Search results for: sustainability assessment framework

Authors: Shinya Yokoyama, Katsunari Jonouchi, Kenji Imou

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This paper discusses the utilization of marine biomass as an energy resource in Japan. A marine biomass energy system in Japan was proposed consisting of seaweed cultivation (Laminaria japonica) at offshore marine farms, biogas production via methane fermentation of the seaweeds, and fuel cell power generation driven by the generated biogas. We estimated energy output, energy supply potential, and CO2 mitigation in Japan on the basis of the proposed system. As a result, annual energy production was estimated to be 1.02-109 kWh/yr at nine available sites. Total CO2 mitigation was estimated to be 1.04-106 tonnes per annum at the nine sites. However, the CO2 emission for the construction of relevant facilities is not taken into account in this paper. The estimated CO2 mitigation is equivalent to about 0.9% of the required CO2 mitigation for Japan per annum under the Kyoto Protocol framework.

Keywords: CO2 mitigation, Fuel cell power generation, Laminaria japonica, Marine biomass, Seaweed.

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Authors: Asar Khan, Peter D. Widdop, Andrew J. Day, Aliaster S. Wood, Steve, R. Mounce, John Machell

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This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by sensors to construct an empirical model for time series prediction and classification of events. These two components have been installed, tested and verified in an experimental site in a UK water distribution system. Verification of the system has been achieved from a series of simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network management.

Keywords: Detection, leakage, neural networks, sensors, water distribution networks

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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Authors: Abioye A. Oyenuga, Rao Bhamidimarri

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Hurling a successful Construction and Demolition Waste (C&DW) recycling operation around the globe is a challenge today, predominantly because secondary materials markets are yet to be integrated. Reducing, Reusing and recycling of (C&DW) have been employed over the years, and various techniques have been investigated. However, the economic and environmental viability of its application seems limited. This paper discusses the costs and benefits in using secondary materials and focus on investigating reuse and recycling process for five major types of construction materials: concrete, metal, wood, cardboard/paper and plasterboard. Data obtained from demolition specialists and contractors are considered and evaluated. The research paper found that construction material recovery process fully incorporate a 3R’s principle contributing to saving energy and natural resources. This scrutiny leads to the empathy of grand challenges in construction material recovery process. Recommendations to deepen material recovery process are also discussed.

Keywords: Construction & Demolition Waste (C&DW), 3R concept, Recycling, Reuse, Life-Cycle Assessment (LCA), Waste Management.

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Authors: Siti Juryiah Mohd Khalid, Norazlina Dol

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Academic libraries in Malaysia are still not prepared for disaster even though several occasions have been reported. The study sets out to assess the current status of preparedness in disaster management among Malaysian academic libraries in the State of Selangor and the Federal Territory of Kuala Lumpur. To obtain a base level of knowledge on disaster preparedness of current practices, a questionnaire was distributed to chief librarians or their assignees in charge of disaster or emergency preparedness at 40 academic libraries and 34 responses were received. The study revolved around the current status of preparedness, on various issues including existence of disaster preparedness plan among academic libraries in Malaysia, disaster experiences by the academic libraries, funding, risk assessment activities and involvement of library staff in disaster management. Frequency and percentage tables were used in the analysis of the data collected. Some of the academic libraries under study have experienced one form of disaster or the other. Most of the academic libraries do not have a written disaster preparedness plan. The risk assessments and staff involvement in disaster preparedness by these libraries were generally adequate.

Keywords: Academic libraries, disaster preparedness plan, disaster management, emergency plan.

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Authors: Milada Krejci, Martin Hill, Vaclav Hosek, Dobroslava Jandova, Jiri Kajzar, Pavel Blaha

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The paper declares effects of exercise intervention of the research project “Basic research of balance changes in seniors”, granted by the Czech Science Foundation. The objective of the presented study is to define predictors, which influence bio-psycho-social consequences and effects of balance ability in senior 65 years old and above. We focused on the Fall-Efficacy Scale changes evaluation in seniors. Comprehensive hypothesis of the project declares, that motion uncertainty (dyskinesia) can negatively affect the well-being of a senior in bio-psycho-social context. In total, random selection and testing of 100 seniors (30 males, 70 females) from Prague and Central Bohemian region was provided. The sample was divided by stratified random selection into experimental and control groups, who underwent input and output testing. For diagnostics the methods of Medical Anamnesis, Functional anthropological examinations, Tinetti Balance Assessment Tool, SF-36 Health Survey, Anamnestic comparative self-assessment scale were used. Intervention method called "Life in Balance" based on yoga techniques was applied in four-week cycle. Results of multivariate regression were verified by repeated measures ANOVA: subject factor, phase of intervention (between-subject factor), body fluid (within-subject factor) and phase of intervention × body fluid interaction). ANOVA was performed with a repetition involving the factors of subjects, experimental/control group, phase of intervention (independent variable), and x phase interaction followed by Bonferroni multiple comparison assays with a test strength of at least 0.8 on the probability level p < 0.05. In the paper results of the first-year investigation of the three years running project are analysed. Results of balance tests confirmed no significant difference between females and males in pre-test. Significant improvements in balance and walking ability were observed in experimental group in females comparing to males (F = 128.4, p < 0.001). In the females control group, there was no significant change in post- test, while in the female experimental group positive changes in posture and spine flexibility in post-tests were found. It seems that females even in senior age react better to incentives of intervention in balance and spine flexibility. On the base of results analyses, we can declare the significant improvement in social balance markers after intervention in the experimental group (F = 10.5, p < 0.001). In average, seniors are used to take four drugs daily. Number of drugs can contribute to allergy symptoms and balance problems. It can be concluded that static balance and walking ability of seniors according Tinetti Balance scale correlate significantly with psychic and social monitored markers.

Keywords: Exercises, balance, seniors 65+, health, mental and social balance.

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Authors: Hong Pan, Yaping Zhu, Liang Zheng Xia

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We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.

Keywords: Adaboost, Face detection, Feature selection, PSO

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Authors: Osamu Saito

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Commercial infrastructures intended for use as leisure retreats such as golf and ski resorts have been extensively developed in many rural areas of Japan. However, following the burst of the economic bubble in the 1990s, several existing resorts faced tough management decisions and some were forced to close their business. In this study, six alternative management options for restructuring the existing golf courses (park, cemetery, biofuel production, reforestation, pasturing and abandonment) are examined and their environmental and economic impacts are quantitatively assessed. In addition, restructuring scenarios of these options and an ex-ante assessment model are developed. The scenario analysis by Monte Carlo simulation shows a clear trade-off between GHG savings and benefit/cost (B/C) ratios, of which “Restoring Nature" scenario absorbs the most CO2 among the four scenarios considered, but its B/C ratio is the lowest. This study can be used to select or examine options and scenarios of golf course management and rural environmental management policies.

Keywords: golf courses, restructuring and management options, scenario analysis, Tokyo Metropolitan Area.

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Authors: T. Santiboon

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This research were investigated, determined, and analyzed of the climate characteristically change in the provincial Udon Thani in the period of 60 surrounding years from 1951 to 2010 A.D. that it-s transferred to effects of climatologically data for determining global warming. Statistically significant were not found for the 60 years- data (R2<0.81). Statistically significant were found after adapted data followed as the Sun Spot cycle in 11 year periods, at the level 0.001 (R2= 1.00). These results indicate the Udon Thani-s weather are affected change; temperatures and evaporation were increased, but rainfall and number days of rainfall, cyclone storm, wind speed, and humidity, forest assessment were decreased. The effects of thermal energy from the sun radiation energy and human activities that they-re followed as the sunspot cycle are able to be predicted from the last to the future of the uniformitarian-s the climate change and global warming effect of the world.

Keywords: Climate Change, Global Warming, Udon Thani Province Weather

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Authors: O. S. Saulters, S. D. Goldberg, W. A. Staples, E. I. Martinez, L. M. Sanchez, D. E. Archuleta, D. L. Williams, S. D. Johnson, A. M. Baker

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To address an important set of unverified field conditions, the Los Alamos National Laboratory Waste Compliance and Tracking System (WCATS) Wall-to-Wall Team performed an unprecedented and advanced inventory. This reconciliation involved confirmation analysis for approximately 5850 hazardous, low-level, mixed low-level, and transuranic waste containers located in more than 200 staging and storage areas across 33 Technical Areas. The interdisciplinary team scoped, planned, and developed the multidimensional assessments. Through coordination with cross-functional site hosts, they were able to verify and validate data while resolving discrepancies identified in WCATS. The results were extraordinary with an updated inventory, tailored outreach, more cohesive communications, and timely closed-loop feedbacks.

Keywords: Circular economy, environmental performance data, social-ecological-technological systems, waste management.

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Authors: Lazim Abdullah, N orhanadiah Zam

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Increasing number of vehicles and lack of awareness among road users may lead to road accidents. However no specific literature was found to rank vehicles involved in accidents based on fuzzy variables of road users. This paper proposes a ranking of four selected motor vehicles involved in road accidents. Human and non-human factors that normally linked with road accidents are considered for ranking. The imprecision or vagueness inherent in the subjective assessment of the experts has led the application of fuzzy sets theory to deal with ranking problems. Data in form of linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. The Multi Criteria Decision Making, fuzzy TOPSIS was applied in computational procedures. From the analysis, it shows that motorcycles vehicles yielded the highest closeness coefficient at 0.6225. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the motorcycles recorded the first rank.

Keywords: Road accidents, decision making, closeness coefficient, fuzzy number

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Authors: Pei-Te Chiueh, Hsiao-Ting Wu, Shang-Lien Lo

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Protecting is the sources of drinking water is the first barrier of contamination of drinking water. The Feitsui Reservoir watershed of Taiwan supplies domestic water for around 5 million people in the Taipei metropolitan area. Understanding the spatial patterns of water quality trends in this watershed is an important agenda for management authorities. This study examined 7 sites in the watershed for water quality parameters regulated in the standard for drinking water source. The non-parametric seasonal Mann-Kendall-s test was used to determine significant trends for each parameter. Significant trends of increasing pH occurred at the sampling station in the uppermost stream watershed, and in total phosphorus at 4 sampling stations in the middle and downstream watershed. Additionally, the multi-scale land cover assessment and average land slope were used to explore the influence on the water quality in the watershed. Regression models for predicting water quality were also developed.

Keywords: Seasonal Mann-Kendall's test, Flow-adjusted concentrations, Water quality trends, Land-use

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Authors: Ines Hamdi, Mohamed Ben Ahmed

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The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower

Keywords: Ontological model, spatio-temporal modeling, Genetic Regulatory Networks (GRNs), knowledge representation.

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Authors: H. Anıl, G. Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations, since the geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning and time series methods, the total generation of the power plants belonging to Zorlu Doğal Electricity Generation, which has a high installed capacity in terms of geothermal, was predicted for the first one-week and first two-weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: Machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting.

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Authors: Ahmed Mateen, Zhu Qingsheng, Faisal Shahzad

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Requirement Engineering (RE) is a part being created for programming structure during the software development lifecycle. Software product line development is a new topic area within the domain of software engineering. It also plays important role in decision making and it is ultimately helpful in rising business environment for productive programming headway. Decisions are central to engineering processes and they hold them together. It is argued that better decisions will lead to better engineering. To achieve better decisions requires that they are understood in detail. In order to address the issues, companies are moving towards Software Product Line Engineering (SPLE) which helps in providing large varieties of products with minimum development effort and cost. This paper proposed a new framework for software product line and compared with other models. The results can help to understand the needs in SPL testing, by identifying points that still require additional investigation. In our future scenario, we will combine this model in a controlled environment with industrial SPL projects which will be the new horizon for SPL process management testing strategies.

Keywords: Requirements engineering, software product lines, scoping, process structure, domain specific language.

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: Weera Chotithammaporn

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This research aims to study employment trends in printing industry for prepress support by Suan Sunandha University Fund. The objectives of this research are to explain the trends of the employment in Thai Printing Industry for prepress in Bangkok and the description of different personnel that prepress entrepreneur need and also the problems of employment. The population of prepress entrepreneurs is about 100 organizations in the area of Bangkok. The questionnaires has been taken and analyzed with SPSS program by using the average percentage and standard deviation. This research is multiple case studies. The conceptual framework is developed on the basis of the open systems theory. The research result show that 1. The most of prepress entrepreneur have trend to choose the employee by any sex, the age 25-29 years old, bachelor degree and have 1-2 years experience. 2. The most problems are the understanding in job, communication/relation and the understanding in new technology. 3. The trends aims to employment in 1-3 years have 57.8% for prepress industry in Bangkok. This research suggests that: 1. Thai printing industry for prepress in Bangkok need quality employee that expert in printing technology. 2. Prepress entrepreneur should have agreement to development with university for practice the employee. 3. Prepress entrepreneur should support personal to fulfill the knowledge.

Keywords: Printing Industry, Prepress.

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Authors: D. Sivakumar

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The groundwater quality was assessed nearby places of Nagalkeni, Chennai, Tamil Nadu, India. The selected physico-chemical parameters were pH, EC, TDS, total hardness (TH), anions like Ca, Mg, Na and K, and cations like SO₄, NO_3, Cl_2, HCO₃, and CO₃, and Cr(VI). In order to suit the groundwater for drinking and irrigation purposes, compared the value of selected parameters with the value of selected parameters from BIS drinking water quality standard and irrigation water quality indices. The physico-chemical study of the groundwater systems of selected sites of nearby places of Nagalkeni showed that the groundwater is nearly acidic and mostly oxidizing in nature and hence, water is not suitable for drinking purpose directly. The results of the irrigation indices indicated that the groundwater samples in the study area found to be brackish water, results, groundwater from the study area is also not suitable for irrigation purpose directly, but the groundwater may be used after implementing some suitable treatment techniques.

Keywords: Physico-Chemical Parameters, Tannery Industry Effluent, Groundwater Quality Indices.

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Authors: Alev Ozkazanc, Fevziye Sayılan

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In this paper our aim is to explore the construction of schoolgirl femininities, drawing on the results of an ethnographic study conducted in a high school in Ankara, Turkey. In this case study which tries to explore the complexities of gender discourses, we were initially motivated by the questions that have been put forward by critical and feminist literature on education which emphasize the necessarily conflicting and partial nature of both reproduction and resistance and the importance of gendered power relations in the school context. Drawing on this paradigm our research tries to address to a more specific question: how are multiple schoolgirl femininities constructed within the context of gendered school culture, and especially in relation to hegemonic masculinity? Our study reveals that the general framework of multiple femininities is engendered by a tension between two inter-related positions. The first one is different strategies of accommodation and resistance to the gender-related problems of education. The second one is the school experience of girls which is conditioned by their differential position vis-à-vis the masculine resistance culture that is dominant in the school.

Keywords: Femininity, gender relations, masculinity, school, education in Turkey

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Authors: Oh Hyeon Jeon, WooYoung Jung

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In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.

Keywords: Weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo Simulation, permeability coefficient.

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Authors: M. Hammerton, J. Trevathan, T. Myers, W. Read

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The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Keywords: Wireless sensor networks, remote method invocation, transmission time.

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Authors: Wuttigrai Ngamsirijit

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Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: Decision making, human capital analytics, talent management, talent value chain.

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Authors: Rozilawati Razali, Paul W. Garratt

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Software maintenance, which involves making enhancements, modifications and corrections to existing software systems, consumes more than half of developer time. Specification comprehensibility plays an important role in software maintenance as it permits the understanding of the system properties more easily and quickly. The use of formal notation such as B increases a specification-s precision and consistency. However, the notation is regarded as being difficult to comprehend. Semi-formal notation such as the Unified Modelling Language (UML) is perceived as more accessible but it lacks formality. Perhaps by combining both notations could produce a specification that is not only accurate and consistent but also accessible to users. This paper presents an experiment conducted on a model that integrates the use of both UML and B notations, namely UML-B, versus a B model alone. The objective of the experiment was to evaluate the comprehensibility of a UML-B model compared to a traditional B model. The measurement used in the experiment focused on the efficiency in performing the comprehension tasks. The experiment employed a cross-over design and was conducted on forty-one subjects, including undergraduate and masters students. The results show that the notation used in the UML-B model is more comprehensible than the B model.

Keywords: Model comprehensibility, formal and semi-formal notation, empirical assessment.

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Authors: Zerrin Erginkaya, Gözde Konuray

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In this study, antimicrobial effect of Greek clover was determined with usage of MIC (minimum inhibition concentration) and agar diffusion method. Moreover, pH, water activity and microbial change were determined during storage of fenugreek paste. At first part of our study, microbial load of spices was evaluated. Two different fenugreek pastes were produced with mixing of Greek clover, spices, garlic and water. Fenugreek pastes were stored at 4 °C. At the second part, antimicrobial effect of Greek clover was determined on Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Debaryomyces hansenii, Aspergillus parasiticus, Candida rugosa, Mucor spp., when the concentrations of Greek clover were 8%, 12% and 16%. According to the results obtained, mould growth was determined at 15^th and 30^th days of storage in first and second fenugreek samples, respectively. Greek clover showed only antifungal effect on Aspergillus parasiticus at previously mentioned concentrations.

Keywords: Antimicrobial, fenugreek, Greek clover, minimum inhibition concentration.

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Authors: Hamidullah Sokout, Samiullah Paracha, Abdul Rashid Ahmadi

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Passing the entrance exam to a university is a major step in one's life. University entrance exam commonly known as Kankor is the nationwide entrance exam in Afghanistan. This examination is prerequisite for all public and private higher education institutions at undergraduate level. It is usually taken by students who are graduated from high schools. In this paper, we reflect the major educational school graduates issues and propose ICT-based test preparation environment, known as ‘Online Kankor Exam Prep System’ to give students the tools to help them pass the university entrance exam on the first try. The system is based on Intelligent Tutoring System (ITS), which introduced an essential package of educational technology for learners that features: (I) exam-focused questions and content; (ii) self-assessment environment; and (iii) test preparation strategies in order to help students to acquire the necessary skills in their carrier and keep them up-to-date with instruction.

Keywords: Web-based test prep systems, Learner-centered design, E-Learning, Intelligent tutoring system.

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Authors: Leila Jafari, Viliam Makis, Akram Khaleghei G.B.

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1 which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed, illustrated by a numerical example.

Keywords: Condition-Based Maintenance, Semi-Markov Decision Process, Multivariate Bayesian Control Chart, Partially Observable System, Two-unit System.

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Authors: Isaac Kofi Mensah

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The adoption and application of Information and Communication Technologies (ICTs) in government administration through e-government is expected to permeate all sectors of state/ public institutions as well as democratic institutions. One of such public institutions is the Electoral Commission of Ghana mandated by the 1992 Constitution to hold all public elections including presidential and parliamentary elections. As Ghana holds its 7th General Elections since 1992, on 7th November 2016, there are demands from key stakeholders for the Election Management Body, which is the Electoral Commission (EC) of Ghana to adopt and implement an electronic voting system. This case study, therefore, attempts to contribute significantly to the debate by examining influencing factors that would impact on citizen’s readiness to adopt and use an electronic voting system in Ghana. The Technology Acceptance Model (TAM) was used as a theoretical framework for this study, out of which a research model and hypotheses were developed. Importantly, the outcome of this research finding would form a basis for appropriate policy recommendation for consideration of Government and EC of Ghana.

Keywords: Citizens readiness, e-government, electronic voting, technology acceptance model (TAM).

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Authors: T. S. Myers, J. Trevathan

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Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto

Abstract:

This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: Somaye Abdollahi Pour, Mohsen Saneei

Abstract:

This paper describes a novel monitoring scheme to minimize total active power in digital circuits depend on the demand frequency, by adjusting automatically both supply voltage and threshold voltages based on circuit operating conditions such as temperature, process variations, and desirable frequency. The delay monitoring results, will be control and apply so as to be maintained at the minimum value at which the chip is able to operate for a given clock frequency. Design details of power monitor are examined using simulation framework in 32nm BTPM model CMOS process. Experimental results show the overhead of proposed circuit in terms of its power consumption is about 40 μW for 32nm technology; moreover the results show that our proposed circuit design is not far sensitive to the temperature variations and also process variations. Besides, uses the simple blocks which offer good sensitivity, high speed, the continuously feedback loop. This design provides up to 40% reduction in power consumption in active mode.

Keywords: active mode, delay monitor, body biasing, VDD scaling, low power.

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