Miracle-dz/UniFAR-FTUs huggingface dataset:
11 Cooperation , Trust and Games in Wireless Networks

As an important concept in network security, trust is interpreted as a set of relations among agents participating in the network activities. Trust relations are based on the previous behavior of an agent within a protocol. Trust establishment in distributed and resource-constraint networks, such as mobile ad hoc networks (MANETs), sensor networks and ubiquitous computing systems, is much more difficult but more crucial than in traditional hierarchical architectures, such as the In-ternet and base station-or access point-centered wireless LANs. Generally, this type of distributed networks have neither pre-established infrastructures, nor centralized control servers or trusted third parties (TTP). The trust information or evidence used to evaluate trustworthiness is provided by peers, i.e. the agents that form the network. Furthermore, resources (power, bandwidth, computation etc.) are normally limited because of the wireless and ad hoc environment, so the trust evaluation procedure should only rely on local information. Schemes that depend only on local interaction also have the desired emergent property that enables fast reaction to network member changes, topology changes and security changes that frequently happen in mobile networks. Therefore, the essential and unique properties of trust management in this new paradigm of wireless networking, as opposed to traditional centralized approaches are: uncertainty and incompleteness of trust evidence, trust value is between −1 and 1; locality in trust information exchange; distributed computation. Trust establishment is a process starting from a small set of agents who are known to be trustworthy. For example, the first few peers to join a network are often known to be trustworthy, while the majority are neutral, i.e. with trust value 0. They are subsequently evaluated by agents who have direct interaction with them. Those evaluating agents are either the physical or logical neighbors of target agents. Based on their observations and evidence, they are able to provide opinions on the target agent, to build the trust value (also called reputation) of the target agent. The whole network therefore evolves as the local interactions iterate from " isolated trust islands " to " a
Why Magnetic Fields Cannot Be the Main Agent Shaping Planetary Nebulae

An increasing amount of the literature reports the detection of magnetic fields in asymptotic giant branch (AGB) stars and in central stars of planetary nebulae (PNe). These detections lead to claims that the magnetic fields are the main agent shaping the PNe. In this paper, I examine the energy and angular momentum carried by magnetic fields expelled from AGB stars, as well as other physical phenomena that accompany the presence of large‐scale fields, such as those claimed in the literature. I show that a single star cannot supply the energy and angular momentum if the magnetic fields have the large coherent structure required to shape the circumstellar wind. Therefore, the structure of nonspherical planetary nebulae cannot be attributed to dynamically important large‐scale magnetic fields. I conclude that the observed magnetic fields around evolved stars can be understood with respect to locally enhanced magnetic loops, which can have a secondary role in the shaping of the PN. The primary role, I argue, rests with the presence of a companion.
Protein seer: a Web server for protein homology detection

We present and evaluate a publicly available Web server which classifies protein sequences into SCOP 1.63 PDB95 structural superfamilies. The Website returns ranked lists of likely superfamilies and hence implicit structural predictions according to three computational techniques: BLAST, HMMER and a discriminative classifier SVM-BLOCKS. It is the first Website to provide predictions using SVM-BLOCKS. In addition to the ranked lists, the Website displays alignment information and a Web services interface is also available for computationally intensive use. We conduct a large-scale evaluation which mimics the predictions returned by the Website. The study indicates that the site provides valid predictions and that SVM-BLOCKS approach can outperform BLAST and HMMER when sufficient examples are available to learn the SVM classifiers.
An intelligent framework for protecting privacy of individuals empirical evaluations on data mining classification

Along with rapid technological advancements, the need for developing suitable frameworks for protecting privacy of individuals becomes essential for the wide-spread acceptance of knowledge-based applications. Privacy Preserving Data Mining has become an active area of research recently to address privacy issues whenever the data is to be provided for a variety of purposes like survey, research etc. Several remarkable frameworks are being developed, but there is not enough sensible solution for considering both privacy and information evenly. Privacy mechanisms which compromise with the information usually weaken the quality of data mining results. An intelligent framework to address this issue is proposed in this paper which also discusses empirical results on classification using original health care data related to Indian population, namely NFHS-3 and shows the effectiveness of our approach.
Influence of mental abacus calculation practice on mental arithmetic in children: a fMRI study

Objective To investigate the influence of mental abacus calculation practice on mental arithmetic in children with functional magnetic resonance imaging (fMRI). Methods Twelve children who had practiced mental abacus calculation for 3 years and 12 untrained children (The two groups were matched in terms of age, handedness and education) underwent fMRI during mental calculation tasks. The related behavior data were recorded at the same time. All data were analyzed with statistical parametric mapping 2. Results The calculation accuracy was significantly higher [(95.00±7.16)% vs.(74.26±16.07)%, t=-4.084, P0.01]; and the reaction time was significantly shorter [(597.91±124.05) ms vs. (770.07± 148.54) ms, t=3.082, P0.01] in trained group than untrained group. The extent and magnitude of the activated areas were significantly increased in the untrained group compared with the trained group. The activated areas mainly localized in the frontal and parietal lobes in untrained group, while the brain activated areas were few and mainly localized in occipital and parietal lobes in the trained group. Conclusion Mental abacus calculation can enhance the information processing in some brain areas, and improve the utilization efficiency of neural resources.
Suivi robuste d'objets complexes en temps réel par asservissement visuel virtuel Real-time robust and complex object tracking by virtual visual servoing

This paper proposes a real-time, robust and efficient 3D modelbased tracking algorithm for a monocular vision system. Nonlinear pose computation is formulated by means of a virtual visual servoing approach. In this context, the derivation of pointto-curves interaction matrices are given for different features. A local moving edges tracker is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating a M-estimator into the visual control law via an iteratively re-weighted least squares implementation. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Furthermore, it is verified with visual servoing as well as augmented reality applications. Results show the method to be robust to occlusion, changes in illumination and miss-tracking.
Sound texture synthesis via filter statistics

Many natural sounds, such as those produced by rainstorms, fires, or insects at night, consist of large numbers of rapidly occurring acoustic events. We hypothesize that humans encode these “sound textures” with statistical measurements that capture their constituent features and the relationship between them. We explored this hypothesis using a synthesis algorithm that measures statistics in a real sound and imposes them on a sample of noise. Simply matching the marginal statistics (variance, kurtosis) of individual frequency subbands was generally necessary, but insufficient, to yield good results. Imposing various pairwise envelope statistics (correlations between bands, and autocorrelations within each band) greatly improved the results, frequently producing synthetic textures that sounded natural and that listeners could reliably recognize. The results suggest that such statistical representations could underlie sound texture perception, and that the auditory system may use fairly simple statistics to recognize many natural sound textures.
BLOCK-BASED TRANSCEIVERS FOR FREQUENCY SELECTIVE CHANNELS WITH REDUCED REDUNDANCY

We propose a transceiver struc- ture for a frequency selective channel that al- lows the introduction of reduced redundancy. We optimize jointly the transmitter and re- ceiver in this structure to maximize the in- formation rate. The simulation results show that the proposed design has good performance while increasing the bandwidth efficiency.
On the convergence of mainstream and mission-critical markets

The computing market has been dominated during the last two decades by the well-known convergence of the high-performance computing market and the mobile market. In this paper we witness a new type of convergence between the mission-critical market (such as avionic or automotive) and the mainstream consumer electronics market. Such convergence is fuelled by the common needs of both markets for more reliability, support for mission-critical functionalities and the challenge of harnessing the unsustainable increases in safety margins to guarantee either correctness or timing. In this position paper, we present a description of this new convergence, as well as the main challenges and opportunities that it brings to computing industry.
Social Support Mediate the Associations Between Gratitude and Post-traumatic Growth in Middle School Students at 3.5 Years After Wenchuan Earthquake

The current study was to investigate the relationship among gratitude,social support and post-traumatic growth among 376 middle school students at 3. 5 years after Wenchuan earthquake. The results found that:( 1) The level of PTG of middle school students were higher,the level of perceived changes in self and change in relationship with others,are higher than the level of changed philosophy of life,female students have more changed sense in philosophy of life than male students,and the students in seventh grade was lower than others grades. ( 2) Both gratitude and social support were positively related to post-traumatic growth. ( 3) Social support mediate the associations between gratitude and post-traumatic growth. The results indicated that for middle school students after three years after Wenchuan earthquake,gratitude not only had a direct effect on post-traumatic growth,but also had an indirect effect on post-traumatic growth throught social support.
Isolation and Identification of Chloroaromatic Degrading Bacterial Strain Isolated from Indigenous Microbial Communities of Petroleum Contaminated Soils

2 Abstract: Soil and sludge samples polluted with petroleum waste from Cairo Oil Refining Company, Mostorod, Al-Qalyubia, Egypt for more than 41 years were used for isolation of indigenous microbial communities. These communities were grow on four chloroaromatic compounds (3-chlorobenzoic acid (3-CBA); 2,4-dichlorophenol (2,4-DCP); 2,6-dichlorophenol indole phenol (2,6-DCPP) and 1,2,4-trichlorobenzene (1,2,4-TCB)) as a sole carbon and energy source. The abilities of the eight different communities to grow and degrade these chlorinated compounds had been investigated by recording their growth (OD) and secretion of extracellular protein at zero time (initial), 7, 15 and 28 days of incubation period. Count of these communities was determined after 28 days incubation. The increase in bacterial count of the eight communities was ranging from 0.2 to 1.5 log cycles on 3-CBA, 1.0 to 2.3 log cycles on 2,4-DCP, 0.6 to 1.7 log cycles on 2,6-DCPP and 0.4 to 2.7 log cycles on 1,2,4-TCB. The highest total bacterial count (zero time) was 3.0×10 CFU/ml and 6
Survivable IP link topology design in an IP-over-WDM architecture

The design of an IP link topology (i.e., deciding which set of router-to-router communication links to establish) is an important factor in determining both the cost and performance of an IP network. In an IP-over-WDM architecture, these router-to-router links consist of wavelengths carried over an optical network. Each physical link in the optical network can carry multiple router-to-router wavelengths. The IP network must be designed for survivability in the event of an optical network failure (i.e., the loss of any given physical link or optical switch). Therefore, if there are particular physical links that carry an inordinate number of router-to-router wavelengths, a substantial amount of capacity may be required elsewhere in the IP network in order to assure survivability. In this paper, we describe a heuristic for designing an IP link topology in an IP-over-WDM architecture. In choosing which IP links to establish, the heuristic explicitly considers which router-to-router wavelengths that would be carried over each physical link and the various failure scenarios that could result. It is particularly targeted toward large, sparse networks. Some computational comparisons are included.
Community Structure in Social Networks: Applications for Epidemiological Modelling

During an infectious disease outbreak people will often change their behaviour to reduce their risk of infection. Furthermore, in a given population, the level of perceived risk of infection will vary greatly amongst individuals. The difference in perception could be due to a variety of factors including varying levels of information regarding the pathogen, quality of local healthcare, availability of preventative measures, etc. In this work we argue that we can split a social network, representing a population, into interacting communities with varying levels of awareness of the disease. We construct a theoretical population and study which such communities suffer most of the burden of the disease and how their awareness affects the spread of infection. We aim to gain a better understanding of the effects that community-structured networks and variations in awareness, or risk perception, have on the disease dynamics and to promote more community-resolved modelling in epidemiology.
A New Fuse Architecture and a New Post-Share Redundancy Scheme for Yield Enhancement in 3-D-Stacked Memories

3-D-stacked memory using through-silicon-vias (TSVs) has emerged as a good alternative for overcoming the limitation of 2-D memory technology. Among many issues with 3-D-stacked memory, yield is one of the major challenges for mass production. This paper proposes a new fuse architecture and redundancy scheme to improve the yield of 3-D-stacked memories. The new fuse architecture is developed based on the fact that the unused redundancies in prebond repair cause the inefficiency. Therefore, the new fuse architecture provides a way to share redundancies in prebond and postbond repairs. There are two kinds of operation modes. One is an enable mode for collecting the used redundancy information. The other is a mask mode for obtaining faulty redundancy information using a short test algorithm. Using the new fuse architecture, a new redundancy scheme called the post-share scheme is developed to achieve optimal yield. The post-share scheme allocates the fixed number of spare rows and columns for each repair just like other schemes. However, only allocated redundancies are used in prebond repair, while both the redundancies allocated for postbond repair and unused redundancies in prebond repair can be used for postbond repair. Experimental results show that the post-share redundancy scheme significantly increases the final yield of 3-D-stacked memories and the increase of area overhead is small.
Development of a new numerical solution of inhomogeneous linear partial differential equations with many independent variables

We derive a new numerical solution of linear in-homogeneous partial differential equations (PDEs) from the optimum interpolation approximation theory on generalized multidimensional filter banks, based on the similarity between the linear inhomogeneous PDEs and the generalized multidimensional filter banks. We will prove that the proposed numerical solution satisfies a given linear inhomogeneous PDE and given initial/boundary conditions at all given sample points, based on the discrete orthogonality of the approximation theory. Because the numerical solution becomes the optimum approximation of the unknown exact solution of the given linear inhomogeneous PDE in the meaning of the optimum interpolation approximation theory, we can consider that the numerical solution is with high degree of accuracy.
Stability results for the finite element approach to the immersed boundary method

The immersed boundary method in its original formulation, introduced by Peskin in [9], exhibits a high degree of numerical stiffness. A finite element approach was proposed by Boffi et al. [1] and further developed in Boffi et al. [2,3] to solve some of the difficulties arising from the original formulation. We present a stability analysis for the two dimensional case with some numerical tests which show how to choose the numerical parameters in order to obtain optimal stability.
Enhancing Elasticity of SaaS Applications using Queuing Theory

Elasticity is one of key features of cloud computing. Elasticity allows Software as a Service (SaaS) applications’ provider to reduce cost of running applications. In large SaaS applications that are developed using service-oriented architecture model, each service is deployed in a separated virtual machine and may use one or more services to complete its task. Although, scaling service independently from its required services propagates scaling problem to other services, most of current elasticity approaches do not consider functional dependencies between services, which increases the probability of violating service level agreement. In this paper, architecture of SaaS application is modeled as multi-class M/M/m processor sharing queuing model with deadline to take into account functional dependencies between services during estimating required scaling resources. Experimental results show effectiveness of the proposed model in estimating required resources during scaling virtual resources.
An Efficient Algorithm for Finding Continuous Coherent Evolution Bicluster in Time-Series Data

Most traditional biclustering algorithms focus on biclustering model on non-continuous column, which are not suitable for the analysis of the time series gene expression data. We proposes an effective and exact algorithm, which can be used to mine biclusters with coherent evolution on the contiguous columns as well as the complementary biclusters and time-lagged biclusters for the analysis of time series gene expression data. The experimental results show that the algorithm can find biclusters with statistical significance and strong biological relevance. We extend it to the currency data analysis in the financial field and obtain meaningful results.
Preliminarily Experimental Study of Isosurface Extraction for Surgical Training Environment

This paper presents experimental study of extracting surface model from volume data by an isosurface extraction algorithm in standard desk-top computational platforms. Using these extracted surfaces, this paper highlights how these models are augmented with the mechanics-based representation which can be deformed, cut and then manipulated in a typical training environment. Experimental study was carried to show the effect of various parameters on the realism of the extracted surfaces and the real-time performance in the visually-haptically rendered environment. How other effects such as texturing and lighting can play a role in the real-time rendering of the extracted surfaces, are discussed in the paper as well.
An ameliorated parallel prefix network algorithm based DQPSK precoder for optical communication

This paper introduced the implementation of differential quadrature phase-shift keying (DQPSK) precoder employing parallel prefix network (PPN). Kogge Stone (KS) adder is a typical parallel PPN algorithm. An ameliorated KS algorithm was proposed and realized to achieve the precoder. With 78Mb/s and 128 parallel channels, 20 Gb/s DQPSK precoder was implemented in ML523. Results showed that the minimum clock period is 1.109ns, and the maximum frequency is 902.038MHz.
Real time obstacle detection in stereovision on non flat road geometry through "v-disparity" representation

Presents a road obstacle detection method able to cope with uphill and downhill gradients and dynamic pitching of the vehicle. Our approach is based on the construction and investigation of the "v-disparity" image which provides a good representation of the geometric content of the road scene. The advantage of this image is that it provides semi-global matching and is able to perform robust obstacle detection even in the case of partial occlusion or errors committed during the matching process. Furthermore, this detection is performed without any explicit extraction of coherent structures. This paper explains the construction of the "v-disparity" image, its main properties, and the obstacle detection method. The longitudinal profile of the road is estimated and the objects located above the road surface are then extracted as potential obstacles; subsequently, the accurate detection of road obstacles, in particular the position of tyre-road contact points is computed in a precise manner. The whole process is performed at frame rate with a current-day PC. Our experimental findings and comparisons with the results obtained using a flat geometry hypothesis show the benefits of our approach.
Association between adiposity and systemic atherosclerosis: a protocol of a cross-sectional autopsy study

Introduction Adiposity has been associated with atherosclerosis in clinical studies. However, few autopsy studies have investigated this association, and they had only examined the coronary artery disease. Moreover, most studies had small sample sizes and were limited to middle-aged or young adults. Our aim is to investigate the association between adiposity and systemic atherosclerosis in an autopsy study. Methods and analysis A sample of 240 deceased with 30 years or more will be evaluated. The sample size was calculated using the lowest correlation coefficient found in previous studies (r=0.109), assuming a power of 90% and α=0.05. We will collect information about sociodemographics, frequency of previous contact of the deceased's next of kin and cardiovascular risk factors. We will measure neck, waist and hip circumferences, weight, height and abdominal subcutaneous tissue thickness, and then we will calculate the body mass index, waist-to-hip ratio, waist-to-height ratio and body shape index. We will also weigh the pericardial and abdominal visceral fat, the heart, and we will measure the left ventricular wall thickness. We will evaluate the presence of myocardial infarction, the degree of atherosclerosis in the aorta, carotid, coronary and cerebral arteries and plaque composition in carotid, coronary and cerebral arteries. For each individual, we will fix arterial and adipose tissue samples in 10% formalin and freeze another adipose tissue sample at −80°C for future studies. Ethics and dissemination Ethical approval was granted by the Ethics Committee of University of Sao Paulo Medical School, Brazil. Results will be submitted for publication in a peer-reviewed journal.