Search results for: multicriteria decision analysis

Authors: Irfan Khan

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Both the analytical methods used to understand the phenomena of peacebuilding and the ensuing viewpoints on achieving and sustaining "sustainable peace" are broad and diverse. This new field of study draws from sociology, anthropology, political theory, and political economy, psychology, international relations, and more recently, the development sciences to examine the wide range of 'conflicts' it describes. This paper emphasizes the significance of investigating the causes of juvenile disputes. It explains how police corruption encourages youth crime and why it's so important to address this issue head-on. It also examines the historical foundations and external pressures that have increased religious extremism and sectarian strife in Pakistan. The primary argument is that peace is not only a desirable 'goal' in itself but also that it may be a means to achieve political stability and long-term prosperity. Strategies for constructing peace may take many shapes, each tailored to the specifics of a given conflict, its scope, and the individuals involved. By drawing on some existing literature and applying it to the situation in Pakistan, this article proposes a viewpoint that centers on the participation of young people in the peacebuilding process. Due to their enhanced susceptibility and penchant for demanding change, young people are more likely to get involved in a conflict when economic failure and unemployment are present. The piece also emphasizes the marginalization young people experience as a result of their absence from decision-making processes and the political system. The article claims that Pakistan's rapidly growing young population presents a significant chance for a long-term "demographic dividend" in the form of improvements in peacebuilding processes. This benefit will only materialize if serious steps are taken to increase young people's voice and agency in political decision-making.

Keywords: peacebuilding, youth-led initiatives, empowerment, conflict & violence, religious extremism, political involvement, decision-making

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

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Waste load allocation (WLA) policies may use multi-objective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: waste load allocation (WLA), value index, multi objective particle swarm optimization (MOPSO), Haraz River, equity

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Authors: A. Baviskar, C. Sandeep, K. Shankar

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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.

Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)

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Authors: R. Tariq, R. Lee

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Background: Heywood, Middleton & Rochdale Urgent Community Care Team (UCCT)1 is a great example of using a multidisciplinary team to cope with demand. The service reduces unnecessary admissions to hospitals and ensures that patients can leave the hospital quicker by making care more readily available within the community and patient’s homes. The team comprises nurses, community practitioners, and allied health professions, including physiotherapy, occupational therapy, pharmacy, and GPs. The main challenge for a team with a range of experiences and skill sets is to maintain consistency of care, which technology can help address. Allied healthcare professionals (HCPs) are often used in expanded roles with duties mainly involving patient consultations and decision making to ease pressure on doctors. The Clinical Reasoning Platform (CRP) Dem Dx is used to support new as well as experienced professionals in the decision making process. By guiding HCPs through diagnosing patients from an expansive directory of differential diagnoses, patients can receive quality care in the community. Actions on the platform are determined using NICE guidelines along with local guidance influencing the assessment and management of a patient. Objective: To compare the clinical assessment, decisions, and actions taken by the UCCT multidisciplinary team in the community and Dem Dx, using retrospective clinical cases. Methodology: Dem Dx was used to analyse 192 anonymised cases provided by the HMR UCCT. The team’s performance was compared with Dem Dx regarding the quality of the documentation of the clinical assessment and the next steps on the patient’s journey, including the initial management, actions, and any onward referrals made. The cases were audited by two medical doctors. Results: The study found that the actions outlined by the Dem Dx platform were appropriate in almost 87% of cases. When in a direct comparison between DemDX and the actions taken by the clinical team, it was found that the platform was suitable 83% (p<0.001) of the time and could lead to a potential improvement of 66% in the assessment and management of cases. Dem Dx also served to highlight the importance of comprehensive and high quality clinical documentation. The quality of documentation of cases by UCCT can be improved to provide a detailed account of the assessment and management process. By providing step-by-step guidance and documentation at every stage, Dem Dx may ensure that legal accountability has been fulfilled. Conclusion: With the ever expanding workforce in the NHS, technology has become a key component in driving healthcare outcomes. To improve healthcare provision and clinical reasoning, a decision support platform can be integrated into HCPs’ clinical practice. Potential assistance with clinical assessments, the most appropriate next step and actions in a patient’s care, and improvements in the documentation was highlighted by this retrospective study. A further study has been planned to ascertain the effectiveness of improving outcomes using the clinical reasoning platform within the clinical setting by clinicians.

Keywords: allied health professional, assessment, clinical reasoning, clinical records, clinical decision-making, ocumentation

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Bahadir Aydin

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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.

Keywords: information, intelligence cycle, knowledge, tacit Knowledge

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Authors: Felicia Iyabode Olasehinde, Michael Maiye Olumorin

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To achieve a liveable and sustainable city, decision makers must engage in holistic approach to the planning and development of infrastructure such as roads. From observation there is great disparity in the development of roads in the northern part of the city while the south is being starved with this infrastructure. This paper attempts to make a comparison between the natures of roads in the north as against the south. The methodology to be adopted is survey research using clusters in the four local government making Kaduna Metropolis. The analysis of the road will be based on existing planning standards for roads in urban areas. This will now provide useful information for critical stakeholders at all levels of governance responsible for achieving liveable and sustainable cities.

Keywords: infrastructure, liveable, sustainable, urbanroads

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Authors: Sevinj Asgarova

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Within the last few decades, major advances in the field of prenatal testing have transpired yet little research regarding the experiences of mothers who chose to continue their pregnancies after prenatally receiving a diagnosis of Down Syndrome (DS) has been undertaken. Using social constructionism and interpretive description, this retrospective research study explores this topic from the point of view of the mothers involved and provides insight as to how the experience could be improved. Using purposive sampling, 23 mothers were recruited from British Columbia (n=11) and Ontario (n=12) in Canada. Data retrieved through semi-structured in-depth interviews were analyzed using inductive, constant comparative analysis, the major analytical techniques of interpretive description. Four primary phases emerged from the data analysis 1) healthcare professional-mothers communications, 2) initial emotional response, 3) subsequent decision-making and 4) an adjustment and reorganization of lifestyle to the preparation for the birth of the child. This study validates the individualized and contextualized nature of mothers’ decisions as influenced by multiple factors, with moral values/spiritual beliefs being significant. The mothers’ ability to cope was affected by the information communicated to them about their unborn baby’s diagnosis and the manner in which that information was delivered to them. Mothers used emotional coping strategies, dependent upon support from partners, family, and friends, as well as from other families who have children with DS. Additionally, they employed practical coping strategies, such as engaging in healthcare planning, seeking relevant information, and reimagining and reorganizing their lifestyle. Over time many families gained a sense of control over their situation and readjusted to the preparation for the birth of the child. Many mothers expressed the importance of maintaining positivity and hopefulness with respect to positive outcomes and opportunities for their children. The comprehensive information generated through this study will also provide healthcare professionals with relevant information to assist them in understanding the informational and emotional needs of these mothers. This should lead to an improvement in their practice and enhance their ability to intervene appropriately and effectively, better offering improved support to parents dealing with a diagnosis of DS for their child.

Keywords: continuing affected pregnancy, decision making, disability, down syndrome, eugenic social attitudes, inequalities, life change events, prenatal care, prenatal testing, qualitative research, social change, social justice

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Alia Aldarmaki, Ahmad Elshennawy

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There is a global shift in healthcare systems’ emphasizing engaging different stakeholders in selecting quality improvement initiatives and incorporating their preferences to improve the healthcare efficiency and outcomes. Although experts bring scientific knowledge based on the scientific model and their personal experience, other stakeholders can bring new insights and information into the decision-making process. This study attempts to explore the impact of incorporating different stakeholders’ preference in identifying the most significant criteria that should be considered in healthcare for electing the improvement projects. A Framework based on a modified Fuzzy Delphi Method (FDM) was built. In addition to, the subject matter experts, doctors/physicians, nurses, administrators, and managers groups contribute to the selection process. The research identifies potential criteria for evaluating projects in healthcare, then utilizes FDM to capture expertise knowledge. The first round in FDM is intended to validate the identified list of criteria from experts; which includes collecting additional criteria from experts that the literature might have overlooked. When an acceptable level of consensus has been reached, a second round is conducted to obtain experts’ and other related stakeholders’ opinions on the appropriate weight of each criterion’s importance using linguistic variables. FDM analyses eliminate or retain the criteria to produce a final list of the critical criteria to select improvement projects in healthcare. Finally, reliability and validity were investigated using Cronbach’s alpha and factor analysis, respectively. Two case studies were carried out in a public hospital in the United Arab Emirates to test the framework. Both cases demonstrate that even though there were common criteria between the experts and the stakeholders, still stakeholders’ perceptions bring additional critical criteria into the evaluation process, which can impact the outcomes. Experts selected criteria related to strategical and managerial aspects, while the other participants preferred criteria related to social aspects such as health and safety and patients’ satisfaction. The health and safety criterion had the highest important weight in both cases. The analysis showed that Cronbach’s alpha value is 0.977 and all criteria have factor loading greater than 0.3. In conclusion, the inclusion of stakeholders’ perspectives is intended to enhance stakeholders’ engagement, improve transparency throughout the decision process, and take robust decisions.

Keywords: Fuzzy Delphi Method, fuzzy number, healthcare, stakeholders

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Authors: Diptimayee Nayak

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Ecotourism has been recognised as a popular component of alternative tourism, which claims to guard host local environment and economy. This concept of ecological tourism (eco-tourism) has become more meaningful in evaluating the recreational function and services of any pristine ecosystem in context of ‘The Economics of Ecosystem and Biodiversity (TEEB)’. This ecotourism is said to be a local solution to the global problem of conserving ecosystems and optimising the utilisations of their services. This paper takes a case of recreational services of an Indian protected area ecosystems ‘Bhitarakanika mangrove protected area’ discussing how ecotourism is functioning taking the perspectives of different stakeholders. Specific stakeholders are taken for analysis, viz., tourists and local people, as they are believed to be the major beneficiaries of ecotourism. The stakeholders’ analysis is evaluated on the basis of travel cost techniques (by using truncated Poisson distribution model) for tourists and descriptive and analytical tools for local people. The evaluation of stakeholders’ analysis of ecotourism has gained its impetus after the formulation of Ecotourism guidelines by the Ministry of Environment and Forest (MoEF), Government of India. The paper concludes that ecotourism issues and challenges are site-specific and region-specific; without critically focussing challenges of ecotourism faced at local level the discourses of ecotourism at global level cannot be tackled. Mere integration and replication of policies at global level to be followed at local level will not be successful (top down policies). Rather mainstreaming the decision making process at local level with the global policy stature helps to solve global issues to a bigger extent (bottom up).

Keywords: ecosystem services, ecotourism, TEEB, economic valuation, stakeholders, travel cost techniques

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: David Tresner-Kirsch

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Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

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Authors: Sergey Podluzhnyy

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One of the most important tasks of investment and pension fund management is building decision support system which helps to make right decision on corporate bond portfolio formation. Today there are several basic methods of bond portfolio management. They are duration management, immunization and convexity management. Identified methods have serious disadvantage: they do not take into account credit risk or insolvency risk of issuer. So, identified methods can be applied only for management and evaluation of high-quality sovereign bonds. Applying article proposes mathematical model for building an optimal in case of risk and yield corporate bond portfolio. Proposed model takes into account the default probability in formula of assessment of bonds which results to more correct evaluation of bonds prices. Moreover, applied model provides tools for visualization of the efficient frontier of corporate bonds portfolio taking into account the exposure to credit risk, which will increase the quality of the investment decisions of portfolio managers.

Keywords: corporate bond portfolio, default probability, effective boundary, portfolio optimization task

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Authors: F. Iberraken, R. Medjoudj, D. Aissani

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The development of the smart grids concept is built around two separate definitions, namely: The European one oriented towards sustainable development and the American one oriented towards reliability and security of supply. In this paper, we have investigated reliability merits enabling decision-makers to provide a high quality of service. It is based on system behavior using interruptions and failures modeling and forecasting from one hand and on the contribution of information and communication technologies (ICT) to mitigate catastrophic ones such as blackouts from the other hand. It was found that this concept has been adopted by developing and emerging countries in short and medium terms followed by sustainability concept at long term planning. This work has highlighted the reliability merits such as: Benefits, opportunities, costs and risks considered as consistent units of measuring power customer satisfaction. From the decision making point of view, we have used the analytic hierarchy process (AHP) to achieve customer satisfaction, based on the reliability merits and the contribution of such energy resources. Certainly nowadays, fossil and nuclear ones are dominating energy production but great advances are already made to jump into cleaner ones. It was demonstrated that theses resources are not only environmentally but also economically and socially sustainable. The paper is organized as follows: Section one is devoted to the introduction, where an implicit review of smart grids development is given for the two main concepts (for USA and Europeans countries). The AHP method and the BOCR developments of reliability merits against power customer satisfaction are developed in section two. The benefits where expressed by the high level of availability, maintenance actions applicability and power quality. Opportunities were highlighted by the implementation of ICT in data transfer and processing, the mastering of peak demand control, the decentralization of the production and the power system management in default conditions. Costs were evaluated using cost-benefit analysis, including the investment expenditures in network security, becoming a target to hackers and terrorists, and the profits of operating as decentralized systems, with a reduced energy not supplied, thanks to the availability of storage units issued from renewable resources and to the current power lines (CPL) enabling the power dispatcher to manage optimally the load shedding. For risks, we have razed the adhesion of citizens to contribute financially to the system and to the utility restructuring. What is the degree of their agreement compared to the guarantees proposed by the managers about the information integrity? From technical point of view, have they sufficient information and knowledge to meet a smart home and a smart system? In section three, an application of AHP method is made to achieve power customer satisfaction based on the main energy resources as alternatives, using knowledge issued from a country that has a great advance in energy mutation. Results and discussions are given in section four. It was given us to conclude that the option to a given resource depends on the attitude of the decision maker (prudent, optimistic or pessimistic), and that status quo is neither sustainable nor satisfactory.

Keywords: reliability, AHP, renewable energy resources, smart grids

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Authors: Laxuman Thakuri

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Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

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Authors: Peter Clutterbuck, Terry Rowlands, Owen Seamons

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In this paper we describe one critical research program within a complex, ongoing multi-year project (2010 to 2014 inclusive) with the overall goal to improve the learning outcomes for first year undergraduate commerce/business students within an Information Systems (IS) subject with very large enrolment. The single research program described in this paper is the analysis of student attitudes and decision making in relation to the availability of formative assessment feedback via Web-based real time conferencing and document exchange software (Adobe Connect). The formative assessment feedback between teaching staff and students is in respect of an authentic problem-based, team-completed assignment. The analysis of student attitudes and decision making is investigated via both qualitative (firstly) and quantitative (secondly) application of the Theory of Planned Behavior (TPB) with a two statistically-significant and separate trial samples of the enrolled students. The initial qualitative TPB investigation revealed that perceived self-efficacy, improved time-management, and lecturer-student relationship building were the major factors in shaping an overall favorable student attitude to online feedback, whilst some students expressed valid concerns with perceived control limitations identified within the online feedback protocols. The subsequent quantitative TPB investigation then confirmed that attitude towards usage, subjective norms surrounding usage, and perceived behavioral control of usage were all significant in shaping student intention to use the online feedback protocol, with these three variables explaining 63 percent of the variance in the behavioral intention to use the online feedback protocol. The identification in this research of perceived behavioral control as a significant determinant in student usage of a specific technology component within a virtual learning environment (VLE) suggests that VLEs could now be viewed not as a single, atomic entity, but as a spectrum of technology offerings ranging from the mature and simple (e.g., email, Web downloads) to the cutting-edge and challenging (e.g., Web conferencing and real-time document exchange). That is, that all VLEs should not be considered the same. The results of this research suggest that tertiary students have the technological sophistication to assess a VLE in this more selective manner.

Keywords: formative assessment feedback, virtual learning environment, theory of planned behavior, perceived behavioral control

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki, Simoni K. Lintzerakou

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Air transport links markets and individuals, promoting social and economic development. The review of management direction towards social responsibility and especially for the enhancement of passengers with autism is the key objective of this paper. According to a top-down approach, the key dimensions that affect the basic principles and directions of airport enterprises management towards social responsibility for the case of passengers with autism are presented. Conventional wisdom is to present actions undertaken in improving accessibility for special population groups and highlight the social dimension in the management of transport hubs. The target is to focus on transport hubs serving special groups of passengers such as passengers with autism and highlight good practices and motivate transport infrastructure management authorities and decision makers to promote the social footprint of transport. The highlights and key findings are essential for managers and decision makers to support actions and plans towards management of airport enterprises towards social responsibility, focusing on the case of passengers traveling with Autism Spectrum Disorder (ASD).

Keywords: social responsibility, special groups, airport enterprises, AUTISM

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Authors: Yu-Ching Liu

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Background: Family numbers usually take responsibility for taking care of their elderly relatives, especially parents. Caring for a patient with chronic diseases is a stressful experience, which makes carers suffer physical and mental health stress, difficulties maintaining family relationships and issues in participating in the labor market, which may lower their quality of life (QoL). The issue of providing care to relatives with chronic illness has been widely explored in Taiwan, but most studies focus on the need for full-time caregivers. Objective: The main goal of this study was to examine the topic of working carers involved in the decision-making process of LTC services and to explore what affects working carers considering when they choose the care services for their disabled, elderly relatives. Method: A total of 7 working caregivers were enrolled in this study. A face-to-face and semi-structured in-depth qualitative interview study were conducted to explore the caregivers' perspectives. Results: Working carers have a positive experience of using LTC service because it allows them to kill two birds with one stone, continue employment, and care for an elderly disabled relative. However, working carers have still been struggling to find friendly community-based LTC services. There were no longer available community services that could be used with the illness condition of patients getting worse. As such, patients have to be cared for at home, which might increase the caregiver burden of carers. Conclusion: Working family caregivers suffer from heavy physical and psychological burdens as they not only have to maintain their employment but care for elderly disabled relatives; however, the current support provided is insufficient. The design of services should consider working carers' employment situation and need rather than the only caring situation of patients at home.

Keywords: family caregiver, Long-term care, work-life balance, decision-making

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Authors: An-Shik Yang, Chiang-Ho Cheng, Jen-Hao Wu, Yu-Hsuan Juan

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Natural ventilation has played an important role for many low energy-building designs. It has been also noticed as a essential subject to persistently bring the fresh cool air from the outside into a building. This study carried out the computational fluid dynamics (CFD)-based simulations to examine the natural ventilation development of a work area in a public building. The simulated results can be useful to better understand the indoor microclimate and the interaction of wind with buildings. Besides, this CFD simulation procedure can serve as an effective analysis tool to characterize the airing performance, and thereby optimize the building ventilation for strengthening the architects, planners and other decision makers on improving the natural ventilation design of public buildings.

Keywords: CFD simulations, natural ventilation, microclimate, wind environment

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Authors: Suraj Kumar Mukti

Abstract:

Enterprise Resource Planning (ERP) system is a management tool to integrate all departments in an organization. It integrates business processes, manages resources efficiently and provides an appropriate decision support system to management. ERP system implementation is a typical and time taking process as well as money consuming process. Articles related to key success factors of ERP system implementation are available in the literature, but rare authors have focused on roadmap of successful ERP system implementation. Postponement is better if the organization is not ready to implement ERP system in better way; hence checking of organization’s preparation to adopt new system is an important prerequisite to ensure the success of ERP system implementation in an organization. Then comes what will be called as success of ERP system implementation. Benefits achieved by ERP system may be categorized into two categories; viz. tangible and intangible benefits. This research article presents a roadmap to ensure the success of ERP system implementation and benefits achieved through the new system as in success indicator. A case study is presented to evaluate the success and benefit achieved through the new system. The article gives a comprehensive approach to academicians and a roadmap to the organizations seeking to implement the ERP system.

Keywords: ERP system, decision support system, tangible, intangible

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Authors: Nivedita Paul

Abstract:

Marriages in India are part and parcel of kinship and cultural practices. Marriage practices differ in India because of cross-regional diversities in social relations which itself has evolved as a result of causal relationship between space and culture. As the place is important for the formation of culture and other social structures, therefore there is regional differentiation in cultural practices and marital customs. Based on the cultural practices some scholars have divided India into North and South kinship regions where women in the North get married early and have lesser autonomy compared to women in the South where marriages are mostly consanguineous. But, the emergence of new modes and alternative strategies such as matrimonial advertisements becoming popular, as well as the increase in women’s literacy and work force participation, matchmaking process in India has changed to some extent. The present study uses data from Indian Human Development Survey II (2011-12) which is a nationally representative multitopic survey that covers 41,554 households. Currently married women of age group 15-49 in their first marriage; whose year of marriage is from the 1970s to 2000s have been taken for the study. Based on spouse selection experiences, the sample of women has been divided into three marriage categories-self, semi and family arranged. Women in self-arranged or love marriage is the sole decision maker in choosing the partner, in semi-arranged marriage or arranged marriage with consent both parents and women together take the decision, whereas in family arranged or arranged marriage without consent only parents take the decision. The main aim of the study is to show the spatial and regional variations in spouse selection decision making. The basis for regionalization has been taken from Irawati Karve’s pioneering work on kinship studies in India called Kinship Organization in India. India is divided into four kinship regions-North, Central, South and East. Since this work was formulated in 1953, some of the states have experienced changes due to modernization; hence these have been regrouped. After mapping spouse selection patterns using GIS software, it is found that the northern region has mostly family arranged marriages (around 64.6%), the central zone shows a mixed pattern since family arranged marriages are less than north but more than south and semi-arranged marriages are more than north but less than south. The southern zone has the dominance of semi-arranged marriages (around 55%) whereas the eastern zone has more of semi-arranged marriage (around 53%) but there is also a high percentage of self-arranged marriage (around 42%). Thus, arranged marriage is the dominant form of marriage in all four regions, but with a difference in the degree of the involvement of the female and her parents and relatives.

Keywords: spouse selection, consent, kinship, regional pattern

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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: Maria A. Castillo H., Andrés R. Leandro C.

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During the last decades, agricultural productivity in Latin America has increased with precision agriculture and more efficient agricultural technologies. The use of automated systems, satellite images, geographic information systems, and tools for data analysis, and artificial intelligence have contributed to making more effective strategic decisions. Twenty years ago, the state of Mérida, located in the Venezuelan Andes, reported the largest area covered by greenhouses in the country, where certified seeds of potatoes, vegetables, ornamentals, and flowers were produced for export and consumption in the central region of the country. In recent years, it is estimated that production under greenhouses has changed, and the area covered has decreased due to different factors, but there are few historical statistical data in sufficient quantity and quality to support this estimate or to be used for analysis and decision making. The objective of this study is to compare data collected about geoposition, use, and covered areas of the greenhouses in 2007 to data available in 2021, as support for the analysis of the current situation of horticultural production in the main municipalities of the state of Mérida. The document presents the development of the work in the diagnosis and integration of geographic coordinates in GIS and data analysis phases. As a result, an evaluation of the process is made, a dashboard is presented with the most relevant data along with the geographical coordinates integrated into GIS, and an analysis of the obtained information is made. Finally, some recommendations for actions are added, and works that expand the information obtained and its geographical traceability over time are proposed. This study contributes to granting greater certainty in the supporting data for the evaluation of social, environmental, and economic sustainability indicators and to make better decisions according to the sustainable development goals in the area under review. At the same time, the methodology provides improvements to the agricultural data collection process that can be extended to other study areas and crops.

Keywords: greenhouses, geographic information system, protected agriculture, data analysis, Venezuela

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Authors: Abbas Hani, Maryam Jassasizadeh

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The concentrations of Cd, Pb, and Ni were determined from 40 soil samples collected in surface soils of Khark Island. Geostatistic methods and GIS were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that level of mentioned heavy metal was lower than the standard level. Then the data obtained from the soil analyzing were studied for the purposes of normal distribution. The best way of interior finding for cadmium and nickel was ordinary kriging and the best way of interpolation of lead was inverse distance weighted. The result of this study help us to understand heavy metals distribution and make decision for remediation of soil pollution.

Keywords: geostatistics, ordinary kriging, heavy metals, GIS, Khark

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Authors: Daniel Alfonso Reséndiz-García, Luis Antonio García-Villanueva

Abstract:

As a result of the high industrial activity, which arises from the search to satisfy the needs of products and services for society, several chemical accidents have occurred, causing serious damage to different sectors: human, economic, infrastructure and environmental losses. Historically, with the study of this chemical accidents, it has been determined that the causes are mainly due to human errors (inexperienced personnel, negligence, lack of maintenance and deficient risk analysis). The industries have the aim to increase production and reduce costs. However, it should be kept in mind that the costs involved in risk studies, implementation of barriers and safety systems is much cheaper than paying for the possible damages that could occur in the event of an accident, without forgetting that there are things that cannot be replaced, such as human lives.Therefore, it is of utmost importance to implement risk studies in all industries, which provide information for prevention and planning. The aim of this study is to compare risk methodologies by identifying the consequences of accidents related to the storage of flammable, dangerous goods for decision making and emergency response.The methodologies considered in this study are qualitative and quantitative risk analysis and consequence analysis. The latter, by means of modeling software, which provides radius of affectation and the possible scope and magnitude of damages.By using risk analysis, possible scenarios of occurrence of chemical accidents in the storage of flammable substances are identified. Once the possible risk scenarios have been identified, the characteristics of the substances, their storage and atmospheric conditions are entered into the software.The results provide information that allows the implementation of prevention, detection, control, and combat elements for emergency response, thus having the necessary tools to avoid the occurrence of accidents and, if they do occur, to significantly reduce the magnitude of the damage.This study highlights the importance of risk studies applying tools that best suited to each case study. It also proves the importance of knowing the risk exposure of industrial activities for a better prevention, planning and emergency response.

Keywords: chemical accidents, emergency response, flammable substances, risk analysis, modeling

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Authors: Zahra Hatami, Hesham Ali, David Volkman

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Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: portfolio management performance, network analysis, centrality measurements, Sharpe ratio

Procedia PDF Downloads 148