Search results for: service level JEL classification: C53

Authors: Renata Hrecska

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This research seeks to fully examine the internal employment law of international organizations by comparing it with the characteristics of the national civil service. The aim of the research is to compare the legal system that has developed over many centuries and the relatively new internal staffing regulations to find out what solution schemes can help each other through mutual legal development in order to respond effectively to the social challenges of everyday life. Generally, the rules of civil service of any country or international entity have in common that they have, in their pragmatics inherently, the characteristic that makes them serving public interests. Though behind the common base there are many differences: there is the clear fragmentation of state regulation and the unity of organizational regulation. On the other hand, however, this difference disappears to some extent: the public service regulation of international organizations can be considered uniform until we examine it within, but not outside an organization. As soon as we compare the different organizations we may find many different solutions for staffing regulations. It is clear that the national civil service is a strong model for international organizations, but the question may be whether the staffing policy of international organizations can serve the national civil service as an example, too. In this respect, the easiest way to imagine a legislative environment would be to have a single comprehensive code, the general part of which is the Civil Service Act itself, and the specific part containing specific, necessarily differentiating rules for each layer of the civil service. Would it be advantageous to follow the footsteps of the leading international organizations, or is there any speciality in national level civil service that we cannot avoid during regulating processes? In addition to the above, the personal competencies of officials working in international organizations and public administrations also show a high degree of similarity, regardless of the type of employment. Thus, the whole public service system is characterized by the fundamental and special values that a person capable of holding a public office must be able to demonstrate, in some cases, even without special qualifications. It is also interesting how we can compare the two spheres of employment in light of the theory of Lawyer Louis Brandeis, a judge at the US Supreme Court, who formulated a complex theory of profession as distinguished from other occupations. From this point of view we can examine the continuous development of research and specialized knowledge at work; the community recognition and social status; that to what extent we can see a close-knit professional organization of altruistic philosophy; that how stability grows in the working conditions due to the stability of the profession; and that how the autonomy of the profession can prevail.

Keywords: civil service, comparative law, international organizations, regulatory systems

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Authors: Nicole Kalemba, Fernando Campa-Planas, Ana-Beatriz Hernández-Lara, Maria Victória Sánchez-Rebull

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The purpose of this paper is to determine the effects of service quality on US airlines’ economic performance. In order to cover this goal, it has been considered four different indexes of service quality in the air transportation industry, and also two indicators of economic performance, revenues and return on investment (ROI). Data from American airline companies over a period that covers from 2006 to 2013 have been used in order to determine if airlines’ profitability increases when service quality improves. Considering the effects on airlines’ profitability, the results confirm the positive and significant influence of service quality on the ROI of the companies in our study. Meanwhile, a non-significant effect was found for airline revenues related to quality. No previous research in this area has been done and these findings could encourage airline companies to invest in quality as far as this policy can have a return on their profitability.

Keywords: airlines, economic performance, key performance indicators, quality

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Authors: Julian Donovan, Jessica Brealey, Matthew Bowker, Marianne Feghali, Gregory Smith, Lee Thompson, Deborah Henderson

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This article details the development of the X-ray response team (XRT), a service that utilises innovative technology to safely deliver acute and elective imaging and medical assessment service in the pre-hospital and community setting. This involves a partnership between Northumbria Healthcare NHS Foundation Trust’s Radiology and Emergency Medicine departments and the North East Ambulance Service to create a multidisciplinary prehospital team. The team committed to the delivery of a two-day acute service every week, alongside elective referrals, starting in November 2020. The service was originally made available to a 15-mile radius surrounding the Northumbria Hospital. Due to demand, this was expanded to include the North Tyneside and Northumberland regions. The target population was specified as frail and vulnerable patients, as well as those deemed to benefit from staying in their own environment. Within the first two months, thirty-six percent of patients assessed were able to stay at home due to the provision of off-site imaging. In the future, this service aims to allow patient transfer directly to an appropriate ward or clinic, bypassing the emergency department to improve the patient journey and reduce emergency care pressures.

Keywords: frailty, imaging, pre-hospital, X-ray

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Authors: Yutae Lee

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In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).

Keywords: availability, performance, stochastic reward net, 2N redundancy

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

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There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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Authors: Hamzeh Awad

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Disability is considered to be a worldwide complex phenomenon which rising at a phenomenal rate and caused by many different factors. Chronic diseases such as cardiovascular disease and diabetes can lead to mobility disability in particular and disability in general. The ICF is an integrative bio-psycho-social model of functioning and disability and considered by the World Health Organization (WHO) to be a reference for disability classification using its categories and core set to classify disorder’s functional limitations. Specialist programs at Sultan Bin Abdul Aziz Humanitarian City (SBAHC) are providing both inpatient and outpatient services have started to implement the ICF and use it as a problem solving tool in Rehab. Diabetes is leading contributing factor for disability and considered epidemic in several Gulf countries including the Kingdom of Saudi Arabia (KSA), where its prevalence continues to increase dramatically. Metabolic disorders, mainly diabetes are not well covered in Rehab field. The purpose of this study is present to research and clinical rehabilitation field of DREAM and ICF as a framework in clinical and research setting in Rehab service. Also, shed the light on using the ICF as problem solving tool at SBAHC. There are synergies between disability causes and wider public health priorities in relation to both chronic disease and disability prevention. Therefore, there is a need for strong advocacy and understanding of the role of ICF as a reference in Rehab settings in Middle East if we wish to seize the opportunity to reverse current trends of acquired disability in the region.

Keywords: international classification of functioning, disability and health (ICF), prototype, rehabilitation and diabetes

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Authors: Sittichai Charoensettasilp, Chong Wu

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This study employs sampling of 400 Thai people who live in Bangkok and have used air transportation to travel. A random convenience sampling technique is used to collect data. The results found that at 0.05 significance level the differences of means of Thai consumers’ expectations (before) and satisfaction (after) receiving services in the service marketing mix, the results of all aspects are different both in general and for each aspect of the service marketing mix. Average levels of expectations before receiving services are higher than satisfaction after receiving services in all aspects, as well. When analyzing further to the correlation between average means, the means of expectations before receiving services are higher than those of satisfaction after receiving services in general. As in all aspects of the service marketing mix, any aspect that has a big difference between expectations before receiving services and satisfaction after receiving services has low correlation.

Keywords: domestic low-cost airlines, Thai consumers, relationship, expectation before receiving services, satisfaction after receiving services

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: E. Elgohary, R. Abdelazyz

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The research aims to clarify the effect of the marketing culture on improving the e-service quality for foreign and domestic information technology companies in the Arab Republic of Egypt. So the researcher sought to include the dimensions of the marketing culture, which are (customer service, management style, sales mission, internal communications, technology, wages and rewards, innovation) as measures of marketing culture for its effect on improving the e-service quality in this research. The research population consists of employees and customers of the companies under study. The research problem was the following question: What is the effect of the actual application of marketing culture on improving the e-service quality? To answer that, three main hypotheses were adopted, and they were tested by statistical means for the data collected through a questionnaire prepared and distributed for this purpose. Accordingly, the research presented a set of results, the most important of which are: the need to pay attention to the dimensions of the marketing culture to improve the e-service quality, foreign companies were the most popular companies in applying the marketing culture compared to local companies. The research also recommends designing a system to continuously measure the performance of electronic service providers and work on spreading the culture of innovation among employees, linking reward programs to the extent of commitment to applying the elements of marketing culture while doing business.

Keywords: marketing culture, e-service quality, measurement models, quality measurements

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: R. Setino, I. M. Ambe, J. A Badenhorst-Weiss

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The South African government supply chain management system is not adequately implemented in State Owned Enterprises (SOEs). There are weaknesses in the SOEs SCM enablers, strategies and policies. In addition, top management of SOEs still do not see SCM as strategic enough to deserve their attention, and therefore, there is very little support from top management, thus making it even difficult for SCM practitioners to execute their day to day functions, let alone delivering the letter and spirit of the relevant legislations. Supply chain strategies lack buy in from the top, and as a result senior SCM practitioners has not been involved in the corporate strategy. This has resulted in supply chain and corporate strategies being misaligned. Due to service delivery backlog, high level of corruption and continuous strikes across the country for better services it is inevitable that government leaders be more strategic about how South Africa can use SCM as a tool to improve service delivery. Consequently, there is a need to close the gap between the strategic level dealt by top management and the application of operational SCM concepts: the use of SCM concepts and, therefore, supply chain strategies – should be aligned with the corporate and business strategies in order to ensure the achievement of top level business objectives. This paper aims to explore supply chain practices in State Owned Enterprises (SOEs). The paper based on a conceptual review provides the status, trends and development and suggests a framework for aligning supply chain strategies and organizational strategies in an SOE environment.

Keywords: alignment, strategies, state owned enterprises, supply chain management, South Africa

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Authors: Umer Mukhtar

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Supply Chain Competitiveness is the capability of a supply chain to deliver value to the customer for the sake of competitive advantage. Service Performance and Quality intervene between supply chain actors including functions inside the firm in a significant way for the supply chain to achieve a competitive position in the market to gain competitive advantage. Supply Chain competitiveness is the current issue of interest because of supply chains’ competition for competitive advantage rather than firms’. A proposed theoretical model is developed by extracting and integrating different theories to pursue further inquiry based on case studies and survey design. It is also intended to develop a scale of service performance for functions of the focal firm that is a revolving center for a whole supply chain.

Keywords: supply chain competitiveness, service performance in supply chain, service quality in supply chain, competitive advantage by supply chain, networks and supply chain, customer value, value supply chain, value chain

Procedia PDF Downloads 596

Authors: Sakul Jaariyachamsit, Kevin Wongleedee

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The objectives of this research were to study five perceptions of service quality from international tourists who visited Bangkok, Thailand. The independent variables included gender, age, levels of education, occupation, and income while the dependent variables included their opinion on the service provided by employees in Thai tourism. An accidental random sampling method was utilized to get 215 respondents. The respondents were both male and female in the same proportion and most were between 21-40 years old. Most were married and had a graduate degree. The average income of the respondents was between $20,000-40,000. The findings revealed that the majority of respondents came to Thailand for the first time and spent about 6-8 days in Thailand and preferred to travel in small groups with no children. The five service perceptions of employees in tourism by the international tourists in descending order according to mean were reliable employees, neat and clean employees, polite employees, timely employees, and competent employees.

Keywords: experience, international tourists, service quality, Thailand

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Authors: Hartomo Soewardi, Bachtiar Jouhari

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Ineffectiveness and inefficiency of the building permit process in Indonesia still becomes a major problems for people to apply. Long time of service, the complicated administration process, and an expensive fees are a process that causing a dissatisfaction and discomfort for applicant. Therefore, it is critical to improve the quality of service of building permit system. Objectives of this research is to develop a better process of the system to improve productivity and quality service. Lean six sigma concept by using DMAIC procedures was used to analyze the existing system. Moreover, improvement of the system was conducted by using the Axiomatic Design method. Verification test was done to test the hypothesis of the proposed system design. Result of this research shows that proposed system can produce increasing 61.8% of efficiency on service time, and more effective and easier.

Keywords: axiomatic design, bbuilding permit system, DMAIC, Lean Six Sigma

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

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Authors: P. Byrnes, F. A. DiazDelaO

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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

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Authors: Sabita Karki

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Occupational health hazards are recognized as global problems for health care workers, it is quiet high in developing countries. It is increasing day by day due to change in science and technology. This study aimed to assess the knowledge and practice of occupational health hazards among the nurses. A descriptive, cross sectional study was carried out among 339 nurses working in three different teaching hospitals of the Kathmandu from February 28, 2016 to March 28, 2016. A self-administered questionnaire was used to collect the data. The study findings revealed that out of 339 samples of all 80.5% were below 30 years; 51.6% were married; 57.5% were graduates and above; 91.4% respondents were working as staff nurse; 56.9% were working in general ward; 56.9% have work experience of 1 to 5 years; 79.1% respondents were immunized against HBV; only 8.6% have received training/ in-service education related to OHH and 35.4% respondents have experienced health hazards. The mean knowledge score was 26.7 (SD=7.3). The level of knowledge of occupational health hazards among the nurses was 68.1% (adequate knowledge). The knowledge was statistically significant with education OR = 0.288, CI: 0.17-0.46 and p value 0.00 and immunization against HBV OR= 1.762, CI: 0.97-0.17 and p value 0.05. The mean practice score was 7.6 (SD= 3.1). The level of practice on prevention of OHH was 74.6% (poor practice). The practice was statistically significant with age having OR=0.47, CI: 0.26-0.83 and p value 0.01; designation OR= 0.32, CI: 0.14-0.70 and p value 0.004; working department OR=0.61, CI: 0.36-1.02 and p value 0.05; work experience OR=0.562, CI: 0.33-0.94 and p value 0.02; previous in-service education/ training OR=2.25; CI: 1.02-4.92 and p value 0.04. There was no association between knowledge and practice on prevention of occupational health hazards which is not statistically significant. Overall, nurses working in various teaching hospitals of Kathmandu had adequate knowledge and poor practice of occupational health hazards. Training and in-service education and availability of adequate personal protective equipments for nurses are needed to encourage them adhere to practice.

Keywords: occupational health hazard, nurses, knowledge, preventive practice

Procedia PDF Downloads 334

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

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This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: Imran Badshah

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This paper study the impact of Un-signalized pedestrian on traffic flow at Stationary Bottleneck. The Highway Capacity Manual (HCM) analyze the methodology of level of service for Urban street segment but it does not include the impact of un-signalized pedestrian crossing at stationary bottleneck. The un-signalized pedestrian crossing in urban road segment causes conflict between vehicles and pedestrians. As a result, the average time taken by vehicle to travel along a road segment increased. The speed of vehicle and the level of service decreases as the running time of a segment increased. To analyze the delay, we need to determine the pedestrian speed while crossing the road at a stationary bottleneck. The objective of this research is to determine the speed of pedestrian and its impact on traffic flow at stationary bottleneck. In addition, the result of this study should be incorporated in the Urban Street Analysis Chapter of HCM.

Keywords: stationary bottleneck, traffic flow, pedestrian speed, HCM

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Authors: Alice Morenike Olagunju, Olufemi A. Fakolade, Abiodun Ezekiel Adesina, Olufemi Akinloye Bolaji, Oriyomi Rabiu

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The use of computer-assisted instruction(CAI) has been suggested as a way out of the problem of Colleges of Education (CoE) in Southwest, Nigeria persistent high failure rate in and negative attitude towards Agricultural Economics (AE).The impacts of this are yet unascertained on high-flyers. This study, therefore, determined the impacts of CAI onhigh-flyers pre-service teachers’ attitude towards AE concepts in Southwest, Nigeria. The study adopted pretest-posttest, control group, quasi-experimental design. Six CoE with e-library facilities were purposively selected. Fourty-nine 200 level Agricultural education students offering introduction to AE course across the six CoE were participants. The participants were assigned to two groups (CAI, 22 and control, 27). Treatment lasted eight weeks. The AE Attitude Scale(r=0.80), Instructional guides and Teacher Performance Assessment Sheets were used for data collection. Data were analysed using t-test. The participants were 62.8% male with mean age of 22 years. Treatment had significant effects on high-flyers pre-service teachers’ attitude (t = 17.44; df = 47, p < .5). Participants in CAI ( =71.03) had higher post attitude mean score compared to those in control ( = 64.92) groups. Gender had no significant effect on attitude (t= 3.06; df= 47, p > .5). The computer assisted instructional mode enhanced students’ attitude towards Agricultural Economics concepts. Therefore, CAI should be adopted for improved attitude towards agricultural economics concepts among high-flyers pre-service teachers.

Keywords: attitude towards agricultural economics concepts, colleges of education in southwest Nigeria, computer-assisted instruction, high-flyers pre-service teachers

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Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan

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In this paper we study that the catastrophic events arrive independently at the service facility according to a Poisson process with rate λ. The nature of a catastrophic event is that upon its arrival at a service station, it destroys all the customers there waiting and in the service. We will derive the net profit associated with queuing system and obtain its probability of the busy period.

Keywords: queueing system, net-profit, busy period, catastrophical events

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Authors: Zeinab Ranjbar

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Service-oriented architecture in the world today, it is proposed to exchange information and services of interest to those such as IT managers, business managers, designers and system builders scene. The basic architecture of the software used to provide service to all users.the worries of all people (managers, business managers, designers, and system builders scene) effectiveness of this model, how reliable it is in security transactions.To increase the reliability of multi-layer fuzzy logic Architectures used.

Keywords: SOA, service oriented architecture, fuzzy logic, multi layer, SOA security

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Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: Chutima Klaysung

Abstract:

This research aims to study the factors that influence the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand. The research method will use quantitative research; data were collected by questionnaires distributed to spa consumers, both female and male, aged between 20 years and 70 years in the Amphawa, Samut Songkhram area for 400 samples by convenience sampling method. The data were analyzed using descriptive statistics including percentage, mean, standard deviation and inferential statistics, including Pearson correlation for hypothesis testing. The results showed that the demographic variables including age, education, occupation, income and frequency of access to service spa were related to the decision to choose the spa service of consumers in Amphawa, Samut Songkhram. In addition, the researchers found the marketing mixed factors such as products, prices, places, promotion, personnel selling, physical evidence and processes were associated with the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand.

Keywords: consumer in amphawa, samut songkhram, decision to choose the spa service, marketing mixed factor, spa service

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

Abstract:

Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

Abstract:

The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature.

Keywords: job-shop scheduling, classification, constraints, objective functions

Procedia PDF Downloads 429