Miracle-dz/UniFAR-FTUs huggingface dataset:
A Trust Transitivity Model Based-on Dempster-Shafer Theory

With the expansion of the Internet, Trust has attracted the attention of more and more researchers. This paper focuses on the trust transitivity problem and proposes a trust transitivity model based on Dempster-Shafer Theory. In our model, we show two types of trust relationship: Identity Trust and Behavior Trust based on Directness Trust and Recommendation Trust. Then we build the trust transitivity network and propose the trustworthiness propagation and combination rules. Finally, we propose a method for transforming the triple of evidence theory to a simple result in order to select the trust entity easily. W e also use the nearness degree to analyze the transitivity rationality and show how to use the trust transitivity model by a shopping scenario in TaoBao and illustrate its legitimacy
Probing MACHOs by observation of M 31 pixel lensing with the 1.5 m Loiano telescope

We analyse a series of pilot observations in order to study microlensing of (unresolved) stars in M 31 with the 1.5 m Loiano telescope, including observations on both identified variable source stars and reported microlensing events. We also look for previously unknown variability and discover a nova. We discuss an observing strategy for an extended campaign with the goal of determining whether MACHOs exist or whether all microlensing events are compatible with lens stars in M 31.
On modeling the rhythm of natural languages

We describe a new model for the formal representation of the rhythmic tendencies of natural languages. The algorithm is a modification of PVI, proposed by Grabe and Low [10]. The model was tested on a fairly substantial corpus of Italian semispontaneous productions, and its outcome compared with that yielded by two well-known algorithms (Ramus [14] and PVI).
Exploring phonetic realization in Danish by Transformation-Based Learning

We align phonemic and semi-narrow phonetic transcriptions in the DanPASS corpus and extend the phonemic description with sound classes and with traditional phonetic features. From this representation, we induce rules for phonetic realization by Transformation-Based Learning (TBL). The rules thus learned are classified according to relevance and qualitatively evaluated.
Almost contact manifolds, connections with torsion and parallel spinors

We classify locally homogeneous quasi-Sasakian manifolds in dimension five that admit a parallel spinor $\psi$ of algebraic type $F \cdot \psi = 0$ with respect to the unique connection $\nabla$ preserving the quasi-Sasakian structure and with totally skew-symmetric torsion. We introduce a certain conformal transformation of almost contact metric manifolds and discuss a link between them and the dilation function in 5-dimensional string theory. We find natural conditions implying conformal invariances of parallel spinors. We present topological obstructions to the existence of parallel spinors in the compact case.
Towards multi-vehicle simultaneous localisation and mapping

This paper presents a novel approach to the multi-vehicle simultaneous localisation and mapping (SLAM) problem that exploits the manner in which observations are fused into the global map of the environment to manage the computational complexity of the algorithm and improve the data association process. Rather than incorporating every observation directly into the global map of the environment, the constrained local submap filter (CLSF) relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment. This representation is shown to reduce the computational complexity of maintaining the global map estimates as well as improving the data association process. This paper examines the prospect of applying the CLSF algorithm to the multi-vehicle SLAM problem.
Influence of silver thickness on optical properties of metal island films fabricated by physical vapour deposition

In this paper we report studies on the influence of silver island films' thickness on their optical and surface-enhanced Raman scattering properties. The semicontinuous silver films of thickness in range 3-10 nm were fabricated using electron beam physical vapour deposition and their optical properties were characterized using UV-Vis-NIR spectroscopy. The SERS enhancement properties of fabricated films were evaluated using p-mercaptoaniline as an testing analyte. It was found that with increasing thickness of the silver films their plasmon resonance becomes broader and its maximum shifts toward longer wavelengths. The largest SERS signal enhancement was observed for the 7 nm thick Ag films.
Adapting a fault prediction model to allow inter languagereuse

An important step in predicting error prone modules in a project is to construct the prediction model by using training data of that project, but the resulting prediction model depends on the training data. Therefore it is difficult to apply the model to other projects. The training data consists of metrics data and bug data, and these data should be prepared for each project. Metrics data can be computed by using metric tools, but it is not so easy to collect bug data. In this paper, we try to reuse the generated prediction model. By using the metrics and bug data which are computed from C++ and Java projects, we have evaluated the possibility of applying the prediction model, which is generated based on one project, to other projects, and have proposed compensation techniques for applying to other projects. We showed the evaluation result based on open source projects.
An evaluation of corporate governance practices of Islamic banks versus Islamic bank windows of conventional banks: a case of Pakistan

Purpose - The purpose of this paper is to explore the perceived importance of management about various corporate governance dimensions being practiced in the Pakistani Islamic banking context. Design/methodology/approach - AHP is applied to analyze the corporate governance indexes and its dimension of five Islamic banks and 12 conventional banks which are providing Islamic banking facilities (Islamic bank window) throughout Pakistan. These dimensions included board of directors (BOD), Shari'ah supervisory board (SSB), audit, investment account holders (IAH), and information disclosure & transparency. Findings - The study reveals that the most significant dimensions which affect the corporate governance in Islamic banks are BOD and SSB, while the significant factors for Islamic banking windows are almost all dimensions of corporate governance. The correlation, regression, and ANOVA tests are applied to check the contributions of various factors of corporate governance mechanisms. These results indicate that there is a significant difference between Islamic banks and Islamic banking windows regarding the BOD and SSB. On the other hand, no significant difference is seen for the rest of the factors. The dissatisfaction level of customers reduces with the increase in the audit and BOD governance and all other factors have no impact in the case of Islamic banking windows; whereas in Islamic banks, in addition to audit and the SSB, information disclosure also significantly reduces the dissatisfaction level of customers. The concern of customers decreases significantly with the increasing level of IAH in the case of Islamic banking windows whereas in the case of Islamic banks a significant impact is seen for BOD, information disclosure, audit and IAH, but improvement in the governance of these rather increases the concern of customers toward compliance of Shari'ah and SSB has no contribution towards the concern of customers. Originality/value - This study has practical significance for conventional and Islamic banking policy makers for understanding the requirements of their stakeholders and aligning them with the fundamentals of Shari'ah compliance according to the guidelines provided by the code of corporate governance so as to get better insight into the relationship between customers' motives behind using Islamic banking products.
Association Rule Mining and Medical Application: A Detailed Survey

rule mining is one of the well established fields in data mining. This paper has surveyed the research papers in this field from 1993 to 2013. This paper gives detailed account of fundamental algorithms and its advantages and disadvantages. This also provides brief overview of current trends of association and frequent pattern mining and medical applications. KeywordsRules, Frequent pattern, Data Mining
Golgi positioning

One of the characteristics of the mammalian Golgi is its position adjacent to the nucleus. This characteristic is maintained through the action of the microtubule (MT) minus end–directed motor dynein and MT-associated proteins (MAPs). Recent findings suggest that GMAP-210, a member of the golgin family of proteins, may help to link Golgi membranes and vesicles with the MT cytoskeleton. However, there are good grounds to doubt that either GMAP-210 or its yeast homologue Rud3p is a MAP. Instead, they appear to function in vesicle trafficking events at the Golgi together with the GTPase ARF1 and a small membrane protein, Erv14. As such, the interesting question of how the Golgi interacts with MTs may well remain open to further investigation.
Learned and designed features for sparse coding in image classification

There is an amount of designed features (SIFT, SURF, or DAISY) which has been chosen in the standard implementation of some visual recognition and multimedia challenges. The power of these features lie on their invariance designed against rotation, scaling, and translation. Recent trends in deep learning, however, have pointed out that data-driven features learning performs better designed features in some tasks, since they can capture the global (via multi-layers network) or inter-local structures (convolutional network) of images. We argue that combining the two types of features can significantly improve visual object recognition performance. We propose in this paper a framework that uses sparse coding and the fusion of learned and designed features in order to build descriptive codewords. Evaluations on Caltech-101 and 15 Scenes validates our argument, with a better result compared with recent approaches.
Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio

Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.
Weighted least-squares estimation of phase errors for SAR/ISAR autofocus

A new method of phase error estimation that utilizes the weighted least-squares (WLS) algorithm is presented for synthetic aperture radar (SAR)/inverse SAR (ISAR) autofocus applications. The method does not require that the signal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of the new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared with other methods, the WLS estimation is optimal in the sense that it has the minimum variance of the estimation error. Excellent results have been obtained in autofocusing and imaging experiments on real SAR and ISAR data.
Rebranding Russia: Norms, Politics and Power

This working paper argues that Russia is in the process of re-branding itself internationally, with a variety of normative arguments increasingly creeping into its wider international discourse. By appealing to norms, Russia tries to reformulate the key messages it sends to the world and implant the concept of its power worldwide. Yet given that Russia's normative messages are often met with scarce enthusiasm in Europe, it is of utmost importance to uncover how the normative segment in Russian foreign policy is perceived, evaluated and debated both inside Russia and elsewhere. Within this framework, this paper focuses on a set of case studies highlighting the normative and non-normative dimensions of Russian foreign policy. These include Russia-EU trans-border cooperation, Moscow's policies towards Estonia, Poland, Ukraine/Georgia and the UK, Russian strategies in the 'war on terror' and energy issues.
The use of promotional tools in the motor carrier industry : An exploratory study

This research explores the current attitudes of marketing managers in the motor carrier industry. Specifically, it examines their attitudes about the nature and degree of the competition they face, the nature of the shippers' carrier selection processes, and their use of promotional tools. It was found that, as a group, they believe the motor carrier marketplace to be highly competitive, that shippers are highly involved, critical, and discerning in their selection of a carrier, and that promotion plays an essential role in the motor carrier marketing mix. Furthermore, these attitudes are particularly pronounced among representatives of larger firms (those with annual revenues of more than $25 million) and among firms that provide LTL service. Personal selling, and, to a lesser degree, the other "personal contact promotions" (telemarketing and direct mail), are perceived to be the most important promotional tools to the motor carrier industry.
Externalities and Property Rights in the Fisheries

merits of a general policy limiting entry into U.S. fisheries has been discussed. Bishop [1973] concluded that a general policy of limiting entry into the U.S. fisheries would lead to only minor benefits. Furthermore, he noted that the resulting benefits could be more than offset by the generation of undesirable effects on the distribution of income as well as a decrease in marketable fish products. Bishop's approach to resource misallocation in fisheries is
Structured Indexing Model for Cross-Language Information Retrieval

In recent digital library systems or World Wide Web environment, parallel corpora are used by many applications (Natural Language Processing, machine translation, terminology extraction, etc.). This paper presents a new cross-language information retrieval model based on the language modeling. The model avoids query and/or document translation or the use of external resources. It proposes a structured indexing schema of multilingual documents by combining a keywords model and a keyphrases model. Applied on parallel collections, a query, in one language, can retrieve documents in the same language as well as documents on other languages. Promising results are reported on the MuchMore parallel collection (German language and English language). RÉSUMÉ. Dans les systèmes récents de bibliothèques numériques ou dans le contexte du Web, les corpus parallèles sont utilisés par de nombreuses applications (traitement du langage naturel, la traduction automatique, extraction de terminologie, etc.). Cet article présente un nouveau modèle de recherche d’information inter-langue basé sur le modèle de langue. Le modèle évite la traduction des requêtes et/ou des documents ainsi que l’utilisation des ressources externes. Il propose un schéma d’indexation structurée des documents multilingues en combinant un modèle de mots-clés et un modèle de phrase-clés. Appliquée sur une collection parallèle, une requête dans une langue, peut récupérer des documents dans la même langue ainsi que des documents dans d’autres langues. Appliqué à la collection parallèle MuchMore (en langue allemande et en langue anglaise), le modèle a montré des résultats prometteurs.
The grammar of meanings in Ibn Sı̄nā and Frege

I thank Manuela Giolfo, Ahmad Hasnaoui, Amirouche Moktefi, Zia Movahed and Kees Versteegh for information, corrections and comments that relate directly to things discussed below. I should also thank Kais Dukes of the Arabic Language Computing group at Leeds University, who sent me some very useful information before going silent — I hope I didn’t make myself a nuisance to him. None of these people are responsible for any errors of fact or judgment below.
A 0 . 6V to 1V Audio ΔΣ Modulator in 65 nm CMOS with 90 . 2 dB SNDR at 0 . 6V

This paper presents a discrete time, single loop, third order ΔΣ modulator. The input feed forward technique combined with 5bit quantizer is adopted to suppress swings of integrators. Harmonic distortions as well as the noise mixture due to the nonlinear amplifier gain are prevented.The design of amplifiers is hence relaxed. To reduce the area and power cost of the 5-bit quantizer, the successive approximation quantizer with only a single comparator instead of traditional flash quantizer is employed. Fabricated in 65 nmCMOS, the modulator achieves 95 dB peak SNDR at 1-V supply with 24 kHz.Thanks to low swing circuit techniques and low threshold voltages of devices, the peak SNDR maintains 90.2 dB under 0.6-V low supply. The total power dissipation is 371μW at 1-V and drops to only 133 μW at 0.6-V.
Geographic Separation of Domestic and Wild Strains of Toxoplasma gondii in French Guiana Correlates with a Monomorphic Version of Chromosome1a

Background Previous studies have stressed the genetic divergence and high pathogenicity of strains of T. gondii from French Guiana. Although strains from coastal, human adapted environments (so called anthropized) resemble those found in other regions of the Caribbean, strains collected from inland jungle environment are genetically quite diverse. To better understand the composition of these distinct strain types, we undertook a more in depth analysis of T. gondii strains from French Guiana including profiling of chromosome 1a (Chr1a), which is often shared as a single monomorphic haplotype among lineages that are otherwise genetically distinct. Methodology/Principal Findings Comparison of intron sequences from selectively neutral genes indicated that anthropized strains were most closely related to clonal type III strains from North America, although wider RFLP analysis revealed that they are natural hybrids. In contrast, strains isolated from the jungle were genetically very diverse. Remarkably, nearly all anthropized strains contained the monomorphic version of Chr1a while wild stains were extremely divergent. The presence of the monomorphic Chr1a strongly correlated with greater transmission in domestic cats, although there were several exceptions, indicating that other factors also contribute. Anthropized strains also varied in their virulence in laboratory mice, and this pattern could not be explained by the simple combination of previously identified virulence factors, indicating that other genetic determinants influence pathogenicity. Conclusions/Significance Our studies underscore the marked genetic separation of anthropized and wild strains of T. gondii in French Guiana and provide additional evidence that the presence of Chr1a is associated with successful expansion of widely different lineages within diverse geographic areas. The predominance of Chr1a among strains in the anthropized environment suggests that it may confer an advantage for transmission in this environment, and thus potentially contribute to the spread of pathogenecity determinants.
Notice of RetractionA 3D non-regular military symbol Deformation method along the Battlefield terrain

Free-Form Deformation (FFD) is an efficient technique for editing the shapes of 3D models, and widely used in the Battlefield Environment Visualization (BEV), computer animation, computer graphics entertainment etc. The basic idea of some famous previous FFD approaches deforms a target 3D model by adjusting some control points of a 3D lattice surrounding the model. It is a tedious work, especially when the lattice contains too many control points. Moreover, how to place the control points of the lattice to make them cover the region of the target model is also a problem, and it is also difficult to keep the geometric measurement for the deformed model. Therefore, in this paper, a novel FFD method without any lattice like structure is proposed by borrowing the idea of non-distortion texture-mapping for freeform surfaces. By using this method, the 3D non-regular military symbol of the deformed model due to a given parametric terrain surface can be predicted easily, so that the user can get his or her desirable results more intuitively and has no necessary to place the control points of a proper lattice. Moreover, since this method is simple, efficient, and has a real-time response, it is more suitable for doing the animation with 3D non-regular military symbol models in the battlefield terrain surface.
Moving target detection with MIMO radar

The use of waveform diversity and angular diversity provides significant improvements in the performance of Multi Input Multi Output (MIMO) radar compared to the conventional radars and the phased array radar systems. One of these improvement areas is the success of moving target detection. In this paper, the moving target detection performance of a MIMO radar with a Neyman-Pearson detector which includes space time codes explicitly is investigated.
Model Word Vectors Constituency Parser Sentiment Modelaspects + aspect-based sentiments Word

Sentiment analysis is an important task in natural language understanding and has a wide range of real-world applications. The typical sentiment analysis focus on predicting the positive or negative polarity of the given sentence(s). This task works in the setting that the given text has only one aspect and polarity. A more general and complicated task would be to predict the aspects mentioned in a sentence and the sentiments associated with each one of them. This generalized task is called aspect-based sentiment analysis (ABSA). In the annual SemEval competition, an ABSA task has been added since 2014. Among submissions of the past two years, most winning models use support vector machines (SVM). Riding on the recent trends of deep learning, this work applies deep neural nets to solve this task. We design a combined model with aspect prediction and sentiment prediction. For both predictions, we achieve better than or close to state-of-theart performance using deep learning models. We also propose a new method to combine the syntactic structure and convolutional neural nets to directly match aspects and corresponding polarities.
A Coarse-Grained Reconfigurable Architecture for Compute-Intensive MapReduce Acceleration

Large-scale workloads often show parallelism of different levels. which offers acceleration potential for clusters and parallel processors. Although processors such as GPGPUs and FPGAs show good performance of speedup, there is still vacancy for a low power, high efficiency and dynamically reconfigurable one, and coarse-grained reconfigurable architecture (CGRA) seems to be one possible choice. In this paper, we introduce how we use our CGRA fabric Chameleon to realize a dynamically reconfigurable acceleration to MapReduce-based (MR-based) applications. A FPGA-shell-CGRA-core (FSCC) architecture is designed for the acceleration PCI-Express board, and a programming model with compilation flow for CGRA is presented. With the supports above, a small evaluation cluster with Hadoop framework is set up, and experiments on compute-intensive applications show that the programming process is significantly simplified, with an 30-60<inline-formula><tex-math notation="LaTeX">$\times$</tex-math><alternatives> <inline-graphic xlink:href="liang-ieq1-2458318.gif"/></alternatives></inline-formula> speedup offered under low power.