Search results for: air quality prediction

Authors: Bahaa Khalil, Taha B. M. J. Ouarda, André St-Hilaire

Abstract:

The world economic crises and budget constraints have caused authorities, especially those in developing countries, to rationalize water quality monitoring activities. Rationalization consists of reducing the number of monitoring sites, the number of samples, and/or the number of water quality variables measured. The reduction in water quality variables is usually based on correlation. If two variables exhibit high correlation, it is an indication that some of the information produced may be redundant. Consequently, one variable can be discontinued, and the other continues to be measured. Later, the ordinary least squares (OLS) regression technique is employed to reconstitute information about discontinued variable by using the continuously measured one as an explanatory variable. In this paper, two record extension techniques are employed to reconstitute information about discontinued water quality variables, the OLS and the Line of Organic Correlation (LOC). An empirical experiment is conducted using water quality records from the Nile Delta water quality monitoring network in Egypt. The record extension techniques are compared for their ability to predict different statistical parameters of the discontinued variables. Results show that the OLS is better at estimating individual water quality records. However, results indicate an underestimation of the variance in the extended records. The LOC technique is superior in preserving characteristics of the entire distribution and avoids underestimation of the variance. It is concluded from this study that the OLS can be used for the substitution of missing values, while LOC is preferable for inferring statements about the probability distribution.

Keywords: Record extension, record augmentation, monitoringnetworks, water quality indicators.

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Authors: Manirath Wongsim, Pawornprat Hongsakon

Abstract:

Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimisation of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: Information quality, information quality dimensions, accounting information systems, accounting Information system adoption.

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Authors: Kanyarat Bussaban, Siriporn Poolsuwan

Abstract:

This study is conducted with the objective to prove how the distorted distribution of welfare affects the quality of school-age children lives differently in the case ofan urban community in Bangkok. 334 samples are households from Suan Oi and Ratchapatubtim communities. The study of sample communities found the difference between two communityareasthatare close. The people of Suan Oi community are economically better off people than the people of the Ratchapatubtim community. They share the benefits of using most services except the welfare of a child’s education.The resulting analysis of the variability in quality of life of the school age children indicate that heads of the households are women looking for quality of life benefits when the compulsory school age is less.A study of the two communities suggests that the inequality in incomedistribution currently affects the quality of life of school-age children.

Keywords: Inequality, Income distribution, Quality of school-age children lives, Welfare state.

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Authors: Jingxian An, Wei Yu

Abstract:

The commercial value (retail price) of wine is mostly determined by the wine quality, ageing potential, and oak influence. This paper reveals that wine quality, ageing potential, and oak influence are favourably correlated, hence positively influencing the commercial value of Pinot noir wines. Oak influence is the most influential of these three sensory attributes on the price set by wine traders and estimated by experienced customers. In the meanwhile, this study gives winemakers with chemical instructions for raising total phenolics, which can improve wine quality, ageing potential, and oak influence, all of which can increase a wine’s economic worth.

Keywords: Retail price, ageing potential, wine quality, oak influence.

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Authors: Y. Y. Su, K. T. Win, H. C. Chiu

Abstract:

This study used Item Analysis, Exploratory Factor Analysis (EFA) and Reliability Analysis (Cronbach-s α value) to exam the Questions which selected by the Delphi method based on the issue of “Socio-technical system (STS)" and user-centered perspective. A structure questionnaire with seventy-four questions which could be categorized into nine dimensions (healthcare environment, organization behaviour, system quality, medical data quality, service quality, safety quality, user usage, user satisfaction, and organization net benefits) was provided to evaluate EMR of the Taiwanese healthcare environment.

Keywords: Instrument development, Reliability test, Validity test, Electronic Medical Record Evaluation.

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Authors: Qasim Kriri, Harsh B. Desai

Abstract:

Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: Acceptable quality level, statistical quality control, control charts, process charts.

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Authors: Nader Gharibnavaz, Mostafa Mosadeghi, Naser Gharibnavaz

Abstract:

In today's world where everything is rapidly changing and information technology is high in development, many features of culture, society, politic and economy has changed. The advent of information technology and electronic data transmission lead to easy communication and fields like e-learning and e-commerce, are accessible for everyone easily. One of these technologies is virtual training. The "quality" of such kind of education systems is critical. 131 questionnaires were prepared and distributed among university student in Toba University. So the research has followed factors that affect the quality of learning from the perspective of staff, students, professors and this type of university. It is concluded that the important factors in virtual training are the quality of professors, the quality of staff, and the quality of the university. These mentioned factors were the most prior factors in this education system and necessary for improving virtual training.

Keywords: Training , Virtual Training, Strategic Positioning, Positioning Mapping, Unique Selling Proposition, Strong Brands, Indoors industry

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Authors: Ribeiro I., Tavares A.M., Sá E., Lopes M.

Abstract:

The increased use of biodiesel implies variations on both greenhouse gases and air pollutant emissions. Some studies point out that the use of biodiesel blends on diesel can help in controlling air pollution and promote a reduction of CO2 emissions. Reductions on PM, SO2, VOC and CO emissions are also expected, however NOx emissions may increase, which may potentiate O3 formation. This work aims to assess the impact of the biodiesel use on air quality, through a numerical modeling study, taking the Northern region of Portugal as a case study. The emission scenarios are focused on 2008 (baseline year) and 2020 (target year of Renewable Energy Directive-RED) and on three biodiesel blends (B0, B10 and B20). In a general way the use of biodiesel by 2020 will reduce the CO2 and air pollutants emissions in the Northern Portugal, improving air quality. However it will be in a very small extension.

Keywords: air quality, biodiesel, emission scenarios, RED.

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Authors: M. Sivaiah, R. Parmar, S. K. Majumder

Abstract:

This article reports on hydrodynamic, mass transfer performances of fine bubble in a modified reactor. The quality of mixing in the modified reactor is discussed in the paper. Mass transfer efficiency based on quality of mixing is enunciated. To interpret the gas phase volume fraction and the quality of mixing is the empirical models for the modified system are developed.

Keywords: Downflow, bubble, hydrodynamics, gas-liquid, mixing, mass transfer, gas holdup

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Authors: Dayang Nailul Munna Abang Abdullah, Francine Rozario

Abstract:

The main objectives of this study were to identify attributes that influence customer satisfaction and determine their relationships with customer satisfaction. The variables included in this research are place/ambience, food quality and service quality as independent variables and customer satisfaction as the dependent variable. A survey questionnaire which consisted of three parts to measure demographic factors, independent variables, and dependent variables was constructed based on items determined by past research. 149 respondents from one of the well known hotel in Kuala Lumpur, MALAYSIA were selected as a sample. Psychometric testing was conducted to determine the reliability and validity of the questionnaire. From the findings, there were positive significant relationship between place/ambience (r=0.563**, p=0.000) and service quality (r=0.544**, p=0.000) with customer satisfaction. However, although relationship between food quality and customer satisfaction was significant, it was in the negative direction (r=- 0.268**, p=0.001). New findings were discovered after conducting this research and previous research findings were strengthened by the results of this research. Future researchers could concentrate on determining attributes that influence customer satisfaction when cost/price is not a factor and reasons for place/ambience is currently becoming the leading factor in determining customer satisfaction.

Keywords: Ambience, Customer Satisfaction, Food Quality, Service Quality.

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Authors: Agnieszka Misztal

Abstract:

The popularity of quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel, it is appropriate to focus attention on the selection of companies aspiring to a quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out a series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car) 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). The identified determinants were divided into two types of criteria: internal and external, as well as hard and soft. The article presents the hard – technical factors that an automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: Automotive industry, quality management system.

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Authors: Ng Yee Luon, Mohd Zamri Yusoff, Norshah Hafeez Shuaib

Abstract:

Meshing is the process of discretizing problem domain into many sub domains before the numerical calculation can be performed. One of the most popular meshes among many types of meshes is tetrahedral mesh, due to their flexibility to fit into almost any domain shape. In both 2D and 3D domains, triangular and tetrahedral meshes can be generated by using Delaunay triangulation. The quality of mesh is an important factor in performing any Computational Fluid Dynamics (CFD) simulations as the results is highly affected by the mesh quality. Many efforts had been done in order to improve the quality of the mesh. The paper describes a mesh generation routine which has been developed capable of generating high quality tetrahedral cells in arbitrary complex geometry. A few test cases in CFD problems are used for testing the mesh generator. The result of the mesh is compared with the one generated by a commercial software. The results show that no sliver exists for the meshes generated, and the overall quality is acceptable since the percentage of the bad tetrahedral is relatively small. The boundary recovery was also successfully done where all the missing faces are rebuilt.

Keywords: Mesh generation, tetrahedral, CFD, Delaunay.

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Authors: M. S. M. El-Bady

Abstract:

Water quality and heavy metals pollution of the Damietta Nile Branch at Damietta governorate were investigated in the current work. Fourteen different sampling points were selected along the Damietta Nile branch from Ras EL-Bar (sample 1) to Sheremsah (sample 14). Physical and chemical parameters and the concentrations of Cd, Cr, Cu, Ni, Fe, Al, Hg, Pb and Zn were investigated for water quality assessment of Damietta Nile Branch at Damietta Governorate. Most of the samples show that the water is suitable for drinking and irrigation purposes. All locations of samples near the sea are unsuitable water but the samples in the south direction away from the sea are suitable or good water for drinking and irrigation.

Keywords: Water quality indices, Damietta Governorate, Nile River, pollution.

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Authors: Karima Siham Aoubid, Mohamed Boulemden

Abstract:

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

Keywords: Compression, linear prediction analysis, multiresolution analysis, speech signal.

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

Abstract:

Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Yu-Chun Lin

Abstract:

We identify clawback triggers from firms- proxy statements (Form DEF 14A) and use the likelihood of restatements to proxy for financial reporting quality. Based on a sample of 578 U.S. firms that voluntarily adopt clawback provisions during 2003-2009, when restatement-based triggers could be decomposed into two types: fraud and unintentional error, and we do observe the evidence that using fraud triggers is associated with high financial reporting quality. The findings support that fraud triggers can enhance deterrent effect of clawback provision by establishing a viable disincentive against fraud, misconduct, and otherwise harmful acts. These results are robust to controlling for the compensation components, to different sample specifications and to a number of sensitivity.

Keywords: Accruals quality, Clawback provisions, Compensation, Restatements.

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Authors: M. Breška, I. Peruš, V. Stankovski

Abstract:

The number of Ground Motion Prediction Equations (GMPEs) used for predicting peak ground acceleration (PGA) and the number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Srinath Shetty K., Shivashankar R., Rashmi P. Shetty

Abstract:

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

Keywords: Bearing pressure, granular bed, radial basis function neural network, strip footing.

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Authors: K.Manimala, Dr.K.Selvi, R.Ahila

Abstract:

Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.

Keywords: back propagation network, power quality, probabilistic neural network, radial basis function support vector machine

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Authors: R. Leelaruji, V. Knazkins

Abstract:

This paper proposes a methodology for mitigating the occurrence of cascading failure in stressed power systems. The methodology is essentially based on predicting voltage instability in the power system using a voltage stability index and then devising a corrective action in order to increase the voltage stability margin. The paper starts with a brief description of the cascading failure mechanism which is probable root cause of severe blackouts. Then, the voltage instability indices are introduced in order to evaluate stability limit. The aim of the analysis is to assure that the coordination of protection, by adopting load shedding scheme, capable of enhancing performance of the system after the major location of instability is determined. Finally, the proposed method to generate instability prediction is introduced.

Keywords: Blackouts, cascading failure, voltage stability indices, singular value decomposition, load shedding.

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Authors: Itgel Bayarsaikhan, Jimin Lee, Sejong Oh

Abstract:

Classification is one of the primary themes in computational biology. The accuracy of classification strongly depends on quality of a dataset, and we need some method to evaluate this quality. In this paper, we propose a new graphical analysis method using 'Membership-Deviation Graph (MDG)' for analyzing quality of a dataset. MDG represents degree of membership and deviations for instances of a class in the dataset. The result of MDG analysis is used for understanding specific feature and for selecting best feature for classification.

Keywords: feature, classification, machine learning algorithm.

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean   Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.

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Authors: M. M. Mashhadi, K. Mohajeri, M. D. Nayeri

Abstract:

Positioning the organization in the strategic environment of its industry is one of the first and most important phases of the organizational strategic planning and in today knowledge-based economy has its importance been duplicated for higher education institutes as the centers of education, knowledge creation and knowledge worker training. Up to now, various models with diverse approaches have been applied to investigate organizations- strategic position in different industries. Regarding the essential importance and strategic role of quality in higher education institutes, in this study, a quality-oriented approach has been suggested to positioning them in their strategic environment. Then the European Foundation of Quality Management (EFQM) model has been adopted to position the top Iranian business schools in their strategic environment. The result of this study can be used in strategic planning of these institutes as well as the other Iranian business schools.

Keywords: Strategic planning, Strategic positioning, Quality, EFQM model, Higher education institutions.

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Authors: Manjie Li, Xiangju Cheng, Yongcan Chen

Abstract:

With rapid development of industrialization and urbanization, water environmental deterioration is widespread in majority of urban rivers, which seriously affects city image and life satisfaction of residents. As an emergency measure to improve water quality, clean water diversion is introduced for water environmental management. Lubao River and Southwest River, two urban rivers in typical plain tidal river network, are identified as technically and economically feasible for the application of clean water diversion. One-dimensional hydrodynamic-water quality model is developed to simulate temporal and spatial variations of water level and water quality, with satisfactory accuracy. The mathematical model after calibration is applied to investigate hydrodynamic and water quality variations in rivers as well as determine the optimum operation scheme of water diversion. Assessment system is developed for evaluation of positive and negative effects of water diversion, demonstrating the effectiveness of clean water diversion and the necessity of pollution reduction.

Keywords: Assessment system, clean water diversion, hydrodynamic-water quality model, tidal river network, urban rivers, water environment improvement.

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Authors: Germán Santos-Boada, Jordi Domingo-Pascual

Abstract:

Recently, in some places, optical-fibre access networks have been used with GPON technology belonging to organizations (in most cases public bodies) that act as neutral operators. These operators simultaneously provide network services to various telecommunications operators that offer integrated voice, data and television services. This situation creates new problems related to quality of service, since the interests of the users are intermingled with the interests of the operators. In this paper, we analyse this problem and consider solutions that make it possible to provide guaranteed quality of service for voice over IP, data services and interactive digital television.

Keywords: GPON networks, multioperator, quality of service, triple-play services.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, Pareto Optimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: P. Konvalina, I. Capouchová, Z. Stehno

Abstract:

The organic farmers use wider range of crop varieties than the conventional farming. Bread wheat is the most favorite and the most common food crop. The organic bread wheat is usually of worse technological quality. Therefore, it is supposed to be an attractive alternative to the hulled wheat species (einkorn, emmer wheat and spelt). Twenty-five hulled bread wheat varieties and control bread wheat ones were grown on the certified organic parcel in České Budějovice (the Czech Republic) between 2009 and 2012. Their baking quality was measured and evaluated with standard methods, and in accordance with ICC. The results have shown that the grain of hulled wheat varieties contain a lot of proteins in grains (up to 18 percent); even the organic hulled bread wheat varieties are characterized by such good baking quality. Einkorn and emmer wheat are of worse technological quality of proteins (low values of gluten index and Zeleny test), which is a disadvantage of these two wheat species. On the other hand, spelt wheat is of better technological quality and is similar to the control bread wheat varieties. Mixtures consisting of bread wheat, among others, are considered good alternatives; they may contribute to wider range of use of the hulled wheat species. It is one of the possibilities which may increase the proportion of proteins in bread wheat grains; the nutrition-rich hulled wheat grains may be also used in such way at the same time.

Keywords: Baking quality, organic farming, einkorn, emmer wheat, spelt.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, non-reference quality measures, objective quality measures.

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Authors: Bilal Alatas, Ahmet Arslan

Abstract:

The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

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