• Steel and Composite Structures
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• 제37권4호
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• pp.493-501
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• 2020

The paper describes an optimization method based on the mathematical model of interaction within multibody 'bridge-track-cars" dynamic system. The interaction is connected with considerable dynamic phenomena influenced by high traffic speed (up to 400 km/h) on high-speed railroads. The trend analysis of a structure is necessary to determine the direction and resource of optimizing the system. Thus, scientific methods of decision-making process are necessary. The process requires a great amount of information analysis dealing with behavior and changes of the "bridge-track-cars system" that consists of mechanisms and structures, including transitions. The paper shows the algorithm of multi-criteria optimization that can essentially reduce weight of a bridge superstructure using big data analysis. This reduction is carried out in accordance with the constraints that have to be satisfied in any case. Optimization of real steel-concrete beam is exemplified. It demonstrates possibility of measures that are offered by the algorithm.

• 한국공작기계학회논문집
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• 제16권2호
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• pp.112-119
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• 2007

In order to predict vibration trends occurred during vehicle drive, acceleration data was processed by using data processing algorithm with moving average and Hilbert transform. Specific mode constants of acceleration were obtained under various disturbance. Vehicle velocity, road condition, property of pointing structure were considered as factors which make change of vibration trend in vehicle dynamics. Results of signal processing were compared and analysed. Advanced performance of the timing selection algorithm from this study was verified by using simple equipment comparing with the deflection measurement laser system(Muzzle Reference System).

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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• pp.105-108
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• 2003

최근의 해킹 동향은 네트워크 상의 대역폭을 목표로 하는 트래픽 폭주 공격이 증가하고 있는 추세이다. 반면 이러한 위협으로부터 네트워크 내의 공격 트래픽을 추출하는 기술은 아직 부족한 실정이다. 이에 본 논문에서는 네트워크 서비스 제공을 위협하는 트래픽을 추출하는 방법을 제시하고, DDoS 공격을 효과과적으로 탐지하는 알고리즘을 제안하였다.

• Journal of Multimedia Information System
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• 제2권1호
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• pp.143-152
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• 2015

Multimedia services in the cloud have become a popular trend in the big data environment. However, how to efficiently schedule a large number of multimedia services in the cloud is still an open and challengeable problem. Current cloud-based scheduling algorithms exist the following problems: 1) the content of the multimedia is ignored, and 2) the cloud platform is a known parameter, which makes current solutions are difficult to utilize practically. To resolve the above issues completely, in this work, we propose a novel distributed multimedia scheduling to satisfy the objectives: 1) Develop a general cloud-based multimedia scheduling model which is able to apply to different multimedia applications and service platforms; 2) Design a distributed scheduling algorithm in which each user makes a decision based on its local information without knowing the others' information; 3) The computational complexity of the proposed scheduling algorithm is low and it is asymptotically optimal in any case. Numerous simulations have demonstrated that the proposed scheduling can work well in all the cloud service environments.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권12호
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• pp.561-565
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• 2001

Recent trend of increasing automated factories needs supply of high quality power from the utilities. Among the items of the power quality, voltage sag can be compensated by Dynamic Voltage Restorer(DVR). The key feature of the DVR is high response with less transient period to recover from the voltage sag due to the lightning or line-to-ground faults. In this paper we report that $H_{\infty}$ controller is very promising for the practical application to the controller of DVR. Experimental results shown in this paper was obtained by applying the control algorithm to 20 kVA DVR system. The experimental set consists of IGBT-based three phase inverter and the TMS320C32-60 DSP used for main processor of the control board. To simulate the 50% voltage sag, the SCR-based experimental set was constructed.

• 한국정보시스템학회지:정보시스템연구
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• 제3권
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• pp.147-169
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• 1994

This paper present s a pattern generation scheme from financial charts. The patterns constitute knowledge which consists of patterns as the conditional part and the impact of the pattern as the conclusion part. The patterns in charts are represented in a syntactic approach. If the pattern elements and the impact of patterns are defined, the patterns are synthesized from simple to the more highly credible by evaluating each intermediate pattern from the instances. The overall process is divided into primitive discovery by Genetic Algorithms and pattern synthesis from the discovered primitives by the Syntactic Pattern-based Inductive Learning (SYNPLE) algorithm which we have developed. We have applied the scheme to a chart : the trend lines of stock price in daily base. The scheme can generate very credible patterns from training data sets.

• Journal of information and communication convergence engineering
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• 제16권1호
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• pp.52-59
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• 2018

Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 C
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• pp.1676-1678
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• 2001

In general, power demand is on an increasing trend as industries have made rapid strides. Power transformer is the most important equipment in substation for this reason. Transformer trobles go with blackout, expensive repair costs and huge economic losses. Therefore it is important to find the quick detection of incipient fault for the least losses. There have been gas, partial discharge, temperature, OLTC, fan and pump diagnosis for preventive techniques by present. Specially gas analysis has been adapted for a long time and proved as confident method. In this paper, we analysed the fault causes of used power transformer. The insulation faults was occupied 40% of inquired 152 faults from 1991 to 2000. This study presents the developed algorithm and expert system for finding abnormal status within transformer. We used the Element Expert tool developed Neuron DATA Inc.

• 전기전자학회논문지
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• 제22권3호
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• pp.585-589
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• 2018

Consumer demand for high quality image/video services led to growing trend in image quality enhancement study. Therefore, recent years was a period of substantial progress in this research field. Through careful observation of the image quality after processing by image enhancement algorithms, we perceived that the dark region in the image usually suffered loss of contrast to a certain extent. In this paper, the low-light stretch preprocessing algorithm is, hence, proposed to resolve the aforementioned issue. The proposed approach is evaluated qualitatively and quantitatively against the well-known histogram equalization and Photoshop curve adjustment. The evaluation results validate the efficiency and superiority of the low-light stretch over the benchmarking methods. In addition, we also propose the 255MHz-capable hardware implementation to ease the process of incorporating low-light stretch into real-time imaging systems, such as aerial surveillance and monitoring with drones and driving aiding systems.

• 대한전기학회논문지
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• 제37권12호
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• pp.894-902
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• 1988

In this paper, a method for the design of robust adaptive controller using the heuristic rules of industrial engineers is presented. This scheme works on the basis of heuristic rules and includes a supervisor, a system identifier and a detuner. The supervisor detects onsetting instability based on the analysis of the amplitude and the trend of error signal, also selects running controllers. Upon detecting instability, the controller is switched to a PID algorithm and run recursively until stability is restored. Simultaneously, new input / output data is gathered and the system identifier runs to get critical sensitivity (kc) and critical period(tc). Based on the new values(kc, tc), a GPC controller is redesigned and normal GPC is finally run. The algorithm described in this paper belongs to the supervised adaptive control category with a limited use of heuristic rules. Finally, we show the robust of this scheme by simulated example.