Search results for: binary decision diagram

Authors: Behrooz Balaei, Suzanne Wilkinson, Regan Potangaroa, Larry Abel, Philip McFarlane

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Water supply system failure has serious direct and indirect effects on people wellbeing. Post-disaster water system serviceability depends on a variety of factors from technical characteristics to social, economic, and organizational attributes of communities. This paper tests the organizational factors affecting water supply resilience to outline how these factors contributed to previous disasters. To do so, a framework is briefly introduced in this study to provide a clear guide to identify the significant relevant organizational factors. Then the factors affecting water serviceability following a disaster are outlines. Next, these factors are measured in the case of Tropical Cyclone Pam, which hit Vanuatu in March 2015. Reviewing the existing literature has also been carried out to obtain a comprehensive understanding of the background A site visit and a series of interviews have also been undertaken following the cyclone to collect site-specific data and information. In the end, the organizational factors were ranked to enable decision makers to identify significance of each factor compared to the others.

Keywords: water supply, resilience, organizational capacity, Vanuatu, Tropical Cyclone Pam

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Authors: Abdullah Ali H. Ahmadini, Firoz Ahmad, Intekhab Alam

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Geometric programming problem (GPP) is a well-known non-linear optimization problem having a wide range of applications in many engineering problems. The structure of GPP is quite dynamic and easily fit to the various decision-making processes. The aim of this paper is to highlight the bounded solution method for GPP with special reference to variation among right-hand side parameters. Thus this paper is taken the advantage of two-level mathematical programming problems and determines the solution of the objective function in a specified interval called lower and upper bounds. The beauty of the proposed bounded solution method is that it does not require sensitivity analyses of the obtained optimal solution. The value of the objective function is directly calculated under varying parameters. To show the validity and applicability of the proposed method, a numerical example is presented. The system reliability optimization problem is also illustrated and found that the value of the objective function lies between the range of lower and upper bounds, respectively. At last, conclusions and future research are depicted based on the discussed work.

Keywords: varying parameters, geometric programming problem, bounded solution method, system reliability optimization

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Authors: Maria Ledinskaya

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This paper examines the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts in the context of Agile, Lean, and Hybrid project management. It is part case study and part literature review. To date, relatively little has been written about non-traditional project management approaches in heritage conservation. This paper seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation, by referencing their practical application on a recent museum-based conservation project. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre for Visual Arts by private collectors Michael and Joyce Morris. The first part introduces the chronological timeline and key elements of the project. It describes a medium-size conservation project of moderate complexity, which was planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown condition and materials, unconfirmed budget. The project was also impacted by the unknown unknowns of the COVID-19 pandemic, such as indeterminate lockdowns, and the need to accommodate social distancing and remote communications. The author, a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Collection Conservation Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. Subsequent sections examine the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment, due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Collection Conservation Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, as well as the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics, particularly with respect to change management, bespoke ethics, shared decision-making, and value-based cost-benefit conservation strategy. The author concludes that the Morris Collection Conservation Project had multiple Agile and Lean features which were instrumental to the successful delivery of the project. These key features are identified as distributed decision making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point largely in favour of a Hybrid model which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: project management, conservation, waterfall, agile, lean, hybrid

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Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Y. R. Lai, J. C. Jehng, T. T. Chang

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Team is a popular job design in the management settings. Because people on a team need to work together to complete a lot of tasks, the interaction between team members strongly influences team effectiveness. The study examines the effect of social capital and empowering leadership on team cohesion. There are three facets of social capital: structural facet, relational facet, and cognitive facet. Empowering leadership includes enhancing the meaningfulness of work, fostering participation in decision making, expressing confidence in high performance, and providing autonomy from bureaucratic constraints. Data were collected from 181 team members of 47 teams in the real estate agency industry. The results show that the relational social capital, enhancing the meaningfulness of work, and providing autonomy from bureaucratic constraints are positively related to two dimensions of team cohesion: sense of belonging and feelings of moral. Additionally, expressing confidence in high performance is negatively related to sense of belonging.

Keywords: social capital, empowering leadership, team cohesion, team effectiveness

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Hussam Alrabaiah

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Some new projects (new proposed harbor, recreational projects) are considered in the eastern coasts of Dammam city, Saudi Arabia. Dredging operations would significantly alter coast hydrological and sediment transport processes. It is important that the project areas must keep flushing the fresh sea water in and out with good water quality parameters, which are currently facing increased pressure from urbanization and navigation requirements in conjunction with industrial developments. A suspended solids or sediments are expected to affect the flora and fauna in that area. Governing advection-diffusion equations are considered to understand the consequences of such projects. A numerical modeling study is developed to study the effect of dredging and, in particular, the suspended sediments concentrations (mg/L) changed in the region. The results were obtained using finite element method using an in-house or commercial software. Results show some consistency with data observed in that region. Recommendations based on results could be formulated for decision makers to protect the environment in the long term.

Keywords: finite element, method, suspended solids transport, advection-diffusion

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Authors: Brian Basvi

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A technique for analyzing a security's intrinsic value is called fundamental analysis. It involves looking at relevant financial, economic, and other qualitative and quantitative aspects. Earnings Per Share (EPS), a crucial metric in fundamental analysis, is calculated by dividing a company's net income by the total number of outstanding shares. With more than 70 listed businesses, the Zimbabwe Stock Exchange (ZSE) is the primary stock exchange in Zimbabwe. This study applies the EPS financial ratio and stock valuation techniques to historical stock data from 68 companies listed on the Zimbabwe Stock Exchange. According to a ZSE study, EPS significantly affects share prices that are listed on the market. The study's objective was to assess how fundamental analysis affected the idea of EPS in ZSE stock valuation. It concluded that EPS is an important consideration for investors when they make judgments about their investments. According to the study's findings, fundamental analysis is a useful tool for ZSE investors since it offers insightful information about a company's financial performance and aids in decision-making. Investors can have a better understanding of a company's underlying worth and prospects for future growth by looking into EPS and other basic aspects.

Keywords: fundamental analysis, stock valuation, EPS, share pricing

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Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: Witthaya Mekhum, Napasri Suwanajote, Isara Sangprasert

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This research on logo design of pajamas, OTOP product of Sainoi community, Sainoi district, Nonthanuri Province is a participatory action research aiming to find the logo for pajamas, an OTOP product of Sainoi community. Sample of this research is 50 local residents from Sainoi community in Sainoi district, Nonthanuri Province. The questionnaire consisted of 4 main parts. Part 1: factors that influence the decisions of consumers; Part 2: characteristics of the materials used in the design; Part 3: attitude assessment and needs of consumers about logo designing to develop marketing channels; Part 4: suggestions. Interviews were conducted. For data analysis, checklist items were analyzed with frequency and percentage. Open-end items were analyzed by summarizing and using ratio scale and mean and standard deviation. The research results showed that the design, cutting and fabric affect the decision of the consumers. They want design to be decent and beautiful. Illustrations used in graphic design logos should be Lines. Fonts should be English letters and the color of the font should be the same color.

Keywords: design, logo, OTOP product, pajamas

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Authors: Dina Safrina

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This paper aims to discuss the suitability of tax administration in Indonesia based on Islamic Shari'a by looking at Abu Yusuf's idea of taxation. This research is a qualitative research and using data collection method by library research, that is by studying, deepening and citing theories or concepts from a number of literature. The purpose of this paper is to find out whether taxation in Indonesia is consistent with the thinking of Islamic economists, namely Abu Yusuf's idea which became known by economists as the canons of taxation. The ability to pay, lax time giving for taxpayers and the centralization of decision-making in the tax administration are some of the principles it emphasizes. In taxation he recommends the use of the Muqassamah (Proportional Tax) system rather than the Mixed (Fixed Tax) system. In this case, the determination of tax rates in Indonesia there are using fixed tax system, proportional tax, progressive tax and regressive tax. Abu Yusuf opposed the existence of Qabalah institution (the guarantor of tax payments to the state) at the time and suggested a tax administration centered and paid directly to the state. This is in accordance with those already applied in Indonesia where tax collection is done centrally. The tax system in Indonesia using self assessment system, which is the authority and responsibility given by the government to the taxpayer to calculate, pay and report the tax itself becomes the gap for taxpayers to commit fraud. Prerequisites that must be met for the success of this system is with the tax consciousness, tax honesty, tax mindedness, and tax discipline.

Keywords: Abu Yusuf, Indonesia, tax, tax administration

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Alejandra Sierra, Maria de los Angeles Covarrubias, Guillermo Julian Gonzalez, Noe Alfaro

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The objective of this study was to identify the cultural dimensions of the terms unplanned pregnancy and unwanted pregnancy built by adolescent women, through the focus of the social representations. Two associative methods were used: free listings and the paired comparison. 72 female students between the ages of 15 and 19 were interviewed, from the downtown area of Leon Guanajuato, Mexico. Words related to inducer terms were classified into five thematic categories: facilitators, consequences, reactions, expectations, and lexicon. The results showed that the social representations of unplanned pregnancy highlighted elements related to economic difficulties and negative emotional aspects, while unwanted pregnancy was associated with negative emotional aspects such as anger, anxiety, and sadness. The meanings each person attributes to terms related to pregnancy are culturally constructed and differ between populations; therefore, more attention should be paid to understanding the cultural meanings and attitudes of people in fertility decision-making, including also the views of adolescent men and other types of population, stratified by age groups and social conditions.

Keywords: adolescent, qualitative research, unplanned pregnancy, unwanted pregnancy

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

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The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

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Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

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This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

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Authors: Murad A. Bein

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This paper empirically examines the time-varying relationship and spillover effects between the international crude oil price and ten emerging equity markets, namely three oil-exporting countries (Brazil, Mexico, and Russia) and seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Poland, Romania, and Slovakia). The results revealed that there are spillover effects from oil markets into almost all emerging equity markets save Slovakia. Besides, the oil supply glut had a homogenous effect on the emerging markets, both net oil-exporting, and oil-importing countries (CEE). Further, the time variance drastically increased during financial turmoil. Indeed, the time variance remained high from 2009 to 2012 in response to aggregate demand shocks (global financial crisis and Eurozone debt crisis) and quantitative easing measures. Interestingly, the time variance was slightly higher for the oil-exporting countries than for some of the CEE countries. Decision-makers in emerging economies should therefore seek policy coordination when dealing with financial turmoil.

Keywords: crude oil, spillover effects, emerging equity, time-varying, aggregate demand shock

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Authors: Tahsien Mohamed Okasha

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Simulation is one of the emerging educational strategies that depend on the creation of scenarios to imitate what could happen in real life. At the time of COVID, we faced big obstacles in medical education, specially the clinical part and how we could apply it, the simulation was the golden key. Simulation is a very important tool of education for medical sector students, through creating a safe, changeable, quiet environment with less anxiety level for students to practice and to have repeated trials on their competencies. That impacts the level of practice, achievement, and the way of acting in real situations and experiences. A blind Random sample of students from different specialties and colleges who came and finished their training in an integrated environment was collected and tested, and the responses were graded from (1-5). The results revealed that 77% of the studied subjects agreed that dealing and interacting with different medical sector candidates in the same place was beneficial. 77% of the studied subjects agreed that simulations were challenging in thinking and decision-making skills .75% agreed that using high-fidelity manikins was helpful. 75% agree .76% agreed that working in a safe, prepared environment is helpful for realistic situations.

Keywords: simulation, clinical training, education, medical sector students

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Authors: Abel Kahuni

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Cooperative game theory (CGT) postulates that groups of players are crucial units of the decision-making and impose cooperative behaviour. Accordingly, cooperative games are regarded as competition between coalitions of players, rather than between individual players. However, the basic supposition in CGT is that the cooperative is formed by all players. One of the emerging questions in CGT is how to develop cooperatives and fairly allocate the payoff. Cooperative Game Theory (CGT) may provide a framework and insights into the ways small holder farmers in rural resettlements may develop competitive advantage through marketing cooperatives. This conceptual paper proposes a non-competition model for small holder farmers of homogenous agri-commodity under CGT conditions. This paper will also provide brief insights into to the theory of cooperative games in-order to generate an understanding of CGT, cooperative marketing gains and its application in small holder farming arrangements. Accordingly, the objective is to provide a basic introduction to this theory in connection with economic competitive theories in the context of small holder farmers. The key value proposition of CGT is the equitable and fair sharing of cooperative gains.

Keywords: game theory, cooperative game theory, cooperatives, competition

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Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

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Authors: Saima Salehjee, Mike Watts

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In our school-based world, we are commonly confronted by young people for whom the study of science is an unpalatable ‘other world’: they simply do not see themselves as science (sciencey) people. To be clear, we are not interested in all young people becoming career scientists – although some small modicum of that would be quite agreeable. We are, though, keen to form or transform (trans(form)) their appreciations of science and retain open minds on matters scientific to develop the feeling of being ‘sciencey’ with or without the aspiration of becoming scientists. Our discussion in this paper draws upon research undertaken in a co-education primary- and lower-secondary school in Scotland, and our arguments chart the trans(formations) of thirty under-representative and under-researched Scottish South-Asian Muslim students (aged 11-13) over a school term. We use science identity theory as the basis for our analysis: what it means to be ‘sciencey’ and whether (or not) structural forces have impacted their decision of being ‘sciencey’. This work offers new insights into how Scottish, South-Asian, and Muslim students perceive and engage with in and out of school science and highlight some science nudges aimed to support their development of being ‘sciencey’.

Keywords: science identity, science nudges, transformative moments, south-Asian, Muslim, scottish, sciencey

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Authors: Arosha Rashmi De Silva, Ananda Chandrasekara

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This study seeks to comprehensively examine the influence of fast-food consumption and physical activity levels on the body weight of young employees within the private sector of Sri Lanka. The escalating popularity of fast food has raised concerns about its nutritional content and associated health ramifications. To investigate this phenomenon, a cohort of 100 individuals aged between 25 and 45, employed in Sri Lanka's private sector, participated in this research. These participants provided socio-demographic data through a standardized questionnaire, enabling the characterization of their backgrounds. Additionally, participants disclosed their frequency of fast-food consumption and engagement in physical activities, utilizing validated assessment tools. The collected data was meticulously compiled into an Excel spreadsheet and subjected to rigorous statistical analysis. Descriptive statistics, such as percentages and proportions, were employed to delineate the body weight status of the participants. Employing chi-square tests, our study identified significant associations between fast-food consumption, levels of physical activity, and body weight categories. Furthermore, through binary logistic regression analysis, potential risk factors contributing to overweight and obesity within the young employee cohort were elucidated. Our findings revealed a disconcerting trend, with 6% of participants classified as underweight, 32% within the normal weight range, and a substantial 62% categorized as overweight or obese. These outcomes underscore the alarming prevalence of overweight and obesity among young private-sector employees, particularly within the bustling urban landscape of Colombo, Sri Lanka. The data strongly imply a robust correlation between fast-food consumption, sedentary behaviors, and higher body weight categories, reflective of the evolving lifestyle patterns associated with the nation's economic growth. This study emphasizes the urgent need for effective interventions to counter the detrimental effects of fast-food consumption. The implementation of awareness campaigns elucidating the adverse health consequences of fast food, coupled with comprehensive nutritional education, can empower individuals to make informed dietary choices. Workplace interventions, including the provision of healthier meal alternatives and the facilitation of physical activity opportunities, are essential in fostering a healthier workforce and mitigating the escalating burden of overweight and obesity in Sri Lanka

Keywords: fast food consumption, obese, overweight, physical activity level

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Authors: Bassem Boshra Thabet, Mohammed Ibrahim Elsabagh, Mohammad Adly Talaat

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The number of cellular mobile phone users has increased enormously worldwide over the last two decades. Consequently, the monitoring of the performance of the Mobile Network Operators (MNOs) in terms of network coverage and broadband signal strength has become vital for both of the MNOs and regulators. This monitoring helps telecommunications operators and regulators keeping the market playing fair and most beneficial for users. However, the adopted methodologies to facilitate this continuous monitoring process are still problematic regarding cost, effort, and reliability. This paper introduces My Operator Coverage (MOC) system that is using Internet of Things (IoT) concepts and tools to monitor the MNOs performance using a crowd-sourced real-time methodology. MOC produces robust and reliable geographical maps for the user-perceived quality of the MNOs performance. MOC is also meant to enrich the telecommunications regulators with concrete, and up-to-date information that allows for adequate mobile market management strategies as well as appropriate decision making.

Keywords: mobile performance monitoring, crowd-sourced applications, mobile broadband performance, cellular networks monitoring

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Authors: Ming-Ta Yang, Jyh-Cherng Gu, Chun-Wei Huang, Jin-Lung Guan

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Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.

Keywords: circuit breaker, condition base maintenance, intelligent electronic device, time base maintenance, SCADA

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

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Authors: Mahkameh Asadi, Habibollah Dadgar

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The precise definition margin of high and low-grade glioma is crucial for choosing best treatment approach after surgery and radio-chemotherapy. The aim of the current study was to assess the O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) positron emission tomography (PET)/computed tomography (CT) in patients with low (LGG) and high grade glioma (HGG). We retrospectively analyzed 18F-FET PET/CT of 10 patients (age: 33 ± 12 years) with suspicious for recurrent LGG and HGG. The final decision of recurrence was made by magnetic resonance imaging (MRI) and registered clinical data. While response to radio-chemotherapy by MRI is often complex and sophisticated due to the edema, necrosis, and inflammation, emerging amino acid PET leading to better interpretations with more specifically differentiate true tumor boundaries from equivocal lesions. Therefore, integrating amino acid PET in the management of glioma to complement MRI will significantly improve early therapy response assessment, treatment planning, and clinical trial design.

Keywords: positron emission tomography, amino acid positron emission tomography, magnetic resonance imaging, low and high grade glioma

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

Abstract:

This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

Procedia PDF Downloads 287

Authors: Rania Ajmi, Faiza Allouche Khebour, Aude Nuscia Taibi, Sirine Essasi

Abstract:

Urban green spaces (UGS) as an important contributor can be a significant part of sustainable development. A spatial method was employed to assess and map the spatial distribution of UGS in five districts in Sousse, Tunisia. Ecological management of UGS is an essential factor for the sustainable development of the city; hence the municipality of Sousse has decided to support the districts according to different green spaces characters. And to implement this policy, (1) a new GIS web application was developed, (2) then the implementation of the various green spaces was carried out, (3) a spatial mapping of UGS using Quantum GIS was realized, and (4) finally a data processing and statistical analysis with RStudio programming language was executed. The intersection of the results of the spatial and statistical analyzes highlighted the presence of an imbalance in terms of the spatial UGS distribution in the study area. The discontinuity between the coast and the city's green spaces was not designed in a spirit of network and connection, hence the lack of a greenway that connects these spaces to the city. Finally, this GIS support will be used to assess and monitor green spaces in the city of Sousse by decision-makers and will contribute to improve the well-being of the local population.

Keywords: distributions, GIS, green space, imbalance, spatial analysis

Procedia PDF Downloads 204

Authors: Walaa W. Diab

Abstract:

The present paper offers a fundamental critique of the macroeconomic effects of fiscal policy after it surveys the theoretical and empirical literature on the macroeconomic effects of fiscal policy. It emphasizes the importance of the fiscal policy after reviewing the revolution of almost all economic schools and bringing them in one summarized figure; the paper links the developmental role of the fiscal policy with the objectives and measures of the economic transformation. Thus, the importance of this study can be seen from several perspectives: First, it reviews the theoretical harvest of fiscal policy and provides a comparison between the main revolutionary Economic thoughts; the classical school, Keynesian school, and monetarist school. Then it turns to conclude the fiscal policy from the new consensus mainstream economic schools. Finally, the study presents grouped and classified empirical pieces of evidence as it divides those empirical studies into two groups; the first for developed economies and the second for developing ones. So the study is important also for the policymakers as well as scholars as it gives its recommendations upon the last analysis in the form of ‘policy implications’. The paper also presents a deeper look into the evaluation approaches of the macroeconomic effects of fiscal policy at the empirical level. Thus it is useful for both researchers and decision makers.

Keywords: economic transformation, fiscal policy, macroeconomic effects, public spending

Procedia PDF Downloads 303

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

Procedia PDF Downloads 397