• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3061-3080
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• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.354-363
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• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• Journal of Engineering Education Research
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• v.15 no.2
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• pp.52-57
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• 2012

This study summarized the case study of a course development of introductory engineering design considering the characteristics of civil and environmental engineering. The course mainly depends on conducting the design projects. The self-developed text book for the course consists of learning and activities of the core elements for the creation and decision of ideas and two independent design projects. Especially, the design project drew from a survey of students majoring in civil and environmental engineering and is well knitted to help students obtain the potential for soft-landing at higher major courses.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.305-306
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• 2022

In accordance with the Act on Punishment of Serious Disasters, terminal operators are required to establish and operate a safety and health management system such as manpower and budget necessary for disaster prevention, and establish and implement measures to prevent recurrence in the event of a disaster. This is a study on how to use the port facility safety management system linkage to prevent safety accidents in port facilities due to the introduction of autonomous driving port equipment and to support decision-making promptly in case of safety accidents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1412-1430
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• 2024

The soft cancellation list (SCANL) decoding algorithm for polar codes runs L soft cancellation (SCAN) decoders with different decoding factor graphs. Although it can achieve better decoding performance than SCAN algorithm, it has high latency. In this paper, a fast simplified SCANL (Fast-SSCANL) algorithm that runs L independent Fast-SSCAN decoders is proposed. In Fast-SSCANL decoder, special nodes in each factor graph is identified, and corresponding low-latency decoding approaches for each special node is propose first. Then, syndrome check aided Fast-SSCANL (SC-Fast-SSCANL) algorithm is further put forward. The ordinary nodes satisfied the syndrome check will execute hard decision directly without traversing the factor graph, thereby reducing the decoding latency further. Simulation results show that Fast-SSCANL and SC-Fast-SSCANL algorithms can achieve the same BER performance as the SCANL algorithm with lower latency. Fast-SSCANL algorithm can reduce latency by more than 83% compared with SCANL, and SC-Fast-SSCANL algorithm can reduce more than 85% latency compared with SCANL regardless of code length and code rate.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.28-38
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• 2013

In this paper, we propose a improved turbo equalizer which generates a feedback signal through a simple calculation to improve performance in single carrier system with the LMS(least mean square) algorithm based equalizer and LDPC(low density parity check) codes. LDPC codes can approach the Shannon limit performance closely. However, computational complexity of LDPC codes is greatly increased by increasing the repetition of the LDPC codes and using a long parity check matrix in harsh environments. Turbo equalization based on LDPC code is used for improvement of system performance. In this system, there is a disadvantage of very large amount of computation due to the increase of the repetition number. To less down the amount of this complicated calculation, The proposed improved turbo equalizer adjusts the adoptive equalizer after the soft decision and the LDPC code. Through the simulation results, it's confirmed that performance of improved turbo equalizer is close to the SISO-MMSE(soft input soft output minimum mean square error) turbo equalizer based on LDPC code with the smaller amount of calculation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.636-642
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• 2019

In this paper, we analyzed BER (Bit Error Rate) communication performance according to the detection order of MMSE (Minimum Mean Square Error) based soft decision interference cancellation. As the detection order method, antenna index order method, absolute value magnitude order method of channel elements, absolute value sum order method of channel elements, and SNR (Signal Noise Ratio) order method are proposed. BER performance for the scheme was measured and analyzed. As a simulation environment, 16-QAM (Quadrature Amplitude Modulation) modulation is used in an uncoded environment of an M×M multiple-input multiple-output system, and an independent Rayleigh attenuation channel is considered. The simulation results show that the performance gain is about 1.5dB when the SNR-based detection order method is M=4, and the performance gain is about 3.5dB when M=8 and about 3.5dB when M=16. The more BER performance was confirmed, the more the detection order method of the received signal prevented the interference and error spreading occurring in the detection process.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.237-240
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• 2000

In this paper, we design the system that support data rate of 6Mbps(BPSK), 12Mbps(QPSK), 24Mbps(16-QAM) with OFDM, and the performance of this system analyze in the indoor channel when BER is 10$\^$-3/. In this simulation, first, we analyze performance of the system with and without channel coding. As the result, the coding gain of each system is 2㏈, 1.6㏈, 2㏈ when BER is 10$\^$-3/ Second, In the case of 16-QAM/OFDM, The effect of soft decision channel decoding method improve 2㏈ than hard decision when BER is 10$\^$-3/.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.886-889
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• 2017

An active Fault Tolerant Model Predictive Control (FTMPC) using Fuzzy scheduler is developed. Fault tolerant Control (FTC) system stages are broadly classified into two namely Fault Detection and Isolation (FDI) and fault accommodation. Basically, the faults are identified by means of state estimation techniques. Then using the decision based approach it is isolated. This is usually performed using soft computing techniques. Fuzzy Decision Making (FDM) system classifies the faults. After identification and classification of the faults, the model is selected by using the information obtained from FDI. Then this model is fed into FTC in the form of MPC scheme by Takagi-Sugeno Fuzzy scheduler. The Fault tolerance is performed by switching the appropriate model for each identified faults. Thus by incorporating the fuzzy scheduled based FTC it becomes more efficient. The system will be thereafter able to detect the faults, isolate it and also able to accommodate the faults in the sensors and actuators of the Continuous Stirred Tank Reactor (CSTR) process while the conventional MPC does not have the ability to perform it.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.83-94
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• 2002

This study was intended to identify fabric impact on decision-making process for clothing purchase, to determine evaluation factors of clothing, and to analyze consumer's preference for fabric on clothing purchase. 396 questionnaires distributed to college students were analyzed by descriptive statistics, oneway ANOVA, correlation, factor analysis and multidimensional scaling. The results are as follows; (1) Fabric impacted on the pre-purchase evaluation and the post-purchase process. (2) 4 factors - physical properties, outer-consciousness, self-satisfaction, and appropriateness- were determined as evaluation factors. Though fabric was included in the physical properties, fabric presented high correlations with other evaluative elements. (3) The most preferred fabric was being composed of natural fiber in fiber contents and having softness in sensation. As a result of multidimensional scaling, 2 dimensions of fabric sensation were developed as 'soft-hard'and 'thin-thick'.