Search results for: medical decision

Authors: Farzane Sadatnia, Bahram Fathi

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Today, all public and private organizations have found that the management of the world for key information related to the activities of a staff and its main essence and philosophy, though they constitute the management information systems are very helpful in this respect the right to apply systems can save a lot in terms of economic organizations including reducing the time decision - making, improve the quality of decision making, and cost savings to bring information systems is a backup system that can never be instead of logic and human reasoning, which can be used in the series is spreading, providing resources, and provide the necessary facilities, provide better services for users, balanced budget allocation, determine strengths and weaknesses and previous plans to review the current decisions and especially the decision . Hence; in this study attempts to the effect of an information system on a review of the organization.

Keywords: information system, planning, organization, coordination, control

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Authors: Tomáš Vyčítal

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In a simulation model of a railway system it is important, besides other crucial algorithms, to have correct behaviour of train overtaking in stochastic conditions. This problem is being addressed in many simulation tools focused on railway traffic, however these are not very human-realistic. The goal of this paper is to create a more human-realistic overtaking decision support system for the use in railway traffic simulations. A fuzzy system has been chosen for this task as fuzzy systems are well-suited for human-like decision making. The fuzzy system designed takes into account timetables, train positions, delays and buffer times as inputs and provides an instruction to overtake or not overtake.

Keywords: decision-making support, fuzzy systems, simulation, railway, transport

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Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

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Authors: Symbat Moldabekova

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This research explores the practice of decision-making in commercial banks in Kazakhstan. It focuses on recent technologies, such as contactless payments and QR code, and uses interviews with bank executives and industry practitioners to gain an understanding of how decisions are made and the role of financial assessment methods. The aim of the research is (1) to study the importance of financial techniques to evaluate IT investments; (2) to understand the role of different expert groups; (3) to explore how market trends and industry features affect decisions on IT; (4) to build a model that defines the real practice of decision-making on IT in commercial banks in Kazakhstan. The theoretical framework suggests that decision-making on IT is a socially constructed process, where actor groups with different background interact and negotiate with each other to develop a shared understanding of IT and to make more effective decisions. Theory and observations suggest that the more parties involved in the process of decision-making, the higher the possibility of disagreements between them. As each actor group has their views on the rational decision on an IT project, it is worth exploring how the final decision is made in practice. Initial findings show that the financial assessment methods are used as a guideline and do not play a big role in the final decision. The commercial banks of Kazakhstan tend to study experience of neighboring countries before adopting innovation. Implementing contactless payments is widely regarded as pinnacle success factor due to increasing competition in the market. First-to-market innovations are considered as priorities therefore, such decisions can be made with exemption of some certain actor groups from the process. Customers play significant role and they participate in testing demo versions of the products before bringing innovation to the market. The study will identify the viewpoints of actors in the banking sector on a rational decision, and the ways decision-makers from a variety of disciplines interact with each other in order to make a decision on IT in retail banks.

Keywords: actor groups, decision making, technology investment, retail banks

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Authors: Denise Hexom, Judith Menoher

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Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

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Authors: Tushar K. Routh

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If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.

Keywords: DNN robustness, decision boundary, local curvature, network complexity

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper introduces an original method of parametric optimization of the structure for multimodal decision-level fusion scheme which combines the results of the partial solution of the classification task obtained from assembly of the mono-modal classifiers. As a result, a multimodal fusion classifier which has the minimum value of the total error rate has been obtained.

Keywords: classification accuracy, fusion solution, total error rate, multimodal fusion classifier

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Authors: Issa M. Shehabat, Huda F. Y. Nimri

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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

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Authors: Yidnekachew Daget, Hong Zhang

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The decision-making process in order to select the suitable housing system for application in housing construction has been a challenge for many developing countries. This study evaluates the decision process to identify the suitable housing systems for adoption in Addis Ababa. Ten industrialized housing systems were considered as alternatives for comparison. These systems have been used in a housing development in different parts of the world. A relevant literature review and contextual analysis were conducted. An analytical hierarchy process and an Expert Choice Comparion platform were employed as a research technique and tool to evaluate the professionals’ level of preferences with regard to the housing systems. The findings revealed the priority rank and characteristics of the suitable housing systems to be adapted for application in housing development. The decision criteria and the analytical process used in this study can help the decision-makers and the housing developers in developing countries make effective evaluations and decisions.

Keywords: analytical hierarchy process, decision-making, expert choice comparion, industrialized housing systems

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Adegoriola Mayowa I., Lai Joseph H. K., Yung Esther H. K., Chan Edwin H. K.

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Heritage buildings (HBs) as structures with historical and architectural relevance that form an integral part of contemporary society. These buildings deserve to be protected for as long as possible to retain their significance. Therefore, the need to prioritize HB maintenance management is pertinent. However, the decision-making process of HBMM can be relatively daunting. The decision-making challenge may be attributed to the multiple 'stakeholders' expectation and requirement which needs to be met. To this end, professionals in the built environment have identified the need to apply the strategic concept of facilities management (FM) in decision making. Furthermore, the different maintenance dimensions have been applied to maintenance management of residential, commercial, and health facilities. Unfortunately, these different maintenance approaches, such as FM, sustainable FM, urban FM, green FM, and strategic FM, are yet to be fully explored in the decision-making process of HBMM. To bridge this gap, this study focuses on developing a framework for strategic decision-making HBMM, which helps achieve HBMM sustainability. At the study's inception, relevant works of literature in the domains of HBMM and FM were conducted. This review helped in the identification of contemporary maintenance practices and their applicability to HBMM. Afterward, a conceptual framework to aid decision-making in HBMM was developed. This framework integrated the concept of FM scope (people, place, process, and technology) while ensuring that decisions plans were made at strategic, tactical, and operational levels. Also, the different characteristics of HBs and stakeholders' requirements were considered in the framework. The conceptual framework presents a holistic guide for professionals in HBMM to ensure that decision processes and outcomes are practical and efficient. It also contributes to the existing body of knowledge on the integration of FM in HBMM. Furthermore, it will serve as a basis for future studies by applying the conceptualized framework in actual cases.

Keywords: decision-making, facility management, strategy, sustainability, heritage building, maintenance

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Authors: Paramet Damchoo

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The purpose of this study is to study the factors that influence the decision making of foreign volunteer tourists in Thailand. A sample size was 400 drawn from 10 provinces of Thailand using cluster sampling method. The factor analysis was used to analysis the data. The findings indicate that volunteer tourism which was based in Thailand contained a total of 45 activities which could be divided into 4 categories. The most of these tourists were from Europe including UK and Scandinavia which was 54.50 percent. Moreover, the tourists were male rather than female and 63.50 Percent of them ware younger than 20 years old. It is also found that there are 67.00 percent of the tourists used website to find where the volunteer tourism was based. Finally, the factors that influence the decision making of foreign volunteer tourists in Thailand consist of a wide variety of activities together with a flexibility in their activities and also low prices.

Keywords: decision making, volunteer tourism, special interest tourism, GAP year

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Authors: Lin Peng, Jin Zhang, Yuanyuan Miao, Quanquan Zheng

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Group discussion and group decision-making have long been a topic of research interest. Traditional research on group decision making typically focuses on the strategies or functional models of combining members’ preferences to reach an optimal consensus. In this research, we want to explore natural process group decision making through discussion and examine relevant, influential factors--common superordinate identity shared by group and size of the groups. We manipulated the social identity of the groups into either a shared superordinate identity or different subgroup identities. We also manipulated the size to make it either a big (6-8 person) group or small group (3-person group). Using experimental methods, we found members of a superordinate identity group tend to modify more of their own opinions through the discussion, compared to those only identifying with their subgroups. Besides, members of superordinate identity groups also formed stronger identification with group decision--the results of group discussion than their subgroup peers. We also found higher member modification in bigger groups compared to smaller groups. Evaluations of decisions before and after discussion as well as group decisions are strongly linked to group identity, as members of superordinate group feel more confident and satisfied with both the results and decision-making process. Members’ opinions are more similar and homogeneous in smaller groups compared to bigger groups. This research have many implications for further research and applied behaviors in organizations.

Keywords: group decision making, group size, identification, modification, superordinate identity

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Authors: Ayman M. Mansour

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In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: fuzzy logic, inference system, monitoring system, multi-agent system

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Authors: Nasser Almonawer

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Timely reaction to an evolving global business environment and volatile market conditions necessitates system and process flexibility, which in turn demands agile and adaptable architecture and a steady infusion of affordable new technologies. On the contrary, a large number of organizations utilize systems characterized by inflexible and obsolete legacy architectures. To effectively respond to the dynamic contemporary business environments, such architectures must be migrated to robust and modular open architectures. To this end, this paper proposes an integrated decision support system for a seamless migration to open systems. The proposed decision support system (DSS) integrates three well-established quantitative and qualitative decision-making models—namely, the Delphi method, Analytic Hierarchy Process (AHP) and Goal Programming (GP) to (1) assess risks and establish evaluation criteria; (2) formulate migration strategy and rank candidate systems; and (3) allocate resources among the selected systems.

Keywords: decision support systems, open systems architecture, analytic hierarchy process (AHP), goal programming (GP), delphi method

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Authors: Erdal Akyol, Mutlu Alkan

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Multi criteria decision analysis (MDCA) covers both data and experience. It is very common to solve the problems with many parameters and uncertainties. GIS supported solutions improve and speed up the decision process. Weighted grading as a MDCA method is employed for solving the geotechnical problems. In this study, geotechnical parameters namely soil type; SPT (N) blow number, shear wave velocity (Vs) and depth of underground water level (DUWL) have been engaged in MDCA and GIS. In terms of geotechnical aspects, the settlement suitability of the municipal area was analyzed by the method. MDCA results were compatible with the geotechnical observations and experience. The method can be employed in geotechnical oriented microzoning studies if the criteria are well evaluated.

Keywords: GIS, spatial analysis, multi criteria decision analysis, geotechnics

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Taksina Bunbut, Kevin Wongleedee

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The purposes of this research were to study factors influencing the decision of international tourists to revisit Bangkok, Thailand. A random 200 samples was collected. Half the sample group was male and the other half was female. A questionnaire was used to collect data and small in-depth interviews were also used to get their opinions about importance of tourist decision making factors. The findings revealed that the majority of respondents rated these factors at medium level of importance. The ranking showed that the first three important factors were a safe place to stay, friendly people, and clean food. The three least important factors were a convenience transportation, clean country, and child friendly. In addition there was no significance difference between male and female in their ratings of the factors of influencing the decision of international tourists to revisit Bangkok, Thailand.

Keywords: factors, international tourists, revisit, Thailand

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Sakul Jariyachansit

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The purposes of this research were to investigate and to compare the factors affecting the decision for Tourism in Thailand by ASEAN Tourists and among ASEAN community tourists. Samples in this research were 400 ASEAN Community Tourists who travel in Thailand at Suvarnabhumi Airport during November 2016 - February 2016. The researchers determined the sample size by using the formula Taro Yamane at 95% confidence level tolerances 0.05. The English questionnaire, research instrument, was distributed by convenience sampling, for gathering data. Descriptive statistics was applied to analyze percentages, mean and standard deviation and used for hypothesis testing. The statistical analysis by multiple regression analysis (Multiple Regression) was employed to prove the relationship hypotheses at the significant level of 0.01. The results showed that majority of the respondents indicated the factors affecting the decision for Tourism in Thailand by ASEAN Tourists, in general there were a moderate effects and the mean of each side is moderate. Transportation was the most influential factor for tourism in Thailand. Therefore, the mode of transport, information, infrastructure and personnel are very important to factor affecting decision making for tourism in Thailand by ASEAN tourists. From the hypothesis testing, it can be predicted that the decision for choosing Tourism in Thailand is at R2 = 0.449. The predictive equation is decision for choosing Tourism in Thailand = 1.195 (constant value) + 0.425 (tourist attraction) +0.217 (information received) and transportation factors, tourist attraction, information, human resource and infrastructure at the significant level of 0.01.

Keywords: factor, decision making, ASEAN tourists, tourism in Thailand

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Authors: Helen Pushkarskaya, Michael Smithson, Jane E. Joseph, Christine Corbly, Ifat Levy

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Studies of decision making under uncertainty generally focus on imprecise information about outcome probabilities (“ambiguity”). It is not clear, however, whether conflicting information about outcome probabilities affects decision making in the same manner as ambiguity does. Here we combine functional Magnetic Resonance Imaging (fMRI) and a simple gamble design to study this question. In this design, the levels of ambiguity and conflict are parametrically varied, and ambiguity and conflict gambles are matched on both expected value and variance. Behaviorally, participants avoided conflict more than ambiguity, and attitudes toward ambiguity and conflict did not correlate across subjects. Neurally, regional brain activation was differentially modulated by ambiguity level and aversion to ambiguity and by conflict level and aversion to conflict. Activation in the medial prefrontal cortex was correlated with the level of ambiguity and with ambiguity aversion, whereas activation in the ventral striatum was correlated with the level of conflict and with conflict aversion. This novel double dissociation indicates that decision makers process imprecise and conflicting information differently, a finding that has important implications for basic and clinical research.

Keywords: decision making, uncertainty, ambiguity, conflict, fMRI

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Alma Sobrevilla

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Using panel data from Mexico, this paper studies the determinants of women’s intrahousehold decision-making power using a generalised ordered logit model. Fixed effects estimations are also carried out to solve potential endogeneity coming from unobservable time-invariant factors. Finally, the paper analyses quadratic and community divergence effects of education on power. Results show heterogeneity in the effect of each of the determinants across different levels of decision-making power and suggest the presence of a significant quadratic effect of education. Having more education than the community average has a negative effect on power, supporting the notion that women tend to compensate their success outside the household with submissive attitudes at home.

Keywords: women, decision-making power, intrahousehold, Mexico

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Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

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Authors: Bright C. Opara, Gideon C. Uboegbulam

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This study can be appreciated from the significant role culture exert in purchase decision of durable goods the world over. This study is motivated by cultural diversity in Nigeria and socio-economic changes that have taken place in the recent times. These call for the validation of similarly studies in order to formulate informed marketing strategies that will enhance purchase behaviour. This study therefore, is set out to examine the cultural influence in family purchase decision-making for durable goods in the three major ethnic groups in Nigeria (Hausa, Ibo, and Yoruba). The primary data was sourced using structured and semi-structured research questionnaire, while the secondary information was generated from existing / available relevant literature journals / periodicals. A judgmental sampling technique was used to determine the sample size of 300 households. The Analysis of Variance (ANOVA) statistical tool was used to test the hypotheses, with the aid of Statistical Packages for Social Sciences (SPSS) version 17.0. The finding showed that cultural influence on the family Purchase Decision of Durable Goods does not significantly differ in three ethnic groups, and that family Purchase Decision Making for Durable Goods does not significantly differ in the three ethnic groups. We therefore, conclude that culture do not really impact significantly on the purchase behaviour of the three ethnic groups in the Nigeria as it does in some others. However, there is need for marketers and marketing decision makers not to generalise the findings of this study. This is because of the significant role culture play in purchase behaviour which differs from one culture or country to another.

Keywords: cultural, durable goods, influence, purchase decision

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Authors: Nora Alkharji, Wafa Fallatah

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Introduction: One of the major issues to consider when is deciding on what to feed a baby is the quality of the food itself. Whilst commercially prepared infant formulas are a nutritious alternative to breast milk, and even contain some vitamins and nutrients, most major medical organizations consider breastfeeding the best nutritional option for babies. Choosing whether to breastfeed or formula feed your baby is one of the first decisions expectant parents will make. The American Academy of Pediatrics (AAP) is in agreement with other organizations such as the American Medical Association (AMA), the American Dietetic Association (ADA), and the World Health Organization (WHO) in recommending breastfeeding as the best nutrition for babies and best suited for a baby's digestive system. In addition, breastfeeding helps in the combatting of infections, prevention of allergies, and protection against various chronic conditions. The decision to breastfeed or formula feed one’s baby is a very personal one. However, certain points need to be clarified regarding the nutritional value of breastfeeding versus formula feeding to allow for informed decision-making. Methodology: -A formal debate about whether to breastfeed or formula feed babies as the better choice. -There will be two debaters, both lactation consultants -Arguments will be based on evidence-based medicine -Duration period of debated: 45 min Result: Clarification and heightened awareness of the benefits of breastfeeding. Conclusion: This debate will make the choice between breastfeeding or formula feeding a relatively easy one to make by both health worker and parents.

Keywords: breastmilk, formula milk, nutritional, comparison

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Authors: M. Karaman, H. Catalkaya

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Due to the complex nature of cyber attacks and their effects ranging from personal to governmental level, it becomes one of the priority tasks for operation planners to take into account the risks, influences and effects of cyber attacks. However it can also be embedded or integrated technically with electronic warfare planning, cyber operation planning is needed to have a sole and broadened perspective. This perspective embodies itself firstly in operational design and then military decision making process. In order to find out the ill-structured problems, understand or visualize the operational environment and frame the problem, operational design can help support cyber operation planners and commanders. After having a broadened and conceptual startup with cyber operational design, military decision making process will follow the principles of design into more concrete elements like reaching results after risk management and center of gravity analysis of our and the enemy. In this paper we tried to emphasize the importance of cyber operational design, cyber operation planning and its integration to military decision making problem. In this foggy, uncertain and unaccountable cyber security environment, it is inevitable to stay away from cyber attacks. Therefore, a cyber operational design should be formed with line of operations, decisive points and end states in cyber then a tactical military decision making process should be followed with cyber security focus in order to support the whole operation.

Keywords: cyber operational design, military decision making process (MDMP), operation planning, end state

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Musthaya Patchanee

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The aim of this research is to study potential factors relating to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province by conducting a random sampling of 400 people aged between 15-59 who migrated from Myanmar. The information collected through interviews was analyzed to find a percentage and mean using the Stepwise Multiple Regression Analysis. The results have shown that 33.25% of Myanmar migrant workers want to return to their home country within the next 1-5 years, 46.25%, in 6-10 years and the rest, in over 10 years. The factors relating to such decision can be concluded that the scale of the decision of return migration has a positive relationship with a statistical significance at 0.05 with a conformity with friends and relatives (r=0.886), a relationship with family and community (r=0.782), possession of land in hometown (r=0.756) and educational level (r=0.699). However, the factor of property possession in Prachuap Khiri Khan is the only factor with a high negative relationship (r=0.-537). From the Stepwise Multiple Regression Analysis, the results have shown that the conformity with friends and relatives and educational level factors are influential to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province, which can predict the decision at 86.60% and the multiple regression equation from the analysis is Y= 6.744+1.198 conformity + 0.647 education.

Keywords: decision of return migration, factors of return migration, Myanmar migrant workers, Prachuap Khiri Khan Province

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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