Search results for: water quality classification

Authors: Noor A. Draman, Campbell Wilson, Sea Ling

Abstract:

Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.

Keywords: Bio-inspired audio content-based retrieval framework, features selection technique, low/high level features, artificial immune system

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Authors: Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis

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In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.

Keywords: Facial expression analysis, Feature extraction, Image processing, Pattern Recognition, Application.

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Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spreadsheet developers competency over a network. It is designed to automatically and autonomously monitor spreadsheet users and gather their development activities based on the utilization of the software multi-agent technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spreadsheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: Classification, Design, MACS, MAS, Prometheus.

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Authors: Ahmad T. Al-Taani, Noor Aldeen K. Al-Awad

Abstract:

In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

Keywords: Text classification, HTML documents, Web pages, Machine learning, Fuzzy logic, Arabic Web pages.

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Authors: M. Sarai Atab, A. Smallbone, A. P. Roskilly

Abstract:

A thermodynamic study is performed on the Reverse Osmosis (RO) desalination process for brackish water. The detailed RO model of thermodynamics properties with and without an energy recovery device was built in Simulink/MATLAB and validated against reported measurement data. The efficiency of desalination plants can be estimated by both the first and second laws of thermodynamics. While the first law focuses on the quantity of energy, the second law analysis (i.e. exergy analysis) introduces quality. This paper used the Main Outfall Drain in Iraq as a case study to conduct energy and exergy analysis of RO process. The result shows that it is feasible to use energy recovery method for reverse osmosis with salinity less than 15000 ppm as the exergy efficiency increases twice. Moreover, this analysis shows that the highest exergy destruction occurs in the rejected water and lowest occurs in the permeate flow rate accounting 37% for 4.3% respectively.

Keywords: Brackish water, exergy, irrigation, reverse osmosis.

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Authors: N. S. Imamverdiyev

Abstract:

The transition to renewable energy sources has become a critical component of global efforts to mitigate climate change and promote sustainable development. However, the deployment of renewable energy technologies can also have significant impacts on ecosystems and the services they provide, such as carbon sequestration, soil fertility, water quality, and biodiversity. These technologies also highlight the potential co-benefits of renewable energy deployment for ecosystem services, such as reducing greenhouse gas emissions and improving air and water quality. Renewable energy sources, such as wind, solar, hydro, and biomass, are increasingly being used to meet the world's energy needs due to their environmentally friendly nature and the desire to reduce greenhouse gas emissions. However, the expansion of renewable energy infrastructure can also impact ecosystem services, which are the benefits that humans derive from nature, such as clean water, air, and food. This geographic assessment aims to evaluate the relationship between renewable energy infrastructure and ecosystem services. Potential solutions such as the use of ecological benefit measures, biodiversity-friendly design of renewable energy infrastructure, and stakeholder participation in decision-making processes are being investigated to determine the positive effects of renewable energy infrastructure on ecosystem services.

Keywords: Renewable energy, solar energy, climate change, energy production.

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Authors: Y. Q. Lv, C.K.M. Lee

Abstract:

This paper develops a quality estimation method with the application of fuzzy hierarchical clustering. Quality estimation is essential to quality control and quality improvement as a precise estimation can promote a right decision-making in order to help better quality control. Normally the quality of finished products in manufacturing system can be differentiated by quality standards. In the real life situation, the collected data may be vague which is not easy to be classified and they are usually represented in term of fuzzy number. To estimate the quality of product presented by fuzzy number is not easy. In this research, the trapezoidal fuzzy numbers are collected in manufacturing process and classify the collected data into different clusters so as to get the estimation. Since normal hierarchical clustering methods can only be applied for real numbers, fuzzy hierarchical clustering is selected to handle this problem based on quality standards.

Keywords: Quality Estimation, Fuzzy Quality Mean, Fuzzy Hierarchical Clustering, Fuzzy Number, Manufacturing system

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Authors: T. K N. Hoang, P. A. Tuan, R. Finsy, L. Deriemaeker

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The pigments covered by film-forming polymers have opened a prospect to improve the quality of water-based printing inks. In this study such pigments were prepared by the initiated polymerization of styrene and methacrylate derivative monomers in the aqueous pigment dispersions. The formation of polymer films covering pigment cores depends on the polymerization time and the ratio of pigment to monomers. At the time of 4 hours and the ratio of 1/10 almost pigment particles are coated by the polymer. The formed polymer covers of pigments have the average thickness of 5.95 nm. The size increasing percentage of the coated particles after a week is 4.5 %, about fourteen-fold lower than of the original ones. The obtained results indicate that the coated pigments are improved dispersion stability in water medium along with a guarantee for the optical colour.

Keywords: Aqueous pigment dispersion stability, colored resin particles, emulsion polymerization, water based ink.

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Authors: M. Guillard, M. Philippe, F. Laurent, J. Martinerie, J. P. Lachaux, G. Florence

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One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.

Keywords: Classification, EEG Synchrony, alpha, resting situation.

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: Ahmad T. Al-Taani, Noor Aldeen K. Al-Awad

Abstract:

In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

Keywords: Text classification, HTML, web pages, machine learning, fuzzy logic, Arabic web pages.

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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Authors: Vadivel Ayyasamy

Abstract:

The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: Emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation.

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

Abstract:

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

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

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Authors: Reza Gharehkhani

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Sedimentation in reservoirs lowers the quality of consumed water, reduce the volume of reservoir, lowers the controllable amount of flood, increases the risk of water overflow during possible floods and the risk of reversal and reduction of dam's useful life. So in all stages of dam establishment such as cognitive studies, phase-1 studies of design, control, construction and maintenance, the problem of sedimentation in reservoir should be considered. What engineers need to do is examine and develop the methods to keep effective capacity of a reservoir, however engineers should also consider the influences of the methods on the flood disaster, functions of water use facilities and environmental issues.This article first examines the sedimentation in reservoirs and shows how to control it and then discusses the studies about the sedimens in Siazakh Dam.

Keywords: Sedimentation, Reservoir, Sediment Control, Dam

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Authors: Shuki Dror

Abstract:

This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

Keywords: HOQ, organizational features, service quality.

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Authors: Asem M. Othman

Abstract:

The expansion of the hospitality industry is distinctive in the 21st century. Services, by nature, are intangible. Hence, service quality, in general, is a complicated process to be measured and evaluated. Hotels, as a service sector and part of the hospitality industry, are growing rapidly. This research paper was carried out to identify the quality determinants that may affect hotel guests’ service quality perception. In this research paper, each quality determinant will be discussed, illustrated, and justified thoroughly via a systematic literature review. This paper sets the stage to measure the significant influence of the service quality determinants on guest satisfaction. The knowledge contribution from this study proposes to practitioners and/or hotel service providers, fundamental elements to adopt the implications into their policies.

Keywords: Hotel service, service quality, quality determinants, quality management.

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Authors: A. Montazar

Abstract:

The great challenge of the agricultural sector is to produce more crop from less water, which can be achieved by increasing crop water productivity. The modernization of the irrigation systems offers a number of possibilities to expand the economic productivity of water and improve the virtual water status. The objective of the present study is to assess the global water productivity (GWP) within the major irrigation command areas of I.R. Iran. For this purpose, fourteen irrigation command areas where located in different areas of Iran were selected. In order to calculate the global water productivity of irrigation command areas, all data on the delivered water to cropping pattern, cultivated area, crops water requirement, and yield production rate during 2002-2006 were gathered. In each of the command areas it seems that the cultivated crops have a higher amount of virtual water and thus can be replaced by crops with less virtual water. This is merely suggested due to crop water consumption and at the time of replacing crops, economic value as well as cultural and political factors must be considered. The results indicated that the lowest GWP belongs to Mahyar and Borkhar irrigation areas, 0.24 kg m-3, and the highest is that of the Dez irrigation area, 0.81 kg m-3. The findings demonstrated that water management in the two irrigation areas is just efficient. The difference in the GWP of irrigation areas is due to variations in the cropping pattern, amount of crop productions, in addition to the effective factors in the water use efficiency in the irrigation areas.

Keywords: Iran, Irrigation command area, Water productivity, Virtual water.

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Authors: S. El Safty, A. El-Zonkoly

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The ability to detect and classify the type of fault plays a great role in the protection of power system. This procedure is required to be precise with no time consumption. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle. The simulation of power system is carried out using PSCAD/EMTDC. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropy of such decompositions is analyzed reaching a successful methodology for fault classification. The suggested approach is tested using different fault types and proven successful identification for the type of fault.

Keywords: Fault classification, wavelet transform, waveletentropy.

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Authors: N. Kannan, Sabu Joseph

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Groundwater is an essential and vital component of our life support system. The groundwater resources are being utilized for drinking, irrigation and industrial purposes. There is growing concern on deterioration of groundwater quality due to geogenic and anthropogenic activities. Groundwater, being a fragile must be carefully managed to maintain its purity within standard limits. So, quality assessment and management are to be carried out hand-in-hand to have a pollution free environment and for a sustainable use. In order to assess the quality for consumption by human beings and for use in agriculture, the groundwater from the shallow aquifers (dug well) in the Palakkad and Chittur taluks of Bharathapuzha river basin - a paddy dominated agricultural basin (order=8th; L= 209 Km; Area = 6186 Km2), Kerala, India, has been selected. The water samples (n= 120) collected for various seasons, viz., monsoon-MON (August, 2005), postmonsoon-POM (December, 2005) and premonsoon-PRM (April, 2006), were analyzed for important physico-chemical attributes. Spatial and temporal variation of attributes do exist in the study area, and based on major cations and anions, different hydrochemical facies have been identified. Using Gibbs'diagram, rock dominance has been identified as the mechanism controlling groundwater chemistry. Further, the suitability of water for irrigation was determined by analyzing salinity hazard indicated by sodium adsorption ratio (SAR), residual sodium carbonate (RSC) and sodium percent (%Na). Finally, stress zones in the study area were delineated using Arc GIS spatial analysis and various management options were recommended to restore the ecosystem.

Keywords: Groundwater quality, agricultural basin, Kerala, India.

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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

Keywords: Cancer classification, feature selection, deep learning, genetic algorithm.

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Authors: Jehad Al Dallal

Abstract:

Software engineers apply different measures to quantify the quality of software design. These measures consider artifacts developed at low or high level software design phases. The results are used to point to design weaknesses and to indicate design points that have to be restructured. Understanding the relationship among the quality measures and among the design quality aspects considered by these measures is important to interpreting the impact of a measure for a quality aspect on other potentially related aspects. In addition, exploring the relationship between quality measures helps to explain the impact of different quality measures on external quality aspects, such as reliability and maintainability. In this paper, we report a replication study that empirically explores the correlation between six well known and commonly applied design quality measures. These measures consider several quality aspects, including complexity, cohesion, coupling, and inheritance. The results indicate that inheritance measures are weakly correlated to other measures, whereas complexity, coupling, and cohesion measures are mostly strongly correlated.  

Keywords: Quality attribute, quality measure, software design quality, spearman correlation.

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Authors: Majid Abdolrazzagh-Nezhad, Salwani Abdullah

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

Keywords: Job-shop scheduling, classification, constraints, objective functions.

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Authors: B. R. Faleye, M. I. Titocan, M. P. Ibitola

Abstract:

Investigation was carried out at Opic Estate in Isheri-Osun River Basin environment using Electrical Resistivity method to study saltwater intrusion into a fresh water aquifer system from the proximal estuarine water body. The investigation is aimed at aquifer characterisation using electrical resistivity method in order to provide the depth to which fresh water fit for both domestic and industrial consumption. The 2D Electrical Resistivity and Vertical Electrical Resistivity techniques alongside Laboratory analysis of water samples obtained from the boreholes were adopted. Three traverses were investigated using Wenner and Pole-Dipole array with multi-electrode system consisting of 84 electrodes and a spread of 581 m, 664 m and 830 m were attained on the traverses. The main lithologies represented in the study area are Sand, Clay and Clayey Sand of which Sand constitutes the aquifer in the study area. Vertical Electrical Sounding data obtained at different lateral distance on the traverses have indicated that the water in the aquifer in the subsurface is brackish. Brackish water is represented by lowelectrical resistivity value signature while fresh water is characterized by relatively high electrical resistivity and in some regionfresh water is existent at depth greater than 200 m. Results of laboratory analysis of samples showed that the pH, Salinity, Total Dissolved Solid and Conductivity indicated existence of water with poor quality, indicating that salinity, TDS and Conductivity is higher in the Northern part of the study area. The 2D electrical resistivity and Vertical Electrical Sounding methods indicate that fresh water region is at ≥200m depth. Aquifers not fit for domestic use in the study area occur downwards to about 200 m in depth. In conclusion, it is recommended that wells should be sunkbeyond 220 m for the possible procurement of portable fresh water.

Keywords: 2D electrical resistivity, aquifer, brackish water, lithologies, freshwater, opic estate.

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Authors: M. A. Lotfollahi Yaghin, R. Rezaei

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Demanding structural safety under various loading conditions, has focused attention on their variation and structural elements behavior due to these variations. Jacket structures are designed for a specific water level (LAT). One of the important issues about these kinds of structures is the water level rise. For example, the level of water in the Caspian Sea has risen by 2.5m in the last fifteen years and is continuing to rise. In this paper, the structural behavior of one typical shallow or medium water jacket platform (a four-leg steel jacket platform in 55m water depth) under water level rise has been studied. The time history of Von Mises stress and nodal displacement has chosen for evaluating structural behavior. The results show that dependent on previous water depth and structural elements position; different structural elements have different behavior due to water level rise.

Keywords: Jacket offshore platform, Time- history, Von Mises, Water level rise, Utilization Ratio.

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Authors: K. Arunachalam, P. Mannar Jawahar

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Presently, engine cooling pump is driven by toothed belt. Therefore, the pump speed is dependent on engine speed which varies their output. At normal engine operating conditions (Higher RPM and low load, Higher RPM and high load), mechanical water pumps in existing engines are inevitably oversized and so the use of an electric water pump together with state-of-the-art thermal management of the combustion engine has measurable advantages. Demand-driven cooling, particularly in the cold-start phase, saves fuel (approx 3 percent) and leads to a corresponding reduction in emissions. The lack of dependence on a mechanical drive also results in considerable flexibility in component packaging within the engine compartment. This paper describes the testing and comparison of existing mechanical water pump with that of the electric water pump. When the existing mechanical water pump is replaced with the new electric water pump the percentage gain in system efficiency is also discussed.

Keywords: Cooling system, Electric water pump, Mechanical water pump.

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Authors: P. Visutsak

Abstract:

The study of the interaction between humans and computers has been emerging during the last few years. This interaction will be more powerful if computers are able to perceive and respond to human nonverbal communication such as emotions. In this study, we present the image-based approach to emotion classification through lower facial expression. We employ a set of feature points in the lower face image according to the particular face model used and consider their motion across each emotive expression of images. The vector of displacements of all feature points input to the Adaptive Support Vector Machines (A-SVMs) classifier that classify it into seven basic emotions scheme, namely neutral, angry, disgust, fear, happy, sad and surprise. The system was tested on the Japanese Female Facial Expression (JAFFE) dataset of frontal view facial expressions [7]. Our experiments on emotion classification through lower facial expressions demonstrate the robustness of Adaptive SVM classifier and verify the high efficiency of our approach.

Keywords: emotion classification, facial expression, adaptive support vector machines, facial expression classifier.

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Authors: Bing Song, Kexi Han, Xuewei Lv

Abstract:

Titania slag is a high quality raw material containing titanium in the subsequent process of titanium pigment. The effects of cooling approaches of granulating, water cooling, and air cooling on chemical, phases, and acidolysis of Panzhihua titania slag were investigated. Compared to the original slag which was prepared by the conventional processing route, the results show that the titania slag undergoes oxidation of Ti³⁺during different cooling ways. The Ti₂O₃ content is 17.50% in the original slag, but it is 16.55% and 16.84% in water cooled and air-cooled slag, respectively. Especially, the Ti₂O₃ content in granulated slag is decreased about 27.6%. The content of Fe₂O₃ in granulated slag is approximately 2.86% also obviously higher than water (<0.5%) or air-cooled slag (<0.5%). Rutile in cooled titania slag was formed because of the oxidation of Ti³⁺. The rutile phase without a noticeable change in water cooled and air-cooled slag after the titania slag was cooled, but increased significantly in the granulated slag. The rate of sulfuric acid acidolysis of cooled slag is less than the original slag. The rate of acidolysis is 90.61% and 92.46% to the water-cooled slag and air-cooled slag, respectively. However, the rate of acidolysis of the granulated slag is less than that of industry slag about 20%, only 74.72%.

Keywords: Cooling approaches, titania slag, granulating, sulfuric acid acidolysis,

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Authors: Bharatendra Rai

Abstract:

Sequences of words in text data have long-term dependencies and are known to suffer from vanishing gradient problem when developing deep learning models. Although recurrent networks such as long short-term memory networks help overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine advantages of long short-term memory networks and convolutional neural networks, can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting of a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning. 

Keywords: Convolutional recurrent networks, hyperparameter tuning, long short-term memory networks, Tukey honest significant differences

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Authors: Denisa Ferenčíková, Petr Briš

Abstract:

Customer audits are generally used to ensure customer that supplier is continuously able to meet his requirements while supplying him required products and services. However, customer audits can be considered as a very useful quality control tool for suppliers as well. In our paper, we analyzed the process of customer audits realized in Czech companies from both perspectives: a supplier´s viewpoint and customer´s viewpoint. At the end, we tried to emphasize some areas that should not be omitted during the audit process.

Keywords: Customer Audit, Quality Control, Quality Management, Product Quality, Service Quality, Process Quality.

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