Miracle-dz/UniFAR-FTUs huggingface dataset:
TelematicsTelematics Transport System Transport System

At the planning and construction of new infrastructures, the information about migration potential of animals in a target area is needed. This information will be used to design of migration corridors for wild animals. To determine the migration potential of animals based on distributed video camera system, new methods for object recognition and classification are developed. In general, an object recognition system consists of three steps, namely, the image feature extraction from the training database, training the classifier and evaluation of query image of object/animal. In this paper, an extraction of local key point by SIFT or SURF descriptors, bags of key points method in combination with SVM classifier and two hybrid key points detection methods are proposed in detail.
Solution of Eigenvalue Integral Equation with Exponentially Oscillating Covariance Function

SUMMARY Karhunen-Loeve(KL)transformisoptimalformanysignaldetection,communicationandﬁlteringapplications. AnexplicitsolutionoftheKLintegralequationforapracticalcasewhenthecovariancefunctionofastationaryprocessisex-ponentiallyoscillatingisproposed. key words: Karhunen-Loeve transform, eigenvalue integralequation 1. IntroductionIntheoriesofsignaldetectionandﬁltering[1]–[3],therefrequentlyoccurtheKLeigenvalueintegralequationortheFredholmequationoftheﬁrsttypewhosekernelisthecovariancefunctionofthestationaryprocess, λϕ ( t )= T−T K ( |t−s| ) ϕ ( s ) ds, (1)where K ( x )representsthecovariancefunctionofacon-tinuousstationarysecondorderprocesspossessingacontinuousspectraldensity S ( w ), −T ≤ t≤ T . Denoteensembleaverageby E [. ]andlet m ( t )= E [ n ( t,v )]and K ( t,s )= E [( n ( t,v ) −m ( t ))( n ( s,v ) −m ( s ))]. Here K ( t , s )isthecovariancefunctionoftheprocess n ( t,v ). Ifthecovariancefunctioniscontinuousinsquare −T ≤t , s ≤ T , theprocessissecond-ordercontinuousin −T ≤ t ≤ T ,andifinaddition
On times and arguments

Abstract Verbs are traditionally assumed to have an “argument structure”, which imposes various constraints on form and meaning of the noun phrases that go with the verb, and an “event structure”, which defines certain temporal characteristics of the “event” to which the verb relates. In this paper, I argue that these two structures should be brought together. The verb assigns descriptive properties to one or more arguments at one or more temporal intervals, hence verbs have an “argument-time structure”. This argument-time structure as well as the descriptive properties connected to it can be modified by various morphological and syntactic operations. This approach allows a relatively simple analysis of familiar but not well-defined temporal notions such as tense, aspect and Aktionsart. This will be illustrated for English. It will be shown that a few simple morphosyntactic operations on the argument-time structure might account for form and meaning of the perfect, the progressive, the passive and related constructions.
Evolution Mining: A Novel Accelerated Framework for Large Data processing in the big Data Paradigm

: The big data focus on the mining of the large volume, complex and exploiting datain the large scale application and Social network communities. The map reduce paradigm is been used to handle large scale data in the big data paradigm through classification and clustering algorithm as it is treated as computational intensive task. The Data Classification and Clustering algorithm using supervised and unsupervised learning models failed in processing dynamic updates as concept and feature evolution to map reduce paradigm in the large streaming application. Therefore it becomes mandatory to build a new accelerated framework which is capable of handling of the data evolution in the large data. In this Paper, we propose a novel technique named as “EvolutionMining” which develop a deep learning model in the map reduce paradigm using key value pair processing &Semantic Mining techniques. Sophisticated iterative models for feature extraction, classification and feature or concept evolution determination been devised. The proposed Technique is capable of handling the diverse data by producing the increased value to the computation characteristics such as accuracy and complexity. The Experimental results prove that proposed System outperforms other state of approaches using evaluation metrics such Runtime &Mean Error and reduces I/O overhead to much extent. Experimental results prove that proposed process significantly reduces the run time and mean error for clustering the data with feature evolution and concept evolutions against re-computation based processes.
Studying the effect of customer relationship management on the quality of relationship, from the perspective of the Iran Insurance Industry customers

Organizations have to focus on beneficial and key customers in order to maintain in competitive field. One of the techniques that can help organization in this regard is customer relationship management which strengthens the relationship with customers. This study aims to evaluate the effects of customer relationship management on the relationship quality (satisfaction, trust, commitment). This study, is practical from the purpose prospective, and is descriptive from method of data collection prospective and is a correlation study. Population of study contains third-party insured of the Iran insurance company in Mashhad. In this study, simple random sampling is used and questionnaire designed by researcher was used to collect data. Reliability and validity of the data collection tool was approved in pre-test section. Lastly the data from 385 questionnaires from statistical population were collected and analyzed. Also in order to analyze the data, structural equation modeling and Amos software were used. Results demonstrate that the customer relationship management has a positive and significant effect on quality dimension of relationship. This means that when customers have a better understanding of the company's customer relationship management then they will have a more positive view of the quality of the relation with company. Therefore, their satisfaction, trust and commitment will increase.
Automated numerical estimation of meander length and amplitude

This paper details a novel numerical method for automatic estimation of stream meander length. It is based upon Langbein et al. (1966) and produces a single meander length and meander amplitude over a given reach that minimises the least-squares error. This algorithm has been applied to 1,456 reach segments, each approximately of 1 km flow path, throughout the Murray-Darling Basin. These estimates were used in the Physical Form theme of the Murray-Darling Basin Sustainable Rivers Audit (SRA). This paper details the method and presents results from one reach and then a summary from all 1,546 study reaches. The algorithm for estimation of meander length is based upon the theory of Langbein et al. (1966) and further applied and assessed by Williams (1986). The theory proposes that the angle between the flow direction at a given point and the regional stream flow path changes, with reach distance, to produce a sinusoidal relationship. By numerically fitting a sine function to this relationship, a wave length and thus the meander length can be estimated. However, a challenge in applying this method is in defining the regional stream flow path to which the observed angle is calculated. If it was to be applied to only a single reach, the regional flow path could simply be qualitatively estimated by the practitioner. However, implementation to the 1,456 reaches investigated herein required an automatic method for estimation of this regional flow path and estimation of the meander length. To achieve this, and after trialling a considerable number of alternatives, an algorithm was developed to rotate the reach, fit a k order polynomial to estimate the regional flow path, calculate the residuals to this path and then numerically fit the Langbein et al. (1966) sinusoidal model to the residuals. The fitting and rotation was undertaken by multi-start Trust-Region non-linear leastsquares regression. Overall, the algorithm developed provided a robust, objective and reproducible means for estimating meander length. Furthermore, those reaches for which the algorithm does not perform satisfactorily can easily be identified by the low coefficient of efficiency. The algorithm does, however, have some weakness. Most notably, the modelled meander length is a single best estimate, in a least-squares sense, to the entire one kilometre reach. If smaller or longer reach chainage were investigated it is likely that the estimate would differ. Therefore, the estimated meander length herein is very likely to be a function of the scale of the application.
Cost-efficacy analysis of biological treatments in psoriasis: an 18-month assessment

Summary This study compared the cost-efficacy of the following approved biological treatment strategies for plaque psoriasis over 18 months: (1) alefacept 15 mg intramuscularly weekly for two 12-week courses; (2) efalizumab 1 mg/kg subcutaneously (SC) weekly; and (3) etanercept 50 mg SC twice weekly for 12 weeks followed by a maintenance dose of 50 mg weekly. Direct utilisation-related costs included drug costs, office fees, injection fees and costs incurred due to adverse events and laboratory monitoring. Efficacy was based on response rates from large-scale clinical trials. At 18 months, total utilisation-related costs for alefacept, efalizumab and etanercept were $26,667, $33,365 and $32,962, respectively. Cost-efficacy, calculated using the corresponding response rates for the three therapies, was comparable ($66,669, $75,828 and $61,041, respectively). Thus, for patients with moderate to severe psoriasis who have responded to therapy, two 12-week courses of alefacept 7 months apart, or weekly maintenance treatment with efalizumab or etanercept, resulted in comparable total cost-efficacy.
Molecular genetics of cork formation

La peridermis es una estructura complexa que protegeix els organs vegetals madurs (secundaris) i les zones que han sofert ferides de la perdua d'aigua i dels patogens. Aquesta funcio barrera es deguda al fel·lema o suber, un teixit format per cel·lules suberificades. Tant el fel·lema com la suberina son crucials per la vida de les plantes terrestres, pero practicament no es coneix res dels processos moleculars que regulen la seva formacio, probablement degut a la manca de models adequats. En aquesta tesi s'han identificat i caracteritzat gens induits al fel·lema mitjancant la combinacio de dues plantes models. L'escorca d'alzina surera (Quercus suber) s'ha utilitzat per aillar gens candidats de la formacio del fel·lema i per investigar el comportament d'alguns d'aquests gens durant l'estacio de creixement, mentre que la pela de la patata (Solanum tuberosum) s'ha utilitzat en estudis de genetica reversa per demostrar la funcio d'alguns gens reguladors al fel·lema.
Exploring uninvolved community members' perceptions of HIV/AIDS care and support in Kwangcolosi, KwaZulu-Natal, South Africa.

This study explores the perceptions of care and support for those with HIV/AIDS by community members within the KwaNgcolosi community who are currently not involved in such care and support, and have no current perceived obligation to do so. The Social Capital framework was used to understand the current community perceptions and dynamics related to current care and support for those who are ill with HIV/AIDS. This was followed with suggestions for how this could be improved, current obstacles to this, and possible personal contributions towards improving the current situation. Data was collected by means of six semi-structured, in-depth focus groups, which were conducted in IsiZulu with the assistance of a translator. These were then transcribed and thematically analysed. Overlapping quantitative data specifically for the themes of social cohesion and trust exists in the form of two social assessment surveys, and so frequency counts were done with applicable survey questions, and compared with data collected from focus group interviews. Focus group discussions revealed a marked difference between perceived ideals of how care and support should be, and what is currently happening within the community. Mistrust and stigma surrounding HIV/AIDS appear to still be prevalent within the community, which hampers community social networks and involvement, and acts as a barrier for those who wish to provide care and support for those who are ill. Triangulation with Social Assessment surveys, revealed a discrepancy between social cohesion as related to HIV/AIDS, and general social cohesion within the KwaNgcolosi community. This social cohesion is not currently leading to collective action, which points to a deficit both in information sharing regarding how to do so, as well as a deficit in Social Bridging.
PREDICTING SENTIMENT-MENTION ASSOCIATIONS IN PRODUCT REVIEWS by VISHWAS VASWANI

With the rising trend in social networking, more people express their opinions on the web. As a consequence, there has been an increase in the number of blogs where people write reviews about the products they buy or services they experience. These reviews can be very helpful to other potential customers who want to know the pros and cons of a product, and also to manufacturers who want to get feedback from customers about their products. Sentiment analysis of online data (such as review blogs) is a rapidly growing field of research in Machine Learning, which can leverage online reviews and quickly extract the sentiment of a whole blog. The accuracy of a sentiment analyzer relies heavily on correctly identifying associations between a sentiment (opinion) word and the targeted mention (token or object) in blog sentences. In this work, we focus on the task of automatically identifying sentiment-mention associations, in other words, we identify the target mention that is associated with a sentiment word in a sentence. Support Vector Machines (SVM), a supervised machine learning algorithm, was used to learn classifiers for this task. Syntactic and semantic features extracted from sentences were used as input to the SVM algorithm. The dataset used in the work has reviews from car and camera domain. The work is divided into two phases. In the first phase, we learned domain specific classifiers for the car and camera domains, respectively. To further improve the predictions of the domain specific classifiers we investigated the use of transfer learning techniques in the second phase. More precisely, the goal was to use knowledge from a source domain to improve predictions for a target domain. We considered two transfer learning approaches: a feature level fusion approach and a classifier level fusion approach. Experimental results show that transfer learning can help to improve the predictions made using the domain specific classifier approach. While both the feature level and classifier level fusion approaches were shown to improve the prediction accuracy, the classifier level fusion approach gave better results.
Zebra-User's Guide and Reference

Zebra is a free, fast, friendly information management system. It can index records in XML/SGML, MARC, e-mail archives and many other formats, and quickly find them using a combination of boolean searching and relevance ranking. Search-and-retrieve applications can be written using APIs in a wide variety of languages, communicating with the Zebra server using industry-standard information-retrieval protocols. This manual explains how to build and install Zebra, configure it appropriately for your application, add data and set up a running information service. It describes version 1.3. 28 of Zebra.
Application of JC1 for non-toxic isolation of cells with MDR transporter activity by flow cytometry

The DNA intercalating dye Hoechst 33342 or its close analog DCV are actively removed from cells by the multidrug resistance transporter ABCG2, a protein overexpressed in metastatic cells and somatic stem cells. In bivariate blue-red flow cytometry fluorescent plots active Hoechst or DCV efflux combined with a concentration dependent bathochromic shifts of these nuclear dyes leads to the segregation of the transporter-rich cells into a distinct cell cohort tilted towards the shorter wavelength axis of the plot, the cohort is generically known as the side population (SP). This feature has facilitated the surface marker-independent isolation of live stem cells. A drawback, though, is the known toxicity of Hoechst dyes. In this study we show that JC1, a bathochromic mitochondrial membrane potential-sensitive dye applied at proper concentration, can yield flow cytometry fluorescent emission bivariate plots containing a low JC1 accumulation (JC1low) cohort. Using a combination of multiple cell lines, ABC-transporter inhibitors and viral vector-driven insertion of the ABCG2 gene or ABCG2 and ABCB1 shRNAs we demonstrate that JC1low can be generated by either of the two aforementioned multidrug resistance transporters. Complete wash out of mitochondrial bound JC1 required more than 24 h. In spite of this tight binding, the dye did not affect either the mitochondrial membrane potentials or the proliferation rate. In contrast, contemporaneous with its nuclear accumulation, Hoechst 33342 or DVC, caused changes in the fluorescent emission of mitochondrial membrane potential sensitive dyes resembling the effects caused by the mitochondrial uncoupler FCCP. In a number of cell lines exposure to Hoechst resulted in marked slow-down of proliferation and abolition of ABCG2 transport activity during the subsequent 2 days but in K562 cells the exposure induced cell extended death. Overall, its lack of toxicity vis. a vis. the toxicity and genotoxicity of the DNA intercalating dyes makes JC1 an ideal tool for isolating live cells expressing high multidrug resistance transport activity.
Epistemological and didactical aspects related to theconcept of periodicity across different school subjects

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Compensatory growth in cattle - revisited

Compensatory growth in cattle has been regularly reviewed (Allden, 1970; O’Donovan, 1984; Ryan, 1990) and factors influencing the recovery of liveweight sacrificed by a period of under-nutrition have been identified (severity and duration of under-nutrition, duration of the recovery period and age at restriction) but not quantified. A data base representing 207 examples of compensatory growth in the literatunz was used to identify factors explaining the variance in recovered liveweight, unrecovered liveweight and % recovery in a general least squares linear model. Sixty percent of the variance in unrecovered gain was associated with the severity of the restriction but the recovered liveweight gain and % recovery was associated with only variablesoftherecoveryperiodOiveweightgainofunrestrictedgroup,28%; liveweightgainofrestrictedgroup,38%anddurationofrecovery, 14%). This focuses attention on the greater importance of the recovery p&cd than the restriction period. Average % recovery was only 37% with a mean liveweight gain of the recovering cattle of 0.95 kg/d over 150 day recovery period. We argue on theoretical grounds and with evidence that high levels of liveweight gain during recovery will only be achieved when an intense restriction has been imposed on older cattle and the recovery period has been long and at a high rate of liveweight gain.
Leveraging quality web‐based library user services in the digital age

Purpose – The purpose of this paper is to explore key issues involved with opportunities, challenges, and future developing trends of delivering dynamic and distributed web‐based academic library information resources, services, and instructions for library users in the digital age.Design/methodology/approach – Based on the typical web‐based, three‐tier client/server architecture, this paper explores ten key issues how to leverage quality library user services in the digital age: roles of academic libraries; funding support; information resources; information access; information services; instructions and trainings; impacts of cutting‐edge technologies and emerging technologies; web contents management and knowledge base; assessment and evaluation; and Librarians. Also discussed are the next‐generation web‐based client/server library information architecture and services in the foreseeable future.Findings – With the rapid development of the internet and the world wide web, information exchange and informa.
Recognition Method for Abnormal Water Surface Based on SOM

Abnormal Water Surface monitoring and recognition technique still is the research focus at present. In this paper, we first establish a background model with Gaussian Mixture Model, achieve the abnormal region quickly using background difference method, then, a improve algorithm of color moment calculation is used to extract the abnormal features, finally the SOM model is used to cluster the characteristics of the data, the data classifier is established. Keywords-Background subtraction; Color moments; Color histogram; Clustering; Recognition.
Investigation of SiC and C nanostructures synthesized by the method of chemical vapor deposition on Ni films

The paper presents the results of experiments on synthesis of SiC and C nanostructures by the method ofmicrowave plasma assisted chemical vapor deposition on Ni films. The plates of polished single-crystal andporous silicon were used, on the surface of which a thin layer of Ni was deposited. The dependence of thestructure and morphology of the samples on the plasma power is studied. Scanning electron microscopy hasshown that the formed nanostructures have a diameter of 100-170 nm and a rough surface. Analysis of theresults showed that, the growth of nanostructures on the surface of porous silicon is more massive in contrast topolished Si. By means of Raman scattering the structure of the obtained samples and its dependence on theplasma power were studied. The results of studies showed the presence of silicon carbide nanostructures with3C-SiC polytype structure. Also, the main carbon peaks in the range of ~1300 and ~1500 cm-1, whichcorrespond to carbon nanostructures were found on both types of substrates.
Adolescent Violence: A Family Health and Community Challenge

ABSTRACT Adolescent violence is increasingly a major national and international problem that particularly affects families and communities. The purpose of this article is to explore the multidimensional features of adolescent violence and profile successful prevention and intervention strategies. A review of contemporary approaches addressing youth violence was conducted and conclusions are drawn for strategies that are effective at the family and community level.