Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaker Recognition Using Artificial Neural Networks : RBFNNs vs

This paper deals with the application of Radial Basis Function Neural Networks (RBFNNs) and Elliptical Basis Function Neural Networks (EBFNNs) for textindependent speaker recognition experiments. These include both closed-set and open-set speaker identification and speaker verification. The database used is a subset of the TIMIT database consisting of 60 speakers from different dialect regions. LP-derived Cepstral Coefficients (LPCC) are used as the speaker specific features. Simulation results show that EBFNN outperform RBFNN for several speaker recognition experiments. KeywordsSpeaker recognition, speaker identification, speaker verification, Radial Basis Function Neural Networks (RBFNNs), Elliptical Basis Function Neural Networks (EBFNNs).
Université de Montréal at the NTCIR-11 IMine Task

In this paper, we describe our participation to the NTCIR-11 IMine task, for both subtopic mining and document ranking sub-tasks. We experimented a new approach for aspect embedding which learns query aspects by selecting (good) expansion terms from a set of resources. In our participation, we used ve representative resources: ConceptNet, Wikipedia, query logs, feedback documents and query suggestions from Bing, Google and Yahoo! Our method is trained in a supervised manner according to the principle that related terms should correspond to the same aspects. We tested our approach when using a single resource, and when using dierent resources. Experimental results show that our best document ranking run is ranked No. 2 of all 15 runs in terms of coarse-grain and ne-grain results.
Dynamic reorganisation of intermediate filaments coordinates early B-cell activation

This study examines the role of vimentin, a type III intermediate filament, in B-cell function using a combination of in vitro and in vivo assays, including super-resolution microscopic techniques. During B-cell activation, the dynamic reorganisation of the cytoskeleton is crucial for multiple cellular responses, such as receptor signalling, cell spreading, antigen internalisation, intracellular trafficking, and antigen presentation. However, the role of intermediate filaments (IFs), which represent a major component of the mammalian cytoskeleton, is not well defined. Here, by using multiple super-resolution microscopy techniques, including direct stochastic optical reconstruction microscopy, we show that IFs in B cells undergo drastic reorganisation immediately upon antigen stimulation and that this reorganisation requires actin and microtubules. Although the loss of vimentin in B cells did not impair B-cell development, receptor signalling, and differentiation, vimentin-deficient B cells exhibit altered positioning of antigen-containing and lysosomal associated membrane protein 1 (LAMP1+) compartments, implying that vimentin may play a role in the fine-tuning of intracellular trafficking. Indeed, vimentin-deficient B cells exhibit impaired antigen presentation and delayed antibody responses in vivo. Thus, our study presents a new perspective on the role of IFs in B-cell activation.
Towards empirically validated software architecture visualization

Visualization is a sound means to facilitate understanding of complex correlations and offers a broad variety of concepts. A problem with the visualization of software architectures is that there are almost no empirical evidences of the benefits of particular visualization concepts. That is why we introduce an approach that explicitly integrates architecture development with the selection, use and validation of visualization metaphors. We successfully applied this approach to realize our software architecture visualization tool and empirically validated the use of the visualization concepts in the software architecture domain. We claim that software architecture visualizations should always be thoroughly assessed, especially by software architects in an industrial environment.
A semantics-based approach to malware detection

Malware detection is a crucial aspect of software security. Current malware detectors work by checking for signatures, which attempt to capture the syntactic characteristics of the machine-level byte sequence of the malware. This reliance on a syntactic approach makes current detectors vulnerable to code obfuscations, increasingly used by malware writers, that alter the syntactic properties of the malware byte sequence without significantly affecting their execution behavior. This paper takes the position that the key to malware identification lies in their semantics. It proposes a semantics-based framework for reasoning about malware detectors and proving properties such as soundness and completeness of these detectors. Our approach uses a trace semantics to characterize the behavior of malware as well as that of the program being checked for infection, and uses abstract interpretation to “hide” irrelevant aspects of these behaviors. As a concrete application of our approach, we show that (1) standard signature matching detection schemes are generally sound but not complete, (2) the semantics-aware malware detector proposed by Christodorescu et al. is complete with respect to a number of common obfuscations used by malware writers and (3) the malware detection scheme proposed by Kinder et al. and based on standard model-checking techniques is sound in general and complete on some, but not all, obfuscations handled by the semantics-aware malware detector.
Efficient simulations of long wave propagation and runup using a LBM approach on GPGPU hardware

We present an efficient implementation of the Lattice Boltzmann method (LBM) for the numerical simulation of the propagation of long ocean waves (e.g., tsunamis), based on the Nonlinear Shallow Water (NSW) wave equation. The LBM solution of NSW equations is fully nonlinear and it is assumed that the surface elevation is single-valued (hence, waves do not break or overturn). For the treatment of wet-dry states, a simple shoreline step-slot algorithm is used. The NVIDIA CUDA framework is used for the implementation, which gives access to the computational power of General Purpose Graphical Processing Units (GPGPUs). The initial analysis of LBM results for standard analytical benchmark problems shows a good agreement with the reference solutions. For all benchmarks, the run times of the numerical simulations are on the same order as the time scale of the real world event, or even less. The presented applications include wave runup studies on a plane beach and a more complex three-dimensional beach, as proposed in the tsunami community as part of the so-called Catalina(Liu et al., 2008) and PMEL sets of benchmark problems. Finally, the results and the performance of the LBM solver are compared to those of the Boussinesq solver FUNWAVE.
Abstract: Mapping Streaming Applications onto GPU Systems

We describe an efficient and scalable code generation framework that automatically maps general purpose streaming applications onto GPU systems. This architecture-driven framework takes into account the idiosyncrasies of the GPU pipeline and the unique memory hierarchy. The framework has been implemented as a back-end to the StreamIt programming language compiler. Several key features in this framework ensure maximized performance and scalability. First, the generated code increases the effectiveness of the on-chip memory hierarchy by employing a heterogeneous mix of compute and memory access threads. Our scheme goes against the conventional wisdom of GPU programming which is to use a large number of homogeneous threads. Second, we utilise an efficient stream graph partitioning algorithm to handle larger applications and achieve the best performance under the given on-chip memory constraints. Lastly, the framework maps complex applications onto multiple GPUs using a highly effective pipeline execution scheme. Our comprehensive experiments show its scalability and significant speedup compared to a state-of-the-art solution.
Modeling stress strain curves for lead-free 95.5Sn-3.8Ag-0.7Cu solder

Mechanics of materials characterization of lead-free solder mechanical properties and stress strain curve properties are needed for applications in finite element analysis. In this study, tensile properties for lead-free 95.5Sn-3.8Ag-0.7Cu solder alloy were obtained from bulk tensile specimen tests. A modified Ramberg-Osgood model was developed to describe the temperature and strain rate dependent stress-strain curves for the solder alloys. The modified Ramberg-Osgood model is able to predict the temperature and strain rate effects on the stress-strain properties for lead free 95.5Sn-3.8Ag-0.7Cu solder alloy. Comparison between the proposed modified Ramberg-Osgood model and the Anand viscoplastic model is made in predicting the stress-strain data obtained from the constant strain rate tensile tests.
Infrared beacon based sub-meter indoor localization

In this work a high precision sub-meter accuracy indoor localization system was developed using low cost infrared (IR) transmitters and receivers. With the help of the optical lenses and orienting mechanisms designed for the IR beacons, at about 0,75 m wide grid zone definitions could be achieved. An FPGA is armed for the evaluation of the data from multiple IR receivers at the mobile user. 0,5 m accuracy levels and 2 Hz update rates could be reached by this technique. After the test results, it has been shown that the system can reach the %88,3 precision level.
A measure of adjusted difference between values of a variable

Both during academic work and everyday life it is usual to come across such situations, where one has to compute the difference between values of a variable. However, this can be done many ways. For example, the comparison of accuracy values of methods for the solution of a scientific problem is usually done by either looking at how much the absolute difference between the two accuracies in percentage points is, how much their relative difference in percentages is, or how much the relative difference between the two error rates in percentages is. The problem is that these different methods usually give different results, often suggesting contradicting conclusions. To overcome this problem I propose a novel measure to compute an adjusted difference ( ) between values of a variable to represent their difference in a better and uniform way, replacing the collection of the previously used conventional measures, and show how the properties of this new measure are superior to those of the other measures.
Attention Allocation , and Learning

A large body of evidence supports the importance of focused attention for encoding and task performance. Yet young children with immature regulation of focused attention are often placed in elementary-school classrooms containing many displays that are not relevant to ongoing instruction. We investigated whether such displays can affect children’s ability to maintain focused attention during instruction and to learn the lesson content. We placed kindergarten children in a laboratory classroom for six introductory science lessons, and we experimentally manipulated the visual environment in the classroom. Children were more distracted by the visual environment, spent more time off task, and demonstrated smaller learning gains when the walls were highly decorated than when the decorations were removed.
Farmer attitudes and preferences regarding a hypothetical lease hunting policy in Saskatchewan

ABSTRACT Lease hunting, as a market-based policy instrument, can introduce monetary incentives to farmers to provide wildlife habitat. This article investigated farmer attitudes toward the introduction of a hypothetical lease hunting policy within a jurisdiction where there is significant demand for recreational hunting on private land but lease hunting is currently not legal. Farmers were evenly split between supporting and failing to support the introduction of lease hunting and indicated that liability and control of access were important lease contract characteristics. A probit model indicated farmer support was influenced by the quantity of land they rented, their experience with previous hunter access and their perceptions of the size of resident wildlife populations. A tobit model showed how farmer perceptions on the quantity of wildlife and the quantity of rented land influenced the magnitude of the monetary payment they would be willing to accept to permit hunter access to their land.
Propofol and AZD3043 Inhibit Adult Muscle and Neuronal Nicotinic Acetylcholine Receptors Expressed in Xenopus Oocytes

Propofol is a widely used general anaesthetic with muscle relaxant properties. Similarly as propofol, the new general anaesthetic AZD3043 targets the GABAA receptor for its anaesthetic effects, but the interaction with nicotinic acetylcholine receptors (nAChRs) has not been investigated. Notably, there is a gap of knowledge about the interaction between propofol and the nAChRs found in the adult neuromuscular junction. The objective was to evaluate whether propofol or AZD3043 interact with the α1β1δε, α3β2, or α7 nAChR subtypes that can be found in the neuromuscular junction and if there are any differences in affinity for those subtypes between propofol and AZD3043. Human nAChR subtypes α1β1δε, α3β2, and α7 were expressed into Xenopus oocytes and studied with an automated voltage-clamp. Propofol and AZD3043 inhibited ACh-induced currents in all of the nAChRs studied with inhibitory concentrations higher than those needed for general anaesthesia. AZD3043 was a more potent inhibitor at the adult muscle nAChR subtype compared to propofol. Propofol and AZD3043 inhibit nAChR subtypes that can be found in the adult NMJ in concentrations higher than needed for general anaesthesia. This finding needs to be evaluated in an in vitro nerve-muscle preparation and suggests one possible explanation for the muscle relaxant effect of propofol seen during higher doses.
Taurine detected using high-resolution magic angle spinning 1H nuclear magnetic resonance: A potential indicator of early myocardial infarction

Magnetic resonance spectroscopy (MRS) is a unique non-invasive method for detecting cardiac metabolic changes. However, MRS in cardiac diagnosis is limited due to insensitivity and low efficiency. Taurine (Tau) is the most abundant free amino acid in the myocardium. We hypothesized that Tau levels may indicate myocardial ischemia and early infarction. Sprague-Dawley rats were divided into seven groups according to different time points during the course of myocardial ischemia, which was induced by left anterior descending coronary artery ligation. Infarcted myocardial tissue was obtained for high-resolution magic angle spinning 1H nuclear magnetic resonance (NMR) analysis. Results were validated via high-performance liquid chromatography. The Tau levels in the ischemic myocardial tissue were reduced significantly within 5 min compared with those in the control group (relative ratio from 20.27±6.48 to 8.81±0.04, P<0.05) and were maintained for 6 h post-ischemia. Tau levels declined more markedly (56.5%) than creatine levels (48.5%) at 5 min after ligation. This suggests that Tau may have potential as an indicator in the early detection of myocardial ischemia by 1H MRS.
The partial-occlusion effect: utilizing semitransparency in 3D human-computer interaction

This study investigates human performance when using semitransparent tools in interactive 3D computer graphics environments. The article briefly reviews techniques for presenting depth information and examples of applying semitransparency in computer interface design. We hypothesize that when the user moves a semitransparent surface in a 3D environment, the “partial-occlusion” effect introduced through semitransparency acts as an effective cue in target localization—an essential component in many 3D interaction tasks. This hypothesis was tested in an experiment in which subjects were asked to capture dynamic targets (virtual fish) with two versions of a 3D box cursor, one with and one without semitransparent surfaces. Results showed that the partial-occlusion effect through semitransparency significantly improved users' performance in terms of trial completion time, error rate, and error magnitude in both monoscopic and stereoscopic displays. Subjective evaluations supported the conclusions drawn from performance measures. The experimental results and their implications are discussed, with emphasis on the relative, discrete nature of the partial-occlusion effect and on interactions between different depth cues. The article concludes with proposals of a few future research issues and applications of semitransparency in human-computer interaction.
Facial Signs and Psycho-physical Status Estimation for Well-being Assessment

Stress and anxiety act as psycho-physical factors that increase the risk of developing several chronic diseases. Since they appear as early indicators, it is very important to be able to perform their evaluation in a contactless and non-intrusive manner in order to avoid inducing artificial stress or anxiety to the individual in question. For these reasons, this paper analyses the methodologies for the extraction of respective facial signs from images or videos, their classification and techniques for coding these signs into appropriate psycho-physical statuses. A review of existing datasets for the assessment of the various methodologies for facial expression analysis is reported. Finally, a short summary of the most interesting findings in the various stages of the procedure are indicated with the aim of achieving new contactless methods for the promotion of an individualâs well-being.
Describing Relational Thinking Process of Junior High School Students with High Capability

Learning mathematics in Junior High School is transition from arithmetic to algebra. In algebra, students must develop a relational view of the symbol if they are to make any sense of more complicated equations with operations on both sides of the equal sign. The term relational thinking is used here to encompass more than a relational understanding of the equal sign. It is important to discuss students’ relational thinking process when solving unknown number on mathematic sentences, so it can prevents students’ misconception about the meaning of equal sign. Descriptive method was used in this study, involving five students of Junior High School in Boyolali with high capability in mathematics. The result of this study showed that students had a deep understanding about the meaning of equal sign. They knew that the equal sign as symbol of mathematical equivalence. Therefore, they were able to solve the mathematic sentences with relational thinking strategies rather than arithmetic procedures. Keywords—relational thinking, equivalence, equal sign
Convergence Properties of a Gradual Learning Algorithm for Harmonic Grammar

This chapter investigates a gradual on-line learning algorithm for Harmonic Grammar. By adapting existing convergence proofs for perceptrons, we show that for any nonvarying target language, Harmonic-Grammar learners are guaranteed to converge to an appropriate grammar, if they receive complete information about the structure of the learning data. We also prove convergence when the learner incorporates evaluation noise, as in Stochastic Optimality Theory. Computational tests of the algorithm show that it converges quickly. When learners receive incomplete information (e.g. some structure remains hidden), tests indicate that the algorithm is more likely to converge than two comparable Optimality-Theoretic learning algorithms.
Flight testing of trajectories computed by G-FOLD: Fuel optimal large divert guidance algorithm for planetary landing

G-FOLD, Guidance for Fuel Optimal Large Divert, is an algorithm that is developed to compute, onboard in real-time, fuel optimal trajectories for large divert maneuvers necessary for planetary pinpoint or precision landing. The algorithm incorporates all relevant mission constraints and computes the global optimal trajectory. It is based on a mathematical result known as “lossless convexification” of the associated optimal control problem, which allowed us to formulate the problem as a convex optimization problem and to guarantee obtaining the global optimal solution when a feasible solution exists. Hence the algorithm ensures that all physically achievable diverts are also computable in real-time. This paper reports the first three flight test results of G-FOLD generated trajectories. The goal of these tests were to test pre-flight computed G-FOLD trajectories to demonstrate that they are computed with relevant mission constraints and appropriate vehicle dynamics accounted for. The results showed good agreement with the desired ideal trajectories with mismatches below expected bounds, which validated that the desired outcome that the trajectories were computed by using the right problem description and the resulting trajectories are flyable.
Metric Based Recommender Systems

Information overload and an abundance of choices create situations where selecting one option becomes extremely difficult or even worse, a guessing game. Collaborative ranking systems address this problem by creating intelligent rankings of items based on user opinions aggregation. This paper presents a metric-based multi-criteria recommender system that can be used on non-rigid sets of criteria. These systems fare well with respect to accuracy, transparency and flexibility.
GPU accelerated fast FEM deformation simulation

In this paper we present a general FEM (finite element method) solution that enables fast dynamic deformation simulation on the newly available GPU (graphics processing unit) hardware with compute unified device architecture (CUDA) from NVIDIA. CUDA-enabled GPUs harness the power of 128 processors which allow data parallel computations. Compared to the previous GPGPU, it is significantly more flexible with a C language interface. We not only implement FEM deformation computation algorithms with CUDA but also analyze the performance in detail. Our test results indicate that the GPU with CUDA enables about 4 times speedup for FEM deformation computation on an Intel(R) Core 2 Quad 2.0 GHz machine with GeForce 8800 GTX.
AUTONOMIC COMPUTING: TOWARDS SELF-HEALING SYSTEM

from past two decades, we have seen ballooning amount of growth in internet usage and information. With this there is simultaneous explosion in amount of data being processed every minute, and technologies being invented. All these enhancements steered us towards unprecedented levels of complexities. To manage this complex system, there was a call for a paradigm which can configure the system i.e. adapt to the changing environment, protect it from errors, optimize its functionality and manage itself, that too, automatically. And this gave birth to new computing era known as autonomic computing, which was in its nascence in early 1990s. In this paper we will be presenting what is autonomic computing, how this concept is inspired by human autonomic nervous system, problems, conclusion and what is the future of autonomic computing.
A new category of waveguide E-plane filters using planar resonators

In this paper, a new category of waveguide E-plane filters is summarized. This kind of filters use the planar stripline as the resonating element. This kind of filters using split-block substrate insert E-plane technology can achieve very compact filtering structure at millimeter-wave with very low fabrication cost. Four different waveguide E-plane filters are presented.