• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.73-81
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• 2005

We propose an automatic modulation recognition scheme which extracts pre-defined key features from the received signal and then applies equal gain combining method to determine the used modulation. Moreover, we compare and analyze the performance of the proposed algorithm with that of decision-theoretic algorithm. Our scheme extracts five pre-defined key features from each data segment, a data unit for the key feature extraction, which are then averaged over all the segments to recognize the modulation according to the decision procedure. We check the performance of the proposed algorithm through computer simulations for analog modulations such as AM, FM, SSB and for digital modulations such as FSK2, FSK4, PSK2, and PSK4, by measuring recognition success rate varying SNR and data collection time. The result shows that the performance of the proposed scheme is comparable to that of the decision-theoretic algorithm with less complexity.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.137-146
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• 2020

The purpose of this study is to confirm the moderating effect of the 'IRrelevance Processing'(IRP) on the relationship between decision maker's openness and business problem solving creativity (BPSC). In order to confirm the psychological mechanism of BPSC and openness, we developed the irrelevance processing. In particular, the creativity in this study is different from the general creativity studied in psychology. BPSC is a study with practical value applied in the management environment. The results showed that openness of the decision maker was correlated with the BPSC, and that the irrelevance processing was a psychological mechanism to moderating effects relationship between openness of decision makers and BPSC. This paper proved the correlation between the propensity of decision makers and BPSC, and contributed to the study of corporate creativity by identifying the psychological mechanisms.

• Journal of Distribution Science
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• v.22 no.2
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• pp.71-82
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• 2024

Purpose: Despite significant research on decision-making, researchers struggle to comprehend the decision-making process. This paper aims to not only examine the relationship between problem-solving skills, cognitive competency, and decision-making but also develop measurement instruments for cognitive competency and problem-solving skills to better model decision-making. Research Design, Methodology and Approach: A cross-sectional study was conducted by surveying 292 university students in HCM City, Vietnam, via email sent randomly by Google Forms. This study identifies the conceptual framework and tests the hypotheses using a deductive approach. The SPSS program was used to evaluate the scales' reliability, and the SmartPLS program was used to assess the measurement and structural models. Results: The results show that the research model better modelled the relationship between problem-solving skills, cognitive competency, and decision-making. Although thinking ability has no direct impact on decision-making, both creativity and problem-solving skills have a positive impact on decision-making. The mediating role of problem-solving skills is also determined by the positive relationship between cognitive competency and decision-making. Conclusions: This study highlights decision-making efficiency through the cognitive process from low to high levels and provides for policymakers and managers to explain the decision-making process in a variety of sectors, such as distribution chains, marketing, and human resource distribution.

• Journal of Korean Academy of Nursing Administration
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• v.17 no.4
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• pp.443-450
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• 2011

Purpose: This study was a descriptive correlation study to increase understanding of, and relationships among critical thinking disposition, clinical decision making and job satisfaction of cancer center nurses. Method: The participants in this study were 150 nurses working in one cancer center located in Gyeonggi Province. The statistic program, SPSS WIN17.0 was used for data analysis and data were analyzed using t-test, ANOVA, and Pearson correlation. Results: The critical thinking disposition of the participants showed statistically significant differences according to areas of practice (F=4.426, p=.005), and current position (F=9.346, p=.000). For clinical decision making of the participants, statistically significant differences were found according to current position (F=10.667, p=.000). Furthermore, for job satisfaction, there were statistically significant differences according to income (F=6.779, p=.002), length of career (F=2.701, p=.033) and current position (F=5.423, p=.005). There were significant positive correlations for critical thinking disposition with clinical decision making, and with job satisfaction. Conclusions: The results of the study indicate that to improve clinical decision making and job satisfaction of cancer center nurses, it is necessary to increase critical thinking disposition. To make this change, appropriate programs are needed to increase critical thinking and clinical decision making of general cancer center nurses.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5593-5596
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• 2014

Background: The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. Materials and Methods: The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Results: Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Conclusions: Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

• Journal of Construction Engineering and Project Management
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• v.4 no.3
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• pp.53-59
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• 2014

Project managers are responsible to conduct project on time with least amount of costs and the most possible quality with respect to shortage of resources and environmental certainties. They have to make the best decision to reach such conflicting objects. In this study the project scheduling with multi goals-multi modes was planned in fuzzy conditions under resource constraints and expanded by fuzzy goal programing (FGP). The project cost was calculated by the price of renewable resources and the quality criteria were evaluated by the quality function deployment method (QFD). Finally the model was verified by a construction case study with 22 activities along with solving by GAMS. The results showed that this model could provide a systematic framework to facilitate the decision making process and made the project managers to be able to schedule the project closer to reality.

• Journal of Animal Science and Technology
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• v.47 no.6
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• pp.1095-1100
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• 2005

For the establishment of prediction strategies of carcass meat quality grade and for the enhancement of prediction accuracy, sixty six Hanwoo steers were ultrasonically tested at 24 months of age. Ultrasonic meat quality grade were predicted by standard ultrasonic image and decision tree method using ultrasonic meat quality index. From the results of decision tree method using ultrasonic meat quality index, it was found that the marbling score was mainly influenced by the distinctness of rib on ultrasound image. Prediction accuracy of meat quality grade by ultrasonic meat quality index was 86.4%, resulting in 7.6% higher accuracy than that by standard ultrasonic image (78.8%).

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.367-376
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• 2009

This paper proposes an application methodology of AHP(Analytic Hierarchy Process) based decision making theory for improvement priority by assessment of various risk factors affecting on deterioration of water supply systems, as major social infrastructure. AHP method is organized with three level of hierarchy which is introduced for multi-criteria decision making in this study. In the first level, assessment outputs are calculated by AHP for each affecting factor. In the second level, criteria are estimated by using assessment results with respect to structural and environmental factors. Consequently, ranking decision is performed in the third level. In order to present the effectiveness, a proposed method is compared with FCP(Fuzzy Composite Programming) for decision making. Since the results of the proposed method show better performance with consistent results, it can be applied as an efficient information for the determination for improvement priority of the study infrastructure.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.359-367
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• 2009

Trust-based solutions provide some form of payment to peers to encourage good behavior. The problem with trust management systems is that they require prior knowledge to work. In other words, peers are vulnerable to attack if they do not have knowledge or correct knowledge of other peers in a trust management system. Therefore, considering only trust is inadequate when a decision is made to identify the best set of peers to utilize. In order to solve the problem, we propose a distributed decision-making mechanism for wireless peer-to-peer (P2P) networks based on game theory and relevant trust mechanisms in which we incorporate the element of trust and risk into a single model. The main idea of our mechanism is to use utility function to express the relationship between benefits and costs of peers, and then make the decision based on expected utility as well as risk attitude in a fully distributed fashion. The unique feature of our mechanism is that it not only helps a peer to select its partners, but also mitigates vulnerabilities in trust-based mechanisms. Through analysis and experiments, we believe our approach is useful for peers to make the decision regarding who to interact with. In addition, it is also a good starting point for exploring tradeoffs among risk, trust and utility.