Search results for: latent sweat fingerprints

Authors: R. Hela, L. Bodnarova

Abstract:

Paper focuses on experimental testing of possibilities of mechanical activation of fly ash and observation of influence of specific surface and granulometry on final properties of fresh and hardened concrete. Mechanical grinding prepared various fineness of fly ash, which was classed by specific surface in accordance with Blain and their granulometry was determined by means of laser granulometer. Then, sets of testing specimens were made from mix designs of identical composition with 25% or Portland cement CEM I 42.5 R replaced with fly ash with various specific surface and granulometry. Mix design with only Portland cement was used as reference. Mix designs were tested on consistency of fresh concrete and compressive strength after 7, 28, 60 and 90 days.

Keywords: Concrete, fly ash, latent hydraulicity, mechanically activated fly ash.

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Authors: Nikolay Nikolaev, Evgueni Smirnov

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This paper develops an unscented grid-based filter and a smoother for accurate nonlinear modeling and analysis of time series. The filter uses unscented deterministic sampling during both the time and measurement updating phases, to approximate directly the distributions of the latent state variable. A complementary grid smoother is also made to enable computing of the likelihood. This helps us to formulate an expectation maximisation algorithm for maximum likelihood estimation of the state noise and the observation noise. Empirical investigations show that the proposed unscented grid filter/smoother compares favourably to other similar filters on nonlinear estimation tasks.

Keywords:

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Authors: A. Naceri, M. S. Bouglada, P. Grosseau

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The setting agent Ca(OH)2 for activation of slag cement is used in the proportions of 0%, 2%, 4%, 6%, 8% and 10% by various methods (substitution and addition by mass of slag cement). The physical properties of slag cement activated by the calcium hydroxide at anhydrous and hydrated states (fineness, particle size distribution, consistency of the cement pastes and setting times) were studied. The activation method by the mineral activator of slag cement (latent hydraulicity) accelerates the hydration process and reduces the setting times of the cement activated.

Keywords: Mineral activator, slag cement, Anhydrous and hydrated states, physical characteristics.

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: Iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, scale invariant feature transform.

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Authors: Fatma Khaled, Khaoula Hidouri, Bechir Chaouachi

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Desalination using solar energy coupled with membrane techniques such as vacuum membrane distillation (VMD) is considered as an interesting alternative for the production of pure water. During this work, a developed model of a polytetrafluoroethylene (PTFE) hollow fiber membrane module of a VMD unit of seawater was carried out. This simulation leads to establishing a comparison between the effects of two different equations of the vaporization latent heat on the membrane surface temperature and on the unit productivity. Besides, in order to study the effect of putting membrane modules in series on the outlet fluid temperature and on the productivity of the process, a simulation was executed.

Keywords: Vacuum membrane distillation, membrane module, membrane temperature, productivity.

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Authors: Norwati Mustapha, Manijeh Jalali, Abolghasem Bozorgniya, Mehrdad Jalali

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Web usage mining algorithms have been widely utilized for modeling user web navigation behavior. In this study we advance a model for mining of user-s navigation pattern. The model makes user model based on expectation-maximization (EM) algorithm.An EM algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. The experimental results represent that by decreasing the number of clusters, the log likelihood converges toward lower values and probability of the largest cluster will be decreased while the number of the clusters increases in each treatment.

Keywords: Web Usage Mining, Expectation maximization, navigation pattern mining.

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Authors: Juliana V. Pereira, Adriana S. M. Batista, Jefferson P. Nascimento, Clascídia A. Furtado, Luiz O. Faria

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Exposure to ionizing radiation has been found to induce changes in poly(vinylidene fluoride) (PVDF) homopolymers. The high dose gamma irradiation process induces the formation of C=C and C=O bonds in its [CH₂-CF₂]_n main chain. The irradiation also provokes crosslinking and chain scission. All these radio-induced defects lead to changes in the PVDF crystalline structure. As a consequence, it is common to observe a decrease in the melting temperature (T_M) and melting latent heat (L_M) and some changes in its ferroelectric features. We have investigated the possibility of preparing nanocomposites of PVDF with graphene oxide (GO) through the radio-induction of molecular bonds. In this work, we discuss how the gamma radiation interacts with the nanocomposite crystalline structure.

Keywords: Gamma irradiation, grapheme oxide, nanocomposites, PVDF.

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Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

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In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: Activity modeling, clustering, PLSA, video representation.

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Authors: W. Hou, X. Shan, X. Ye

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Bidding is a very important business function to find latent contractors of construction projects. Moreover, bid markup is one of the most important decisions for a bidder to gain a reasonable profit. Since the bidding system is a complex adaptive system, bidding agent need a learning process to get more valuable knowledge for a bid, especially from past public bidding information. In this paper, we proposed an iterative agent leaning model for bidders to make markup decisions. A classifier for public bidding information named PIBS is developed to make full use of history data for classifying new bidding information. The simulation and experimental study is performed to show the validity of the proposed classifier. Some factors that affect the validity of PIBS are also analyzed at the end of this work.

Keywords: bidding markup, decision making, agent learning, information similarity.

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Authors: Zhang Yan, Yu Bin

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Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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Authors: Z. Jannoo, B. W. Yap, N. Auchoybur, M. A. Lazim

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The two common approaches to Structural Equation Modeling (SEM) are the Covariance-Based SEM (CB-SEM) and Partial Least Squares SEM (PLS-SEM). There is much debate on the performance of CB-SEM and PLS-SEM for small sample size and when distributions are nonnormal. This study evaluates the performance of CB-SEM and PLS-SEM under normality and nonnormality conditions via a simulation. Monte Carlo Simulation in R programming language was employed to generate data based on the theoretical model with one endogenous and four exogenous variables. Each latent variable has three indicators. For normal distributions, CB-SEM estimates were found to be inaccurate for small sample size while PLS-SEM could produce the path estimates. Meanwhile, for a larger sample size, CB-SEM estimates have lower variability compared to PLS-SEM. Under nonnormality, CB-SEM path estimates were inaccurate for small sample size. However, CB-SEM estimates are more accurate than those of PLS-SEM for sample size of 50 and above. The PLS-SEM estimates are not accurate unless sample size is very large.  

Keywords: CB-SEM, Monte Carlo simulation, Normality conditions, Nonnormality, PLS-SEM.

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Authors: Awni H. Alkhazaleh, Baljinder K. Kandola

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In this study, a form-stable composite Paraffin/Nanoclay (PA-NC) has been prepared by absorbing PA into porous particles of NC to be used for low-temperature latent heat thermal energy storage. The leakage test shows that the maximum mass fraction of PA that can be incorporated in NC without leakage is 60 wt.%. Differential scanning calorimetry (DSC) has been used to measure the thermal properties of the PA and PA-NC both before and after incorporation in plasterboard (PL). The mechanical performance of the samples has been evaluated in flexural mode. The thermal energy storage performance has been studied using a small test chamber (100 mm × 100 mm × 100 mm) made from 10 mm thick PL and measuring the temperatures using thermocouples. The flammability of the PL+PL-NC has been discussed using a cone calorimeter. The results indicate that the form composite PA has good potential for use as thermal energy storage materials in building applications.

Keywords: Flammability, paraffin, plasterboard, thermal energy storage.

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Authors: Hossein Mohammadzadeh, Mojtaba Heydarizad

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Among various water resources, the surface water has a dominant role in providing water supply in the arid and semi-arid region of Iran. Andarokh-Kardeh basin is located in 50 km from Mashhad city - the second biggest city of Iran (NE of Iran), draining by Kardeh river which provides a significant portion of potable and irrigation water needs for Mashhad. The stable isotopes (¹⁸O, ²H,¹³C-DIC, and ¹³C-DOC), as reliable and precious water fingerprints, have been measured in Kardeh river (Kharket, Mareshk, Jong, All and Kardeh stations) and in Kardeh dam reservoirs (at five different sites S1 to S5) during March to June 2011 and June 2012. On δ¹⁸O vs. δ²H diagram, the river samples were plotted between Global and Eastern Mediterranean Meteoric Water lines (GMWL and EMMWL) which demonstrate that various moisture sources are providing humidity for precipitation events in this area. The enriched δ¹⁸O and δ²H values (-6.5 ‰ and -44.5 ‰ VSMOW) of Kardeh dam reservoir are compared to Kardeh river (-8.6‰and-54.4‰), and its deviation from Mashhad meteoric water line (MMWL- δ²H=7.16δ¹⁸O+11.22) is due to evaporation from the open surface water body. The enriched value of δ ¹³C-DIC and high amount of DIC values (-7.9 ‰ VPDB and 57.23 ppm) in the river and Kardeh dam reservoir (-7.3 ‰ VPDB and 55.53 ppm) is due to dissolution of Mozdooran Carbonate Formation lithology (Jm1 to Jm3 units) (contains enriched δ¹³C DIC values of 9.2‰ to 27.7‰ VPDB) in the region. Because of the domination of C3 vegetations in Andarokh_Kardeh basin, the δ¹³C-DOC isotope of the river (-28.4‰ VPDB) and dam reservoir (-32.3‰ VPDB) demonstrate depleted values. Higher DOC concentration in dam reservoir (2.57 ppm) compared to the river (0.72 ppm) is due to more biologogical activities and organic matters in dam reservoir.

Keywords: Dam reservoir, Iran, Kardeh river, Khorasan razavi, Stable isotopes.

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: Kalyankumar M. Matti, Chandrashekhar J. Savanurmath, Shivayogeppa B. Hinchigeri

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A rare phenomenon of SDS-induced activation of a latent protease activity associated with the purified silkworm excretory red fluorescent protein (SE-RFP) was noticed. SE-RFP aliquots incubated with SDS for different time intervals indicated that the protein undergoes an obligatory breakdown into a number of subunits which exhibit autoproteolytic (acting upon themselves) and/or heteroproteolytic (acting on other proteins) activities. A strong serine protease activity of SE-RFP subunits on Bombyx mori nucleopolyhedrovirus (BmNPV) polyhedral protein was detected by zymography technique. A complete inhibition of BmNPV infection to silkworms was observed by the oral administration assay of the SE-RFP. Here, it is proposed that the SE-RFP prevents the initial infection of BmNPV to silkworms by obliterating the polyhedral protein. This is the first report on a silkworm red fluorescent protein that exhibits a protease activity on exposure to SDS. The present studies would help in understanding the antiviral mechanism of silkworm red fluorescent proteins.

Keywords: BmNPV, polyhedra, SE-RFP, SDS-induced protease activity, zymography.

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Authors: Norazah Mohd Suki, T Ramayah

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e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.

Keywords: E-government, structural equation modelling, attitude, service.

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Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla

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Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.

Keywords: Denial-of-service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities.

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Authors: Tristan O'Neill, Trina Myers, Jarrod Trevathan

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The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: Impact measurement model, lean bundles, lean manufacturing, organizational performance.

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Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on hyperspectral image (HSI) dataset on Indian Pines. The results confirm the capability of the proposed method.

Keywords: Continual learning, data reconstruction, remote sensing, hyperspectral image segmentation.

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Authors: Satoru Kaneko, Takeshi Ito, Kensuke Akiyama, Manabu Yasui, Chihiro Kato, Satomi Tanaka, Yasuo Hirabayashi, Takeshi Ozawa, Akira Matsuno, Takashi Nire, Hiroshi Funakubo, Mamoru Yoshimoto

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As application of re-activation of backside on power device Insulated Gate Bipolar Transistor (IGBT), laser annealing was employed to irradiate amorphous silicon substrate, and resistivities were measured using four point probe measurement. For annealing the amorphous silicon two lasers were used at wavelength of visible green (532 nm) together with Infrared (793 nm). While the green laser efficiently increased temperature at top surface the Infrared laser reached more deep inside and was effective for melting the top surface. A finite element method was employed to evaluate time dependent thermal distribution in silicon substrate.

Keywords: laser, annealing, silicon, recrystallization, thermal distribution, resistivity, finite element method, absorption, melting point, latent heat of fusion.

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Authors: Salman Iqbal

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Knowledge management (KM) literature has mainly focused on the antecedents of KM. The purpose of this study is to investigate the effect of specific human resource management (HRM) practices on employee knowledge sharing and its outcome as individual knowledge capability. Based on previous literature, a model is proposed for the study and hypotheses are formulated. The cross-sectional dataset comes from a sample of 19 knowledge intensive firms (KIFs). This study has run an item parceling technique followed by Confirmatory Factor Analysis (CFA) on the latent constructs of the research model. Employees’ collaboration and their interpersonal trust can help to improve their knowledge sharing behaviour and knowledge capability within organisations. This study suggests that in future, by using a larger sample, better statistical insight is possible. The findings of this study are beneficial for scholars, policy makers and practitioners. The empirical results of this study are entirely based on employees’ perceptions and make a significant research contribution, given there is a dearth of empirical research focusing on the subcontinent.

Keywords: Employees’ collaboration, individual knowledge capability, knowledge sharing, monetary rewards, structural equation modelling.

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Authors: Adriana Souza M. Batista, Cláubia Pereira, Luiz O. Faria

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The irradiation of polymeric materials has received much attention because it can produce diverse changes in chemical structure and physical properties. Thus, studying the chemical and structural changes of polymers is important in practice to achieve optimal conditions for the modification of polymers. The effect of gamma irradiation on the crystalline structure of poly(vinylidene fluoride) (PVDF) has been investigated using differential scanning calorimetry (DSC) and X-ray diffraction techniques (XRD). Gamma irradiation was carried out in atmosphere air with doses between 100 kGy at 3,000 kGy with a Co-60 source. In the melting thermogram of the samples irradiated can be seen a bimodal melting endotherm is detected with two melting temperature. The lower melting temperature is attributed to melting of crystals originally present and the higher melting peak due to melting of crystals reorganized upon heat treatment. These results are consistent with those obtained by XRD technique showing increasing crystallinity with increasing irradiation dose, although the melting latent heat is decreasing.

Keywords: Differential scanning calorimetry, gamma irradiation, PVDF, X-ray diffraction technique.

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Authors: Mária Stachová, Lukáš Sobíšek

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Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

Keywords: data mining, classification, drug design, QSAR

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Authors: S. Lgarch, M. Khalidi Idrissi, S. Bennani

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For best collaboration, Asynchronous tools and particularly the discussion forums are the most used thanks to their flexibility in terms of time. To convey only the messages that belong to a theme of interest of the tutor in order to help him during his tutoring work, use of a tool for classification of these messages is indispensable. For this we have proposed a semantics classification tool of messages of a discussion forum that is based on LSA (Latent Semantic Analysis), which includes a thesaurus to organize the vocabulary. Benefits offered by formal ontology can overcome the insufficiencies that a thesaurus generates during its use and encourage us then to use it in our semantic classifier. In this work we propose the use of some functionalities that a OWL ontology proposes. We then explain how functionalities like “ObjectProperty", "SubClassOf" and “Datatype" property make our classification more intelligent by way of integrating new terms. New terms found are generated based on the first terms introduced by tutor and semantic relations described by OWL formalism.

Keywords: Classification of messages, collaborative communication tools, discussion forum, e-learning, formal description, latente semantic analysis, ontology, owl, semantic relations, semantic web, thesaurus, tutoring.

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Authors: I. Abasi, L. Fata, M. Sadeghi, S. Banihashemi, A. Mohammadee

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Background: Dimensional and transdiagnostic approaches as a result of high comorbidity among mental disorders have captured researchers and clinicians interests for exploring the latent factors to development and maintenance of some psychological disorders. The goal of present study is comparing some of these common factors between generalized anxiety disorder and unipolar mood disorder. Methods: 27 patients with generalized anxiety disorder, 29 patients with depression disorder were recruited by using SCID-I and 69 non-clinical populations were selected by using GHQ cut off point. MANCOVA was used for analyzing data. Results: The results show that worry, rumination, intolerance of uncertainty, maladaptive metacognitive beliefs, and experiential avoidance were all significantly different between GAD and unipolar mood disorder groups. However, there weren’t any significant differences in difficulties in emotion regulation and neuroticism between GAD and unipolar mood disorder groups. Discussion: Results indicate that although there are some transdiagnostic and common factors in GAD and unipolar mood disorder, there may be some specific vulnerability factors for each disorder. Further study is needed for answering these questions.

Keywords: Depression, emotion regulation, generalized anxiety disorder, transdiagnostic.

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Authors: N. Hatraf, L. Merabeti, Z. Neffeh, W. Taane

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The excessive consumption of fossil energies (electrical energy) during summer caused by the technological development involves more and more climate warming.

In order to reduce the worst impact of gas emissions produced from classical air conditioning, heat driven solar absorption chiller is pretty promising; it consists on using solar as motive energy which is clean and environmentally friendly to provide cold.

Solar absorption machine is composed by four components using Lithium Bromide /water as a refrigerating couple. LiBr- water is the most promising in chiller applications due to high safety, high volatility ratio, high affinity, high stability and its high latent heat. The lithium bromide solution is constitute by the salt lithium bromide which absorbs water under certain conditions of pressure and temperature however if the concentration of the solution is high in the absorption chillers; which exceed 70%, the solution will crystallize.

The main aim of this article is to study the phenomena of the crystallization and to evaluate how the dependence between the electric conductivity and the concentration which should be controlled.

Keywords: Absorption chillers, crystallization, experimental results, Lithium Bromide solution.

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Authors: XhevrieMamaqi

Abstract:

Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspectsexplaining the variation in business results.

Keywords: Business results, Human and Social Capital resources, training, RBV Theory, SEM.

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Authors: Varun Joshi, Manish K. Rathod

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The latent heat thermal energy storage system is a thrust area of research due to exuberant thermal energy storage potential. The thermal performance of PCM is significantly augmented by installation of the high thermal conductivity fins. The objective of the present study is to obtain optimum size and location of the fins to enhance diffusion heat transfer without altering overall melting time. Hence, the constructal theory is employed to eliminate, resize, and re-position the fins. A numerical code based on conjugate heat transfer coupled enthalpy porosity approached is developed to solve Navier-Stoke and energy equation.The numerical results show that the constructal fin design has enhanced the thermal performance along with the increase in the overall volume of PCM when compared to conventional. The overall volume of PCM is found to be increased by half of total of volume of fins. The elimination and repositioning the fins at high temperature gradient from low temperature gradient is found to be vital.

Keywords: Constructal theory, enthalpy porosity approach, phase change materials, fins.

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