Search results for: classification quality

Authors: Ya-Chuan Tseng, Hsin-Yi Liu, Meei-Fang Lou, Guey-Shiun Huang

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Purpose: Sensory impairments are common in older adults. Hearing and visual impairments affect their physical and mental health and quality of life (QOL) adversely. However, systematic reviews of the relationship between hearing impairment, visual impairment, dual sensory impairment and quality of life are scarce. The purpose of this systematic review was to determine the relationship between hearing impairment, visual impairment, dual sensory impairment and quality of life. Methods: Searches of EMBASE, PubMed, CINAHL, MEDLINE, Cochrane Library and Airiti Library were conducted between January 2006 and December 2017 using the keywords ‘quality of life,’ ‘life satisfaction,’ ‘well-being,’ ‘hearing impairment’ and ‘visual impairment’ Two authors independently assessed methodologic quality using a modified Downs and Black tool. Data were extracted by the first author and then cross-checked by the second author. Results: Twenty-three studies consisting mostly of community-dwelling older adults were included in our review. Sensory impairment was found to be in significant association with quality of life, with an increase in hearing impairment or visual impairment severity resulting in a lower quality of life. Quality of life for dual sensory impairment was worse than for hearing impairment or visual impairment individually. Conclusions: A significant association was confirmed between hearing impairment, visual impairment, dual sensory impairment and quality of life. Our review can be used to enhance health care personnel’s understanding of sensory impairment in older adults and enable healthcare personnel to actively assess older adults’ sensory functions so that they can help alleviate the negative impact of sensory impairments on QOL in older adults.

Keywords: nursing, older adults, quality of life, systematic review, hearing impairment, visual impairment

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Jayoung Cho

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Poverty has become a social problem in South Korea, given that seven out of ten elderly experience multidimensional poverty. As quality of life is a major social welfare measure of a society, verifying the major factors affecting the quality of life among the elderly in poverty can be used as baseline data for the promotion of welfare. This study aims to investigate the longitudinal relationships between food insecurity and quality of life among the elderly in poverty. In this study, panel regression analysis using 5-year longitudinal panel data were derived from Korea Welfare Panel Study (KWPS, 2011-2015) were used to identify the research question. A total of 1,327 elderly people aged 65 or older with less than 60% of median income was analyzed. The main results of the study are as follows; first, the level of quality of life of the poor elderly was on average of 5, and repeated the increase and decrease over time. Second, food insecurity and quality of life of the elderly in poverty had a longitudinal causal relationship. Furthermore, the statistical significance of food insecurity was the highest despite controlling for major variables affecting the quality of life among the poor elderly. Therefore, political and practical approaches are strongly suggested and considered regarding the food insecurity for the quality of life among the elderly in poverty. In practical intervention, it is necessary to pay attention to food insecurity when assessing the poor elderly. Also, there is a need to build a new delivery system that incorporates segmented health and nutrition-related services. This study has an academic significance in that it brought out the issue of food insecurity of the poor elderly and confirmed the longitudinal relationship between food insecurity and quality of life.

Keywords: food insecurity, longitudinal panel analysis, poor elderly, quality of life

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Authors: Rouighi Mustapha, Bouzid Laghaa Souad, Rouighi Tahar

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Due to rain Shortage and the increase of population in the last years, wells excavation and groundwater use for different purposes had been increased without any planning. This is a great challenge for our country. Moreover, this scarcity of water resources in this region is unfortunately combined with rapid fresh water resources quality deterioration, due to salinity and contamination processes. Therefore, it is necessary to conduct the studies about groundwater quality in Algeria. In this work consists in the identification of the factors which influence the water quality parameters in Laghouat region by using statistical analysis Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and geographic information system (GIS) in an attempt to discriminate the sources of the variation of water quality variations. The results of PCA technique indicate that variables responsible for water quality composition are mainly related to soluble salts variables; natural processes and the nature of the rock which modifies significantly the water chemistry. Inferred from the positive correlation between K+ and NO3-, NO3- is believed to be human induced rather than naturally originated. In this study, the multivariate statistical analysis and GIS allows the hydrogeologist to have supplementary tools in the characterization and evaluating of aquifers.

Keywords: cluster, analysis, GIS, groundwater, laghouat, quality

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: M. S. V. K. V. Prasad, G. Siva Praveena, P. V. V. Prasada Rao

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It is known that the groundwater quality is very important parameter because it is the main factor determining its suitability for drinking, agricultural and industrial purposes. Water Quality Index (WQI) has been calculated for ground water samples taken from Narsapur-Mogalthur mandals, West Godavari district, Andhra Pradesh, India, from 10 different locations in the pre-monsoon season as well as post monsoon. The water samples were analyzed for pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Total Hardness (TH), major cations like calcium, magnesium, sodium, potassium and anions like chloride, nitrate and sulphate in the laboratory using the standard methods given by the American Public Health Association (APHA). The overall quality of water in the study area is somewhat good for all constituents. Drinking water at almost all the locations was found to be slightly contaminated, except a few locations during the year 2014. It was found that some effective measures are urgently required for water quality management in this region.

Keywords: Water Quality Index, Physico-chemical parameters, Quality rating, monsoon

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Authors: Rahman Mofidi, Sina Rahimi, Farnoosh Darban

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Communication plays a key role in today’s world, and to support it, the quality of service has the highest priority. It is very important to differentiate between traffic based on priority level. Some traffic classes should be a higher priority than other classes. It is also necessary to give high priority to customers who have more payment for better service, however, without influence on other customers. So to realize that, we will require effective quality of service methods. To ensure the optimal performance of the network in accordance with the quality of service is an important goal for all operators in the mobile network. In this work, we propose an algorithm based on control parameters which it’s based on user feedback that aims at minimizing the access to system transmit power and thus improving the network key performance indicators and increasing the quality of service. This feedback that is known as channel quality indicator (CQI) indicates the received signal level of the user. We aim at proposing an algorithm in control parameter criterion to study improving the quality of service and throughput in a cellular network at the simulated environment. In this work we tried to parameter values have close to their actual level. Simulation results show that the proposed algorithm improves the system throughput and thus satisfies users' throughput and improves service to set up a successful call.

Keywords: quality of service, key performance indicators, control parameter, channel quality indicator

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Authors: A. Ali, V. Strezov, P. Davies, I. Wright, T. Kan

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The environmental impacts arising from mining activities affect the air, water, and soil quality. Impacts may result in unexpected and adverse environmental outcomes. This study reports on the impact of coal production on sediment in Sydney region of Australia. The sediment samples upstream and downstream from the discharge points from three mines were taken, and 80 parameters were tested. The results were assessed against sediment quality based on presence of metals. The study revealed the increment of metal content in the sediment downstream of the reference locations. In many cases, the sediment was above the Australia and New Zealand Environment Conservation Council and international sediment quality guidelines value (SQGV). The major outliers to the guidelines were nickel (Ni) and zinc (Zn).

Keywords: coal mine, environmental impact, produced water, sediment quality guidelines value (SQGV)

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Authors: Ibrahim Abdel Gadir Malik, Dafalla Siddig Dafalla, Osama Abdelgadir El-Bushra

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Geological and engineering characteristics of intact rock and the discontinuity surfaces was used to describe and classify rock mass into zones based on mechanical and physical properties. Many conditions terms that affect the rock mas; such as Rock strength, Rock Quality Designation (RQD) value, joint spacing, and condition of joint, water condition with block size, joint roughness, separation, joint hardness, friction angle and weathering were used to classify the rock mass into: Good quality (class II) (RMR values range between 75% and 56%), Good to fair quality (class II to III) (RMR values range between 70% and 55%), Fair quality (class III) (RMR values range between 60% and 50%) and Fair to poor quality (Class III to IV) (RMR values, range between (50% and 35%).

Keywords: rock strength, RQD, joints, weathering

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Yulmaida Amir, Fahrul Rozi, Insany C. Kamil, Fanny Aryani

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ODAPUS (Orang dengan Lupus) is an Indonesian term for people with Lupus, a chronic autoimmune disease in which immune system of the body becomes hyperactive and attacks normal tissue. The number of ODAPUS indicate an increase in Indonesia, thereby helping to improve their quality of life to be important to help their recovery. This study aims to examine the effect of resilience, self-esteem, and social support on the quality of life of women who had been diagnosed as having Lupus. Data were collected from 64 ODAPUS in Indonesia, using the World Health Organization Quality of Life (WHOQOL), Resilience Scale from Wagnil and Young (1993), self-esteem scale (developed from Coopersmith’s theory), and Social Support Questioner from Northouse (1988). Regression data analysis showed that resilience, social support, and self-esteem predict the quality of life of the ODAPUS simultaneously. If the variable was analysed individually, self-esteem did not significantly contribute to the quality of life. Resilience contributed most significantly to the quality of life, followed by social support. Of five sources of social supports included in the research, support from family members (parents and brother/sisters) has the most significant contribution to the quality of life, followed by support from spouse, and from friends. Interestingly, social support from medical personnel (medical doctors and nurses) had not a significant contribution to the quality of life of ODAPUS. As a conclusion, this research showed that the ability of ODAPUS to cope with difficulty in life, and support from family members, spouse, and friends were the significant predictors for their quality of life.

Keywords: quality of life, resilience, self-esteem, social supports

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Authors: Rodrigo Guimarães Santos

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The quality of public transport services has been considered as a critical factor by their users and also by users of individual transport. Thus, this dissertation aims to adapt a model that assesses the quality of public transport and determines its level of service based on the views of its users. The methodology is widely used by marketers and allows measuring the quality of services by assessing the perceptions and expectations of users. The adapted SERVQUAL was tested with users of public transport service users and car in Brasília-DF, city of Brazil. This research involved 241 questionnaires answered by people living in the various administrative regions of Brasília-DF. The analysis of the determinants pointed out that the quality of the public transport service offered in the city is low and users of public transport and cars have a high degree of expectations for improvement in all tested determinants. This method enabled the identification of the most critical determinants and those needing strategic actions for continuous improvement of quality. Adapting the SERVQUAL for a public transport service was satisfactory and demonstrated applicability to internal and external services, including measuring the public transport services in other cities with the opinion of the users.

Keywords: transportation services, quality services, servqual scale and marketing services

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Authors: Aklilu Alemu, Tak Cheung Chan

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Following the intensification of secondary education in the developing world, the attention of Ethiopia has currently shifted to its quality education and its management. This study is aimed to explore experts’ perceptions of quality management challenges in secondary education in Ethiopia. The researchers employed a case study design recruiting participating supervisors from the Ministry of Education, region, zone, wereda, and cluster by using a purposeful sampling technique. Twenty-six interviewees took part in this study. The researchers employed NVivo 8 versions together with a thematic analysis process to analyze the data. This study revealed that major problems that affected quality management practices in Ethiopia were: lack of qualified experts at all levels; lack of accountability in every echelon; the changing nature of teacher education; the ineffectiveness of teacher-licensing programs; and lack of educational budget and the problem of utilizing this limited budget. The study concluded that the experts at different levels were not genuinely fulfilling their roles and responsibilities. Therefore, the Ministry of Finance and Economic Development, together with the concerned parties, needs to reconsider budget allocation for secondary education.

Keywords: education quality, Ethiopia, quality challenge, quality management, secondary education

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Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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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: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Olu Ale, Olugbenga Aribisala, Sanmi Awopetu

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Groundwater (Wells) is obtained from several well-defined and different water-bearing geological layers or strata. The physical, chemical and bacteriological quality of the water contributed from each of these water-bearing formations and resultant effects of indiscriminate wastes disposal will be dependent on the dissolution of material within the formation. Therefore, water withdrawn from any ground water source will be a composite of these individual aquifers. The water quality was determined by actual sampling and analysis of the completed wells. This study attempted to examine the physicochemical and bacteriological water quality of twenty five selected wells comprising twenty boreholes (deep wells) and five hand dug wells (shallow wells). The twenty five wells cut across the entire Ado Ekiti Metropolitan area. The water samples collected using standard method was promptly taken to water laboratory at the Federal Polytechnic Ado-Ekiti for analysis, physical, chemical and bacteriological tests were carried out. Quality characteristics tested were found to meet WHO’s standard and generally acceptable, making it potable for drinking in most situations, thus encouraging the use of groundwater. Possible improvement strategies to groundwater exploitation were highlighted while remedies to poor quality water were suggested.

Keywords: bacteriological, physicochemical, quality, wells, Ado Ekiti

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Authors: Zainab Khalifah, Wong Chiet Bing, Noor Hazarina Hashim

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The evolution of customer behavior in purchasing products or services through the Internet leads to airline companies engaging in the e-ticketing process in order to maintain their business. A well-designed website is vitally significant for the airline companies to provide effective communication, support, and competitive advantage. This study was conducted to identify the dimensions of website quality for low cost airline and to investigate the relationship between the website quality and customer e-satisfaction at low cost airline. A total of 381 responses were conveniently collected among local passengers at Low Cost Carrier Terminal, Kuala Lumpur via questionnaire distribution. This study found that the five determinant factors of website quality for AirAsia were Information Content, Navigation, Responsiveness, Personalization, and Security and Privacy. The results of this study revealed that there is a positive relationship between the five dimensions of website quality and customer e-satisfaction, and also information content was the most significant contributor to customer e-satisfaction.

Keywords: website quality, customer e-satisfaction, low cost airline, e-ticketing

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Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

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Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

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Authors: Mehrnoosh Askarizadeh

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People, process and IT are the most important assets of any organization. Optimal utilization of these resources has been the question of research in business for many decades. The business world have responded by inventing various methodologies that can be used for addressing problems of quality improvement, efficiency of processes, continuous improvement, reduction of waste, automation, strategy alignments etc. Some of these methodologies can be commonly called as Business Process Quality Management methodologies (BPQM). In essence, the first references to the process management can be traced back to Frederick Taylor and scientific management. Time and motion study was addressed to improvement of manufacturing process efficiency. The ideas of scientific management were in use for quite a long period until more advanced quality management techniques were developed in Japan and USA. One of the first prominent methods had been Total Quality Management (TQM) which evolved during 1980’s. About the same time, Six Sigma (SS) originated at Motorola as a separate method. SS spread and evolved; and later joined with ideas of Lean manufacturing to form Lean Six Sigma. In 1990’s due to emerging IT technologies, beginning of globalization, and strengthening of competition, companies recognized the need for better process and quality management. Business Process Management (BPM) emerged as a novel methodology that has taken all this into account and helped to align IT technologies with business processes and quality management. In this article we will study various aspects of above mentioned methods and identified their relations.

Keywords: e-process, quality, TQM, BPM, lean, six sigma, CPI, information technology, management

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Marlon B. Espedillon

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This qualitative study examines practice teaching as an important component of teacher education and its entanglement with the teacher quality discourse. How the key actors -student teachers, supervising instructors, cooperating teachers, and school principals- construe teacher quality is essential in understanding how the student teachers articulate their voices and challenge the cultural myths in teacher education. The ethnographic method of research was used to provide an ecological picture of field experiences. Three cultural myths were uncovered based on the thematic analysis of the interview transcripts, observations, and documents.

Keywords: teacher quality, practice teaching, student teacher agency, cultural myths

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Authors: S. Boulenouar, A. Boukli Hacene, S. Brahmi

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Quality is an old concept but which recently became omnipresent in the society. It is a pledge of the well done job and therefore the satisfaction of the customer. Now, dispensing pharmacies seem to be held away from this approach. Officinal staff is called to dispense drugs. However this essential function is rarely studied and taken into account. To contribute to the good use of medicines and to reduce the dangers, it is important to consider the dispensation of drugs practised in the pharmacies. It is a both descriptive and retrospective study .The descriptive part is to conduct a survey near to the dispensary pharmacists. The retrospective section concentrates on the analysis of medicine prescriptions dispensed to patients. Following the survey that we carried out near the pharmacists of dispensary of the town of Oran, it appears that in majority, they are not inclined, by themselves, to take up the challenge of quality at the dispensary. The approach requires time and a motivation that pharmacists do not have for the moment. Efforts are still needed on the part of pharmacists, but also of authorities and organizations in charge of quality in the dispensary. At the end of this work, it seems to us that the implementation of a quality approach is part of our reflection on the added value of the pharmacist of dispensary in the drug chain.

Keywords: customer satisfaction, dispensary, dispensing of the drug, quality approach

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Authors: Wanida Suwunniponth

Abstract:

The purpose of this research was to study the factors of characteristic of business, website quality and trust affected intention to use electronic payment systems for online purchasing. This survey research used questionnaire as a tool to collect the data of 300 customers who purchased online products and used an electronic payment system. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that customers had a good opinion towards the characteristic of the business and website quality. However, they have a moderate opinion towards trust and intention to repurchase. In addition, the characteristics of the business affected the purchase intention the most, followed by website quality and the trust with statistical significance at 0.05 level. For particular, the terms of reputation, communication, information quality, perceived risk and word of mouth affected the intention to use the electronic payment system. In contrast, the terms of size, system quality and service quality did not affect intention to use an electronic payment system.

Keywords: electronic payment, intention, online purchasing, trust

Procedia PDF Downloads 222

Authors: Subhadeep Mandal, Sujoy Bhattacharya, Pabitra Mitra, Diya Guha Roy, Seema Bhattacharya

Abstract:

E-commerce firms allow customers to evaluate and review the things they buy as a positive or bad experience. The e-commerce transaction processes are made up of a variety of diverse organizations and activities that operate independently but are connected together to complete the transaction (from placing an order to the goods reaching the client). After a negative shopping experience, clients frequently disregard the critical assessment of these businesses and submit their feedback on an all-over basis, which benefits certain enterprises but is tedious for others. In this article, we solely dealt with negative reviews and attempted to distinguish between negative reviews where the e-commerce firm is explicitly blamed by customers for a bad purchasing experience and other negative reviews.

Keywords: e-commerce, online shopping, customer reviews, customer behaviour, text analytics, n-grams classification

Procedia PDF Downloads 238

Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

Abstract:

This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry 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 labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an 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). 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 following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w 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 a 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” and are feasible as complementing methods to the computer vision system.

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

Procedia PDF Downloads 218

Authors: Wim Zeiler

Abstract:

The indoor quality of occupied space is very important for the well-being of its occupants, especially in the case of babies. The lungs of a young child are still growing and adverse conditions could affect this development. Presently little children spend a lot of their time in day care centers while parents are at work. Little is known about the effects of different indoor environmental factors present in these day care centers and the quality of air of baby cots in which the babies are accommodated in these day care centers. Therefore this research investigated the quality of the accommodation of Dutch day care centers. Besides an extensive literature research actual measurements were performed in baby cots within three-day care center. Some experiments were performed to find out the importance of the configuration and types of baby cots. This research investigated the quality of the accommodation of a Dutch day care center which led to a tool describing the quality needs (e.g., quality standard) for the accommodation of day care centers. The results of our detailed studies were compared with the results of earlier Dutch more global studies in day care centers, in which more than 60 day care centers were investigated. Also the results are compared with the outcomes of research on school ventilation. The results proved that the situation in day care centers is even worse than that of schools within the Netherlands. More attention is needed to improve the current situation.

Keywords: ventilation, baby cots, day care centers, case study

Procedia PDF Downloads 454