Miracle-dz/UniFAR-FTUs huggingface dataset:
What is an information source?: information design based on information source selection behavior

This article examines information source selection behavior among maintenance technicians and how this behavior might influence the design of technical information. For this entry, "maintenance technicians" are individuals who maintain machine equipment (e.g., generators or bearings) in industrial enterprises, and this process includes the troubleshooting of problems and the repairing of machine equipment. In this entry, the authors use a review of the literature on information source selection behavior to discuss core concepts within the field of source selection behavior. Three of the main concepts examined are "information," "information source," and "source preference criteria. " These core concepts function as a frame of reference for discussing how maintenance technicians might select information sources to perform maintenance activities. The authors also use these concepts to review why certain sources are selected for use over others. The results tentatively suggest maintenance technicians prefer information sources that can be adapted to specific workplace contexts.
Assessment of nonintrusive motor efficiency estimators

Three instruments have been evaluated for their ability to estimate the load conditions and efficiency of operating motors based solely on measurements of terminal voltage and current. Laboratory tests, compared to a high-accuracy dynamometer system were used to assess the instruments' accuracy. Field tests were conducted in a paper mill to determine the ease of use and lack of intrusion. In both laboratory and field tests the instruments were applied to 50-hp, 100-hp, and 200-hp 460-V induction motors. Data of the relative accuracies of the three instruments, as functions of motor load and supply voltage, are presented together with observations of ease and lack of intrusion in use.
Firewall model for cloud computing

Cloud computing is becoming increasingly popular in the business world due to the advantages that it offers by eliminating the need to have infrastructure within business premises and dedicated staff to maintain infrastructure. Apart from the advantages the cloud offers, it can also bring in some potential security threats to the organization by not having organization specific firewalls, monitoring mechanisms and physical security. This limits the chances that companies move onto the cloud, which could have otherwise become an extremely attractive alternative for the businesses. The need is to make cloud services more reliable and trustworthy for the businesses by providing a proper security mechanism that addresses the existing drawbacks in cloud computing. The key is a firewall model that constitutes a centralized Cloud Firewall Management Server and Firewall Clients that communicate with the Cloud Firewall Management Server. This enables the organizations to maintain their own control over the firewall and firewall policies. This model does not share any information with the cloud service provider thereby providing a fully trusted solution for the businesses and additionally caters for the audit needs of the businesses by making all the information available at the central Cloud Firewall Management Server.
THE EFFECT OF VOCABULARY LEARNING STRATEGIES ON VOCABULARY MASTERY BASED ON GENDER DIFFERENCES

There are lots of studies about vocabulary learning strategies used by EFL learners. In this recent study focuses on the effect of vocabulary learning strategies (VLSs) on learners’ vocabulary mastery. Nevertheless, in this study the subject were categorized based on gender (male and female). This study aims to identify the effect of vocabulary learning strategies employed by female and male learner at LBPP LIA Solo in learning new vocabularies on their vocabulary mastery. This qualitative study was a qualitative study proposed by Pawlak (2008). The participants of this research involved 10 male learners and 10 female learners of higher intermediate level at LBPP LIA Solo. The data were collected via vocabulary learning strategy questionnaaires (VLSQs), interview and test. The data collected were analyzed qualitatively. The research finding showed that female learner tend to use more vocabulary learning strategies than male did. In addition, the the more vocabulary learning strategies applied, the better effect they got in vocabulary mastery.
Layered animation using displacement maps

This paper presents a layered animation framework which uses displacement maps for efficient representation and animation of highly detailed surfaces. The model consists of three layers: a skeleton; low-resolution control model; and a displacement map image. The novel aspects of this approach are an automatic closed-form solution for displacement map generation and animation of the layered displacement map model. This approach provides an efficient representation of complex geometry which allows realistic deformable animation with multiple levels-of-detail.
A New Hybrid Approach for Detection and Estimation in Wireless Sensor Networks

Wireless sensor network is a network that contains a set of autonomous inexpensive devices called sensors. These sensors communicate together to detect, track, and monitor physical environments. Since energy is the scarcest resource in wireless sensor networks, some necessary improvements should be made to current detection algorithms to reduce the amount of consumed energy.In this paper, two detection algorithms are studied named value fusion algorithm and decision fusion algorithm. Hybrid approach was developed as combinations between these two algorithms. In hybrid approach, event region was divided into a number of clusters. In each cluster, a cluster head is selected. Only one cluster is activated and participated in the detection process. Members of the active cluster perform the value fusion algorithm locally and the cluster head (CH) performs the decision fusion algorithm globally.To implement the hybrid approach, Hybrid Value-Decision (HVD) clustering protocol was developed as an extension to LEACH protocol.The results show that the hybrid algorithm is superior to value and decision algorithms in terms of energy consumption when more sensors are deployed in the event region (i.e. more scalable event region).
Rural Lodging Establishments as Drivers of Rural Development

Different programs designed to develop rural areas in Europe grant significant funds to support several economic activities. In particular, rural lodging establishments have been key recipients of many development investments. Therefore, identifying the determinants of business success for these establishments is important for authorities, who must allocate their funding accordingly. The establishments themselves can benefit from such knowledge as well. This article examines the influence of three general factors related to the business and the entrepreneur—product, knowledge, and promotional tools—on performance, measured as occupancy, prices, sales, and profits. A survey conducted in a rural Spanish region produces results that largely confirm the proposed hypotheses.
Improving resource utilization of enterprise-level world wide web proxy servers

The resource utilization of enterprise-level Web proxy servers is primarily dependent on network and disk I/O latencies and is highly variable due to a diurnal workload pattern with very predictable peak and off-peak periods. Often, the cost of resources depends on the purchased resource capacity instead of the actual utilization. This motivates the use of off-peak periods to perform speculative work in the hope that this work will later reduce resource utilization during peak periods. We take two approaches to improve resource utilization. In the first approach we reduce disk I/O by cache compaction during off-peak periods and by carefully designing the way a cache architecture utilizes operating system services such as the file system buffer cache and the virtual memory system. Evaluating our designs with workload generators on standard file systems we achieve disk I/O savings of over 70% compared to existing Web proxy server architectures. In the second approach we reduce peak bandwidth levels by prefetching bandwidth during off-peak periods. Our analysis reveals that 40% of the cacheable miss bandwidth is prefetchable. We found that 99% of this prefetchable bandwidth is based on objects that the Web proxy server under study has not accessed before. However, these objects originate from servers which the Web proxy server under study has accessed before. Using machine learning techniques we are able to automatically generate prefetch strategies of high accuracy and medium coverage. A test of these prefetch strategies on real workloads achieves a peak-level reduction of up to 12%.
Examining Multiple Features for Author Profiling

Authorship analysis aims at classifying texts based on the stylistic choices of their authors. The idea is to discover characteristics of the authors of the texts. This task has a growing importance in forensics, security, and marketing. In this work, we focus on discovering age and gender from blog authors. With this goal in mind, we analyzed a large number of features -- ranging from Information Retrieval to Sentiment Analysis. This paper reports on the usefulness of these features. Experiments on a corpus of over 236K blogs show that a classifier using the features explored here have outperformed the state-of-the art. More importantly, the experiments show that the Information Retrieval features proposed in our work are the most discriminative and yield the best class predictions.
Automatic Speech Recognition for Under-Resourced Languages: Application to Vietnamese Language

This paper presents our work in automatic speech recognition (ASR) in the context of under-resourced languages with application to Vietnamese. Different techniques for bootstrapping acoustic models are presented. First, we present the use of acoustic-phonetic unit distances and the potential of crosslingual acoustic modeling for under-resourced languages. Experimental results on Vietnamese showed that with only a few hours of target language speech data, crosslingual context independent modeling worked better than crosslingual context dependent modeling. However, it was outperformed by the latter one, when more speech data were available. We concluded, therefore, that in both cases, crosslingual systems are better than monolingual baseline systems. The proposal of grapheme-based acoustic modeling, which avoids building a phonetic dictionary, is also investigated in our work. Finally, since the use of sub-word units (morphemes, syllables, characters, etc.) can reduce the high out-of-vocabulary rate and improve the lack of text resources in statistical language modeling for under-resourced languages, we propose several methods to decompose, normalize and combine word and sub-word lattices generated from different ASR systems. The proposed lattice combination scheme results in a relative syllable error rate reduction of 6.6% over the sentence MAP baseline method for a Vietnamese ASR task.
Random graphs from a block class

A block class is a class of graphs such that a graph is in the class if and only if each of its blocks is. We show that, as for trees, for most random n-vertex graphs in such a class, each vertex is in at most (1+o(1))log n/ log log n blocks, and each path passes through at most 5(n log n)^{1/2} blocks. Further, these results remain true when we condition on the numbers of components and blocks, and on the list of blocks appearing; and if there are at most k blocks (where k=k(n) tends to infinity) we may replace n by k to obtain improved bounds.
The Resource-Based View: A Review and Assessment of Its Critiques

The resource-based view (RBV) of the firm has been around for over 20 years—during which time it has been both widely taken up and subjected to considerable criticism. The authors review and assess the principal critiques evident in the literature, arguing they fall into eight categories. They conclude the RBV’s core message can withstand criticism from five of these quite well provided the RBV’s variables, boundaries, and applicability are adequately specified. Three critiques that cannot be readily dismissed call for further theorizing and research. They arise from the indeterminate nature of two of the RBV’s basic concepts—resource and value—and the narrow conceptualization of a firm’s competitive advantage. As their suggestions for this work indicate, the authors feel the RBV community has clung to an inappropriately narrow neoclassical economic rationality, thereby diminishing its opportunities for progress. The authors’ suggestions may assist with developing the RBV into a more viable theory of competitive advantage, especially if it is moved into a genuinely dynamic framework.
A New Concept Relatedness Measure of Heterogeneous Ontologies in Collaborative System

With the rapid development of the Semantic Web, the ontology technology has played an increasingly important role in collaborative System. The concept relatedness measure of heterogeneous ontology can be used to support information retrieval and information sharing among different users. Traditional method to solve the question of similarity between the concepts is based on the concept distance or information content between the two concepts of a single ontology concept tree. This paper presents a hybrid method to calculate the concept relatedness of heterogeneous ontologies. It is divided into two parts: The first is a fixed weighted measure based on the concept of the tree which was combined by multiple heterogeneous ontologies in a mapping way; the other variable calculation is based on users' communications. We have applied this method in our experimental platform IPVita and been proved to be a good one.
FACEBOOK’TA AİLE İLİŞKİLERİ VE SOSYAL MEDYA ADANMIŞLIĞINA YÖNELİK BİR İÇERİK ANALİZİ - A CONTENT ANALYSIS FOR THE INVESTIGATION OF FAMILY RELATIONSHIPS AND SOCIAL MEDIA ENGAGEMENT ON FACEBOOK

Farkli sehirlerde yasayan ikinci ve ucuncu derece aile uyelerinin iletisim ihtiyaclarinin karsilanmasinda Facebook’ta olusturulmus olan aile grup sayfalari bulunmaktadir. Aile adanmislik arastirmalari temel olarak ebeveynler tarafindan baslatilan davranis ve ebeveynlerin programda ya da evdeki cocuklariyla yaptiklari gorevleri olcme uzerine odaklanmaktadir. Turk aile yapisi degisime ugramakla birlikte sosyal medya araclariyla iliskiler korunmaya calisilmistir. Bu arastirmada, Facebook kullanan aile sayfalarindaki aile ici iletisim ile sosyal medya adanmisligini temsil eden populer konular, begeni sayisi ve yorumlarin karakter benzerligi arasinda bir etkinin bulunup bulunmadiginin tespit edilmesi amaclanmaktadir. Bu calismada Facebook’taki verilerin analizinde bilgisayar destekli bir icerik analizi kullanilmistir. 2012-2016 donemlerini kapsayan toplam bes yuz (N=500) yorum 37 farkli aile sayfasindan toplanmistir. Ayrica bagimli ve bagimsiz degisken gruplar arasindaki arasinda etki duzeyinin belirlenmesi icin One Way Anova (tek yonlu varyans analizi) testi, kullanilmistir. Populer konular ile sosyal medya adanmisligi (social media engagement) arasindaki iliskiyi belirlemek icin GLM (general linear model) kullanilmistir. Sonucta, Facebook’ta yer alan aile sayfalarindaki icerikle sosyal medya adanmislik duzeyleri arasinda anlamli bir iliski bulunmustur
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This paper presents a discrete-event simulator for the General Packet Radio Service (GPRS) at IP level. The simulator focuses on the communication over the radio interface because it is one of the central aspects of GPRS. The study is mainly related to scheduling algorithms for QoS (Quality of Service) traffic. In particular we study the correlation of GSM and GPRS users with both a static and dynamic channel allocation scheme. We also takes into account users with different QoS profiles: seven scheduling algorithms (implemented in the our simulation environment) have been considered and they have been carried out with respect to average carried traffic, average time in the scheduling phase, packet loss probabilities for different channel allocation schemes and packet priorities as well as curves for average throughput per GPRS user. A detailed comparison between static and dynamic channel allocation schemes is provided. The simulated traffic is related to an ATIS (Advanced Travelers Information System) system but the study can be extended to others scenario.
Research on the Shift of Default Risk in Supply Chain Based on the Credit Default Swap

Taking the retailerpsilas default in supply chain for example, in this paper, using the theory of credit default swap, the writer intends to make a research on the shift of default risk in supply chain. On the condition of insured interest rate and recovery rate, a supposition is made that the default rate of supply chain depends on the doubly stochastic Poisson default process, and then a model of credit default swap is established, and a simple pricing model of standard credit default swap and long-term credit default swap are discussed.
Tumour response evaluation with fluorodeoxyglucose positron emission tomography: research technique or clinical tool?

Abstract The evaluation of treatment response is an established role for imaging in oncologic research and clinical practice. In early phase trials, imaging response criteria are used to determine the presence and magnitude of the drug effect on tumour to aid decisions concerning progress to late phase trials, and to inform dose selection and scheduling. In late phase trials and clinical practice, the imaging response is used as a surrogate for clinical outcome. Due to the limitations of current anatomic response criteria, there is growing interest in the use of [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) to assess treatment response. The technique is beginning to be adopted within mainstream approaches for evaluation of response in solid tumours and lymphoma. Difficulties with standardisation across PET centres and tumour types combined with uncertainty concerning the timing of assessment relative to treatment, have limited the use of quantitative measurements of FDG uptake to research applications. However, with a growing body of evidence that qualitative criteria such as the development of new PET lesions or complete metabolic response following treatment can provide surrogates marker for clinical outcome, [18F]FDG-PET is becoming established as a clinical technique for assessing tumour response, especially for FDG-avid lymphoma subtypes. Multimodality imaging using perfusion computed tomography/PET is an exciting novel technique with the potential to define treatment response in a new way.
An experimental comparison of classification techniques for imbalanced credit scoring data sets using SAS ® Enterprise

In this paper, we set out to compare several techniques that can be used in the analysis of imbalanced credit scoring data sets. In a credit scoring context, imbalanced data sets frequently occur as the number of defaulting loans in a portfolio is usually much lower than the number of observations that do not default. As well as using traditional classification techniques such as logistic regression, neural networks and decision trees, this paper will also explore the suitability of gradient boosting and memory based reasoning (k-NN) in SAS® Enterprise MinerTM for loan default prediction. Five real-world credit scoring data sets are used to build classifiers and test their performance. In our experiments, we progressively increase class imbalance in each of these data sets by randomly under-sampling the minority class of defaulters, so as to identify to what extent the predictive power of the respective techniques is adversely affected. The performance criterion chosen to measure this effect is the area under the receiver operating characteristic curve (AUC); Friedman's statistic and Nemenyi post-hoc tests are used to test for significance of AUC differences between techniques. The results from this empirical study indicate that the Gradient Boosting performs very well in a credit scoring context and are able to cope comparatively well with pronounced class imbalances in these data sets. We also found that, when faced with a large class imbalance, the decision tree algorithm, quadratic discriminant analysis and k-nearest neighbours perform significantly worse than the best performing classifiers.
Gauge symmetry and supersymmetry of multiple M2-branes

In previous work we proposed a field theory model for multiple M2-branes based on an algebra with a totally antisymmetric triple product. In this paper we gauge a symmetry that arises from the algebra's triple product. We then construct a supersymmetric theory with no free parameters that is consistent with all the continuous symmetries expected of a multiple M2-brane theory: 16 supersymmetries, conformal invariance, and an SO(8) R-symmetry that acts on the eight transverse scalars. The gauge field is not dynamical. The result is a new type of maximally supersymmetric gauge theory in three dimensions.
Acceptability of a guided self-help Internet intervention for family caregivers: mastery over dementia

ABSTRACT Background: The number of people with dementia is increasing rapidly. Providing care to a relative or friend with dementia may lead to serious mental health problems. Internet interventions may offer opportunities to improve the availability and accessibility of (cost)effective interventions to reduce family caregivers’ psychological distress. This study describes the acceptability of a guided self-help Internet intervention “mastery over dementia” (MoD), aimed at reducing caregivers’ psychological distress, in terms of reach, adherence and user evaluation. Methods: The sample for this study is the experimental group that participated in the (cost)effectiveness trial of MoD (N = 149). Data on characteristics of family caregivers and people with dementia, completion and user evaluation were used and analyzed with descriptive statistics, χ2and T-tests. Results: MoD reaches a wide variety of caregivers, also those aged 75+, having a relative with a recent diagnosis of dementia or living in a care home. However, the percentage of caregivers who did not complete all eight lessons was rather high (55.7%). Among the completers (N = 66; 44.3%) were significantly more spouses, caregivers living in the same household, older caregivers, and those caring for somebody with another formal diagnosis than Alzheimer's disease. Caregivers’ evaluation showed that females rated higher on the comprehensibility of the lessons and feedback and spent less time on the lessons. Conclusion: The guided self-help Internet intervention MoD is acceptable for a broad range of family caregivers of people with dementia. The next step is to substantiate its (cost)effectiveness.