Search results for: decision tree

Authors: Katejarinporn Chaiya, Jarumon Nookong, Nutthapat Kaewrattanapat

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The purposes of this research were to develop and find users’ satisfaction after using the Decision Support System for Examination Selection. This research presents the design of information systems. In order to find the necessary examination of the statistics. Based on the examination of the candidate and then taking the easy difficulty setting statistics applied to the test. In addition, research has also made performance appraisals from experts and user satisfaction. By results of analysis showed that the performance appraisals from experts on the system as a whole and at a good level. mean was 3.44 and S.D. was 0.55 and user satisfaction per system as a whole and the good level mean was 3.37 and S.D. was 0.42 can conclude that effective systems are in a good level. Work has been completed in accordance with the scope of work. The website used developing this project is PHP, MySQL.5.0.45 for database.

Keywords: secision support system, examination, PHP, information systems

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Authors: Ali S. Gargoum

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Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

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Authors: P. Ghann, J. Shiguang, C. Zhou

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Access control is one of the most challenging issues facing information security. Access control is defined as, the ability to permit or deny access to a particular computational resource or digital information by an unauthorized user or subject. The concept of usage control (UCON) has been introduced as a unified approach to capture a number of extensions for access control models and systems. In UCON, an access decision is determined by three factors: Authorizations, obligations and conditions. Attribute mutability and decision continuity are two distinct characteristics introduced by UCON for the first time. An observation of UCON components indicates that, the components are predefined and static. In this paper, we propose a new and flexible model of usage control for the creation and elimination of some of these components; for example new objects, subjects, attributes and integrate these with the original UCON model. We also propose a model for concurrent usage scenarios in UCON.

Keywords: access control, concurrency, digital container, usage control

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Authors: Claudia Cocozza, Niccolò Frassinelli, Enrico Marchi, Cristiano Foderi, Alessandro Bizzarri, Margherita Paladini, Maria Laura Traversi, Eleftherious Touloupakis, Alessio Giovannelli

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The development of tools to quickly identify the fate of injured trees after stress is highly relevant when biodiversity restoration of damaged sites is based on nature-based solutions. In this context, an approach to assess irreversible physiological damages within trees could help to support planning management decisions of perturbed sites to restore biodiversity, for the safety of the environment and understanding functionality adjustments of the ecosystems. Tree vitality can be estimated by a series of physiological proxies like cambium activity, starch, and soluble sugars amount in C-sinks whilst the accumulation of ethanol within the cambial cells and phloem is considered an alert of cell death. However, their determination requires time-consuming laboratory protocols, which makes the approach unfeasible as a practical option in the field. The project aims to develop biosensors to assess the concentration of soluble sugars and ethanol in stem tissues. Soluble sugars and ethanol concentrations will be used to define injured trees to discriminate compromised and recovering trees in the forest directly. To reach this goal, we select study sites subjected to prescribed fires or recent wildfires as experimental set-ups. Indeed, in Mediterranean countries, forest fire is a recurrent event that must be considered as a central component of regional and global strategies in forest management and biodiversity restoration programs. A biosensor will be developed through a multistep process related to target analytes characterization, bioreceptor selection, and, finally, calibration/testing of the sensor. To validate biosensor signals, soluble sugars and ethanol will be quantified by HPLC and GC using synthetic media (in lab) and phloem sap (in field) whilst cambium vitality will be assessed by anatomical observations. On burnt trees, the stem growth will be monitored by dendrometers and/or estimated by tree ring analyses, whilst the tree response to past fire events will be assessed by isotopic discrimination. Moreover, the fire characterization and the visual assessment procedure will be used to assign burnt trees to a vitality class. At the end of the project, a well-defined procedure combining biosensor signal and visual assessment will be produced and applied to a study case. The project outcomes and the results obtained will be properly packaged to reach, engage and address the needs of the final users and widely shared with relevant stakeholders involved in the optimal use of biosensors and in the management of post-fire areas. This project was funded by National Recovery and Resilience Plan (NRRP), Mission 4, Component C2, Investment 1.1 - Call for tender No. 1409 of 14 September 2022 – ‘Progetti di Ricerca di Rilevante interesse Nazionale – PRIN’ of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Grant N° P2022Z5742, CUP B53D23023780001.

Keywords: phloem, scorched crown, conifers, prescribed burning, biosensors

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Authors: Ipek Kivanc, Demet Ozgur-Unluakin

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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.

Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes

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Authors: Ruijia Hu, Susanna T.Y. Tong

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Light detection and ranging (LiDAR) and four-channel red, green, blue, and near-infrared (RGBI) remote sensed imageries allow an accurate quantification and contiguous measurement of vegetation characteristics and forest structures. This information facilitates the generation of habitat structure variables for forest species distribution modelling. However, applications of remote sensing data, especially the combination of structural and spectral information, to support evidence-based decisions in forest managements and conservation practices at local scale are not widely adopted. In this study, we examined the habitat requirements of pileated woodpecker (Dryocopus pileatus) (PW) in Hamilton County, Ohio, using ecologically relevant forest structural and vegetation characteristics derived from LiDAR and RGBI data. We hypothesized that the habitat of PW is shaped by vegetation characteristics that are directly associated with the availability of food, hiding and nesting resources, the spatial arrangement of habitat patches within home range, as well as proximity to water sources. We used 186 PW presence or absence locations to model their presence and absence in generalized additive model (GAM) at two scales, representing foraging and home range size, respectively. The results confirm PW’s preference for tall and large mature stands with structural complexity, typical of late-successional or old-growth forests. Besides, the crown size of dead trees shows a positive relationship with PW occurrence, therefore indicating the importance of declining living trees or early-stage dead trees within PW home range. These locations are preferred by PW for nest cavity excavation as it attempts to balance the ease of excavation and tree security. In addition, we found that PW can adjust its travel distance to the nearest water resource, suggesting that habitat fragmentation can have certain impacts on PW. Based on our findings, we recommend that forest managers should use different priorities to manage nesting, roosting, and feeding habitats. Particularly, when devising forest management and hazard tree removal plans, one needs to consider retaining enough cavity trees within high-quality PW habitat. By mapping PW habitat suitability for the study area, we highlight the importance of riparian corridor in facilitating PW to adjust to the fragmented urban landscape. Indeed, habitat improvement for PW in the study area could be achieved by conserving riparian corridors and promoting riparian forest succession along major rivers in Hamilton County.

Keywords: deadwood detection, generalized additive model, individual tree crown delineation, LiDAR, pileated woodpecker, RGBI aerial imagery, species distribution models

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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Authors: Lee Waters, Itay Basevitch, Matthew Timmis

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Objectives: Eye tracking technology is a valuable method of assessing individuals gaze behaviour, but it does not unveil why they are engaging in certain practices. To address limitations in sport eye tracking research the present paper aims to investigate the gaze behaviours soccer officials engage in during successful and unsuccessful offside decisions, but also why. Methods: 20 male active amateur qualified (Level 4-7) soccer officials (Mage 22.5 SD 4.61 yrs) with an average experience of 41-50 games wore eye tracking technology during an applied attack versus defence drill. While reviewing the eye tracking footage, retrospective semi-structured interviews were conducted (M=20.4 min; SD=6.2; Range 11.7 – 26.8 min) and once transcribed inductive thematic analysis was performed. Findings and Discussion: To improve the understanding of gaze behaviours and how officials make sense of the environment, during the interview’s key constructs of offside, decision making, obstacles and emotions were summarised as the higher order themes while making offside decisions. Gaze anchoring was highlighted to be a successful technique to allow officials to see all relevant information, whereas the type of offside was emphasised to be a key factor in correct interpretation. Furthermore, specific decision-making training was outlined to be inconsistent and not always applicable. Conclusions: Key constructs have been identified and explained, which can be shared with soccer officials through training regimes. Eye tracking technology has also been shown to be a useful and innovative reflective tool to assist in the understanding of individuals gaze behaviours.

Keywords: eye tracking, gaze behvaiour, decision making, reflection

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Shahab Mirzaean Mahabadi, Elham Ebrahimi

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The urban development process in the historical urban context has predominately witnessed two main approaches: the first is the Preservation and conservation of the urban fabric and its value, and the second approach is urban renewal and redevelopment. The latter is generally supported by political and economic aspirations. These two approaches conflict evidently. The authors go through the history of urban planning in order to review the historical development of the mentioned approaches. In this article, various values which are inherent in the historical fabric of a city are illustrated by emphasizing on cultural identity and activity. In the following, it is tried to find an optimized plan which maximizes economic development and minimizes change in historical-cultural sites simultaneously. In the proposed model, regarding the decision maker’s intention, and the variety of functions, the selected zone is divided into a number of components. For each component, different alternatives can be assigned, namely, renovation, refurbishment, destruction, and change in function. The decision Variable in this model is to choose an alternative for each component. A set of decisions made upon all components results in a plan. A plan developed in this way can be evaluated based on the decision maker’s point of view. That is, interactions between selected alternatives can make a foundation for the assessment of urban context to design a historical-cultural landscape. A genetic algorithm (GA) approach is used to search for optimal future land use within the historical-culture landscape for a sustainable high-growth city.

Keywords: urban sustainability, green city, regeneration, genetic algorithm

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Authors: Adepoju A. A., Olapade-Ogunwole F., Ganiyu M. O.

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This study examined women's empowerment in cassava production in southwest Nigeria. The contributions of the five domains namely decision about agricultural production, decision-making power over productive resources, control of the use of income, leadership and time allocation to women disempowerment, profiled the women based on their socio-economics features and determined factors influencing women's disempowerment. Primary data were collected from the women farmers and processors through the use of structured questionnaires. Purposive sampling was used to select the LGAs and villages based on a large number of cassava farmers and processors, while cluster sampling was used to select 360 respondents in the study area. Descriptive statistics such as bar charts and percentages, Women Empowerment in Agriculture (WEAI), and the Logit regression model were used to analyze the data collected. The results revealed that 63.88% of the women were disempowered. Lack of decision-making power over productive resources; 36.47% and leadership skills; 33.26% contributed mostly to the disempowerment of the women. About 85% of the married women were disempowered, while 76.92% of the women who participated in social group activities were more empowered than their disempowered counterparts. The findings showed that women with more years of processing experience have the probability of being disempowered while those who engage in farming as a primary livelihood activity, and participate in social groups among others have the tendency to be empowered. In view of this, it was recommended that women should be encouraged to farm and contribute to social group activities.

Keywords: cassava, production, empowerment, southwest, Nigeria

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Authors: Pablo Cardozo Herrera

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In a dynamic market of Information Technology (IT) Service and with high quality demands and high performance requirements in decreasing costs, it is imperative that IT companies invest organizational effort in order to increase the effectiveness of their Information Technology Service Management (ITSM) processes through the improvement of ITSM project management and through solid support to the strategic decision-making process of IT directors. In this article, the author presents an analysis of common issues of IT companies around the world, with strategic needs of information unmet that provoke their ITSM processes and projects management that do not achieve the effectiveness and efficiency expected of their results. In response to the issues raised, the author proposes a framework consisting of an innovative theoretical framework model of ITSM management and a technological solution aligned to the Information Technology Infrastructure Library (ITIL) good practices guidance and ISO/IEC 20000-1 requirements. The article describes a research that proves the proposed framework is able to integrate, manage and coordinate in a holistic way, measurable and auditable, all ITSM processes and projects of IT organization and utilize the effectiveness assessment achieved for their strategic decision-making process increasing the process maturity level and improving the capacity of an efficient management.

Keywords: innovation in IT services, ITSM processes, ITIL and ISO/IEC 20000-1, IT service management, IT service excellence

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Authors: Oluwafemi Samuel Oyamakin

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The forest in Nigeria is currently estimated to extend to around 9.6 million hectares, but used to expand over central and southern Nigeria decades ago. The forest estate is shrinking due to long-term human exploitation for agricultural development, fuel wood demand, uncontrolled forest harvesting and urbanization, amongst other factors, compounded by population growth in rural areas. Nigeria has lost more than 50% of its forest cover since 1990 and currently less than 10% of the country is forested. The current deforestation rate is estimated at 3.7%, which is one of the highest in the world. Reducing Emissions from Deforestation and forest Degradation plus conservation, sustainable management of forests and enhancement of forest carbon stocks constituted what is referred to as REDD+. This study evaluated some of the existing way of computing carbon stocks using eight indigenous tree species like Mansonia, Shorea, Bombax, Terminalia superba, Khaya grandifolia, Khaya senegalenses, Pines and Gmelina arborea. While these components are the essential elements of REDD+ programme, they can be brought under a broader framework of systems analysis designed to arrive at optimal solutions for future predictions through statistical distribution pattern of carbon sequestrated by various species of tree. Available data on height and diameter of trees in Ibadan were studied and their respective potentials of carbon sequestration level were assessed and subjected to tests so as to determine the best statistical distribution that would describe the carbon sequestration pattern of trees. The result of this study suggests a reasonable statistical distribution for carbons sequestered in simulation studies and hence, allow planners and government in determining resources forecast for sustainable development especially where experiments with real-life systems are infeasible. Sustainable management of forest can then be achieved by projecting future condition of forests under different management regimes thereby supporting conservation and REDD+ programmes in Nigeria.

Keywords: REDD+, carbon, climate change, height and diameter

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Authors: Javeria Arain, Saad Malik

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The management of solid waste is a crucial and essential aspect of urban environmental management especially in a city with an ever increasing population such as Karachi. The total amount of municipal solid waste generated from Gulshan e Iqbal town on average is 444.48 tons per day and landfill sites are a widely accepted solution for final disposal of this waste. However, an improperly selected site can have immense environmental, economical and ecological impacts. To select an appropriate landfill site a number of factors should be kept into consideration to minimize the potential hazards of solid waste. The purpose of this research is to analyse the study area for the construction of an appropriate landfill site for disposal of municipal solid waste generated from Gulshan e-Iqbal Town by using geospatial techniques considering hydrological, geological, social and geomorphological factors. This was achieved using analytical hierarchy process and fuzzy analysis as a decision support tool with integration of geographic information sciences techniques. Eight most critical parameters, relevant to the study area, were selected. After generation of thematic layers for each parameter, overlay analysis was performed in ArcGIS 10.0 software. The results produced by both methods were then compared with each other and the final suitability map using AHP shows that 19% of the total area is Least Suitable, 6% is Suitable but avoided, 46% is Moderately Suitable, 26% is Suitable, 2% is Most Suitable and 1% is Restricted. In comparison the output map of fuzzy set theory is not in crisp logic rather it provides an output map with a range of 0-1, where 0 indicates least suitable and 1 indicates most suitable site. Considering the results it is deduced that the northern part of the city is appropriate for constructing the landfill site though a final decision for an optimal site could be made after field survey and considering economical and political factors.

Keywords: Analytical Hierarchy Process (AHP), fuzzy set theory, Geographic Information Sciences (GIS), Multi-Criteria Decision Analysis (MCDA)

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Authors: Elzbieta Babula, Juhyun Park

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Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory.

Keywords: binary choice experiment, cumulative prospect theory, decision weights, parameter interactions

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Authors: Serhat Tüzün, Tufan Demirel

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The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

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Authors: Mustafa Tekke, Nurullah Kurt

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This study examined the level of career maturity of undergraduate foreign students in a public university in Malaysia by examining on cultural aspect by using the Career Maturity Inventory. Two hundred and twenty nine (Male = 106, Female = 123) foreign students studying in various majors completed the Career Maturity Inventory and the scores of the foreign students on the CMI suggested that they had slightly higher levels than the mean level of maturity in career. Result was also supported by testing the feeling about major, consideration of changing major and planning after graduation, which indicated that foreign students had their own career decision making. However, this result should be viewed with caution within ethnic difference.

Keywords: career maturity, foreign students, career decision making, feeling about major, knowledge about major

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Authors: Suwimol Apapol, Punrapha Praditpong

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The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions as well as the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of several Goods service. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively which is in harmony with the research hypotheses as well.

Keywords: advertising captions, captions on internet, consumer purchasing decision, e-commerce

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Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

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Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: data mining, digital libraries, digital preservation, file format

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Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

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Authors: An-Yi Wang, Wei-Fong Kao, Shin-Han Tsai

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Introduction: Information as patient characteristics, resuscitation scene, resuscitation provider perspectives and families wish affects on resuscitation decision-making for out-of-hospital cardiac arrest (OHCA). There is no consistency consensus on how families and emergency physicians approach this decision. The main purpose of our study is to evaluate the characteristics of withholding resuscitation efforts arrival at the hospital. Methods: We retrospectively analyzed patients with OHCA without pre-hospital return-of-spontaneous circulation (ROSC) who was sent to our emergency department (ED) between January 2014 and December 2015. Baseline characteristics, pre-hospital course, and causes of the cardiopulmonary arrest among patients were compared. Results: In 2 years, total 155 arrest patients without pre-hospital ROSC was included. 33(21.3%) patients withhold the resuscitation efforts in ED with mean resuscitation duration 4.45 ± 7.04 minutes after ED arrival. In withholding group, the initial rhythm of arrests was all non-shockable. 9 of them received endotracheal intubation before decision-making. None of the patients in withhold resuscitation group survived to discharge. There was no significant difference among gender, underlying cardiovascular disease, malignancy, chronic renal disease, nor witness collapse between withhold and continue resuscitation groups. Univariate analysis showed there was lower percentage of bystander resuscitation (32.3% vs. 50.4%, p=0.071), and the lower percentage of transport via emergency medical service (EMS) (78.8% vs. 91.8%, p=0.054) in withholding group. Multivariate analysis showed old age (adjusted odds ratio=1.06, 95% C.I.=[1.02-1.11], p<0.05), with underlying respiratory insufficiency (adjusted odds ratio=12.16, 95% C.I.=[3.34-44.29], p<0.05), living at home compared with nursing home (adjusted odds ratio=37.75, 95% C.I.=[1.09-1110.70], p<0.05) were more likely to withhold resuscitation. Transport via EMS was more likely to continue resuscitation (adjusted odds ratio=0.11, 95% C.I.=[0.02-0.71], p<0.05). Conclusion: The decision-making for families and emergency physicians to withhold or continue resuscitation for out-of-hospital cardiac arrest is complex and multi-factorial. Continue resuscitation efforts in nursing home residents is high, and further study among this population is warranted.

Keywords: cardiopulmonary resuscitation, out-of-hospital cardiac arrest, termination resuscitation, withhold resuscitation

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Cory Cannon

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In the current era of shrinking budgets, increasing amounts of worldwide natural disasters, state and non-state initiated conflicts within the world. The response has involved multinational coalitions to conduct effective military operations. The need for a Knowledge Management strategy when developing these coalitions have been overlooked in the past and the need for developing these accords early on will save time and help shape the way information and knowledge are transferred from the staff and action officers of the coalition to the decision-makers in order to make timely decisions within an ever changing environment. The aim of this paper is to show how Knowledge Management has developed within the United States military and how the transformation of working within a Combined/ Joint environment in both the Middle East and the Far East has improved relations between members of the coalitions as well as being more effective as a military force. These same principles could be applied to multinational corporations when dealing with cultures and decision-making processes.

Keywords: civil-military, culture, joint environment, knowledge management

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Authors: Elizabeth Perry, Jylana Sheats

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Scholars posit that there is an overlap between the fields of Behavioral Economics (BE) and Behavior Science (BSci)—and that consideration of concepts from both may facilitate a greater understanding of health decision-making processes. For example, the ‘intention-action gap’ is one BE concept to explain sup-optimal decision-making. It is described as having knowledge that does not translate into behavior. Complementary best BSci practices may provide insights into behavioral determinants and relevant behavior change techniques (BCT). Within the context of BSci, this exploratory study aimed to apply a BE concept with demonstrated effectiveness in financial decision-making to a health behavior: influenza (flu) vaccine uptake. Adults aged >18 years were recruited on Amazon’s Mechanical Turk, a digital labor market where anonymous users perform simple tasks at low cost. Eligible participants were randomized into 2 groups, reviewed a scenario, and then completed a survey on the likelihood of receiving a flu shot. The ‘usual care’ group’s scenario included standard CDC guidance that supported the behavior. The ‘intervention’ group’s scenario included messaging about people who did not receive the flu shot. The framing was such that participants could learn from others’ (strangers) mistakes and the subsequent health consequences: ‘Last year, other people who didn’t get the vaccine were about twice as likely to get the flu, and a number of them were hospitalized or even died. Don’t risk it.’ Descriptive statistics and chi-square analyses were performed on the sample. There were 648 participants (usual care, n=326; int., n=322). Among racial/ethnic minorities (n=169; 57% aged < 40), the intervention group was 22% more likely to report that they were ‘extremely’ or ‘moderately’ likely to get the flu vaccine (p = 0.11). While not statistically significant, findings suggest that framing messages from the perspective of learning from the mistakes of unknown others coupled with the BCT ‘knowledge about the health consequences’ may help influence flu vaccine uptake among the study population. With the widely documented disparities in vaccine uptake, exploration of the complementary application of these concepts and strategies may be critical.

Keywords: public health, decision-making, vaccination, behavioral science

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Authors: Diego Saldo Alves, Marcelo Paveck Ayub

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The quality of accounting information is very important for the decision-making of managers, investors government and other information users. The opinion of the independent audit has a significant influence on the decision-making, especially the investors. Therefore, the aim of this study is to analyze the reasons that companies listed on Brazilian Stock Exchange B3, if they received qualified opinion and disclaimer of opinion of the independent auditors. We analyzed the reports of the independent auditors of 23 Brazilian companies listed in B3 that received qualified opinion and disclaimer of opinion between the years 2012 and 2017. The findings show that the companies do not comply the International Financial Reporting Standard, IFRS, also they did not provide documentation to prove the operations performed, did not account expenses, problems in corporate governance and internal controls.

Keywords: audit, disclaimer of opinion, independent auditors, qualified opinion

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Authors: Masayuki Mori

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This study investigates the relationship between teachers’ perceptions of the usability of classroom space and various elements, including both physical and non-physical, of classroom environments. With the introduction of the GIGA School funding program in Japan in 2019, understanding its impact on learning in classroom space is crucial. The program enabled local educational authorities (LEA) to make it possible to provide one PC/tablet for each student of both elementary and junior high schools. Moreover, at the same time, the program also supported LEA to purchase other electronic devices for educational purposes such as electronic whiteboards, large displays, and real image projectors. A nationwide survey was conducted using random sampling methodology among 100 junior high schools to collect data on classroom space. Of those, 60 schools responded to the survey. The survey covered approximately fifty items, including classroom space size, class size, and educational electronic devices owned. After the data compilation, statistical analysis was used to identify correlations between the variables and to explore the extent to which classroom environment elements influenced teachers’ perceptions. Furthermore, decision tree analysis was applied to visualize the causal relationships between the variables. The findings indicate a significant negative correlation between class size and teachers’ evaluation of usability. In addition to the class size, the way students stored their belongings also influenced teachers’ perceptions. As for the placement of educational electronic devices, the installation of a projector produced a small negative correlation with teachers’ perceptions. The study suggests that while the GIGA School funding program is not significantly influential, traditional educational conditions such as class size have a greater impact on teachers’ perceptions of the usability of classroom space. These results highlight the need for awareness and strategies to integrate various elements in designing the learning environment of the classroom for teachers and students to improve their learning experience.

Keywords: classroom space, GIGA School, questionnaire survey, teachers’ perceptions

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

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Authors: Ira Irawati, Muhammad Rangga Sururi

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The expansion of built-up areas in many cities, particularly, as the consequences of urbanization process, is a common phenomenon in our contemporary world. As happened in many cities in developing world, this horizontal expansion let only a handful size of the area left for green open spaces, creating an extreme unbalance between built-up and green spaces. Combined with the high density and variety of human activities with its transportation modes; a process of urban heat island will occur, resulting in an increase in air temperature. This is one of the indicators of decreasing of the quality of urban microclimate. This paper will explore the effect of several variables of built-up areas and open spaces to the increase of air temperature using multiple linear regression analysis. We selected 11 zones within the radius of 1 km in Inner Bandung city center, and each zones measured within 300 m radius to represent the variety of land use, as well as the composition of buildings and green open spaces. By using a quantitative method which is multiple linear regression analysis, six dependent variables which are a) tree density-x1, b) shade level of tree-x2, c) surface area of buildings’ side which are facing west and east-x3, d) surface area of building side material-x4, e) surface area of pathway material, and f) numbers of motorized vehicles-x6; are calculated to find those influence to the air temperature as an independent variable-y. Finally, the relationship between those variables shows in this equation: y = 30.316 - 3.689 X1 – 6.563 X2 + 0.002 X3 – 2,517E6 X4 + 1.919E-9 X5 + 1.952E-4 X6. It shows that the existence of vegetation has a great impact on lowering temperature. In another way around, built up the area and motorized vehicles would increase the temperature. However, one component of built up area, the surface area of buildings’ sides which are facing west and east, has different result due to the building material is classified in low-middle heat capacity.

Keywords: built-up area, microclimate, vehicles, urban heat island, vegetation

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