Search results for: binary decision diagram

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

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

Keywords: 5C4C, data, information, knowledge

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Authors: Ghouas Halima, Haddou Boumedienne, Jean Peal Cancelier, Cristophe Gourdon, Ssaka Collines

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This work concerns the coacervate extraction of industrial dye, namely BezanylGreen - F2B, from an aqueous solution by nonionic surfactant “Lutensol AO7 and TX-114” (readily biodegradable). Binary water/surfactant and pseudo-binary (in the presence of solute) phase diagrams were plotted. The extraction results as a function of wt.% of the surfactant and temperature are expressed by the following four quantities: percentage of solute extracted, E%, residual concentrations of solute and surfactant in the dilute phase (Xs,w, and Xt,w, respectively) and volume fraction of coacervate at equilibrium (Фc). For each parameter, whose values are determined by a design of experiments, these results are subjected to empirical smoothing in three dimensions. The aim of this study is to find out the best compromise between E% and Фc. E% increases with surfactant concentration and temperature in optimal conditions, and the extraction extent of TA reaches 98 and 96 % using TX-114 and Lutensol AO7, respectively. The effect of sodium sulfate or cetyltrimethylammonium bromide (CTAB) addition is also studied. Finally, the possibility of recycling the surfactant is proved.

Keywords: extraction, cloud point, non ionic surfactant, bezanyl green

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Authors: Irina Khutsishvili

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The presented study develops a decision support methodology for multi-criteria group decision-making problem. The proposed methodology is based on the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) approach in the hesitant fuzzy environment. The main idea of decision-making problem is a selection of one best alternative or several ranking alternatives among a set of feasible alternatives. Typically, the process of decision-making is based on an evaluation of certain criteria. In many MCDM problems (such as medical diagnosis, project management, business and financial management, etc.), the process of decision-making involves experts' assessments. These assessments frequently are expressed in fuzzy numbers, confidence intervals, intuitionistic fuzzy values, hesitant fuzzy elements and so on. However, a more realistic approach is using linguistic expert assessments (linguistic variables). In the proposed methodology both the values and weights of the criteria take the form of linguistic variables, given by all decision makers. Then, these assessments are expressed in triangular fuzzy numbers. Consequently, proposed approach is based on triangular hesitant fuzzy TOPSIS decision-making model. Following the TOPSIS algorithm, first, the fuzzy positive ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are defined. Then the ranking of alternatives is performed in accordance with the proximity of their distances to the both FPIS and FNIS. Based on proposed approach the software package has been developed, which was used to rank investment projects in the real investment decision-making problem. The application and testing of the software were carried out based on the data provided by the ‘Bank of Georgia’.

Keywords: fuzzy TOPSIS approach, investment project, linguistic variable, multi-criteria decision making, triangular hesitant fuzzy set

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Authors: Taksina Bunbut, Kevin Wongleedee

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

Keywords: factors, international tourists, revisit, Thailand

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Authors: F. Amireche, I. Mokbel, J. Jose, B. F. Belaribi

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The experimental vapour-liquid equilibria (VLE) at isothermal conditions and excess molar Gibbs energies GE are carried out for the three binary mixtures: 1, 2- dichloroethane + ethylene glycol dimethyl ether, + diethylene glycol dimethyl ether or + diethylene glycol diethyl ether, at ten temperatures ranging from 273 to 353.15 K. A good static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P, the excess molar Gibbs energies GE and the excess molar enthalpies HE.

Keywords: Disquac model, Dortmund UNIFAC model, 1, 2- dichloroethane, excess molar Gibbs energies GE, polyethers, VLE

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Authors: Sakul Jariyachansit

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

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

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Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

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

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

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

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Authors: John Cheferson R. De Belen, John Paul G. Elizares, Ronald John G. Raz, Janina Elyse A. Reyes, Charie G. Salengua, Aristotle L. Soriano

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Plastic is a type of synthetic or man-made polymer that can readily be molded into a variety of products. Its usage over the past century has enabled society to make huge technological advances. The workers of United Asia International Plastics Corporation (UAIPC), a plastic manufacturing company performs manual packaging which causes fatigue and stress on their arm, neck, and legs due to extended periods of standing and repetitive motions. With the use of the Fishbone Diagram, Five-Why Analysis, Rapid Entire Body Assessment (REBA), and Anthropometry, the stressful tasks and activities were identified and analyzed. Given the anthropometric measurements obtained from the workers, improved dimensions for the tables and chairs should be used and provide a new packaging machine. The validation of this proposal shall follow after its implementation. By eliminating fatigue during working hours in the production, the workers will be at ease at performing their work properly; productivity will increase that will lead to more profit. Further areas for study include measurement and comparison of the worker’s anthropometric measurement with the industry standard.

Keywords: anthropometry, fishbone diagram, five-why analysis, rapid entire body assessment

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Authors: Alma Sobrevilla

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

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

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Authors: Andras Dezső, Peter Baumli, George Kaptay

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The phosphorous is the important components in the steels, because it makes the changing of the mechanical properties and possibly modifying the structure. The phosphorous can be create the Fe3P compounds, what is segregated in the ferrite grain boundary in the intervals of the nano-, or microscale. This intermetallic compound is decreasing the mechanical properties, for example it makes the blue brittleness which means that the brittle created by the segregated particles at 200 ... 300°C. This work describes the phosphide solubility by the other components effect. We make calculations for the Ni, Mo, Cu, S, V, C, Si, Mn, and the Cr elements by the Thermo-Calc software. We predict the effects by approximate functions. The binary Fe-P system has a solubility line, which has a determinating equation. The result is below: lnwo = -3,439 – 1.903/T where the w0 means the weight percent of the maximum soluted concentration of the phosphorous, and the T is the temperature in Kelvin. The equation show that the P more soluble element when the temperature increasing. The nickel, molybdenum, vanadium, silicon, manganese, and the chromium make dependence to the maximum soluted concentration. These functions are more dependent by the elements concentration, which are lower when we put these elements in our steels. The copper, sulphur and carbon do not make effect to the phosphorous solubility. We predict that all of cases the maximum solubility concentration increases when the temperature more and more high. Between 473K and 673 K, in the phase diagram, these systems contain mostly two or three phase eutectoid, and the singe phase, ferritic intervals. In the eutectoid areas the ferrite, the iron-phosphide, and the metal (III)-phospide are in the equilibrium. In these modelling we predicted that which elements are good for avoid the phosphide segregation or not. These datas are important when we make or choose the steels, where the phosphide segregation stopping our possibilities.

Keywords: phosphorous, steel, segregation, thermo-calc software

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Authors: Hubert Beisch, Janik Marx, Svenja Garlof, Roman Shvets, Ivan Grygorchak, Andriy Kityk, Bodo Fiedler

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Three-dimensional carbon materials can be used as electrode materials for energy storage systems such as batteries and supercapacitors. Fast charging and discharging times are realizable without reducing the performance due to aging processes. Furthermore high specific surface area (SSA) of three-dimensional carbon structures leads to high specific capacities. One newly developed carbon foam is Globugraphite. This interconnected globular carbon morphology with statistically distributed hierarchical pores is manufactured by a chemical vapor deposition (CVD) process from ceramic templates resulting from a sintering process. Via scanning electron (SEM) and transmission electron microscopy (TEM), the morphology is characterized. Moreover, the SSA was measured by the Brunauer–Emmett–Teller (BET) theory. Measurements of Globugraphite in an organic and inorganic electrolyte show high energy densities and power densities resulting from ion absorption by forming an electrochemical double layer. A comparison of the specific values is summarized in a Ragone diagram. Energy densities up to 48 Wh/kg and power densities to 833 W/kg could be achieved for an SSA from 376 m²/g to 859 m²/g. For organic electrolyte, a specific capacity of 100 F/g at a density of 20 mg/cm³ was achieved.

Keywords: BET, carbon foam, CVD process, electrochemical cell, Ragone diagram, SEM, TEM

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Authors: Angela Meyer

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

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

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Authors: Bright C. Opara, Gideon C. Uboegbulam

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

Keywords: cultural, durable goods, influence, purchase decision

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Authors: Khalid H. Abass

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Al-Ni-Cr alloy contains different ratios of Ni and Cr was prepared by mixing Al, Ni and Cr at 800oC under an argon atmosphere. The prepared alloys were heated for 1300 hr to 560oC, and then cooled rapidly by water at the ambient temperature. Surface morphology for alloys is studied by scanning electron microscope (SEM). The resultant homogeneous surface is a result of heat treatment. The X-ray diffraction patterns showed (111), (200), and (220) diffraction lines from cubic Al crystal structure, and suggested that the intensity of peak (111) orientation is predominant. Three binary phases were observed and grown in alloys: Al3Ni (Orthorhombic, a = 6.598Ǻ, b = 7.352 Ǻ, c = 4.802 Ǻ), Cr9Al17 (Rhombohedra, a = 12.910 Ǻ, c = 15.677), and Ni2Cr3 (Tetragonal, a = 8.82 Ǻ, c = 4.58 Ǻ). The average crystallite sizes of the prepared samples were found to be from 3000 to 3094 nm by SEM, which is much smaller than that estimated from XRD data. Corrosion resistance increases with increasing Ni-Cr content in Al alloys. The electrical volume resistivity decreased with increasing Ni-Cr content at low frequency. This behavior can be seen generally at 50Hz, where the electrical volume resistivity reached the value of 3.98×10-8Ω.cm for the ratio Al-1.8 at.%Ni-0.18at.%Cr.

Keywords: Al-Ni-Cr alloy, corrosion current, electrical volume resistivity, binary phase, homogeneous surface

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Authors: M. Karaman, H. Catalkaya

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

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

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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

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

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Authors: Musthaya Patchanee

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

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

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Zouari Ezzeddine, Tarchoun Monaem

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Despite the multiplicity of advanced approaches, the concept of financial integration couldn’t be an explicit analysis. Indeed, empirical studies appear that the measures of international financial integration are one-dimensional analyses. For the ambivalence of the concept and its multiple determinants, it must be analyzed in multidimensional level. The interest of this research is a proposal of a decision support by multicriteria approach for determining the positions of countries according to their international and financial dependencies links with the behavior of financial actors (trying to make governance decisions or diversification strategies of international portfolio ...

Keywords: financial integration, decision support, behavior, multicriteria approach, governance and diversification

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Authors: Dmitriy Kuptsov

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Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

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Authors: Nurullah Ekmekci, Ömer Akkaya, Kazım Karaboğa, Mahmut Tekin

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Job selection is one of the most important decisions that affect their lives in the name of being more useful to themselves and the society. There are many criteria to consider in the job selection. The amount of criteria in the job selection makes it a multi-criteria decision-making (MCDM) problem. In this study; job selection has been discussed as multi-criteria decision-making problem and has been solved by Analytic Hierarchy Process (AHP), one of the multi-criteria decision making methods. A survey, contains 5 different job selection criteria (finding a job friendliness, salary status, job , social security, work in the community deems reputation and business of the degree of difficulty) within many job selection criteria and 4 different job alternative (being academician, working at the civil service, working at the private sector and working at in their own business), has been conducted to the students of Selcuk University Faculty of Economics and Administrative Sciences. As a result of pairwise comparisons, the highest weighted criteria in the job selection and the most coveted job preferences were identified.

Keywords: analytical hierarchy process, job selection, multi-criteria, decision making

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Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Helen Pushkarskaya, David Tolin, Lital Ruderman, Ariel Kirshenbaum, J. MacLaren Kelly, Christopher Pittenger, Ifat Levy

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Obsessive-Compulsive Disorder (OCD) produces profound morbidity. Difficulties with decision making and intolerance of uncertainty are prominent clinical features of OCD. The nature and etiology of these deficits are poorly understood. We used a well-validated choice task, grounded in behavioral economic theory, to investigate differences in valuation and value-based choice during decision making under uncertainty in 20 unmedicated participants with OCD and 20 matched healthy controls. Participants’ choices were used to assess individual decision-making characteristics. Compared to controls, individuals with OCD were less consistent in their choices and less able to identify options that were unambiguously preferable. These differences correlated with symptom severity. OCD participants did not differ from controls in how they valued uncertain options when outcome probabilities were known (risk) but were more likely than controls to avoid uncertain options when these probabilities were imprecisely specified (ambiguity). These results suggest that the underlying neural mechanisms of valuation and value-based choices during decision-making are abnormal in OCD. Individuals with OCD show elevated intolerance of uncertainty, but only when outcome probabilities are themselves uncertain. Future research focused on the neural valuation network, which is implicated in value-based computations, may provide new neurocognitive insights into the pathophysiology of OCD. Deficits in decision-making processes may represent a target for therapeutic intervention.

Keywords: obsessive compulsive disorder, decision-making, uncertainty intolerance, risk aversion, ambiguity aversion, valuation

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Authors: Eric Ohene, Albert P. C. Chan, Shu-Chien HSU

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The rising building energy consumption and related carbon emissions make it necessary to construct net-zero carbon buildings (NZCBs). The objective of net-zero buildings has raised the benchmark for building performance and will alter how buildings are designed and constructed. However, there have been growing concerns about uncertainty in net-zero building design and cost implications in decision-making. Lessons from practice have shown that a robust net-zero building design is complex, expensive, and time-consuming. Moreover, climate conditions have an enormous implication for choosing the best-optimal passive and active solutions to ensure building energy performance while ensuring the indoor comfort performance of occupants. It is observed that 20% of the design decisions made in the initial design phase influence 80% of all design decisions. To design and construct NZCBs, it is crucial to ensure adequate decision-making during the early design phases. Therefore, this study aims to explore practical strategies to design NZCBs and to offer a design framework that could help decision-making during the design stage of net-zero buildings. A parametric simulation approach was employed, and experts (i.e., architects, building designers) perspectives on the decision framework were solicited. The study could be helpful to building designers and architects to guide their decision-making during the design stage of NZCBs.

Keywords: net-zero, net-zero carbon building, energy efficiency, parametric simulation, hot climate

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Authors: Ru-Yu Lien, Shih-Hsin Hung, Shu-Fen Lu, Ju-Jen Shie, Wen-Ju Yang, Yuann-Meei Tzeng, Chien-Ying Wang

Abstract:

Background: The quality of care in intensive care units (ICUs) is crucial, especially for terminally ill patients. Shared decision-making (SDM) with families is essential to ensure appropriate care and reduce suffering. Aim: This study explores the effectiveness of an end-of-life decision support Patient Decision Aid (PDA) in an ICU setting. Methods: This study employed a cross-sectional research design conducted in an ICU from August 2020 to June 2023. Participants included family members of end-of-life patients aged 20 or older. A total of 319 participants. Family members of end-of-life patients received the PDA, and data were collected after they made medical decisions. Data collection involved providing family members with a PDA during family meetings. A post-PDA questionnaire with 17 questions assessed PDA effectiveness and anxiety levels. Statistical analysis was performed using SPSS 22.0. Results: The PDA significantly reduced anxiety levels among family members (p < 0.001). It helped them organize their thoughts, prepare for discussions with doctors, and understand critical decision factors. Most importantly, it influenced decision outcomes, with a shift towards palliative care and withdrawal of life-sustaining treatment. Conclusion: This study highlights the importance of family-centered end-of-life care in ICUs. PDAs promote informed decision-making, reduce conflicts, and enhance patient and family involvement. These tools align patient values and goals with medical recommendations, ultimately leading to decisions that prioritize comfort and quality of life. Implementing PDAs in healthcare systems can ensure that patients' care aligns with their values.

Keywords: shared decision-making, patient decision aid, end-of-life care, intensive care unit, family-centered care

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Authors: Arturo J. Anci Alméstar, Jose D. Fernandez Huapaya, David Mauricio

Abstract:

Companies make erroneous decisions by not evaluating the inherent difficulties of entering electronic commerce without a prior review of current digital and alternate means of payment. For this reason, it is very important for businesses to have reliable, complete and integrated information on the means of current digital and alternate payments that allow decisions to be made about which of these to use. However, there is no such consolidated information or criteria that companies use to make decisions about the means of payment according to their needs. In this paper, we propose a decision tree model based on a taxonomy that presents us with a categorization of digital and alternative means of payment, as well as the visualization of the flow of information at a high level from the company to obtain a recommendation. This will allow the company to make the most appropriate decision about the implementation of the digital means of payment or alternative ideal for their needs, which allows a reduction in costs and complexity of the payment process. Likewise, the efficiency of the proposed model was evaluated through a satisfaction survey presented to company personnel, confirming the satisfactory quality level of the recommendations obtained by the model.

Keywords: digital payment medium, decision tree, decision making, digital payments taxonomy

Procedia PDF Downloads 179

Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

Abstract:

Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

Procedia PDF Downloads 73

Authors: Rifqi Irvansyah, Abdullah Abdullah, Yunita Idris, Bunga Raihanda

Abstract:

Banda Aceh is particularly susceptible to heightened vulnerability during natural disasters due to its concentrated exposure to multi-hazard risks. Despite urgent priorities during the aftermath of natural disasters, such as the 2004 Indian Ocean earthquake and tsunami, several public facilities, including school buildings, sustained damage yet continued operations without adequate repairs, even though they were submerged by the tsunami. This research aims to evaluate the consequences of column damage induced by tsunami inundation on the structural integrity of buildings. The investigation employs interaction diagrams for columns to assess their capacity, taking into account factors such as rebar deterioration and corrosion. The analysis result shows that one-fourth of the K1 columns on the first floor fall outside of the column interaction diagram, indicating that the column structure cannot handle the load above it, as evidenced by the presence of Pu and Mu, which are greater than the column's design strength. This suggests that the five columns of K1 should be cause for concern, as the column's capacity is decreasing. These results indicate that the structure of the building cannot sustain the applied load because the column cross-section has deteriorated. In contrast, all K2 columns meet the design strength, indicating that the column structure can withstand the structural loads.

Keywords: tsunami inundation, column damage, column interaction diagram, mitigation effort

Procedia PDF Downloads 67