Search results for: air quality prediction

Authors: Vethathirri Ramanujam Srinivasan, S. M. Shiva Nagendra

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Air quality management in urban areas is a serious concern in both developed and developing countries. In this regard, more number of air quality monitoring stations are planned to mitigate air pollution in urban areas. In India, Central Pollution Control Board has set up 574 air quality monitoring stations across the country and proposed to set up another 500 stations in the next few years. The number of monitoring stations for each city has been decided based on population data. The setting up of ambient air quality monitoring stations and their operation and maintenance are highly expensive. Therefore, there is a need to optimize monitoring networks for air quality management. The present paper discusses the various methods such as Indian Standards (IS) method, US EPA method and European Union (EU) method to arrive at the minimum number of air quality monitoring stations. In addition, optimization of rain-gauge method and Inverse Distance Weighted (IDW) method using Geographical Information System (GIS) are also explored in the present work for the design of air quality network in Chennai city. In summary, additionally 18 stations are required for Chennai city, and the potential monitoring locations with their corresponding land use patterns are ranked and identified from the 1km x 1km sized grids.

Keywords: air quality monitoring network, inverse distance weighted method, population based method, spatial variation

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Authors: Samaneh Abolli, Mahdi Ahmadi Nasab, Kamyar Yaghmaeian, Mahmood Alimohammadi

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The quality of drinking water, in addition to the presence of physicochemical parameters, depends on the type and geographical location of water sources. In this study, groundwater quality was investigated by sampling total dissolved solids (TDS), electrical conductivity (EC), total hardness (TH), Cl, Ca²⁺, and Mg²⁺ parameters in 13 sites, and 40 water samples were sent to the laboratory. Electrometric, titration, and spectrophotometer methods were used. In the next step, the water quality index (WQI) was used to investigate the impact and weight of each parameter in the groundwater. The results showed that only the mean of magnesium ion (40.88 mg/l) was lower than the guidelines of World Health Organization (WHO). Interpreting the WQI based on the WHO guidelines showed that the statuses of 21, 11, and 7 samples were very poor, poor, and average quality, respectively, and one sample had excellent quality. Among the studied parameters, the means of EC (2,087.49 mS/cm) and Cl (1,015.87 mg/l) exceeded the global and national limits. Classifying water quality of TH was very hard (87.5%), hard (7.5%), and moderate (5%), respectively. Based on the geographical distribution, the drinking water index in sites 4 and 11 did not have acceptable quality. Chloride ion was identified as the responsible pollutant and the most important ion for raising the index. The outputs of statistical tests and Spearman correlation had significant and direct correlation (p < 0.05, r > 0.7) between TDS, EC, and chloride, EC and chloride, as well as TH, Ca²⁺, and Mg²⁺.

Keywords: water quality index, groundwater, chloride, GIS, Garmsar

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Authors: Fotis Vouzas

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This paper is an attempt to investigate the Business Ethics link to Quality Management. Business Ethics as a management practice is well rooted in many organizations, but its contribution to quality management implementation programs and practices is not well documented. The ISO 9000 and the Business Excellence frameworks and Awards seem to provide a basis for the implementation of a TQM philosophy contributing to efficiency, enhanced performance and sustainability. The author examines a series of Corporate Ethics initiatives and investigates the relationship to Total Quality Management in an MNC operating in Greece. The data gathering was carried out through extensive and in-depth interviews with several multiple informants, i.e., the plant manager, the production manager, and the personnel manager, using a semi-structured questionnaire with open-ended questions.

Keywords: total quality management, business ethics, Greece, ISO 9000

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Mehrzad Mohabbi Yadollahi, Ramazan Demirboğa, Majid Atashafrazeh

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Geopolymers are highly complex materials which involve many variables which makes modeling its properties very difficult. There is no systematic approach in mix design for Geopolymers. Since the amounts of silica modulus, Na2O content, w/b ratios and curing time have a great influence on the compressive strength an ANFIS (Adaptive neuro fuzzy inference system) method has been established for predicting compressive strength of ground pumice based Geopolymers and the possibilities of ANFIS for predicting the compressive strength has been studied. Consequently, ANFIS can be used for geopolymer compressive strength prediction with acceptable accuracy.

Keywords: geopolymer, ANFIS, compressive strength, mix design

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Authors: Alireza Shahraki, Kaveh Keshmiry Zadeh

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Total quality management in libraries is of particular importance because high-quality libraries can facilitate the sustained development process in countries. This study has been conducted to examine the feasibility of implementation of total quality management in libraries of Sistan and Baluchestan and to provide an appropriate model for this concern. All of the officials and employees of Sistan and Baluchestan libraries (23 individuals) constitute the population of the study. Data gathering tool is a questionnaire that is designated based on ISO9000. The data extracted from questionnaires were analyzed using SPSS software. Results indicate that the highest degree of conformance to the 8 principles of ISO9000 is attributed to the principle of 'users' (69.9%) and the lowest degree is associated with 'decision making based on facts' (39.1%). Moreover, a significant relationship was observed among the items (1 and 3), (2 and 5), (2 and 7), (3 and 5), (4 and 5), (4 and 7), (4 and 8), (5 and 7), and (7 and 8). According to the research findings, it can generally be said that it is not eligible now to utilize TQM in libraries of Sistan and Baluchestan.

Keywords: quality management, total quality, university libraries, libraries management

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Maha Mourad

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Higher education in any competitive European economy should serve the new information society by increasing the supply of good quality education services and by creating good international brands in the international higher education market. Hence, continuous risk management techniques through higher educational reforms programs became one of the top priorities within the European Union to control the quality of higher education. Risk is higher education is studies by several researchers who agreed that the risk in higher education has a direct influence on continuity of quality education and research contribution. The focus of this research is to highlights the Internal Quality Assurance (IQA) activities in the Polish higher education system as a risk management tool used to control the quality of education. This paper presents a qualitative empirical analysis in 5 different universities in Poland. In addition, it aims to help in finding global practical and create benchmark for policy makers concerning the risk management techniques based on the Polish experience.

Keywords: education development, quality assurance, sustainability, european higher education

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Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

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Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

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Authors: A. Boudiaf

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The purpose of this paper is to analyze and apprehend, through four case studies, the interest of the project of the implementation of the quality management system (QMS) at four Moroccan small and medium-sized enterprises (SMEs). This project could generate significant organizational change to improve the functioning of the organization. In fact, quality is becoming a necessity in the current business world. It is considered to be a major component in companies’ competitive strategies. It should be noted that quality management is characterized by a set of methods and techniques that can be used to solve malfunctions and reorganize companies. It is useful to point out that the choice of the adoption of the quality approach could be influenced by the circumstances of the business context, it could also be derived from its strategic vision; this means that this choice can be characterized as either a strategic aspect or a reactive aspect. This would probably have a major impact on the functioning of the QMS and also on the perception of the quality issue by company managers and their employees.

Keywords: business context, organizational change, quality, reorganization

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Authors: Laura Mion

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The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of QA (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: H. Bonakdari, I. Ebtehaj

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The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), bridge pier, scour depth, nonlinear regression (NLR)

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: Jiaojiao Zhang

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Boar sperm quality, as an important indicator of reproductive efficiency, directly affects the efficiency of livestock production. Here, this study was conducted to improve the boar sperm quality by using a non-thermal dielectric barrier discharge (DBD) plasma. Our results showed that DBD plasma exposure at 2.1 W for 15 s could improve boar sperm quality by increasing the exon methylation level of adenosine monophosphate-activated protein kinase (AMPK) and thus improving the glycolytic flux, mitochondrial function, and antioxidant capacity without damaging the integrity of sperm DNA and acrosome. In addition, DBD plasma could rescue DNA methyltransferase inhibitor decitabine-caused low sperm quality by reducing oxidative stress and mitochondrial damage. Therefore, the application of non-thermal plasma provides a new strategy for reducing sperm oxidative damage and improving sperm quality, which shows great potential in assisted reproduction to solve the problem of male infertility.

Keywords: non-thermal DBD plasma, sperm quality, AMPK methylation, energy metabolism, antioxidant capacity

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Authors: Liubov Lutsyshyn, Yaroslava Zhukova

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Over the past twenty years, there has been a drastic change in the mode of nutrition in many countries which has been reflected in the development of new products, production techniques, and has also led to the expansion of sales markets for food products. Studies have shown that solution of the food safety problems is almost impossible without the active and systematic activity of organizations directly involved in the production, storage and sale of food products, as well as without management of end-to-end traceability and exchange of information. The aim of this research is development of the integrated system of the quality management and safety assurance based on the principles of HACCP, traceability and system approach with creation of an algorithm for the identification and monitoring of parameters of technological process of manufacture of cooked sausage products. Methodology of implementation of the integrated system based on the principles of HACCP, traceability and system approach during the manufacturing of cooked sausage products for effective provision for the defined properties of the finished product has been developed. As a result of the research evaluation technique and criteria of performance of the implementation and operation of the system of the quality management and safety assurance based on the principles of HACCP have been developed and substantiated. In the paper regularities of influence of the application of HACCP principles, traceability and system approach on parameters of quality and safety of the finished product have been revealed. In the study regularities in identification of critical control points have been determined. The algorithm of functioning of the integrated system of the quality management and safety assurance has also been described and key requirements for the development of software allowing the prediction of properties of finished product, as well as the timely correction of the technological process and traceability of manufacturing flows have been defined. Based on the obtained results typical scheme of the integrated system of the quality management and safety assurance based on HACCP principles with the elements of end-to-end traceability and system approach for manufacture of cooked sausage products has been developed. As a result of the studies quantitative criteria for evaluation of performance of the system of the quality management and safety assurance have been developed. A set of guidance documents for the implementation and evaluation of the integrated system based on the HACCP principles in meat processing plants have also been developed. On the basis of the research the effectiveness of application of continuous monitoring of the manufacturing process during the control on the identified critical control points have been revealed. The optimal number of critical control points in relation to the manufacture of cooked sausage products has been substantiated. The main results of the research have been appraised during 2013-2014 under the conditions of seven enterprises of the meat processing industry and have been implemented at JSC «Kyiv meat processing plant».

Keywords: cooked sausage products, HACCP, quality management, safety assurance

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Ahmed Najah Ahmed Al-Mahfoodh, Ali Najah Ahmed Al-Mahfoodh, Ahmed Al-Shafie

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In this study, genetic programming (GP) technique has been investigated in prediction of set of rainfall-runoff data. To assess the effect of input parameters on the model, the sensitivity analysis was adopted. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Correlation Coefficient (CC), Mean Square Error (MSE) and Correlation of Efficiency (CE). The principle aim of this study is to develop a computationally efficient and robust approach for predict of rainfall-runoff which could reduce the cost and labour for measuring these parameters. This research concentrates on the Johor River in Johor State, Malaysia.

Keywords: genetic programming, prediction, rainfall-runoff, Malaysia

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Ben Clapperton, Daniel Stahl, Kimberley Goldsmith, Trudie Chalder

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Chronic fatigue syndrome (CFS) is a condition characterised by chronic disabling fatigue and other symptoms that currently can't be explained by any underlying medical condition. Although clinical trials support the effectiveness of cognitive behaviour therapy (CBT), the success rate for individual patients is modest. Patients vary in their response and little is known which factors predict or moderate treatment outcomes. The aim of the project is to develop a prediction model from baseline characteristics of patients, such as demographics, clinical and psychological variables, which may predict likely treatment outcome and provide guidance for clinical decision making and help clinicians to recommend the best treatment. The project is aimed at identifying subgroups of patients with similar baseline characteristics that are predictive of treatment effects using modern cluster analyses and data mining machine learning algorithms. The characteristics of these groups will then be used to inform the types of individuals who benefit from a specific treatment. In addition, results will provide a better understanding of for whom the treatment works. The suitability of different clustering methods to identify subgroups and their response to different treatments of CFS patients is compared.

Keywords: chronic fatigue syndrome, latent class analysis, prediction modelling, self-organizing maps

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Authors: Luca Zarrilli, Miguel Brito, Marianna Cappucci

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Tourists recently awarded Lisbon as the best city break destination in Europe. This article analyses the various types of tourist experiences in the city of Lisbon. The research method is the questionnaire, aimed at investigating the choices of tourists in the area of mobility, their perception of the quality of life and their level of appreciation of neighbourhoods, landmarks and infrastructures. There is an obvious link between the quality of life and the quality of the tourist experience, but it is difficult to measure it. Through this questionnaire, we hope to have made a small contribution to the understanding of the perceptive sphere of the individual and his choices in terms of behaviour, which is an essential element of any strategy for tourism marketing.

Keywords: Lisbon, mobility, quality of life, perception, tourism, hospitality

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Authors: Irene Doosuur Mngutyo

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The preliminary stages in the development of human communities are the formation of a correct understanding of people’s needs. However, perception of human needs is highly subjective and difficult to aggregate. Quality of life measurements are an appropriate means for achieving an understanding of Human needs. Hence this study endeavors to measure quality of life in Makurdi using subjective indices to measure three aspects of subjective wellbeing. A sample of 400 respondents achieved by applying the Taro Yamane formula to Makurdi’s projected population. Questionnaires were randomly distributed to residents of nine wards in Makurdi. Findings from a pilot study( N=100) demonstrated that among the 2 aspects of overall quality of life investigated,22% had a mean low overall assessment of quality of life now being3on the scale and an even poorer assessment for projected quality in the next five years by 17%(3)although an equal percentage are hopeful for a better life(10)in the next five years.60% of the respondents record very rare positive feelings while only 10% have positive feelings always on the eudaimonic scale69%strongly agree that they have a purposeful and meaningful life. Findings indicate good social ties as a strong indicator for perceived good feelings and even though quality of life is perceived as low there is optimism for the future.

Keywords: quality of life, subjective indicators, development, urban planning

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Authors: Tarik Bazgour, Cedric Heuchenne, Danielle Sougne

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We examine time variation in the market beta of portfolios sorted on quality, liquidity level and liquidity beta characteristics across stock market phases. Using US stock market data for the period 1970-2010, we find, first, the US stock market was driven by four regimes. Second, during the crisis regime, low (high) quality, high (low) liquidity beta and illiquid (liquid) stocks exhibit an increase (a decrease) in their market betas. This finding is consistent with the flight-to-quality and liquidity phenomena. Third, we document the same pattern across stocks when the market volatility is low. We argue that, during low volatility times, investors shift their portfolios towards low quality and illiquid stocks to seek portfolio gains. The pattern observed in the tranquil regime can be, therefore, explained by a flight-to-low-quality and to illiquidity. Finally, our results reveal that liquidity level is more important than liquidity beta during the crisis regime.

Keywords: financial crises, quality, liquidity, liquidity risk, regime-switching models

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Authors: Zhenzhong Yang

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Herbal medicines are important supplements to chemical drugs and usually consist of a complex mixture of constituents. The current quality control strategy of herbal medicines is mainly based on chemical markers, which largely failed to owe to the markers, not reflecting the herbal medicines’ multiple mechanisms of action. Herein, a bioactive chemical markers based strategy was proposed and applied to the quality assessment and control of herbal medicines. This strategy mainly includes the comprehensive chemical characterization of herbal medicines, bioactive chemical markers identification, and related quantitative analysis methods development. As a proof-of-concept, this strategy was applied to a Panax notoginseng derived herbal medicine. The bioactive chemical markers based strategy offers a rational approach for quality assessment and control of herbal medicines.

Keywords: bioactive chemical markers, herbal medicines, quality assessment, quality control

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Authors: Brahim Fares Zaidi

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech based on the Hidden Models of Markov and the Hidden Markov Model Toolkit to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients and Perceptual Linear Prediction and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: ARSDS, HTK, HMM, MFCC, PLP

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Zuriati Ismail, Naomie Salim

Abstract:

Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly.

Keywords: content quality, forum search, thread retrieval, voting techniques

Procedia PDF Downloads 213

Authors: Mochammad Indra Permana, Andhiani Sharfina Arnellya, Dika Pramita Destiani, Budhi Prihartanto

Abstract:

Cardiovascular disease is the cause of the highest mortality rates in the world. The number of cardiovascular disease patients is increasing every year. Data obtained from World Health Organization (WHO) that 17,5 million people died from this disease. The condition of cardiovascular diseases such as atrial fibrillation, myocardial infarction, venous thromboembolism, and several other conditions need anticoagulant therapy. Results of the anticoagulant therapy are measured not only by the effectiveness of International Normalized Ratio (INR) value but also by the quality of life of the patients. The purpose of this study was to determine the quality of life of patients on oral anticoagulant therapy in outpatient cardiac department Dr. Hasan Sadikin central general hospital, Bandung, Indonesia. This is a cross-sectional study with collecting data from the quality of life questionnaire and medical record of the patients. The results of this study showed that 28 patients (46,7%) had a good quality of life, 30 patients (50%) had a moderate quality of life, and 2 patients (3,3%) had a poor quality of life with no significant differences in quality of life based on age, gender, diagnosis, and duration of drug use.

Keywords: anticoagulant, cardiovascular diseases, INR, quality of life

Procedia PDF Downloads 314

Authors: Mohammad Matin

Abstract:

Nowadays, one of the basic problems of higher education is a significant decline in the quality of education and reduction in efficiency of training. These research and studies are aiming to assess affecting factors of the erosion of academic quality, including educational environmental and content, social and economic factors, elements of the training, elements of education, family factors, from the perspective of students. The result of such improper competition, totally, has led to the decline of education quality in higher education centers, and in many aspects. The results showed a significant difference between male and female students' perspective for two areas of social and economic factors.

Keywords: higher education, decline, the quality of education, student

Procedia PDF Downloads 341

Authors: Jay L. Fu

Abstract:

Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 143