Search results for: multi-criteria decision making methods

Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to realworld data.

Keywords: rule induction, decision table, missing data, noise

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Authors: Anum Obaid, Bushra Noor, Zoshia Zainab

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In South Asian countries, Pakistan faces significant public health challenges regarding maternal and neonatal health (MNH). Despite global efforts to improve maternal, newborn, child, and health (MNCH) outcomes through initiatives like the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs), high maternal and neonatal mortality rates persist. In patriarchal societies, cultural norms, family dynamics, and gender roles heavily influence healthcare accessibility and decision-making processes, often leading to delayed and inadequate maternal care. Addressing these socio-cultural barriers and enhancing healthcare resources is crucial to improving maternal health outcomes in areas like Faisalabad. A qualitative study was conducted involving two groups of informants: gynecologists practicing in private clinics and first-time pregnant women receiving care in government hospitals. Data collection included obtaining institutional permission, conducting semi-structured in-depth interviews, and using non-probability sampling techniques. A proactive strategy to overcome maternal health challenges involves using aversion therapy and disseminating knowledge among family members. This approach aims to foster a deep understanding within the family unit regarding the importance of maternal well-being, thereby creating a supportive environment and facilitating informed decision-making related to healthcare access and lifestyle choices. The findings indicate that maternal health is compromised both physiologically and psychologically, with significant implications for the baby's health. Mental well-being is profoundly affected, largely due to familial behavior and entrenched cultural taboos.

Keywords: maternal health, neonatal health, socio-cultural norms, primigravida women, gynecologist, familial conduct, cultural taboos

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Authors: Sevgi Özlem Bulu, Arif Furkan Mendi, Tolga Erol, İzzet Gökhan Özbilgin

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The rapid progress of technology in today's competitive conditions has also accelerated companies' technology development activities. As a result, companies are paying more attention to R&D studies and are beginning to allocate a larger share to R&D projects. A more systematic, comprehensive, target-oriented implementation of R&D studies is crucial for the company to achieve successful results. As a consequence, Technology Roadmap (TRM) is gaining importance as a management tool. It has critical prospects for achieving medium and long term success as it contains decisions about past business, future plans, technological infrastructure. When studies on TRM are examined, projects to be placed on the roadmap are selected by many different methods. Generally preferred methods are based on multi-criteria decision making methods. Management of selected projects becomes an important point after the selection phase of the projects. At this stage, TRM are used. TRM can be created in many different ways so that each institution can prepare its own Technology Roadmap according to their strategic plan. Depending on the intended use, there can be TRM with different layers at different sizes. In the evaluation phase of the R&D projects and in the creation of the TRM, HAVELSAN, Turkey's largest defense company in the software field, carries out this process with great care and diligence. At the beginning, suggested R&D projects are evaluated by the Technology Management Board (TMB) of HAVELSAN in accordance with the company's resources, objectives, and targets. These projects are presented to the TMB periodically for evaluation within the framework of certain criteria by board members. After the necessary steps have been passed, the approved projects are added to the time-based TRM, which is composed of four layers as market, product, project and technology. The use of a four-layered roadmap provides a clearer understanding and visualization of company strategy and objectives. This study demonstrates the benefits of using TRM, four-layered Technology Roadmapping and the possibilities for the institutions in the defense industry.

Keywords: technology roadmap, research and development project, project selection, research development in defense industry

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Authors: Cate MacMillan, Nicholas J. Stevens, Johanna Rosier, Steven Boyd

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Choosing where to live is an important decision for anybody, however, this decision is more complex if you are an adult with intellectual disability. Our research asked adults with intellectual disability, parents and carers and disability, housing and built environment decision makers what they considered important in deciding where to live. If medical advances continue to improve the longevity of adults with intellectual disability, many of these adults will outlive their parents. With appropriate community support, and in appropriately designed neighbourhoods, many will be able to live independently. Our research suggests that the key to achieving independent living as an adult with intellectual disability is not so much about the house but the type of neighbourhood and its design. This paper presents the results of interviews and details a practical approach which will better inform urban development decision-makers in establishing safe, inclusive and accessible neighbourhood design.

Keywords: inclusion, independent living, intellectual disability, neighbourhoods, systems thinking, urban design and planning

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Authors: Christina Zourna, Ioanna Papavassiliou-Alexiou

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Drama in Education (DiE) is a dynamic experiential method that can be used in many interdisciplinary contexts. In the Educational and Social Policy Department, University of Macedonia, Thessaloniki, Greece, DiE is being used as a core method for developing professional competences in pre- and postgraduate courses as well as adult education training programs. In this presentation, an innovative DiE application will be described concerning the development of educational leaders’ skills necessary to meet unprecedented, unexpected challenges in the 21st century schools. In a non-threatening risk-taking no-penalty environment, future educational leaders live-in-role problems, challenges, and dilemmas before having to face similar ones in their profession. Through personal involvement, emotional engagement, and reflection, via individual and group activities, they experience the behaviour, dilemmas, decision-making processes, and informed choices of a recognized leader and are able to make connections with their own life. As pretext serves the life of Alexander the Great, the Macedonian King who defeated the vast Persian empire in the 4th century BC and, by uniting all Greeks, conquered the up-to-date known eastern world thanks to his authentic leadership skills and exceptional personality traits. Since the early years of his education mastered by the famous Greek philosopher Aristotle, Alexander proved his unique qualities by providing the world with the example of an undeniably genuine, inspirational, effective, and most recognizable authentic leader. Through questionnaires and individual interviews, participants in these workshops revealed how they developed active listening, empathy, creativity, imagination, critical strategic and out-of-the-box thinking, cooperation and own vision communicating, crisis management skills, self-efficacy, self-awareness, self-exposure, information management, negotiation and inspiration skills, enhanced sense of responsibility and commitment, and decision-making skills.

Keywords: drama in education method, educational leadership, professional competences, skills’ development

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Authors: Michelle Eichinger, Upali Nanda

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Behavior choices during college years can establish the pattern of lifelong healthy living. Nearly 1/3rd of American college students are either overweight (25 < BMI < 30) or obese (BMI > 30). In addition, overweight/obesity contributes to depression, which is a rising epidemic among college students, affecting academic performance and college drop-out rates. Overweight and obesity result in an imbalance of energy consumption (diet) and energy expenditure (physical activity). Overweight/obesity is a significant contributor to heart disease, diabetes, stroke, physical disabilities and some cancers, which are the leading causes of death and disease in the US. There has been a significant increase in obesity and obesity-related disorders such as type 2 diabetes, hypertension, and dyslipidemia among people in their teens and 20s. Historically, the evidence-based interventions for obesity prevention focused on changing the health behavior at the individual level and aimed at increasing awareness and educating people about nutrition and physical activity. However, it became evident that the environmental context of where people live, work and learn was interdependent to healthy behavior change. As a result, a comprehensive approach was required to include altering the social and built environment to support healthy living. College campus provides opportunities to support lifestyle behavior and form a health-promoting culture based on some key point of decisions such as stairs/ elevator, walk/ bike/ car, high-caloric and fast foods/balanced and nutrient-rich foods etc. At each point of decision, design, can help/hinder the healthier choice. For example, stair well design and motivational signage support physical activity; grocery store/market proximity influence healthy eating etc. There is a need to collate the vast information that is in planning and public health domains on a range of successful point of decision prompts, and translate it into architectural guidelines that help define the edge condition for critical point of decision prompts. This research study aims to address healthy behaviors through the built environment with the questions, how can we make the healthy choice an easy choice through the design of critical point of decision prompts? Our hypothesis is that well-designed point of decision prompts in the built environment of college campuses can promote healthier choices by students, which can directly impact mental and physical health related to obesity. This presentation will introduce a combined health and architectural framework aimed to influence healthy behaviors through design applied for college campuses. The premise behind developing our concept, point-of-decision design (PODD), is healthy decision-making can be built into, or afforded by our physical environments. Using effective design intervention strategies at these 'points-of-decision' on college campuses to make the healthy decision the default decision can be instrumental in positively impacting health at the population level. With our model, we aim to advance health research by utilizing point-of-decision design to impact student health via core sectors of influences within college settings, such as campus facilities and transportation. We will demonstrate how these domains influence patterns/trends in healthy eating and active living behaviors among students. how these domains influence patterns/trends in healthy eating and active living behaviors among students.

Keywords: architecture and health promotion, college campus, design strategies, health in built environment

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Authors: R. Tariq, R. Lee

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Background: Additional demands placed on senior clinical teams with ongoing COVID-19 management has accelerated the need to harness the wider healthcare professional resources and upskill them to take on greater clinical responsibility safely. The UK NHS Long Term Plan (2019)¹ emphasises the importance of expanding Advanced Practitioners’ (APs) roles to take on more clinical diagnostic responsibilities to cope with increased demand. In acute settings, APs are often the first point of care for patients and require training to take on initial triage responsibilities efficiently and safely. Critically, their roles include determining which onward services the patients may require, and assessing whether they can be treated at home, avoiding unnecessary admissions to the hospital. Dem Dx is a Clinical Reasoning Platform (CRP) that claims to help frontline healthcare professionals independently assess and triage patients. It guides the clinician from presenting complaints through associated symptoms to a running list of differential diagnoses, media, national and institutional guidelines. The objective of this study was to compare the clinical referral rates and guidelines adherence registered by the HMR Urgent Community Care Team (UCCT)² and Dem Dx recommendations using retrospective cases. Methodology: 192 cases seen by the UCCT were anonymised and reassessed using Dem Dx clinical pathways. We compared the UCCT’s performance with Dem Dx regarding the appropriateness of onward referrals. We also compared the clinical assessment regarding adherence to NICE guidelines recorded on the clinical notes and the presence of suitable guidance in each case. The cases were audited by two medical doctors. Results: Dem Dx demonstrated appropriate referrals in 85% of cases, compared to 47% in the UCCT team (p<0.001). Of particular note, Dem Dx demonstrated an almost 65% (p<0.001) improvement in the efficacy and appropriateness of referrals in a highly experienced clinical team. The effectiveness of Dem Dx is in part attributable to the relevant NICE and local guidelines found within the platform's pathways and was found to be suitable in 86% of cases. Conclusion: This study highlights the potential of clinical decision support, as Dem Dx, to improve the quality of onward clinical referrals delivered by a multidisciplinary team in primary care. It demonstrated that it could support healthcare professionals in making appropriate referrals, especially those that may be overlooked by providing suitable clinical guidelines directly embedded into cases and clear referral pathways. Further evaluation in the clinical setting has been planned to confirm those assumptions in a prospective study.

Keywords: advanced practitioner, clinical reasoning, clinical decision-making, management, multidisciplinary team, referrals, triage

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Zahid Hussain

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Provincial Disaster Management Authority (PDMA) Punjab was established under NDM Act 2010 and now working under Senior Member Board of Revenue, deals with the whole spectrum of disasters including preparedness, mitigation, early warning, response, relief, rescue, recovery and rehabilitation. The District Disaster Management Authorities (DDMA) are acting as implementing arms of PDMA in the districts to respond any disaster. DDMAs' role is very important in disaster mitigation, response and recovery as they are the first responder and closest tier to the community. Keeping in view the significant role of DDMAs, technical and human resource capacity are need to be checked. For calculating the technical efficiencies of District Disaster Management Authority (DDMA) in Punjab, three inputs like number of labour, the number of transportation and number of equipment, two outputs like relief assistance and the number of rescue and 25 districts as decision making unit have been selected. For this purpose, 8 years secondary data from 2005 to 2012 has been used. Data Envelopment Analysis technique has been applied. DEA estimates the relative efficiency of peer entities or entities performing the similar tasks. The findings show that all decision making unit (DMU) (districts) are inefficient on techonological and scale efficiency scale while technically efficient on pure and total factor productivity efficiency scale. All DMU are found technically inefficient only in the year 2006. Labour and equipment were not efficiently used in the year 2005, 2007, 2008, 2009 and 2012. Furthermore, only three years 2006, 2010 and 2011 show that districts could not efficiently use transportation in a disaster situation. This study suggests that all districts should curtail labour, transportation and equipment to be efficient. Similarly, overall all districts are not required to achieve number of rescue and relief assistant, these should be reduced.

Keywords: DEA, DMU, PDMA, DDMA

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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Authors: Areti Angeliki Veroniki, Sofia Tsokani, Evangelos Paraskevaidis, Dimitris Mavridis

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The plethora of diagnostic test accuracy (DTA) studies has led to the increased use of systematic reviews and meta-analysis of DTA studies. Clinicians and healthcare professionals often consult DTA meta-analyses to make informed decisions regarding the optimum test to choose and use for a given setting. For example, the human papilloma virus (HPV) DNA, mRNA, and cytology can be used for the cervical intraepithelial neoplasia grade 2+ (CIN2+) diagnosis. But which test is the most accurate? Studies directly comparing test accuracy are not always available, and comparisons between multiple tests create a network of DTA studies that can be synthesized through a network meta-analysis of diagnostic tests (DTA-NMA). The aim is to summarize the DTA-NMA methods for at least three index tests presented in the methodological literature. We illustrate the application of the methods using a real data set for the comparative accuracy of HPV DNA, HPV mRNA, and cytology tests for cervical cancer. A search was conducted in PubMed, Web of Science, and Scopus from inception until the end of July 2019 to identify full-text research articles that describe a DTA-NMA method for three or more index tests. Since the joint classification of the results from one index against the results of another index test amongst those with the target condition and amongst those without the target condition are rarely reported in DTA studies, only methods requiring the 2x2 tables of the results of each index test against the reference standard were included. Studies of any design published in English were eligible for inclusion. Relevant unpublished material was also included. Ten relevant studies were finally included to evaluate their methodology. DTA-NMA methods that have been presented in the literature together with their advantages and disadvantages are described. In addition, using 37 studies for cervical cancer obtained from a published Cochrane review as a case study, an application of the identified DTA-NMA methods to determine the most promising test (in terms of sensitivity and specificity) for use as the best screening test to detect CIN2+ is presented. As a conclusion, different approaches for the comparative DTA meta-analysis of multiple tests may conclude to different results and hence may influence decision-making. Acknowledgment: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Extension of Network Meta-Analysis for the Comparison of Diagnostic Tests ” (MIS 5047640).

Keywords: colposcopy, diagnostic test, HPV, network meta-analysis

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: S. Hasan, I. Beshara

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Infrastructure maintenance is a great challenge facing sustainable development of infrastructure assets due to the high cost of passive implementation of a sustainable maintenance plan. An assessment model of sustainable maintenance for highway infrastructure projects in Egypt is developed in this paper. It helps in improving the implementation of sustainable maintenance criteria. Thus, this paper has applied the analytical hierarchy processes (AHP) to rank and explore the weight of 26 assessment indicators using three hierarchy levels containing the main sustainable categories and subcategories with related indicators. Overall combined weight of each indicator for sustainable maintenance evaluation has been calculated to sum up to a sustainable maintenance performance index (SMI). The results show that the factor "Preventive maintenance cost" has the highest relative contribution factor among others (13.5%), while two factors of environmental performance have the least weights (0.7%). The developed model aims to provide decision makers with information about current maintenance performance and support them in the decision-making process regarding future directions of maintenance activities. It can be used as an assessment performance tool during the operation and maintenance stage. The developed indicators can be considered during designing the maintenance plan. Practices for successful implementation of the model are also presented.

Keywords: analytical hierarchy process, assessment performance Model, KPIs for sustainable maintenance, sustainable maintenance index

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Authors: Dana Al-Qattan, Faiza Goodarzi, Heba Al-Resheedan, Kawther Shehab, Shoug Al-Ansari

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This project involves working with different types of forecasting methods and facility planning tools to help the company we have chosen to improve and reduce its inventory, increase its sales, and decrease its wastes and losses. The methods that have been used by the company have shown no improvement in decreasing the annual losses. The research made in the company has shown that no interest has been made in exploring different techniques to help the company. In this report, we introduce several methods and techniques that will help the company make more accurate forecasts and use of the available space efficiently. We expect our approach to reduce costs without affecting the quality of the product, and hence making production more viable.

Keywords: production planning, inventory management, inventory control, simulation, facility planning and design, engineering economy and costs

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Authors: Sulafah Basahel

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Nowadays, Higher Education Institutions (HEIs) around the world are attempting to utilize Information and Communication Technologies (ICTs) to enhance learning process and strategies of knowledge delivery for students through Distance Education (DE) system. Stakeholders in DE system face a complex situation of different ill-defined and related issues that influence decision making process. In this study system thinking as a body of knowledge is used to explore the emergent properties that produced from these connections between issues and could have either positive or negative outcomes for the DE development. Checkland Soft System Methodology (SSM) - Mode 2 is employed in a cultural context of Saudi Arabia for more knowledge acquisition purposes among multiple stakeholders in DE rather than solving problems to achieve an overall development of DE system. This paper will discuss some political, cultural issues and connections between them that impact on effectiveness of stakeholders’ activities and relations. This study will significantly contribute to both system thinking and education fields by leading decision makers in DE to reconsider future plans, strategies and right actions for more successful educational practices.

Keywords: distance education, higher education institutions, ill-defined issues, soft system methodology-Mode 2

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Authors: Yanqing Yi, Maria Cristina Lavagnolo, Alessandro Manzardo

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Construction and demolition waste (C&DW) is a major challenge in the European Union, emphasizing the urgent need for appropriate waste management processes. Selecting these solutions is challenging, as it requires identifying efficient C&DW management techniques that balance acceptable practices, regulatory compliance, resource conservation, economic viability, and environmental concerns. Techniques for analyzing many kinds of criteria allow for the use of multi-criteria analysis in life cycle assessment (LCA). Although LCA is commonly used to analyze environmental effects, the economic factor has not been fully integrated into the LCA approach in C&DW management. The life cycle costing (LCC) approach was designed to assess economic performance in the C&DW management process. The choice of an effective multi-criteria decision-making (MCDM) technique is critical for the C&DW system. This study seeks to propose a model that employs MCDM by considering LCA and LCC results, thereby augmenting both environmental and economic sustainability. A widely used compensatory MCDM technique, TOPSIS, has been chosen to identify the most effective C&DW management scheme by comparing and ranking various scenarios. Four waste management alternatives were examined in the Lombardy region of Italy, namely, (i) landfill; (ii) recycling for concrete production and road construction, incineration with energy recovery; (iii) recycling for road construction; (iv) recycling for concrete production and road construction. We determine that, with the implementation of various scenarios, the most suitable scenario emerges to be recycled for concrete production and road construction, with a score of 0.711/1; recycling for road construction, with a final score of 0.291/1, ranks second; recycling for concrete production and road construction, incineration with energy recovery scores 0.002/1, ranks third; and landfill (scores: 0/1) is the worst choice, indicating it has the highest environmental impact. Finally, suggestions were developed to improve the system's environmental performance.

Keywords: life cycle assessment, life cycle costing, construction and demolition waste, multi-criteria decision making

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Authors: Lee Da Hyun

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The purpose of this study is to explore the relation between the internal dynamics of standing committees and legislative productivity of the Korean National Assembly using statistical methods. Studies on legislation in South Korea have been largely revolved around political parties due to the uniqueness of its political context including strong party cohesion and party’s nomination right. However, as standing committees have been at the center of legislatures since the 6th National Assembly, there is a growing need for studying the operation and effectiveness of standing committees in legislation process. Thus, through panel data analysis for the sixteen standing committees across the four terms of the Korean National Assembly-from the 16th to the 19th-this article attempts to reveal that legislators’ bill passing rate is not a sole function of factors pertaining to political party as the existing studies have believed. By measuring the ideological distribution within a committee and the bill passing rate, this article provides differentiated interpretation from established theories of standing committees and presents compelling evidence describing complex interactions and independent operation of the standing committees with the subsequent legislative results.

Keywords: collective decision-making, lawmaking, legislation, political polarization, standing committees

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Authors: Musyimi Mbathi

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Information regarding social, political, demographic, economic and other attributes of human settlement is important for decision makers at all levels of planning, as they have to grapple with dynamic environments often associated with settlements. At the local level, it is particularly important for both communities and urban managers to have accurate and reliable information regarding all planning attributes. Settlement mapping, in particular, informal settlements mapping in Kenya, has over the past few years been carried out using modern tools like Geographic information systems (GIS) and remote sensing for spatial data analysis and planning. GIS tools offer a platform for integration of spatial and non-spatial data as well as visualisation of the settlements. The capabilities offered by these tools have enabled communities to participate especially in the planning and management of new infrastructure as well as settlement upgrading. Land tenure based projects within informal settlements have also relied on GIS and related tools with considerable success. Additionally, the adoption of participatory approaches and use of geo-information tools helped to provide a basis for all inclusive planning thus promoting accountability, transparency, legitimacy, and other dimensions of governance within human settlement planning. The paper examines the context and application of geo-information tools for planning within low-income settlements of Kenya. A case study of Kiambiu settlement will be used to demonstrate how the tools have been applied for planning and decision-making purposes.

Keywords: informal settlements, GIS, governance, modern tools

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Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

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Authors: Garima Sarkar

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The main purpose of the present paper is to investigate the development and progress achieved by women in the decision-making sphere and to access the level of their political-participation in Parliamentary Elections of Malaysia and their status in overall Malaysian political domain. The paper also focuses on the role and status of women in the major political parties of the state both the parties in power as well as the parties in opposition. The primary objective of the study is to focus on the major hindrances and social malpractices faced by women and also Muslim women’s access to justice in Malaysia. It also demonstrates the linkages between national policy initiatives and the advancement of women in various areas, such as economics, health, employment, politics, power-sharing, social development and law and most importantly evaluating their status in the dominant religion of the nation. In Malaysia, women’s political participation is being challenged from every nook and corner of the society. A high percentage of women are getting educated, forming a significant labor force in present day Malaysia, who can be employed in the manufacturing sector, retail trade, hotels and restaurant, agriculture etc. Women today consist of almost half of the population and exceed boys in the tertiary sector by a ratio of 80:20. Despite these achievements, however, women’s labor force engagement remains confined to ‘ traditional women’s occupations’, such as those of primary school teachers, data entry clerks and organizing polls during elections and motivating other less enlightened women to cast their votes. In the political arena, the past few General Elections of Malaysia clearly exhibited a slight change in the number of women Members of Parliament from 10.6% (20 out of 193 Parliamentary seats in 1999) to 10.5% (23 out of 219 Parliamentary seats in 2004). Amidst the political posturing for the recent General Election in 2013 of Malaysia, women’s political participation remains a prime concern in Malaysia. It is evident that while much of the attention of women revolves around charitable assistance, they are much less likely to be portrayed as active participants in electoral politics and governance. According to the electoral roll for the third quarter of 2012, 6,578,916 women are registered as voters. They represent 50.2% of the total number of the registered voters. However, this parity in terms of voter registration is not reflected in the number of elected representatives at the Parliamentary level. Only 10.4% of sitting Members of Parliament are women. The women’s participation in the legislature and executive branches are important since their presence brings the spotlight squarely on issues that have been historically neglected and overlooked. In the recent 2013 General Elections in Malaysia out of 35 full ministerial position only two, or 5.7% have been filled by women. In each of the 2009, 2010, and in the present 2013 Cabinet members, there have only been two women ministers, with this number reduced to one briefly when the Prime Minister appointed himself placeholder in the Ministry of Women, Family and Community Development. In the recent past, in its Election Manifesto, Barisan Nasional made a pledge of ‘increasing the number of women participating in national decision-making processes’. Even after such pledges, the Malaysian leadership has failed to mirror the strong presence of women in leadership positions of public life which primarily includes politics, the judiciary and in business. There has been a strong urge to political parties by various gender-sensitive groups to nominate more women as candidates for contesting elections at the Parliamentary as well as at the State level. The democratization process will never be truly democratic without a proper gender agenda and representation. Although Malaysia signed the Beijing Platform for Action document in 1995, the state has a long way to go in enhancing the participation of women in every segment of Malaysian political, economic and cultural. There has been a small percentage of women representation in decision-making bodies compared to the 30% targeted by the Beijing Platform for Action. Thus, democratization in terms of representation of women in leadership positions and decision-making positions or bodies is essential since it’s a move towards a qualitative transformation of women in shaping national decision-making processes. The democratization process has to ensure women’s full participation and their goals of development and their full participation has to be included in the process of formulating and shaping the developmental goals.

Keywords: women, gender equality, Islam, democratization, political representation, Parliament

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Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

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Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

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Authors: Julia Córdoba

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People are not completely autonomous, as we live in society; therefore, people could be defined as relationally dependent. The lack, decrease or loss of physical, psychological and/or social interdependence due to a disability situation is known as dependence. This is related to the need for help from another person in order to carry out activities of daily living. This population group lives with major social limitations that significantly reduce their participation and autonomy. They have high levels of stigma and invisibility from private environments (family and close networks), as well as from the public order (environment, community). The importance of this study lies in the fact that the lack of support and adjustments leads to what authors call the circle of exclusion. This circle describes how not accessing services - due to the difficulties caused by the disability situation impacts biological, social and psychological levels. This situation produces higher levels of exclusion and vulnerability. This study will focus on the process of autonomy and dependence of adults with disability from the model of disability proposed by the International Classification of Functioning, Health and Disability (ICF). The objectives are: i) to write down the relationship between autonomy and dependence based on socio-health variables and ii) to determine the relationship between the situation of autonomy and dependence and the expectations and interests of the participants. We propose a study that will use a survey technique through a previously validated virtual questionnaire. The data obtained will be analyzed using quantitative and qualitative methods for the details of the profiles obtained. No less than 200 questionnaires will be administered to people between 18 and 64 years of age who self-identify as having some degree of dependency due to disability. For the analysis of the results, the two main variables of autonomy and dependence will be considered. Socio-demographic variables such as age, gender identity, area of residence and family composition will be used. In relation to the biological dimension of the situation, the diagnosis, if any, and the type of disability will be asked. For the description of these profiles of autonomy and dependence, the following variables will be used: self-perception, decision-making, interests, expectations and life project, care of their health condition, support and social network, and labor and educational inclusion. The relationship between the target population and the variables collected provides several guidelines that could form the basis for the analysis of other research of interest in terms of self-perception, autonomy and dependence. The areas and situations where people state that they have greater possibilities to decide and have a say will be obtained. It will identify social (networks and support, educational background), demographic (age, gender identity and residence) and health-related variables (diagnosis and type of disability, quality of care) that may have a greater relationship with situations of dependency or autonomy. It will be studied whether the level of autonomy and/or dependence has an impact on the type of expectations and interests of the people surveyed.

Keywords: life project, disability, inclusion, autonomy

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Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Olatunji Sabitu Alimi

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This study investigated the extent to which administrators’ information storage, retrieval and processing capacities influence decisions on staff promotion in the Teaching Service Commissions (TESCOMs) in The South-West, Nigeria. One research question and two research hypotheses were formulated and tested respectively at 0.05 level of significance. The study used the descriptive research of the survey type. One hundred (100) staff on salary grade level 09 constituted the sample. Multi- stage, stratified and simple random sampling techniques were used to select 100 staff from the TESCOMs in The South-West, Nigeria. Two questionnaires titled Administrators’ Information Storage, Retrieval and Processing Capacities (AISRPC), and Staff Promotion Effectiveness (SPE) were used for data collection. The inventory was validated and subjected to test-re-test and reliability coefficient of r = 0.79 was obtained. The data were collected and analyzed using Pearson Product Moment Correlation coefficient and simple percentage. The study found that Administrators at TESCOM stored their information in files, hard copies, soft copies, open registry and departmentally in varying degrees while they also processed information manually and through electronics for decision making. In addition, there is a significant relationship between administrators’ information storage and retrieval capacities in the TESCOMs in South – West, Nigeria, (r cal = 0.598 > r table = 0.195). Furthermore, administrators’ information processing capacity and staff promotion effectiveness were found to be significantly related (r cal = 0.209 > r table = 0.195 at 0.05 level of significance). The study recommended that training, seminars, workshops should be organized for administrators on information management, while educational organizations should provide Information Management Technology (ICT) equipment for the administrators in the TESCOMs. The staff of TESCOM should be promoted having satisfied the promotion criteria such as spending required number of years on a grade level, a clean record of service and vacancy.

Keywords: information processing capacity, staff promotion effectiveness, teaching service commission, Nigeria

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Authors: Mehmet Bulent Topkaya, Mustafa Yildirim

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Wastewater treatment systems are designed and used to minimize adverse impacts of the wastewater on the environment before discharging. Various treatment options for wastewater treatment have been developed, and each of them has different performance characteristics and environmental impacts (e.g. material and land usage, energy consumption, greenhouse gas emission, water and soil emission) during construction, operation or maintenance phases. Assessing the environmental impacts during these phases are essential for the overall evaluation of the treatment systems. In this study, wastewater treatment options, such as vegetated land treatment, constructed wetland, rotating biological contactor, conventional activated sludge treatment, membrane bioreactor, extended aeration and stabilization pond are evaluated. The comparison of the environmental impacts is conducted under the assumption that the effluents will be discharged to sensitive and less sensitive areas respectively. The environmental impacts of each alternative are evaluated by life cycle assessment (LCA) approach. For this purpose, data related to energy usage, land requirement, raw material consumption, and released emissions from the life phases were collected with inventory studies based on field studies and literature. The environmental impacts were assessed by using SimaPro 7.1 LCA software. As the scale of the LCA results is global, an MS-Excel based decision support tool that includes the LCA result is developed in order to meet also the local demands. Using this tool, it is possible to assign weight factors on the LCA results according to local conditions by using Analytical Hierarchy Process and finally the most environmentally appropriate treatment option can be selected.

Keywords: analytical hierarchy process, decision support system, life cycle assessment, wastewater treatment

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Authors: Ahcene Boucied

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In this paper, a case study is conducted to analyze the effectiveness of web pages designed in Barbados for the tourism and hospitality industry. The assessment is made from two perspectives: to understand how the Barbados’ tourism industry is using the web, and to identify the effect of information technology on economic issues. In return, this is used: (a) to provide interested parties with accurate information and marketing insight necessary for decision making for electronic commerce/e-commerce, and (b) to demonstrate pragmatic difficulties in searching and designing web pages.

Keywords: segmentation, tourism stakeholders, destination marketing, case study

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Authors: C. L. Wu, W. W. Tseng

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From the National Health Insurance (NHI) system was introduced in Taiwan in 2000, there have been some problems in transformed small-scale hospitals, such as mobility of patients, shortage of nursing staff, medical pipelines breaking fire compartments and insufficient fire protection systems. Due to shrinking of the funding scale and the aging society, fire safety in small-scale hospitals has recently given cause for concern. The aim of this study is to determine fire risk index for small-scale hospital through a systematic approach The selection of fire safety mitigation methods can be regarded as a multi-attribute decision making process which must be guaranteed by expert groups. First of all, identify and select safety related factors and identify evaluation criteria through literature reviews and experts group. Secondly, application of the Fuzzy Analytic Hierarchy Process method is used to ascertain a weighted value which enables rating of the importance each of the selected factors. Overall, Sprinkler type and Compartmentation are the most crucial indices in mitigating fire, that is to say, structural approach play an important role to decrease losses in fire events.

Keywords: Fuzzy Delphi Method, fuzzy analytic hierarchy, process risk assessment, fire events

Procedia PDF Downloads 445