Search results for: Information Management Systems

Authors: P. Maheshwari, M. Shapurkar

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The present research aimed at studying the awareness and attitudes of teachers towards inclusive education. The sample consisted of 60 teachers, teaching in the primary section (1st – 4th) of regular schools affiliated to the SSC board in Mumbai. Sample was selected by Multi-stage cluster sampling technique. A semi-structured self-constructed interview schedule and a self-constructed attitude scale was used to study the awareness of teachers about disability and Inclusive education, and their attitudes towards inclusive education respectively. Themes were extracted from the interview data and quantitative data was analyzed using SPSS package. Results revealed that teachers had some amount of awareness but an inadequate amount of information on disabilities and inclusive education. Disability to most (37) teachers meant “an inability to do something”. The difference between disability and handicap was stated by most as former being cognitive while handicap being physical in nature. With regard to Inclusive education, a large number (46) stated that they were unaware of the term and did not know what it meant. Majority (52) of them perceived maximum challenges for themselves in an inclusive set up, and emphasized on the role of teacher training courses in the area of providing knowledge (49) and training in teaching methodology (53). Although, 83.3% of teachers held a moderately positive attitude towards inclusive education, a large percentage (61.6%) of participants felt that being in inclusive set up would be very challenging for both children with special needs and without special needs. Though, most (49) of the teachers stated that children with special needs should be educated in regular classroom but they further clarified that only those should be in a regular classroom who have physical impairments of mild or moderate degree.

Keywords: Attitudes, awareness, inclusive education, teachers.

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: Android, permissions combination, API calls, machine learning.

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Authors: T. Chaiechi, N. Stoeckl

Abstract:

Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

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In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: Amelioration, deterioration, small sized poultry farmers, optimal price.

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Authors: J. Novak, A. Kohoutkova, V. Kristek, J. Vodicka, M. Sramek

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While the use of cast-in-place concrete for an airfield and highway pavement overlay is very common, the application of precast concrete elements is very limited today. The main reasons consist of high production costs and complex structural behavior. Despite that, several precast concrete systems have been developed and tested with the aim to provide a system with rapid construction. The contribution deals with the reinforcement design of a hexagonal element developed for a proposed airfield pavement system. The sub-base course of the system is composed of compacted recycled concrete aggregates and fiber reinforced concrete with recycled aggregates place on top of it. The selected element belongs to a group of precast concrete elements which are being considered for the construction of a surface course. Both high costs of full-scale experiments and the need to investigate various elements force to simulate their behavior in a numerical analysis software by using finite element method instead of performing expensive experiments. The simulation of the selected element was conducted on a nonlinear model in order to obtain such results which could fully compensate results from experiments. The main objective was to design reinforcement of the precast concrete element subject to quasi-static loading from airplanes with respect to geometrical imperfections, manufacturing imperfections, tensile stress in reinforcement, compressive stress in concrete and crack width. The obtained findings demonstrate that the position and the presence of imperfection in a pavement highly affect the stress distribution in the precast concrete element. The precast concrete element should be heavily reinforced to fulfill all the demands. Using under-reinforced concrete elements would lead to the formation of wide cracks and cracks permanently open.

Keywords: Imperfection, numerical simulation, pavement, precast concrete element, reinforcement design, stress analysis.

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Authors: Emma K. Sales

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Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments: 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR Analysis, genotype, genetic diversity, cultivars.

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Authors: Ibrahim H. Kilic, A. B. Tugrul

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Energy is a fundamental component in economic development and energy consumption is an index of prosperity and the standard of living. The consumption of energy per capita has increased significantly over the last decades, as the standard of living has improved. Turkey’s geographical location has several advantages for extensive use of wind power. Among the renewable sources, Turkey has very high wind energy potential. Information such as installation capacity of wind power plants in installation, under construction and license stages in the country are reported in detail. Some suggestions are presented in order to increase the wind power installation capacity of Turkey. Turkey’s economic and social development has led to a massive increase in demand for electricity over the last decades. Since the Turkey has no major oil or gas reserves, it is highly dependent on energy imports and is exposed to energy insecurity in the future. But Turkey does have huge potential for renewable energy utilization. There has been a huge growth in the construction of wind power plants and small hydropower plants in recent years. To meet the growing energy demand, the Turkish Government has adopted incentives for investments in renewable energy production. Wind energy investments evaluated the impact of feed-in tariffs (FIT) based on three scenarios that are optimistic, realistic and pessimistic with APLUS software that is developed for rational evaluation for energy market. Results of the three scenarios are evaluated in the view of electricity market for Turkey.

Keywords: APLUS, energy policy, renewable energy, wind power, Turkey.

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Authors: Md. Khademul Islam Molla, Akimasa Sumi, M. Sayedur Rahman

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The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Keywords: Empirical mode decomposition, instantaneous frequency, Hilbert spectrum, Chi-square distribution, anthropogenic impact.

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Authors: Osama Elgadi, Martin Birkett, Wai Ming Cheung

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This paper investigates the barriers behind the underutilisation of six sigma in Libyan manufacturing companies (LMCs). A mixed-method methodology is proposed, starting by conducting interviews to collect qualitative data followed by the development of a questionnaire to obtain quantitative data. The focus of this paper is on discussing the findings of the interview stage and how these can be used to further develop the questionnaire stage. The interview results showed that only four key barriers were highlighted as being encountered by LMCs. With a difference in terms of their significance, these factors were identified, and placed in descending order according to their importance, namely: “Lack of top management commitment”, “Lack of training”, “Lack of knowledge about six sigma”, and “Culture effect”. The findings also showed that some barriers which, were found in previous studies of six sigma implementation were not considered as barriers to LMCs but can, in fact, be considered as success factors or enablers for six sigma adoption. These factors were identified as: “sufficiency of time and financial resources”; “customers unsatisfied”; “good communication between all departments in the company”; “we are certain about its results and benefits to our company and unhappy with the current quality system”. These results suggest that LMCs face fewer barriers to adopting six sigma than many well-established global companies operating in other countries and could take advantage of these successful factors by developing and implementing a six sigma framework to improve their product quality and competitiveness.

Keywords: Six sigma, barriers, Libyan manufacturing companies, interview.

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: S. Chuenchooklin, T. Ichikawa, P. Mekpruksawong

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This research was conducted in the Lower Namkam Irrigation Project situated in the Namkam River Basin in Thailand. Degradation of groundwater quality in some areas is caused by saline soil spots beneath ground surface. However, the tail regulated gate structure on the Namkam River, a lateral stream of the Mekong River. It is aimed for maintaining water level in the river at +137.5 to +138.5 m (MSL) and flow to the irrigation canals based on a gravity system since July 2009. It might leach some saline soil spots from underground to soil surface if lack of understanding of the conjunctive surface water and groundwater behaviors. This research has been conducted by continuously the observing of both shallow and deep groundwater level and quality from existing observation wells. The simulation of surface water was carried out using a hydrologic modeling system (HEC-HMS) to compute the ungauged side flow catchments as the lateral flows for the river system model (HEC-RAS). The constant water levels in the upstream of the operated gate caused a slight rising up of shallow groundwater level when compared to the water table. However, the groundwater levels in the confined aquifers remained less impacted than in the shallow aquifers but groundwater levels in late of wet season in some wells were higher than the phreatic surface. This causes salinization of the groundwater at the soil surface and might affect some crops. This research aims for the balance of water stage in the river and efficient groundwater utilization in this area.

Keywords: Surface water, groundwater observation, irrigation, water balance.

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: O. I. H. Dimitry, N. A. Mansour, A. L. G. Saad

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Natural sodium montmorillonite (NaMMT), Cloisite Na⁺ and two organophilic montmorillonites (OMMTs), Cloisites 20A and 15A were used. Polycaprolactone (PCL)/MMT composites containing 1, 3, 5, and 10 wt% of Cloisite Na⁺ and PCL/OMMT nanocomposites containing 5 and 10 wt% of Cloisites 20A and 15A were prepared via solution intercalation technique to study the influence of organic modifier loading on particle dispersion of PCL/ NaMMT composites. Thermal stabilities of the obtained composites were characterized by thermal analysis using the thermogravimetric analyzer (TGA) which showed that in the presence of nitrogen flow the incorporation of 5 and 10 wt% of filler brings some decrease in PCL thermal stability in the sequence: Cloisite Na+>Cloisite 15A > Cloisite 20A, while in the presence of air flow these fillers scarcely influenced the thermoxidative stability of PCL by slightly accelerating the process. The interaction between PCL and silicate layers was studied by Fourier transform infrared (FTIR) spectroscopy which confirmed moderate interactions between nanometric silicate layers and PCL segments. The electrical conductivity (σ) which describes the ionic mobility of the systems was studied as a function of temperature and showed that σ of PCL was enhanced on increasing the modifier loading at filler content of 5 wt%, especially at higher temperatures in the sequence: Cloisite Na⁺<Cloisite 20A<Cloisite 15A, and was then decreased to some extent with a further increase to 10 wt%. The activation energy E_σ obtained from the dependency of σ on temperature using Arrhenius equation was found to be lowest for the nanocomposite containing 5 wt% of Cloisite 15A. The dispersed behavior of clay in PCL matrix was evaluated by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses which revealed partial intercalated structures in PCL/NaMMT composites and semi-intercalated/semi-exfoliated structures in PCL/OMMT nanocomposites containing 5 wt% of Cloisite 20A or Cloisite 15A.

Keywords: Polycaprolactone, organoclay, nanocomposite, montmorillonite, electrical conductivity, activation energy, exfoliation, intercalation.

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: Flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings.

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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Authors: Mahdiyeh Zafaranchi

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With rapid development of urbanization and improvement of living standards in the world, energy consumption and carbon emissions of the building sector are expected to increase in the near future; because of that, energy-saving issues have become more important among the engineers. Besides, the building sector is a major contributor to energy consumption and carbon emissions. The concept of efficient building appeared as a response to the need for reducing energy demand in this sector which has the main purpose of shifting from standard buildings to low-energy buildings. Although energy-saving should happen in all steps of a building during the life cycle (material production, construction, demolition), the main concept of efficient energy building is saving energy during the life expectancy of a building by using passive and active systems, and should not sacrifice comfort and quality to reach these goals. The main aim of this study is to investigate passive strategies (do not need energy consumption or use renewable energy) to achieve energy-efficient buildings. Energy retrofit measures were explored by eQuest software using a case study as a base model. The study investigates predictive accuracy for the major factors like thermal transmittance (U-value) of the material, windows, shading devices, thermal insulation, rate of the exposed envelope, window/wall ration, lighting system in the energy consumption of the building. The base model was located in Istanbul, Turkey. The impact of eight passive parameters on energy consumption had been indicated. After analyzing the base model by eQuest, a final scenario was suggested which had a good energy performance. The results showed a decrease in the U-values of materials, the rate of exposing buildings, and windows had a significant effect on energy consumption. Finally, savings in electric consumption of about 10.5%, and gas consumption by about 8.37% in the suggested model were achieved annually.

Keywords: Efficient building, electric and gas consumption, eQuest, passive parameters.

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Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: Hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen.

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Authors: Mohsen Nikaein

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Because of importance of energy, optimization of power generation systems is necessary. Gas turbine cycles are suitable manner for fast power generation, but their efficiency is partly low. In order to achieving higher efficiencies, some propositions are preferred such as recovery of heat from exhaust gases in a regenerator, utilization of intercooler in a multistage compressor, steam injection to combustion chamber and etc. However thermodynamic optimization of gas turbine cycle, even with above components, is necessary. In this article multi-objective genetic algorithms are employed for Pareto approach optimization of Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are entropy generation of RIGT cycle (Ns) derives using Exergy Analysis and Gouy-Stodola theorem, thermal efficiency and the net output power of RIGT Cycle. These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters such as compressor pressure ratio (Rp), excess air in combustion (EA), turbine inlet temperature (TIT) and inlet air temperature (T0). At the first stage single objective optimization has been investigated and the method of Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used for multi-objective optimization. Optimization procedures are performed for two and three objective functions and the results are compared for RIGT Cycle. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of three objective optimization the results are given in tables.

Keywords: Exergy, Entropy Generation, Brayton Cycle, DesignParameters, Optimization, Genetic Algorithm, Multi-Objective.

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Authors: Diako Azizi, Ahmad Gholami, Vahid Abbasi

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High voltage generators are being subject to higher voltage rating and are being designed to operate in harsh conditions. Stator windings are the main component of generators in which Electrical, magnetical and thermal stresses remain major failures for insulation degradation accelerated aging. A large number of generators failed due to stator winding problems, mainly insulation deterioration. Insulation degradation assessment plays vital role in the asset life management. Mostly the stator failure is catastrophic causing significant damage to the plant. Other than generation loss, stator failure involves heavy repair or replacement cost. Electro thermal analysis is the main characteristic for improvement design of stator slot-s insulation. Dielectric parameters such as insulation thickness, spacing, material types, geometry of winding and slot are major design consideration. A very powerful method available to analyze electro thermal performance is Finite Element Method (FEM) which is used in this paper. The analysis of various stator coil and slot configurations are used to design the better dielectric system to reduce electrical and thermal stresses in order to increase the power of generator in the same volume of core. This paper describes the process used to perform classical design and improvement analysis of stator slot-s insulation.

Keywords: Electrical field, field distribution, insulation, winding, finite element method, electro thermal

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Authors: Takeshi Takeda

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An experiment utilizing the ROSA/LSTF (rig of safety assessment/large-scale test facility) simulated a 1.9% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under the total failure of high-pressure injection system of emergency core cooling system in a pressurized water reactor. Steam generator (SG) secondary-side depressurization on the AM measure was started by fully opening relief valves in both SGs when the maximum core exit temperature rose to 623 K. A large increase took place in the cladding surface temperature of simulated fuel rods on account of a late and slow response of core exit thermocouples during core boil-off. The author analyzed the LSTF test by reference to the matrix of an integral effect test for the validation of a thermal-hydraulic system code. Problems remained in predicting the primary coolant distribution and the core exit temperature with the RELAP5/MOD3.3 code. The uncertainty analysis results of the RELAP5 code confirmed that the sample size with respect to the order statistics influences the value of peak cladding temperature with a 95% probability at a 95% confidence level, and the Spearman’s rank correlation coefficient.

Keywords: LSTF, LOCA, uncertainty analysis, RELAP5.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Nurcihan Hacioglu, Cigdem Gul, Murat Tosunoglu

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In this article, the antibiogram and heavy metal resistance profile of the bacteria isolated from total 34 studied animals (Pelophylax ridibundus = 12; Mauremys rivulata = 14; Natrix natrix = 8) captured around the Biga Stream, are described. There was no database information on antibiogram and heavy metal resistance profile of bacteria from these area’s amphibians and reptiles. A total of 200 bacteria were successfully isolated from cloaca and oral samples of the aquatic amphibians and reptiles as well as from the water sample. According to Jaccard’s similarity index, the degree of similarity in the bacterial flora was quite high among the amphibian and reptile species under examination, whereas it was different from the bacterial diversity in the water sample. The most frequent isolates were A. hydrophila (31.5%), B. pseudomallei (8.5%), and C. freundii (7%). The total numbers of bacteria obtained were as follows: 45 in P. ridibundus, 45 in N. natrix 30 in M. rivulata, and 80 in the water sample. The result showed that cefmetazole was the most effective antibiotic to control the bacteria isolated in this study and that approximately 93.33% of the bacterial isolates were sensitive to this antibiotic. The multiple antibiotic resistances (MAR) index indicated that P. ridibundus (0.95) > N. natrix (0.89) > M. rivulata (0.39). Furthermore, all the tested heavy metals (Pb+2, Cu+2, Cr+3, and Mn+2) inhibit the growth of the bacterial isolates at different rates. Therefore, it indicated that the water source of the animals was contaminated with both antibiotic residues and heavy metals.

Keywords: Amphibian, Bacteriological Quality, Reptile, Antibiotic & Heavy Metal Resistance.

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Authors: Hemant I. Joshi, Vivek J. Pandya

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This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.

Keywords: Smart Grid, Real Time Pricing, Peak to Average Ratio, Home Area Network, Home Energy Controller, Smart Plug, Utility Server, Linear Programming Problem.

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Authors: Ergin Kosa, Ali Göksenli

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Erosion and abrasion are wear mechanisms reducing the lifetime of machine elements like valves, pump and pipe systems. Both wear mechanisms are acting at the same time, causing a “Synergy” effect, which leads to a rapid damage of the surface. Different parameters are effective on erosive abrasive wear rate. In this study effect of particle impact angle on wear rate and wear mechanism of ductile and brittle materials was investigated. A new slurry pot was designed for experimental investigation. As abrasive particle, silica sand was used. Particle size was ranking between 200- 500 μm. All tests were carried out in a sand-water mixture of 20% concentration for four hours. Impact velocities of the particles were 4.76 m/s. As ductile material steel St 37 with Vickers Hardness Number (VHN) of 245 and quenched St 37 with 510 VHN was used as brittle material. After wear tests, morphology of the eroded surfaces were investigated for better understanding of the wear mechanisms acting at different impact angles by using Scanning Electron Microscope. The results indicated that wear rate of ductile material was higher than brittle material. Maximum wear rate was observed by ductile material at a particle impact angle of 300 and decreased further by an increase in attack angle. Maximum wear rate by brittle materials was by impact angle of 450 and decreased further up to 900. Ploughing was the dominant wear mechanism by ductile material. Microcracks on the surface were detected by ductile materials, which are nucleation centers for crater formation. Number of craters decreased and depth of craters increased by ductile materials by attack angle higher than 300. Deformation wear mechanism was observed by brittle materials. Number and depth of pits decreased by brittle materials by impact angles higher than 450. At the end it is concluded that wear rate could not be directly related to impact angle of particles due to the different reaction of ductile and brittle materials.

Keywords: Erosive wear, particle impact angle, silica sand, wear rate, ductile-brittle material.

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Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: Pedestrian detection, color segmentation, false positives, feature extraction.

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Authors: Hossein Taherian Far, Ali Bazaee

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Achieving continuous sustained economic growth and following economic development can be the target for all countries which are looking for it. In this regard, distribution industry plays an important role in growth and development of any nation. So, estimating the efficiency and productivity of the so called industry and identifying factors influencing it, is very necessary. The objective of the present study is to measure the efficiency and productivity of seven branches of Nina Distribution Company using window data envelopment analysis and Malmquist productivity index from spring 2013 to summer 2015. In this study, using criteria of fixed assets, payroll personnel, operating costs and duration of collection of receivables were selected as inputs and people and net sales, gross profit and percentage of coverage to customers were selected as outputs. Then, the process of performance window data envelopment analysis was driven and process efficiency has been measured using Malmquist index. The results indicate that the average technical efficiency of window Data Envelopment Analysis (DEA) model and fluctuating trend is sustainable. But the average management efficiency in window DEA model is related with negative growth (decline) of about 13%. The mean scale efficiency in all windows, except in the second one which is faced with 8%, shows growth of 18% compared to the first window. On the other hand, the mean change in total factor productivity in all branches of the industry shows average negative growth (decrease) of 12% which are the result of a negative change in technology.

Keywords: Nina Distribution Company branches, window data envelopment analysis, Malmquist productivity index.

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Authors: Vijay Shankar, C.S.P. Ojha, K.S. Hari Prasad

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Maize and Indian mustard are significant crops in semi-arid climate zones of India. Improved water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop evapotranspiration (ETc). Daily crop evapotranspiration comes as a product of reference evapotranspiration (ET0) and the growth stage specific crop coefficients modified for daily variation. The first objective of present study is to develop crop coefficients Kc for Maize and Indian mustard. The estimated values of Kc for maize at the four crop growth stages (initial, development, mid-season, and late season) are 0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc values at the four growth stages are 0.3, 0.6, 1.12, and 0.35, respectively. The second objective of the study is to compute daily crop evapotranspiration from ET0 and crop coefficients. Average daily ETc of maize varied from about 2.5 mm/d in the early growing period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3 mm/d and it occurred 64 days after sowing at the reproductive growth stage when leaf area index was 4.54. In the case of Indian mustard, average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season and achieves a peak value of 2.12 mm/d on 56 days after sowing. Improved schedules of irrigation have been simulated based on daily crop evapo-transpiration and field measured data. Simulation shows a close match between modeled and field moisture status prevalent during crop season.

Keywords: Crop coefficient, Crop evapotranspiration, Field moisture, Irrigation Scheduling

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

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Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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Authors: Feng-Yi Huang, Yuan-Jye Tseng

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In the traditional concept of product life cycle management, the activities of design, manufacturing, and assembly are performed in a sequential way. The drawback is that the considerations in design may contradict the considerations in manufacturing and assembly. The different designs of components can lead to different assembly sequences. Therefore, in some cases, a good design may result in a high cost in the downstream assembly activities. In this research, an integrated design evaluation and assembly sequence planning model is presented. Given a product requirement, there may be several design alternative cases to design the components for the same product. If a different design case is selected, the assembly sequence for constructing the product can be different. In this paper, first, the designed components are represented by using graph based models. The graph based models are transformed to assembly precedence constraints and assembly costs. A particle swarm optimization (PSO) approach is presented by encoding a particle using a position matrix defined by the design cases and the assembly sequences. The PSO algorithm simultaneously performs design evaluation and assembly sequence planning with an objective of minimizing the total assembly costs. As a result, the design cases and the assembly sequences can both be optimized. The main contribution lies in the new concept of integrated design evaluation and assembly sequence planning model and the new PSO solution method. The test results show that the presented method is feasible and efficient for solving the integrated design evaluation and assembly planning problem. In this paper, an example product is tested and illustrated.

Keywords: assembly sequence planning, design evaluation, design for assembly, particle swarm optimization

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