Search results for: Data Analytics

Authors: Z. A. Ahmad Noor Syukri, A. J. Nawal Aswan, S. V. Wong

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The motorcycle has become one of the most common type of vehicles used on the road, particularly in the Asia region, including Malaysia, due to its size-convenience and affordable price. This study focuses only on crashes involving motorcycles with passenger cars consisting 43 real world crashes obtained from in-depth crash investigation process from June 2016 till July 2017. The study collected and analyzed vehicle and site parameters obtained during crash investigation and injury information acquired from the patient-treating hospital. The investigation team, consisting of two personnel, is stationed at the Emergency Department of the treatment facility, and was dispatched to the crash scene once receiving notification of the related crashes. The injury information retrieved was coded according to the level of severity using the Abbreviated Injury Scale (AIS) and classified into different body regions. The data revealed that weekend crashes were significantly higher for the night time period and the crash occurrence was the highest during morning hours (commuting to work period) for weekdays. Bad weather conditions play a minimal effect towards the occurrence of motorcycle – passenger vehicle crashes and nearly 90% involved motorcycles with single riders. Riders up to 25 years old are heavily involved in crashes with passenger vehicles (60%), followed by 26-55 year age group with 35%. Male riders were dominant in each of the age segments. The majority of the crashes involved side impacts, followed by rear impacts and cars outnumbered the rest of the passenger vehicle types in terms of crash involvement with motorcycles. The investigation data also revealed that passenger vehicles were the most at-fault counterpart (62%) when involved in crashes with motorcycles and most of the crashes involved situations whereby both of the vehicles are travelling in the same direction and one of the vehicles is in a turning maneuver. More than 80% of the involved motorcycle riders had sustained yellow severity level during triage process. The study also found that nearly 30% of the riders sustained injuries to the lower extremities, while MAIS level 3 injuries were recorded for all body regions except for thorax region. The result showed that crashes in which the motorcycles were found to be at fault were more likely to occur during night and raining conditions. These types of crashes were also found to be more likely to involve other types of passenger vehicles rather than cars and possess higher likelihood in resulting higher ISS (>6) value to the involved rider. To reduce motorcycle fatalities, it first has to understand the characteristics concerned and focus may be given on crashes involving passenger vehicles as the most dominant crash partner on Malaysian roads.

Keywords: Motorcycle crash, passenger vehicle, in-depth crash investigation, injury mechanism.

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Authors: Abdel-Samad M. Ali

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Does the spatial perspective provide a common thread for rural sociology? Have rural sociologists succeeded in bringing order to their data using spatial analysis models and techniques? A trial answer to such questions, as touchstones of theoretical and applied sociological studies in rural areas, is the point at issue in the present paper. Spatial analyses have changed the way rural sociologists approach scientific problems. Rural sociology is spatial by nature because much, if not most, of its research topics has a spatial “awareness." However, such spatial awareness is not quite the same as spatial analysis because it is not typically associated with underlying theories and hypotheses about spatial patterns that are designed to be tested for their specific spatial content. This paper presents pressing issues for future research to reintroduce mainstream rural sociology to the concept of space.

Keywords: Maps, Rural Sociology, Space, Spatial variations

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Authors: A. I. Dounis, P. Tiropanis, D. Tseles, G. Nikolaou, G. P. Syrcos

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The prediction of meteorological parameters at a meteorological station is an interesting and open problem. A firstorder linear dynamic model GM(1,1) is the main component of the grey system theory. The grey model requires only a few previous data points in order to make a real-time forecast. In this paper, we consider the daily average ambient temperature as a time series and the grey model GM(1,1) applied to local prediction (short-term prediction) of the temperature. In the same case study we use a fuzzy predictive model for global prediction. We conclude the paper with a comparison between local and global prediction schemes.

Keywords: Fuzzy predictive model, grey model, local andglobal prediction, meteorological forecasting, time series.

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Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah

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This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.

Keywords: 3-D numerical analysis, damage mechanics, RC slab with opening.

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Authors: Alexandra Gheorghiu, Marie-Line Félonneau

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Speeding represents one of the main concerns for road safety and it still is a subject for research. The need to address this problem and to understand why drivers over speed increases especially in Romania, where in 2011, speed was the main cause of car accidents. This article addresses this problem by using the theory of planned behaviour. A questionnaire was administered to a sample of young Romanian drivers (18 to 25 years) and several path analyses were made in order to verify if the model proposed by the theory of planned behaviour fits the data. One interesting result is that perceived behavioural control does not predict the intention to speed or self-reported driving speed, but subjective norms do. This implies that peers and social environment have a greater impact on young Romanian drivers than we thought.

Keywords: Speed, traffic safety, theory of planned behaviour, young drivers.

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Authors: Esmaeil Poursaeidi, Mostafa Kamalzadeh Yazdi

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Different problems may causes distortion of the rotor, and hence vibration, which is the most severe damage of the turbine rotors. In many years different techniques have been developed for the straightening of bent rotors. The method for straightening can be selected according to initial information from preliminary inspections and tests such as nondestructive tests, chemical analysis, run out tests and also a knowledge of the shaft material. This article covers the various causes of excessive bends and then some applicable common straightening methods are reviewed. Finally, hot spotting is opted for a particular bent rotor. A 325 MW steam turbine rotor is modeled and finite element analyses are arranged to investigate this straightening process. Results of experimental data show that performing the exact hot spot straightening process reduced the bending of the rotor significantly.

Keywords: Distortion, FEM, Hot Spot Area, Rotor Straightening

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Authors: Gavin Perin, Linda Matthews

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Webcam systems now function as the new privileged vantage points from which to view the city. This transformation of CCTV technology from surveillance to promotional tool is significant because its'scopic regime' presents, back to the public, a new virtual 'site' that sits alongside its real-time counterpart. Significantly, thisraw 'image' data can, in fact,be co-optedand processed so as to disrupt their original purpose. This paper will demonstrate this disruptive capacity through an architectural project. It will reveal how the adaption the webcam image offers a technical springboard by which to initiate alternate urban form making decisions and subvert the disciplinary reliance on the 'flat' orthographic plan. In so doing, the paper will show how this 'digital material' exceeds the imagistic function of the image; shiftingit from being a vehicle of signification to a site of affect.

Keywords: Surveillance, virtual, scopic, additive

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Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: Empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer.

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Authors: M. F. Zaiyadi, B. Baharudin

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Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.

Keywords: Ant colony optimization, feature selection, information gain, text categorization, text representation.

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Authors: Azam Marjani, Saeed Shirazian

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In this study is presented a general methodology to predict the performance of a continuous near-critical fluid extraction process to remove compounds from aqueous solutions using hollow fiber membrane contactors. A comprehensive 2D mathematical model was developed to study Porocritical extraction process. The system studied in this work is a membrane based extractor of ethanol and acetone from aqueous solutions using near-critical CO2. Predictions of extraction percentages obtained by simulations have been compared to the experimental values reported by Bothun et al. [5]. Simulations of extraction percentage of ethanol and acetone show an average difference of 9.3% and 6.5% with the experimental data, respectively. More accurate predictions of the extraction of acetone could be explained by a better estimation of the transport properties in the aqueous phase that controls the extraction of this solute.

Keywords: Solvent extraction, Membrane, Mass transfer, Densegas, Modeling

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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Authors: Takashi Sakai, Shinsaku Kikuta, Jun-ichi Koyama

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Using a texture database, a statistical estimation of spring-back was conducted in this study on the basis of statistical analysis. Both spring-back in bending deformation and experimental data related to the crystal orientation show significant dispersion. Therefore, a probabilistic statistical approach was established for the proper quantification of these values. Correlation was examined among the parameters F(x) of spring-back, F(x) of the buildup fraction to three orientations after 92° bending, and F(x) at an as-received part on the basis of the three-parameter Weibull distribution. Consequent spring-back estimation using a texture database yielded excellent estimates compared with experimental values.

Keywords: Bending, Spring-back, Database, Crystallographic Orientation, Texture, SEM-EBSD, Weibull distribution, Statistical analysis.

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Authors: Danping Lin, C.K.M. Lee

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Re-entrant scheduling is an important search problem with many constraints in the flow shop. In the literature, a number of approaches have been investigated from exact methods to meta-heuristics. This paper presents a genetic algorithm that encodes the problem as multi-level chromosomes to reflect the dependent relationship of the re-entrant possibility and resource consumption. The novel encoding way conserves the intact information of the data and fastens the convergence to the near optimal solutions. To test the effectiveness of the method, it has been applied to the resource-constrained re-entrant flow shop scheduling problem. Computational results show that the proposed GA performs better than the simulated annealing algorithm in the measure of the makespan

Keywords: Resource-constrained, re-entrant, genetic algorithm (GA), multi-level encoding

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Authors: Amany M. Alshawi, Khaled Alduhaiman

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This paper proposes a technique to protect against email bombing. The technique employs a statistical approach, Naïve Bayes (NB), and Neural Networks to show that it is possible to differentiate between good and bad traffic to protect against email bombing attacks. Neural networks and Naïve Bayes can be trained by utilizing many email messages that include both input and output data for legitimate and non-legitimate emails. The input to the model includes the contents of the body of the messages, the subject, and the headers. This information will be used to determine if the email is normal or an attack email. Preliminary tests suggest that Naïve Bayes can be trained to produce an accurate response to confirm which email represents an attack.

Keywords: Email bombing, Legitimate email, Naïve Bayes, Neural networks, Non-legitimate email.

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Authors: A. H. Akhaveissy

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Nonlinear finite element method with eight noded isoparametric quadrilateral element is used for prediction of loaddeformation behavior including bearing capacity of foundations. Modified generalized plasticity model with non-associated flow rule is applied for analysis of soil-footing system. Also Von Mises and Tresca criterions are used for simulation of soil behavior. Modified generalized plasticity model is able to simulate load-deformation including softening behavior. Localization phenomena are considered by different meshes. Localization phenomena have not been seen in the examples. Predictions by modified generalized plasticity model show good agreement with laboratory data and theoretical prediction in comparison the other models.

Keywords: Localization phenomena, Generalized plasticity, Non-associated Flow Rule

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Authors: Sandy Daley, Sandra Jones, Don Iverson

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The benefits of physical activity for children are promoted widely and well understood; however factors which impact on children-s beliefs and attitudes towards physical education need to be explored in more detail. The purpose of this study was to evaluate how primary school children value and perceive their involvement in physical education (PE) classes through the use of drawings. While this type of data collection has been used previously to determine a child-s response to specific health education classes, such as drug education, to the best of our knowledge it has not been used in the context of PE. Results from this study showed that kindergarten children found PE classes fun and engaging. Children in Year 4 and Year 6 were less satisfied with PE classes because of the activities offered, the lack of opportunity to play sport, and perception that teachers did not appear to value this area of the curriculum.

Keywords: attitudes, physical education, primary school children, write and draw

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Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy. 

Keywords: Association Rules, FP-growth, Multiple minimum supports, Weka Tool

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Authors: M.A. Kamely, S.M. Kamil, C.W. Chong

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A mathematical model of the surface roughness has been developed by using response surface methodology (RSM) in grinding of AISI D2 cold work tool steels. Analysis of variance (ANOVA) was used to check the validity of the model. Low and high value for work speed and feed rate are decided from design of experiment. The influences of all machining parameters on surface roughness have been analyzed based on the developed mathematical model. The developed prediction equation shows that both the feed rate and work speed are the most important factor that influences the surface roughness. The surface roughness was found to be the lowers with the used of low feed rate and low work speed. Accuracy of the best model was proved with the testing data.

Keywords: Mathematical Modeling, Response surfacemethodology, Surface roughness, Cylindrical Grinding.

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Authors: Kepeng Li

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This paper examines the phenomenon of recidivism in the Chinese stock market, emphasizing the significance of mitigating repeat offences within the corporate domain. Using a contingency model and data from Chinese publicly listed companies (1999-2018), the study investigates the impact of underperformance, governance factors, and managerial traits on unethical conduct. The research suggests that persistently unmet economic objectives can foster problem-focused exploration, potentially leading to misconduct. Furthermore, the study considers the unique cultural context of China, where “guanxi” and corruption may influence corporate behavior. It concludes that governance mechanisms play a pivotal role in regulating corporate behavior, underscoring the necessity for enhanced oversight and enforcement of corporate governance standards.

Keywords: Recidivism, corporate misbehavior, BTOF, aspiration level, corporate governance, individual characteristics.

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Authors: Watcharin Kaewapichai, Pakorn Kaewtrakulpong

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In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.

Keywords: Direct Least Square Fitting, Ellipse Detection, RANSAC

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Authors: J. Jezierski, K. Janerka

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The results of the two-phase gas-solid jet in pneumatic powder injection process analysis were presented in the paper. The researches were conducted on model set-up with high speed camera jet movement recording. Then the recorded material was analyzed to estimate main particles movement parameters. The values obtained from this direct measurement were compared to those calculated with the use of the well-known formulas for the two-phase flows (pneumatic conveying). Moreover, they were compared to experimental results previously achieved by authors. The analysis led to conclusions which to some extent changed the assumptions used even by authors, regarding the two-phase jet in pneumatic powder injection process. Additionally, the visual analysis of the recorded clips supplied data to make a more complete evaluation of the jet behavior in the lance outlet than before.

Keywords: injection lance, liquid metal, powder injection, slip velocity, two-phase jet

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Authors: V. Komarova

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The main purpose of this research is the calculation of implicit prices of the environmental level of air quality in the city of Moscow on the basis of housing property prices. The database used contains records of approximately 20 thousand apartments and has been provided by a leading real estate agency operating in Russia. The explanatory variables include physical characteristics of the houses, environmental (industry emissions), neighbourhood sociodemographic and geographic data: GPS coordinates of each house. The hedonic regression results for ecological variables show «negative» prices while increasing the level of air contamination from such substances as carbon monoxide, nitrogen dioxide, sulphur dioxide, and particles (CO, NO2, SO2, TSP). The marginal willingness to pay for higher environmental quality is presented for linear and log-log models.

Keywords: Air pollution, environment, hedonic prices, real estate, willingness to pay.

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Authors: Anastasia Katsamaki, Nikolaos Bilalis, Vassilis Dedoussis

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This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Keywords: End-of-life treatment, Lean thinking, WEEE

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Authors: M. S. Osman, A. A. Tharwat, I. A. El-Khodary, A. G. Chalabi

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In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.

Keywords: Equity Markets, Future Scenarios, PortfolioSelection, Multiple Criteria Fuzzy Optimization

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Authors: Erez Cohen

Abstract:

The study examines the socioeconomic impact of development of an advanced industry in Israel. The research method is based on data collected from the Israel Central Bureau of Statistics and from the National Insurance Institute (NII) databases, which provided information that allows to examine the Economic and Social Changes during the 1990s. The study examined the socioeconomic effects of the development of advanced industry in Israel. The research findings indicate that as a result of globalization processes, the weight of traditional industry began to diminish as a result of factory closures and the laying off of workers. These circumstances led to growing unemployment among the weaker groups in Israeli society, detracting from their income and thus increasing inequality among different socioeconomic groups in Israel and enhancement of social disparities.

Keywords: Globalization, Israeli advanced industry, public policy, socio-economic indicators.

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Authors: Marzieh Talebzadeh Shoushtari

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The present study aimed to determine the effectiveness of Metaphor therapy on depression among female students. The sample included 60 female students with depression symptoms selected by simple sampling and randomly divided into two equal groups (experimental and control groups). Beck Depression Inventory was used to measure the variables. This was an experimental study with a pre-test/post-test design with control group. Eight metaphor therapy sessions were held for the experimental group. A post-test was administered to both groups. Data were analyzed using multivariate analysis of covariance (MANCOVA). Results showed that the Metaphor therapy decreased depression in the experimental group compared to the control group.

Keywords: Metaphor therapy, depression, female, students.

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Authors: Eric Jiang

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As a popular rank-reduced vector space approach, Latent Semantic Indexing (LSI) has been used in information retrieval and other applications. In this paper, an LSI-based content vector model for text classification is presented, which constructs multiple augmented category LSI spaces and classifies text by their content. The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms. The proposed classifier has been applied to email classification and its experiments on a benchmark spam testing corpus (PU1) have shown that the approach represents a competitive alternative to other email classifiers based on the well-known SVM and naïve Bayes algorithms.

Keywords: Feature Selection, Latent Semantic Indexing, Text Classification, Vector Space Model.

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Authors: Alba Barbarà Molinero, Rosalía Cascón Pereira

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We assert here that there might be some factors that influence professional identity construction at the university/higher education stage. In accord, we propose a conceptual framework of intervening factors in professional identity construction at university from a literature review and preliminary data from a qualitative pilot study using focus groups. This model identifies several factors that might influence university students- professional identity construction and group them into categories. In turn, we describe how these factors might contribute in strengthening or weakening their professional identity. Finally, we discuss the implications of strengthening students- PI for the university, individuals and organizations and we provide a roadmap for future empirical work in this area.

Keywords: Professional Identity, Higher education, influencing factors.

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Authors: S. Shaaban, T. McNamara, S. Hudson

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This paper reports on the performance of deliberately unbalanced, reliable, non-automated and assembly lines that merge, whose workstations differ in terms of their mean operation times. Simulations are carried out on 5- and 8-station lines with 1, 2 and 4 buffer capacity units, % degrees of line imbalance of 2, 5 and 12, and 24 different patterns of means imbalance. Data on two performance measures, namely throughput and average buffer level were gathered, statistically analysed and compared to a merging balanced line counterpart. It was found that the best configurations are a balanced line arrangement and a monotone decreasing order for each of the parallel merging lines, with the first generally resulting in a lower throughput and the second leading to a lower average buffer level than those of a balanced line.

Keywords: Average buffer level, merging lines, simulation, throughput, unbalanced.

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: Document analysis, sentimental analysis, emotion detection, WEKA tool, NRC Lexicon.

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