• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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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.

• Journal of Korea Multimedia Society
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• v.23 no.6
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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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• v.7 no.3
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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.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.11-19
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• 2020

Software education is provided for 6th grade students. This study explored the algorithmic composition patterns of elementary school students. After investigating the algorithm for the 6th grade students, the algorithmic pattern of the learner was explored by calculating the cyclomatic complexity of MacCabe based on the structural programming technique. Students often use one or two choice structures to solve problems, which tend to be biased towards the starting and ending points of the problem. It is also passive in the use of selection structures. Algorithm composition depends on visible objects and one's own background. Therefore, in elementary school software education, it is necessary to present the task of thinking about the algorithm structure in the context of the algorithm and the students' experiences in accordance with the algorithm composition pattern.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.281-288
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• 2005

It is generally accepted that self-similar (or fractal) Processes may provide better models for teletraffic in modem computer networks than Poisson processes. f this is not taken into account, it can lead to inaccurate conclusions about performance of computer networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A generator of pseudo-random self similar sequences, based on the SRA (successive random addition) method, is implemented and analysed in this paper. Properties of this generator were experimentally studied in the sense of its statistical accuracy and the time required to produce sequences of a given (long) length. This generator shows acceptable level of accuracy of the output data (in the sense of relative accuracy of the Hurst parameter) and is fast. The theoretical algorithmic complexity is O(n).

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.37-47
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• 2005

Most of the methods of estimating the size of software are based on the functions provided to costumers and in the process of granting the score to each function we consider the complexity during the process. The FFP technique has advantages applied to vast areas like data management. real-time system, algorithmic software, etc, but on the other hand, has disadvantage on estimating sizes for weights for necessary function elements. This paper proposes the estimating method for software size by considering the complexity of each function elements in full function point calculation method applied to a new developed project and maintenance projects. For this, based on function point by using surveyed data proved the validity of proposed method. The valid result. was that the function elements, the attributes used in size estimation of software, est mated better estimated sizes than in the case of other weights being applied.

• Korean Management Science Review
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• v.15 no.2
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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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.10
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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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• v.17 no.1
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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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• 2000.10a
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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.