Search results for: investment decision

Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: Search path planning, false alarm, search-and-delivery, entropy, genetic algorithm.

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Authors: Yung-Chien Sun, O. Grant Clark

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In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: Saleh Komies, Mona Alharbi, Razan Alhayyani, Mozah Almulhim, Roseanne Khawaja, Ahmed Alradhi

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One of the proposed solutions that face some challenges is encouraging sustainable energy consumption across Saudi Arabia through crowdfunding platforms. To address these challenges, we need to determine the level of awareness of crowdfunding and green projects, as well as the preferences and willingness of Saudis to utilize crowdfunding as an alternative funding source for green projects in Saudi Arabia. In this study, we aim to determine the influence of environmental awareness and concern on the propensity to crowdfund green projects. The survey is being conducted as part of environmental initiatives to assess public perceptions and opinions on crowdfunding green projects in Saudi Arabia. A total of 450 responses to an online questionnaire distributed via convenience and snowball sampling were utilized for data analysis. The survey reveals that Saudis have a low understanding of crowdfunding concepts and a relatively high understanding of implementing green projects. The public is interested in crowdfunding green projects if there is a return on investment.

Keywords: Crowdfunding, green projects, renewable energy, Saudi Arabia, solar farms, wind resources.

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Authors: Jin Xu, Albert Y.S. Lam, Victor O.K. Li

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Stock portfolio selection is a classic problem in finance, and it involves deciding how to allocate an institution-s or an individual-s wealth to a number of stocks, with certain investment objectives (return and risk). In this paper, we adopt the classical Markowitz mean-variance model and consider an additional common realistic constraint, namely, the cardinality constraint. Thus, stock portfolio optimization becomes a mixed-integer quadratic programming problem and it is difficult to be solved by exact optimization algorithms. Chemical Reaction Optimization (CRO), which mimics the molecular interactions in a chemical reaction process, is a population-based metaheuristic method. Two different types of CRO, named canonical CRO and Super Molecule-based CRO (S-CRO), are proposed to solve the stock portfolio selection problem. We test both canonical CRO and S-CRO on a benchmark and compare their performance under two criteria: Markowitz efficient frontier (Pareto frontier) and Sharpe ratio. Computational experiments suggest that S-CRO is promising in handling the stock portfolio optimization problem.

Keywords: Stock portfolio selection, Markowitz model, Chemical Reaction Optimization, Sharpe ratio

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Authors: Pejman Hosseinioun, Rose Shayeghi, Ghasem Ghorbani Rostam

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Nowadays, obtaining traditional statistics and reports is not adequate for the needs of organizational managers. The managers need to analyze and to transform the raw data into knowledge in the world filled with information. Therefore in this regard various processes have been developed. In the meantime the artificial intelligence-based processes are used and the new topics such as business intelligence and knowledge discovery have emerged. In the current paper it is sought to study the business intelligence and its applications in the organizations.

Keywords: Business intelligence, business intelligence infrastructures, business processes.

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Authors: S. K. Dewangan, K. R. Sahu, S. K. Patnayak, S. Soni

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Among many agro- based cottage industries in India sericulture has been promoted as an agro-based, labor intensive, rural oriented cottage industry, providing gainful employment mainly to the weaker and marginalized section of the society specially tribal. Sericulture occupies the place of pride in the rural economy can be practiced even with very low land holding, low gestation, high returns make sericulture an ideal program, requiring little capital investment. In 2010-2011 the employment in sericulture sector was 72.5 lakh persons. The involvement of landless rural people in tasar sericulture is because they understood its potential for rural and tribal upliftment. This article demonstrates that certain developmental initiatives have been playing an important role in the socio-economic progress of tribal masses in Raigarh district and explains the increased returns from sericulture as a result of development programs. The study concludes with some suggestions to improve the long term feasibility of sericulture.

Keywords: Development, Employment, Income, Sericulture, Tribal, Tasar,

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Authors: Sanjoy Mukherjee

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Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (G_inc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: Tracking system, grid-connected PV systems, cost reduction.

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Authors: M. Priscila Ramos, Omar O. Chisari, Juan Pablo Vila Martínez

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Current literature about trade liberalization of environmental goods and services (EGS) raises doubts about the extent of the triple win-win situation for trade, development and the environment. However, much of this literature does not consider the possibility that this agreement carries technological transmissions, either through trade or foreign direct investment. This paper presents a computable general equilibrium model calibrated for Argentina, where there are alternative technologies (one dirty and one clean according to carbon emissions) to produce the same goods. In this context, the trade liberalization of EGS allows to increase GDP, trade, reduce unemployment and improve the households welfare. However, the capital mobility appears as the key assumption to jointly reach the environmental target, when the positive scale effect generated by the increase in trade is offset by the change in the composition of production (composition and technical effects by the use of the clean alternative technology) and of consumption (composition effect by substitution of relatively lesspolluting imported goods).

Keywords: CGE modeling, CO2 emissions, composition effect, scale effect, technique effect, trade liberalization of EGS.

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Authors: Nasrin Farajiparvar

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In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.

Keywords: Condition-based maintenance, Economic savings, Iran industries, Machine life prediction software.

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Authors: Hirohide Ushida

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This paper discusses an artificial mind model and its applications. The mind model is based on some theories which assert that emotion is an important function in human decision making. An artificial mind model with emotion is built, and the model is applied to action selection of autonomous agents. In three examples, the agents interact with humans and their environments. The examples show the proposed model effectively work in both virtual agents and real robots.

Keywords: Artificial mind, emotion, interactive agent, pet robot

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Authors: Beata Czarnacka-Chrobot

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Majority of Business Software Systems (BSS) Development and Enhancement Projects (D&EP) fail to meet criteria of their effectiveness, what leads to the considerable financial losses. One of the fundamental reasons for such projects- exceptionally low success rate are improperly derived estimates for their costs and time. In the case of BSS D&EP these attributes are determined by the work effort, meanwhile reliable and objective effort estimation still appears to be a great challenge to the software engineering. Thus this paper is aimed at presenting the most important synthetic conclusions coming from the author-s own studies concerning the main factors of effective BSS D&EP work effort estimation. Thanks to the rational investment decisions made on the basis of reliable and objective criteria it is possible to reduce losses caused not only by abandoned projects but also by large scale of overrunning the time and costs of BSS D&EP execution.

Keywords: Benchmarking data, business software systems development and enhancement projects, effort estimation, software engineering economics, software functional size measurement.

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Authors: Peter Newton, Peter Newman, Stephen Glackin, Roman Trubka

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Pressures for urban redevelopment are intensifying in all large cities. A new logic for urban development is required – green urbanism – that provides a spatial framework for directing population and investment inwards to brownfields and greyfields precincts, rather than outwards to the greenfields. This represents both a major opportunity and a major challenge for city planners in pluralist liberal democracies. However, plans for more compact forms of urban redevelopment are stalling in the face of community resistance. A new paradigm and spatial planning platform is required that will support timely multi-level and multi-actor stakeholder engagement, resulting in the emergence of consensus plans for precinct-level urban regeneration capable of more rapid implementation. Using Melbourne, Australia as a case study, this paper addresses two of the urban intervention challenges – where and how – via the application of a 21st century planning tool ENVISION created for this purpose.

Keywords: Green urbanism, greyfields, planning tools, urban regeneration.

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Authors: Tin Seong Kam, Ketan Barshikar, Shaun Tan

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The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner-s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners to explore and analyze city-s transportation data to gain valuable insights about city-s traffic flow and transportation requirements. We demonstrate the potential of DIVAD through the use of interactive choropleth and hexagon binning maps to explore and analyze large taxi-transportation data of Singapore for different geographic and time zones.

Keywords: Geographic Information System (GIS), MovementData, GeoVisual Analytics, Urban Planning.

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Authors: K. Balamurugan, R. Muralisachithanandam, V. Dharmalingam, R. Srikanth

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This paper deals with the optimal choice and allocation of multi FACTS devices in Deregulated power system using Evolutionary Programming method. The objective is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices are simulated in this study such as UPFC, TCSC, TCPST, and SVC. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and allocation of FACTS devices in deregulated electricity market environment. The standard data of IEEE 14 Bus systems has been taken into account and simulated with aid of MAT-lab software and results were obtained.

Keywords: FACTS devices, Optimal allocation, Deregulated electricity market, Evolutionary programming, Mat Lab.

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Authors: Veljko Jeremic, Milica Kostic-Stankovic, Aleksandar Markovic, Milan Martic

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Evaluating the efficiency of decision making units has been frequently elaborated on in numerous publications. In this paper, the theoretical framework for a novel method of Distance Based Analysis (DBA) is presented. In addition, the method is performed on a sample of the ARWU’s top 54 Universities of the United States; the findings of which clearly demonstrate that the best ranked Universities are far from also being the most efficient.

Keywords: Evaluating Efficiency, Distance Based Analysis, Ranking of Universities, ARWU.

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Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani

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Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.

Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.

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Authors: Ali A. Bazzi, Ameer Hamza, Riley O’Hara, Kimberly Kado, Karen H. Hagglund, Lamia Fathallah, Robert T. Morris

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Introduction: Endometrial Cancer is a common gynecologic malignancy primarily treated with complete surgical staging, which may include complete pelvic and para-aortic lymphadenectomy. The role of lymphadenectomy is controversial, especially the intraoperative indications for the procedure. Three factors are important in decision to proceed with lymphadenectomy: Myometrial invasion, maximum tumor dimension, and histology. Many institutions incorporate these criteria in varying degrees in the decision to proceed with lymphadenectomy. This investigation assesses the use of intraoperatively measured MTD with and without pre-operative histologic grade. Methods: This study compared retrospectively EEC patients with intraoperatively measured MTD ≤2 cm to those with MTD >2 cm from January 1, 2002 to August 31, 2017. This assessment compared those with MTD ≤ 2cm with endometrial biopsy (EB) grade 1-2 to patients with MTD > 2cm with EB grade 3. Lymph node metastasis (LNM), recurrence, and survival were compared in these groups. Results: This study reviewed 222 patient cases. In tumors > 2 cm, LNM occurred in 20% cases while in tumors ≤ 2 cm, LNM was found in 6% cases (p=0.04). Recurrence and mean survival based on last follow up visit in these two groups were not statistically different (p=0.78 and 0.36 respectively). Data demonstrated a trend that when combined with preoperative EB International Federation of Gynecology and Obstetrics (FIGO) grade, a higher proportion of patients with EB FIGO Grade 3 and MTD > 2 cm had LNM compared to those with EB FIGO Grade 1-2 and MTD ≤ 2 cm (43% vs, 11%, p=0.06). LNM was found in 15% of cases in which lymphadenectomy was performed based on current practices, whereas if the criteria of EB FIGO 3 and MTD > 2 cm were used the incidence of LNM would have been 44% cases. However, using this criterion, two patients would not have had their nodal metastases detected. Compared to the current practice, the sensitivity and specificity of the proposed criteria would be 60% and 81%, respectively. The PPV and NPV would be 43% and 90%, respectively. Conclusion: The results indicate that MTD combined with EB FIGO grade can detect LNM in a higher proportion of cases when compared to current practice. MTD combined with EB FIGO grade may eliminate the need of frozen section sampling in a substantial number of cases.

Keywords: Endometrial cancer, FIGO grade, lymphadenectomy, tumor size.

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Authors: Y. Egercioglu, S. Yalciner

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With the development of technology, the growing trend of fast and safe passenger transport, air pollution, traffic congestion, increase in problems such as the increasing population and the high cost of private vehicle usage made many cities around the world with a population of more or less, start to build rail systems as a means of urban transport in order to ensure the economic and environmental sustainability and more efficient use of land in the city. The implementation phase of rail systems costs much more than other public transport systems. However, social and economic returns in the long term made these systems the most popular investment tool for planned and developing cities. In our country, the purpose, goals and policies of transportation plans are away from integrity, and the problems are not clearly detected. Also, not defined and incomplete assessment of transportation systems and insufficient financial analysis are the most important cause of failure. Rail systems and other transportation systems to be addressed as a whole is seen as the main factor in increasing efficiency in applications that are not integrated yet in our country to come to this point has led to the problem.

Keywords: Urban Transportation Projects, Urban Light Rail Systems, Urbanization, Izmir.

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: Case-based reasoning, knowledge, police, public efficiency.

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: Artificial Neural Network, Decision Support System, drug abuse, drug addiction, Multilayer Perceptron.

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Authors: Paitoon Kraipornsak

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Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.

Keywords: Complementary effect, government capital spending, government consumption spending, private consumption on food, nonfood, and services, substitution effect, vector error correction mechanism.

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Authors: Rajendra M. Sonar

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The recent trend has been using hybrid approach rather than using a single intelligent technique to solve the problems. In this paper, we describe and discuss a framework to develop enterprise solutions that are backed by intelligent techniques. The framework not only uses intelligent techniques themselves but it is a complete environment that includes various interfaces and components to develop the intelligent solutions. The framework is completely Web-based and uses XML extensively. It can work like shared plat-form to be accessed by multiple developers, users and decision makers.

Keywords: Intelligent System Development Framework, WebbasedIntelligent Systems, Retail Banking.

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Authors: Toshihiko Takemura, Makoto Osajima, Masatoshi Kawano

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This paper includes a positive analysis to quantitatively grasp the relationship among vulnerability, information security incidents, and the countermeasures by using data based on a 2007 questionnaire survey for Japanese ISPs (Internet Service Providers). To grasp the relationships, logistic regression analysis is used. The results clarify that there are relationships between information security incidents and the countermeasures. Concretely, there is a positive relationship between information security incidents and the number of information security systems introduced as well as a negative relationship between information security incidents and information security education. It is also pointed out that (especially, local) ISPs do not execute efficient information security countermeasures/ investment concerned with systems, and it is suggested that they should positively execute information security education. In addition, to further heighten the information security level of Japanese telecommunication infrastructure, the necessity and importance of the government to implement policy to support the countermeasures of ISPs is insisted.

Keywords: Information security countermeasures, information security incidents, internet service providers, positive analysis

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Authors: Tal Ben-Zvi, Donald N. Lombardi

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This study uses a simulation to establish a realistic environment for laboratory research on Accountable Care Organizations. We study network attributes in order to gain insights regarding healthcare providers- conduct and performance. Our findings indicate how network structure creates significant differences in organizational performance. We demonstrate how healthcare providers positioning themselves at the central, pivotal point of the network while maintaining their alliances with their partners produce better outcomes.

Keywords: Social Networks, Decision-Making, Accountable Care Organizations, Performance

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: Recurrent Neural Network, players lineup, basketball data, decision making model.

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Authors: N. Javadian, J. Rezaeian, Y. Maali

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In this paper a multi-objective nonlinear programming model of cellular manufacturing system is presented which minimize the intercell movements and maximize the sum of reliability of cells. We present a genetic approach for finding efficient solutions to the problem of cell formation for products having multiple routings. These methods find the non-dominated solutions and according to decision makers prefer, the best solution will be chosen.

Keywords: Cellular Manufacturing, Genetic Algorithm, Multiobjective, Life-Cycle.

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Authors: B. Farhadinia

Abstract:

Although so far, many methods for ranking fuzzy numbers have been discussed broadly, most of them contained some shortcomings, such as requirement of complicated calculations, inconsistency with human intuition and indiscrimination. The motivation of this study is to develop a model for ranking fuzzy numbers based on the lexicographical ordering which provides decision-makers with a simple and efficient algorithm to generate an ordering founded on a precedence. The main emphasis here is put on the ease of use and reliability. The effectiveness of the proposed method is finally demonstrated by including a comprehensive comparing different ranking methods with the present one.

Keywords: Ranking fuzzy numbers, Lexicographical ordering.

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Authors: Giovane Gurgel, Cristina S. Rodrigues, Filipa D. Vieira

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IFRN – Mossoró is a Brazilian technical education institute that develops several activities to encourage entrepreneurship, such as a curricular discipline about enterprise management and the existence of a business incubator. Despite efforts, the business incubator does not produce the expected effects. Therefore, what predisposes students to start their own business? If literature review explores determinant factors like the family and personal characteristics, it can be sustained that entrepreneurship skills can be taught since primary level, until university level. This paper presents the results of research project “Empreende IFRN” to understand the entrepreneurial predisposition and intention of the students from technical level courses. Data from 365 students from technical level courses reveal an increased entrepreneurial intention of students during time (from a 2 years period to someday in the future). The entrepreneurial behavior of parents affects students’ perception about starting their own business. Students also present a cautions behavior, preferring bank deposit and investment fund instead starting a business.

Keywords: Brazil, Entrepreneurial intention, Entrepreneurship, Secondary technical students.

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Authors: H. Fallah, Z. Naddaf Baghdadabadi

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Planning of economic activities development has various dimensions one of which determines adequate capacity of economic activities in provinces regarding the government-s goals. Paralleling planning goals of economic activities development including subjects being focused on the view statement is effective to better realize the statement's goals. Current paper presents a native framework for economic activities development in provincial level. Triple steps within the framework are concordant with the view statement-s goals achievement. At first step of the proposed framework, economic activities are being prioritized in terms of employment indices, and secondly economic activities regarding to the province's relative advantages are being recognized. In the third step, desirable capacity of economic activities is determined with regards to the government's goals and effective constraints in economic activities development. Development of economic activities related to the provinces- relative advantages, contributes on regional balance and on equal development of economic activities. Furthermore, results of the framework enable more confident investment, affect employment development and remove unemployment concern as the main goals of the view statement.

Keywords: Development, economic activity, regional planning, view statement.

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Authors: Chiung-ying Lee, Chia-hua Chang

Abstract:

In July 1, 2007, Taiwan Stock Exchange (TWSE) on market observation post system (MOPS) adds a new "Financial reference database" for investors to do investment reference. This database as a warning to public offering companies listed on the public financial information and it original within eight targets. In this paper, this database provided by the indicators for the application of company financial crisis early warning model verify that the database provided by the indicator forecast for the financial crisis, whether or not companies have a high accuracy rate as opposed to domestic and foreign scholars have positive results. There is use of Logistic Regression Model application of the financial early warning model, in which no joined back-conditions is the first model, joined it in is the second model, has been taken occurred in the financial crisis of companies to research samples and then business took place before the financial crisis point with T-1 and T-2 sample data to do positive analysis. The results show that this database provided the debt ratio and net per share for the best forecast variables.

Keywords: Financial reference database, Financial early warning model, Logistic Regression.

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