Search results for: Efficiency Improvement

Authors: Giorgi Gaprindashvili

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One of the best examples, in evolution of the public procurement, from post-soviet countries are reforms carried out in Georgia, which brought them close to international standards of procurement. In Georgia, public procurement legislation started functioning short after gaining independence. The reform has passed several stages and came in the form as it is today. It should also be noted, that countries with economy in transition, including Georgia, implemented all the reforms in public procurement based on recommendations and support of World Bank, the United Nations and other international organizations. The aim of first adopted law was regulation of the procurement process of budget-organizations, transparency and creation of competitive environment for private companies to access state funds legally. The priorities were identified quite clearly in the wording of the law, but operation/function of this law could not be reached on its level, because of some objective and subjective reasons. The high level of corruption in all levels of governance can be considered as a main obstacle reason and of course, it is natural, that it had direct impact on the procurement process, as well as on transparency and rational use of state funds. These circumstances were the reasons that reforms in this sphere continued, to improve procurement process, in particular, the first wave of reforms began after several years. Public procurement agency carried out reform with World Bank with main purpose of smartening the procurement legislation and its harmonization with international treaties and agreements. Also with the support of World Bank various activities were carried out to raise awareness of participants involved in procurement system. Further major changes in the legislation were filed bit later, which was also directed towards the improvement and smarten of the procurement process. The third wave of the reform more or less guaranteed the transparency of the procurement process, which later became the basis for the rational spending of state funds. The reform of the procurement system completely changed the procedures. Carried out reform in Georgia resulted in introducing new electronic tendering system, which benefit the transparency of the process, after this became the basis for the further development of a competitive environment, which become a prerequisite for the state rational spending. Increased number of supplier organizations participating in the procurement process resulted in reduction of the estimated cost and the actual cost. Assessment of the reforms in Georgia in the field of public procurement can be concluded, that proper regulation of the sector and relevant policy may proceed to rational and transparent spending of the budget from country’s state institutions. Also, the business sector has the opportunity to work in competitive market conditions and to make a preliminary analysis, which is a prerequisite for future strategy and development.

Keywords: Public Administration, Public Procurement, Reforms, Transparency.

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Authors: Márcia Afonso, Marisa Dinis-Almeida, Cristina Fael

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Climate change, namely precipitation patterns alteration, has led to extreme conditions such as floods and droughts. In turn, excessive construction has led to the waterproofing of the soil, increasing the surface runoff and decreasing the groundwater recharge capacity. The permeable pavements used in areas with low traffic lead to a decrease in the probability of floods peaks occurrence and the sediments reduction and pollutants transport, ensuring rainwater quality improvement. This study aims to evaluate the porous asphalt performance, developed in the laboratory, with addition of cellulosic fibres. One of the main objectives of cellulosic fibres use is to stop binder drainage, preventing its loss during storage and transport. Comparing to the conventional porous asphalt the cellulosic fibres addition improved the porous asphalt performance. The cellulosic fibres allowed the bitumen content increase, enabling retention and better aggregates coating and, consequently, a greater mixture durability. With this solution, it is intended to develop better practices of resilience and adaptation to the extreme climate changes and respond to the sustainability current demands, through the eco-friendly materials use. The mix design was performed for different size aggregates (with fine aggregates – PA1 and with coarse aggregates – PA2). The percentage influence of the fibres to be used was studied. It was observed that overall, the binder drainage decreases as the cellulose fibres percentage increases. It was found that the PA2 mixture obtained most binder drainage relative to PA1 mixture, irrespective of the fibres percentage used. Subsequently, the performance was evaluated through laboratory tests of indirect tensile stiffness modulus, water sensitivity, permeability and permanent deformation. The stiffness modulus for the two mixtures groups (with and without cellulosic fibres) presented very similar values between them. For the water sensitivity test it was observed that porous asphalt containing more fine aggregates are more susceptible to the water presence than mixtures with coarse aggregates. The porous asphalt with coarse aggregates have more air voids which allow water to pass easily leading to ITSR higher values. In the permeability test was observed that asphalt porous without cellulosic fibres presented had lower permeability than asphalt porous with cellulosic fibres. The resistance to permanent deformation results indicates better behaviour of porous asphalt with cellulosic fibres, verifying a bigger rut depth in porous asphalt without cellulosic fibres. In this study, it was observed that porous asphalt with bitumen higher percentages improve the performance to permanent deformation. This fact was only possible due to the bitumen retention by the cellulosic fibres.

Keywords: Binder drainage, cellulosic fibres, permanent deformation, porous asphalt.

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Authors: Wei-Chieh Yeh, Yung-Tang Shen

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The concept of community building started in 1994 in Taiwan. After years of development, it fostered the notion of active local resident participation in community issues as co-operators, instead of minions. Participatory design gives participants more control in the decision-making process, helps to reduce the friction caused by arguments and assists in bringing different parties to consensus. This results in an increase in the efficiency of projects run in the community. Therefore, the participation of local residents is key to the success of community building. This study applied participatory design to develop plans for the reuse of deserted spaces in the community from the first stage of brainstorming for design ideas, making creative models to be employed later, through to the final stage of construction. After conducting a series of participatory designed activities, it aimed to integrate the different opinions of residents, develop a sense of belonging and reach a consensus. Besides this, it also aimed at building the residents’ awareness of their responsibilities for the environment and related issues of sustainable development. By reviewing relevant literature and understanding the history of related studies, the study formulated a theory. It took the “2012-2014 Changhua County Community Planner Counseling Program” as a case study to investigate the implementation process of participatory design. Research data are collected by document analysis, participants’ observation and in-depth interviews. After examining the three elements of “Design Participation”, “Construction Participation”, and” Follow–up Maintenance Participation” in the case, the study emerged with a promising conclusion: Maintenance works were carried out better compared to common public works. Besides this, maintenance costs were lower. Moreover, the works that residents were involved in were more creative. Most importantly, the community characteristics could be easy be recognized.

Keywords: Participatory design, Deserted spaces, Community building, Reuse.

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Authors: Anatoly Krivinsh

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The results of dissertation research "Preventing and  combating corruption in public procurement" are presented in this  publication. The study was conducted 2011 till 2013 in a Member  State of the European Union– in the Republic of Latvia.  Goal of the thesis is to explore corruption prevention and  combating issues in public procurement sphere, to identify the  prevalence rates, determinants and contributing factors and  prevention opportunities in Latvia.  In the first chapter the author analyzes theoretical aspects of  understanding corruption in public procurement, with particular  emphasis on corruption definition problem, its nature, causes and  consequences. A separate section is dedicated to the public  procurement concept, mechanism and legal framework. In the first  part of this work the author presents cognitive methodology of  corruption in public procurement field, based on which the author has  carried out an analysis of corruption situation in public procurement  in Republic of Latvia.  In the second chapter of the thesis, the author analyzes the  problem of corruption in public procurement, including its historical  aspects, typology and classification of corruption subjects involved,  corruption risk elements in public procurement and their  identification. During the development of the second chapter author's  practical experience in public procurements was widely used.  The third and fourth chapter deals with issues related to the  prevention and combating corruption in public procurement, namely  the operation of the concept, principles, methods and techniques,  subjects in Republic of Latvia, as well as an analysis of foreign  experience in preventing and combating corruption. The fifth chapter  is devoted to the corruption prevention and combating perspectives  and their assessment. In this chapter the author has made the  evaluation of corruption prevention and combating measures  efficiency in Republic of Latvia, assessment of anti-corruption  legislation development stage in public procurement field in Latvia. 

Keywords: Prevention of corruption, public purchases.

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Authors: T. R. Bandara, H. Jaelani, G. J. Griffin

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The conversion of lignocellulosic waste materials, such as sugar cane bagasse, to biofuels such as ethanol has attracted significant interest as a potential element for transforming transport fuel supplies to totally renewable sources. However, the refractory nature of the cellulosic structure of lignocellulosic materials has impeded progress on developing an economic process, whereby the cellulose component may be effectively broken down to glucose monosaccharides and then purified to allow downstream fermentation. Ionic liquid (IL) treatment of lignocellulosic biomass has been shown to disrupt the crystalline structure of cellulose thus potentially enabling the cellulose to be more readily hydrolysed to monosaccharides. Furthermore, conventional hydrolysis of lignocellulosic materials yields byproducts that are inhibitors for efficient fermentation of the monosaccharides. However, selective extraction of monosaccharides from an aqueous/IL phase into an organic phase utilizing a combination of boronic acids and quaternary amines has shown promise as a purification process. Hydrolysis of sugar cane bagasse immersed in an aqueous solution with IL (1-ethyl-3-methylimidazolium acetate) was conducted at different pH and temperature below 100 ºC. It was found that the use of a high concentration of hydrochloric acid to acidify the solution inhibited the hydrolysis of bagasse. At high pH (i.e. basic conditions), using sodium hydroxide, catalyst yields were reduced for total reducing sugars (TRS) due to the rapid degradation of the sugars formed. For purification trials, a supported liquid membrane (SLM) apparatus was constructed, whereby a synthetic solution containing xylose and glucose in an aqueous IL phase was transported across a membrane impregnated with phenyl boronic acid/Aliquat 336 to an aqueous phase. The transport rate of xylose was generally higher than that of glucose indicating that a SLM scheme may not only be useful for purifying sugars from undesirable toxic compounds, but also for fractionating sugars to improve fermentation efficiency.

Keywords: Biomass, bagasse, hydrolysis, monosaccharide, supported liquid membrane, purification.

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: Human Motion Recognition, Motion representation, Laban Movement Analysis, Discrete Hidden Markov Model.

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Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev

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In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.

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Authors: Francis William S, Imtiaz Ahmed Choudhury, Ananda Kumar Eriki, A. John Rajan

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Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.

Keywords: Diesel Engine trap, thermophoresis, Exhaust pipe, PM-Simulation modeling.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Mohanapriya Subramanian, V. Raj

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Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: Biopolymers, fuel cells, nanocomposite, methanol crossover.

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: Sensor, electricity sub-meters, database, energy anomaly detection.

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: Smart city, social innovation, eHealth, innovation hubs, emerging technologies, equitable healthcare, healthy cities.

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Authors: Ekin Kıpçak, Mesut Akgün

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Recently, a growing interest has emerged on the development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of these alternative sources which have a great potential and sustainability to meet up the energy demand is biomass energy. This significant energy source can be utilized with various energy conversion technologies, one of which is biomass gasification in supercritical water.

Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical circumstances. At temperatures above its critical point (374.8^oC and 22.1MPa), water becomes more acidic and its diffusivity increases. Working with water at high temperatures increases the thermal reaction rate, which in consequence leads to a better dissolving of the organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.

In this study the gasification of a real biomass, namely olive mill wastewater (OMW), in supercritical water conditions is investigated with the use of Ru/Al₂O₃ catalyst. OMW is a by-product obtained during olive oil production, which has a complex nature characterized by a high content of organic compounds and polyphenols. These properties impose OMW a significant pollution potential, but at the same time, the high content of organics makes OMW a desirable biomass candidate for energy production.

The catalytic gasification experiments were made with five different reaction temperatures (400, 450, 500, 550 and 600°C) and five reaction times (30, 60, 90, 120 and 150s), under a constant pressure of 25MPa. Through these experiments, the effects of reaction temperature and time on the gasification yield, gaseous product composition and OMW treatment efficiency were investigated.

Keywords: Catalyst, Gasification, Olive mill wastewater, Ru/Al2O3, Supercritical water.

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Authors: B. Frączek

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The paper analyses the usage of the Internet by university students in Visegrad Countries (4V Countries) who study economic fields in their formal and informal financial education and captures the areas of untapped potential of Internet in educational processes. Higher education and training, technological readiness, and the financial market development are in the group of pillars, that are key for efficiency driven economies. These three pillars have become an inspiration to the research on using the Internet in the financial education among economic university students as the group of the best educated people in finance. The financial education is a process that allows for improving the level of financial literacy. In turn, the financial literacy it is the set of financial knowledge, skills, awareness and patterns influencing the financial decisions. The level of financial literacy influences the level of financial well-being of individuals, determines the scale of saving of households and at the same time gives the greater chance for sustainable and more predictable development of the financial market with the positive impact on economy. The financial literacy is necessary for each group of society but its appropriate level is desirable especially in respect of economics students as future participants of financial markets as well as the experts and advisors in financial decision making. The low level of financial literacy is the great problem of many target groups in both developing and developed countries and the financial education is seen as the best way of improving this situation. Also the financial inclusion plays the special role in enhancing the level of financial literacy in the aspect of education by practice as well as due to interrelation between level of financial literacy and degree of financial inclusion. Despite many initiatives under financial education, the level of financial literacy is still very low. Scientists still search for new ways of solving this problem. One of the proposal is more effective usage of the new technology in financial education, especially the Internet, because of the growing popularity of e-learning and the increasing number of Internet users, especially among young people who are called the Generation Net. Due to special role of the university students studying the economics fields for the future financial markets, students of four universities from Visegrad Countries (Czech Republic, Hungary, Poland and Slovakia) were invited to participate in the survey. The aim of the article is to present the level and ways of using the Internet technology in financial education and indicating the so far unused or underused opportunities.

Keywords: Financial education, financial inclusion, financial literacy, usage of Internet in education.

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: Landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture.

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Large Neural Network, Short-Term Load Forecasting, Particle Swarm Optimization.

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Authors: Rawia M. Khalil, Ahmed A. Abd El Rahman, Mahfouz A. Kassem, Mohamed S. El Ridi, Mona M. Abou Samra, Ghada E. A. Awad, Soheir S. Mansy

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Solid lipid nanoparticles (SLNs) have gained great attention for the topical treatment of skin associated fungal infection as they facilitate the skin penetration of loaded drugs. Our work deals with the preparation of nystatin loaded solid lipid nanoparticles (NystSLNs) using the hot homogenization and ultrasonication method. The prepared NystSLNs were characterized in terms of entrapment efficiency, particle size, zeta potential, transmission electron microscopy, differential scanning calorimetry, rheological behavior and in vitro drug release. A stability study for 6 months was performed. A microbiological study was conducted in male rats infected with Candida albicans, by counting the colonies and examining the histopathological changes induced on the skin of infected rats. The results showed that SLNs dispersions are spherical in shape with particle size ranging from 83.26±11.33 to 955.04±1.09 nm. The entrapment efficiencies are ranging from 19.73±1.21 to 72.46±0.66% with zeta potential ranging from -18.9 to -38.8 mV and shear-thinning rheological Behavior. The stability studies done for 6 months showed that nystatin (Nyst) is a good candidate for topical SLN formulations. A least number of colony forming unit/ ml (cfu/ml) was recorded for the selected NystSLN compared to the drug solution and the commercial Nystatin® cream present in the market. It can be fulfilled from this work that SLNs provide a good skin targeting effect and may represent promising carrier for topical delivery of Nyst offering the sustained release and maintaining the localized effect, resulting in an effective treatment of cutaneous fungal infection.

Keywords: Candida infections, Hot homogenization, Nystatin, Solid lipid nanoparticles, Stability, Topical delivery.

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: Agriculture 4.0, agri-food supply chain, Industry 4.0, voluntary traceability.

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Authors: Mohammad Reza Pirestani, Hamid Reza Vosoghifar, Pegah Jazayeri

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In designing river intakes and diversion structures, it is paramount that the sediments entering the intake are minimized or, if possible, completely separated. Due to high water velocity, sediments can significantly damage hydraulic structures especially when mechanical equipment like pumps and turbines are used. This subsequently results in wasting water, electricity and further costs. Therefore, it is prudent to investigate and analyze the performance of lateral intakes affected by sediment control structures. Laboratory experiments, despite their vast potential and benefits, can face certain limitations and challenges. Some of these include: limitations in equipment and facilities, space constraints, equipment errors including lack of adequate precision or mal-operation, and finally, human error. Research has shown that in order to achieve the ultimate goal of intake structure design – which is to design longlasting and proficient structures – the best combination of sediment control structures (such as sill and submerged vanes) along with parameters that increase their performance (such as diversion angle and location) should be determined. Cost, difficulty of execution and environmental impacts should also be included in evaluating the optimal design. This solution can then be applied to similar problems in the future. Subsequently, the model used to arrive at the optimal design requires high level of accuracy and precision in order to avoid improper design and execution of projects. Process of creating and executing the design should be as comprehensive and applicable as possible. Therefore, it is important that influential parameters and vital criteria is fully understood and applied at all stages of choosing the optimal design. In this article, influential parameters on optimal performance of the intake, advantages and disadvantages, and efficiency of a given design are studied. Then, a multi-criterion decision matrix is utilized to choose the optimal model that can be used to determine the proper parameters in constructing the intake.

Keywords: Diversion structures lateral intake, multi criteria decision making, optimal design, sediment control.

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Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: Assessment, hard skills, soft skills, standardized tests.

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm.

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Authors: Sungin Jeong

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This paper presents a linear oscillating generator of cylindrical type for hybrid electric vehicle application. The focus of the study is the suggestion of the optimal model and the design rule of the cylindrical linear oscillating generator with permanent magnet in the back-iron translator. The cylindrical topology is achieved using equivalent magnetic circuit considering leakage elements as initial modeling. This topology with permanent magnet in the back-iron translator is described by number of phases and displacement of stroke. For more accurate analysis of an oscillating machine, it will be compared by moving just one-pole pitch forward and backward the thrust of single-phase system and three-phase system. Through the analysis and comparison, a single-phase system of cylindrical topology as the optimal topology is selected. Finally, the detailed design of the optimal topology takes the magnetic saturation effects into account by finite element analysis. Besides, the losses are examined to obtain more accurate results; copper loss in the conductors of machine windings, eddy-current loss of permanent magnet, and iron-loss of specific material of electrical steel. The considerations of thermal performances and mechanical robustness are essential, because they have an effect on the entire efficiency and the insulations of the machine due to the losses of the high temperature generated in each region of the generator. Besides electric machine with linear oscillating movement requires a support system that can resist dynamic forces and mechanical masses. As a result, the fatigue analysis of shaft is achieved by the kinetic equations. Also, the thermal characteristics are analyzed by the operating frequency in each region. The results of this study will give a very important design rule in the design of linear oscillating machines. It enables us to more accurate machine design and more accurate prediction of machine performances.

Keywords: Equivalent magnetic circuit, finite element analysis, hybrid electric vehicle, free piston engine, cylindrical linear oscillating generator

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Authors: Selvam M, Natarajan. A M, Thangarajan R

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Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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Authors: Pratik Dhabal Deo, Manoj P.

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With the increasing number of social media users, the amount of video content available has also significantly increased. Currently, the number of smartphone users is at its peak, and many are increasingly using their smartphones as their main photography and recording devices. There have been a lot of developments in the field of video quality assessment in since the past years and more research on various other aspects of video and image are being done. Datasets that contain a huge number of videos from different high-end devices make it difficult to analyze the performance of the metrics on the content from most used devices even if they contain contents taken in poor lighting conditions using lower-end devices. These devices face a lot of distortions due to various factors since the spectrum of contents recorded on these devices is huge. In this paper, we have presented an analysis of the objective Video Quality Analysis (VQA) metrics on contents taken only from most used devices and their performance on them, focusing on full-reference metrics. To carry out this research, we created a custom dataset containing a total of 90 videos that have been taken from three most commonly used devices, and Android smartphone, an iOS smartphone and a Digital Single-Lens Reflex (DSLR) camera. On the videos taken on each of these devices, the six most common types of distortions that users face have been applied in addition to already existing H.264 compression based on four reference videos. These six applied distortions have three levels of degradation each. A total of the five most popular VQA metrics have been evaluated on this dataset and the highest values and the lowest values of each of the metrics on the distortions have been recorded. Finally, it is found that blur is the artifact on which most of the metrics did not perform well. Thus, in order to understand the results better the amount of blur in the data set has been calculated and an additional evaluation of the metrics was done using High Efficiency Video Coding (HEVC) codec, which is the next version of H.264 compression, on the camera that proved to be the sharpest among the devices. The results have shown that as the resolution increases, the performance of the metrics tends to become more accurate and the best performing metric among them is VQM with very few inconsistencies and inaccurate results when the compression applied is H.264, but when the compression is applied is HEVC, Structural Similarity (SSIM) metric and Video Multimethod Assessment Fusion (VMAF) have performed significantly better.

Keywords: Distortion, metrics, recording, frame rate, video quality assessment.

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Authors: Qurbanov Huseyn Nuraddin

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Reliable food supply of the population of a country is one of the main directions of the state's economic policy. Grain growing, which is the basis of agriculture, is important in this area. In the cultivation of cereals on slopes, the application of equal amounts of mineral fertilizers to under the soil before sowing is a very important technological process. The low level of technical equipment in this area prevents producers from providing the country with the necessary quality cereals. Experience in the operation of modern technical means has shown that at present, there is a need to provide an equal amount of fertilizer to under the soil on slopes, fully meeting the agro-technical requirements. No fundamental changes have been made to the industrial machines that fertilize under the soil, and unequal application of fertilizers to under the soil on slopes has been applied. This technological process leads to the destruction of new seedlings and reduced productivity due to intolerance to frost during the winter for the plant planted in the fall. In special climatic conditions, there is an optimal fertilization rate for each agricultural product. The application of fertilizers to the soil is one of the conditions that increase their efficiency in the field. As can be seen, the development of a new technical proposal for fertilizing and plowing the slopes in equal amounts on the slopes, improving the technological and design parameters, taking into account the physical and mechanical properties of fertilizers, is very important. Taking into account the above-mentioned issues, a combined plough was developed in our laboratory. Combined plough carries out pre-sowing technological operation in the cultivation of cereals, providing a smooth equal amount of mineral fertilizers to under the soil on the slopes. Mathematical models of a smooth spreader that evenly distributes fertilizers in the field have been developed. Thus, diagrams and graphs obtained without distribution on the eight partitions of the smooth spreader are constructed under the inclined angles of the slopes. Percentage and productivity of equal distribution in the field were noted by practical and theoretical analysis.

Keywords: Combined plough, mineral fertilizer, equal sowing, fertilizer norm, grain-crops, sowing fertilizer.

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Authors: Khaled M. Khader, Mamdouh I. Elimy, Omayma A. Nada

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Sustainable development is the nominal goal of most countries at present. In general, fossil fuels are the development mainstay of most world countries. Regrettably, the fossil fuel consumption rate is very high, and the world is facing the problem of conventional fuels depletion soon. In addition, there are many problems of environmental pollution resulting from the emission of harmful gases and vapors during fuel burning. Thus, clean, renewable energy became the main concern of most countries for filling the gap between available energy resources and their growing needs. There are many renewable energy sources such as wind, solar and wave energy. Energy can be obtained from the motion of sea waves almost all the time. However, power generation from solar or wind energy is highly restricted to sunny periods or the availability of suitable wind speeds. Moreover, energy produced from sea wave motion is one of the cheapest types of clean energy. In addition, renewable energy usage of sea waves guarantees safe environmental conditions. Cheap electricity can be generated from wave energy using different systems such as oscillating bodies' system, pendulum gate system, ocean wave dragon system and oscillating water column device. In this paper, a multi-criteria model has been developed using Analytic Hierarchy Process (AHP) to support the decision of selecting the most effective system for generating power from sea waves. This paper provides a widespread overview of the different design alternatives for sea wave energy converter systems. The considered design alternatives have been evaluated using the developed AHP model. The multi-criteria assessment reveals that the off-shore Oscillating Water Column (OWC) system is the most appropriate system for generating power from sea waves. The OWC system consists of a suitable hollow chamber at the shore which is completely closed except at its base which has an open area for gathering moving sea waves. Sea wave's motion pushes the air up and down passing through a suitable well turbine for generating power. Improving the power generation capability of the OWC system is one of the main objectives of this research. After investigating the effect of some design modifications, it has been concluded that selecting the appropriate settings of some effective design parameters such as the number of layers of Wells turbine fans and the intermediate distance between the fans can result in significant improvements. Moreover, simple dynamic analysis of the Wells turbine is introduced. Furthermore, this paper strives for comparing the theoretical and experimental results of the built experimental prototype.

Keywords: Renewable energy, oscillating water column, multi-criteria selection, wells turbine.

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Authors: Tomas Makaras, Gintaras Svecevičius

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Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Keywords: Fish behavior biomarker, landfill leachate, locomotor activity, rainbow trout juveniles, sublethal effects.

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Authors: Moatlhodi Wise Letshwenyo, Lesedi Lebogang

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Botswana is an arid country that needs to start reusing wastewater as part of its water security plan. Pilot scale slow sand filtration in combination with roughing filter was investigated for the treatment of effluent from Botswana International University of Science and Technology to meet Botswana irrigation standards. The system was operated at hydraulic loading rates of 0.04 m/hr and 0.12 m/hr. The results show that the system was able to reduce turbidity from 262 Nephelometric Turbidity Units to a range between 18 and 0 Nephelometric Turbidity Units which was below 30 Nephelometric Turbidity Units threshold limit. The overall efficacy ranged between 61% and 100%. Suspended solids, Biochemical Oxygen Demand, and Chemical Oxygen Demand removal efficiency averaged 42.6%, 45.5%, and 77% respectively and all within irrigation standards. Other physio-chemical parameters were within irrigation standards except for bicarbonate ion which averaged 297.7±44 mg L^-1 in the influent and 196.22±50 mg L^-1 in the effluent which was above the limit of 92 mg L^-1, therefore averaging a reduction of 34.1% by the system. Total coliforms, fecal coliforms, and Escherichia coli in the effluent were initially averaging 1.1 log counts, 0.5 log counts, and 1.3 log counts respectively compared to corresponding influent log counts of 3.4, 2.7 and 4.1, respectively. As time passed, it was observed that only roughing filter was able to reach reductions of 97.5%, 86% and 100% respectively for faecal coliforms, Escherichia coli, and total coliforms. These organism numbers were observed to have increased in slow sand filter effluent suggesting multiplication in the tank. Water quality index value of 22.79 for the physio-chemical parameters suggests that the effluent is of excellent quality and can be used for irrigation purposes. However, the water quality index value for the microbial parameters (1820) renders the quality unsuitable for irrigation. It is concluded that slow sand filtration in combination with roughing filter is a viable option for the treatment of secondary effluent for reuse purposes. However, further studies should be conducted especially for the removal of microbial parameters using the system.

Keywords: Irrigation, roughing filter, slow sand filter, turbidity, water quality index.

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Authors: Refaat H. Abd El Razek, Ahmed M. Diab, Sherif M. Hafez, Remon F. Aziz

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Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.

Keywords: Project management, typical (repetitive) large scale projects, line of balance, multi-objective optimization, genetic algorithms, time-cost-quality trade-offs.

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

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The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: Angle of internal friction, Cone penetrating test, General regression neural network, Soil modulus of elasticity.

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