Miracle-dz/UniFAR-FTUs huggingface dataset:
Process Platform and Production Configuration for Integrated Manufacturing and Service

In regard to global competition, integrated manufacturing and service systems has emerged as a new manufacturing paradigm to assist manufacturers in achieving faster design, manufacturing and delivery of customer-specified products at low costs. The linchpin of realizing an economy of scale in production in such systems lies in routings to be adopted to produce product variety. This paper thus proposes a concept of production configuration as a means for manufacturers to obtain the set of optimal and similar routings for families of customized products. In turn the economy of scale in production can be achieved through production activity repetition and manufacturing resources reuse. Production configuration has been applied to the high variety production of vibration motors in a local electronics company. The preliminary results show the potential of production configuration for the quick and low cost product fulfillment for integrated manufacturing and service.
Multisensory Facilitation of Behavior in Monkeys: Effects of Stimulus Intensity

Abstract Multisensory stimuli can improve performance, facilitating RTs on sensorimotor tasks. This benefit is referred to as the redundant signals effect (RSE) and can exceed predictions on the basis of probability summation, indicative of integrative processes. Although an RSE exceeding probability summation has been repeatedly observed in humans and nonprimate animals, there are scant and inconsistent data from nonhuman primates performing similar protocols. Rather, existing paradigms have instead focused on saccadic eye movements. Moreover, the extant results in monkeys leave unresolved how stimulus synchronicity and intensity impact performance. Two trained monkeys performed a simple detection task involving arm movements to auditory, visual, or synchronous auditory–visual multisensory pairs. RSEs in excess of predictions on the basis of probability summation were observed and thus forcibly follow from neural response interactions. Parametric variation of auditory stimulus intensity revealed that in both animals, RT facilitation was limited to situations where the auditory stimulus intensity was below or up to 20 dB above perceptual threshold, despite the visual stimulus always being suprathreshold. No RT facilitation or even behavioral costs were obtained with auditory intensities 30–40 dB above threshold. The present study demonstrates the feasibility and the suitability of behaving monkeys for investigating links between psychophysical and neurophysiologic instantiations of multisensory interactions.
A Cascade of Structure in a Drop Falling from a Faucet

A drop falling from a faucet is a common example of a mass fissioning into two or more pieces. The shape of the liquid in this situation has been investigated by both experiment and computer simulation. As the viscosity of the liquid is varied, the shape of the drop changes dramatically. Near the point of breakup, viscous drops develop long necks that then spawn a series of smaller necks with ever thinner diameters. Simulations indicate that this repeated formation of necks can proceed ad infinitum whenever a small but finite amount of noise is present in the experiment. In this situation, the dynamical singularity occurring when a drop fissions is characterized by a rough interface.
Very High Frequency of Hypermethylated Genes in Breast Cancer Metastasis to the Bone, Brain, and Lung

Purpose: Most often it is not the primary tumor, but metastasis to distant organs that results in the death of breast cancer patients. To characterize molecular alterations in breast cancer metastasis, we investigated the frequency of hypermethylation of five genes (Cyclin D2, RAR-β, Twist, RASSF1A, and HIN-1) in metastasis to four common sites: lymph node, bone, brain, and lung. Experimental Design: Methylation-specific PCR for the five genes was performed on DNA extracted from archival paraffin-embedded specimens of paired primary breast cancer and its lymph nodes (LN) metastasis (n = 25 each); in independent samples of metastasis to the bone (n = 12), brain (n = 8), and lung (n = 10); and in normal bone, brain, and lung (n = 22). Results: No hypermethylation was detected in the five genes in the normal host tissues. In paired samples, LN metastasis had a trend of higher prevalence of methylation compared with the primary breast carcinoma for all five genes with significance for HIN-1 (P = 0.04). Compared with the primary breast carcinomas, all five genes had higher methylation frequencies in the bone, brain, and lung metastasis, with HIN-1 and RAR-β methylation being significantly higher (P < 0.01) in each group. Loss of expression of all five genes correlated, with a few exceptions, to hypermethylation of their promoter sequences in metastatic carcinoma cells microdissected from LNs. Conclusion: The frequent presence of hypermethylated genes in locoregional and distant metastasis could render them particularly susceptible to therapy targeted toward gene reactivation combining demethylating agents, histone deacetylase inhibitors, and/or differentiating agents.
Security Solutions for Cloud Computing

In the recent times, most organizations in the world have increasingly realized the importance of cloud platforms. Cloud computing is an emerging technology to store and access personal data along with business information from remote locations. One of the benefits of using cloud computing is the ability to tap into huge quantities of both structured and unstructured data. With every new technology there are certain drawbacks associated with it and cloud is no exception. Unlike others, Cloud environment also faces challenges such as Distributed denial of service (DDoS) attacks, data thefts, particularly when they are insider attacks. Increase in the number of DDoS attacks is one of the latest issues. We have studied various intrusion detection techniques that includes Cloud trace back model, use of back propagation neural network and Virtual Intrusion Detection Systems (V-IDS). Now these attacks can be prevented using the proposed Intrusion Prevention System i.e. Service-based Intrusion Prevention System in Cloud Computing (SIPSCC). A technique called fog computing can be used to detect and prevent data theft attacks by malicious insiders is studied. General Terms Cloud Computing Security
10.4.1 Architected Agile Solutions for Software‐Reliant Systems

Systems are becoming increasingly reliant on software due to needs for rapid fielding of “70%” capabilities, interoperability, net‐centricity, and rapid adaptation to change. The latter need has led to increased interest in agile methods of software development, in which teams rely on shared tacit interpersonal knowledge rather than explicit documented knowledge. However, such capabilities often need to be scaled up to higher level of performance and assurance, requiring stronger architectural support. Several organizations have recently transformed themselves by developing successful combinations of agility and architecture that scale up to projects of up to 100 personnel. This paper identifies a set of key principles for such architected agile solutions for software‐reliant systems, and illustrates them with several case studies.
A data processing architecture for realtime decoding of extremely long LDPC codes

Low-Density Parity-Check (LDPC) codes belong to a class of linear block codes that can approach the Shannon limit. However, due to the high decoding complexity, LDPC codes with extremely long block lengths will result in large decoding latency in practical applications. Recently, Cloud Radio Access Networks (C-RANs) have attracted much attention because of their innovative architecture, which involves embedding cloud computing capability into wireless networks. In this context, C-RANs provide an ideal platform for breaking the decoding bottleneck of LDPC codes with extremely long block lengths. However, given that there are currently as yet no specific cloud computing techniques proposed for C-RAN, the data processing architecture for LDPC decoding is still an open problem. In this paper, based on the Spark cloud computing platform, a data processing architecture is proposed for realtime decoding of extremely long LDPC codes. Based on the principle behind the belief propagation (BP) decoding algorithm, a novel distributed BP decoding algorithm is proposed and implemented on a Spark based cloud computing platform. Extensive experimentation illustrates that the proposed architecture enjoys a significant performance gain in decoding latency. Therefore, this work can be seen as a promising example of applying powerful cloud computing techniques to enhance the performance of wireless networks.
Social support of romantic partners moderates cortisol response to stress

v CHAPTER ONE INTRODUCTION . 1 CHAPTER TWO LITERATURE REVIEW . 4 Theoretical Framework . 5 What Triggers the Release of Cortisol? 7 Operationalizing Stress . 9 Health and Well-being . 15 Social Support: A Natural Resource . 15 Sex Differences . 25 Purpose of This Study . 25 Hypotheses . 26 CHAPTER THREE METHODS . 28 Participants . 28 Study Design . 28 Stress Measure . 31 Social Support Measures. 33 CHAPTER FOUR RESULTS . 41 Statistical Analyses . 41 CHAPTER FIVE DISCUSSION . 51 Summary of Research Findings . 51 Did Social Support Buffer Cortisol Reactivity? 53 Is There Support for Biopsychosocial Processes? 54 Sex Differences . 58 Implications for Health and Well-Being . 58 Limitations of This Study . 59 Conclusion . 60 REFERENCES . 62
RAVIOLI: A parallel video processing library with auto resolution adjustability

Video processing applications are now in demand on a great variety of platforms such as mobile devices or high performance servers. On the other hand, a great variety of performance is required for video processing applications such as high throughput, good accuracy, long battery life, and so on. Therefore, programmers today should study hard about various platforms and techniques under the pressure of necessity. This must make the burden heavy for them. This paper proposes a parallel video processing library RaVioli. RaVioli achieves self-optimizations for multi-core processors and self-adjustment of resolutions. RaVioli conceals two resolutions, frame rate and number of pixels, from users and provides dynamic and transparent resolution adjustability based on user-preferred priority parameters. This makes pseudo real-time video processing feasible for any platform by adjusting resolutions according to situations. Generally, video processing has some parallelism in its algorithm. For example, pixels in a frame have data parallelism, and many video processing algorithms can be divided into some processing stages which can be pipelined. Concealing resolutions makes implicit parallelism more obvious. Hence, RaVioli can parallelize programs semi-automatically.
Analysis of Colon Cancer Dataset using K-Means based Algorithms & See5 Algorithms

Data mining is used in several medical applications like tumor classification, prediction of medical test effectiveness, genomics, proteomics and DNA sequence analysis. Cancer detection is one of the hot research topics in the bioinformatics age. Data mining techniques, such as pattern association, classification and clustering is applied over gene expression data for detection of cancer. Accuracy is the vital thing to be considered during estimation over colon data. Association works on the basis of correlation, classification helps in categorizing and locate accurately, and clustering is the unsupervised learning ability that is able to discover hidden patterns of dataset. The objective of our work is to make comparative study about various clustering algorithms like simple K-means, global K-means, K-means++ and C5 over cancer dataset is made. Clustering algorithms are compared based on accuracy.
African Culture and Lesbian Feminism

Abstract This paper seeks to critically examine the claims of lesbian feminism in the quest for women liberation in a patriarchal society and in relation to its compatibility with culture and human value with particular reference to Africa. The paper analysed the significance of heterosexual relationships in Africa as a major domain where women affect the human race. And notes that the most unique, distinct and unequivocal value of women in Africa is the target of lesbian dissolution. It then charges African women to beware of falling prey to an unpopular pedestal in their struggle for liberation while encouraging them to maintain heterosexual relationships for the purpose of procreation alongside a capacity for public life which will dialectically enhance liberation.
Evolution of mammalian sensorimotor cortex: thalamic projections to parietal cortical areas in Monodelphis domestica

The current experiments build upon previous studies designed to reveal the network of parietal cortical areas present in the common mammalian ancestor. Understanding this ancestral network is essential for highlighting the basic somatosensory circuitry present in all mammals, and how this basic plan was modified to generate species specific behaviors. Our animal model, the short-tailed opossum (Monodelphis domestica), is a South American marsupial that has been proposed to have a similar ecological niche and morphology to the earliest common mammalian ancestor. In this investigation, we injected retrograde neuroanatomical tracers into the face and body representations of primary somatosensory cortex (S1), the rostral and caudal somatosensory fields (SR and SC), as well as a multimodal region (MM). Projections from different architectonically defined thalamic nuclei were then quantified. Our results provide further evidence to support the hypothesized basic mammalian plan of thalamic projections to S1, with the lateral and medial ventral posterior thalamic nuclei (VPl and VPm) projecting to S1 body and S1 face, respectively. Additional strong projections are from the medial division of posterior nucleus (Pom). SR receives projections from several midline nuclei, including the medial dorsal, ventral medial nucleus, and Pom. SC and MM show similar patterns of connectivity, with projections from the ventral anterior and ventral lateral nuclei, VPm and VPl, and the entire posterior nucleus (medial and lateral). Notably, MM is distinguished from SC by relatively dense projections from the dorsal division of the lateral geniculate nucleus and pulvinar. We discuss the finding that S1 of the short-tailed opossum has a similar pattern of projections as other marsupials and mammals, but also some distinct projections not present in other mammals. Further we provide additional support for a primitive posterior parietal cortex which receives input from multiple modalities.
Metabolic Syndrome Is Associated with Increased Breast Cancer Risk: A Systematic Review with Meta-Analysis

Background. Although individual metabolic risk factors are reported to be associated with breast cancer risk, controversy surrounds risk of breast cancer from metabolic syndrome (MS). We report the first systematic review and meta-analysis of the association between MS and breast cancer risk in all adult females. Methods. Studies were retrieved by searching four electronic reference databases [PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and ProQuest through June 30, 2012] and cross-referencing retrieved articles. Eligible for inclusion were longitudinal studies reporting associations between MS and breast cancer risk among females aged 18 years and older. Relative risks and 95% confidence intervals were calculated for each study and pooled using random-effects models. Publication bias was assessed quantitatively (Trim and Fill) and qualitatively (funnel plots). Heterogeneity was examined using Q and I 2 statistics. Results. Representing nine independent cohorts and 97,277 adult females, eight studies met the inclusion criteria. A modest, positive association was observed between MS and breast cancer risk (RR: 1.47, 95% CI, 1.15–1.87; z = 3.13; p = 0.002; Q = 26.28, p = 0.001; I 2 = 69.55%). No publication bias was observed. Conclusions. MS is associated with increased breast cancer risk in adult women.
The contributions of facial features on the smiling and angry expressions judgment and its implication for the computer recognition system

The better understanding of human face perception helps to create the more intelligent computer system to recognize the expressions in the faces. In this paper, we investigated how the expression-dependent facial features (i.e., eye area, mouth area) and expression-independent facial features contribute to smiling and angry expression judgments in the human expression system, using a high level facial adaptation paradigm. We used eye area, mouth area, combination of eye area and mouth area, and holistic face as adapting stimuli, and tested in holistic expression images. The result revealed that the eye area or the mouth area would induce approximately the same expression aftereffect when they were separately presented, suggesting that these two areas can activate the expression neural system to the similar degree. Furthermore, the combination of eye area and mouth area can not generate significantly stronger expression aftereffect than that of isolated counterparts, suggesting no accumulation effect for different expression dependent facial features. Finally, the holistic face obtains the stronger adaptation effect than that by single expression dependent facial features, indicating that the expression-independent facial features also contribute to the expression recognition. Our findings help to gain the further insight into the neural mechanism of human vision system, and has implication for computer system to simulate the human behavior of expression recognition.
De l'ingénierie des connaissances à la gestion des compétences

La gestion des competences porte sur un nombre important de connaissances de l'entreprise et de ses individus. Nous avons propose un modele des competences (CRAI), comme une base pour le developpement d'un systeme d'information pour les competences. Toutefois, les techniques classiques de l'ingenierie des systemes d'information ne sont pas suffisantes pour assurer une gestion efficace des competences : la gestion des competences comprend plusieurs processus complexes et lourds a mener. Il nous semble interessant d'investiguer les techniques d'ingenierie des connaissances. Cet article synthetise des travaux de recherche dans la litterature, portant sur les methodes d'ingenierie des connaissances appliquees a la gestion des competences, classes selon leur apport aux differents processus de gestion des competences.
A robust band compression technique for hyperspectral image classification

Dimension reduction is the key step of hyperspectral image classification. Many techniques have been developed in the past years, but our classification experiments show that some of these techniques are not robust while others suffer from the accuracy and the effectiveness for the classification of hyperspectral data. In this paper, a novel band compression algorithm is proposed based on the fusion of segmented principle component analysis (SPCA) and linear discriminant analysis (LDA) for dimension reduction. We first select the bands independently via SPCA and LDA. Theoretical analysis shows that the selected bands have little correlation, and therefore, an iterative algorithm is adopt to adaptively co-optimizing both the parameter of merging SPCA bands and LDA bands, and the classification accuracy. Our extensive experiments on two real hyperspectral datasets (AVIRIS 1992 Indian pine image and HYDICE image of Washington DC Mall), proves that the proposed technique is not only robust but offers more classification accuracy than many conventional dimension reduction techniques over several well known classifiers.
Adaptive Triangulation of Point-Based Level Sets

Point based level sets are a recently developed implicit surface representation that combines the benefits of point-set surfaces and grid-based level sets. They provide convenient topology changes and adaptivity and are thus useful for tracking the evolution of heavily deforming surfaces. However, it is often useful to extract an explicit mesh from the implicit surface, for example for rendering or post-processing. In this report we adapt an algorithm originally designed for triangulating point-set surfaces to be used with point-based level sets, describe the necessary modifications and present a successful implementation, and discuss various details not provided in the original paper.
Experiments on Surface Reconstruction for Partially Submerged Marine Structures

Over the past 10 years, significant scientific effort has been dedicated to the problem of three‐dimensional (3‐D) surface reconstruction for structural systems. However, the critical area of marine structures remains insufficiently studied. The research presented here focuses on the problem of 3‐D surface reconstruction in the marine environment. This paper summarizes our hardware, software, and experimental contributions on surface reconstruction over the past few years (2008–2011). We propose the use of off‐the‐shelf sensors and a robotic platform to scan marine structures both above and below the waterline, and we develop a method and software system that uses the Ball Pivoting Algorithm (BPA) and the Poisson reconstruction algorithm to reconstruct 3‐D surface models of marine structures from the scanned data. We have tested our hardware and software systems extensively in Singapore waters, including operating in rough waters, where water currents are around 1–2 m/s. We present results on construction of various 3‐D models of marine structures, including slowly moving structures such as floating platforms, moving boats, and stationary jetties. Furthermore, the proposed surface reconstruction algorithm makes no use of any navigation sensor such as GPS, a Doppler velocity log, or an inertial navigation system.
Generation of Multi-modal Dialogue for a Net Environment Conference Item

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Automatic Identification of Learners’ Language Background Based on Their Writing in Czech

The goal of this study is to investigate whether learners’ written data in highly inflectional Czech can suggest a consistent set of clues for automatic identification of the learners’ L1 background. For our experiments, we use texts written by learners of Czech, which have been automatically and manually annotated for errors. We define two classes of learners: speakers of Indo-European languages and speakers of non-Indo-European languages. We use an SVM classifier to perform the binary classification. We show that non-content based features perform well on highly inflectional data. In particular, features reflecting errors in orthography are the most useful, yielding about 89% precision and the same recall. A detailed discussion of the best performing features is provided.