Miracle-dz/UniFAR-FTUs huggingface dataset:
Spreading rumors cheaply, quickly, and reliably

Gossip protocols have been shown to be a useful tool in the development of simple, robust, and efficient distributed systems. This thesis addresses a number of problems associated with gossip protocols, including dealing with the failure of a large fraction of the hosts in a system, accommodating the topology of the underlying network, improving the efficiency of information exchange between hosts, and tolerating Byzantine failures.
Performance evaluation of AODV, DSDV & DSR routing protocol in grid environment

Grid computing has recently migrated from traditional high performance and distributed computing to pervasive and utility computing based on the advanced capabilities of the wireless networks and the lightweight, thin devices. This has as result the emergence of a new computing paradigm which is the Mobile Grid. This paper presents the simulation results in order to choose the best routing protocol to give the highest performance when implement the routing protocols in the target mobile grid application. The simulations comparing three ad hoc routing protocols named DSDV, DSR and AODV. The simulations have shown that the conventional routing protocols like DSR have a dramatic decrease in performance when mobility is high. However the AODV and DSDV are perform very well when mobility is high.
GPU implementation of 3D object selection by conic volume techniques in virtual environments

In this paper we present a GPU implementation to accurately select 3D objects based on their silhouettes by a pointing device with six degrees of freedom (6DOF) in a virtual environment (VE). We adapt a 2D picking metaphor to 3D selection in VE's by changing the projection and view matrices according to the position and orientation of a 6DOF pointing device and rendering a conic selection volume to an off-screen pixel buffer. This method works for triangulated as well as volume rendered objects, no explicit geometric representation is required.
Using biological spring to improve propulsive efficiency for fishlike robot

This paper proposes a new way for improving the swimming efficiency of fishlike robots. The approach is based on the observation of natural fishes whose muscle tendons play the role of ldquobiological springsrdquo. These springs allow the fish to recover a part of the energy usually lost (by dissipation in the actuators). Mechanically, this energy is produced by the negative work of inertial forces. This principle is here applied to the swim through a spring located between the body and the tail of the robot. More than qualitatively exploring this way, the article proposes a computation of the ldquooptimal valuerdquo of the spring stiffness based on the use of a simple efficiency criterion. The results deduced from this study are physically interpreted, and applied through first simulations, where the propulsive efficiency is improved of 12%.
Non-linear learning factor control for statistical adaptive background subtraction algorithm

The background subtraction algorithm has been proven to be a very effective technique for automated video surveillance applications. In statistical approach, background model is usually estimated using Gaussian model and is adaptively updated to deal with changes in dynamic scene environment. However, most algorithms update background parameters linearly. As a result, the classification results are erroneous when performing background convergence process. In this paper, we present a novel learning factor control for adaptive background subtraction algorithm. The method adaptively adjusts the rate of adaptation in background model corresponding to events in video sequence. Experimental results show the algorithm improves classification accuracy compared to other known methods.
A set of design oriented scientific tools to assist abstract B machine specification

The B method is known to be efficient, as a process of certifiable software implementation building in the domain of guided transports. There is important work to be performed using the informal specification before entering the B process. The upstream requirement analysis may be assisted with some graphical tools using UML notations. Nevertheless, the main problem to be solved may be the choice of the adequate tool. Currently, there are several kinds of diagrams in the UML notation and they are partially redundant. Considering a more general point of view, a main human contribution is to choose the representation which is specifically adapted to the considered assessment problem.
PERFORMANCE OF SMART ANTENNA ARRAYS WITH MAXIMAL-RATIO EIGEN-COMBINING

Conventionally, maximum average signal-to-noise ratio beamforming (Max-ASNR BF) and maximal-ratio combining (MRC) are applied to antenna array systems. A recently-proposed combining approach based on the Karhunen-Lo ève Transform (KLT) followed by MRC of the strongest resultant signals, denoted herein as maximal-ratio eigen-beamforming (MREC), was claimed to be superior and flexible compared to Max-ASNR BF and MRC for correlated, imperfectly-estimated channels, but comprehensive analytical tools required to understand, evaluate and apply MREC to smart antenna arrays were not available. For Rayleigh fading and BPSK modulation, general MREC average error probability (AEP) expressions are derived herein for correlated channels which are imperfectly estimated. Particular cases of these formulas also describe Max-ASNR BF and MRC of the original untransformed received signals (MRCO). A criterion which allows flexible MREC tuning to the actual environment by trading-off detection performance versus complexity is proposed. The analytical results are applied for channel estimation using pilot-symbol-aided modulation (PSAM) and interpolation and they show that significant gains can be obtained with MREC-based smart antenna arrays in scenarios with significant correlation of the received signals, compared to MaxASNR BF as well as MRCO.
A Map-Reduce Method for Training Autoencoders on Xeon Phi

The stacked autoencoder is a deep learning model that consists of multiple autoencoders. This model has been widely applied in numerous machine learning applications. A significant amount of effort has been made to increase the size of the deep learning model with respect to the size of the training dataset and the parameter of the model to improve performance. However, training a large deep learning model is highly time consuming. Recent studies have applied the CPU cluster with thousands of machines as well as the single GPU or the GPU cluster, to train large scale deep learning models. As a high-performance coprocessor like GPU, the Xeon Phi can be an alternative tool for training large scale deep learning models on a single machine. The Xeon Phi can be recognized as a small cluster which features about 60 cores, and each core supports four hardware threads. Massive parallelism offsets the low computing capacity of every core, but challenges an efficient parallel autoencoders design. In this paper, we analyze the training algorithm of autoen-coders based on the matrix operation and point out the thread oversubscription problem, which results in performance degradation. Based on the observation, we propose our map-reduce implementation of autoencoders on the Xeon Phi coprocessor. Our basic idea is to parallelize multiple autoencoder model replicas with bulk synchronous parallel (BSP) communication model where the parameters are updated after the computations of all replicas are completed. Each thread is responsible for one model replica, and all replicas work together on the same mini-batch. This data parallelism method is suitable for training autoencoders on the Xeon Phi, and can extend to asynchronous parallel training method without thread oversubscription. In our experiment the speedup is four times higher than that of sequential implementation. Enlarging the size of the autoencoder model, our method still gets stable speedup.
Chronic Diseases and Conditions Related to Alcohol Use

Alcohol consumption is a risk factor for many chronic diseases and conditions. The average volume of alcohol consumed, consumption patterns, and quality of the alcoholic beverages consumed likely have a causal impact on the mortality and morbidity related to chronic diseases and conditions. Twenty-five chronic disease and condition codes in the International Classification of Disease (ICD)-10 are entirely attributable to alcohol, and alcohol plays a component-risk role in certain cancers, other tumors, neuropsychiatric conditions, and numerous cardiovascular and digestive diseases. Furthermore, alcohol has both beneficial and detrimental impacts on diabetes, ischemic stroke, and ischemic heart disease, depending on the overall volume of alcohol consumed, and, in the case of ischemic diseases, consumption patterns. However, limitations exist to the methods used to calculate the relative risks and alcohol-attributable fractions. Furthermore, new studies and confounders may lead to additional diseases being causally linked to alcohol consumption, or may disprove the relationship between alcohol consumption and certain diseases that currently are considered to be causally linked. These limitations do not affect the conclusion that alcohol consumption significantly contributes to the burden of chronic diseases and conditions globally, and that this burden should be a target for intervention.
Hybrid Control of Induction Motors via Sampled Closed Representations

In this paper, a controller for induction motors is proposed. A continuous feedback is first applied to obtain a discrete-time model in closed form. Then, on the basis of these exact sampled dynamics, a discrete-time controller ensuring speed and flux modulus reference tracking is determined, making use of the sliding mode technique. The resulting controller is hence hybrid, in the sense that it contains both continuous and discrete-time terms. It is shown how to implement such a hybrid controller using the so-called exponential holder, which is the only device to be implemented analogically, together with an analog integrator. Moreover, a discrete-time reduced-order observer is designed for rotor fluxes and load torque estimation. The performance of the proposed controller is finally studied by simulation and experimental tests.
Exendin-4 Potently Decreases Ghrelin Levels in Fasting Rats

Ghrelin is a potent orexigenic and adipogenic hormone that strongly influences fat deposition and the generation of hunger in obesity. Indeed, hyperghrelinemia appears to promote an increase in food intake as seen in Prader-Willi Syndrome (PWS). Exendin (Ex)-4 is an agonist of the glucagon-like peptide (GLP)-1 receptor (GLP-1r) that has anorexigenic and fat-reducing properties. Here, we report that Ex-4 reduces the levels of ghrelin by up to 74% in fasted rats. These effects are dose dependent and long lasting (up to 8 h), and they can be detected after both central and peripheral administration of Ex-4. Suppression of ghrelin was neither mimicked by GLP-1(7–36)-NH2 nor blocked by the GLP-1r antagonist Ex-(9–39). Moreover, it was independent of the levels of leptin and insulin. The decrease in ghrelin levels induced by Ex-4 may explain the reduced food intake in fasted rats, justifying the more potent anorexigenic effects of Ex-4 when compared with GLP-1. As well as the potential benefits of Ex-4 in type 2 diabetes, the potent effects of Ex-4 on ghrelin make it tempting to speculate that Ex-4 could offer a therapeutic option for PWS and other syndromes characterized by substantial amounts of circulating ghrelin.
The value of diffusion-weighted MRI for prostate cancer detection and localization.

PURPOSE The aim of this study was to evaluate the role of prebiopsy T2-weighted imaging (T2WI), quantitative diffusion-weighted imaging (DWI), and the combination of these magnetic resonance (MR) techniques (T2WI+DWI) in the detection and localization of peripheral zone prostate cancer. MATERIALS AND METHODS T2WI and DWI (b value = 800 s/mm2) with an endorectal coil at 1.5 T were performed prospectively in 43 consecutive male patients with suspicion of prostate cancer before a systematic 12-core prostate biopsy. The peripheral zone of the prostate was evaluated after dividing it into sextants (n = 258). Minimum apparent diffusion coefficient (ADC) values of each sextant in the peripheral zone were measured. Two core biopsies were obtained from each sextant under transrectal ultrasound guidance. RESULTS The mean minimum ADC values of the malignant sextants were significantly lower than that of noncancerous tissue, with a significant negative correlation between the ADC value and the Gleason score. The sensitivity, specificity, and area under the receiver operating characteristic curve for the detection and localization of prostate cancer within the peripheral zone were 71%, 77%, and 0.741 for T2WI alone; 84%, 82%, and 0.830 for quantitative DWI alone; and 81%, 92%, and 0.863 for T2WI+DWI, respectively. The use of quantitative DWI, alone or combined with T2WI, improved diagnostic performance in prostate cancer detection and localization compared with T2WI alone (P = 0.020 and P = 0.001, respectively). CONCLUSION Prebiopsy DWI is valuable in detecting, localizing, and grading prostate cancer within the peripheral zone, and the lowest ADC values can indicate the regions to be biopsied.
Diagnosis of compromised accounts for online social performance profile network

Proliferation of internet technologies has changed the way content is created and exchanged through the Internet, prompting expansion of online networking applications and administrations. Online networking empower creation and exchanged the clients produced content and design of a scope of Internet-based applications. This development is fueled by more administrations as well as by the rate of their adoption by the users. While determined spammers misuse the built up trust connections between account proprietors and their companions to proficiently spread malignant spam, auspicious discovery of traded off records is quite challenge, because of the fixed trust association among the administration suppliers, account proprietors, and their companions. The proposed paper depicts a novel method to notice the cooperated user account in systems like Facebook and Twitter. Our novel scheme consists of statistical method of modelling and detected to identity accounts that behaves a sudden change along with detected the compromised accounts. This paper gives validation of these behavioral elements by gathering and dissecting genuine client clickstreams to an OSN site. Taking into account our estimation study, further devise every client's social behavioral profile (SBP) by joining its separate behavioral element measurements. We assess the capacity of social behavioral profiles in recognizing distinctive OSN clients, and the simulation results demonstrate the social behavioral profiles precisely separate every OSN clients and distinguish traded off records.
Suppression of DNA-damage checkpoint signaling by Rsk-mediated phosphorylation of Mre11

Significance We have identified a pathway that links MAPK/ribosomal s6 kinase (Rsk) signaling to the inhibition of the response to a double-stranded break (DSB) in DNA, potentially explaining radioresistance in tumors with high rapidly accelerated fibrosarcoma (Raf)/MAPK/Rsk activity. The locus of this regulation was identified as meiotic recombination 11, whose phosphorylation by Rsk prevented its DNA binding and consequent activation of the central DSB checkpoint regulator, ataxia telangiectasia mutant. Ataxia telangiectasia mutant (ATM) is an S/T-Q–directed kinase that is critical for the cellular response to double-stranded breaks (DSBs) in DNA. Following DNA damage, ATM is activated and recruited by the MRN protein complex [meiotic recombination 11 (Mre11)/DNA repair protein Rad50/Nijmegen breakage syndrome 1 proteins] to sites of DNA damage where ATM phosphorylates multiple substrates to trigger cell-cycle arrest. In cancer cells, this regulation may be faulty, and cell division may proceed even in the presence of damaged DNA. We show here that the ribosomal s6 kinase (Rsk), often elevated in cancers, can suppress DSB-induced ATM activation in both Xenopus egg extracts and human tumor cell lines. In analyzing each step in ATM activation, we have found that Rsk targets loading of MRN complex components onto DNA at DSB sites. Rsk can phosphorylate the Mre11 protein directly at S676 both in vitro and in intact cells and thereby can inhibit the binding of Mre11 to DNA with DSBs. Accordingly, mutation of S676 to Ala can reverse inhibition of the response to DSBs by Rsk. Collectively, these data point to Mre11 as an important locus of Rsk-mediated checkpoint inhibition acting upstream of ATM activation.
Checking Non-Interference in SPMD Programs

We study one of the basic multicore and GPU programming models, namely, SPMD (Single-Program Multiple-Data) programs. We define a formal model of SPMD programs based on interleaving threads that manipulate global and local arrays, and synchronize via barriers. SPMD programs are written with the intention to be deterministic, although programming errors may result in this not being true. SPMD programs are also frequently modified toward optimal performance. These facts motivate the need for methods to check determinism and program equivalence. A key property in achieving this is non-interference. We formulate non-interference as validity of logical formulas automatically derived from the program, we show that non-interference implies determinism, and we report on a prototype that can prove noninterference of NVIDIA CUDA programs.
Collaborative learning in virtual seminars: analyzing learning processes and learning outcomes

This paper focuses on the analysis of a virtual seminar in respect to learning processes and learning outcomes of its participants who collaborated over a four month period. To investigate the learning processes in this field study, we analyzed the learners' contributions according to four main learning processes: epistemic activities, construction of a conceptual space, dissemination of shared knowledge, and conflict-orientation. To investigate the learning outcome, we analyzed the joint task solutions with respect to knowledge acquisition and knowledge application. Learners were assigned to three groups who had to solve four tasks relating to the main topics on knowledge management. Results show that learning processes varied depending on the tasks and groups, but no general trend was found. Furthermore, the four task solutions also differed in their quality. The fact that learning processes were related to group products confirms the relevance of learning processes for acquiring and applying knowledge.
The Combinatorial Seller ’ s Bid Double Auction : An Asymptotically Efficient Market Mechanism *

We consider the problem of efficient mechanism design for multilateral trading of multiple goods with independent private types for players and incomplete information among them. The problem is partly motivated by an efficient resource allocation problem in communication networks where there are both buyers and sellers. In such a setting, ex post budget balance and individual rationality are key requirements, while efficiency and incentive compatibility are desirable goals. Such mechanisms are difficult if not impossible to design [34]. We propose a combinatorial market mechanism which in the complete information case is always efficient, budget-balanced, ex post individual rational and “almost” dominant strategy incentive compatible. In the incomplete information case, it is budget-balanced, ex post individual rational and asymptotically efficient and Bayesian incentive compatible. Thus, we are able to achieve efficiency, budget-balance and individual rationality by compromising on incentive compatibility, achieving only a weak version of it. This seems to be the only known combinatorial market mechanism with these properties.
Benchmarking of English-Hindi parallel corpora

In this paper we present several parallel corpora for EnglishâHindi and talk about their natures and domains. We also discuss briefly a few previous attempts in MT for translation from English to Hindi. The lack of uniformly annotated data makes it difficult to compare these attempts and precisely analyze their strengths and shortcomings. With this in mind, we propose a standard pipeline to provide uniform linguistic annotations to these resources using state-of-art NLP technologies. We conclude the paper by presenting evaluation scores of different statistical MT systems on the corpora detailed in this paper for EnglishâHindi and present the proposed plans for future work. We hope that both these annotated parallel corpora resources and MT systems will serve as benchmarks for future approaches to MT in EnglishâHindi. This was and remains the main motivation for the attempts detailed in this paper.
Implementation of ATM Endpoint Congestion Control

We describe the implementation of two ATM congestion control mechanisms, credit-based ow control and ATM Forum-style ABR rate control, on the Credit Net experimental ATM LAN testbed. This document focuses speciically on the implementation choices and performance tradeoos available to the designer of a network interface card. We conclude that although credit protocols are more eecient and easier to implement on current hardware, eecient rate implementations are also possible with modest hardware support.
The Trusted Route - Mitigating the Effects of Sel(cid:2)sh Nodes in Ad-hoc Networks

(cid:151) Node sel(cid:2)shness refers to nodes that use the resources of an ad-hoc wireless network but do not perform their basic network responsibilities of route management and packet forwarding. A security concern in ad-hoc networks is that nodes may become sel(cid:2)sh users of the network in order to conserve their battery or processing power. This results in poor network performance and unreliable network paths. In this paper a distributed trust mechanism is proposed to identify sel(cid:2)sh nodes. A novel path metric is also proposed that rates network routes according to the trustworthiness of the intermediate nodes. Through experimentation on a practical evaluation framework, it is shown that the distributed trust mechanism together with the novel path metric can increase overall traf(cid:2)c throughput in ad-hoc networks where sel(cid:2)sh nodes are present.
A RECONFIGURABLE ACTIVE ARRAY ANTENNA SYSTEM WITH THE FREQUENCY RECONFIGURABLE AMPLIFIERS BASED ON RF MEMS SWITCHES

In this paper, a frequency reconflgurable active array antenna (RAA) system, which can be reconflgurable at three difierent frequency bands, is proposed. The proposed RAA system is designed with a novel frequency reconflgurable front-end ampliflers (RFA) with the simple reconflgurable impedance matching circuits (RMC) with the MEMS switches. With the MEMS switch, the RFA is realized without any performance sacriflce especially linear characteristic. The proposed RAA antenna system is composed of the RMC, RFA with the RMC, 2 £ 2 array of reconflgurable antenna elements (RAE), as well as a reconflguration control board (RCB) for MEMS switch control, and the validity of the proposed RMC, RFA, as well as RAA system which is presented with the experimental results.