Search results for: demand selection

Authors: Ambra Giovannelli, Erika Maria Archilei

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The electrical power consumption related to refrigeration systems is evaluated to be in the order of 15% of the total electricity consumption worldwide. For this reason, in the last years several energy saving techniques have been suggested to reduce the power demand of refrigeration and air conditioning plants. The research work deals with the development of an innovative internal power recovery system for industrial cryogenic cooling plants. Such system is based on a Compressor-Expander Group (CEG). Both the expander and the compressor have been designed starting from automotive turbocharging components, strongly modified to take refrigerant fluid properties and specific system requirements into consideration. A preliminary choice of the machines (radial compressors and expanders) among existing components available on the market was realised according to the rules of the similarity theory. Once the expander was selected, it was strongly modified and performance verified by means of steady-state 3D CFD simulations. This paper focuses the attention on the development of the second CEG main component: the compressor. Once the preliminary selection has been done, the compressor geometry has been modified to take the new boundary conditions into account. In particular, the impeller has been machined to address the required total enthalpy increase. Such evaluation has been carried out by means of a simplified 1D model. Moreover, a vaneless diffuser has been added, modifying the shape of casing rear and front disks. To verify the performance of the modified compressor geometry and suggest improvements, a numerical fluid dynamic model has been set up and the commercial Ansys-CFX software has been used to perform steady-state 3D simulations. In this work, all the numerical results will be shown, highlighting critical aspects and suggesting further developments to increase compressor performance and flexibility.

Keywords: vapour compression systems, energy saving, refrigeration plant, organic fluids, centrifugal compressor

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Authors: Akiko Kondo, Akio Kondo

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We are facing regional problems to low birth rate and longevity in Japan. Under this situation, there are some local municipalities which lose their vitality. The aims of this study are to clarify the present state of local public transportation services in local municipalities and relation between local public transportation services and population quantitatively. We conducted a questionnaire survey concerning regional agenda in all local municipalities in Japan. We obtained responses concerning the present state of convenience in use of public transportation and local public transportation services. Based on the data gathered from the survey, it is apparent that we should some sort of measures concerning public transportation services. Convenience in use of public transportation becomes an object of public concern in many rural regions. It is also clarified that some local municipalities introduce a demand bus for the purpose of promotion of administrative and financial efficiency. They also introduce a demand taxi in order to secure transportation to weak people in transportation and eliminate of blank area related to public transportation services. In addition, we construct a population model which includes explanatory variables of present states of local public transportation services. From this result, we can clarify the relation between public transportation services and population quantitatively.

Keywords: public transportation, local municipality, regional analysis, regional issue

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Authors: Lenshie, Nsemba Edward

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This paper examines political sexuality as an identity construct, which imparts on democratic practices globally. The manifestation of political sexuality reflect on the dynamics of social, economic, cultural and political relations among different gender affecting a number of issues, such as the questions of citizenship, poverty alleviation, property rights, ownership and inheritance, rights to sexual consent, polygamous marriage, governance and representation among other issues. This paper is concerned with the aspect of political participation among different genders in Nigeria. This paper posit that political sexuality is an outcome of ‘sexuality differences’, which seeks to glorify and gratify the superiority of a particular sexuality over another. Political sexuality, therefore, motivate and exacerbate socio-cultural, economic, and political struggles among different sexualities. The paper asserts further that majority of women have been discriminated, sexually harassed, and are often denied certain rights and privileges in Nigeria. A few number of women who have found themselves at the corridors of government have used the Beijing protocol on Women to demand for ‘affirmative action’ to expand their political space. It contends that the ‘affirmative action’ in Nigeria is far from achieving it throughout the country. The paper conclude that women require more than just a ‘self-rediscovery’ to assertively demand for a more and proper inclusion in Nigeria’s democratic process.

Keywords: gender democracy, identity, politics, political sexuality

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Authors: Shohreh Azizi, Wag Nel

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The rapid population growth in South Africa has increased the requirement of waste water treatment facilities. The aim of this study is to assess the potential use of Fluidized bed Bio Reactor for Mmabatho sewage treatment plant. The samples were collected from the Inlet and Outlet of reactor daily to analysis the pH, Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solid (TSS) as per standard method APHA 2005. The studies were undertaken on a continue laboratory scale, and analytical data was collected before and after treatment. The reduction of 87.22 % COD, 89.80 BOD % was achieved. Fluidized Bed Bio Reactor remove Bod/COD removal as well as nutrient removal. The efforts also made to study the impact of the biological system if the domestic wastewater gets contaminated with any industrial contamination and the result shows that the biological system can tolerate high Total dissolved solids up to 6000 mg/L as well as high heavy metal concentration up to 4 mg/L. The data obtained through the experimental research are demonstrated that the FBBR may be used (<3 h total Hydraulic Retention Time) for secondary treatment in Mmabatho wastewater treatment plant.

Keywords: fluidized bed bioreactor, wastewater treatment plant, biological system, high TDS, heavy metal

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Authors: Swapna Begum, Higano Yoshiro

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Dhaka is the capital city of Bangladesh. It is considered as one of the traffic congested cities in the world. The growth of the population of this city is increasing day by day. The land use pattern and the increased socio-economic characteristics increase the motor vehicle ownership of this city. The rapid unplanned urbanization and poor transportation planning have deteriorated the transport environment of this city. Also, the huge travel demand with non-motorized traffics on streets is accounted for enormous traffic congestion in this city. The land transport sector in Dhaka is mainly dependent on road transport comprised of both motorized and non-motorized modes of travel. This improper modal mix and the un-integrated system have resulted in huge traffic congestion in this city. Moreover, this city has no well-organized public transport system and any Mass Transit System to cope with this ever increasing demand. Traffic congestion causes serious air pollution and adverse impact on the economy by deteriorating the accessibility, level of service, safety, comfort and operational efficiency. Therefore, there is an imperative need to introduce a well-organized, properly scheduled mass transit system like (Bus Rapid Transit) BRT minimizing the existing problems.

Keywords: air pollution, BRT, mass transit, traffic congestion

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Kevin Molina, Daniel Ortega, Manuel Martinez, Andres Gonzalez-Estrada, William Pinto

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Due to the increasing environmental impact, the wind energy is getting strong. This research studied the relationship between the power produced by a horizontal axis wind turbine (HAWT) and the aerodynamic profiles used for its construction. The analysis is studied using the Computational Fluid Dynamic (CFD), presenting the parallel between the energy generated by a turbine designed with selected profiles and another one optimized. For the study, a selection process was carried out from profile NACA 6 digits recommended by the National Renewable Energy Laboratory (NREL) for the construction of this type of turbines. The selection was taken into account different characteristics of the wind (speed and density) and the profiles (aerodynamic coefficients Cl and Cd to different Reynolds and incidence angles). From the selected profiles, was carried out a sensitivity analysis optimization process between its geometry and the aerodynamic forces that are induced on it. The 3D model of the turbines was realized using the Blade Element Momentum method (BEM) and both profiles. The flow fields on the turbines were simulated, obtaining the forces induced on the blade, the torques produced and an increase of 3% in power due to the optimized profiles. Therefore, the results show that the sensitivity analysis optimization process can assist to increment the wind turbine power.

Keywords: blade element momentum, blade, fluid structure interaction, horizontal axis wind turbine, profile design

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Authors: Ahmed Mahmoud Ahmed Abouelmagd

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The diversity is the usual remedy of the transmitted signal level variations (Fading phenomena) in radio frequency channels. Diversity techniques utilize two or more copies of a signal and combine those signals to combat fading. The basic concept of diversity is to transmit the signal via several independent diversity branches to get independent signal replicas via time – frequency - space - and polarization diversity domains. Coding and decoding processes can be an alternative remedy for fading phenomena, it cannot increase the channel capacity, but it can improve the error performance. In this paper we propose the use of replication decoding with BCH code class, and Viterbi decoding algorithm with convolution coding; as examples of coding and decoding processes. The results are compared to those obtained from two optimized selection space diversity techniques. The performance of Rayleigh fading channel, as the model considered for radio frequency channels, is evaluated for each case. The evaluation results show that the coding and decoding approaches, especially the BCH coding approach with replication decoding scheme, give better performance compared to that of selection space diversity optimization approaches. Also, an approach for combining the coding and decoding diversity as well as the space diversity is considered, the main disadvantage of this approach is its complexity but it yields good performance results.

Keywords: Rayleigh fading, diversity, BCH codes, Replication decoding, ‎convolution coding, viterbi decoding, space diversity

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Authors: Hugo Badia

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This research answers which is the most suitable transit network structure to serve specific demand requirements in an increasing urban dispersion process. Two main approaches of network design are found in the literature. On the one hand, a traditional answer, widespread in our cities, that develops a high number of lines to connect most of origin-destination pairs by direct trips; an approach based on the idea that users averse to transfers. On the other hand, some authors advocate an alternative design characterized by simple networks where transfer is essential to complete most of trips. To answer which of them is the best option, we use a two-step methodology. First, by means of an analytical model, three basic network structures are compared: a radial scheme, starting point for the other two structures, a direct trip-based network, and a transfer-based one, which represent the two alternative transit network designs. The model optimizes the network configuration with regard to the total cost for each structure. For a scenario of dispersion, the best alternative is the structure with the minimum cost. This dispersion degree is defined in a simple way considering that only a central area attracts all trips. If this area is small, we have a high concentrated mobility pattern; if this area is too large, the city is highly decentralized. In this first step, we can determine the area of applicability for each structure in function to that urban dispersion degree. The analytical results show that a radial structure is suitable when the demand is so centralized, however, when this demand starts to scatter, new transit lines should be implemented to avoid transfers. If the urban dispersion advances, the introduction of more lines is no longer a good alternative, in this case, the best solution is a change of structure, from direct trips to a network based on transfers. The area of applicability of each network strategy is not constant, it depends on the characteristics of demand, city and transport technology. In the second step, we translate analytical results to a real case study by the relationship between the parameters of dispersion of the model and direct measures of dispersion in a real city. Two dimensions of the urban sprawl process are considered: concentration, defined by Gini coefficient, and centralization by area based centralization index. Once it is estimated the real dispersion degree, we are able to identify in which area of applicability the city is located. In summary, from a strategic point of view, we can obtain with this methodology which is the best network design approach for a city, comparing the theoretical results with the real dispersion degree.

Keywords: analytical network design model, network structure, public transport, urban dispersion

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Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

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Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Zarema Urustamova, Chunsheng Shi, Ghulam Mujtaba Kayani 

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This research paper helps to understand the comparative analysis of recruitment problems which majorly faced by HRD of Public/Semi-Govt. and private sectors of Russia. The natures of different recruitment problems faced by HRD are different in both sector of Russia. Recruitment is one of very critical and important decision taken by HR department and some recruitment problems are highly faced by HR department of public/semi Govt. sector but are not major problems for private sector. Moreover, some problems are majorly influence in private sector but are not major problems in public/semi-govt. sector of Russia in recruitment. It is also identified that some recruitment problems are majorly affect in recruitment in both sectors. This paper helps to understand the recruitment problems faced by HR department while recruiting the new employee in both sectors. This paper also identified that “environment” and “prejudice” in public sector have higher affect and considered as a major problems in employee recruitment and “reference”, “selection standards” are considered as a least affecting problems of recruitment in public sector. Further, in private sector, “prejudice” and “culture” are major issues and “selection standards” and “reference” is considered as least affecting recruitment problems in private sector of Russia. So, HR department will be able to hire right person on right time, and it is possible when different HR departments focus to overcome these recruitment problems more efficiently and effectively.

Keywords: Govt. /Semi-Govt. vs. private sector, HR department, recruitment problems, Russia

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Authors: Sarbjit Singh, Amit Kumar Lal

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In India there is no governing body to control advertisement apart from ASCI due to which most of the companies are targeting children in their advertisements that have a negative impact on their behaviour. The main purpose of this research paper is to find out the impact of the television advertisement on the behaviour of the children as observed and reported by parents. The exploratory research design is adopted by using in-depth interviews with 20 parents in various cities of Punjab on the basis semi-structured interviews a self-administered structured Questionnaire was developed for data collection. Exploratory factor analysis using varimax rotation is used to analyse the data from 100 parents from the conjoint cities of Punjab. (Jalandhar, Amritsar and Ludhiana) The finding suggests that children demand those products which are more advertised. Parents believe that television advertisements are affecting the study of their children. Moreover, the children are becoming more violent, stubborn and rebellious. They try to start copying from the advertisements and indulge in bad habits. Children demand, nag and pester their parents to purchase the advertised product. This research paper would help advertisers to understand children behaviour towards advertisements and more over what should be done to control the negative impact of advertisement on children. Advertisers can also understand the parental perception towards advertisement.

Keywords: advertisement, consumer behaviour, children perception, teen marketing

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Authors: Ángel de J. López-Pérez, Sonia E. Ruiz, Vanessa A. Segovia

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Buildings vulnerability due to seismic activity has been highly studied since the middle of last century. As a solution to the structural and non-structural damage caused by intense ground motions, several seismic energy dissipating devices, such as buckling-restrained braces (BRB), have been proposed. BRB have shown to be effective in concentrating a large portion of the energy transmitted to the structure by the seismic ground motion. A design approach for buildings with BRB elements, which is based on a seismic Displacement-Based formulation, has recently been proposed by the coauthors in this paper. It is a practical and easy design method which simplifies the work of structural engineers. The method is used here for the design of the structure-BRB damper system. The objective of the present study is to extend and apply a methodology to find the best combination of design parameters on multiple-degree-of-freedom (MDOF) structural frame – BRB systems, taking into account simultaneously: 1) initial costs and 2) an adequate engineering demand parameter. The design parameters considered here are: the stiffness ratio (α = K_frame/K_total), and the strength ratio (γ = V_damper/V_total); where K represents structural stiffness and V structural strength; and the subscripts "frame", "damper" and "total" represent: the structure without dampers, the BRB dampers and the total frame-damper system, respectively. The selection of the best combination of design parameters α and γ is based on an initial costs analysis and on the structural dynamic response of the structural frame-damper system. The methodology is applied to a 12-story 5-bay steel building with BRB, which is located on the intermediate soil of Mexico City. It is found the best combination of design parameters α and γ for the building with BRB under study.

Keywords: best combination of design parameters, BRB, buildings with energy dissipating devices, buckling-restrained braces, initial costs

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Authors: Ahmad Afif, Teuku Yuri M. Zagloel

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Sustainable supply chain management is a new pattern that has emerged recently in industry and companies. The procurement process is one of the key factors for efficiency in supply chain management practices. Partnership is one of the procurement strategies for strategic items. The success factors of the partnership must be determined to avoid things that endanger the financial and operational status of the company. The current supplier partnership research focuses on the selection of general criteria and sustainable supplier selection. Currently, there is still limited research on the success factors of supplier partnerships that focus on strategic items in the coal mining industry. Meanwhile, the procurement of coal mining has its own characteristics, and there are regulations related to the procurement of goods. Therefore, this research was conducted to determine the categories of goods that are included in the strategic items and to design the success factors of supplier partnerships. The main factors studied are general, financial, production, reputation, synergies, and sustainable. The research was conducted using the Kraljic method to determine the categories of goods that are included in the strategic items. To design a supplier partnership success factor using the Hybrid Multi Criteria Decision Making method. Integrated Fuzzy AHP-Fuzzy TOPSIS is used to determine the weight of the success factors of supplier partnerships and to rank suppliers on the factors used.

Keywords: supplier, partnership, strategic item, success factors, and coal mining industry

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Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Vinh Duy Cao, Carlos Salas-Bringas, Anna M. Szczotok, Marianne Hiorth, Anna-Lena Kjøniksen

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The increasing cost of energy supply for the purposes of heating and cooling creates a demand for more energy efficient buildings. Improved construction techniques and enhanced material technology can greatly reduce the energy consumption needed for the buildings. Microencapsulated phase change materials (MPCM) suspensions utilized as heat transfer fluids for energy storage and heat transfer applications provide promising potential solutions. A full understanding of the flow and thermal characteristics of microcapsule suspensions is needed to optimize the design of energy storage systems, in order to reduce the capital cost, system size, and energy consumption. The MPCM suspensions exhibited pseudoplastic and thixotropic behaviour, and significantly improved the thermal performance of the suspensions. Three different models were used to characterize the thixotropic behaviour of the MPCM suspensions: the second-order structural, kinetic model was found to give a better fit to the experimental data than the Weltman and Figoni-Shoemaker models. For all samples, the initial shear stress increased, and the breakdown rate accelerated significantly with increasing concentration. The thermal performance and rheological properties, especially the selection of rheological models, will be useful for developing the applications of microcapsules as heat transfer fluids in thermal energy storage system such as calculation of an optimum MPCM concentration, pumping power requirement, and specific power consumption. The effect of temperature on the shear thinning properties of the samples suggests that some of the phase change material is located outside the capsules, and contributes to agglomeration of the samples.

Keywords: latent heat, microencapsulated phase change materials, pseudoplastic, suspension, thixotropic behaviour

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Authors: Habib Alshuwaikhat, Nahid Hossain

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Residential sector consumes more than half of the produced electricity in Saudi Arabia, and fossil fuel is the main source of energy to meet growing household electricity demand in the Kingdom. Several studies forecasted and expressed concern that unless the domestic energy demand growth is controlled, it will reduce Saudi Arabia’s crude oil export capacity within a decade and the Kingdom is likely to be incapable of exporting crude oil within next three decades. Though the Saudi government has initiated to address the domestic energy demand growth issue, the demand side energy management policies and programs are focused on industrial and commercial sectors. It is apparent that there is an urgent need to develop a comprehensive energy efficiency strategy for addressing efficient energy use in residential sector in the Kingdom. Then again as Saudi Arabia is at its primary stage in addressing energy efficiency issues in its residential sector, there is a scope for the Kingdom to learn from global energy efficiency practices and design its own energy efficiency policies and programs. However, in order to do that sustainable, it is essential to address local contexts of energy efficiency. It is also necessary to find out the policies and programs that will fit to the local contexts. Thus the objective of this study was set to identify globally best practice energy efficiency policies and programs in residential sector that have replication potential in Saudi Arabia. In this regard two sets of multi-criteria decision analysis matrices were developed to evaluate the energy efficiency policies and programs. The first matrix was used to evaluate the global energy efficiency policies and programs, and the second matrix was used to evaluate the replication potential of global best practice energy efficiency policies and programs for Saudi Arabia. Wuppertal Institute’s guidelines for energy efficiency policy evaluation were used to develop the matrices, and the different attributes of the matrices were set through available literature review. The study reveals that the best practice energy efficiency policies and programs with good replication potential for Saudi Arabia are those which have multiple components to address energy efficiency and are diversified in their characteristics. The study also indicates the more diversified components are included in a policy and program, the more replication potential it has for the Kingdom. This finding is consistent with other studies, where it is observed that in order to be successful in energy efficiency practices, it is required to introduce multiple policy components in a cluster rather than concentrate on a single policy measure. The developed multi-criteria decision analysis matrices for energy efficiency policy and program evaluation could be utilized to assess the replication potential of other globally best practice energy efficiency policies and programs for the residential sector of the Kingdom. In addition it has potential to guide Saudi policy makers to adopt and formulate its own energy efficiency policies and programs for Saudi Arabia.

Keywords: Saudi Arabia, residential sector, energy efficiency, policy evaluation

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Authors: Rowland R. Ogunrinde, Yusmadi Y. Jusoh, Noraini Che Pa, Wan Nurhayati W. Rahman, Azizol B. Abdullah

Abstract:

Enterprise Applications (EAs) aid the organizations achieve operational excellence and competitive advantage. Over time, most Small and Medium Enterprises (SMEs), which are known to be the major drivers of most thriving global economies, use the costly on-premise versions of these applications thereby making business difficult to competitively thrive in the same market environment with their large enterprise counterparts. The advent of cloud computing presents the SMEs an affordable offer and great opportunities as such EAs can be cloud-hosted and rented on a pay-per-use basis which does not require huge initial capital. However, as there are numerous Cloud Service Providers (CSPs) offering EAs as Software-as-a-Service (SaaS), there is a challenge of choosing a suitable provider with Quality of Service (QoS) that meet the organizations’ customized requirements. The proposed model takes care of that and goes a step further to select the most affordable among a selected few of the CSPs. In the earlier stage, before developing the instrument and conducting the pilot test, the researchers conducted a structured interview with three experts to validate the proposed model. In conclusion, the validity and reliability of the instrument were tested through experts, typical respondents, and analyzed with SPSS 22. Results confirmed the validity of the proposed model and the validity and reliability of the instrument.

Keywords: cloud service provider, enterprise application, quality of service, selection criteria, small and medium enterprise

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

Abstract:

The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Thanduxolo Nomngcoyiya, Simon M. Kang’ethe

Abstract:

The paper aimed to critically analyse gaps pertaining to the cultural policy environments governing traditional male circumcision in the Eastern Cape as exemplified by an empirical case study. The original study which this paper is derived from utilized qualitative paradigm; and encompassed 28 participants. It used in-depth one-on-one interviews complemented by focus group discussions and key informants as a method of data collection. It also adopted interview guide as a data collection instrument. The original study was cross-sectional in nature, and the data was audio recorded and transcribed later during the data analysis and coding process. The study data analysis was content thematic analysis and identified the following key major findings on the culture of male circumcision policy: Lack of clarity on culture of male circumcision policy operations; Myths surrounding procedures on culture of male circumcision; Divergent views on cultural policies between government and male circumcision custodians; Unclear cultural policies on selection criteria of practitioners; and Lack of policy enforcement and implementation on transgressors of culture of male circumcision. It recommended: a stringent selection criteria of practitioners; a need to carry out death-free male circumcision; a need for male circumcision stakeholders to work with other culture and tradition-friendly stakeholders.

Keywords: human rights, policy enforcement, traditional male circumcision, traditional surgeons and nurses

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Authors: Raj Chavan

Abstract:

Currently, there are over 14,500 Water Resource Recovery Facilities (WRRFs) in the United States, with ~35% of them having some type of nutrient limits in place. These WRRFs account for about 1% of overall power demand and 2% of total greenhouse gas emissions (GHG) in the United States and contribute for 10 to 15% of the overall nutrient load to surface rivers in the United States. The evolution of densification technologies toward more compact and energy-efficient nutrient removal processes has been impacted by a number of factors. Existing facilities that require capacity expansion or biomass densification for higher treatability within the same footprint are being subjected to more stringent requirements relating to nutrient removal prior to surface water discharge. Densification of activated sludge has received recent widespread interest as a means for achieving process intensification and nutrient removal at WRRFs. At the core of the technology are the aerobic sludge granules where the biological processes occur. There is considerable interest in the prospect of producing granular sludge in continuous (or traditional) activated sludge processes (CAS) or densification of biomass by moving activated sludge flocs to a denser aggregate of biomass as a highly effective technique of intensification. This presentation will provide a fundamental understanding of densification by presenting insights and practical issues. The topics that will be discussed include methods used to generate and retain densified granules; the mechanisms that allow biological flocs to densify; the role that physical selectors play in the densification of biological flocs; some viable ways for managing biological flocs that have become densified; effects of physical selection design parameters on the retention of densified biological flocs and finally some operational solutions for customizing the flocs and granules required to meet performance and capacity targets. In addition, it will present some case studies where biological and physical parameters were used to generate aerobic granular sludge in the continuous flow system.

Keywords: densification, aerobic granular sludge, nutrient removal, intensification

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Authors: Walailak Atthirawong

Abstract:

By the end of 2015, the Association of Southeast Asian Nations (ASEAN) countries proclaim to transform into the next stage of an economic era by having a single market and production base called ASEAN Economic Community (AEC). One objective of the AEC is to establish ASEAN as a single market and one production base making ASEAN highly competitive economic region and competitive with new mechanisms. As a result, it will open more opportunities to enterprises in both trade and investment, which offering a competitive market of US$ 2.6 trillion and over 622 million people. Location decision plays a key role in achieving corporate competitiveness. Hence, it may be necessary for enterprises to redesign their supply chains via enlarging a new production base which has low labor cost, high labor skill and numerous of labor available. This strategy will help companies especially for apparel industry in order to maintain a competitive position in the global market. Therefore, in this paper a generic model for location selection decision for Thai apparel industry using Fuzzy Analytical Network Process (FANP) is proposed. Myanmar, Vietnam and Cambodia are referred for alternative location decision from interviewing expert persons in this industry who have planned to enlarge their businesses in AEC countries. The contribution of this paper lies in proposing an approach model that is more practical and trustworthy to top management in making a decision on location selection.

Keywords: apparel industry, ASEAN Economic Community (AEC), Fuzzy Analytical Network Process (FANP), location decision

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Authors: Mrinal Saurabh Bhaskar, Rahul E Ravindranathan, Priyangana Borah

Abstract:

Energy plays a key role and as a driving force for economic and social growth for any country. To manage the energy sources and its efficient utilization in different economic sectors, energy policy of a country is critical. The energy performance of a country is measured in Energy Intensity and India’s Energy Intensity due to several policies interventions has reduced from 0.53 toe/1000USD (2010) in the year 2000 to 0.38 toe/1000USD (2010) in the year 2014, which is about 28 per cent reduction. The Government of India has taken several initiates to manage their increasing energy demand and meet the climate change goals defined by them. The major policy milestones in India related to energy are (i) Enactment of Energy Conservation (EC) Act 2001 (ii) Establishment of Bureau of Energy Efficiency 2001 (iii) National Action Plan on Climate Change (iv) Launch of Demand Side Management schemes (v) Amendment of EC Act 2010 (vi) Launch of Perform Achieve and Trade scheme 2012. Through a critical review, this paper highlights the key energy policy interventions by India, its benefits and impact, challenges faced and efforts of the Government to overcome such challenges. Such take away would be helpful for other countries who are proposing to prepare or amend their energy policy for their different economic sectors.

Keywords: energy, efficiency, climate, policy

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Authors: Alemi Asefa Wordofa

Abstract:

The textile industry is among the biggest industries in the world, producing a wide variety of products. Industry plays an important role in the world economy as well as in our daily lives. In Ethiopia, this has also been aided by the country’s impressive economic growth over the years. However, Textile industries consume large amounts of water and produce colored wastewater, which results in polluting the environment. In this study, the efficiency of the electrocoagulation treatment process using Iron electrodes to treat textile wastewater containing Reactive black everzol was studied. The effects of parameters such as voltage, time of reaction, and inter-electrode distance on Chemical oxygen demand (COD) and dye removal efficiency were investigated. In addition, electrical energy consumption at optimum conditions has been investigated. The results showed that COD and dye removals were 90.76% and 97.66%, respectively, at the optimum point of input voltage of 14v, inter-electrode distance of 7.24mm, and 47.86min electrolysis time. Energy consumption at the optimum point is also 2.9*10-3. It can be concluded that the electrocoagulation process by the iron electrode is a very efficient and clean process for COD and reactive black removal from wastewater.

Keywords: iron electrode, electrocoagulation, chemical oxygen demand, wastewater

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Authors: Kiatkulchai Jitt-Aer, Graham Wall, Dylan Jones

Abstract:

As a result of the Indian Ocean tsunami in 2004, logistics applied to disaster relief operations has received great attention in the humanitarian sector. As learned from such disaster, preparing and responding to the aspect of delivering essential items from distribution centres to affected locations are of the importance for relief operations as the nature of disasters is uncertain especially in suffering figures, which are normally proportional to quantity of supplies. Thus, this study proposes a spatial decision support system (SDSS) for humanitarian logistics by integrating Geographical Information Systems (GIS) and the capacitated vehicle routing problem (CVRP). The GIS is utilised for acquiring demands simulated from the tsunami flooding model of the affected area in the first stage, and visualising the simulation solutions in the last stage. While CVRP in this study encompasses designing the relief routes of a set of homogeneous vehicles from a relief centre to a set of geographically distributed evacuation points in which their demands are estimated by using both simulation and randomisation techniques. The CVRP is modeled as a multi-objective optimization problem where both total travelling distance and total transport resources used are minimized, while demand-cost efficiency of each route is maximized in order to determine route priority. As the model is a NP-hard combinatorial optimization problem, the Clarke and Wright Saving heuristics is proposed to solve the problem for the near-optimal solutions. The real-case instances in the coastal area of Phuket, Thailand are studied to perform the SDSS that allows a decision maker to visually analyse the simulation scenarios through different decision factors.

Keywords: demand simulation, humanitarian logistics, geographical information systems, relief operations, capacitated vehicle routing problem

Procedia PDF Downloads 248