Search results for: Bayes' decision

Authors: O. Badagadze, G. Sirbiladze, I. Khutsishvili

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The work proposes a decision support methodology for the credit risk minimization in selection of investment projects. The methodology provides two stages of projects’ evaluation. Preliminary selection of projects with minor credit risks is made using the Expertons Method. The second stage makes ranking of chosen projects using the Possibilistic Discrimination Analysis Method. The latter is a new modification of a well-known Method of Fuzzy Discrimination Analysis.

Keywords: expert valuations, expertons, investment project risks, positive and negative discriminations, possibility distribution

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Authors: Shahram Keshavarzi

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Today, getting good service, having a good time, and leaving the company with good feelings are importanttforbothcustomers and businesses. It has been observed that when customersareexposedtopleasantsmells, their visit times increase by 26%, and theyvisittheaislesfor 3 times longer. Byusingtheeffect of scents on people, it is toensurethatcustomersshopmore, benefit from the service and be satisfied. Intoday'sresearch, visual memory can be 40% effective after a period of 4 months, whileolfactorymemory is 60% moreeffectiveevenafter 1 year. The purpose of the research is thehiddenandeffectivepower of skepticism in the behavior of consumersandtheeffectivestrategy of modern marketing. Special scentsdirectlyaffecttheincrease in sales by influencing the customer's-decision mechanism in purchasing products.

Keywords: modern marketing strategy, scent, scent marketing, consumer behavior

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Authors: Ione Loots, Marco van Dijk, Jay Bhagwan

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Historically, South Africa had various small-scale hydropower installations in remote areas that were not incorporated in the national electricity grid. Unfortunately, in the 1960s most of these plants were decommissioned when Eskom, the national power utility, rapidly expanded its grid and capability to produce cheap, reliable, coal-fired electricity. This situation persisted until 2008, when rolling power cuts started to affect all citizens. This, together with the rising monetary and environmental cost of coal-based power generation, has sparked new interest in small-scale hydropower development, especially in remote areas or at locations (like wastewater treatment works) that could not afford to be without electricity for long periods at a time. Even though South Africa does not have the same, large-scale, hydropower potential as some other African countries, significant potential for micro- and small-scale hydropower is hidden in various places. As an example, large quantities of raw and potable water are conveyed daily under either pressurized or gravity conditions over large distances and elevations. Due to the relative water scarcity in the country, South Africa also has more than 4900 registered dams of varying capacities. However, institutional capacity and skills have not been maintained in recent years and therefore the identification of hydropower potential, as well as the development of micro- and small-scale hydropower plants has not gained significant momentum. An assessment model and decision support system for low head hydropower development has been developed to assist designers and decision makers with first-order potential analysis. As a result, various potential sites were identified and many of these sites were situated at existing infrastructure like weirs, barrages or pipelines. One reason for the specific interest in existing infrastructure is the fact that capital expenditure could be minimized and another is the reduced negative environmental impact compared to greenfield sites. This paper will explore the case study of retrofitting an unconventional and innovative hydropower plant to the outlet of a wastewater treatment works in South Africa.

Keywords: low head hydropower, retrofitting, small-scale hydropower, wastewater treatment works

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Authors: Stefano Federici, Alessandro Lepri, Antonella Carrera

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Kessler and McKenna in the seventies, and recently Federici and Lepri investigated how an individual attributes gender to a person. By administering nudes of human figures, the scholars have found that the penis more than the vagina and the male sexual characteristics more than the female ones are significantly more salient in the gender attribution process. Federici and Lepri suggested that the asymmetrical salience of sexual characteristics is attributable to evolved decision-making processes for the solution of gender attribution problems to avoid the greatest danger of an (angry) adult male. The present study has observed the behaviour of 60 children, aged between 3 and 6 years, and their parents verifying whether the child gender attribution mechanisms are permeable to cultural stereotypes. The participating children were asked to make a male or a female on a tablet by combining 12 human physical characteristics (long hair, short hair, wide hips, narrow hips, breasts, flat chest, body hair, hairless body, penis, vagina, male face, and female face) and four cloths (male t-shirt, female t-shirt, pants, and skirt) by superimposing one or more of them on a sexually neutral manikin. On the tablet was installed an App, created by authors, to replicate the Kessler and McKenna and Federici and Lepri previous studies. One of the parents of each of the participating children was asked to make a male or a female using the same apparatus used by children. In addition, the participating parents were asked to complete a test, as proposed by Federici and Lepri in their previous study, to compare adult and child processes of gender attribution. The results suggested that children are affected both by evolved mechanisms as adults were (e.g., taking less time to make a male than a female, using the penis more often than the vagina), and by cultural modeling of parental and environmental gender stereotypes (e.g., the genitals were often covered with pants in case the delivery was to make a male and a skirt in the case was to make a female).

Keywords: biological sex, cognitive biases, cultural modeling, gender attribution, evolved decision-making processes

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Authors: T. H. Bitebe, T. M. Lima, F. Charrua-Santos, C. J. Matias Oliveira

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This study aims to present a proposal for an economic integration model for the development of the manufacturing industry in Cabinda, Angola. It seeks to analyze the degree of economic integration of Cabinda and the dynamics of the manufacturing industry. Therefore, in the same way, to gather information to support the decision-making for public financing programs that will aim at the disengagement of the manufacturing industry in Angola and Cabinda in particular. The Cabinda Province is the 18^th of Angola, the enclave is located in a privileged area of the African and arable land.

Keywords: economic integration, industrial development, Cabinda industry, Angola

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Authors: Preeti Madan, Shalini Malhotra, Nirmaljit Kaur, Charoo Hans, VK Sabarwal

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Hospital is one of the most diverse and complex institutions frequented by people from every walk of life without any distinction between age, sex, gender, religion or intellect. This is over and above the normal inhabitant of hospital i.e. doctors, patients, and paramedical staff. The hospital waste generated 85% is non hazardous, 10% infectious and around 5% are non-infectious but hazardous waste. The management of biomedical waste is still in its infancy. There is a lot of confusion with the problems among the generators, operators, decision makers, and general community about the safe management of biomedical waste prompt action initiated to seek new scientific, safe, and cost-effective management of waste.

Keywords: biomedical waste, nosocomial infection, waste management, hospitals

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: Lundqvist M., Alwin J., Levin L-A.

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Background: Assistance dogs are dogs trained to assist persons with functional impairment or chronic diseases. The assistance dog concept includes different types: guide dogs, hearing dogs, and service dogs. The service dog can further be divided into subgroups of physical services dogs, diabetes alert dogs, and seizure alert dogs. To examine the long-term effects of health care interventions, both in terms of resource use and health outcomes, cost-effectiveness analyses can be conducted. This analysis can provide important input to decision-makers when setting priorities. Little is known when it comes to the cost-effectiveness of assistance dogs. The study aimed to assess the cost-effectiveness of certified service or hearing dogs in comparison to regular companion dogs. Methods: The main data source for the analysis was the “service and hearing dog project”. It was a longitudinal interventional study with a pre-post design that incorporated fifty-five owners and their dogs. Data on all relevant costs affected by the use of a service dog such as; municipal services, health care costs, costs of sick leave, and costs of informal care were collected. Health-related quality of life was measured with the standardized instrument EQ-5D-3L. A decision-analytic Markov model was constructed to conduct the cost-effectiveness analysis. Outcomes were estimated over a 10-year time horizon. The incremental cost-effectiveness ratio expressed as cost per gained quality-adjusted life year was the primary outcome. The analysis employed a societal perspective. Results: The result of the cost-effectiveness analysis showed that compared to a regular companion dog, a certified dog is cost-effective with both lower total costs [-32,000 USD] and more quality-adjusted life-years [0.17]. Also, we will present subgroup results analyzing the cost-effectiveness of physicals service dogs and diabetes alert dogs. Conclusions: The study shows that a certified dog is cost-effective in comparison with a regular companion dog for individuals with functional impairments or chronic diseases. Analyses of uncertainty imply that further studies are needed.

Keywords: service dogs, hearing dogs, health economics, Markov model, quality-adjusted, life years

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Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

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Authors: Anna Carolina De Paula Sermarini, Rodrigo Flora Calili

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Energy Efficiency (EE) needs investments, new technologies, greater awareness and management on the side of citizens and organizations, and more planning. However, this issue is usually remembered and discussed only in moments of energy crises, and opportunities are missed to take better advantage of the potential of EE in the various sectors of the economy. In addition, there is little concern about the subject among the less favored classes, especially in low-income communities. Accordingly, this article presents suggestions for public policies that aim to increase EE for low-income housing and communities based on international and national experiences. After reviewing the literature, eight policies were listed, and to evaluate them; a multicriteria decision model was developed using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods, combined with fuzzy logic. Nine experts analyzed the policies according to 9 criteria: economic impact, social impact, environmental impact, previous experience, the difficulty of implementation, possibility/ease of monitoring and evaluating the policies, expected impact, political risks, and public governance and sustainability of the sector. The results found in order of preference are (i) Incentive program for equipment replacement; (ii) Community awareness program; (iii) EE Program with a greater focus on low income; (iv) Staggered and compulsory certification of social interest buildings; (v) Programs for the expansion of smart metering, energy monitoring and digitalization; (vi) Financing program for construction and retrofitting of houses with the emphasis on EE; (vii) Income tax deduction for investment in EE projects in low-income households made by companies; (viii) White certificates of energy for low-income. First, the policy of equipment substitution has been employed in Brazil and the world and has proven effective in promoting EE. For implementation, efforts are needed from the federal and state governments, which can encourage companies to reduce prices, and provide some type of aid for the purchase of such equipment. In second place is the community awareness program, promoting socio-educational actions on EE concepts and with energy conservation tips. This policy is simple to implement and has already been used by many distribution utilities in Brazil. It can be carried out through bids defined by the government in specific areas, being executed by third sector companies with public and private resources. Third on the list is the proposal to continue the Energy Efficiency Program (which obliges electric energy companies to allocate resources for research in the area) by suggesting the return of the mandatory investment of 60% of the resources in projects for low income. It is also relatively simple to implement, requiring efforts by the federal government to make it mandatory, and on the part of the distributors, compliance is needed. The success of the suggestions depends on changes in the established rules and efforts from the interested parties. For future work, we suggest the development of pilot projects in low-income communities in Brazil and the application of other multicriteria decision support methods to compare the results obtained in this study.

Keywords: energy efficiency, low-income community, public policy, multicriteria decision making

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Authors: Dimitrios J. Dimitriou

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Considering a worldwide tendency, air transports are growing very fast and many changes have taken place in planning, management and decision making process. Given the complexity of airport operation, the best use of existing capacity is the key driver of efficiency and productivity. This paper deals with the evaluation framework for the ground access at airports, by using a set of mode choice indicators providing key messages towards airport’s ground access performance. The application presents results for a sample of 12 European airports, illustrating recommendations to define policy and improve service for the air transport access chain.

Keywords: airport ground access, air transport chain, airport access performance, airport policy

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Authors: Jiri Barta

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This paper deals with a simulation programs and technologies using in the educational process for members of the crisis management. Risk analysis, simulation, preparation and planning are among the main activities of workers of crisis management. Made correctly simulation of emergency defines the extent of the danger. On this basis, it is possible to effectively prepare and plan measures to minimize damage. The paper is focused on simulation programs that are trained at the University of Defence. Implementation of the outputs from simulation programs in decision-making processes of crisis staffs is one of the main tasks of the research project.

Keywords: crisis management, continuity, critical infrastructure, dangerous substance, education, flood, simulation programs

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Authors: Adedeji S. Adegoke, Olakunle N. Popoola

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Promotion is indispensible and inestimable property of marketing through which different organizations persuade their prospective customers. The idea of passing information about a product to the consumer at outside the world is known as promotional activities. A study was determined whether there was relationship between promotional mix and consumer buying decision, that is may be customers were influenced by promotion. It was investigated to determine whether promotion can be used to influence competitors’ activities in the market and also research was conducted to determine if there was any problem encountered by Nigeria bottling company plc, in promoting its beverages products. The various forms of promotional mix available for an organization were examined and recommended the appropriate promotional mix that company can adopt to boost the company sales. The research design was depended on the primary and secondary data. The primary data were information collected from the subjects using methods of data collection, that is through the use of questionnaire, interview, direct observation, etc. The secondary data consist of information that already exists having been collected for another purpose by some researchers. These include internal and external sources. The questionnaire was designed and administered to the staff of production and marketing department of Nigeria bottling company plc., which served as the population of this study, out of which sample was drawn randomly from the population, using sample random technique. It was deduced that 90% of the respondents opined that advertising influenced competition in the market and that there was a good sale after they started advert while 10% of them were not sure. At advertising level, 85% of the respondents chose 81-100% as the increase in the percentage recorded in their sales level, while 10% of them agreed that increase in the percentage recorded in their sales was within 61-80% and 5% of them chose 45-60% as the percentage increase in their sales record. Due to unstable economic condition of the Nigeria, many business organizations adopted the promotional strategies. Apart from advertising, it was discovered through research that sales promotion served as an incentive to consumers of Nigeria bottling company plc at a time offer gifts and prizes to consumers which drastically increased their level of sales. Since advertising and sales promotion increased the level of sales, more money should be allocated for this purpose to maintain market share and thereby increase profit.

Keywords: consumer, marketing, organization, promotional mix

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Authors: Dorra Gherib

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This article explores in depth the technological innovations by the Top Managements of banks in the Tunisian banking sector. The framework of this research is based on an amalgamation of four theories related to the decision of adopting technological innovations: The Theory of Reasoned Action (TRA), the Theory of Planned Behaviour (TPB), Technology Acceptance Model (TAM), and Diffusion of Innovation (DI). The result of our qualitative study highlights four variables which influence the attitude of the Top Managements towards the adoption of internet banking: Relative advantage, Perceived Ease of Use, compatibility and Perceived risk.

Keywords: top management, attitude, internet banking, TRA, TAM, TPB, DI

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Authors: Jeena R. S., Sukesh Kumar A.

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Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: John M. Ikome

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In the process of manufacturing, a machine breakdown usually forces a modified flow shop out of the prescribed state, this strategy reschedules part of the initial schedule to match up with the pre-schedule at some point with the objective to create a schedule that is reliable with the other production planning decisions like material flow, production and suppliers by utilizing a critical decision-making concept. We propose a rescheduling strategy and a match-up point that will have a determination procedure through an advanced feedback control mechanism to increase both the schedule quality and stability. These approaches are compared with alternative re-scheduling methods under different experimental settings.

Keywords: scheduling, heuristics, branch, integrated

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Authors: Mai Hoang Minh

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Financial statements (FS) are tools which provide information to users for making business decisions. This article is going to present the survey which clarifies the role of financial statement to Commercial Banks’ loan decisions in Vietnam. Moreover, this also discusses about financial statement’s quality currently, thereby making suggestions for enterprises to enhance the usefulness of accounting information in borrowing activities.

Keywords: usefulness of financial statement, accounting information quality, loan decisions

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Authors: Evangelia-Chrysanthi Kouklari, Evdokia Tagkouli, Vassiliki Ntre, Artemios Pehlivanidis, Stella Tsermentseli, Gerasimos Kolaitis, Katerina Papanikolaou

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Executive Function (EF) is a set of goal-directed cognitive skills essentially needed in problem-solving and social behavior. Developmental EF research has indicated that EF emerges early in life and marks dramatic changes before the age of 5. Research evidence has suggested that it may continue to develop up to adolescence as well, following the development of the prefrontal cortex. Over the last decade, research evidence has suggested distinguished domains of cool and hot EF, but traditionally the development of EF in Autism Spectrum Disorder (ASD) has been examined mainly with tasks that address the “cool” cognitive aspects of EF. Thus, very little is known about the development of “hot” affective EF processes and whether the cross-sectional developmental pathways of cool and hot EF present similarities in ASD. Cool EF has also been proven to have a strong correlation with Theory of Mind (ToM) in young and middle childhood in typical development and in ASD, but information about the relationship of hot EF to ToM skills is minimal. The present study’s objective was to explore the age-related changes of cool and hot EF in ASD participants from middle childhood to adolescence, as well as their relationship to ToM. This study employed an approach of cross-sectional developmental trajectories to investigate patterns of cool and hot EF relative to chronological age within ASD. Eighty-two participants between 7 and 16 years of age were recruited to undertake measures that assessed cool EF (working memory, cognitive flexibility, planning & inhibition), hot EF (affective decision making & delay discounting) and ToM (false belief and mental state/emotion recognition). Results demonstrated that trajectories of all cool EF presented age-related changes in ASD (improvements with age). With regards to hot EF, affective decision-making presented age-related changes, but for delay discounting, there were no statistically significant changes found across younger and older ASD participants. ToM was correlated only to cool EF. Theoretical implications are discussed as the investigation of the cross-sectional developmental trajectories of the broader EF (cool and hot domains) may contribute to better defining cognitive phenotypes in ASD. These findings highlight the need to examine developmental trajectories of both hot and cool EF in research and clinical practice as they may aid in enhancing diagnosis or better-informed intervention programs.

Keywords: autism spectrum disorder, developmental trajectories, executive function, theory of mind

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Authors: Mohammad Mahbub Alam Talukder, Shahnewaz, Hasanat-E-Rabbi, Mohammed Nazrul Islam

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Road traffic accident is a global problem which is severe in the developing countries like Bangladesh. In consequence, in developing countries road trauma has now been recognized as an increasing public health hazards and economic burning issue. And after road traffic accidents the lack of management and economic costs related with health seeking behavior have a disproportionate impact on lower income groups, thus contributing to the persistence of poverty in conjunction with disability. This cross sectional study, carried out during July 2012 to June 2013, aimed to explore health seeking decision and culture of handling the road traffic accident related victims, as taken from experiences of the poor disabled people of slum dwellers of Dhaka city. The present study has been designed based on qualitative techniques such as in-depth interview and case studies. Additionally, a survey questionnaire was used to collect the demographic characteristics of the study population (n=150) and to select participants purposely for in-depth interview (n=50) and case study (n=30). Content analysis of qualitative data was done through theme coding and matrix analysis of case study was done to use relevant verbatim. Most of the time the health seeking decision totally depended on the surrounded people of the accidental place, their knowledge, awareness and remaining facility and capacity regarding proper management of the victims. However, most of the cases the victims did not get any early treatment and it took 2-12 hours to get even the first aid because of distance, shortage of money, lack of availability of getting the aid, lack of mass awareness etc. Under the reality of discriminated and unaffordable health service provision better treatment could not turn out due to economic inability of the poor victims. To avoid the severe trauma, treatment delay must be reduced by providing first aid within very short time and to do so, mass awareness campaign is necessary for handing the victims. Moreover, necessary measures should be taken to ensure cost free health service provision to treat the chronic disabled condition of the road traffic accident related poor victims.

Keywords: accident, injury, disabled, qualitative, slum

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Authors: S. M. Amin Hosseini, Oriol Pons, Carmen Mendoza Arroyo, Albert de la Fuente

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In the aftermath of a natural disaster, the major challenge most cities and societies face, regardless of their diverse level of prosperity, is to provide temporary housing (TH) for the displaced population (DP). However, the features of TH, which have been applied in previous recovery programs, greatly varied from case to case. This situation demonstrates that providing temporary accommodation for DP in a short period time and usually in great numbers is complicated in terms of satisfying all the beneficiaries’ needs, regardless of the societies’ welfare levels. Furthermore, when previously used strategies are applied to different areas, the chosen strategies are most likely destined to fail, unless the strategies are context and culturally based. Therefore, as the population of disaster-prone cities are increasing, decision-makers need a platform to help to determine all the factors, which caused the outcomes of the prior programs. To this end, this paper aims to assess the problems, requirements, limitations, potential responses, chosen strategies, and their outcomes, in order to determine the main elements that have influenced the TH process. In this regard, and in order to determine a customizable strategy, this study analyses the TH programs of five different cases as: Marmara earthquake, 1999; Bam earthquake, 2003; Aceh earthquake and tsunami, 2004; Hurricane Katrina, 2005; and, L’Aquila earthquake, 2009. The research results demonstrate that the main vertexes of TH are: (1) local characteristics, including local potential and affected population features, (2) TH properties, which needs to be considered in four phases: planning, provision/construction, operation, and second life, and (3) natural hazards impacts, which embraces intensity and type. Accordingly, this study offers decision-makers the opportunity to discover the main vertexes, their subsets, interactions, and the relation between strategies and outcomes based on the local conditions of each case. Consequently, authorities may acquire the capability to design a customizable method in the face of complicated post-disaster housing in the wake of future natural disasters.

Keywords: post-disaster temporary accommodation, urban resilience, natural disaster, local characteristic

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Authors: Kim Jin-OK, Lee Jin-Eui, Han Seung-Hoon, Kim Nam-Jo

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This study aimed to analyze the effect of the motivation of Chinese tourists to visit North Korea on their decision making process. Chinese tourists account for a considerable portion of foreign tourists in the world, while North Korea is the favorite tourist attraction of Chinese tourists. The motivation to visit North Korea was divided into three factors: the redness, which is the modern cultural heritage of Communism based on the red tourism accounting for the significant portion of domestic tourism, the novelty of the special environment of North Korean society, and the convenience of tour to North Korea in terms of geographical distance and policy of China. Red tourism refers to visiting the places of revolutionary events, monuments, artifacts and the residences of previous communist leaders, and other places related to the past Chinese Communist Party. As a revolutionary tourism, red tourism has recently been taking place in the old communist countries to recall their memories on the revolutionary places in China, as well as in North Korea, Vietnam, Cambodia, Russia, Bulgaria, Cuba, etc. In order to examine the effect of the segmented motivations on the revisit intention of Chinese tourists who have experienced a tour to North Korea, this study employed the model of goal-directed behavior, a model developed by adding a variable of emotion to the theory of planned behavior, which has a strong explanatory power on the decision making process of people in social science. For achieving the aim of the study, the data was collected through the survey in Dandong, China against Chinese tourists who have visited North Korea. The results of this study found that not only the novelty of North Korea, but also the redness, which accounts for the largest proportion in the domestic tourism, are significantly affecting overseas tour of Chinese tourists at this time point where overseas tour of Chinese tourists continue to increase. The results, therefore, suggest that the old communist countries, including those in Asia, need an emotional promotion strategy that stimulates nostalgia by focusing on the redness of the modern cultural heritage of Communism to attract Chinese tourists.

Keywords: model of goal-directed behavior, modern cultural heritage, North Korea, red tourism

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Mohammad Daud Ali

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For the past decade, marketing ethics has been a central point for academic researchers and practitioners. In particular, the development of frameworks and models to help in the analysis of marketing decisions are the focus of research. The current study aims at finding whether ethical decisions (honesty, fairness, responsibility, and respect) affect organizational marketing decisions. A selection of 250 respondents was purposely made from the telecommunication industry of Pakistan, out of which 204 responses were induced at an acceptable rate of 81.6%. A five-point Likert Scale, itemized with 12 items, was adopted from Taylor-Dunlop & Lester (2000) and used to draw responses regarding ethics.

Keywords: marketing, ethics, decisions making, telecommunication, Pakistan

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Authors: Cachanda K. Orellana

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This study examined preservice teachers’ perceptions of their role in digital citizenship education. Data was gathered via surveys and coursework from the preservice teachers’ instructional technology course. Pre-service teachers were asked about their role in digital citizenship education during a unit on digital dilemmas. Findings suggest that teacher education programs should consider digital citizenship education as more than the acquisition of a set of skills and behaviors and prepare preservice teachers to support students’ ability to engage in ethical decision-making in digital spaces.

Keywords: digital citizenship, digital dilemmas, pre-service teachers, teacher education

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Authors: Mine Koyaz, M. Cem Altun

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Selection of the materials satisfying the expected performances is significantly important for any design. Today, with the constantly evolving and developing technologies, the material options are so wide that the necessity of the use of some support tools in the selection process is arising. Therefore, as a sub process of building element design, a systematic material selection tool is developed, that defines four main steps of the material selection; definition, research, comparison and decision. The main purpose of the tool is being an educational instrument that would show a methodic way of material selection in architectural detailing for the use of architecture students. The tool predefines the possible uses of various material databases and other sources of information on material properties. Hence, it is to be used as a guidance for designers, especially with a limited material knowledge and experience. The material selection tool not only embraces technical properties of materials related with building elements’ functional requirements, but also its sensual properties related with the identity of design and its environmental impacts with respect to the sustainability of the design. The method followed in the development of the tool has two main sections; first the examination and application of the existing methods and second the development of trial versions and their applications. Within the scope of the existing methods; design support tools, methodic approaches for the building element design and material selection process, material properties, material databases, methodic approaches for the decision making process are examined. The existing methods are applied by architecture students and newly graduate architects through different design problems. With respect to the results of these applications, strong and weak sides of the existing material selection tools are presented. A main flow chart of the material selection tool has been developed with the objective to apply the strong aspects of the existing methods and develop their weak sides. Through different stages, a different aspect of the material selection process is investigated and the tool took its final form. Systematic material selection tool, within the building element design process, guides the users with a minimum background information, to practically and accurately determine the ideal material that is to be chosen, satisfying the needs of their design. The tool has a flexible structure that answers different needs of different designs and designers. The trial version issued in this paper shows one of the paths that could be followed and illustrates its application over a design problem.

Keywords: architectural education, building element design, material selection tool, systematic approach

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Authors: Satish Kumar, Nisha Goyal

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In the stock market, individual investors exhibit different kinds of behaviour. Traditional finance is built on the notion of 'homo economics', which states that humans always make perfectly rational choices to maximize their wealth and minimize risk. That is, traditional finance has concern for how investors should behave rather than how actual investors are behaving. Behavioural finance provides the explanation for this phenomenon. Although finance has been studied for thousands of years, behavioural finance is an emerging field that combines the behavioural or psychological aspects with conventional economic and financial theories to provide explanations on how emotions and cognitive factors influence investors’ behaviours. These emotions and cognitive factors are known as behavioural biases. Because of these biases, investors make irrational investment decisions. Besides, the emotional and cognitive factors, the social influence of media as well as friends, relatives and colleagues also affect investment decisions. Psychological factors influence individual investors’ investment decision making, but few studies have used qualitative methods to understand these factors. The aim of this study is to explore the behavioural factors or biases that affect individuals’ investment decision making. For the purpose of this exploratory study, an in-depth interview method was used because it provides much more exhaustive information and a relaxed atmosphere in which people feel more comfortable to provide information. Twenty investment advisors having a minimum 5 years’ experience in securities firms were interviewed. In this study, thematic content analysis was used to analyse interview transcripts. Thematic content analysis process involves analysis of transcripts, coding and identification of themes from data. Based on the analysis we categorized the statements of advisors into various themes. Past market returns and volatility; preference for safe returns; tendency to believe they are better than others; tendency to divide their money into different accounts/assets; tendency to hold on to loss-making assets; preference to invest in familiar securities; tendency to believe that past events were predictable; tendency to rely on the reference point; tendency to rely on other sources of information; tendency to have regret for making past decisions; tendency to have more sensitivity towards losses than gains; tendency to rely on own skills; tendency to buy rising stocks with the expectation that this rise will continue etc. are some of the major concerns showed by experts about investors. The findings of the study revealed 13 biases such as overconfidence bias, disposition effect, familiarity bias, framing effect, anchoring bias, availability bias, self-attribution bias, representativeness, mental accounting, hindsight bias, regret aversion, loss aversion and herding bias/media biases present in Indian investors. These biases have a negative connotation because they produce a distortion in the calculation of an outcome. These biases are classified under three categories such as cognitive errors, emotional biases and social interaction. The findings of this study may assist both financial service providers and researchers to understand the various psychological biases of individual investors in investment decision making. Additionally, individual investors will also be aware of the behavioural biases that will aid them to make sensible and efficient investment decisions.

Keywords: financial advisors, individual investors, investment decisions, psychological biases, qualitative thematic content analysis

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Authors: Rawan Hakawati, Beatrice Smyth, David Rooney, Geoffrey McCullough

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Targets have been set in the EU to increase the share of renewable energy consumption to 20% by 2020, but developments have not occurred evenly across the member states. Northern Ireland is almost 90% dependent on imported fossil fuels. With such high energy dependency, Northern Ireland is particularly susceptible to the security of supply issues. Linked to fossil fuels are greenhouse gas emissions, and the EU plans to reduce emissions by 20% by 2020. The use of indigenously produced biomass could reduce both greenhouse gas emissions and external energy dependence. With a wide range of both crop and waste feedstock potentially available in Northern Ireland, anaerobic digestion has been put forward as a possible solution for renewable energy production, waste management, and greenhouse gas reduction. Not all feedstock, however, is the same, and an understanding of feedstock suitability is important for both plant operators and policy makers. The aim of this paper is to investigate biomass suitability for anaerobic digestion in Northern Ireland. It is also important that decisions are based on solid scientific evidence. For this reason, the methodology used is multi-criteria decision matrix analysis which takes multiple criteria into account simultaneously and ranks alternatives accordingly. The model uses the weighted sum method (which follows the Entropy Method to measure uncertainty using probability theory) to decide on weights. The Topsis method is utilized to carry out the mathematical analysis to provide the final scores. Feedstock that is currently available in Northern Ireland was classified into two categories: wastes (manure, sewage sludge and food waste) and energy crops, specifically grass silage. To select the most suitable feedstock, methane yield, feedstock availability, feedstock production cost, biogas production, calorific value, produced kilowatt-hours, dry matter content, and carbon to nitrogen ratio were assessed. The highest weight (0.249) corresponded to production cost reflecting a variation of £41 gate fee to 22£/tonne cost. The weights calculated found that grass silage was the most suitable feedstock. A sensitivity analysis was then conducted to investigate the impact of weights. The analysis used the Pugh Matrix Method which relies upon The Analytical Hierarchy Process and pairwise comparisons to determine a weighting for each criterion. The results showed that the highest weight (0.193) corresponded to biogas production indicating that grass silage and manure are the most suitable feedstock. Introducing co-digestion of two or more substrates can boost the biogas yield due to a synergistic effect induced by the feedstock to favor positive biological interactions. A further benefit of co-digesting manure is that the anaerobic digestion process also acts as a waste management strategy. From the research, it was concluded that energy from agricultural biomass is highly advantageous in Northern Ireland because it would increase the country's production of renewable energy, manage waste production, and would limit the production of greenhouse gases (current contribution from agriculture sector is 26%). Decision-making methods based on scientific evidence aid policy makers in classifying multiple criteria in a logical mathematical manner in order to reach a resolution.

Keywords: anaerobic digestion, biomass as feedstock, decision matrix, renewable energy

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Authors: Gete Umbrey, Saifur Rahman

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Graphs are found to be most capable in computing, and its abstract structures have been applied in some specific computations and algorithms like in phase encoding controller, processor microcontroller, and synthesis of a CMOS switching network, etc. Being motivated by these works, we develop an independent approach to study semiring structures and various properties by defining the binary operations which in fact, seems analogous to an existing definition in some sense but with a different approach. This work emphasizes specifically on the construction of semigroup and semiring structures on the set of undirected graphs, and their properties are investigated therein. It is expected that the investigation done here may have some interesting applications in theoretical computer science, networking and decision making, and also on joining of two network systems.

Keywords: graphs, join and union of graphs, semiring, weighted graphs

Procedia PDF Downloads 148