Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Service Composition Network from Social Network Analysis and User Historical Composite Services

Service composition, which achieves the goal of value-added services, has been considered as the core technique of Service-oriented Computing (SOC). To cope with the challenge of ever-increasing number of web services, graph-based web service network has emerged as a potential solution to the state of art SOC. In such a way, composite services are constructed by applying searching algorithms to the built graph, and proved to achieve outstanding performance in complexity. However, web service network suffers two crucial disadvantages: poor connectivity and negative links, and both of them have crucial negative impact on service composition. To cope with the problems, we propose two methods in this paper. Firstly, leveraging social network analysis, we focus on enriching web service network by adding valuable services, which will play positive roles in solving poor connective problem. Secondly, we show a serious status that numerous negative links contained in the underlying networks, and then we propose to identify and remove the negative links based on users’ historical composite services.
Implementation of the Digital Correlation Unit for Synthetic Aperture Interferometric Radiometer

A Ka-band two dimensional Synthetic Aperture Interferometric Radiometer (SAIR) called BHU-2D-U has been developed. The radiometer can obtain images in real-time benefiting from the adoption of the Digital Correlation Unit (DCU). The DCU requires a data acquisition module to digitalize the received analog signal and a correlation module to compute the visibility function samples. The design and implement of the DCU in BHU-2D-U will be presented in this paper. Based on the system requirements, the performance of the digital acquisition module in BHU-2D-U is discussed. For correlation module, a pipeline structure is proposed to improve the computational efficiency. A series of validation experiments have been conducted. Measurement results have proved that the performance of the DCU can meet the requirements of BHU-2D-U system.
Collegiate Recreational Sports Participation as an Adjustment Aid for Former High School Athletes Experiencing Athlete Role Exit

Successful transition to college is an important consideration in student retention and success. Students who highly identify as high school athletes may experience adjustment difficulty when entering college without this role. The current study investigates participation in collegiate recreation programs as part of a positive adjustment process after the transition out of high school athletics. Results indicated that those with high involvement in collegiate recreation programs had greater perceptions of loss related to the cessation of their athlete role, but also experienced greater perceptions of life satisfaction. Feelings of loss following sport role exit were found to interact with recreational sports involvement on the outcome variable of life satisfaction. Specifically, among those with high loss levels, high recreational sports involvement was associated with greater satisfaction. Results have implications regarding the support of collegiate recreation as a contributor to the successful transition to college, particularly for students experiencing difficulty related to an exit from the high school athlete role.
A Novel Classification Strategy to Distinguish Five Levels of Pain Using the EEG Signal Features

Research studies have tried to extract pain-related features from electroencephalogram(EEG) signals for quantitative measuring of pain. In this study, we go one step further to measure three/five levels of pain by proposing efficient EEG processing steps in conjunction with a new classification strategy. 24 healthy subjects voluntarily performed the cold pressor test while their EEGs were recorded. First, the EEGs were decomposed by independent component analysis and the artifact sources were removed. Among the remained sources, pain-related sources, were chosen according to an adopted information criterion. Next, the EEGs were reconstructed by projecting back the selected sources. Then, grand average brain maps of train subjects were estimated for each pain level over the Alpha(8-12 Hz) and Delta(0.5-4 Hz) bands. By tracing the brain maps' changes over different pain levels, the structure of the proposed decision tree was formed. To enrich the feature set, we also extracted other EEG features. For each decision node, a specific subset of features was selected by sequential forward selection method. Considering <italic>k</italic>-nearest neighbor(KNN) as the decision marker,the classification accuracies for the three and five pain levels was determined <inline-formula><tex-math notation="LaTeX">${{80\pm 5}}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>80</mml:mn><mml:mo>±</mml:mo><mml:mn>5</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="nezam-ieq1-2851236.gif"/></alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">${{60\pm 5}}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>60</mml:mn><mml:mo>±</mml:mo><mml:mn>5</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="nezam-ieq2-2851236.gif"/></alternatives></inline-formula> percent, respectively while by choosing support vector machine(SVM), the results improved up to <inline-formula><tex-math notation="LaTeX">${{83\pm 5}}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>83</mml:mn><mml:mo>±</mml:mo><mml:mn>5</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="nezam-ieq3-2851236.gif"/></alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">${{62\pm 6}}$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>62</mml:mn><mml:mo>±</mml:mo><mml:mn>6</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="nezam-ieq4-2851236.gif"/></alternatives></inline-formula> percent,respectively.
Thermal Spreading Resistance Inside Anisotropic Plates with Arbitrarily Located Hotspots

Graphite-based anisotropic materials are becoming the key component of next-generation cooling systems in electronics and telecommunication industries. Proper use of these materials in the form of thermal spreaders, compared to conventional metallic ones, can significantly reduce the thermal stress and thermal resistance in the system. In this study, a new analytical model for temperature distribution inside anisotropic rectangular plates subjected to multiple sources and sinks on the top and bottom surfaces is presented. All lateral faces are assumed insulated. The solution is first justified for the case with single hotspots on each side and then using the superposition principle, it is extended into the general form to cover multihotspot cases. The model is validated by numerical simulation data and a perfect agreement is observed. Thermal spreading resistance is defined for the anisotropic plate and a comprehensive parametric study for optimization purpose is performed. The influence of both anisotrop.
Community Detection Algorithm Combining Stochastic Block Model and Attribute Data Clustering

We propose a new algorithm to detect the community structure in a network that utilizes both the network structure and vertex attribute data. Suppose we have the network structure together with the vertex attribute data, that is, the information assigned to each vertex associated with the community to which it belongs. The problem addressed this paper is the detection of the community structure from the information of both the network structure and the vertex attribute data. Our approach is based on the Bayesian approach that models the posterior probability distribution of the community labels. The detection of the community structure in our method is achieved by using belief propagation and an EM algorithm. We numerically verified the performance of our method using computer-generated networks and real-world networks.
Nonlinear filtering with perfect discrete time observations

We consider the problem of estimating the state of a diffusion process, based on discrete time observations in singular noise. We reduce the problem to a static problem, and we show that the solution is provided by the area or co-area formula of geometric measure theory, provided the observed value is a regular value of the observation function. In order to address the case of singular values, we propose another approach, based on small-noise perturbation and asymptotics of Laplace integrals.
Dynamics of Search Engine Rankings - A Case Study

The objective of this study was to characterize the changes in the rankings of the top-n results of major search engines over time and to compare the rankings between these engines. We considered only the top-ten results, since users usually inspect only the first page returned by the search engine, which normally contains ten results. In particular, we compare rankings of the top ten results of the search engines Google and AlltheWeb on identical queries over a period of three weeks. The experiment was repeated twice, in October 2003 and in January 2004 in order to assess changes to the top ten results of some of the queries during a three months period. Results show that the rankings of AlltheWeb were highly stable over each period, while the rankings of Google underwent constant yet minor changes, with occasional major ones. Changes over time can be explained by the dynamic nature of the Web or by fluctuations in the search engines’ indexes (especially when frequent switches in the rankings are observed). The top ten results of the two search engines have surprisingly low overlap. With such small overlap (occasionally only a single URL) the task of comparing the rankings of the two engines becomes extremely challenging, and additional measures are needed to assess rankings in such situations.
Object Tracking via Robust Multitask Sparse Representation

Sparse representation has been applied to the object tracking problem. Mining the self-similarities between particles via multitask learning can improve tracking performance. However, some particles may be different from others when they are sampled from a large region. Imposing all particles share the same structure may degrade the results. To overcome this problem, we propose a tracking algorithm based on robust multitask sparse representation (RMTT) in this letter. When we learn the particle representations, we decompose the sparse coefficient matrix into two parts in our algorithm. Joint sparse regularization is imposed on one coefficient matrix while element-wise sparse regularization is imposed on another matrix. The former regularization exploits self-similarities of particles while the later one considers the differences between them. Experiments on the benchmark data show the superior performance over other state-of-art algorithms.
Consciousness and the cerebral cortex.

The scientific study of conciousness is difficult. Indeed, the enterprise seems to be almost a contradiction in terms. By most people's standards science cannot begin until the subject to be investigated has a definition, written down and generally agreed. "Consciousness" has no such definition. There have, in fact, been many serious attempts to remedy the situation. The most successful move consisted of a change of name. "Level of arousal" is the phrase usually used by psychologists to refer to those aspects of human experience and animal behaviour which are linked to "consciousness". The change of label is itself important and constructive. "Consciousness", with its antithesis "unconsciousness", implies a bistable system. "Level of arousal" implies that the system is capable of subtle and continuous variation—obviously a much better description of what one actually observes. Unfortunately, the invention of a rather better name has been the only successful step towards adequate definition. Attempts to go further, and to achieve the scientific ideal—a fully agreed definition, specifying measurable changes in a clearly defined variable—have all failed. Definitions abound, but consensus is totally unobtainable, a failure which has been described and documented by Andrew (1974).
A style controller for generating virtual human behaviors

Creating a virtual character that exhibits realistic physical behaviors requires a rich set of animations. To mimic the variety as well as the subtlety of human behavior, we may need to animate not only a wide range of behaviors but also variations of the same type of behavior influenced by the environment and the state of the character, including the emotional and physiological state. A general approach to this challenge is to gather a set of animations produced by artists or motion capture. However, this approach can be extremely costly in time and effort. In this work, we propose a model that can learn styled motion generation and an algorithm that produce new styles of motions via style interpolation. The model takes a set of styled motions as training samples and creates new motions that are the generalization among the given styles. Our style interpolation algorithm can blend together motions with distinct styles, and improves on the performance of previous work. We verify our algorithm using walking motions of different styles, and the experimental results show that our method is significantly better than previous work.
Design methodology for multifunction vehicle bus devices

The specifications analysis for an MVB (Multifunction Vehicle Bus) bus administrator showed that system-on-a-chip strategies should be adopted to cope with its great complexity. Particularly, a new hardware/software codesign methodology has been followed. Its main concept is that the MVB devices (the bus administrator itself and the less complex devices) constitute a "progressive family". This notion establishes a functional partition that helps to generate the behavioral design: 14 operational blocks and a special memory for the communication data. The whole architecture has been coded in SystemC, not only for verification purposes, but also to set the start point in hardware/software partitioning. After validating this executable description by simulation, estimations about cost and performance in both, hardware and software, have been made. From these, an optimum hardware-software architecture has been obtained. As a result, the electronic platform for the Master device has been generated on an FPGA.
An efficient and fast local algorithm to identify clusters in networks

Resumen. A characteristic feature of many relevant real life networks, like the WWW, Internet, transportation and communication networks, or even biological and social networks, is their clustering structure. We discuss in this paper a novel algorithm to identify clusters -sets of densely interconnected nodesin a network. The algorithm is based on local information and therefore it is very fast with respect other proposed methods, while it keeps a similar performance in detecting the clusters.
Piecewise-consistent color mappings of images acquired under various conditions

Many applications in computer vision require comparisons between two images of the same scene. Comparison applications usually assume that corresponding regions in the two images have similar colors. However, this assumption is not always true. One way to deal with this problem is to apply a color mapping to one of the images. In this paper we address the challenge of computing color mappings between pairs of images acquired under different acquisition conditions, and possibly by different cameras. For images taken from different viewpoints, our proposed method overcomes the lack of pixel correspondence. For images taken under different illumination, we show that no single color mapping exists, and we address and solve a new problem of computing a minimal set of piecewise color mappings. When both viewpoint and illumination vary, our method can only handle planar regions of the scene. In this case, the scene planar regions are simultaneously co-segmented in the two images, and piecewise color mappings for these regions are calculated. We demonstrate applications of the proposed method for each of these cases.
mTOR Directs Breast Morphogenesis through the PKC-alpha-Rac1 Signaling Axis

Akt phosphorylation is a major driver of cell survival, motility, and proliferation in development and disease, causing increased interest in upstream regulators of Akt like mTOR complex 2 (mTORC2). We used genetic disruption of Rictor to impair mTORC2 activity in mouse mammary epithelia, which decreased Akt phosphorylation, ductal length, secondary branching, cell motility, and cell survival. These effects were recapitulated with a pharmacological dual inhibitor of mTORC1/mTORC2, but not upon genetic disruption of mTORC1 function via Raptor deletion. Surprisingly, Akt re-activation was not sufficient to rescue cell survival or invasion, and modestly increased branching of mTORC2-impaired mammary epithelial cells (MECs) in culture and in vivo. However, another mTORC2 substrate, protein kinase C (PKC)-alpha, fully rescued mTORC2-impaired MEC branching, invasion, and survival, as well as branching morphogenesis in vivo. PKC-alpha-mediated signaling through the small GTPase Rac1 was necessary for mTORC2-dependent mammary epithelial development during puberty, revealing a novel role for Rictor/mTORC2 in MEC survival and motility during branching morphogenesis through a PKC-alpha/Rac1-dependent mechanism.
Investigation of bacteria in the agricultural by-products imported for the use as media materials in mushroom cultivation

*For correspondence. E-mail: piceae@dankook.ac. kr; Tel. : +82-41-550-3454; Fax: +82-41-523-3454 It is urgently required to construct safety data on agricultural by-products imported for use as medium materials for domestic mushroom production. However, research on microorganisms is insufficient. This study was conducted to investigate the presence of bacteria that have the possibility of harmful effects on human, plants and mushroom in wheat straw, peatmoss, cottonseed hull, cottonseed meal, and beet pulp imported from Australia, Canada, China, Egypt, Germany. Bacteria were found in the range of 1.35 × 10 2 to 8.34 × 10 6 CFU/g. As a result of 16S rDNA sequence analysis, total of 19 genera and 45 species of bacteria were identified. Bacillus genus was dominant, followed by Paenibacillus genus. At the species level, diverse species was in the order of Firmicute, Proteobacteria and Actinobacteria. Regarding the agricultural by-products, straw and peat moss had more diverse bacteria than other agricultural by-products. Among the indentified bacteria, 6 species of 5 genera (Enterobacter asburiae, Enterobacter ludwigii, Stenotrophomonas maltophilia, Pseudomonas monteilii, Bacillus anthracis, and Cellulosimicrobium funkei) were present as potent harmful bacteria to human. Surprisingly, both the human and plant pathogenic Klebsiella pneumoniae subsp. pneumonia was present. Bacillus altitudinis was present as a plant pathogen. Lysinibacillus sphaericus, an insect pathogen, and Ochrobactrum pseudogrignonense, a mushroom pathogen, were also present. The results of this study confirmed that several kinds of pathogenic bacteria were present in the agricultural by-products for the mushroom cultivation medium imported into Korea. Our work suggests that hygiene inspection and management is urgently needed for imported agricultural by-products to be safely used for mushroom production.
Discovery of VHE gamma-rays from the high-frequency-peaked BL lacertae object RGB J0152+017

Aims: The BL Lac object RGB J0152+017 (z=0.080) was predicted to be a very high-energy (VHE; > 100 GeV) gamma-ray source, due to its high X-ray and radio fluxes. Our aim is to understand the radiative processes by investigating the observed emission and its production mechanism using the High Energy Stereoscopic System (H.E.S.S.) experiment. Methods: We report recent observations of the BL Lac source RGB J0152+017 made in late October and November 2007 with the H.E. S.S. array consisting of four imaging atmospheric Cherenkov telescopes. Contemporaneous observations were made in X-rays by the Swift and RXTE satellites, in the optical band with the ATOM telescope, and in the radio band with the Nancay Radio Telescope. Results: A signal of 173 gamma-ray photons corresponding to a statistical significance of 6.6 sigma was found in the data. The energy spectrum of the source can be described by a powerlaw with a spectral index of 2.95+/-0.36stat+/-0.20syst. The integral flux above 300 GeV corresponds to ~2% of the flux of the Crab nebula. The source spectral energy distribution (SED) can be described using a two-component non-thermal synchrotron self-Compton (SSC) leptonic model, except in the optical band, which is dominated by a thermal host galaxy component. The parameters that are found are very close to those found in similar SSC studies in TeV blazars. Conclusions: RGB J0152+017 is discovered as a source of VHE gamma-rays by H.E. S.S. The location of its synchrotron peak, as derived from the SED in Swift data, allows clearly classification it as a high-frequency-peaked BL Lac (HBL).
‘You can see their minds grow’: identity development of LGBTQ youth at a residential wilderness camp

ABSTRACT There is a substantial literature on the meaning of residential wilderness camps for youth and the benefits that they experience as a result of these camps. However, there is little work that details the experiences of Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ) youth at camps that are specifically designed for them and run by LGBTQ staff. Two focus groups were held at an LGBTQ camp and qualitative data analysis was undertaken. Results indicate support for the extant camp literature through positive identity development, experiences of social inclusion as well as support for cultivating positive attitudes toward physical activity. There was a lack of evidence to support increased spiritual connections and environmental awareness, possibly due to emphasizing programming around queer issues rather than intentionally programming nature-based activities and facilitating spiritual connections.
Constant Proportion Portfolio Insurance in Presence of Jumps in Asset Prices

Constant proportion portfolio insurance (CPPI) allows an investor to limit downside risk while retaining some upside potential by maintaining an exposure to risky assets equal to a constant multiple of the cushion, the difference between the current portfolio value and the guaranteed amount. Whereas in diffusion models with continuous trading, this strategy has no downside risk, in real markets this risk is nonnegligible and grows with the multiplier value. We study the behavior of CPPI strategies in models where the price of the underlying portfolio may experience downward jumps. Our framework leads to analytically tractable expressions for the probability of hitting the floor, the expected loss, and the distribution of losses. This allows to measure the gap risk but also leads to a criterion for adjusting the multiplier based on the investor's risk aversion. Finally, we study the problem of hedging the downside risk of a CPPI strategy using options. The results are applied to a jump-diffusion model with parameters estimated from returns series of various assets and indices.
Fault Detection in Hard Disk Drives Based on Mixture of Gaussians

Being able to detect faults in Hard Disk Drives (HDD) can lead to significant benefits to computer manufacturers, users and storage system providers. As a consequence, several works have focused on the development of fault detection algorithms for HDDs. Recently, promising results were achieved by methods using SMART (Self-Monitoring Analysis and Reporting Technology) features and anomaly detection algorithms based on Mahalanobis distance. Nevertheless, the performance of such methods can be seriously degraded when the normality assumption of the data does not hold. As a way to overcome this issue, we propose a new method for fault detection in HDD based on a Gaussian Mixture Model (GMM). The proposed method is tested in a real world dataset and its performance is compared to three other HDD fault detection methods.