Miracle-dz/UniFAR-FTUs huggingface dataset:
Number : WUCSE-2005-20 2005-05-09 Manifold Clustering

Manifold learning has become a vital tool in data driven methods for interpretation of video, motion capture, and handwritten character data when they lie on a low dimensional, non-linear manifold. This work extends manifold learning to classify and parameterize unlabeled data which lie on multiple, intersecting manifolds. This approach significantly increases the domain to which manifold learning methods can be applied, allowing parameterization of example manifolds such as figure eights and intersecting paths which are quite common in natural data sets. This approach introduces several technical contributions which may be of broader interest, including node-weighted multidimensional scaling and a fast algorithm for weighted lowrank approximation for rank-one weight matrices. We show examples for intersecting manifolds of mixed topology and dimension and demonstrations on human motion capture data.
use of a right internal thoracic artery increase deep ound infection and risk after previous use of a left nternal thoracic artery ?

ethods: Reoperations (n 2875; 2381 men) in patients with previous left internal horacic artery bypass were performed between January 1990 and January 2003; 939 (67%) had no repeat internal thoracic artery grafting, 923 (32%) received an dditional right internal thoracic artery graft, and 13 (0.5%) had bilateral internal horacic artery grafting with reuse of the left internal thoracic artery. Of the patients, 52 (12%) were insulin-treated and 590 (21%) non–insulin-treated diabetics. Mulivariable logistic regression analysis was used to identify preoperative variables ssociated with right versus non–right internal thoracic artery use in diabetics and ondiabetics and to formulate propensity models. Propensity scores were used for atching and adjusted multivariable analyses of deep wound infection and hospital ortality.
itting outbreak models to data from many small orovirus outbreaks

Infectious disease often occurs in small, independent outbreaks in populations with varying characteristics. Each outbreak by itself may provide too little information for accurate estimation of epidemic model parameters. Here we show that using standard stochastic epidemic models for each outbreak and allowing parameters to vary between outbreaks according to a linear predictor leads to a generalized linear model that accurately estimates parameters from many small and diverse outbreaks. By estimating initial growth rates in addition to transmission rates, we are able to characterize variation in numbers of initially susceptible individuals or contact patterns between outbreaks. With simulation, we find that
An evaluation component for categorization systems

Automatic categorization is a way to combat the information overflow many companies face every day. For such an automatic categorization to be useful, the categorization model must correctly represent the intended ‘meaning’ of the categories. An important factor is the categorization model used which is created in a training step based on representative sets of training documents for each category. The quality of the categorization model critically depends on the quality of the ‘training base’, which is the set of categories that make up the taxonomy together with the sets of training documents associated with each categories of the taxonomy. While a number of categorization systems are commercially available, assessing the categorization quality is a costly and labor-intensive task when performed manually on the basis of separate validation data. In this article, we describe an evaluation component that automatically evaluates the quality of a training base independent from the categorization system used. Furthermore, we show how this component can be used to propose changes to the training base that can help to reduce the number of problematic areas thereby improving the quality of the categorization system. We illustrate our approach using a sample taxonomy with 10 categories and approx. 400 training documents.
Progress on research and development of Paederia scandens as a natural medicine

Paederia scandens (Lour.) (P. scandens) has been used in folk medicines as an important crude drug. It has mainly been used for treatment of toothaches, chest pain, piles, hemorrhoids, and emesis. It has also been used as a diuretic. Research has shown that P. scandens delivers anti-nociceptive, anti-inflammatory, and antitumor activity. Phytochemical screening has revealed the presence of iridoid glucosides, volatile oils, flavonoids, glucosides, and other metabolites. This review provides a comprehensive report on traditional medicinal uses, chemical constituents, and pharmacological profiles of P. scandens as a natural medicine.
Destination Branding and Its Influence on Tourist's Satisfaction and Loyalty

Brand is known as a valuable asset as it enables to differentiate from competitors offerings as well as to generate positive perceptions in the consumers' mind. In the tourism sector, as part of winning competition, it is suggested that destination should also be branded. Destination brand is believed to enable a location to attract investment, business, and tourist which is then improving the local economy. The objective of this study is to empirically examine the structural model to understand the relationship between destination branding and behaviours in the tourism sector. Destination branding is built based on three elements namely destination image, perceived quality, and destination awareness while tourist loyalty is represented by tourist satisfaction and loyalty. By applying purposive sampling, 150 valid questionnaires were analysed using Partial Least Squares. Results indicate that there were positive influences between perceived quality and brand awareness to satisfaction whereas brand image had no significant influence on satisfaction. Further, satisfaction significantly influenced loyalty.
HOW HANDHELD DEVICES TRANSFORM, AUGMENT AND REINFORCE UNIVERSITY STUDENT’S STUDY HABITS: EMERGING THEMES FROM A THREE-YEAR STUDY

Ownership and use of handheld devices for university study and revision is transforming learning habits and posing new learning design and pedagogic challenges to educators. How is seamless learning affecting study habits, what is the impact of simultaneous multiple-device use, and can existing learning platforms cope with new demands? Whilst surveys in the UK, US and other countries have helped monitor trends, there remains a paucity of comparably sized analysis of qualitative data. Such insight is essential to help interrogate and explain observed trends and to probe the new ‘opportunity time’ that mobile learning creates. This paper will present the results from a thematic analysis of open-comment survey data collected from UK distance learners. This work was conducted as part of the long-running E-Pedagogies Project which began in 2012. The dataset includes undergraduate learners from all subject disciplines and used an emergent coding scheme that was framed by key issues identified in a literature review, an analysis of initial learner interviews, and previous statistical analysis of the survey by the authors. The paper focuses on three learner groups identified in the statistical analysis: those using devices for a wide range of study purposes, those using devices for a limited number of purposes, and those deciding not to use devices for study. The paper will present findings that unpack differences as to how, why and where handheld devices are used, highlight examples of innovative, necessary or unusual study practice reported by learners, and summarise what changes learners want to see.
RP-HPLC method for determination of norethindrone in dissolution media and application to study release from a controlled release nanoparticulate liquid medicated formulation

Several methods are available for the determination of norethindrone. These methods are either complicated or need validation. The objective of this work was to develop and validate a simple reversed phase-high performance liquid chromatographic method for the determination of norethindrone in dissolution media. A Thermo Scientific C18 column (250 mm × 4.6 mm ID, 5 μm pore size) was used. A mobile phase consisting of deionized water: acetonitrile (50:50, v/v) and 5 ml/l acetic acid was used. The flow rate was 1.3 ml/minute and the wavelength of the detection was 245 nm. Validation of linearity, accuracy and precision, limit of detection, limit of quantification, specificity, and stability (degradation) was carried out according to the International Conference on Harmonization guidelines. The developed and validated method was used to study norethindrone release from a nanoparticulate liquid medicated formulation (LMF). The results indicated that the method was simple, accurate and precise, and met the acceptance criteria. The drug exhibited higher stability in basic media when compared to acidic media. Drug release from a LMF (nanoemulsion) followed zero order kinetics. In conclusion, a simple method was developed, validated, and used successfully in evaluating in vitro drug release from a sustained release/controlled release nanoparticulate LMF.
Nonlinear Finite Element Analysis of Non-Seismically Detailed Interior Reinforced concrete Beam-Column Connection under Reversed Cyclic Load

This paper presents a nonlinear finite element analysis of non-seismically detailed reinforced concrete (RC) beam-column connections under reversed cyclic load. The test of half-scale nonductile reinforced concrete beam-column joints was conducted. The tested specimens represented those of the actual mid-rise reinforced concrete frame buildings designed according to the non-seismic provisions of the American Concrete building code (ACI). The test results show that the specimens representing small and medium column tributary area failed in brittle joint shear while the specimen representing large column tributary area failed by ductile flexure though no ductile reinforcement details were provided. The nonlinear finite element analysis was applied to simulate the behavior of the specimens. The finite element analysis employed the smeared crack approach for modeling beam, column and joint, and employed the discrete crack approach for modeling the interface between beam and joint face. The nonlinear constitutive models of reinforced concrete elements consisted of coupled tension-compression model to model normal force orthogonal and paralleled to the crack and shear transfer model to capture the shear sliding mechanism. The finite element model (FEM) shows good comparison with test results in terms of load-displacement relations, hysteretic loops, cracking process and the failure mode of the tested specimens. The finite element analysis clarified that the joint shear failure was caused by the collapse of principal diagonal concrete strut.
Metal-Decorated Silicene for Hydrogen Storage

Environmental and energy security concerns makes renewable energy research imperative. A key issue that needs to be addressed before the implementation of a renewable energy system is the issue of energy storage, in which materials-based hydrogen storage is considered as an option. In this paper, the metal-decorated silicene was studied for hydrogen storage applications. These were performed using the Vienna Ab Initio Simulation Package (VASP), a plane wavebased code. The potential was described using the projector-augmented wave (PAW) method. The exchange-correlation energy was approximated using Generalized Gradient Approximation (GGA) functional in the Perdew, Burke, and Ernzerhof (PBE) form. The k points were gamma-centered and automatically generated using the Monkhorst-Pack scheme. The energy cutoff, number of k points, vacuum spacing, silicene lattice constant, and silicene buckling height were determined using various convergence tests. The transition metals Co, Ni, Pd, and Pt were used for the metal decoration. Relaxation calculations were done to determine the most stable adsorption site for the metal adatoms. Results show the hollow site to be the most stable among the four adsorption sites (bridge, hollow, top, and valley). Static calculations with Pd and Pt decoration also confirmed this.
Relationships between Middle School Students’ Smartphone dependency and Aggression: Mediating and Moderating Effects of Ego-Resilience, Parenting Behavior and Peer Attachment

This study was conducted to examine the moderating and mediating effect of ego - resilience, parenting attitude, and peer attachment in the relation between smartphone dependency and aggression. Participants were 1,863 youths using a smartphone among the first middle school students responded in the 7th Korean Children and Youth Panel Survey (KCYPS) conducted by the National Youth Policy Institute in Korea. The data were analyzed by descriptive statistics, a correlation, and a hierarchical regression analysis. First, ego-resilience showed a partial mediating effect on the relationship between smartphone dependency, aggression and significant moderating effects were revealed. Second, parenting behavior showed a partial mediating effect on the relationship between smartphone dependency and aggression, with no moderating effects seen. Third, peer attachment had a partial mediating effect on the relationship between smartphone dependency and aggression, with no moderating effects seen. The research suggested the mental health and growth of students could be improved by applying various nursing and health care programs to improve ego-resilience, parenting behavior and peer attachment as they grow into adulthood.
PEMANFAATAN SPARQL INFERENCING NOTATION (SPIN)DALAM PROTOTIPE PENCARIAN SEMANTIKPADA DATA RESTORAN

Today, more and more information circulating on the internet that cause more difficulty in finding users desired information because many search engine have not used in understanding the concept of semantic search phrase. Application developed in this research is prototype of semantic search on restaurant data using SPARQL Inferencing Notation (SPIN). Search sentence must follow a rule that must be preceded by direction word (tampil, cari, sebut) and followed by a synonym of class which want to find (restoran, makanan menu, minuman, kategori, lokasi). Every search phrase which entered by user will be translated with tokenization process, stemming, stopword removal (filtering process) and followed by the representation of search sentence using keywords in support ontology (words.owl) thus formed run SPARQL to query data located on restaurant.owl ontology. The test result of this research show that the search application which built have an ability to handle wide variety of pattern of question and got the ratio of recall and precision 1:1, thus meaning that this application has a high effectiveness in search result.
1 THE ROLE OF HEALTHY URBAN PERFORMANCE ON WALKABILITY : BROADENING THE THEORY OF PLANNED BEHAVIOUR

This study aims to broaden Theory of Planned Behaviour (TPB) by inclusion of healthy urban performance attributes of the residential neighbourhoods as an additional predictor for walking behaviour. First, the study reviews the literature on TPB and walkability in residential environments, then construct a TPB model based on walkability to set the hypotheses. The study will explore the correlations through a survey of residents in Ankara, Turkey (n= 220). To analyse the data, first confirmatory factor analysis and later, structural equation modelling will be used. The findings of the study highlights two aspects of planning for a walkable neighbourhood: (i) a walkability model based on the three constructs of TPB should not neglect the measured and experienced urban performance; (ii) utilizing pedestrian environment for walking as fully as possible requires a collaborative and experiential approach and a multi-parameter decision-making process, which are all closely related with observations of walking behaviours both in the present day and future.
Would you fight ? An inquiry among high-risk youth in Eastern Congo

Why would an individual choose to take up arms and fight? Several decades of research on armed conflict have yielded relatively few quantitative analyses on the individual propensity to participate in collective violence. This paper studies the intention to fight among a high-risk population of miners in Eastern Congo. The majority of our respondents have been exposed to armed conflict in the past and some have participated in activities of armed groups. We inquire about their intention to fight at a time when their main income source is under threat because of the arrival of a large-scale mining company. We identify how their responses vary with four motivations that have been highlighted in the theoretical literature: grievances, material incentives, social incentives and previous exposure to conflict. The results suggest that all four motivations play a significant role. * IOB – Institute of Development Policy and Management (University of Antwerp), LICOS – Centre for Institutions and Economic Performance (University of Leuven). e-mail: nik.stoop@kuleuven.be † IOB – Institute of Development Policy and Management (University of Antwerp), LICOS – Centre for Institutions and Economic Performance (University of Leuven). e-mail: marijke.verpoorten@uantwerp.be
Entropy based method for keypoint selection

In order to improve the performance of affine invariant detectors, approaches that combine different keypoint extraction methods can be found in literature. However, such a combining has two major drawbacks: a high computational cost in matching similar objects, and a large number of false positives because only a relatively small subset of those keypoints is really discriminative. In this paper we propose a method to overcome these limitations: First we combine different keypoint extractors in order to obtain a large set of possible interest points for a given object. Then, a two step filtering approach is applied: First, a reduction using a spatial criterion to reject points that are close in a specified neighborhood, and second, filtering based on the information entropy in order to select only a small subset of keypoints that offer the highest information content. A qualitative analysis of this method is presented.
From the SelectedWorks of Ananth N Iyer September , 2004 Robust speaker verification with principal pitch components

We are presenting a new method that improves the accuracy of text dependent speaker identification systems. The new method exploits a set of novel speech features that is derived from a principal component analysis (PC) of voiced speech segments. The new PC features are only weakly correlated with the corresponding cepstral features. A distance measure that combines both, cepstral and PC pitch features provides a discriminative power that cannot be achieved with cepstral features alone. It is well known that the discriminative power of cepstral features declines if the dimensionality of the feature space is increased beyond its optimal value. By augmenting the feature space of a cepstral baseline system with PC pitch features we are able to reduce the equal error probability of incorrect customer rejection versus incorrect impostor acceptance by 12.5% beyond the discriminative limit of the cepstral analysis.
THE DISTRIBUTION OF TP 53 GENE POLYMORPHISMS IN CHRONIC LYMPHOCYTIC LEUKEMIA PATIENTS , SUFFERERS OF CHORNOBYL NUCLEAR POWER PLANT ACCIDENT

Previous analyses in a cohort of Chornobyl cleanup workers revealed significantly increased radiation-related risk for all leukemia types, including chronic lymphocytic leukemia (CLL). Numerous investigations emphasized the significance of genetic susceptibility to the radiation carcinogenesis. The aim of the work was to study the distribution of TP53 single nucleotide polymorphisms (SNPs) in CLL patients exposed to ionizing radiation (IR) due to Chornobyl nuclear power plant accident and estimate their impact on disease development. Materials and Methods: The TP53 exonic and intronic SNPs were analyzed in 236 CLL patients by polymerase chain reaction and direct sequencing. The main group included 106 IR exposed CLL patients and the control group was composed of 130 IR non-exposed CLL patients. Results: Nineteen TP53 SNPs were found in the observed CLL cohort. No significant differences were found between the main and the control groups, but increased frequencies of T/T rs12947788 + G/G rs12951053 homozygotes and rs146340390 C/T variants were found among IR-exposed CLL patients compared with healthy Europeans (data from the 1000 Genomes Project). Rare nucleotide substitution rs146340390 (c.665C>T) was found only in the main group. These features were primarily typical for the most affected group of IR-exposed patients, namely, cleanup workers engaged in emergency works in the 2nd quarter of 1986. Conclusion: These preliminary findings don’t contradict the assumption on possible influence of IR on CLL development via the p53-dependent pathway. This article is a part of a Special Issue entitled “The Chornobyl Nuclear Accident: Thirty Years After”.
Special Section on Recent Advances in Machine Learning for Spoken Language Processing Investigation of DNN-Based Audio-Visual Speech Recognition

Audio-Visual Speech Recognition (AVSR) is one of techniques to enhance robustness of speech recognizer in noisy or real environments. On the other hand, Deep Neural Networks (DNNs) have recently attracted a lot of attentions of researchers in the speech recognition field, because we can drastically improve recognition performance by using DNNs. There are two ways to employ DNN techniques for speech recognition: a hybrid approach and a tandem approach; in the hybrid approach an emission probability on each Hidden Markov Model (HMM) state is computed using a DNN, while in the tandem approach a DNN is composed into a feature extraction scheme. In this paper, we investigate and compare several DNN-based AVSR methods to mainly clarify how we should incorporate audio and visual modalities using DNNs. We carried out recognition experiments using a corpus CENSREC-1-AV, and we discuss the results to find out the best DNN-based AVSR modeling. Then it turns out that a tandembased method using audio Deep Bottle-Neck Features (DBNFs) and visual ones with multi-stream HMMs is the most suitable, followed by a hybrid approach and another tandem scheme using audio-visual DBNFs. key words: audio-visual speech recognition, deep neural network, Deep Bottleneck Feature, multi-stream HMM
A Query based Approach to Reduce the Web Crawler Traffic using HTTP Get Request and Dynamic Web Page

The functions of Web crawler download information from web for search engine. Web pages changed without any notice. Web crawler has to revisit web site to download updated and new web pages. It is estimated 40% of current web traffic is generated by web crawler. This paper proposes query based approach to inform updates on web site to web crawler using Dynamic web page and HTTP GET Request. Dynamic web page generates HTML based response having list of updates on web site after crawler last visit. Web crawler only visits updated web pages instead of visiting full web sites for updates. Proposed scheme is tested & results show that it is very promising.