• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1999-2005
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• 2005

Collaboration in wireless sensor networks must be fault-tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding signal processing algorithms for collaborative target detection based on the generalized approach to signal processing in the presence of noise that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor network. Two algorithms, namely, value fusion and decision fusion constructed according to the generalized approach to signal processing in the presence of noise, are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors to fault free sensors increases. The use of the generalized approach to signal processing in the presence of noise under designing value and decision fusion algorithms in wireless sensor networks allows us to obtain the same performance, but at low values of signal energy, as under the employment of universally adopted signal processing algorithms widely used in practice.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.5
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• pp.85-93
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• 1994

We have studied the effect of channel and/or spacing chirpings on the near field and near field intensity patterns, modal gains and radiation angles of 6 supermodes in the index-guided laser arrays with 6 channels, on the basis of the coupled mode theory. The spacings between channels can be indenpendent parameters for control of the radiation angle. It is found that an asymmetrically v channel-chirped array has both a smaller radiation angle and better supermode discrimination characteristics than a uniform array. Comparing two approaches for enhancing modal stability in point of supermode discrimination characteristics, approach I which increases the coupling cofficient between the outer-most waveguides at each end of an otherwise uniform array, has superior discrimination characteristics to the approach II which increases the propagation constant for the end elements with the same coupling between neighbor elements. Approach III which has a narrower spacing between the outer-most waveguides at one end and a wider channel width of the outer-most waveguide at another end, gets a narrower radiation angle than the approach I and good supermode discrimination characteristics by applying optimized gain profiles.

• Archives of Plastic Surgery
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• v.44 no.2
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• pp.166-169
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• 2017

The goal of auricular cartilage harvest is to obtain a sufficient amount for reconstruction and to minimize the change in ear shape. The cartilage can be harvested by a posterior or anterior approach, and each method has advantages and disadvantages. The posterior approach presents the advantage of scar concealment, but there are limits to the amount of cymba cartilage that may be harvested. In contrast, the anterior approach may cause a noticeable scar. However, as cartilage is collected, the anterior approach provides a view that facilitates the preservation ear structure. In addition, it is possible to obtain a greater amount of cartilage. From January 2014 to December 2015, we harvested auricular cartilage graft material in 17 patients. To prevent the development of trapdoor scars or linear scar contracture, short incisions were made on the superior border of the cymba and cavum. Two small and narrow incisions were made, resulting in suboptimal exposure of the surgical site, which heightens the potential for damaging the cartilage when using existing tools. To minimize this, the authors used a newly invented ball-type elevator. All patients recovered without complications after surgery and reported satisfaction with the shape of the ear.

• Archives of Plastic Surgery
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• v.33 no.2
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• pp.155-160
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• 2006

Although several reports have been introduced about dual plane augmentation mammaplasty, the description of periareolar approach dual plane augmentation mammaplasty was few. This article describes specific characteristics, and different classification and techniques for the periareolar dual plane breast augmentation while postoperative scars resulted from inframammary crease approach caused complaints. A total of 124 patients(248 breasts) had periareolar dual plane augmentation surgery from 1998 to 2004. Anatomic implants were used in 43 cases. Most of the patients were satisfied with the outcomes of periareolar dual plane augmentation. Periareolar dual plane augmentation mammaplasty adjusts implant and tissue relationships to ensure adequate soft-tissue coverage while optimizing implant-breast parenchymal dynamics to offer increased benefits and fewer faults compared to a single pocket location in a wide range of breast types with minimal scars. Two types of dual plane classifications are discussed in this study for the periareolar approach exclusively. The boundaries of retroglandular dissection remain constant, as the costal origin of pectoralis major are divided. Type A dual plane implies that the inferior edge of pectoralis muscle lies below the inferior areolar border, and type B dual plane implies that the inferior edge lies above the superior areolar border.

• Journal of Veterinary Clinics
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• v.34 no.3
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• pp.200-203
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• 2017

The objective of this study was to evaluate the effectiveness of the minimally invasive plate osteosynthesis (MIPO) method for treatment of tibial shaft fractures in dogs by comparing MIPO radiographic and fracture healing time results with those from the popular open reduction and internal fixation (ORIF) technique. In this clinical study at the Royal Animal Medical Center, five consecutive dogs with diagnoses of comminuted tibial shaft fractures were treated with the MIPO surgical approach. For comparison, an additional five breed-, age-, and weight-matched dogs with comminuted tibial shaft fractures were treated with the ORIF technique. Mean healing time was $75.6{\pm}12.5$ days in the MIPO group and $131.8{\pm}18.6$ days in the ORIF group (p < 0.01). The mean surgery time in the MIPO group ($36.4{\pm}3.5$ minutes) was significantly shorter (p < 0.01) than that for the ORIF group ($47.0{\pm}2.2$ minutes). Based on the short surgical and healing times, the MIPO approach is clinically superior to the ORIF approach and should be the preferred approach in tibial fracture cases.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.33-41
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• 2018

Most important thing when designing and implementing a supply chain network is to consider various problems which may occur in real world situation. In this paper, we propose a supply chain network considering two problems (environmental factor and transportation types) under real world situation. CO2 emission amount as environmental factor is considered since it is usually generated from production and transportation processes. Normal delivery, direct delivery and direct shipment as transportation types are also considered since many customers ask various transportation types for delivery or shipment of their products under on-line or off-line purchase environment. The proposed supply chain network considering environmental factor and transportation types is represented in a mathematical formulation and implemented using hybrid genetic algorithm (HGA) approach. In numerical experiments, several scales of supply chain networks are presented and implemented using HGA approach. The performance of the HGA approach is compared with those of some conventional approaches under various measures of performance. Finally, it is proved that the performance of the HGA approach is superior to those of the others.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• Computers and Concrete
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• v.20 no.6
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• pp.645-654
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• 2017

Continuing from previous studies of sustainable concrete containing environmentally friendly materials and existing modeling approach to predicting concrete properties, this study developed an estimation methodology to predicting the strength of sustainable concrete using an advanced case-based reasoning approach. It was conducted in two steps: (i) establishment of a case database and (ii) development of an advanced case-based reasoning model. Through the experimental studies, a total of 144 observations for concrete compressive strength and tensile strength were established to develop the estimation model. As a result, the prediction accuracy of the A-CBR model (i.e., 95.214% for compressive strength and 92.448% for tensile strength) performed superior to other conventional methodologies (e.g., basic case-based reasoning and artificial neural network models). The developed methodology provides an alternative approach in predicting concrete properties and could be further extended to the future research area in durability of sustainable concrete.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.58-66
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• 2018

This paper represents a systematic approach aimed at improving the performance of the proportional integral (PI) controller for the Advanced Power Reactor (APR) 1400 Feedwater Control System (FWCS). When the performance of the PI controller offers superior control and enhanced robustness, the steam generator (SG) level is properly controlled. This leads to the safe operation and increased the availability of the nuclear power plant. In this paper, a systems engineering approach is used in order to design a novel PI controller for the FWCS. In the reverse engineering stage, the existing FWCS configuration, especially the characteristics of the feedwater controller as well as the feedwater flow path to each SG from the FWCS, were reviewed and analysed. The overall block diagram of the FWCS and the SG was also developed in the reverse engineering process. In the re-engineering stage, the actual design of the feedwater PI controller was carried out using a genetic algorithm (GA). Lastly, in the validation and verification phase, the existing PI controller and the PI controller designed using GA method were simulated in Simulink/Matlab. From the simulation results, the GA-PI controller was found to exhibit greater stability than the current controller of the FWCS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.633-652
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• 2024

Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case coverage. However, the existing approaches show limitations in test case generation from UML diagrams. Therefore, in this research study, we propose an approach to generate the test cases using UML State Chart Diagram (SCD), Activity Diagram (AD), and Sequence Diagram (SD). The proposed approach transforms UML diagrams into intermediate forms: SCD Graph, AD Graph, and SD Graph respectively. Furthermore, by integrating these three graphs, a System Testing Graph (STG) is formed. Finally, test cases are identified from STG by using a traversal algorithm such as Depth First Search (DFS) that is an optimization method. The results show that the proposed approach is better compared to existing approaches in terms of coverage and performance. Moreover, the generated test cases have the ability to detect faults at the unit level, integration, and system level testing.