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Improved Simulated-Annealing Technique for Sequence-Pair based Floorplan (Sequence-Pair 기반의 플로어플랜을 위한 개선된 Simulated-Annealing 기법)

  • Sung, Young-Tae;Hur, Sung-Woo
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.4
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    • pp.28-36
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    • 2009
  • Sequence-Pair(SP) model represents the topological relation between modules. In general, SP model based floorplanners search solutions using Simulated-Annealing(SA) algorithm. Several SA based floorplanning techniques using SP model have been published. To improve the performance of those techniques they tried to improve the speed for evaluation function for SP model, to find better scheduling methods and perturb functions for SA. In this paper we propose a two phase SA based algorithm. In the first phase, white space between modules is reduced by applying compaction technique to the floorplan obtained by an SP. From the compacted floorplan, the corresponding SP is determined. Solution space has been searched by changing the SP in the SA framework. When solutions converge to some threshold value, the first phase of the SA based search stops. Then using the typical SA based algorithm, ie, without using the compaction technique, the second phase of our algorithm continues to find optimal solutions. Experimental results with MCNC benchmark circuits show that how the proposed technique affects to the procedure for SA based floorplainning algorithm and that the results obtained by our technique is better than those obtained by existing SA-based algorithms.

Comparison of Cost Function of IMRT Optimization with RTP Research Tool Box (RTB)

  • Ko, Young-Eun;Yi, Byong-Yong;Lee, Sang-Wook;Ahn, Seung-Do;Kim, Jong-Hoon;Park, Eun-Kyung
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.65-67
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    • 2002
  • A PC based software, the RTP Research Tool Box (RTB), was developed for IMRT optimization research. The software was consisted of an image module, a beam registration module, a dose calculation module, a dose optimization module and a dose display module. The modules and the Graphical User Interface (GUI) were designed to easily amendable by negotiating the speed of performing tasks. Each module can be easily replaced to new functions for research purpose. IDL 5.5 (RSI, USA) language was used for this software. Five major modules enable one to perform the research on the dose calculation, on the dose optimization and on the objective function. The comparison of three cost functions, such as the uncomplicated tumor control probability (UTCP), the physical objective function and the pseudo-biological objective function, which was designed in this study, were performed with the RTB. The optimizations were compared to the simulated annealing and the gradient search optimization technique for all of the optimization objective functions. No significant differences were found among the objective functions with the dose gradient search technique. But the DVH analysis showed that the pseudo-biological objective function is superior to the physical objective function when with the simulated annealing for the optimization.

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Inversion of Acoustical Properties of Sedimentary Layers from Chirp Sonar Signals (Chirp 신호를 이용한 해저퇴적층의 음향학적 특성 역산)

  • 박철수;성우제
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.8
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    • pp.32-41
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    • 1999
  • In this paper, an inversion method using chirp signals and two near field receivers is proposed. Inversion problems can be formulated into the probabilistic models composed of signals, a forward model and noise. Forward model to simulate chirp signals is chosen to be the source-wavelet-convolution planewave modeling method. The solution of the inversion problem is defined by a posteriori pdf. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂norm of the difference between measured and modeled signals. The observed signals can be separated into a set of two signals reflected from the upper and lower boundaries of a sediment. The separation of signals and successive applications of the genetic algorithm optimization process reduce the search space, therefore improving the inversion results. Not only the marginal pdf but also the statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied here show that, for synthetic data with noise, it is possible to carry out an inversion for sedimentary layers using the proposed inversion method.

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Design of a line balancing algorithm for the PCB assembly line including multiple surface mounters (다수 표면실장기계를 포함하는 PCB 조립라인의 라인균형화 알고리즘 설계)

  • Kim, Jin-Cheol;Lee, Sung-Han;Kim, Dae-Won;Lee, Bum-Hee
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.4
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    • pp.381-388
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    • 1997
  • This paper proposes a heuristic algorithm to efficiently perform line balancing in the PCB assembly line including multiple surface mounters efficiently. Generally, the problems in line balancing are classified into two kinds. Firstly, is the determining of the minimum number of machines required for achieving the desired production rate. Secondly, is the assign of jobs to multiple machines in order to minimize the cycle time which is defined as a maximum among the working times of machines when the number of machines is fixed. In this paper, we deal with the latter. We consider a PCB assembly line, including the multiple surface mounters arranged serially as a target system. Also, the conveyor is assumed to move at a constant speed and have no buffer. Considering that the minimum number of machines required for the desired production rate is a discrete nonincreasing function which is inversely proportional to the cycle time, we propose an optimization algorithm for line balancing by using the binary search method. The algorithm is validated through computer simulation, the results of which show that their shapes coincide nearly with those of optimal line balancing efficiency graphs regardless of the number of components, the performance of surface mounters, and the structure of assembly line.

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An Implementation of Optimum Tender Price Automatic Calculation System using Statistical Analysis Technique (통계분석 기법을 이용한 최적의 투찰가 자동 산출 시스템의 구현)

  • Kim, Bong-Hyun;Lee, Se-Hwan;Cho, Dong-Uk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.11B
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    • pp.1013-1019
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    • 2008
  • Recently, various information and data are efficiently used by the rapid growth of its Internet in our real life. But, users have spent lots of time finding necessary information for the increased amounts of information. To solve this problem, it can be provided the speed, accuracy of information search with development of intelligent search engines, agent system etc. In this paper, we propose the method of getting the best tender price in the analysis of the construction bid information that needs its professionalism by on the purpose to maximize users' satisfaction. Of course, if it is not under the unit of a results in the future, we put target of this paper on part to heighten supreme successful bid success rate. Therefore, this paper embodies offered system of web based on producing tender price of most suitable through techniques to produce tender price about successful bid that compare with bidder fare by statistical analysis incidental and value approaching successful bidder fare by frequency analysis method.

A Study on Bicycle Route Selection Using Optimal Path Search (최적 경로 탐색을 이용한 자전거 경로 선정에 관한 연구)

  • Baik, Seung Heon;Han, Dong Yeob
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.5
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    • pp.425-433
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    • 2012
  • Dijkstra's algorithm is one of well-known methods to find shortest paths over a network. However, more research on $A^*$ algorithm is necessary to discover the shortest route to a goal point with the heuristic information rather than Dijkstra's algorithm which aims to find a path considering only the shortest distance to any point for an optimal path search. Therefore, in this paper, we compared Dijkstra's algorithm and $A^*$ algorithm for bicycle route selection. For this purpose, the horizontal distance according to slope angle and average speed were calculated based on factors which influence bicycle route selection. And bicycle routes were selected considering the shortest distance or time-dependent shortest path using Dijkstra's or $A^*$ algorithm. The result indicated that the $A^*$ algorithm performs faster than Dijkstra's algorithm on processing time in large study areas. For the future, optimal path selection algorithm can be used for bicycle route plan or a real-time mobile services.

Fast k-NN based Malware Analysis in a Massive Malware Environment

  • Hwang, Jun-ho;Kwak, Jin;Lee, Tae-jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.6145-6158
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    • 2019
  • It is a challenge for the current security industry to respond to a large number of malicious codes distributed indiscriminately as well as intelligent APT attacks. As a result, studies using machine learning algorithms are being conducted as proactive prevention rather than post processing. The k-NN algorithm is widely used because it is intuitive and suitable for handling malicious code as unstructured data. In addition, in the malicious code analysis domain, the k-NN algorithm is easy to classify malicious codes based on previously analyzed malicious codes. For example, it is possible to classify malicious code families or analyze malicious code variants through similarity analysis with existing malicious codes. However, the main disadvantage of the k-NN algorithm is that the search time increases as the learning data increases. We propose a fast k-NN algorithm which improves the computation speed problem while taking the value of the k-NN algorithm. In the test environment, the k-NN algorithm was able to perform with only the comparison of the average of similarity of 19.71 times for 6.25 million malicious codes. Considering the way the algorithm works, Fast k-NN algorithm can also be used to search all data that can be vectorized as well as malware and SSDEEP. In the future, it is expected that if the k-NN approach is needed, and the central node can be effectively selected for clustering of large amount of data in various environments, it will be possible to design a sophisticated machine learning based system.

Effects of Treadmill Training on Gait of Stroke Patients : A Systematic Review (트레드밀운동이 뇌졸중 환자의 걷기기능향상에 관한 문헌연구)

  • Kang, Kwon-Young;Ko, Tae-Sung
    • Journal of Korean Physical Therapy Science
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    • v.15 no.3
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    • pp.73-79
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    • 2008
  • Background : Treadmill training has been proposed as a useful adjunct to conventional physical therapy to restore ability to walk after stroke. The purpose of this study to inform clinical practise by evaluating the research evidence for the effectiveness of treadmill training after stroke. Methods : We searched to the effectiveness of any form of intervention for effect of treadmill training by Dankook University electronic library databases of Medline, Embase, Cinahl, Amed and PEDro combined with a hand search of papers published in relevant peer-reviewed journals. Any type of study relevant to the topic published in English during time period from 1980 to 2007 was included. Results : The literature search identified 35 studies. The included studies enrolled a total of 374 subjects. 1. Treadmill retraining without partial body weight support might be more effective than no treatment at improving gait velocity, get up and go time, gait endurance and step length symmetry. 2. Treadmill retraining with partial body weight support might be more effective than no treatment in improving step length symmetry, gait velocity, gait endurance and balance. 3. Treadmill retraining might be more effective with partial body weight support than without it at improving gait velocity and motor improvement as measured by The Stroke Rehabilitation Assessment of Movement(STREAM). 4. Treadmill retraining without partial body weight support may be no different from physiotherapy and increase gait velocity to conventional gait therapy. 5. Treadmill retraining with partial body weight support may be no different from physiotherapy for gait velocity, motor recovery and balance. Conclusion The review suggests that although treadmill training of gait, especially with partial body weight support, might Improve gait parameters and functional mobility, unless treadmill training is directed at Improving gait speed it might be no more effective than conventional physical therapy at improving gait parameters.

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Design of QCA Content-Addressable Memory Cell for Quantum Computer Environment (양자컴퓨터 환경에서의 QCA 기반 내용주소화 메모리 셀 설계)

  • Park, Chae-Seong;Jeon, Jun-Cheol
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.2
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    • pp.521-527
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    • 2020
  • Quantum-dot cellular automata (QCA) is a technology that attracts attention as a next-generation digital circuit design technology, and several digital circuits have been proposed in the QCA environment. Content-addressable memory (CAM) is a storage device that conducts a search based on information stored therein and provides fast speed in a special process such as network switching. Existing CAM cell circuits proposed in the QCA environment have a disadvantage in that a required area and energy dissipation are large. The CAM cell is composed of a memory unit that stores information and a match unit that determines whether or not the search is successful, and this study proposes an improved QCA CAM cell by designing the memory unit in a multi-layer structure. The proposed circuit uses simulation to verify the operation and compares and analyzes with the existing circuit.

Efficient Data Clustering using Fast Choice for Number of Clusters (빠른 클러스터 개수 선정을 통한 효율적인 데이터 클러스터링 방법)

  • Kim, Sung-Soo;Kang, Bum-Su
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.2
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    • pp.1-8
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    • 2018
  • K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, this method has the limitation to be used with fixed number of clusters because of only considering the intra-cluster distance to evaluate the data clustering solutions. Silhouette is useful and stable valid index to decide the data clustering solution with number of clusters to consider the intra and inter cluster distance for unsupervised data. However, this valid index has high computational burden because of considering quality measure for each data object. The objective of this paper is to propose the fast and simple speed-up method to overcome this limitation to use silhouette for the effective large-scale data clustering. In the first step, the proposed method calculates and saves the distance for each data once. In the second step, this distance matrix is used to calculate the relative distance rate ($V_j$) of each data j and this rate is used to choose the suitable number of clusters without much computation time. In the third step, the proposed efficient heuristic algorithm (Group search optimization, GSO, in this paper) can search the global optimum with saving computational capacity with good initial solutions using $V_j$ probabilistically for the data clustering. The performance of our proposed method is validated to save significantly computation time against the original silhouette only using Ruspini, Iris, Wine and Breast cancer in UCI machine learning repository datasets by experiment and analysis. Especially, the performance of our proposed method is much better than previous method for the larger size of data.