Search results for: multi variable decision making

Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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The optimal construction design used during the execution of a construction project is a key factor in determining high productivity and customer satisfaction, however, this management process sometimes is carried out without care and the systematic method that it deserves, bringing negative consequences. This study proposes a knowledge management (KM) approach that will enable the intelligent use of experienced and acknowledged engineers to improve the management of construction design works for a project. Then a knowledge-based application to support this decision-making process is proposed and described. To define and design the system for the application, semi-structured interviews were conducted within five construction consulting organizations with the purpose of studying the way that the method’ optimizing process is implemented in practice and the knowledge supported with it. A system of an optimizing construction design works (OCDW) based on knowledge was developed then validated with construction experts. The OCDW was liked as a valuable tool for construction design works’ optimization, by supporting organizations to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The benefits are described as provided by the performance support system, reducing costs and time, improving product design quality, satisfying customer requirements, expanding the brand organization.

Keywords: optimizing construction design work, construction consultant organization, knowledge management, knowledge-based application

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Authors: Mengqiu Deng, Xiao Peng, Yang Zhao

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The development of local energy systems requires the collective involvement of different actors from various levels of society. However, the stakeholder analysis of local energy systems still has been under-developed. This paper proposes an multi-agent system (MAS) framework to facilitate the development of stakeholder analysis of local energy systems. The framework takes into account the most influencing stakeholders, including prosumers/consumers, system operators, energy companies and government bodies. Different stakeholders are modeled based on agent architectures for example the belief-desire-intention (BDI) to better reflect their motivations and interests in participating in local energy systems. The agent models of different stakeholders are then integrated in one model of the whole energy system. An illustrative case study is provided to elaborate how to develop a quantitative agent model for different stakeholders, as well as to demonstrate the practicability of the proposed framework. The findings from the case study indicate that the suggested framework and agent model can serve as analytical instruments for enhancing the government’s policy-making process by offering a systematic view of stakeholder interconnections in local energy systems.

Keywords: multi-agent system, BDI agent, local energy systems, stakeholders

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Authors: Winita Kitisak, Boontarika Panyomoon, Siriyakorn Nilpoun, Nithit Yosit, Peeraya Somsak

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The purpose of this study will affect the marketing mix that influences the consumers’ behavior towards beverage purchasing from retail stores. It aims to study the consumers and to better understand their behaviors and factors influencing their decision making on buying beverage in retail stores. We study the example of 400 consumers in Chiang Mai. The study shows that most of the respondents were male, 50 percent is 20-30 year old, and 36.66 percent is 31-40 year old, only 2.66 percent is upper 50 years old, bachelor’s degree holders, working in business field and student with 10,001-15,000 Baht income. Most buyers spend 4-6 times a week buying cheap beverage from retail stores. The consumer bought alcoholic beverages, green tea drinks, and soft drinks, but the mainly purchased product was beer. The results indicate that the brand of the product motivates more on consumers’ demand. While shelf displays, products presentation, and sales promotion affect the most on the consumers’ decision to purchase from the retail stores, the promotions moderately impact the consumers’ decision on purchasing from retail stores.

Keywords: consumer behavior, beverage, retail stores, convenience store

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Authors: Zeenath Solih

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The aim of the study is to analyze the factors that influence the decision to pursue a hospitality and tourism program for students of Maldives when pursuing higher education options. This research would further explore the implications and relationship between the universities and students. Quantitative research method will be used to demonstrate the hypothesis and achieve the objectives of this research, a questionnaire consisting of 30 closed questions will be used which will be analyzed based on SPSS18 software to handle and extract the data.10 public school and 3 private schools with secondary education and 3 universities with higher education facilities and a total of 500 students participated in the survey. The findings include selection criteria for decision making for higher studies being the university’s reputation, excellence and quality of educational program, the preference of pursuing further studies from a public over private universities and the academic, cultural and socio demographic factors that influence the students choice of program and university. Finally the study will provide valuable insight to how universities need to market their programs to attract the right students.

Keywords: choice criteria, higher education, hospitality and tourism studies, information sources

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Authors: Luke Miller

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This paper develops an options pricing methodology to value strategic pricing strategies in the services sector. More specifically, this study provides a unifying taxonomy of current service sector pricing practices, frames these pricing decisions as strategic real options, demonstrates accepted option valuation techniques to assess service sector pricing decisions, and suggests future research areas where pricing decisions and real options overlap. Enhancing revenue in the service sector requires proactive decision making in a world of uncertainty. In an effort to strategically price service products, revenue enhancement necessitates a careful study of the service costs, customer base, competition, legalities, and shared economies with the market. Pricing decisions involve the quality of inputs, manpower, and best practices to maintain superior service. These decisions further hinge on identifying relevant pricing strategies and understanding how these strategies impact a firm’s value. A relatively new area of research applies option pricing theory to investments in real assets and is commonly known as real options. The real options approach is based on the premise that many corporate decisions to invest or divest in assets are simply an option wherein the firm has the right to make an investment without any obligation to act. The decision maker, therefore, has more flexibility and the value of this operating flexibility should be taken into consideration. The real options framework has already been applied to numerous areas including manufacturing, inventory, natural resources, research and development, strategic decisions, technology, and stock valuation. Additionally, numerous surveys have identified a growing need for the real options decision framework within all areas of corporate decision-making. Despite the wide applicability of real options, no study has been carried out linking service sector pricing decisions and real options. This is surprising given the service sector comprises 80% of the US employment and Gross Domestic Product (GDP). Identifying real options as a practical tool to value different service sector pricing strategies is believed to have a significant impact on firm decisions. This paper identifies and discusses four distinct pricing strategies available to the service sector from an options’ perspective: (1) Cost-based profit margin, (2) Increased customer base, (3) Platform pricing, and (4) Buffet pricing. Within each strategy lie several pricing tactics available to the service firm. These tactics can be viewed as options the decision maker has to best manage a strategic position in the market. To demonstrate the effectiveness of including flexibility in the pricing decision, a series of pricing strategies were developed and valued using a real options binomial lattice structure. The options pricing approach discussed in this study allows service firms to directly incorporate market-driven perspectives into the decision process and thus synchronizing service operations with organizational economic goals.

Keywords: option pricing theory, real options, service sector, valuation

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Authors: Shameka Stanford

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This presentation will discuss how cognitive and communication disorders in the areas of executive functioning, receptive and expressive language can impact the problem-solving and decision making of individuals with such impairments. More specifically, this presentation will discuss approaches the legal defense team of capital case lawyers can add to their experience when servicing individuals who have a history of educational decline, special education, and limited intervention and treatment. The objective of the research is to explore and identify the correlations between impaired executive function skills and decision making and competency for individuals facing death penalty charges. To conduct this research, experimental design, randomized sampling, qualitative analysis was employed. This research contributes to the legal and criminal justice system related to how they view, defend, and characterize, and judge individuals with documented cognitive and communication disorders who are eligible for capital case charges. More importantly, this research contributes to the increased ability of death penalty lawyers to successfully defend clients with a history of academic difficulty, special education, and documented disorders that impact educational progress and academic success.

Keywords: communication disorders, cognitive disorders, capital murder, death penalty, executive function

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Authors: Sandesh Achar

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Cloud computing security is a broad term that covers a variety of security concerns for organizations that use cloud services. Multi-cloud service providers must consider several factors when addressing security for their customers, including identity and access management, data at rest and in transit, egress and ingress traffic control, vulnerability and threat management, and auditing. This paper explores each of these aspects of cloud security in detail and provides recommendations for best practices for multi-cloud service providers. It also discusses the challenges inherent in securing a multi-cloud environment and offers solutions for overcoming these challenges. By the end of this paper, readers should have a good understanding of the various security concerns associated with multi-cloud environments in the context of today’s modern cyber threats and how to address them.

Keywords: multi-cloud service, system organization control, data loss prevention, identity and access management

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Authors: Roopa Singh, Anurag Singh, Ajay

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Agriculture contributes a major share in the national economy of India. A major portion of Indian economy (about 70%) depends upon agriculture as it forms the main source of income. About 43% of India’s geographical area is used for agricultural activity which involves 65-75% of total population of India. The given work deals with the Fast moving Consumer Goods (FMCG) industries and their inventories which use agricultural produce as their raw material or input for their final product. Since the beginning of inventory practices, many developments took place which can be categorised into three phases, based on the review of various works. The first phase is related with development and utilization of Economic Order Quantity (EOQ) model and methods for optimizing costs and profits. Second phase deals with inventory optimization method, with the purpose of balancing capital investment constraints and service level goals. The third and recent phase has merged inventory control with electrical control theory. Maintenance of inventory is considered negative, as a large amount of capital is blocked especially in mechanical and electrical industries. But the case is different in food processing and agro-based industries and their inventories due to cyclic variation in the cost of raw materials of such industries which is the reason for selection of these industries in the mentioned work. The application of electrical control theory in inventory control makes the decision-making highly instantaneous for FMCG industries without loss in their proposed profits, which happened earlier during first and second phases, mainly due to late implementation of decision. The work also replaces various inventories and work-in-progress (WIP) related errors with their monetary values, so that the decision-making is fully target-oriented.

Keywords: control theory, inventory control, manufacturing sector, EOQ, feedback, FMCG sector

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Authors: M. Hemam, M. Djezzar, T. Djouad

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We are interested in the problem of building an ontology in a heterogeneous organization, by taking into account different viewpoints and different terminologies of communities in the organization. Such ontology, that we call multi-viewpoint ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. In addition, these partial descriptions share at global level, ontological elements constituent a consensus between the various viewpoints. In order to provide response elements to this problem we define a multi-viewpoints knowledge model based on viewpoint and ontology notions. The multi-viewpoints knowledge model is used to formalize the multi-viewpoints ontology in description logics language.

Keywords: description logic, knowledge engineering, ontology, viewpoint

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Authors: Adeaga Ibiyemi Iyabo, Adeaga Oyetunde Adeoye

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Interestingly, mechanical drying methods has played a major role in the commercialization of agricultural and agricultural allied sectors. In the overall, drying enhances the favorable storability and preservation of agricultural produce which in turn promotes its producibility, marketability, salability, and profitability. Recent researches have shown that solar drying is easier, affordable, controllable, and of course, cleaner and purer than other means of drying methods. It is, therefore, needful to persistently appraise solar dryers with a view to improving on the existing advantages. In this paper, mathematical equations were formulated for solar dryer using mass conservation law, material balance law and least cost savings method. Computer codes were written in Visual Basic.Net. The developed computer software, which considered Ibadan, a strategic south-western geographical location in Nigeria, was used to investigate the relationship between variable orientation angle of flat plate collector on solar energy trapped, derived monthly heat load, available energy supplied by solar and fraction supplied by solar energy when 50000 Kg/Month of produce was dried over a year. At variable collector tilt angle of 10°.13°,15°,18°, 20°, the derived monthly heat load, available energy supplied by solar were 1211224.63MJ, 102121.34MJ, 0.111; 3299274.63MJ, 10121.34MJ, 0.132; 5999364.706MJ, 171222.859MJ, 0.286; 4211224.63MJ, 132121.34MJ, 0.121; 2200224.63MJ, 112121.34MJ, 0.104, respectively .These results showed that if optimum collector angle is not reached, those factors needed for efficient and cost reduction drying will be difficult to attain. Therefore, this software has revealed that off - optimum collector angle in commercial solar drying does not worth it, hence the importance of the software in decision making as to the optimum collector angle of orientation.

Keywords: energy, ibadan, heat - load, visual-basic.net

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Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: M. Y. Malik, Farzana Khan

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In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

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Authors: Muhadam Labolo, Afdal R. Anwar, Sucia Miranti Sipisang

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Electronic Local Finance Management Information System (ELFMIS) is integrated application that was used as a tool for local governments to improve the effectiveness of the implementation of the various areas of financial management regulations. Appropriate With Exceptions Opinion (WDP) of Indonesia Audit Agency (BPK) for local governments Mempawah is a financial management problem that must be improved to avoid mistakes in decision-making. The use of Electronic Local Finance Management Information System (ELFMIS) by Mempawah authority has not yet performed maximally. These problems became the basis for research in measuring the effectiveness LFMIS in Mempawah regency. This research uses an indicator variable for measuring information systems effectiveness proposed by Bodnar. This research made use descriptive with inductive approach. Data collection techniques were mixed from qualitative and quantitative techniques, used questionnaires, interviews and documentation. The obstacles in Local Finance Board (LFB) for the application of ELFMIS such as connection, the quality and quantity of human resources, realization of financial resources, absence of maintenance and another facilities of ELFMIS and verification for financial information.

Keywords: effectiveness, E-LFMIS, finance, local government, system

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Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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Authors: Busaba Phurksaphanrat

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This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions.

Keywords: multi-mode resource constrained project scheduling problem, fuzzy set, goal programming, pre-emptive fuzzy goal programming

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Authors: Lior Davidovitch

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Traditional training based on static models and case studies is the backbone of most teaching and training programs of engineering education. However, project management learning is characterized by dynamics models that requires new and enhanced learning method. The results of empirical experiments evaluating the effectiveness and efficiency of using cognitive simulator as a new training technique are reported. The empirical findings are focused on the impact of keeping and reviewing learning history in a dynamic and interactive simulation environment of engineering education. The cognitive simulator for engineering project management learning had two learning history keeping modes: manual (student-controlled), automatic (simulator-controlled) and a version with no history keeping. A group of industrial engineering students performed four simulation-runs divided into three identical simple scenarios and one complicated scenario. The performances of participants running the simulation with the manual history mode were significantly better than users running the simulation with the automatic history mode. Moreover, the effects of using the undo enhanced further the learning process. The findings indicate an enhancement of engineering students’ learning and decision making when they use the record functionality of the history during their engineering training process. Furthermore, the cognitive simulator as educational innovation improves students learning and training. The practical implications of using simulators in the field of engineering education are discussed.

Keywords: cognitive simulator, decision making, engineering learning, project management

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Authors: Recep Sait Arpat, Hakan Güreşci

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Emergency, disaster and crisis management terms are generally perceived as the same processes. This conflict effects the approach and delegating policy of the political order. Crisis management starts in the aftermath of the mismanagement of disaster and emergency. In the light of the information stated above in this article Turkey and United Kingdom(UK)’s crisis management systems are analyzed. This article’s main aim is to clarify the main points of the emergency management system of United Kingdom and Turkey’s disaster management system by comparing them. To do this: A prototype model of the political decision making processes of the countries is drawn, decision making mechanisms and the planning functions are compared. As a result it’s found that emergency management policy in Turkey is reactive whereas it’s proactive in UK; as the delegating policy Turkey’s system is similar to UK; levels of emergency situations are similar but not the same; the differences are stemming from the civil order and nongovernmental organizations effectiveness; UK has a detailed government engagement model to emergencies, which shapes the doctrine of the approach to emergencies, and it’s successful in gathering and controlling the whole state’s efforts; crisis management is a sub-phase of UK emergency management whereas it’s accepted as a outmoded management perception and the focal point of crisis management perception in UK is security crisis and natural disasters while in Turkey it is natural disasters. In every anlysis proposals are given to Turkey.

Keywords: crisis management, disaster management, emergency management, turkey, united kingdom

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Authors: Jeon Chi-Ho, Lee Jae-Bin, Shim Chang-Su

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National bridge inventory in Korea shows that the number of old prestressed concrete (PSC) bridgeover 30 years of service life is rapidly increasing. Recently tendon corrosion is one of the most critical issues in the maintenance of PSC bridges. In this paper, mechanical properties of corroded strands, which were removed from old bridges, were evaluated using tensile test. In the result, the equations to express the mechanical behavior of corroded strand were derived and compared to existing equation. For the decision of tendon replacement, it is necessary to evaluate the effect of corrosion level on strength and ductility of the structure. Considerations on analysis of PSC girders were introduced, and decision making on tendon replacement was also proposed.

Keywords: prestressed concrete bridge, tendon, corrosion, strength, ductility

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Authors: Mehmet Yörükoğlu, Serhat Aydın

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Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.

Keywords: digital library, multi criteria decision making, SWARA-WASPAS method

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Authors: M. N. A. Azman, M. S. S. Ahamad

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The Construction Industry Development Board of Malaysia has been actively promoting the use of precast manufacturing in the local construction industry over the last decade. In an era of rapid technological changes, precast manufacturing significantly contributes to improving construction activities and ensuring sustainable economic growth. Current studies on the location decision of precast manufacturing plants aimed to enhanced local economic development are scarce. To address this gap, the present research establishes a new set of spatial criteria, such as attribute maps and preference weights, derived from a survey of local industry decision makers. These data represent the input parameters for the MCE-GIS site selection model, for which the weighted linear combination method is used. Verification tests on the model were conducted to determine the potential precast manufacturing sites in the state of Penang, Malaysia. The tests yield a predicted area of 12.87 acres located within a designated industrial zone. Although, the model is developed specifically for precast manufacturing plant but nevertheless it can be employed to other types of industries by following the methodology and guidelines proposed in the present research.

Keywords: geographical information system, multi criteria evaluation, industrialised building system, civil engineering

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

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In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: Katejarinporn Chaiya, Thawit Janbanklong

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The purposes of this study were to design and find users’ satisfaction after using the decision support system for tourism in the Northern part of Thailand, which can provide tourists with touristic information and plan their personal voyage. Such information can be retrieved systematically based on personal budget and provinces. The samples of this study were five experts and users: 30 "white collars" in Bangkok. This decision support system was designed via ASP.NET. Its database was developed by using MySQL, for administrators to effectively manage the database. The application outcome revealed that the innovation works properly as sought in objectives. Specialists and white collars in Bangkok have evaluated the decision support system; the result was satisfactorily positive.

Keywords: decision Support System, ASP.NET, MySQL, white collars

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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The assessment variables of the accessibility and the sustainability of access infrastructure for remote regions may vary significant by location and a wide range of factors may affect the decision process. In this paper, the environmental disturbance implications of transportation system to key demand and supply variables impact the economic system in remote destination are descripted. According to a systemic approach, the key sustainability variables deals with decision making process that have to be included in strategic plan for the critical transport infrastructure development and their relationship to regional socioeconomic system are presented. The application deals with the development of railway in remote destinations, where the traditional CBA not include the external cost generated by the environmental impacts that may have a range of diverse impacts on transport infrastructure and services. The analysis output provides key messages to decision and policy makers towards sustainable development of transport infrastructure, especially for remote destinations where accessibility is a key factor of regional economic development and social stability. The key conclusion could be essential useful for relevant applications in remote regions in the same latitude.

Keywords: sustainable development in remote regions, transport infrastructure, strategic planning, sustainability variables

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Authors: Libena Cernohorska, Barbora Sutorova, Petr Teply

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There are pending discussions over an impact of global regulatory efforts on banks. In this paper we present a literature review on the profitability-risk-capital relationship in banking. Research papers dealing with this topic can be divided into two groups: the first group focusing on a capital-risk relationship and the second group analyzing a capital-profitability relationship. The first group investigates whether the imposition of stricter capital requirements reduces risk-taking incentives of banks based on a simultaneous equations model. Their model pioneered the idea that the changes in both capital and risk have endogenous and exogenous components. The results obtained by the authors indicate that changes in the capital level are positively related to the changes in asset risk. The second group of the literature concentrating solely on the relationship between the level of held capital and bank profitability is limited. Nevertheless, there are a lot of studies dealing with the banks’ profitability as such, where bank capital is very often included as an explanatory variable. Based on the literature review of dozens of relevant papers in this study, an empirical research on banks’ profitability and risk adjustment decisions under new banking rules Basel III rules can be easily undertaken.

Keywords: bank, Basel III, capital, decision making, profitability, risk, simultaneous equations model

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: S. Kaira, S. Mohamed, A. Rahman

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Traditionally, highway infrastructure projects are initiated based on their economic benefits, thereafter environmental, social and governance impacts are addressed discretely for the selected project from a set of pre-determined alternatives. When opting for cost-benefit analysis (CBA), multi-criteria decision-making (MCDM) has been used as the default assessment tool. But this tool has been critiqued as it does not mimic the real-world dynamic environment. Indeed, it is because of the fact that public sector projects like highways have to experience intense exposure to dynamic environments. Therefore, it is essential to appreciate the impacts of various dynamic factors (factors that change or progress with the system) on project performance. Thus, this paper presents various sustainability assessment tools that have been globally developed to determine sustainability performance of infrastructure projects during the design, procurement and commissioning phase. Indeed, identification of the current gaps in the available assessment methods provides a potential to add prominent part of knowledge in the field of ‘road project development systems and procedures’ that are generally used by road agencies.

Keywords: dynamic impact factors, micro and macro factors, sustainability assessment framework, sustainability performance

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

Abstract:

Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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