Search results for: Over dimension cargo

Authors: S. Mahmoodzadeh, J. Shahrabi, M. A. Torkamani, J. Sabaghzadeh Ghomi

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Recognizing behavioral patterns of financial markets is essential for traders. Japanese candlestick chart is a common tool to visualize and analyze such patterns in an economic time series. Since the world was introduced to Japanese candlestick charting, traders saw how combining this tool with intelligent technical approaches creates a powerful formula for the savvy investors. This paper propose a generalization to box counting method of Grassberger-Procaccia, which is based on computing the correlation dimension of Japanese candlesticks instead commonly used 'close' points. The results of this method applied on several foreign exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower chaotic dimension of Japanese candlesticks series than regular Grassberger-Procaccia method applied merely on close points of these same candles. This means there is some valuable information inside candlesticks.

Keywords: Chaos, Japanese candlestick, generalized box counting, strange attractor.

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Authors: M. A Anjum, M. Y. Javed, A. Basit

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In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.

Keywords: Biometrics, DCT, Face Recognition, Feature extraction.

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Authors: Pongsiri K.

Abstract:

This research aimed to study the market feasibility for new brand coffee house, the case study of Thailand.. This study is a mixed methods research combining quantitative research and the qualitative research. Primary data 350 sets of questionnaires were distributed, and the high quality completed questionnaires of 320 sets returned. Research samples are identified as customers’ of Hi-end department stores in Thailand. The sources of secondary data were critical selected from highly reliable sources, both from public and private sectors. The results were used to classify the customer group into two main groups, the younger than 25 and the older than 25years old. Results of the younger group, are give priority to the dimension of coffee house and its services dimension more than others, then branding dimension and the product dimension respectively. On the other hand, the older group give the difference result as they rate the important of the branding, coffee house and its services, then the product respectively. Coffee consuming is not just the trend but it has become part of people lifestyle. And the new cultures also created by the wise businessman. Coffee was long produced and consumed in Thailand. But it is surprisingly the hi-end brand coffee houses in Thai market are mostly imported brands. The café business possibility for Thai brand coffee house in Thai market were discussed in the paper.

Keywords: Coffee House, Café, Coffee Consuming and new entry branding, market feasibility

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Authors: Peña Aguilar Juan M., Valencia Luis, Pastrana Alberto, Nava Estefany, Martinez A., Vivanco M., Castañeda A.

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This paper seeks to compare the innovation of Mexico from an economic and human perspective, with the seven most innovative countries according to the Global Innovation Index 2013, done by the World Intellectual Property Organization (WIPO). The above analysis suggests nine dimensions: Expenditure on R & D, intellectual property, appropriate environment to conduct business, economic stability, triple helix for R & D, ICT Infrastructure, education, human resources and quality of life. Each dimension is represented by an indicator which is later used to construct a radial graph that compares the innovative capacity of the countries analyzed. As a result, it is proposed a new indicator of innovation called The Area of Innovation. Observations are made from the results, and finally as a conclusion, those items or dimensions in which Mexico suffers lag in innovation are identify.

Keywords: Dimension, measure, innovation level, economy, radar chart.

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Authors: Ali Anaissi, Paul J. Kennedy, Madhu Goyal

Abstract:

Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.

Keywords: Linear Dimension Reduction, Non-Linear Dimension Reduction, Principal Component Analysis, Biologists.

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Authors: M. Bougamouza, M. Bouhadef, T. Zitoun

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The aim of this study is to examine, through experimentation in the laboratory, the supercritical flow in the presence of an obstacle in a rectangular channel. The supercritical regime in the whole hydraulic channel is achieved by adding a convergent. We will observe the influence of the obstacle shape and dimension on the characteristics of the supercritical flow, mainly the free-surface elevation and the velocity profile. The velocity measurements have been conducted with the one dimension laser anemometry technique.

Keywords: Experiments, free-surface flow, hydraulic channel, uneven bottom, laser anemometry, supercritical regime.

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Authors: Oleg Demchenko

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The aim of the present study is to analyze empirical researches on the social resources dimension of occupational status attainment process and relate them to the rational choice approach. The analysis suggests that the existing data on the strength of ties aspect of social resources is insufficient and does not allow any implication concerning rational actor-s behavior. However, the results concerning work relation aspect are more encouraging.

Keywords: Social resources, status attainment, rational choice, weak ties, work-related ties.

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Authors: M. Almas Anjum, M. Younus Javed, A. Basit

Abstract:

In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.

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Authors: Rajasekhar Mamilla, Janardhana G., Anjan Babu G.

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The present research study analyses the students’ satisfaction with university performance regarding the reliability dimension, ability of professors and staff to perform the promised services with quality to students in the post-graduate courses offered by Sri Venkateswara University in India. The research is done with the notion that the student compares the perceived performance with prior expectations. Customer satisfaction is seen as the outcome of this comparison. The sample respondents were administered with schedule based on stratified random technique for this study. Statistical techniques such as factor analysis, t-test and correlation analysis were used to accomplish the respective objectives of the study.

Keywords: Satisfaction, Reliability, Service Quality.

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Authors: M.Radmehr, S.M.Anisheh, I.Yousefian

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In this work a new offline signature recognition system based on Radon Transform, Fractal Dimension (FD) and Support Vector Machine (SVM) is presented. In the first step, projections of original signatures along four specified directions have been performed using radon transform. Then, FDs of four obtained vectors are calculated to construct a feature vector for each signature. These vectors are then fed into SVM classifier for recognition of signatures. In order to evaluate the effectiveness of the system several experiments are carried out. Offline signature database from signature verification competition (SVC) 2004 is used during all of the tests. Experimental result indicates that the proposed method achieved high accuracy rate in signature recognition.

Keywords: Fractal Dimension, Offline Signature Recognition, Radon Transform, Support Vector Machine

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Authors: Dyah E. Herwindiati

Abstract:

A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paper

Keywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance

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Authors: K. Puren, H. Coetzee, V. Roos

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Uniqueness and distinctiveness of localities (referred to as genius loci or sense of place) are important to ensure people-s identification with their locality. Existing frameworks reveals that the affective dimension of environments is rarely mentioned or explored and limited public participation was used in constructing the frameworks. This research argues that the complexity of sense of place would be recognised and appropriate planning guidelines formulated by exploring and integrating the affective dimension of a site. Aims of the research therefore are to (i) explore relational dimensions between people and a natural rural landscape, (ii) to implement a participatory approach to obtain insight into different relational dimensions, and (ii) to concretise socio-affective relational dimensions into site planning guidelines. A qualitative, interdisciplinary research approach was followed and conducted on the farm Kromdraai, Vredefort Dome World Heritage Site. In essence the first phase of the study reveals various affective responses and projections of personal meanings. The findings in phase 1 informed the second phase, to involve people from various disciplines and different involvement with the area to make visual presentations of appropriate planning and design of the site in order to capture meanings of the interactions between people and their environment. Final site planning and design guidelines were formulated, based on these. This research contributed to provide planners with new possibilities of exploring the dimensions between people and places as well as to develop appropriate methods for participation to obtain insight into the underlying meanings of sites.

Keywords: Affective dimension, Sense of place, spatialplanning, Vredefort Dome World Heritage Site.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

Abstract:

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: Mukesh Doble, Sunil K Narayan

Abstract:

Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.

Keywords: Chaos, Diffuse encephalitis, Electroencephalogram, Fractal dimension, Fourier spectrum.

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Authors: Joseph C. Chen, Joshua Cox

Abstract:

This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L₁₈ Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi parameter design, surface roughness, dimensional accuracy, Wire EDM.

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Authors: Michele Sinico

Abstract:

The psychological present has an actual extension. When a sequence of instantaneous stimuli falls in this short interval of time, observers perceive a compresence of events in succession and the temporal order depends on the qualitative relationships between the perceptual properties of the events. Two experiments were carried out to study the influence of perceptual grouping, with and without temporal displacement, on the duration of auditory sequences. The psychophysical method of adjustment was adopted. The first experiment investigated the effect of temporal displacement of a white noise on sequence duration. The second experiment investigated the effect of temporal displacement, along the pitch dimension, on temporal shortening of sequence. The results suggest that the temporal order of sounds, in the case of temporal displacement, is organized along the pitch dimension.

Keywords: Time perception, perceptual present, temporal displacement, gestalt laws of perceptual organization

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Authors: Khaled Harrar, Rachid Jennane

Abstract:

The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an agematched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: Osteoporosis, fractal dimension, fractal signature, bone mineral density.

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Authors: Hamad Hussain Balhareth, Kecheng Liu, Sharm Manwani

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Business and IT alignment has continued as a top concern for business and IT executives for almost three decades. Many researchers have conducted empirical studies on the relationship between business-IT alignment and performance. Yet, these approaches, lacking a social perspective, have had little impact on sustaining performance and competitive advantage. In addition to the limited alignment literature that explores organisational learning that is represented in shared understanding, communication, cognitive maps and experiences. Hence, this paper proposes an integrated process that enables social and intellectual dimensions through the concept of organisational learning. In particular, the feedback and feedforward process which provide a value creation across dynamic multilevel of learning. This mechanism enables on-going effectiveness through development of individuals, groups and organisations, which improves the quality of business and IT strategies and drives to performance.

Keywords: business-IT alignment, social dimension, intellectual dimension, organisational learning

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Authors: Zeynep İltüzer Samur, Gül Tekin Temur

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Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.

Keywords: Option Pricing, Neural Network, S&P 100 Index, American/European options

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Authors: T. Männistö, M. Finger

Abstract:

The events of October 2010, where terrorists managed to get explosive devices onboard of three passenger aircrafts and two air freighters, demonstrated weaknesses of the international air cargo and airmail security. Ever since, postal security has gained interest among policymakers and authorities. This study augments the limited body of academic literature on the topic bydemarcating areas of postal security, identifying relevant stakeholders in each area, and investigating why these stakeholders engage in postal security. Research is based on a case study on Swiss Post’s mail service.

Keywords: Dangerous goods, mail bombs, postal security, supply chain security, theft of mail, trafficking.

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Authors: Khashayar Kashani Jou, Ilnaz Fathololoomi

Abstract:

Nowadays, access to sustainable development in cities is assumed as one of the most important goals of urban managers. In the meanwhile, neighborhood as the smallest unit of urban spatial organization has a substantial effect on urban sustainability. Hence, attention to and focus on this subject is highly important in urban development plans. The objective of this study is evaluation of the status of Jahanshahr Neighborhood in Karaj city based on sustainable neighborhood development indicators. This research has been applied based on documentary method and field surveys. Also, evaluating of Jahanshahr Neighborhood of Karaj shows that it has a high level in sustainability in physical and economical dimension while a low level in cultural and social dimension. For this purpose, this neighborhood as a semi-sustainable neighborhood must take measures for development of collective spaces and efficiency of utilizing the public neighborhood spaces via collaboration of citizens and officials.

Keywords: Neighborhood, Sustainable Development, Sustainable Neighborhood Development, Jahanshahr Neighborhood.

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Authors: Mousa Mojarrad, Amir Masoud Rahmani, Mehrab Mohebi

Abstract:

Detection, feature extraction and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes and the high dimensionality of articulated body models and also the important field in Image, Signal and Vision Computing in recent years. In this paper, four types of people in 2D dimension image will be tested and proposed. The system will extract the size and the advantage of them (such as: tall fat, short fat, tall thin and short thin) from image. Fat and thin, according to their result from the human body that has been extract from image, will be obtained. Also the system extract every size of human body such as length, width and shown them in output.

Keywords: Analysis of Image Processing, Canny Edge Detection, Human Body Recognition, Measurement, Pose Estimation, 2D Human Dimension.

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Authors: Al-Rousan, M. Ramzi, Badaruddin Mohamed

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In the present Jordan hotels scenario, service quality is a vital competitive policy to keep customer support and build great base. Hotels are trying to win customer loyalty by providing enhanced quality services. This paper attempts to examine the impact of tourism service quality dimension in the Jordanian five star hotels. A total of 322 surveys were administrated to tourists who were staying at three branches Marriott hotel in Jordan. The results show that dimensions of service quality such as empathy, reliability, responsiveness and tangibility significantly predict customer loyalty. Specifically, among the dimension of tourism service quality, the most significant predictor of customer loyalty is tangibility. This paper implies that five star hotels in Jordan should also come forward and try their best to present better tourism service quality to win back their customers- loyalty.

Keywords: Tourism, Service Quality, Loyalty, Five Star hotels, Jordan.

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Authors: Eva Čáslavová, Andrej Višněvský

Abstract:

This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.

Keywords: Brand personality dimensions, ice hockey, international sport event, sports marketing.

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Authors: César Garza

Abstract:

In supervised binary classification and regression problems, it is well-known that learnability is equivalent to uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: Statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization.

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Authors: Huseyin Cetin, Halil Akmese, Sercan Aras, Vahit Aytekin

Abstract:

Economic crisis, terrorism, global crisis and the relations between countries are the factors affecting tourism industry and tourism industry is vulnerable against these factors. In our study, there are two dimensions about Russian crisis. The crisis between Russia and Ukraine and decreased oil prices in global market have been entailed Russian economic crisis. This crisis has induced that the ruble, Russian currency, has depreciated against American dollars and consequently the purchasing power of Russian has weakened. This is the first dimension of our study. Second dimension is a political crisis between Turkey and Russia owing to the fact that the Russian Warcraft was brought down by Turkish army. The aim of this study is to explain the impact of the consequences of Russian crisis on Turkish tourism industry. The study has been limited only Antalya province.

Keywords: Economic crisis, Turkey-Russian crisis, Turkey's tourism industry, tourism in Turkey.

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Authors: Takeru YOKOI, Hidekazu YANAGIMOTO, Sigeru OMATU

Abstract:

We have proposed an information filtering system using index word selection from a document set based on the topics included in a set of documents. This method narrows down the particularly characteristic words in a document set and the topics are obtained by Sparse Non-negative Matrix Factorization. In information filtering, a document is often represented with the vector in which the elements correspond to the weight of the index words, and the dimension of the vector becomes larger as the number of documents is increased. Therefore, it is possible that useless words as index words for the information filtering are included. In order to address the problem, the dimension needs to be reduced. Our proposal reduces the dimension by selecting index words based on the topics included in a document set. We have applied the Sparse Non-negative Matrix Factorization to the document set to obtain these topics. The filtering is carried out based on a centroid of the learning document set. The centroid is regarded as the user-s interest. In addition, the centroid is represented with a document vector whose elements consist of the weight of the selected index words. Using the English test collection MEDLINE, thus, we confirm the effectiveness of our proposal. Hence, our proposed selection can confirm the improvement of the recommendation accuracy from the other previous methods when selecting the appropriate number of index words. In addition, we discussed the selected index words by our proposal and we found our proposal was able to select the index words covered some minor topics included in the document set.

Keywords: Information Filtering, Sparse NMF, Index wordSelection, User Profile, Chi-squared Measure

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Authors: Yalçın Ozdemir

Abstract:

The purpose of this study was to examine to what extend classroom management efficacy, marital status, gender, and teaching experience predict burnout among primary school teachers. Participants of this study were 523 (345 female, 178 male) teachers who completed inventories. The results of multiple regression analysis indicated that three dimensions of teacher burnout (Emotional Exhaustion, Depersonalization, Personal Accomplishment) were affected differently from four predictor variables. Findings indicated that for the emotional exhaustion, classroom management efficacy, marital status and teaching experience; for depersonalization dimension, classroom management efficacy and marital status and finally for the personal accomplishment dimension, classroom management efficacy, gender, and teaching experience were significant predictors.

Keywords: Classroom management efficacy, teacher burnout.

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Authors: Lejla Mušić

Abstract:

Gender dimension of migration analyzes the intersection in between the world statistics on male and female migrations, around the world, involving the questions of youth migrations. Comparative analyses of world migration statistics as methodology offer the insight into the position of women in labor market around world. There are different forms of youth debris in contemporary world. The main problems are illegal migration, feminization of poverty, kidnapping the girls in Nigeria, femicides in Juarez and Mexico. Illegal migrations involve forced labor, rape and prostitution. Transgender youth share ideas through the online media (anti-bullying videos) and develop their own styles such as anarcho-punk, rave, or rock. Therefore, the stronger gender equality laws and laws for protection of women on work should be enforced.

Keywords: Hyper feminization, rape, gangs of girls, rent boys masculinities, Varoç in Istanbul.

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Authors: T. Sungkaworn, W. Triampo, P. Nalakarn, D. Triampo, I. M. Tang, Y. Lenbury, P. Picha

Abstract:

Semiconductor nanomaterials like TiO2 nanoparticles (TiO2-NPs) approximately less than 100 nm in diameter have become a new generation of advanced materials due to their novel and interesting optical, dielectric, and photo-catalytic properties. With the increasing use of NPs in commerce, to date few studies have investigated the toxicological and environmental effects of NPs. Motivated by the importance of TiO2-NPs that may contribute to the cancer research field especially from the treatment prospective together with the fractal analysis technique, we have investigated the effect of TiO2-NPs on colony morphology in the dark condition using fractal dimension as a key morphological characterization parameter. The aim of this work is mainly to investigate the cytotoxic effects of TiO2-NPs in the dark on the growth of human cervical carcinoma (HeLa) cell colonies from morphological aspect. The in vitro studies were carried out together with the image processing technique and fractal analysis. It was found that, these colonies were abnormal in shape and size. Moreover, the size of the control colonies appeared to be larger than those of the treated group. The mean Df +/- SEM of the colonies in untreated cultures was 1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs was 1.287±0.045. It was found that the circularity of the control group (0.401±0.071) is higher than that of the treated group (0.103±0.042). The same tendency was found in the diameter parameters which are 1161.30±219.56 μm and 852.28±206.50 μm for the control and treated group respectively. Possible explanation of the results was discussed, though more works need to be done in terms of the for mechanism aspects. Finally, our results indicate that fractal dimension can serve as a useful feature, by itself or in conjunction with other shape features, in the classification of cancer colonies.

Keywords: Tumor growth, Cell colonies, TiO2, Nanoparticles, Fractal, Morphology, Aggregation.

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