• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.44-52
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• 2000

This paper is contented with packet transmission scheduling problem for repeating all-to-all broadcasts in WDM optical passive-star networks in which there are N nodes and k wavelengths. It is assumed that each node has one tunable transmitter and one fixed-tuned receiver, and each transmitter can tune to k different wavelengths. The tuning delay represents the time taken for a transmitter to tune from one wavelength to another and represented as ${\delta}$(>0) in units of packet durations. We define all-to-all broadcast as the one where every node transmits packets to all the other nodes except itself. So, there are in total N(N-1) packets to be transmitted for an all-to-all broadcast. The optimal transmission scheduling is to schedule In such a way that all packets can be transmitted within the minimum time. In this paper, we propose the condition for optimal transmission schedules and present an optimal transmission scheduling algorithm for arbitrary values of N, k, and ${\delta}$ The cycle length of the optimal schedules is $max{[\frac{N}{k}](M-1)$, $k{\delta}+N-1$}.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.19-31
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• 2013

Since the high readable source codes help us to understand and modify the program, it is much easy to maintain them. The readability of source code is not only affected by the complexity of algorithms such as control structures but also affected by the coding styles such as naming and indentation. Although various coding standards have been presented for promoting the readability of source codes, it has been usually lost or ignored in a programming course. One of the reasons is that the coding standard is not a hard-and-false rule since it does not contribute to the performance of software. In this paper, we propose a simple automatic system, namely StyleJigsaw, which checks the style of the source codes written by C/C++ or Java. In this system, the coding style score is calculated and visualized as a jigsaw puzzle. To measure the educational effectiveness of StyleJigsaw, several experiments have been conducted on a class students in C++ programming course. According to the experimental results, the coding style score increased about 8.0 points(10.9%) on average using StyleJigsaw. Further, according to a questionnaire survey targeting the students who attended the programming course, about 88.5% of the students responded that StyleJigsaw was of help to learn the coding standards. We expect that the StyleJigsaw can be effectively used to encourage the students to obey the coding standards, resulting in high readable programs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.903-913
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• 2015

The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.13-23
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• 2022

In this paper, we propose a detailed component image classification algorithm by fashion item for unstructured data retrieval in the fashion field. Due to the COVID-19 environment, AI-based online shopping malls are increasing recently. However, there is a limit to accurate unstructured data search with existing keyword search and personalized style recommendations based on user surfing behavior. In this study, pre-processing using Mask R-CNN was conducted using images crawled from online shopping sites and then classified components for each fashion item through CNN. We obtain the accuaracy for collar of the shirt's as 93.28%, the pattern of the shirt as 98.10%, the 3 classese fit of the jeans as 91.73%, And, we further obtained one for the 4 classes fit of jeans as 81.59% and the color of the jeans as 93.91%. At the results for the decorated items, we also obtained the accuract of the washing of the jeans as 91.20% and the demage of jeans accuaracy as 92.96%.