• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2554-2580
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• 2018

Lenstra-Lenstra-$Lov{\acute{a}}sz$ (LLL) is an effective receiving algorithm for Multiple-Input-Multiple-Output (MIMO) systems, which is believed can achieve full diversity in MIMO detection of fading channels. However, the LLL algorithm features polynomial complexity and shows poor performance in terms of convergence. The reduction of algorithmic complexity and the acceleration of convergence are key problems in optimizing the LLL algorithm. In this paper, a variant of the LLL algorithm, the Hybrid-Fix-and-Round LLL algorithm, which combines both fix and round measurements in the size reduction procedure, is proposed. By utilizing fix operation, the algorithmic procedure is altered and the size reduction procedure is skipped by the hybrid algorithm with significantly higher probability. As a consequence, the simulation results reveal that the Hybrid-Fix-and-Round-LLL algorithm carries a faster rate of convergence compared to the original LLL algorithm, and its algorithmic complexity is at most one order lower than original LLL algorithm in real field. Comparing to other families of LLL algorithm, Hybrid-Fix-and-Round-LLL algorithm can make a better compromise in performance and algorithmic complexity.

• 한국멀티미디어학회논문지
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• 제23권6호
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• pp.756-764
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• 2020

A typical algorithm used for image analysis is the Convolutional Neural Network(CNN). R-CNN, Fast R-CNN, Faster R-CNN, etc. have been studied to improve the performance of the CNN, but they essentially require large amounts of data and high algorithmic complexity., making them inappropriate for small and medium-sized services. Therefore, in this paper, the image label prediction algorithm based on CNN with collaborative layer with low complexity, high accuracy, and small amount of data was proposed. The proposed algorithm was designed to replace the part of the neural network that is performed to predict the final label in the existing deep learning algorithm by implementing collaborative filtering as a layer. It is expected that the proposed algorithm can contribute greatly to small and medium-sized content services that is unsuitable to apply the existing deep learning algorithm with high complexity and high server cost.

• Journal of Communications and Networks
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• 제7권3호
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• pp.263-277
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• 2005

In this paper, we introduce algorithms for constructing broadcasting and multicasting trees. These algorithms are general because they may be used for tree cost functions that are of arbitrary form. Thus, essentially the same algorithmic procedures are used for different tree cost functions. We evaluate the effectiveness of the general algorithms by applying them to different cost functions that are often used to model wired and wireless net­works. Besides providing a unifying framework for dealing with many present and future tree-construction applications, these algorithms typically outperform some existing algorithms that are specifically designed for energy-aware wireless networks. These general algorithms perform well at the expense of higher computational complexity. They are centralized algorithms, requiring the full network information for tree construction. Thus, we also present variations of these general algorithms to yield other algorithms that have lower complexity and distributed implementation.

• 정보교육학회논문지
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• 제24권1호
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• pp.11-19
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• 2020

초등학교 6학년 학생을 대상으로 소프트웨어교육이 실시되고 있다. 본 연구에서는 초등학생의 알고리즘 구성 패턴에 대해 탐색하였다. 초등학교 6학년 학생을 대상으로 알고리즘을 구상하는 문항을 투입한 후 구조적 프로그래밍 기법에 기반한 MacCabe의 사이클로매틱 복잡도를 산출하여 학습자의 알고리즘 구성 패턴을 탐색하였다. 학생들은 문제 해결을 위해 주로 1~2가지의 선택구조를 사용하며, 이는 문제의 출발점, 도착점에 편중되는 경향이 있다. 또한 선택 구조 사용에 있어 소극적인 모습을 보인다. 알고리즘 구성에 있어서는 눈에 보이는 구체물과 자신의 배경지식에 의존하는 모습을 보인다. 따라서 초등학교 소프트웨어교육에서는 알고리즘 구성 패턴에 따라 학생들의 경험과 친숙한 문제 상황에서 알고리즘 구조를 복합적으로 사고할 수 있는 과제를 제시할 필요가 있으며, 구체적 조작물을 활용하여 지도하는 것이 유효할 것으로 보인다.

• 정보처리학회논문지C
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• 제12C권2호
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• pp.281-288
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• 2005

최근의 컴퓨터 네트워크에서 teletraffic의 양상은 Poisson 프로세스보다 self-similar 프로세스에 의해서 더 잘 반영된다. 이는 컴퓨터 네트워크의 teletraffic에 관련하여 self-similar한 성질을 고려하지 않는다면, 컴퓨터 네트워크의 성능에 관한 결과는 부정확 할 수밖에 없다는 의미가 된다. 따라서, 통신 네트워크에 관한 시뮬레이션을 수행하기 위한 매우 중요한 요소 중에 하나는 충분히 긴 self-similar한 sequence를 얼마나 잘 생성하느냐의 문제이다. 본 논문에서는 SRA (successive random addition) 방법을 이용한 pseudo-random self-similar sequence 생성기를 구현 및 분석하였다. 본 pseudo-random self-similar sequence 생성기의 성질을 매우 긴 sequence를 생성하는데 요구되는 통계적인 정확도와 생성시간에 대해서 분석하였다. 본 논문에서 제안한 SRA 방법을 이용한 pseudo-random self-similar sequence 생성기의 성능은 Hurst 변수의 상대적인 정확도로 보았을 때, 그리고 sequence의 생성시간을 고려했을 때에 적합함을 보였다. 이 생성기의 이론적 complexity는 n개의 난수를 발생하는데 O(n)이 요구된다.

• 인터넷정보학회논문지
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• 제6권2호
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• pp.37-47
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• 2005

대부분 소프트웨어 규모 추정 기법들은 사용자에게 제공될 기능에 기반을 두고 있으며, 기능에 대한 점수를 부여하는 과정에서 복잡도를 함께 고려하고 있다. 완전기능점수 기법은 데이터 처리, 실시간 시스템과 알고리즘 소프트웨어 등 광범위한 분야에 적용되는 장점을 갖고 있는 반면에 규모를 추정하는데 필요한 기능 요소들에 대한 가중치를 부여하지 않는 단점도 갖고 있다. 본 논문은 신규로 개발되는 프로젝트와 유지보수 프로젝트들에 적용되는 완전기능점수 계산 방법에 각기능 요소들에 대한 복잡도를 고려하여 소프트웨어 규모를 추정할 수 있는 방법을 제안하였다. 이를 위해 기능 점수 기반으로 실측된 데이터를 이용하여 제안된 방법의 타당성을 검증하였다. 검증한 결과, 소프트웨어의 규모 추정에 사용되는 속성들인 기능 요소들에 다른 가중치를 적용하였을 경우 보다 좋은 규모 추정이 가능하였다.

• 경영과학
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• 제15권2호
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• pp.201-210
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• 1998

Truck dispatching is one of the most commonly occurring problems of transprot management. We developed an interactive decision support system named IDSSTD, for the truck dispatching problem where two conflicting objectives are treated and travel speed varies depending on the passing areas and time of day. The IDSSTD aids the decision-making process by allowing the user to interact directly with the database, to direct data to a decision model, and to portray results in a convenient form. The IDSSTD is consisted of two major interactive phases. The pre-scheduling interactive phase is to reduce the complexity of a given problem before applying the BC-saving heuristic algorithm and the post-scheduling interactive phase is to improve practically the algorithmic solution. The IDSSTD has the capabilities of its own manipulation(analysis and recommendation) and diverse graphic features in order to facilitate a user's interaction.

• 전자공학회논문지A
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• 제30A권10호
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• pp.67-76
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• 1993

This paper presents the design and implementation of SVSIM (Sogang VHDL SIMulator), a multi-level VHDL simulator, designed for the construction of an integrated VGDL design environment. The internal model of SVSIM is the hierarchical C/DFG which is extended from C/DFG to include the network hierarchy and local/glabal control informations. Hierarchical network is not flattened for simulation, resulting in the reduction of space complexity. The predufined/user-defined types except for the record type and the predefined/user-defined attributes are supported in SVSIM. Algorithmic-level descriptions can be siumlated by the support of recursive procedure/function calls. Input stimuli can be generated by command script in stimuli file or in VHDL source code. Experimential results show SVSIM can be efficiently used for the simulation of the pure behavioral descriptions, structural descriptions or mixture of these.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권1호
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• pp.162-166
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• 2017

Earliest virtual deadline zero laxity (EVDZL) algorithm is proposed for mobile GPU schedulers for its improved responsiveness. Responsiveness of user interface (UI) is one of the key factors in evaluating smart devices because of its significant impacts on user experiences. However, conventional GPU schedulers based on completely fair scheduling (CFS) shows a poor responsiveness due to its algorithmic complexity. In this letter, we present the EVDZL scheduler based on the conventional earliest deadline zero laxity (EDZL) algorithm by accommodating the virtual laxity concept into the scheduling. Experimental results show that the EVDZL scheduler improves the response time of the Android UI by 9.6% compared with the traditional CFS scheduler.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.