Miracle-dz/UniFAR-FTUs huggingface dataset:
Matrix-Stripe-Cache-Based Contiguity Transform for Fragmented Writes in RAID-5

Given that contiguous reads and writes between a cache and a disk outperform fragmented reads and writes, fragmented reads and writes are forcefully transformed into contiguous reads and writes via a proposed matrix-stripe-cache-based contiguity transform (MSC-CT) method which employs a rule of consistency for data integrity at the block level and a rule of performance that ensures no performance degradation. MSC-CT performs for reads and writes, both of which are produced by write requests from a host as a write request from a host employs reads for parity update and writes to disks in a redundant array of independent disks (RAID)-5. MSC-CT is compatible with existing disk technologies. The proposed implementation in a Linux kernel delivers a peak throughput that is 3.2 times higher than a case without MSC-CT on representative workloads. The results demonstrate that MSC-CT is extremely simple to implement, has low overhead, and is ideally suited for RAID controllers not only for random writes but also for sequential writes in various realistic scenarios.
Experimental characterization of a wind generator prototype for sustainable small wind farms

This paper presents the experimental characterization of a wind turbine prototype used for micro wind farms. The proposed prototype, whose advantages can be summarized in versatility of application, low noise and compactness, can generate 1 kW of rated power for a wind speed equal to 4 m/s. The tests here reported and carried out by means of an experimental test bench confirm that the prototype is well designed and adequate for the purpose of its application.
Online Path Planning in a Continuous Gaussian Process Occupancy Map

This paper demonstrates the application of Gaussian Process (GP) occupancy map to 3D online path planning for a 6DOF Rotary Unmanned Aerial Vehicle (RUAV) operating in a naturally cluttered environment. Traditional grid-based occupancy map suffers from the curse in dimensionality for platforms that operate in higher configuration space. The flexibility of the path planner is also limited by the resolution of the grid size. The GP map however, performs inference directly on the collected sensor datasets which allows it to infer the probability of collision for any query point in continuous 3D space. Dealing with datasets directly removes the need of maintaining a full discrete map; its continuous property maximizes the flexibility of the path planner; the planned path inheritantly embeded with the the probability of collision which is valuable for decision making. We embed the GP map approach into our previous work on smooth path planning and control for an aerial vehicle and present results in a simulated cluttered environment.
EFFECTS OF EXERCISES INTENSITY ON FACIAL HEAT DISTRIBUTION IN MALE SUBJECTS AND RELATIONSHIP WITH FEELING SCALE

The purpose of this study is to identify the effects of exercises intensity on facial thermoregulation and to evaluate the relationships between changes in men’s facial temperature and changes in affect that occur during muscular exercise. Moreover, a special attention has been paid on the possible relationship between the skin facial temperature and the heart rate of subjects. Fifty-four male performed a 12 min long session of aerobic exercise at moderate-to-high intensity. IR cartographies were performed using an IR camera. Pleasure and displeasure levels were assessed repeatedly over the exercise session.
Thinking Skills in the 12th Grade English Course book in Timor Leste

This study aims to analyze the English course book of (Manual do Aluno INGLES 12.o ano de escolaridade/Students’ English Manual for 12th Year Schooling) in Timor Leste. The activities in the reading and listening sections of the course book were performed to determine whether they emphasized on lower or higher levels of cognitive process. The study attempted to answer the following question: Do the cognitive levels of the activities that relate to the focus on reading and listening in the 12th grade English course book sufficiently represent all the six levels of the New Bloom Taxonomy of thinking skills? The objective of this analysis was to discover the reading and listening activities that can sufficiently promote the levels of cognitive process. The activities determined as the criteria for analysis were: Wh-questions, true/false question, yes/no question, multiple choice question, complete the sentence phrase, a chart, matching questions, statement question, and a key word request question. The activities of the questions were gathered, listed with the total numbers of 161 questions and analyzed according to the six levels of New Bloom’s Taxonomy. The results showed that 98 activities emphasized mostly on lower levels cognitive order while only 63 activities emphasized the higher levels of thinking skills. So, the course book mentioned above targeted as a resource for students to learn the language, not as a resource for students to develop thinking skills because it fails to equip learners with the activities requiring higher levels of thinking order. By implication, for the teacher/syllabus designer can be aware to modify their own learning material by integrating more higher-order questions to achieve higher levels of thinking skills. Keywords: Course book Activities Analysis, and New Bloom’s Taxonomy
The TREAT-NMD DMD Global Database: Analysis of More than 7,000 Duchenne Muscular Dystrophy Mutations

Analyzing the type and frequency of patient‐specific mutations that give rise to Duchenne muscular dystrophy (DMD) is an invaluable tool for diagnostics, basic scientific research, trial planning, and improved clinical care. Locus‐specific databases allow for the collection, organization, storage, and analysis of genetic variants of disease. Here, we describe the development and analysis of the TREAT‐NMD DMD Global database (http://umd.be/TREAT_DMD/). We analyzed genetic data for 7,149 DMD mutations held within the database. A total of 5,682 large mutations were observed (80% of total mutations), of which 4,894 (86%) were deletions (1 exon or larger) and 784 (14%) were duplications (1 exon or larger). There were 1,445 small mutations (smaller than 1 exon, 20% of all mutations), of which 358 (25%) were small deletions and 132 (9%) small insertions and 199 (14%) affected the splice sites. Point mutations totalled 756 (52% of small mutations) with 726 (50%) nonsense mutations and 30 (2%) missense mutations. Finally, 22 (0.3%) mid‐intronic mutations were observed. In addition, mutations were identified within the database that would potentially benefit from novel genetic therapies for DMD including stop codon read‐through therapies (10% of total mutations) and exon skipping therapy (80% of deletions and 55% of total mutations).
Impact of programming and application-specific knowledge on maintenance effort:A hazard rate model

We empirically test the relative impact of general programming knowledge and application-specific knowledge on maintenance productivity. One hundred undergraduates participated in a quasi-experiment that required them to perform two maintenance tasks in sequence on an inventory control application. Each maintenance task involved a modification to the original application and the hours needed to complete each maintenance task are used to measure productivity. Since subjects may submit modifications that do not meet all the user requirements, the person-hours spent can be less than the actual hours required if modified applications were to meet the user requirements completely. That is, the observed time effort censored the actual required time effort. To overcome the challenge of this censored time problem, we use a proportional hazard model to model the effect of human capital on productivity. The method of maximum likelihood estimation was used to estimate the model parameters. Our study enables us to draw several implications for formulating hiring policies relating to software maintenance.
Energy efficiency contours for amplify-and-forward and decode-and-forward cooperative protocols

In this paper we compare the energy efficiency of different cooperative schemes by means of energy efficiency contours. We consider a three-nodes cooperative scenario, employing either the amplify-and-forward (AF) or the decode-and-forward (DF) protocol. In the case of the DF protocol we analyse the performance of both repetition coding (RC) and parallel coding (PC). Our analysis shows that the maximum energy efficiency operating point is usually related to the allocation of different transmission rates to each user, while enforcing rate fairness leads the system to a sub-optimum operating point in terms of energy efficiency. Depending on the particular topology, the most energy efficient scheme may be AF or DF, with a clear advantage of DF when the two users are close. Moreover, we demonstrate that the exploitation of a return channel may have a large impact in the energy efficiency, being able to almost double it.
Tag-based social image search with hyperedges correlation

In social image search, most existing hypergraph methods use the visual and textual features in isolation by treating each feature term as a hyperedge. Nevertheless, they neglect the correlations of visual and textual hyperedges, which are more robust to represent the high-order relationship among vertices. In this paper, we propose a hypergraph with correlated hyperedges (CHH), which introduces high-order relationship of hyperedges into hypergraph learning. Based on CHH, a pairwise visual-textual correlation hypergraph (VTCH) model is used for tag-based social image search. To overcome the large number of newly generated hybrid hyperedges, a bagging-based method is adopted to balance the accuracy and speed. Finally, adaptive hyperedges learning method is used to obtain the relevance score for social image search. The experiments conducted on MIR Flickr show the effectiveness of our proposed method.
UWB down-conversion mixer in CMOS 130 nm technology for wireless sensor network applied to aerospace application

This paper presents a low power, UWB down-conversion mixer, implemented in CMOS 0.13 μm technology. This mixer is based on a double balanced Gilbert topology with inter-stage inductance. This mixer shifts an RF (Radio Frequency) signal from 6-8.5 GHz frequency range to IF (Intermediate Frequency) signal over 10-510 MHz frequency range. This down-conversion mixer has 8 dB Conversion Gain, require -1dBm LO (Local Oscillator) power, and consume only 6 mW.
Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers. This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing the results from the approximation with simulations.
Real-time Recursive State Estimation for Nonlinear Discrete Dynamic Systems with Gaussian or non-Gaussian Noise

Many systems in the real world are more accurately described by nonlinear models. Since the original work of Kalman (Kalman, 1960; Kalman & Busy, 1961), which introduces the Kalman filter for linear models, extensive research has been going on state estimation of nonlinear models; but there do not yet exist any optimum estimation approaches for all nonlinear models, except for certain classes of nonlinear models; on the other hand, different suboptimum nonlinear estimation approaches have been proposed in the literature (Daum, 2005). These suboptimum approaches produce estimates by using some sorts of approximations for nonlinear models. The performances and implementation complexities of these suboptimum approaches surely depend upon the types of approximations which are used for nonlinear models. Model approximation errors are an important parameter which affects the performances of suboptimum estimation approaches. The performance of a nonlinear suboptimum estimation approach is better than the other estimation approaches for specific models considered, that is, the performance of a suboptimum estimation approach is model-dependent. The most commonly used recursive nonlinear estimation approaches are the extended Kalman filter (EKF) and particle filters. The EKF linearizes nonlinear models by Taylor series expansion (Sage & Melsa, 1971) and the unscented Kalman filter (UKF) approximates a posteriori densities by a set of weighted and deterministically chosen points (Julier, 2004). Particle filters approximates a posterior densities by a large set of weighted and randomly selected points (called particles) in the state space (Arulampalam et al., 2002; Doucet et al., 2001; Ristic et al., 2004). In the nonlinear estimation approaches proposed in (Demirbas, 1982; 1984; Demirbas & Leondes, 1985; 1986; Demirbas, 1988; 1989; 1990; 2007; 2010): the disturbance noise and initial state are first approximated by a discrete noise and a discrete initial state whose distribution functions the best approximate the distribution functions of the disturbance noise and initial state, states are quantized, and then multiple hypothesis testing is used for state estimation; whereas Grid-based approaches approximate a posteriori densities by discrete densities, which are determined by predefined gates (cells) in the predefined state space; if the state space is not finite in extent, then the state space necessitates some truncation of the state space; and grid-based estimation approaches assume the availability of the state Real-time Recursive State Estimation for Nonlinear Discrete Dynamic Systems with Gaussian or non-Gaussian Noise 1
Tracking time-varying parameters in software systems with extended Kalman filters

Autonomic control of a service system can take advantage of a performance model only if a way can be found to track the changes in the system. A Kalman Filter provides a framework for integrating various kinds of measured data, and for tracking changes in any time-varying system. This work evaluates the effectiveness of such a filter in tracking changes in performance parameters of a software system that occur at different rates and amplitudes. The time-varying system is a Web application deployed in a data centre with layered queuing resources, in which parameter variations happen at random instants. The tracking filter is based on a layered queuing model of this system, with parameters representing CPU demands and the user load intensity. Experiments were performed to evaluate the effectiveness of the filter in tracking the changes, and the requirements for the filter settings for fast and slow variations in the parameters. The target application is autonomic control of a service centre.
A Semantic Recommendation Procedure for Electronic Product Catalog

— To overcome the product overload of Internet shoppers, we introduce a semantic recommendation procedure which is more efficient when applied to Internet shopping malls. The suggested procedure recommends the semantic products to the customers and is originally based on Web usage mining, product classification, association rule mining, and frequently purchasing. We applied the procedure to the data set of MovieLens Company for performance evaluation, and some experimental results are provided. The experimental results have shown superior performance in terms of coverage and precision.
Core Discussion Paper 9866 Smooth Transition Garch Models: a Bayesian Perspective

This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two di erent regimes with a smooth transition function. In one formulation, the conditional variance reacts di erently to negative and positive shocks while in a second formulation, small and big shocks have separate e ects. The introduction of a threshold allows for a mixed e ect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for detecting the presence and the shape of nonlinearities. The method is applied to the Brussels and Tokyo stock indexes. The need for an alternative parameterisation of the GARCH model is emphasised as a solution to numerical problems.
Gibraltar: A Reed‐Solomon coding library for storage applications on programmable graphics processors

Reed–Solomon coding is a method for generating arbitrary amounts of erasure correction information from original data via matrix–vector multiplication in finite fields. Previous work has shown that modern CPUs are not well‐matched to this type of computation, requiring applications that depend on Reed–Solomon coding at high speeds (such as high‐performance storage arrays) to use hardware implementations. This work demonstrates that high performance is possible with current cost‐effective graphics processing units across a wide range of operating conditions and describes how performance will likely evolve in similar architectures. It describes the characteristics of the graphics processing unit architecture that enable high‐speed Reed–Solomon coding. A high‐performance practical library, Gibraltar, has been prototyped that performs Reed–Solomon coding on graphics processors in a manner suitable for storage arrays, along with applications with similar data resiliency needs. This library enables variably resilient erasure correcting codes to be used in a broad range of applications. Its performance is compared with that of a widely available CPU implementation, and a rationale for its API is presented. Its practicality is demonstrated through a usage example. Copyright © 2011 John Wiley & Sons, Ltd.
PULLBACKS OF EISENSTEIN SERIES ON U(3, 3) AND NON-VANISHING OF SHAFAREVICH-TATE GROUPS

In this paper we construct a pullback formula of a Siegel Eisenstein series on GU(3, 3) to GSp(4) × GL(2) and use it to study the Bloch-Kato conjecture for automorphic forms on GL(2). Let f ∈ S2k−2(SL2(Z)) be a normalized eigenform and let p > 2k− 2 be a prime so that p | Lalg(k, f). Then up to some reasonable hypotheses, we use this formula to construct a congruence between the Saito-Kurokawa lift Ff of f and a Siegel eigenform G that does not lie in the space of Maass spezialchars. We use this congruence to give evidence for a conjecture of Katsurada’s characterizing the congruence primes of Saito-Kurokawa lifts. We then use this congruence to study the 4-dimensional Galois representation attached to G. This allows us to construct a non-trivial p-torsion element in the Shafarevich-Tate group of the k-twist of the residual p-adic Galois representation associated to f . We conclude by showing how this provides evidence for the Bloch-Kato conjecture in this setting.
Application of automatic speaker recognition techniques to pathological voice assessment (dysphonia)

This paper investigates the adaptation of Automatic Speaker Recognition (ASR) techniques to the pathological voice assessment (dysphonic voices). The aim of this study is to provide a novel method, suitable for keeping track of the evolution of the patient's pathology: easy-to-use, fast, non-invasive for the patient, and affordable for the clinicians. This method will be complementary to the existing ones - the perceptual judgment and the usual objective measurement (jitter, airflows.) which remain time and human resource consuming. The system designed for this particular task relies on the GMMbased approach, which is the state-of-the-art for speaker recognition. It is derived from the open source ASR tools (LIA_Spk- Det and ALIZE) of the LIA lab.Experiments conducted on a dysphonic corpus provide promising results, underlining the interest of such an approach and opening further research investigation.
60GHz passive and active RF-path phase shifters in silicon

Integrated 60-GHz active and passive phase shifters for RF-path phase-shifting phased array transceivers are demonstrated in this paper. The reflection-type passive phase shifter achieves ≫180° phase variation across the 57GHz–64GHz band with insertion loss varying from 4.2dB–7.5dB at 60GHz. The active phase shifter employs vector-interpolation architecture and achieves 360° phase variation, −2dB gain, 12GHz 3dB bandwidth and 16.5dB noise figure at 60GHz. Measurements over process and temperature are also discussed and comparisons are drawn between active and passive phase shifting approach for 60GHz phased arrays.
Characterization of the Intracellular Deproteinized Relaxed Circular DNA of Hepatitis B Virus: an Intermediate of Covalently Closed Circular DNA Formation

ABSTRACT Covalently closed circular DNA (cccDNA) of hepatitis B virus (HBV) is formed by conversion of capsid-associated relaxed circular DNA (rcDNA) via unknown mechanisms and exists in the nucleus of the infected hepatocyte as a minichromosome that serves as the transcription template for viral RNAs. To study the molecular pathway of cccDNA formation and its regulation by viral and cellular factors, we have established a cell line that supports the replication of an envelope protein-deficient HBV genome in a tetracycline-inducible manner. Following induction of HBV replication, the cells accumulate higher levels of cccDNA as well as larger amounts of deproteinized rcDNA (DP-rcDNA) than cells that replicate wild-type HBV genomes. These results indicate that HBV envelope proteins negatively regulate cccDNA formation, and conversion of DP-rcDNA into cccDNA is a rate-limiting step of cccDNA formation in HepG2 cells. Detailed analyses reveal the following: (i) DP-rcDNA exists in both cytoplasm and nucleus; (ii) while nuclear DP-rcDNA is sensitive to DNase I digestion, a small fraction of cytoplasmic DP-rcDNA is DNase I resistant; (iii) both DNase I-sensitive and -resistant cytoplasmic DP-rcDNAs cosediment with capsids and can be immunoprecipitated with HBV core antibody; and (iv) a primer extension assay maps the 5′ end of the minus strand of DP-rcDNA at the authentic end of virion rcDNA. Hence, our results favor a hypothesis that the removal of viral polymerase protein covalently linked to the 5′ end of the minus-strand DNA occurs inside the capsid in the cytoplasm and most possibly via a reaction that cleaves the phosphodiester bond between the tyrosine of the polymerase and the 5′ phosphoryl group of minus-strand DNA.
Foreground detection via robust low rank matrix factorization including spatial constraint with Iterative reweighted regression

Foreground detection is the first step in video surveillance system to detect moving objects. Robust Principal Components Analysis (RPCA) shows a nice framework to separate moving objects from the background. The background sequence is then modeled by a low rank subspace that can gradually change over time, while the moving foreground objects constitute the correlated sparse outliers. In this paper, we propose to use a low-rank matrix factorization with IRLS scheme (Iteratively reweighted least squares) and to address in the minimization process the spatial connexity of the pixels. Experimental results on the Wallflower and I2R datasets show the pertinence of the proposed approach.