Search results for: decision criteria

Authors: Sara Bouzekri, Said Madani

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In many Mediterranean cities such as Algiers, the human activity, the strong mobility the urban sprawl, the air pollution, the problems of waste management, the wasting of the resources and the degradation of the environment weaken in an unquestionable way the farming. The question of sustainable action vis-a-vis these threats arises then in order to maintain a level of desired local development. The methodology is based on a multi-criteria method based on the AFOM diagnosis, which classifies agricultural strength indicators and those of threat, according to an analytical approach. In a sustainable development perspective, it will be appropriate to link the threat factors of the case study with the factors of climate change to see their impact on the future of agriculture. This will be accompanied by a SWOT analysis, which crosses the most significant criteria to arrive at the necessary recommendations based on future projects for urban agriculture.

Keywords: Algiers, environment, urban agriculture, threat factors

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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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: A. Lubis, S. S. Pasulu, Z. Hikmah, A. Endaryanto, A. Harsono

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Infection by group A streptococci (GAS) can trigger an autoantibody that cause a poststreptococcal reactive arthritis (PSRA). Four patients with PSRA aged 10 years to 14 years old with the main complaint of joint pain for five days to 10 days after suffering a fever and sore throat. The joint pain was persistent, additive, and non migratory. All patients revealed an increase in erythrocyte sedimentation rate (ESR) and anti-streptolysin O (ASLO), but the chest x-ray, electrocardiography, and echocardiography were normal. Bone imaging showed no destruction on the affected joint. Jones Criteria were not fulfilled in all patients. Erythromycin and ibuprofen were given in all patients and an improvement was shown. Erythromycin was continued for one year and routine controls were conducted for cardiac evaluation. The prognosis of all the patients was good.

Keywords: arthritis, group a streptococcus, autoantibody, Jones criteria

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Authors: Pisit Potjanajaruwit

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The objective of this research was to study the influence of Integrated Marketing Communication on Buying Decision of Consumers in Bangkok. A total of 397 respondents were collected from customers who drive in Bangkok. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences. The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. In terms of occupation, the majority worked for private companies. The effect to the Buying Decision of Consumers in Bangkok to including sale promotion with the low interest and discount for an installment, selling by introducing and gave product information through sales persons, public relation by website, direct marketing by annual motor show and advertisement by television media.

Keywords: Bangkok metropolis, ECO car, integrated marketing communication, international standard

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Authors: Isabela Vieira, Leonor Carvalho Garcez, Adalmiro Pereira, Tânia Teixeira

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In the present work, we aim to analyse IKEA as a company, by focusing on its development, financial analysis and future benchmarks, as well as applying some of the knowledge learned in class, namely hedging and other financial risk mitigation solutions, to understand how IKEA navigates and protects itself from risk. The decision that led us to choose IKEA for our casework has to do with the long history of the company since the 1940s and its high internationalization in 63 different markets. The company also has clear financial reports which aided us in the making of the present essay and naturally, was a factor that contributed to our decision.

Keywords: Ikea, financial risk, risk management, hedge

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Authors: Priyanka Bharti

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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.

Keywords: cognition, visual, decision making, graphics, recognition

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Authors: Woosik Jang, Seung Heon Han, Seung Won Baek

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Natural gas (NG) is an energy resource in a few countries, and most NG producers do business in politically unstable countries. In addition, as 90% of the LNG market is controlled by a small number of international oil companies (IOCs) and national oil companies (NOCs), entry of latecomers into the market is extremely limited. To meet these challenges, project viability needs to be assessed based on limited information from a project screening perspective. However, the early stages of the project have the following difficulties: (1) What are the factors to consider? (2) How many professionals do you need to decide? (3) How to make the best decision with limited information? To address this problem, this study proposes a model for evaluating LNG project viability based on the Dempster-Shafer theory (DST). A total of 11 indicators for analyzing the gas field, reflecting the characteristics of the LNG industry, and 23 indicators for analyzing the market environment, were identified. The proposed model also evaluates the LNG project based on the survey and provides uncertainty of the results based on DST as well as quantified results. Thus, the proposed model is expected to be able to support the decision-making process of the gas field project using quantitative results as a systematic framework, and it was developed as a stand-alone system to improve its usefulness in practice. Consequently, the amount of information and the mathematical approach are expected to improve the quality and opportunity of decision making for LNG projects for enterprises.

Keywords: project screen, energy enterprise, decision support system, Dempster-Shafer theory

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Authors: M. Taghavi Zavareh, H. Saremi

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Railway transportation is one of the types of transportation systems which, due to the advantages such as the ability to transport a large number of passengers, environmental protection, low energy consumption, and contribution to tourism, has importance. The existence of suitable and accessible stations is one of the requirements that leads to better performance and plays a significant role in the economic, social, political, and cultural development of urban areas. This paper aims to propose a framework for locating railway passenger stations. This research used descriptive-analytical methods and library tools to answer which definitions and theoretical approaches are suitable for the location of railway passenger stations. The results showed that theoretical approaches such as Transit-Oriented Development and Urban Regeneration are of the utmost importance theoretical bases in the field of research. Moreover, we studied three stations in Iran to find out about real trends and criteria in this research. This study also proposed four major criteria including accessibility, development, rail related and economics, and environmental harmony. Ultimately with an emphasis on the proposed criteria, the study concludes that the combination of Transit-Oriented Development and Urban Regeneration is the most suitable framework to locate railway passenger stations.

Keywords: railway passenger station, railway station, site selection, transit-oriented development, urban regeneration

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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: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Deepak Singh, Rail Kuliev

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This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.

Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Wan Noorul Hafilah Binti Wan Ariffin

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Dam safety management is the crucial infrastructure as dam failure has a catastrophic effect on the community. Dam safety management is the effective framework of key actions and activities for the dam owner to manage the safety of the dam for its entire life cycle. However, maintaining dam safety is a challenging task as there are changes in current dam states. These changes introduce new risks to the dam's safety, which had not been considered when the dam was designed. A new framework has to be developed to adapt to the changes in the dam risk and make the dams resilient. This study proposes a risk-based decision-making adaptation framework for dam safety management. The research focuses on climate change's impact on hydrological situations as it causes floods and damages the dam structure. The risk analysis framework is adopted to improve the dam management strategies. The proposed study encompasses four phases. To start with, measuring the effect by assessing the impact of climate change on embankment dam, the second phase is to analyze the potential embankment dam failures. The third is analyzing the different components of risks related to the dam and, finally, developing a robust decision-making framework.

Keywords: climate change, embankment dam, failure, risk-informed decision making

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Mohamed Khallaf, Hossein M Rizeei

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Simulating wind pattern behavior over proposed urban features is critical in the early stage of the conceptual design of both architectural and urban disciplines. However, it is typically not possible for designers to explore the impact of wind flow profiles across new urban developments due to a lack of real data and inaccurate estimation of building parameters. Modeling the details of existing and proposed urban features and testing them against wind flows is the missing part of the conceptual design puzzle where architectural and urban discipline can focus. This research aims to develop a spatial decision-support design method utilizing LiDAR, GIS, and performance-based wind simulation technology to mitigate wind-related hazards on a design by simulating alternative design scenarios at the pedestrian level prior to its implementation in Sydney, Australia. The result of the experiment demonstrates the capability of the proposed framework to improve pedestrian comfort in relation to wind profile.

Keywords: spatial decision-support design, performance-based wind simulation, LiDAR, GIS

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Authors: Jou-An Chung

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The purpose of this study is to investigate the verb bias of the Mandarin verbs in children’s reading materials and provide the criteria for categorization. Verb bias varies cross-linguistically. As Mandarin and English are typological different, this study hopes to shed light on Mandarin verb bias with the use of corpus and provide thorough and detailed criteria for analysis. Moreover, this study focuses on children’s reading materials since it is a significant issue in understanding children’s sentence processing. Therefore, investigating verb bias of Mandarin verbs in children’s reading materials is also an important issue and can provide further insights into children’s sentence processing. The small corpus is built up for this study. The corpus consists of the collection of school textbooks and Mandarin Daily News for children. The files are then segmented and POS tagged by JiebaR (Chinese segmentation with R). For the ease of analysis, the one-word character verbs and intransitive verbs are excluded beforehand. The total of 20 high frequency verbs are hand-coded and are further categorized into one of the three types, namely DO type, SC type and other category. If the frequency of taking Other Type exceeds the threshold of 25%, the verb is excluded from the study. The results show that 10 verbs are direct object bias verbs, and six verbs are sentential complement bias verbs. The paired T-test was done to assure the statistical significance (p = 0.0001062 for DO bias verb, p=0.001149 for SC bias verb). The result has shown that in children’s reading materials, the DO biased verbs are used more than the SC bias verbs since the simplest structure of sentences is easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child's reading materials but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context. Sentences are easier for children’s sentence comprehension or processing. In sum, this study not only discussed verb bias in child corpus, but also provided basic coding criteria for verb bias analysis in Mandarin and underscored the role of context.

Keywords: corpus linguistics, verb bias, child language, psycholinguistics

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Authors: Jose Ramon Sanabria Navarro, Yahilina Silveira Perez, Valentin Molina Moreno, Digna Dionisia Perez Bravo

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The general objective of this research is to conceive a model of strategic direction for Latin American high-performance sports centers for the improvement of their results. The sample is 62 managers, 187 trainers, 2930 athletes and 62 expert researchers from centers in Cuba, Venezuela, Ecuador, Colombia and Argentina, for 3241. The measurement instrument includes 12 key variables in the process of management strategies which are consolidated with the factorial analysis and the ANOVA of a factor through the SPSS 24.0. The reliability of the scale obtained an alpha higher than 0.7 in each sample. In this sense, a model is obtained that taxes the deficiencies detected in the diagnosis, based on the needs of the members of these organizations, considering criteria and theories of the strategic direction in the improvement of the organizational results. The validation of the model for high performance sports centers of the countries analyzed aims to develop joint strategies to generate synergies in their operational mode, which leads to enhance the sports organization.

Keywords: sports organization, information management, decision making, control

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Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

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ALOHA code was used to calculate the concentration under the CO₂ storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan

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Authors: Ali E. Abbas

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This paper summarizes some of the discussions that occurred in a workshop in West Virginia, U.S.A which was sponsored by the National Science Foundation (NSF) in February 2016. The goal of the workshop was to explore the opportunities and challenges for applying systems engineering in large enterprises, and some of the issues that still persist. The main topics of the discussion included challenges with elaboration and abstraction in large systems, interfacing physical and social systems, and the need for axiomatic frameworks for large enterprises. We summarize these main points of discussion drawing parallels with decision making in organizations to instigate research in these discussion areas.

Keywords: decision analysis, systems engineering, framing, value creation

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Authors: Oren Shtayermman

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The current investigation expended on research among parents caring for a child who is diagnosed with an autism spectrum disorder (ASD). An online web survey was used to collect data from 253 parents caring for a child with a diagnosis of ASD. Both parents reported on elevated levels of parental stress associated with caring for the child on the spectrum. In addition, lower levels of marital satisfaction were found in both parents. About 13% of the parents in the sample met the diagnostic criteria for Major Depressive Disorder and About 15% of the parents met the diagnostic criteria for Generalized Anxiety Disorder. Although the majority of the sample was females (94%) significant differences were found between males and females in relation to meeting the diagnostic criteria for Major Depressive Disorder and for Generalized Anxiety Disorder. Higher levels of stress were associated with higher number of Generalized Anxiety Disorder symptoms and higher number of Major Depressive Disorder symptoms. Findings from this study indicate how vulnerable parents and especially females are in relation to caring to a child diagnosed with ASD. Educational Objectives: At the conclusion of the paper, the readers should be able to: -Identify levels of stress and marital satisfaction among parents caring for a child diagnosed with autism spectrum disorder, -Recognize the impact of stress on the development of mental health issues, -Name the two most common mood and anxiety related disorders associated with caring for a child diagnosed with an autism spectrum disorder.

Keywords: autism, stress, parents, children

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Authors: E. Baltas, E. Feloni, G. Bariamis

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The operation of a network of hydrometeorological-hydrometric stations is basic infrastructure for the management of water resources, as well as, for flood protection. The assessment of water resources potential led to the necessity of adoption management practices including a multi-criteria analysis for the optimum design of the region’s station network. This research work aims at the optimisation of a new/existing network, using GIS methods. The planning of optimum network stations is based on the guidelines of international organizations such as World Meteorological Organization (WMO). The uniform spatial distribution of the stations, the drainage basin for the hydrometric stations and criteria concerning the low terrain slope, the accessibility to the stations and proximity to hydrological interest sites, were taken into consideration for its development. The abovementioned methodology has been implemented for two different areas the Florina municipality and the Argolis area in Greece, and comparison of the results has been conducted.

Keywords: GIS, hydrometeorological, hydrometric, network, optimisation

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Ying Chuan Wang, Zhang Tao

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The aim of this article intends to explore the differences of well-being of employees in casino hotels before and after the Chinese government began to fight corruption. This researcher also attempted to find out the relationship between work pressure and well-being of employees in gambling workplaces before and after the Chinese government crackdowns the corruption. The category of well-being including life well-being, workplace well-being, and psychological well-being was included for analyzing well-being of employees in gaming workplaces. In addition, the psychological pressure classification was applied into this study and the Job Content Questionnaire (JCQ) would be adopted on investigating employees’ work pressure in terms of decision latitude, psychological demands, and workplace support. This study is a quantitative approach research and was conducted in March 2017. A purposive sampling was used in this study. A total of valid 339 responses were collected and the participants were casino hotel employees. The findings showed that decision latitude was significantly different prior to and after Chinese government crackdowns on corruption. Moreover, workplace support was strongly significantly related to employees’ well-being before Chinese government crackdowns. Decision latitude was strongly significantly related to employees’ well-being after Chinese government crackdowns. The findings suggest that employees’ work pressure affects their well being. In particular, because of workplace supports, it may alleviate employees’ work pressure and affect their perceptions of well-being but only prior to fighting the crackdowns. Importantly, decision latitude has become an essential factor affecting their well-being after the crackdown. It is finally hoped that the findings of this study provide suggestion to the managerial levels of hospitality industries. It is important to enhance employees’ decision latitude. Offering training courses to equip employees’ skills could be a possible way to reduce work pressure. In addition, establishing career path for the employees to pursuit is essential for their self-development and the improvement of well being. This would be crucial for casino hotels’ sustainable development and strengthening their competitiveness.

Keywords: well-being, work pressure, Casino hotels’ employees, gaming workplace

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Authors: Chang Ting, Wu Chun Kuan

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Wireless sensing technology is increasingly developed, in order to avoid caregiver neglect children in poor physiological condition, so there are more and more products into the wireless sensor-related technologies, in order to reduce the risk of infants. In view of this, the study will focus on Somatosensory detection wristbands Applied Research of Baby, and to explore through observation and literature, to find design criteria which conform baby products, as well as the advantages and disadvantages of existing products. This study will focus on 0-2 years of infant research and product design, to provide 2-3 new design concepts and products to identify weaknesses through the use of the actual product, further provide future baby wristbands design reference.

Keywords: infants, observation, design criteria, wireless sensing

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Authors: Xizhen Zhou, Yanjie Ji

Abstract:

The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Wided Khiari, Adel Karaa

Abstract:

This study aims to establish a typology of Tunisian listed firms according to their corporate governance characteristics and disclosure quality. The paper uses disclosed scores to examine corporate governance practices of Tunisian listed firms. A content analysis of 46 Tunisian listed firms from 2001 to 2010 has been carried out and a disclosure index developed to determine the level of disclosure of the companies. The disclosure quality is appreciated through the quantity and also through the nature (type) of information disclosed. Applying the decision tree method, the obtained tree diagrams provide ways to know the characteristics of a particular firm regardless of its level of disclosure. Obtained results show that the characteristics of corporate governance to achieve good quality of disclosure are not unique for all firms. These structures are not necessarily all of the recommendations of best practices, but converge towards the best combination. Indeed, in practice, there are companies which have a good quality of disclosure, but are not well-governed. However, we hope that by improving their governance system their level of disclosure may be better. These findings show, in a general way, a convergence towards the standards of corporate governance with a few exceptions related to the specificity of Tunisian listed firms and show the need for the adoption of a code for each context. These findings shed the light on corporate governance features that enhance incentives for good disclosure. It allows identifying, for each firm and in any date, corporate governance determinants of disclosure quality. More specifically, and all being equal, obtained tree makes a rule of decision for the company to know the level of disclosure based on certain characteristics of the governance strategy adopted by the latter.

Keywords: corporate governance, disclosure, decision tree, economics

Procedia PDF Downloads 331

Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

Abstract:

Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

Procedia PDF Downloads 118