Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the integration of a query mechanism and navigation for retrieval of data on multimedia documents

Traditionally, two paradigms are discerned with respect to data retrieval [3, 17]:1. A query mechanism enables the user to express conditions that characterize the data he is looking for. The Data Base Management System (DBMS) is responsible for retrieval of the data that satisfy these conditions.2. Navigation or browsing can be used to investigate the content of the database by following links between related data.We will start with a discussion of these paradigms in the first two sections. We will then explore how both approaches can be combined. Finally, a practical implementation of the advocated approach will be presented. The implemented prototype supports access to a database on multimedia material. A more elaborated discussion of our ideas and results in this area can be found in [16].
The Road of ERP Success: a Framework Model for Successful ERP Implementation

To compete with nowadays business is to implement technology and align it into their business strategy. One of technology that commonly implement is Enterprise Resource Planning (ERP). This research will examined what are critical success factor of ERP and the impact of their business outcomes. A framework model for ERP Implementation success is constructs from several research or previous study in Implementation ERP. This study will extends in the research field of successful implementation ERP and implication factor for business practice to have more knowledge in term of implementation ERP and their business strategy.
General Concentric Black Rings

Supersymmetric black ring solutions of five-dimensional supergravity coupled to an arbitrary number of vector multiplets are constructed. The solutions are asymptotically flat and describe configurations of concentric black rings which have regular horizons with topology ${S}^{1}\ifmmode\times\else\texttimes\fi{}{S}^{2}$ and no closed timelike curves at the horizons.
affylmGUI: a graphical user interface for linear modeling of single channel microarray data

SUMMARY affylmGUI is a graphical user interface (GUI) to an integrated workflow for Affymetrix microarray data. The user is able to proceed from raw data (CEL files) to QC and pre-processing, and eventually to analysis of differential expression using linear models with empirical Bayes smoothing. Output of the analysis (tables and figures) can be exported to an HTML report. The GUI provides user-friendly access to state-of-the-art methods embodied in the Bioconductor software repository. AVAILABILITY affylmGUI is an R package freely available from http://www.bioconductor. org. It requires R version 1.9. 0 or later and tcl/tk 8.3 or later and has been successfully tested on Windows 2000, Windows XP, Linux (RedHat and Fedora distributions) and Mac OS/X with X11. Further documentation is available at http://bioinf.wehi.edu.au/affylmGUI CONTACT: keith@wehi.edu.au.
A Survey of Terahertz Applications in Cultural Heritage Conservation Science

The authors present a review of the advances that have been made to establish terahertz applications in the cultural heritage conservation sector over the last several years. This includes material spectroscopy, 2D and 3D imaging and tomographic studies, using a broad range of terahertz sources demonstrating the breadth and application of this burgeoning community.
Maximally Stable Color Regions Based Natural Scene Recognition

In this paper, we propose a maximally stable color regions (MSCR) based method to perform reliable scene recognition. Firstly, to construct the maximally stable regions, we exploit the MSCR detector for improving the identification of stable regions. Secondly, each detected region is processed properly by using the method of mathematics morphology. Finally, the descriptor is computed using the scale invariant feature transform (SIFT), with the detected MSCR regions as input. The matching result is obtained according to the nearest neighbor matching based on Euclidean distance of SIFT descriptors. The experimental results prove that this algorithm wins high recognition accuracy and robustness against non-linear image intensity transformation, a substantial range of affine distortion and changes in 3D viewpoint. Also we compare our algorithm to the global appearance based method, and show through experiments in both indoor and outdoor environments that our approach performs better.
Modelling Long Lifetime Systems : Building a Referential with UML

The capacity for large software intensive systems to be operational for a long time (about twenty years or more) raises many complex problems. Information about their definition and design, but also about the various products developed for their realisation and their verification is of crucial importance in order to succeed when functional or technological evolutions are required. One goal in two of our current studies is to address the definition of information models for the representation of system engineering data. The considered applications are defense systems and avionics systems. This paper presents an overview of some of these information models we defined with a focus on the representation of one particular category of information: the modelling of requirements. Requirements are the reference for verification and validation and, any required change/evolution should be analysed against the system requirements in order to determine what are the impacts of changes. Our information models are expressed by using the UML notation.
Genetic Algorithm to Compute Fuzzy FS-Testors

In this paper, a genetic algorithm to compute sets of attributes, which maintain similarity between objects in a same class, and at same time, these sets of attributes distinguish objects in a class of objects in the other classes (FS-testors), is presented. Since the computational complexity to compute fuzzy FS-testors is exponential, our algorithm appear as an alternative to solve practical problems of classification or feature selection. The application of the algorithm to a set of objects in a standard public database is shown. Key-Words: FS-Testors, Testors, Genetic Algorithm, Feature Selection
Robust Principal Component Analysis by Projection Pursuit

Different algorithms for principal component analysis (PCA) based on the idea of projection pursuit are proposed. We show how the algorithms are constructed, and compare the new algorithms with standard algorithms. With the R implementation pcaPP we demonstrate the usefulness at real data examples. Finally, it will be outlined how the algorithms can be used for robustifying other multivariate methods.
A survey of controlled experiments in software engineering

The classical method for identifying cause-effect relationships is to conduct controlled experiments. This paper reports upon the present state of how controlled experiments in software engineering are conducted and the extent to which relevant information is reported. Among the 5,453 scientific articles published in 12 leading software engineering journals and conferences in the decade from 1993 to 2002, 103 articles (1.9 percent) reported controlled experiments in which individuals or teams performed one or more software engineering tasks. This survey quantitatively characterizes the topics of the experiments and their subjects (number of subjects, students versus professionals, recruitment, and rewards for participation), tasks (type of task, duration, and type and size of application) and environments (location, development tools). Furthermore, the survey reports on how internal and external validity is addressed and the extent to which experiments are replicated. The gathered data reflects the relevance of software engineering experiments to industrial practice and the scientific maturity of software engineering research.
Simulation of the Expanded Iterated Version of the Prisoner's Dilemma Game

This paper presents the model and software to explore pair interactions of objects with different behavior and their patterns. The research is based on the enhanced version of a classic prisoner’s dilemma game. The non-cooperative finite and infinite pair games with non-zero sums are investigated. Pure and mixed strategies with finite and infinite memory developed by Biology School of V. N. Karazin Kharkiv National University are used to analyze the results.
Claim Synthesis via Predicate Recycling

Computational Argumentation has two main goals - the detection and analysis of arguments on the one hand, and the synthesis of arguments on the other. Much attention has been given to the former, but considerably less to the latter. A key component in synthesizing arguments is the synthesis of claims. One way to do so is by employing argumentation mining to detect claims within an appropriate corpus. In general, this appears to be a hard problem. Thus, it is interesting to explore if - for the sake of synthesis - there may be other ways to generate claims. Here we explore such a method: we extract the predicate of simple, manually-detected, claims, and attempt to generate novel claims from them. Surprisingly, this simple method yields fairly good results.
Object Recognition Based on Biologic Visual Mechanisms

For speedy robust object recognition, our model builds on Serre’s standard model and modifies it by additional biological characteristics, such as introducing the manner of neuron firing, feature localization, and merging unit features in the higher layers. According to the four-layer architecture of standard model, we first apply Gabor filters on a higher intermediate frequency band of original image, and then compute the number of firing neurons in the next layer to create shift- and scale-tolerance. To build up feature complexity we use prototype matching for all scales in the third layer. In the last layer we max pool local units to achieve larger shift-tolerance. We use SVM at the classifying stage. Tested on the Caltech datasets, our improved model offers a significant gain in speed with fewer features and achieves even better state-of-the-art performance than standard model.
Towards a CRM and SCM Benefits Measurement Model

Organizations invest heavily in Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems, and their related infrastructure, presumably expecting positive benefits to the organization. Assessing the benefits of such systems is an important aspect of managing such systems. Given the substantial differences between CRM and SCM systems with traditional intra-organizational applications, existing Information Systems benefits measurement models and frameworks are ill-suited to gauge CRM and SCM benefits. This paper reports the preliminary findings of a research that seeks to develop a measurement model to assess benefits of CRM and SCM applications. The a-priori benefits measurement model is developed reviewing the 55 academic studies and 40 practitioner papers. The review of related literature yielded 606 benefits, which were later synthesized into 74 mutually exclusive benefit measures of CRM and SCM applications arranged under five dimensions.
Fast bivariate P‐splines: the sandwich smoother

We propose a fast penalized spline method for bivariate smoothing. Univariate P‐spline smoothers are applied simultaneously along both co‐ordinates. The new smoother has a sandwich form which suggested the name ‘sandwich smoother’ to a referee. The sandwich smoother has a tensor product structure that simplifies an asymptotic analysis and it can be fast computed. We derive a local central limit theorem for the sandwich smoother, with simple expressions for the asymptotic bias and variance, by showing that the sandwich smoother is asymptotically equivalent to a bivariate kernel regression estimator with a product kernel. As far as we are aware, this is the first central limit theorem for a bivariate spline estimator of any type. Our simulation study shows that the sandwich smoother is orders of magnitude faster to compute than other bivariate spline smoothers, even when the latter are computed by using a fast generalized linear array model algorithm, and comparable with them in terms of mean integrated squared errors. We extend the sandwich smoother to array data of higher dimensions, where a generalized linear array model algorithm improves the computational speed of the sandwich smoother. One important application of the sandwich smoother is to estimate covariance functions in functional data analysis. In this application, our numerical results show that the sandwich smoother is orders of magnitude faster than local linear regression. The speed of the sandwich formula is important because functional data sets are becoming quite large.
Natural Sound Rendering for Headphones: Integration of signal processing techniques

With the strong growth of assistive and personal listening devices, natural sound rendering over headphones is becoming a necessity for prolonged listening in multimedia and virtual reality applications. The aim of natural sound rendering is to naturally recreate the sound scenes with the spatial and timbral quality as natural as possible, so as to achieve a truly immersive listening experience. However, rendering natural sound over headphones encounters many challenges. This tutorial article presents signal processing techniques to tackle these challenges to assist human listening.
Bayesian Inference Algorithm on Raw by Alda Luong

This work explores the performance of Raw, a parallel hardware platform developed at MIT, running a Bayesian inference algorithm. Motivation for examining this parallel system is a growing interest in creating a self-learning and cognitive processor, which these hardware and software components can potentially produce. The Bayesian inference algorithm is mapped onto Raw in a variety of ways to try to account for the fact that different implementations give different processor performance. Results for the processor performance, determined by looking at a wide variety of metrics look promising, suggesting that Raw has the potential to successfully run such algorithms.
A Crosslinked HA-Based Hydrogel Ameliorates Dry Eye Symptoms in Dogs

Keratoconjunctivitis sicca, commonly referred to as dry eye or KCS, can affect both humans and dogs. The standard of care in treating KCS typically includes daily administration of eye drops to either stimulate tear production or to hydrate and lubricate the corneal surface. Lubricating eye drops are often applied four to six times daily for the life of the patient. In order to reduce this dosing regimen yet still provides sufficient hydration and lubrication, we have developed a crosslinked hydrogel based on a modified, thiolated hyaluronic acid (HA), xCMHA-S. This xCMHA-S gel was found to have different viscosity and rheologic behavior than solutions of noncrosslinked HA. The gel was also able to increase tear breakup time in rabbits, indicating a stabilization of the tear film. Further, in a preliminary clinical study of dogs with KCS, the gel significantly reduced the symptoms associated with KCS within two weeks while only being applied twice daily. The reduction of symptoms combined with the low dosing regimen indicates that this gel may lead to both improved patient health and owner compliance in applying the treatment.
OPTIMIZING SPARSE MATRIX-VECTOR MULTIPLICATION BASED ON GPU

In recent years, Graphics Processing Units(GPUs) have attracted the attention of many application developers as powerful massively parallel system. Computer Unified Device Architecture (CUDA) as a general purpose parallel computing architecture makes GPUs an appealing choice to solve many complex computational problems in a more efficient way. Sparse Matrix-vector Multiplication(SpMV) algorithm is one of the most important scientific computing kernel algorithms. In this paper, we proposed new parallelization algorithms that CSR-M based on CSR format and ELLPACK-R based on ELLPACK format, which are realized the parallelism kernel on GPU with CUDA. We discussed implementing optimizing SpMV on GPUs using CUDA programming model, the optimization strategies including: mapping thread, mergering access, reusing data, avoiding branch, optimization thread block. The experiment results showed the proposed optimization strategies can improve performance, memory bandwidth and reduce the execution time of kernel.
Primary Aldosteronism in Diabetic Subjects With Resistant Hypertension

OBJECTIVE Despite the high prevalence of hypertension in patients with type 2 diabetes, the prevalence of primary aldosteronism in this population has not been determined. RESEARCH DESIGN AND METHODS One hundred subjects with type 2 diabetes and resistant hypertension, defined as blood pressure > 140/90 mmHg despite the use of > or = 3 antihypertensive agents, were screened for primary aldosteronism. Screening was performed by measuring the plasma aldosterone (PAC)-to-plasma renin activity (PRA) ratio. Subjects with a PAC-to-PRA ratio > 30 ng x ml(-1) x h(-1) underwent confirmatory salt load testing. Diagnostic criteria included 24-h urine aldosterone > or = 12 microg during the 3rd day of the oral salt load or a PAC > or = 5 ng/dl after the 4-h intravenous saline load. RESULTS Thirty-four subjects had a PAC-to-PRA ratio >30 ng x ml(-1) x h(-1). Fourteen subjects (14% [95% CI 7.2-20.8]) had a confirmed diagnosis of primary aldosteronism. Ninety-three patients were African Americans. There were no differences in age, glycemic control, and number of antihypertensive drugs between subjects with and without primary aldosteronism. Subjects with primary aldosteronism had lower serum potassium (3.7 +/- 0.4 vs. 4.0 +/- 0.4 mmol/l, P = 0.012), higher PAC (15.6 +/- 8 vs. 9.1 +/- 6 ng/dl, P = 0.0016), and higher PAC-to-PRA ratio (98 +/- 74 vs. 21 +/- 30 x ml(-1) x h(-1), P < 0.001) than patients without primary aldosteronism. CONCLUSIONS Primary aldosteronism is common in diabetic patients with resistant hypertension, with a prevalence of 14%. Our results indicate that diabetic subjects with poorly controlled hypertension who are taking > or = 3 antihypertensive drugs should be screened for primary aldosteronism.
Photometric redshifts from evolutionary synthesis with PÉGASE: The code Z-PEG and the z=0 age constraint

Photometric redshifts are estimated on the basis of template scenarios with the help of the code Z-PEG, an extension of the galaxy evolution model P EGASE.2 and available on the P EGASE web site. The spectral energy distribution (SED) templates are computed for nine spectral types including starburst, irregular, spiral and elliptical. Dust, extinction and metal eects are coherently taken into account, depending on evolution scenarios. The sensitivity of results to adding near-infrared colors and IGM absorption is analyzed. A comparison with results of other models without evolution measures the evolution factor which systematically increases the estimated photometric redshift values byz 0:2 for z> 1:5. Moreover we systematically check that the evolution scenarios match observational standard templates of nearby galaxies, implying an age constraint of the stellar population at z = 0 for each type. The respect of this constraint makes it possible to signicantly improve the accuracy of photometric redshifts by decreasing the well-known degeneracy problem. The method is applied to the HDF-N sample (see in Fern andez-Soto et al. 1999). From ts on SED templates by a 2 -minimization procedure, not only is the photometric redshift derived but also the corresponding spectral type and the formation redshift zfor when stars rst formed. Early epochs of galaxy formationzfor > 5 are found from this new method and results are compared to faint galaxy count interpretations. The new tool is available at: http://www.iap. fr/pegase
Automatic segmentation fusing color and depth

Graph-based segmentation requires interactive input, and color segmentation poses challenges when foreground has similar color with background. This paper presents an automatic robust segmentation fusing color and depth. A saliency detection algorithm based on visual attention is proposed. Depth is firstly used as a filter to limit object pixel candidates, color is used to further detect object region by saliency calculation. The saliency detection algorithm is incorporated into graph-based segmentation by automatically setting the detected range as uncertain pixel set. Our segmentation algorithm uses color as main information to set energy terms of graph function, and uses depth as supplemental information to adjust these terms basing on consistency decision of color and depth. Experimental results demonstrate that the proposed segmentation enhances the performance using color alone, and realizes fully automation.
Factors influencing residents' attitude towards marine resource utilization in Tun Sakaran Marine Park, Malaysia

Communities living in the Tun Sakaran Marine Park (TSMP) depend on the marine resources for their livelihood. The marine park is managed by state government, the Sabah Parks, with the main objective of conserving the high marine biodiversity in the area. The communities living in the area use the resources on a daily basis, for family consumption and subsistence. The marine park is also popular for its world class diving sites which has contributed to the growth of the ecotourism industry. The main objective of this study is to determine the sociodemographic characteristics of the resident communities in order to evaluate the factors that determine the attitude of the communities towards the utilization of the marine resources. Data from 116 respondents in three islands in the park were collected using the convenient sampling method. Results of the regression analysis showed that citizenship (non-citizen), education, sense of ownership to the place and responses towards destructive fishing methods had significant influences on the attitudes towards the utilization of the marine resources. Relevant agencies can help to improve the attitudes of the communities by increasing awareness of the communities through informal education and providing extension information to reduce uses of destructive fishing methods.
Hybrid CMOS-memristor based FPGA architecture

It is understood that FPGAs suffer in terms of area, performance and power consumption relative to ASICs. With increasing demand for greater density and lower power consumption in memory devices, memristors have emerged as a cutting-edge alternative to transistor based circuitry. The basic issue of static power consumption in routing architecture is solved here as there is no static current flow in memristors; they hold their state when no power is applied. In this paper, a single memory cell based on hybrid technology is designed using TEAM model in memristors. In addition, the design of a configurable logic block (CLB), which can be used to fabricate a hybrid CMOS - Memristor FPGA architecture is explained. The paper also presents an Interconnect design based on hybrid technology which is very easy to design and flexible to program. As the routing architecture is the most important factor determining system speed, this hybrid interconnect could create a new generation of fast and power efficient memristor based FPGAs.
Aberrant amplification of torsional oscillating torques in turbine-generator shaft due to multiple EAF operation

Electric arc furnace (EAF) acts as a source of sub-synchronous frequencies (SSFs) in the electrical network. If these SSFs lead to resonance, respective matched torsional modes of turbine-generator (T-G) shaft are excited causing torsional oscillating torques (TOTs) amplification. This may lead to gear damage, shaft fatigue lifetime reduction, severe damages to T-G shaft. This paper presents an assessment of TOTs amplification due to multiple EAF operations at the same PCC. The EAFs have been modeled using mathematical model of the electric arc, where resistances of EAFs varied deterministically in frequency range of 1.2-45.5 Hz to comport with realistic EAF. TOTs have been measured with/without resonant excitation of torsional modes. Eigenvalue analysis and FFT technique have been used to analyse torsional torques.