Search results for: Sustainable Water Management

Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market.By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: Precision Machinery Industry, Key Success Factors (KSPs), Key Success Paths (KSPs), Overall Profitability, Product Pricing Power, Competitive Advantages.

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Authors: Satu Lautamäki

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This paper presents findings from a multidisciplinary course (bachelor level) implemented at Seinäjoki University of Applied Sciences, Finland. The course aims to develop innovative thinking of students, by having projects given by companies, using design thinking methods as a tool for creativity and by integrating students into multidisciplinary teams working on the given projects. The course is obligatory for all first year bachelor students across four faculties (business and culture, food and agriculture, health care and social work, and technology). The course involves around 800 students and 30 pedagogical coaches, and it is implemented as an intensive one-week course each year. The paper discusses the pedagogy, structure and coordination of the course. Also, reflections on methods for the development of creative skills are given. Experts in contemporary, global context often work in teams, which consist of people who have different areas of expertise and represent various professional backgrounds. That is why there is a strong need for new training methods where multidisciplinary approach is at the heart of learning. Creative learning takes place when different parties bring information to the discussion and learn from each other. When students in different fields are looking for professional growth for themselves and take responsibility for the professional growth of other learners, they form a mutual learning relationship with each other. Multidisciplinary team members make decisions both individually and collectively, which helps them to understand and appreciate other disciplines. Our results show that creative and multidisciplinary project learning can develop diversity of knowledge and competences, for instance, students’ cultural knowledge, teamwork and innovation competences, time management and presentation skills as well as support a student’s personal development as an expert. It is highly recommended that higher education curricula should include various studies for students from different study fields to work in multidisciplinary teams.

Keywords: Multidisciplinary learning, creative skills, innovative thinking, project-based learning.

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Authors: Cholpassorn Sitthiwarongchai, Chutikarn Sriviboon

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The two primary objectives of this research were (1)  to examine the current knowledge and actual circumstance of  agricultural workers about mangosteen product processing; and (2) to  analyze and evaluate ways to develop capacity of mangosteen  product processing. The population of this study was 15,125 people  who work in the agricultural sector, in this context, mangosteen  production, in the eastern part of Thailand that included Chantaburi  Province, Rayong Province, Trad Province and Pracheenburi  Province. The sample size based on Yamane’s calculation with 95%  reliability was therefore 392 samples. Mixed method was employed  included questionnaire and focus group discussion with  Connoisseurship Model used in order to collect quantitative and  qualitative data. Key informants were used in the focus group  including agricultural business owners, academic people in agro food  processing, local academics, local community development staff,  OTOP subcommittee, and representatives of agro processing  industry professional organizations. The study found that the  majority of the respondents agreed with a high level (in five- rating  scale) towards most of variables of knowledge management in agro  food processing. The result of the current knowledge and actual  circumstance of agricultural human resource in an arena of  mangosteen product processing revealed that mostly, the respondents  agreed at a high level to establish 7 variables. The guideline to  developing the body of knowledge in order to enhance the capacity  of the agricultural workers in mangosteen product processing was  delivered in the focus group discussion. The discussion finally  contributed to an idea to produce manuals for mangosteen product  processing methods, with 4 products chosen: (1) mangosteen soap;  (2) mangosteen juice; (3) mangosteen toffee; and (4) mangosteen  preserves or jam.

Keywords: Capacity Enhancement, Agricultural Workers, Mangosteen Product Processing.

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Authors: Eman. K. Ramadan, Abdelgawad. S. El-Tahawy

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The objective of this study was to evaluate the effects of calving season on the production and economic efficiency of dairy farms in Egypt. Our study was performed at dairy production farms in the Alexandria, Behera, and Kafr El-Sheikh provinces of Egypt from summer 2010 to winter 2013. The randomly selected dairy farms had herds consisting of Baladi, Holstein-Friesian, or cross-bred (Baladi × Holstein-Friesian) cows. The data were collected from production records and responses to a structured questionnaire. The average total return differed significantly (P < 0.05) between the different cattle breeds and calving seasons. The average total return was highest for the Holstein- Friesian cows that calved in the winter (29106.42 EGP/cow/year), and it was lowest for Baladi cows that calved in the summer (12489.79 EGP/cow/year). Differences in total returns between the cows that calved in the winter or summer or between the foreign and native breeds, as well as variations in calf prices, might have contributed to the differences in milk yield. The average net profit per cow differed significantly (P < 0.05) between the cattle breeds and calving seasons. The average net profit values for the Baladi cows that calved in the winter or summer were 2413 and 2994.96 EGP/cow/year, respectively, and those for the Holstein- Friesian cows were 10744.17 and 7860.56 EGP/cow/year, respectively, whereas those for the cross-bred cows were 10174.86 and 7571.33 EGP/cow/year, respectively. The variations in net profit might have resulted from variation in the availability or price of feed materials, milk prices, or sales volumes. Our results show that the breed and calving season of dairy cows significantly affected the economic efficiency of dairy farms in Egypt. The cows that calved in the winter produced more milk than those that calved in the summer, which may have been the result of seasonal influences, such as temperature, humidity, management practices, and the type of feed or green fodder available.

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Authors: C. S. Quah, S. P. L. Sim

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This study examined how individuals in their respective teams contributed to innovation performance besides defining the term of innovation in their own respective views. This study also identified factors that motivated University staff to contribute to the innovation products. In addition, it examined whether there is a significant relationship between professional training level and the length of service among university staff towards innovation and to what extent do the two variables contributed towards innovative products. The significance of this study is that it revealed the strengths and weaknesses of the university staff when contributing to innovation performance. Stratified-random sampling was employed to determine the samples representing the population of lecturers in the study, involving 123 lecturers in one of the local universities in Malaysia. The method employed to analyze the data is through categorizing into themes for the open-ended questions besides using descriptive and inferential statistics for the quantitative data. This study revealed that two types of definition for the term “innovation” exist among the university staff, namely, creation of new product or new approach to do things as well as value-added creative way to upgrade or improve existing process and service to be more efficient. This study found that the most prominent factor that propels them towards innovation is to improve the product in order to benefit users, followed by selfsatisfaction and recognition. This implies that the staff in the organization viewed the creation of innovative products as a process of growth to fulfill the needs of others and also to realize their personal potential. This study also found that there was only a significant relationship between the professional training level and the length of service of 4 - 6 years among the university staff. The rest of the groups based on the length of service showed that there was no significant relationship with the professional training level towards innovation. Moreover, results of the study on directional measures depicted that the relationship for the length of service of 4- 6 years with professional training level among the university staff is quite weak. This implies that good organization management lies on the shoulders of the key leaders who enlighten the path to be followed by the staff.

Keywords: Innovation, length of service, performance, professional training level, motivation.

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Authors: Kim H. K. Choy, Oliva H. K. Chu, W. Y. Keung, B. Lim, Winnie P. Y. Tang

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Background: The prevalence of workplace obesity is rising worldwide; therefore, the workplace is an ideal venue to implement weight control intervention. This pilot randomized controlled trial aimed to develop, implement, and evaluate a nutritional wellness program for obese health care providers working in a hospital. Methods: This hospital-based nutritional wellness program was an 8-week pilot randomized controlled trial for obese health care providers. The primary outcomes were body weight and body mass index (BMI). The secondary outcomes were serum fasting glucose, fasting cholesterol, triglyceride, high-density (HDL) and low-density (LDL) lipoprotein, body fat percentage, and body mass. Participants were randomly assigned to the intervention (n = 20) or control (n = 22) group. Participants in both groups received individual nutrition counselling and nutrition pamphlets, whereas only participants in the intervention group were given mobile phone text messages. Results: 42 participants completed the study. In comparison with the control group, the intervention group showed approximately 0.98 kg weight reduction after two months. Participants in intervention group also demonstrated clinically significant improvement in BMI, serum cholesterol level, and HDL level. There was no improvement of body fat percentage and body mass for both intervention and control groups. Conclusion: The nutritional wellness program for obese health care providers was feasible in hospital settings. Health care providers demonstrated short-term weight loss, decrease in serum fasting cholesterol level, and HDL level after completing the program.

Keywords: Health care provider, hospital, weight management, weight control.

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Authors: Prima Gusti Yanti, Fairul Zabadi

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The purpose of the study is to find out relation of moral massage between the authority and globalization in proverb. Proverb is one of the many forms of cultural identity of the Indonesian/Malay people filled with moral values. The values contained within those proverbs are beneficial not only to the society, but also to those who held power amidst on this era of globalization. The method being used is qualitative research through content analysis which is done by describing and uncovering the forms and meanings of proverbs used within Indonesia Minangkabau society. Sources for this study’s data were extracted from a Minangkabau native speaker in the sub district of Tanah Abang, Jakarta. Said sources were retrieved through a series of interviews with the Minangkabau native speaker, whose speech is still adorned with idiomatic expressions. The research findings show that there are 30 existed proverbs or idiomatic expressions in the Minangkabau language often used by its indigenous people. The thirty data contain moral values which are closely interwoven with the matter of power and globalization. Analytical results show that the fourteen moral values contained within proverbs reflect a firm connection between rule and power in globalization; such as: responsible, brave, togetherness and consensus, tolerance, politeness, thorough and meticulous, honest and keeping promise, ingenious and learning, care, self-correction, be fair, alert, arbitrary, self-awareness. Structurally, proverbs possess an unchangeably formal construction; symbolically, proverbs possess meanings that are clearly decided through ethnographic communicative factors along with situational and cultural contexts. Values contained within proverbs may be used as a guide in social management, be it between fellow men, between men and nature, or even between men and their Creator. Therefore, the meanings and values contained within the morals of proverbs could also be utilized as a counsel for those who rule and in charge of power in order to stem the tides of globalization that had already spread into sectoral, territorial and educational continuums.

Keywords: Continuum, globalization, identity, proverb, rule-power.

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Authors: S. Karthikeyan, Naveen Bindra

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Introduction: To update ourselves and understand the concept of latest electronic formats available for Health care providers and how it could be used and developed as per standards. The idea is to correlate between the patients Manual Medical Records keeping and maintaining patients Electronic Information in a Health care setup in this world. Furthermore, this stands with adapting to the right technology depending upon the organization and improve our quality and quantity of Healthcare providing skills. Objective: The concept and theory is to explain the terms of Electronic Medical Record (EMR), Electronic Health Record (EHR) and Personal Health Record (PHR) and selecting the best technical among the available Electronic sources and software before implementing. It is to guide and make sure the technology used by the end users without any doubts and difficulties. The idea is to evaluate is to admire the uses and barriers of EMR-EHR-PHR. Aim and Scope: The target is to achieve the health care providers like Physicians, Nurses, Therapists, Medical Bill reimbursements, Insurances and Government to assess the patient’s information on easy and systematic manner without diluting the confidentiality of patient’s information. Method: Health Information Technology can be implemented with the help of Organisations providing with legal guidelines and help to stand by the health care provider. The main objective is to select the correct embedded and affordable database management software and generating large-scale data. The parallel need is to know how the latest software available in the market. Conclusion: The question lies here is implementing the Electronic information system with healthcare providers and organization. The clinicians are the main users of the technology and manage us to “go paperless”. The fact is that day today changing technologically is very sound and up to date. Basically, the idea is to tell how to store the data electronically safe and secure. All three exemplifies the fact that an electronic format has its own benefit as well as barriers.

Keywords: Medical records, digital records, health information, electronic record system.

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Authors: Fiona Curran-Cournane

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Soil quality monitoring is a science-based soil management tool that assesses soil ecosystem health. A soil monitoring program in Auckland, New Zealand’s largest city extends from 1995 to the present. The objective of this study was to firstly determine changes in soil parameters (basic soil properties and heavy metals) that were assessed from rural land in 1995-2000 and repeated in 2008-2012. The second objective was to determine differences in soil parameters across various land uses including native bush, rural (horticulture, pasture and plantation forestry) and urban land uses using soil data collected in more recent years (2009- 2013). Across rural land, mean concentrations of Olsen P had significantly increased in the second sampling period and was identified as the indicator of most concern, followed by soil macroporosity, particularly for horticultural and pastoral land. Mean concentrations of Cd were also greatest for pastoral and horticultural land and a positive correlation existed between these two parameters, which highlights the importance of analysing basic soil parameters in conjunction with heavy metals. In contrast, mean concentrations of As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites had the lowest concentrations of heavy metals and were used to calculate a ‘pollution index’ (PI). The mean PI was classified as high (PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As and Hg, indicating high levels of heavy metal pollution across both rural and urban soils. From a land use perspective, the mean ‘integrated pollution index’ was highest for urban sites at 2.9 followed by pasture, horticulture and plantation forests at 2.7, 2.6 and 0.9, respectively. It is recommended that soil sampling continues over time because a longer spanning record will allow further identification of where soil problems exist and where resources need to be targeted in the future. Findings from this study will also inform policy and science direction in regional councils.

Keywords: Heavy metals, Pollution Index, Rural and Urban land use.

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

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Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: Connected vehicles, GLOSA, intelligent transportation systems, infrastructure-to-vehicle communication.

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Authors: Diana Flores Galindo, Richard Gil Herrera

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Nowadays, Lean Manufacturing and Industry 4.0 are very important in every country. One of the main benefits is continued market presence. It has been identified that there is a need to change existing educational programs, as well as update the knowledge and skills of existing employees. It should be borne in mind that behind each technological improvement, there is a human being. Human talent cannot be neglected. The main objectives of this article are to review the link between Lean Manufacturing, the incorporation of Industry 4.0 and the steps to follow to implement it; analyze the current situation and study the implications and benefits of this new trend, with a particular focus on Mexico. Lean Manufacturing and Industry 4.0 implementation waves must always take care of the most important capital – intellectual capital. The methodology used in this article comprised the following steps: reviewing the reality of the fourth industrial revolution, reviewing employees’ skills on the journey to become world-class, and analyzing the situation in Mexico. Lean Manufacturing and Industry 4.0 were studied not as exclusive concepts, but as complementary ones. The methodological framework used is focused on motivating companies’ collaborators to guarantee common results, innovate, and remain in the market in the face of new requirements from company stakeholders. The key findings were that both trends emphasize the need to improve communication across the entire company and incorporate new technologies into everyday work, from the shop floor to administrative staff, to help improve processes. Taking care of people, activities and processes will bring a company success. In the specific case of Mexico, companies in all sectors need to be aware of and implement technological improvements according to their specific needs. Low-cost labor represents one of the most typical barriers. In conclusion, companies must build a roadmap according to their strategy and needs to achieve their short, medium- and long-term goals.

Keywords: Lean management, lean manufacturing, industry 4.0, motivation, SWOT analysis, Hoshin Kanri.

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Authors: Analiza Acuña-Villacorte

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The Institutional Sustainability Performance (ISP) of State Universities and Colleges (SUCs) in the Philippines reveals the level of compliance and fidelity of the latter to the mandates of the state. This performance evaluation procedure aims to perpetually monitor and sustain the quality of services provided by the state institutions in the country. Importantly, the SUC level rating is one of the key indicators of the merit system adopted by the state to give incentives to government institutions. With the crucial role of the ISP and SUC level in the performance of an institution and in sustaining quality assurance, this study theorized that the top managers’ capacity to influence is the critical factor in meeting the expectations of the state. This study assessed the top managers’ capacity to influence. The hypothesis in this study proved that leadership style of top managers has significant relationship to the managers’ capacity to influence for institutional sustainability performance. Thus, the subjects of this study were restricted only to the State Universities and Colleges (SUC) that qualified in the top 20 Institutional Sustainability Performance; the digital governance performance, and the SUC leveling status nationwide. The top managers and their subordinates with doctorate of Bulacan State University and Bataan Peninsula State University whose programs have been consistently submitted to accreditation and were ranked Levels III and IV were subjected and participated to the study. This study assessed the top managers’ capacity to influence. The hypothesis in this study proved that leadership style of top managers has significant relationship to the managers’ capacity to influence for institutional sustainability performance. Thus, the subjects of this study were restricted only to the State Universities and Colleges (SUC) that qualified in the top 20 Institutional Sustainability Performance; the digital governance performance, and the SUC leveling status nationwide. The top managers and their subordinates with doctorate of Bulacan State University and Bataan Peninsula State University whose programs have been consistently submitted to accreditation and were ranked Levels III and IV were subjected and participated to the study.

Keywords: Capacity to Influence, Descriptive Design, Institutional Sustainability Performance, Management.

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Authors: P. Phenpun, S. Wareewan

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This qualitative study aimed to describe the opinions in relation to humanized care emerging from the volunteer activities of nursing students at Boromarajonani College of Nursing, Chonburi, Thailand. One hundred and twenty-seven second-year nursing students participated in this study. The volunteer activity model was composed of preparation, implementation, and evaluation through a learning log, in which students were encouraged to write their daily activities after completing practical training at the healthcare center. The preparation content included three main categories: service minded, analytical thinking, and client participation. The preparation process took over three days that accumulates up to 20 hours only. The implementation process was held over 10 days, but with a total of 70 hours only, with participants taking part in volunteer work activities at a healthcare center. A learning log was used for evaluation and data were analyzed using content analysis. The findings were as follows. With service minded, there were two subcategories that emerged from volunteer activities, which were service minded towards patients and within themselves. There were three categories under service minded towards patients, which were rapport, compassion, and empathy service behaviors, and there were four categories under service minded within themselves, which were self-esteem, self-value, management potential, and preparedness in providing good healthcare services. In line with analytical thinking, there were two components of analytical thinking, which were analytical skill for their works and analytical thinking for themselves. There were four subcategories under analytical thinking for their works, which were evidence based thinking, real situational thinking, cause analysis thinking, and systematic thinking, respectively. There were four subcategories under analytical thinking for themselves, which were comparative between themselves, towards their clients that leads to the changing of their service behaviors, open-minded thinking, modernized thinking, and verifying both verbal and non-verbal cues. Lastly, there were three categories under participation, which were mutual rapport relationship; reconsidering client’s needs services and providing useful health care information.

Keywords: Humanized care service, volunteer activity, nursing student, and learning log.

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Authors: Rupinder Bakshi, Geeta Walia, Anita Gupta

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Urinary Tract Infections are considered as one of the most common bacterial infections with an estimated annual global incidence of 150 million. Antimicrobial drug resistance is one of the major threats due to wide spread usage of uncontrolled antibiotics. In this study, a total number of 9149 urine samples were collected from R.H Patiala and processed in the Department of Microbiology G. M. C Patiala (January 2013 to December 2013). Urine samples were inoculated on MacConkey’s and blood agar plates and incubated at 370C for 24 hrs. The organisms were identified by colony characters, Gram’s staining, and biochemical reactions. Antimicrobial susceptibility of the isolates was determined against various antimicrobial agents (Hi – Media Mumbai India) by Kirby Bauer DISK diffusion method on Muller Hinton agar plates. Maximum patients were in the age group of 21-30 yrs followed by 31-40 yrs. Males (34%) are less prone to urinary tract infections than females (66%). Culture was positive in 25% of the samples. Escherichia coli was the most common isolate 60.3% followed by Klebsiella pneumoniae 13.5%, Proteus spp. 9% and Staphylococcus aureus 7.6%. Most of the urinary isolates were sensitive to, carbepenems, Aztreonam, Amikacin, and Piperacillin + Tazobactum. All the isolates showed a good sensitivity towards Nitrofurantoin (82%). ESBL production was found to be 70.6% in Escherichia coli and 29.4% in Klebsiella pneumonia. Susceptibility of ESBL producers to Imipenem, Nitrofurantoin and Amikacin were found to be 100%, 76%, and 75% respectively. Uropathogens are increasingly showing resistance to many antibiotics making empiric management of outpatient UTIs challenging. Ampicillin, Cotrimoxazole and Ciprofloxacin should not be used in empiric treatment. Nitrofurantoin could be used in lower urinary tract infection. Knowledge of uropathogens and their antimicrobial susceptibility pattern in a geographical region will help in appropriate and judicious antibiotic usage in a health care setup.

Keywords: Urinary Tract Infection, UTI, antibiotic susceptibility pattern, ESBL.

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Authors: Jasna Prester, Ivana Rašić Bakarić, Božidar Matijević

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Innovations not only contribute to competitiveness of the company but have also positive effects on revenues. On average, product innovations account to 14 percent of companies’ sales. Innovation management has substantially changed during the last decade, because of growing reliance on external partners. As a consequence, a new task for purchasing arises, as firms need to understand which suppliers actually do have high potential contributing to the innovativeness of the firm and which do not. Proper organization of the purchasing function is important since for the majority of manufacturing companies deal with substantial material costs which pass through the purchasing function. In the past the purchasing function was largely seen as a transaction-oriented, clerical function but today purchasing is the intermediate with supply chain partners contributing to innovations, be it product or process innovations. Therefore, purchasing function has to be organized differently to enable firm innovation potential. However, innovations are inherently risky. There are behavioral risk (that some partner will take advantage of the other party), technological risk in terms of complexity of products and processes of manufacturing and incoming materials and finally market risks, which in fact judge the value of the innovation. These risks are investigated in this work. Specifically, technological risks which deal with complexity of the products, and processes will be investigated more thoroughly. Buying components or such high edge technologies necessities careful investigation of technical features and therefore is usually conducted by a team of experts. Therefore it is hypothesized that higher the technological risk, higher will be the centralization of the purchasing function as an interface with other supply chain members. Main contribution of this research lies is in the fact that analysis was performed on a large data set of 1493 companies, from 25 countries collected in the GMRG 4 survey. Most analyses of purchasing function are done by case study analysis of innovative firms. Therefore this study contributes with empirical evaluations that can be generalized.

Keywords: Purchasing function organization, innovation, technological risk, GMRG 4 survey.

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Authors: C. Ardil

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In this study, a model, together with a software tool that implements it, has been developed to determine the performance ratings of employees in an organization operating in the information technology sector using the indicators obtained from employees' online study data. Weighted Sum (WS) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method based on multidimensional decision making approach were used in the study. WS and TOPSIS methods provide multidimensional decision making (MDDM) methods that allow all dimensions to be evaluated together considering specific weights, allowing employees to objectively evaluate the problem of online performance tracking. The application of WS and TOPSIS mathematical methods, which can combine alternatives with a large number of dimensions and reach simultaneous solution, has been implemented through an online performance tracking software. In the application of WS and TOPSIS methods, objective dimension weights were calculated by using entropy information (EI) and standard deviation (SD) methods from the data obtained by employees' online performance tracking method, decision matrix was formed by using performance scores for each employee, and a single performance score was calculated for each employee. Based on the calculated performance score, employees were given a performance evaluation decision. The results of Pareto set evidence and comparative mathematical analysis validate that employees' performance preference rankings in WS and TOPSIS methods are closely related. This suggests the compatibility, applicability, and validity of the proposed method to the MDDM problems in which a large number of alternative and dimension types are taken into account. With this study, an objective, realistic, feasible and understandable mathematical method, together with a software tool that implements it has been demonstrated. This is considered to be preferable because of the subjectivity, limitations and high cost of the methods traditionally used in the measurement and performance appraisal in the information technology sector.

Keywords: Weighted sum, entropy ınformation, standard deviation, online performance tracking, performance evaluation, performance management, multidimensional decision making.

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.

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Authors: Péricles Maia Andrade, Temístocles Damasceno Silva, Hector Luiz Rodrigues Munaro

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The school physical education is going through several changes over the years, and diversification of its content from specific interests is one of the reasons for these changes, soon, the formality in education do not have to stay out, but needs to open up the possibilities offered by the world, so the Mountain Bike, an adventure sport, offers several opportunities for intervention Its application in the school allows diverse interventions in front of the psychomotor development, besides opening possibilities for other contents, respecting the previous experiences of the students in their common environment. The choice of theme was due to affinity with the practice and experience of the Mountain Bike at different levels. Both competitive as recreational, professional standard and amateur, focus as principle the bases of the Cycling, coupled with the inclusion in the Centre for Studies in Management of Sport and Leisure and of the Southwest Bahia State University and the preview of the modality's potential to help the children’s psychomotor development. The goal of this research was to demonstrate like a pilot project the effects of the Mountain Bike as psychomotor instrument in physical education at one of the psychomotor valences, Balance, evaluating Immobility, Static Balance and Dynamic Balance. The methodology used Fonseca’s Psychomotor Battery in 10 students (n=10) of a brazilian public primary’s school, with ages between 9 and 11 years old to use the Mountain Biking contents. The balance’s skills dichotomized in Regular and Good. Regarding the variable Immobility, in the initial test, regardless of gender, 70% (n = 7) were considered Regular. After four months of activity, the Good profile, which had only 30% (n = 3) of the sample, evolved to 60% (n = 6). As in Static and Dynamic Balance there was an increase of 30% (n = 3) and 50% (n = 5) respectively for Good. Between genders, female evolution was better for Good in Immobility and in Static Equilibrium. Already the male evolution was better observed in the Dynamic Equilibrium, with 66.7% (n = 4) for Good. Respecting the particularities of the motor development, an indication of the positive effects of the MTB for the evolution in the balance perceived, necessitating studies with greater sampling.

Keywords: Psychomotricity, balance, mountain biking, education.

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Authors: Pranee Pathomchaiwat

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The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).

Keywords: English language, language learning strategies, English learning achievement, students majoring in English, Business English

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Authors: Y. O’Connor, C. Heavin, S. O’ Connor, J. Gallagher, J. Wu, J. O’Donoghue

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Background: To improve the delivery of paediatric healthcare in low resource settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (inadequate adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (SL eCCM app) as an exemplar. Results: A service blueprint is developed which illustrates how the SL eCCM app can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users.

Keywords: Adherence, community health workers, developing countries, mobile clinical decision support systems, CDSS, service blueprint.

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain builder, WebGL, virtual globe, CesiumJS, tiled map service, TMS, height-map, regular grid, Geovisual analytics, DTM.

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Authors: P. V. Pramila, V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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Authors: M. Alizadeh, M. Mahdavi, M.H. Jouri

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The rangelands, as one of the largest dynamic biomes in the world, have very capabilities. Regulation of greenhouse gases in the Earth's atmosphere, particularly carbon dioxide as the main these gases, is one of these cases. The attention to rangeland, as cheep and reachable resources to sequestrate the carbon dioxide, increases after the Industrial Revolution. Rangelands comprise the large parts of Iran as a steppic area. Rudshur (Saveh), as area index of steppic area, was selected under three sites include long-term exclosure, medium-term exclosure, and grazable area in order to the capable of carbon dioxide’s sequestration of dominated species. Canopy cover’s percentage of two dominated species (Artemisia sieberi Besser & Stipa barbata Desf) was determined via establishing of random 1 square meter plot. The sampling of above and below ground biomass style was obtained by complete random. After determination of ash percentage in the laboratory; conversion ratio of plant biomass to organic carbon was calculated by ignition method. Results of the paired t-test showed that the amount of carbon sequestration in above ground and underground biomass of Artemisia sieberi Besser & Stipa barbata Desf is different in three regions. It, of course, hasn’t any difference between under and surface ground’s biomass of Artemisia sieberi Besser in long-term exclosure. The independent t-test results indicate differences between underground biomass corresponding each other in the studied sites. Carbon sequestration in the Stipa barbata Desf was totally more than Artemisia sieberi Besser. Altogether, the average sequestration of the long-term exclosure was 5.842gr/m², the medium-term exclosure was 4.115gr/m², and grazable area was 5.975gr/m² so that there isn’t valuable statistical difference in term of total amount of carbon sequestration to three sites.

Keywords: Carbon sequestration, the Industrial Revolution, greenhouse gases, Artemisia sieberi Besser, Stipa barbata Desf, steppic rangelands

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: Business intelligence, business intelligence capability, decision making, decision quality.

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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

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

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

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Authors: Stamatios A. Theocharis, George A. Tsihrintzis

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One of the most important factors for the success of e-government is training and preparing the workforce of the public sector. As changes and innovation in the public sector progress at a very slow pace and more slowly than in the private sector, issues related to human resources require special care. This is because the workforce will eventually seize the opportunities of the technological solutions used in e-Government. Thus, the central administration should provide employees with continuous and focused training not only on new technologies but also on a wide range of subjects and also improve interdepartmental interaction.

To achieve all this, new methods and training tools need to be implemented in addition to assessment of the employees. In this spirit, we propose the development of an educational platform with user personalization features. We propose the development of this platform using Moodle as the basic tool. Incorporating a personalization mechanism is very important since different employees have different backgrounds, education levels, computer skills, or different capability to develop further. Key features of the proposed platform include, besides typical e-learning tools, communities organized in order to exchange experiences and knowledge, groups of users based on certain criteria, automatic evaluation of users and potential self-education and self-assessment. In its fully developed form, this platform can be part of a more comprehensive knowledge management system for the public sector.

Keywords: e-Government, civil employees education, education technologies.

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively recent concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This is clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification, cellular connectivity, connectivity to the vehicle computer, and connectivity to analog and digital sensors by means of a specially targeted design of expansion board. Specifically, the latter offers a number of adaptability features to cope with the diverse sensor types employed in different vehicles. In standard mode, the IoT sensor node communicates to the data center through cellular network, transmitting all digital/digitized sensor data, IoT device identity and position. Moreover, the proposed IoT sensor node offers connectivity, through WiFi and an appropriate application, to smart phones or tablets allowing the registration of additional vehicle- and driver-specific information and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware.

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: E. L. Suarez, D. E. Meeroff, Y. Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: Community resilience, conflation, flood risk, nuisance flooding.

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