• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1012-1020
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• 2013

In this work, Self-adaptive Differential Evolutionary (SaDE) algorithm is proposed to solve Optimal Location and Size of Capacitor (OLSC) problem in radial distribution networks. To obtain the SaDE algorithm, two improvements have been applied on control parameters of mutation and crossover operators. To expand the study, three load conditions have been considered, i.e., constant, varying and effective loads. Objective function is introduced for the load conditions. The annual cost is fitness of problem, in addition to this cost, CPU time, voltage profile, active power loss and total installed capacitor banks and their related costs have been used for comparisons. To confirm the ability of each improvements of SaDE, the improvements are studied both in separate and simultaneous conditions. To verify the effectiveness of the proposed algorithm, it is tested on IEEE 10-bus and 34-bus radial distribution networks and compared with other approaches.

• Journal of Auto-vehicle Safety Association
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• v.12 no.3
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• pp.43-51
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• 2020

Currently, the second level of the six stages of self-driving technology, as defined by SAE, is commercialized, and the third level is preparing for commercialization. The purpose of ACC is to be evaluated as a system useful for preventing and preventing accidents by minimizing driver fatigue through longitudinal speed control and relative distance control of the vehicle. In this regard, for the study of safety assessment methods in the practical environment of ACC. Distance measurement method using monocular camera and data acquisition equipment such as DGPS are utilized. Based on the evaluation scenario considering the domestic road environment proposed by the preceding study, the relative distance obtained from equipment such as DPGS and the relative distance using a monocular camera in the actual test is verified by comparing and analyzing the safety assessment. The comparison by scenario results showed a minimum error rate of 3.83% in Scenario 1 and a maximum of 14.61% in Scenario 6. The cause of the maximum error is that the lane recognition is not accurate in the camera image and irregular operation conditions such as rushing in or exiting the surrounding area from the walkway. It is expected that safety evaluation using a monocular camera will be possible for other ADAS systems in the future.

• Journal of KIISE
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• v.42 no.12
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• pp.1503-1521
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• 2015

Agent-based modeling and simulation (ABMS) is used to model of market and social phenomena by utilizing agents' fine-grained behaviors and interactions that cannot be implemented in a conventional simulation. However, ABMS represents irrational agents and hinders the achievement of individual or overall goals since ABMS is based on agent-based software, which follows the principle of rationality at the knowledge level [1]. This problem was solved in the agent-based software engineering (ABSE) field by using behavior laws for the social level [2]. However, they still do not propose the specific development methodology for how to develop the social level in a systematic way. Therefore, in order to propose agent-based modeling and simulation methods that reflect the behavior laws of social level characteristics, our study used the Tropos that can combine ABSE and social behavior laws for the presentation of concrete tasks and deliverables for each development step by step. In addition, the proposed method will be specified through experiments with specific application examples and case studies on the self-adaptive smart grid and the military domain system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.9-18
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• 2015

In recent years, the number of applications embedded in the various devices such as a smart phone is getting larger. Due to the frequent changes of states in the execution environment, various malfunctions may occur. In order to handle the issue, this paper suggests an approach to detecting method-level failures in the legacy software systems. We can determine if the software executes the abnormal behavior based on the behavior model. However, when we apply the context-sensitive behavior model to the method-level, several problems happen such as false alarms and monitoring overhead. To tackle those issues, we propose CIBFD (Context-Insensitive Behavior Model-based Failure Detection) method. Through the case studies, we compare CIBFD method with the existing method. In addition, we analyze the effectiveness of the method for each application domains.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.354-358
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• 2001

This paper presents a fuzzy neural network model which solves the underutilization problem. This fuzzy neural network has both stability and flexibility because it uses the control structure similar to AHT(Adaptive Resonance Theory)-l neural network. And this fuzzy nenral network does not need to initialize weights and is less sensitive to noise than ART-l neural network is. The learning rule of this fuzzy neural network is the modified and fuzzified version of Kohonen learning rule and is based on the fuzzification of leaky competitive leaming and the fuzzification of conditional probability. The similarity measure of vigilance test, which is performed after selecting a winner among output neurons, is the relative distance. This relative distance considers Euclidean distance and the relative location between a datum and the prototypes of clusters. To compare the performance of the proposed fuzzy neural network with that of Kohonen Self-Organizing Feature Map the IRIS data and Gaussian-distributed data are used.

• Journal of Korean Academy of Nursing
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• v.9 no.2
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• pp.49-61
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• 1979

A review of this literature and discussions reveal a development of ideas concerning the elements of nursing models. The elements of a nursing model are the nurses view of the human being, nursing's goal, and nursing activities. It has long been recognized that human beings, at one time or another, require nursing care. Varieties of literature were reviewed in regard to the human being as recipient of nursing care through the theory development in nursing. Florence Nightingale initiated the modern era of nursing and described more clearly man as the recipient of nursing care. She looked at man as responding to the laws of nature whether the person was healthy or sick. Henderson added to Nightingale's concept of man , the recipient of nursing care by emphasizing that man is a whole, complete, and independent being. Her view is further specified by her enumeration of the activities the human being must perform. Johnson has developed a very comprehensive view of man as the recipient of nursing care. Man is a behavioral system which has a tendency to achieve and maintain stability in patterns of functioning. Like Nightingale, Johnson sees that similar patterns occur in both health and illness. Johnson postulates that the whole behavioral system of the human is composed of eight sub-systems: affiliative, achievement, aggressive, dependency, eliminative, ingestive, restorative, sexual. Roger's main contribution to the development of nursing models was her emphasis upon unitary man. She pointed out that man is a unified whole, possessing his own integrity and manifesting characteristics that“are more than and different from the sum of his parts.”Rogers focuses on the life processes of the human and points out that these processes have the following characteristics. Wholeness, openness, unidirectionality, pattern and organization, sentence, and thought. According to Roy, man is a biopsychosocial being in constant interaction with a changing environment. To cope with this changing environment, man has certain innate and acquired mechanisms. Man's ability to respond positively or to adapt, depends upon the degree of the change taking place and the state of the person coping with the change. When she analyzes man as an adaptive organism she further describes man as being composed of four adaptive modes: physiological needs, self-concept, role function, and interdependence. Based on the literary review through the theory development in nursing, general approach by a unified nursing model to a view of the recipient of nursing care may be stated as follows: Man is a unified whole composed of subsystems with a flexible and normal line of defense; his internal regulating mechanisms help him to cope with a changing environment; he functions by the principles of homeodynamics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1594-1617
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• 2018

In this paper, we consider a spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cooperative Cognitive Radio Networks (CCRNs). SUs cooperatively relay PUs messages based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperative techniques, in exchange for accessing some of the spectrum for their secondary communications. From the literatures, we found that the Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA) aim to maximize the PU sum-rate resulting in a lower sum-rate for the SU. In this contribution, we have investigated a suit of distributed matching algorithms. More specifically, we investigated SU-based CDA (CDA-SU) and SU-based PDA (PDA-SU) that maximize the SU sum-rate. We have also proposed the All User-based PDA (PDA-ALL), for maximizing the sum-rates of both PU and SU groups. A comparative study of CDA, PDA, CDA-SU, PDA-SU and PDA-ALL is conducted, and the strength of each scheme is highlighted. Different schemes may be suitable for different applications. All schemes are investigated under the idealistic scenario involving perfect coding and perfect modulation, as well as under practical scenario involving actual coding and actual modulation. Explicitly, our practical scenario considers the adaptive coded modulation based DF schemes for transmission flexibility and efficiency. More specifically, we have considered the Self-Concatenated Convolutional Code (SECCC), which exhibits low complexity, since it invokes only a single encoder and a single decoder. Furthermore, puncturing has been employed for enhancing the bandwidth efficiency of SECCC. As another enhancement, physical layer security has been applied to our system by introducing a unique Advanced Encryption Standard (AES) based puncturing to our SECCC scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.1-14
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• 2006

Sort-last parallel rendering using a cluster of GPUs has been widely used as an efficient method for visualizing large- scale volume datasets. The performance of this method is constrained by load balancing when data parallelism is included. In previous works static partitioning could lead to self-balance when only task level parallelism is included. In this paper, we present a load balancing scheme that adapts to the characteristic of volume dataset when data parallelism is also employed. We effectively combine the hierarchical data structures (octree and BSP tree) in order to skip empty regions and distribute workload to corresponding rendering nodes. Moreover, we also exploit a 3D clustering method to determine visibility order and save the AGP bandwidths on each rendering node. Experimental results show that our scheme can achieve significant performance gains compared with traditional static load distribution schemes.

• Journal of Power Electronics
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• v.13 no.1
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.112-118
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• 2011

In this paper, we conduct an objective performance analysis of the crosstalk cancellation scheme studied in [11]. While the conventional scheme is only applicable to a listener on the optimal listenable region (sweetspot), the space skew/crosstalk cancellation (SS/CC) scheme in [11] can mitigate crosstalk regardless of the listener's position by using listener position tracking (LPT) system. The SS/CC scheme is composed of two parts: LPT-based SS and CC parts. In this paper, the SS/CC scheme is evaluated by some criteria such as follows: condition number, and the balance characteristic, its root mean square error, and running average.