Search results for: decision tree

Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

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In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Malay Niraj, Praveen Kumar

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The present study is a new approach for improving equipment life and Overall Equipment Efficiency (O.E.E.) through suitable maintenance practice with the help of value engineering. Value engineering is a one of the most powerful decision-making techniques which depend on many factors. The improvements are the result of recommendations made by multidisciplinary teams representing all parties involved. VE is a rigorous, systematic effort to improve the OEE and optimize the life cycle cost of a facility. The study describes problems in maintenance arising due to the absence of having clear criteria and strong decision constrain how to maintain failing equipment. Using factor comparisons, the study has been made between different maintenance practices and finally best maintenance practice based on value engineering technique has been selected.

Keywords: maintenance strategy, overall equipment efficiency, value engineering, decision-making

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Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

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Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: group decision making, intuitionistic fuzzy set, intuitionistic fuzzy entropy measure, vendor selection, VIKOR

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Authors: Miguel Mellado, Cecilia Zapata

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Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

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Authors: Gunawan Prayitno, Kakuya Matshusima, Kiyoshi Kobayashi

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Indonesia’s rural regions are characterized by wide-spread poverty, under-employment, and surplus of low-skilled labor. The aim of this paper is to empirically prove the effect of social ties (strong and weak tie) as social capital construct on households’ migration decision in the case of developing country (Indonesia). The methodology incorporated indicators of observe variables (four demographic attributes data: income, occupation, education, and family members) and indicators of latent variables (ties to neighbors, ties to community and sense of place) provided by responses to survey questions to aid in estimating the model. Using structural equation model that we employed in Mplus program, the result of our study shows that ties to community positively have a significant impact to the decision of respondents (migrate or not). Besides, education as observed variable directly influences the migration decisions. It seems that higher level of education have impact on migration decision. Our current model so far could explain the relation between social capital and migration decision choice.

Keywords: migration, ties to community, ties to neighbors, education

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Mehtap Dursun, Zeynep Şener

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Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

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Authors: Rebecca Greenberg, Nipa Chauhan, Rashad Rehman

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Paternalism, in its traditional form, seems largely incompatible with Western medicine. In contrast, Family-Centred Care, a partial response to historically authoritative paternalism, carries its own challenges, particularly when operationalized as family-directed care. Specifically, in neonatology, decision-making is left entirely to Substitute Decision Makers (most commonly parents). Most models of shared decision-making employ both the parents’ and medical team’s perspectives but do not recognize the inherent asymmetry of information and experience – asking parents to act like physicians to evaluate technical data and encourage physicians to refrain from strong medical opinions and proposals. They also do not fully appreciate the difficulties in adjudicating which perspective to prioritize and, moreover, how to mitigate disagreement. Introducing a mild form of paternalism can harness the unique skillset both parents and clinicians bring to shared decision-making and ultimately work towards decision-making in the best interest of the child. The notion expressed here is that within the model of shared decision-making, mild paternalism is prioritized inasmuch as optimal care is prioritized. This mild form of paternalism is known as Beneficent Paternalism and justifies our encouragement for physicians to root down in their own medical expertise to propose treatment plans informed by medical expertise, standards of care, and the parents’ values. This does not mean that we forget that paternalism was historically justified on ‘beneficent’ grounds; however, our recommendation is that a re-integration of mild paternalism is appropriate within our current Western healthcare climate. Through illustrative examples from the NICU, this paper explores the appropriateness and merits of Beneficent Paternalism and ultimately its use in promoting family-centered care, patient’s best interests and reducing moral distress. A distinctive feature of the NICU is the fact that communication regarding a patient’s treatment is exclusively done with substitute decision-makers and not the patient, i.e., the neonate themselves. This leaves the burden of responsibility entirely on substitute decision-makers and the clinical team; the patient in the NICU does not have any prior wishes, values, or beliefs that can guide decision-making on their behalf. Therefore, the wishes, values, and beliefs of the parent become the map upon which clinical proposals are made, giving extra weight to the family’s decision-making responsibility. This leads to why Family Directed Care is common in the NICU, where shared decision-making is mandatory. However, the zone of parental discretion is not as all-encompassing as it is currently considered; there are appropriate times when the clinical team should strongly root down in medical expertise and perhaps take the lead in guiding family decision-making: this is just what it means to adopt Beneficent Paternalism.

Keywords: care, ethics, expertise, NICU, paternalism

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Authors: M. Babul Hasan

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Management sciences (MS), big group of companies and industries or government policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. After formulating these models there arises large-scale mixed integer programming (MIP) problem. In this paper, we developed decomposition-based pricing procedure to filter the unnecessary decision ingredients from MIP where the variables in huge number will be abated and the complicacy of restrictions will be elementary. A real life numerical example has been illustrated to demonstrate the methods. We develop the computer techniques for these methods by using a mathematical programming language (AMPL).

Keywords: Lagrangian relaxation, decomposition, sub-problem, master-problem, pricing, mixed IP, AMPL

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Alia Al Rayssi, Mahra Al Marar, Alyazia Alkhaili, Reem Al Dhaheri, Shayma Alkobaisi, Hoda Amer

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We present in this paper a web-based system called “HelpMeBreathe” for managing asthma. The proposed system provides analytical tools, which allow better understanding of environmental triggers of asthma, hence better support of data-driven decision making. The developed system provides warning messages to a specific asthma patient if the weather in his/her area might cause any difficulty in breathing or could trigger an asthma attack. HelpMeBreathe collects, stores, and analyzes individuals’ moving trajectories and health conditions as well as environmental data. It then processes and displays the patients’ data through an analytical tool that leads to an effective decision making by physicians and other decision makers.

Keywords: asthma, environmental triggers, map interface, web-based systems

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Authors: Anne N. Heirman, Lisette van der Molen, Richard Dirven, Gyorgi B. Halmos, Michiel W.M. van den Brekel

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Background: Due to the rising incidence of oropharyngeal squamous cell cancer (OPSCC), many patients are challenged with choosing between transoral(robotic) surgery and radiotherapy, with equal survival and oncological outcomes. Also, functional outcomes are of little difference over the years. With this study, the wants and needs of patients and caregivers are identified to develop a comprehensible patient decision aid (PDA). Methods: The development of this PDA is based on the International Patient Decision Aid Standards criteria. In phase 1, relevant literature was reviewed and compared to current counseling papers. We interviewed ten post-treatment patients and ten doctors from four head and neck centers in the Netherlands, which were transcribed verbatim and analyzed. With these results, the first draft of the PDA was developed. Phase 2 beholds testing the first draft for comprehensibility and usability. Phase 3 beholds testing for feasibility. After this phase, the final version of the PDA was developed. Results: All doctors and patients agreed a PDA was needed. Phase 1 showed that 50% of patients felt well-informed after standard care and 35% missed information about treatment possibilities. Side effects and functional outcomes were rated as the most important for decision-making. With this information, the first version was developed. Doctors and patients stated (phase 2) that they were satisfied with the comprehensibility and usability, but there was too much text. The PDA underwent text reduction revisions and got more graphics. After revisions, all doctors found the PDA feasible and would contribute to regular counseling. Patients were satisfied with the results and wished they would have seen it before their treatment. Conclusion: Decision-making for OPSCC should focus on differences in side-effects and functional outcomes. Patients and doctors found the PDA to be of great value. Future research will explore the benefits of the PDA in clinical practice.

Keywords: head-and-neck oncology, oropharyngeal cancer, patient decision aid, development, shared decision making

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Authors: Chutima Klaysung

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This research aims to study the factors that influence the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand. The research method will use quantitative research; data were collected by questionnaires distributed to spa consumers, both female and male, aged between 20 years and 70 years in the Amphawa, Samut Songkhram area for 400 samples by convenience sampling method. The data were analyzed using descriptive statistics including percentage, mean, standard deviation and inferential statistics, including Pearson correlation for hypothesis testing. The results showed that the demographic variables including age, education, occupation, income and frequency of access to service spa were related to the decision to choose the spa service of consumers in Amphawa, Samut Songkhram. In addition, the researchers found the marketing mixed factors such as products, prices, places, promotion, personnel selling, physical evidence and processes were associated with the decision to choose the spa service of consumers in Amphawa, Samut Songkhram, Thailand.

Keywords: consumer in amphawa, samut songkhram, decision to choose the spa service, marketing mixed factor, spa service

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Authors: Chuan-Ching Sue, Kai-Chun Chuang

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Peer-to-Peer (P2P) live streaming systems still suffer a challenge when thousands of new peers want to join into the system in a short time, called flash crowd, and most of new peers suffer long start-up delay. Recent studies have proposed a slot-based user access control mechanism, which periodically determines a certain number of new peers to enter the system, and a user batch join mechanism, which divides new peers into several tree structures with fixed tree size. However, the slot-based user access control mechanism is difficult for accurately determining the optimal time slot length, and the user batch join mechanism is hard for determining the optimal tree size. In this paper, we propose a structured access control (SAC) mechanism, which constructs new peers to a multi-layer mesh structure. The SAC mechanism constructs new peer connections layer by layer to replace periodical access control, and determines the number of peers in each layer according to the system’s remaining upload bandwidth and average video rate. Furthermore, we propose an analytical model to represent the behavior of the system growth if the system can utilize the upload bandwidth efficiently. The analytical result has shown the similar trend in system growth as the SAC mechanism. Additionally, the extensive simulation is conducted to show the SAC mechanism outperforms two previously proposed methods in terms of system growth and start-up delay.

Keywords: peer-to-peer, live video streaming system, flash crowd, start-up delay, access control

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Dimitrios J. Dimitriou

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The decades after the end of the second War provide evidence that infrastructures investments contibute to economic development, on terms of productivity and income growth. In order to force productivity and increase competitiveness the financing of large transport infrastructure projects are on the top of the agenda in strategic planning process. Such a decision may take form some days to some decades and stakeholders as well as decision makers need tools in order to estimate the economic impact on natioanl economy of such an investment. The key question in such decisions is if the effects caused by the new infrastructure could be able to boost economic development on one hand, and create new jobs and activities on the other. This paper deals with the review of estimation of the mega transport infrastructure projects economic effects in economy.

Keywords: economic impact, transport infrastructure, strategic planning, decision making

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Authors: Khalid Bashir, Hammad Zahid

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Most of the investors consider that economic and financial information is the most important at the time of making investment decisions. But it is not true, as in the past two decades, the Behavioral aspects and the behavioral biases have gained an important place in the decision-making process of an investor. This study is basically conducted on this fact. The purpose of this study is to examine the impact of behavioral factors on the decision-making of the individual real estate investor in Pakistan. Some important behavioral factors like overconfidence, anchoring, gambler’s fallacy, home bias, loss aversion, regret aversion, mental accounting, herding and representativeness are used in this study to find their impact on the psychology of individual investors. The targeted population is the real estate investor of Pakistan, and a sample of 650 investors is selected on the basis of convenience sampling technique. The data is collected through the questionnaire with a response rate of 46.15 %. Descriptive statistical techniques and SEM are used to analyze the data by using statistical software. The results revealed the fact that some behavioral factors have a significant impact on the decision-making of investors. Among all the behavioral biases, overconfidence, anchoring, gambler’s fallacy, loss aversion and representativeness have a significant positive impact on the decision-making of the individual investor, while the rest of biases like home bias, regret aversion, mental accounting, herding have less impact on the decision-making process of an individual.

Keywords: behavioral finance, anchoring, gambler’s fallacy, loss aversion

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Authors: Pongsawee Supanonth

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This study aims to investigate the consumer behavior and marketing mixed factor affect on consumer decision making for independent movies presented in Lido cinema. The research method will use quantitative research, data was collected by questionnaires distributed to the audience in the Lido cinema for 400 sample by accidental sampling technique. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including independent t-test for hypothesis testing. The results showed that marketing mixed factors affecting consumer decision-making for Independent movies presented in Lido cinema by gender as different as less than the 0.05 significance level, it was found that the kind of movie ,quality of theater ,price of ticket, facility of watching movies, staff services and promotion of Lido cinema respectively had a vital influence on their attention and response which makes the advertisement more attractive is in harmony with the research hypotheses also.

Keywords: consumer behavior, marketing mixed factor, resonance, consumer decision making, Lido cinema

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Authors: Chen T. Chen, Hui L. Cheng

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Due to the different knowledge, experience and expertise of experts, they usually provide the different opinions in the group decision-making process. Therefore, it is an important issue to reach the group consensus of opinions of experts in group multiple-criteria decision-making (GMCDM) process. Because the subjective opinions of experts always are fuzziness and uncertainties, it is difficult to use crisp values to describe the real opinions of experts or decision-makers. It is reasonable for experts to use the linguistic variables to express their opinions. The hesitant fuzzy set are extended from the concept of fuzzy sets. Experts use the hesitant fuzzy sets can be flexible to describe their subjective opinions. In order to aggregate the hesitant fuzzy linguistic variables of all experts effectively, an adjustment method based on distance function will be presented in this paper. Based on the opinions adjustment method, this paper will present an effective approach to adjust the hesitant fuzzy linguistic variables of all experts to reach the group consensus. Then, a new hesitant linguistic GMCDM method will be presented based on the group consensus of hesitant fuzzy linguistic variables. Finally, an example will be implemented to illustrate the computational process to enhance the practical value of the proposed model.

Keywords: group multi-criteria decision-making, linguistic variables, hesitant fuzzy linguistic variables, distance function, group consensus

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Considering the increasing demand for water and limited resources, there is a possibility of a water crisis in the not-so-distant future. Therefore, to prevent this crisis, other options for drinking water supply should be examined. In this regard, the application of multi-criteria decision-making methods in various aspects of water resource management and planning has always been of great interest to researchers. In this report, six options for supplying drinking water to Tehran City were considered. Then, experts' opinions were collected through matrices and questionnaires, and using the TOPSIS method, which is one of the types of multi-criteria decision-making methods, they were calculated and analyzed. In the TOPSIS method, the options were ranked by calculating their proximity to the ideal (Ci). The closer the numerical value of Ci is to one, the more desirable the option is. Based on this, the option with the optimization pattern of water consumption, with Ci = 0.9787, is the best option among the proposed options for supplying drinking water to Tehran City. The other options, in order of priority, are rainwater harvesting, wastewater reuse, increasing current water supply sources, desalination and its transfer, and transferring water from freshwater sources between basins. In conclusion, the findings of this study highlight the importance of exploring alternative drinking water supply options and utilizing multi-criteria decision-making approaches to address the potential water crisis.

Keywords: multi-criteria decision, sustainable development, topsis, water supply

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Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Chiara Mansanta, Daniela Sani

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This paper studies the concept of intrapreneurship discovery for innovation and technology development related to the manufacturing industries set up in the center of Italy, in Marche Region. The study underlined the key drivers of the innovation process and the main factors that influence innovation. Starting from a literature study on open innovation, this paper examines the role of human capital to support company’s development. The empirical part of the study is based on a survey to 151 manufacturing companies that represent the 34% of that universe at the regional level. The survey underlined the main KPI’s that influence companies in their decision processes; then tools for these decision processes are presented.

Keywords: business model, decision making, intrapreneurship discovery, standard methodology

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Authors: S. da Costa, D. Páez, E. Martínez, A. Torres, M. Beramendi, D. Hermosilla, M. Muratori

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This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.

Keywords: creativity, innovation, military, organization, teams

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Authors: Rasha A. Salameh

Abstract:

This research attempts to evaluate the treatment provided by the Qatari media to the decision to allow Saudi women to drive, and then activate this decision after a few months, that is, within the time frame between September 26, 2017 until June 30, 2018. This is through asking several questions, including whether the political dispute between Qatar and Saudi Arabia has cast a shadow over this handling, and if these Qatari media handlings are used to criticize the Saudi regime for delaying this step. Here emerges one of the research hypotheses that says that the coverage did not have the required professionalism, due to the fact that the decision and its activation took place in light of the political stalemate between Qatar and the Kingdom of Saudi Arabia, which requires testing the media framing and agenda theories to know to what extent they apply to this case. The research dealt with a sample of five Qatari media read in this sample: Al-Jazeera Net, The New Arab Newspaper, Al-Sharq Newspaper, The Arab Newspaper, and Al-Watan Newspaper. The results showed that most of the authors who covered the decision to allow Saudi women to drive a car did not achieve a balance in their writing, and that almost half of them did not have objectivity, and this indicates the proof of the hypothesis that there is a defect in the professional competence in covering the decision to allow Saudi women to drive cars by means of Qatari media, and the researcher attributes this result to the political position between Qatar and Saudi Arabia, in addition to the fact that the Arab media in most of them are characterized by a low ceiling of freedom, and most of them are identical in their position with the position of the regime’s official view.

Keywords: Saudi women, objectivity, hate speech, stereotype

Procedia PDF Downloads 114

Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

Abstract:

The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

Procedia PDF Downloads 368

Authors: Deepika Christopher, Garima Anand

Abstract:

To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

Abstract:

Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

Procedia PDF Downloads 393