tactile sensation are summarized.
Analysing degeneracies in networks spectra

Many real-world networks exhibit a high degeneracy at few eigenvalues. We show that a simple transformation of the network's adjacency matrix provides an understanding to the origins of the occurrence of high multiplicities in the networks spectra. We find that the eigenvectors associated with the degenerate eigenvalues shed light on the structures contributing to the degeneracy. Since these degeneracies are rarely observed in model graphs, we present results for various cancer networks. This approach gives the opportunity to search for structures contributing to degeneracy which might have an important role in a network.
Macroeconomic and Social Change and Popular Demand for Redistribution

This paper tests the self-interest hypothesis arguing that changes in macroeconomic and social conditions affect popular demand for redistribution. I analyze data from four waves of the European Social Survey and use a synthetic cohort design to generate pseudo panel data for socio-demographic groups that are matched over time. I estimate fixed effect models and find that (1) changes in macroeconomic and social conditions affect the demand for redistribution; (2) results are mostly consistent with the self-interest hypothesis claiming that agents demand more redistribution in economically hard times (and vice versa in good times); and (3) the effect of macroeconomic and social conditions on the demand for redistribution are highly non-linear.
Blended Approach: The Convergence of Resilience and Psychoeducation in Science Learning

This paper introduces the "Proud Of Your Own" module (POYO), the Blended Module that combines the academic resilience constructs and the contents of the form four physics subjects contained in the Physics curriculum in Malaysia, the topic of Light and Vision. The purpose of the module development is to improve the academic achievement of the topic as well as the academic resiliency of the students involved through the psychoeducation approach. The POYO module focuses on the promotion and enhancement of academic resilience that can widen the inner strength of the students from four aspects which are social skills, social support, goal efficiencies and planning priority behaviours. The combination of the idea of Social Constructivism theory as proposed by Vygotsky (1978) and the Cultural-ecological transactional Theory by Bronfenbrenner (1979) has been adapted in line with the goal of creating a conducive environment for science learning and student personality development. This paper also discusses the formulation of psychoeducation approaches based on Behaviourism theory. The key elements in the theory are convincing in a psycho-educational approach that can help the subject teachers in and out of the classroom. The development of this module can be a catalyst for the other subjects and helps teachers to practice counselling skills in the classroom through psychoeducation approaches.
Biphasic decay of the Ca transient results from increased sarcoplasmic reticulum Ca leak

Ca leak from the sarcoplasmic reticulum through the ryanodine receptor (RyR) reduces the amplitude of the Ca transient and slows its rate of decay. In the presence of β‐adrenergic stimulation, RyR‐mediated Ca leak produces a biphasic decay of the Ca transient with a fast early phase and a slow late phase. Two forms of Ca leak have been studied, Ca‐sensitising (induced by caffeine) and non‐sensitising (induced by ryanodine) and both induce biphasic decay of the Ca transient. Only Ca‐sensitising leak can be reversed by traditional RyR inhibitors such as tetracaine. Ca leak can also induce Ca waves. At low levels of leak, waves occur. As leak is increased, first biphasic decay and then slowed monophasic decay is seen. The level of leak has major effects on the shape of the Ca transient.
Incorporating Global and Local Knowledge in Intentional Narrative Planning

The inclusion of independent, imperfect knowledge that represents virtual agents' belief of the local state of a narrative planning world has become a key component of narrative generation through simulation of multiple characters. However such models of belief incur significant computational cost. This paper demonstrates that despite the computational complexity, narratives can be generated not only as emergent stories in simulations, but also by global search using Planning that includes a model of differing, independent beliefs. We define a narrative state suitable for planning, detail how it incorporates belief, and how this can be used in an intent-based global search based planning algorithm. Two example narratives are used to illustrate how imperfect belief and social actions can be used in the generation process. The planning algorithm, which integrates global narrative planning with local character level belief reasoning, is fully implemented in a prototype system which was used in the experimental evaluation in which narratives were generated against several objective functions with both global and greedy search. The results show that intent-based planning with belief modelling is able to: generate narratives beyond the reach of planners that have complete knowledge; and also efficiently produce objectively higher quality narratives than those generated by evaluation of only local character knowledge and beliefs.
On noisy source vector quantization via a subspace constrained mean shift algorithm

The subspace constrained mean shift (SCMS) algorithm is an iterative method for finding an underlying manifold associated with an intrinsically low dimensional data set embedded in a high dimensional space. We investigate the application of the SCMS algorithm to the problem of noisy source vector quantization where the clean source needs to be estimated from its noisy observation before quantizing with an optimal vector quantizer. We demonstrate that an SCMS-based preprocessing step can be effective for sources that have intrinsically low dimensionality in situations where clean source samples are unavailable and the system design relies only on noisy source samples for training.
Musical Instrument Classification Based on Improved Matching Pursuit with Instrument-Specific Atoms

Taking advantage of the features that atomic parameters describe the essential characteristics of musical instrument, we propose an improved matching pursuit (MP) algorithm with instrument-specific atoms for musical instrument classification. Firstly, through experiment and mechanism analysis, it is observed that the parameters of atoms from sparse decomposition are closely related and have close ties with the structure and vocal mechanism of each musical instrument. Secondly, an improved matching pursuit algorithm is proposed by analyzing the regularity of the atomic parameters of each specific instrument, which simplifies the extraction process of the scale parameters and narrows the range of the frequency parameters of Gabor atoms in traditional MP algorithm. Finally, the atomic parameters extracted from the improved MP algorithm are fed to the support vector machines (SVMs) for identification and classification. Simulation experimental results show that the time cost of the proposed algorithm is about 1/3 of the traditional one, while the recognition rate only decreases from 89.17% to 87.44%.
Modelling High-Dimensional Time Series by Generalized Linear Dynamic Factor Models: an Introductory Survey

Factor models are used to condense high dimensional data consisting of many variables into a much smaller number of factors. Here we present an introductory survey to factor models for time series, where the factors represent the comovement between the single time series. Principal component analysis, linear dynamic factor models with idiosyncratic noise and generalized linear dynamic factor models are introduced and structural properties, such as identifiability, as well as estimation are discussed.
Requirements for Integrating Defect Prediction and Risk-Based Testing

Defect prediction is a powerful method that provides information about the likely defective parts in software system and is applicable to improve effectiveness and efficiency of software quality assurance. This makes defect prediction a perfect candidate to be combined with risk-based testing to optimally guide testing activities towards risky parts of software. As a first step towards a successful combination, this paper presents requirements that have to be fulfilled for enabling the synergies between defect prediction and risk-based testing.
The Disruptive Potential of Software as a Service: Validation and Application of an Ex-Ante Methodology

We address current discussions on the potential of cloud computing to disrupt the structures of the software industry by selecting, validating and further developing a method for ex-ante identification of disruptive innovations that we imported from innovation management theory into the information systems area. Based on a review of a previous forecast in the area of web applications, we could show that this method was able to predict the likelihood for web applications to pose a minor disruptive threat to incumbents in the industry. Furthermore, we adapted and modified this method and applied it to the cloud computing market through the example of CRM software and the firms Salesforce and SAP. Our results indicate that Salesforce's on-demand software products in the CRM market show a high disruptive potential but at the same time the method also reveals that SAP response strategy limits its possible failure to this disruptive threat.
Joint segmentation of multiple images with shared classes: A Bayesian nonparametrics approach

A combination of the hierarchical Dirichlet process (HDP) and the Potts model is proposed for the joint segmentation/classification of a set of images with shared classes. Images are first divided into homogeneous regions that are assumed to belong to the same class when sharing common characteristics. Simultaneously, the Potts model favors configurations defined by neighboring pixels belonging to the same class. This HDP-Potts model is elected as a prior for the images, which allows the best number of classes to be selected automatically. A Gibbs sampler is then designed to approximate the Bayesian estimators, under a maximum a posteriori (MAP) paradigm. Preliminary experimental results are finally reported using a set of synthetic images.
The critical role of CD40/CD40L in the CD4‐dependent generation of CD8+ T cell immunity

Control of virus infections and eradication of tumors usually involves the lytic activity of CD8+ cytotoxic T lymphocytes (CTLs). The induction of effective CTL immunity relies on several factors, one of the most important of which is CD4+ T cell help. Numerous studies have demonstrated the dependence of CTL priming on the presence of CD4+ T cells, but until recently little was known of the mechanisms regulating this process. Based on reports that CD4+ and CD8+ T cells must recognize antigen on the same antigen‐presenting cell (APC), help was originally thought to be provided through the delivery of short‐range, CD4+ T cell‐secreted cytokines. However, the results of subsequent studies favor an alternative mechanism, whereby CD4+ T cells modify the APC, converting it into a stimulatory cell for CD8+ T cell priming. It is important that CD40 and its ligand, CD40L, have been implicated in the provision of this help and, in particular, the generation of long‐lasting CTL memory. J. Leukoc. Biol. 67: 607–614; 2000.
Monitoring Stealthy Network Conversations with Sampled Traffic

Network conversations—communication patterns between communities of network endpoints—can reveal important information about the nature of applications and about the participants in a particular application. Logging information about network flows can help network operators expose and monitor these conversations, but many large networks apply sampling to traffic monitoring (e.g., “sampled NetFlow”), a technique that potentially obscures these conversations. This paper studies networklevel conversations among botnets, a specific type of network community, as visible in sampled traffic flows. We first characterize the limitations of traffic sampling in exposing these conversations: we compare conversations visible in packet traces of known botnet activity to the same conversations in sampled traffic of two large transit ISPs, each of which uses a different flow sampling rate. We also use controlled experiments to examine the extent to which increasing flow sampling rates beyond the rates commonly used in today’s networks can better expose these communities. The results of our study emphasize that, in many cases, monitoring interesting network conversations (e.g., for network security purposes, monitoring peer-to-peer applications, etc.) will require significant advances in network flow monitoring algorithms.
Instituting the Self-Regulating Consumer: Fake Fighters, Netizens, and Rights’ Defenders in China

ABSTRACT The emergence and evolution of the consumer as a socioeconomic figure developed gradually in Western consumer societies. In the postwar period, consumption became associated with democracy as a means of facilitating social change. This article focuses on China as a case study to explore the formation of the Chinese consumer through marketization in an authoritative context. By examining the development of consumer protection policy, this article highlights the way the state instituted the consumer with a responsibility to facilitate national developments. It also examines the evolution of consumer activism and highlights how consumers strived unsuccessfully to become agents for market governance. Illustrating that a specific type of citizen consumer is instituted in China, this article argues that the consumer is instituted by political interactions and the self-regulating consumer has emerged as a political subject that supports a specific type of market society.
Relating Hierarchy of Linear Temporal Properties to Model Checking

The hierarchy of properties as overviewed by Manna and Pnueli [23] relates language, topology, ω-automata, and linear temporal logic classifications of properties. We provide new characterisations of this hierarchy in terms of automata with Büchi, co-Büchi, and Streett acceptance condition and in terms of Σ i and Π LTL i hierarchies. Afterwards, we analyse the complexity of the model checking problem for particular classes of the hierarchy and thanks to the new characterisations we identify those linear time temporal properties for which the model checking problem can be solved more efficiently than in the general case.
RGB-D sensor-based visual SLAM for localization and navigation of indoor mobile robot

To increase the localization accuracy of the moving service robot in restaurant, A localization method and a landmark recognition method based on RGB and depth (RGB-D) vision sensor is presented. Based on the landmarks, we utilized an Extend Kalman Filter(EKF) method to calculate robot position and pose. The path planning approach based on a differential-flatness point-to-point trajectory planning is proposed for the robot. There are kinds of control manners which improved the enjoyment of human-machine interface, such as mobile client and voice control. Finally, the proposed methods have been verified to be effective and feasible by experiment in indoor environments.