• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• Journal of Korean Home Economics Education Association
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• v.29 no.2
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• pp.1-22
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• 2017

The purpose of this research is to share the experience of reflective practice of a Home Economics teacher professional learning community(PLC) operator and to share better suggestions through reflection on PLC operation. All conversation in the 18 sessions of the PLC totally from May 31st 2013 to May 19th 2014 was recorded and transcribed. All materials of PLC activity were qualitatively analysed. Its themes were grounded on its coding and categorization scheme. Findings and conclusions of this study are as followings. The experience of learning the PLC for a year has found that it is the power to keep the PLC alive: courage and anxiety to face anxiety and anxiety about new challenges, the importance of theme selection, a teacher with a reckless challenge, shares of becoming a leader. Through reflection, I learned that concerns require attention to other teachers and the need for a 'New Round' for ongoing meetings. I, as a operator, did not fully consider participant's different interest as well as a program for a new round due to the lack of management experience. It led to the low participations in latter sessions of PLC. Suggestions are put as solutions to improve these problems; (1) grouping participants by school levels when collecting participants, (2) setting operation period and program applying participants' opinions, and (3) operating short-term PLC with certain themes to immerse reaching goal and satisfaction in short time.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.29-48
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• 2011

Recently not only industry but also academy have shown an intense interest in social networking service. However, reckless imitation will not guarantee the successful eco-system of social networking service without rich understanding of growth driver and business model. Hence, this study aims at analyzing open platform strategy and business model conducted by a representative social networking service provider in order to provide platform operator, network operator, and portal provider with meaningful implications. Advertisers may pay great attention to social networking service because it has strong ability to provide users with spontaneous motivation to manage and update their profile, and these valuable information can be utilized for providing personalized advertisement on social networking service. As a result, one side of consumers in two side market, advertisers, tend to pay more expenditure to place advertisements. In addition, the open platform adopted by social networking service providers causes pro-sumers to participate in the eco-system, and thereby the explosive quantitative growth is realized. The fact of that this open social networking service can invade other web service area via an unified platform indicates that it may expand its service scope into a wide variety of web service areas. Hence, domestic portal services providers and network providers should consider social networking service not as one of new web services but as an disruptive service platform. Corresponding to the emergence of social networking service, especially if their business area is related to display advertising market, they should seek a way to provide social networking service access users's newly updated information and develop innovative media technologies to enter context awareness ads market.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.120-126
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• 2019

Recently, there is an increasing need for highly precise processing with the rapid development of precision machinery, electrical and electronics, and semiconductor industries. Cutting machine control relies on the operator's sense and experience in tradition, but it has been greatly enhanced by the adoption of CNC(Computerized Numeric Controller). In addition, cutting dynamics technology has been paid attention to reflect the operating state of machine in real time. This paper presents a method to detect and stabilize tool vibration by attaching an acoustic sensor to a CNC machine. The sensed acoustic data is synchronized with the tool position and the abnormal vibration frequency is separated from the collected acoustic frequency, then analyzed to detect the tool vibration. Also the reliability the tool vibration detection and stabilization is improved by applying the cutting dynamic method. The proposed method is analyzed and evaluated in terms of the surface roughness.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.641-656
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• 2022

This article investigates how Baedal Minjok(BaeMin) has grown to be a dominant mobility platform operator in food delivery sector in South Korea and what roles its brand and branding have played in the process, drawing on the idea of origination. For the purpose, BaeMin is considered as a typical platformized mobility service provider and origination is framed to be an appropriate analytical lens for the business sector. For the origination conception, unlike mainstream neoclassical theory and concepts, is able to deal fairly well with the issues of imperfect competition, imperfect information, and monopolistic brand rent, which are apparent in today's platformized mobility services. Drawing evidence from textual data, empirical analysis pays particular attention to discursive and symbolic dimensions of BaeMin's socio-spatial biography. It is found that national origination underpinning ethnicity comprises an important pillar of BaeMin's brand and branding. Another form of place-based origination is also observed to matter, especially in the varied relation between the mobility service brand's owner and consumers. However, this configuration of BaeMin's brand origination has yet to be fully stabilized, as it has faced with serious challenges including brand vandalism and anti-brand movement especially since its merger to German food delivery platform giant Delivery Hero in 2020. This origination crisis moment appears to be associated with a series of contractions intrinsic to so-called 'platform capitalism'.

• Journal of the Korean Society of Marine Environment & Safety
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• v.2 no.1
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• pp.137-150
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• 1996

Safety is built in to the activities of the prudent ship operator. Ant investment made towards this end is likely to have a measurable payback in positive terms. That there must be an investment is inevitable, because the industry at large has let things slip too far too long. Those who have not allowed it to slip too far and who are the first to recognize that safety, far from costing money, in the long term actually preserves it, will be wieners. Too many seem to have lost sight of the fact that every one hundred pennies saved is a full one hundred pennies profit. Every hundred pennies of additional revenue contributes no more then fifteen pence to profit. Environmental protection is not so simple, nor so financially attractive. Man needs the minerals of the Earth as well as the products of the soil and sea survive. We(the human race) are still not in the position, politically or financially to manage the Earth's assets without causing damage. The evidence of our damage is evident in many different parts of the Glove and will in some cases haunt several generations still to come. We have learned a lot, and continue to learn, but despite the best intentions some Government needs for their people will be at the expense of people in another region for the foreseeable future. We sailors ply the seas with the raw materials of commerce as well as the finished and part finished goods. It does not always sit well to consider too deeply what effect the ship and the cargo it carries is having, or may have, on some communities, or on the sea through which sail. None my generation can hold up his head and claim to be without blame in the pollution of the seas. Times are changing though, and Governments are turning their attention more to the protection of our planet and its precious resources. This will not be without cost. The investment will have to be made not for our benefit, but for the benefit of generations yet to come, however the cost will have to be borne by society as a whole, not by the shipping community alone. The debate surrounding the choice between engineering our way to a better tomorrow, or adapting our working practices will continue. Each method has the same goal as its target and as long as we attain the goal does it really matter how we get there?

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.1-9
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• 2020

Along with the growth of Blockchain, DApp (Distributed Application) is getting attention. As interest in DApp grows, market size continues to grow and many developers participate in development. Many developers are using API(Application Programming Interface) services to mediate Blockchain nodes, such as Infura, for DApp development. However, when using such a service, there is a serious risk that the API service operator can violate the user's privacy by 1 to 1 matching the account address of the Transaction executed by the DApp user with the IP address of the DApp user. It can have an adverse effect on the reliability of public Blockchains that need to provide users with a secure DApp service environment. The proposed Blockchain platform is expected to provide user privacy protection from API services and provide a reliable DApp use environment that existing Blockchain platforms did not provide. It is also expected to help to activate DApp and increase the number of DApp users, which has not been activated due to the risk of an existing privacy breach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.191-197
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• 2019

As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.85-92
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• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.