• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.95-110
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• 2014

The purpose of this research is to further investigate the influence of partnership between with the mediator effect of the social business on the outcome of SCM. IT technology fusion electronic tags, mobile phone, such as cloud computing is also activated in supply chain management of recently, business is faster, if social business is applied here that are smarter, customers or suppliers, there may be communication directly and to further improve the relationship partnership. 150 questionnaires were sent to companies that have introduced SCM to their systems and are operating it. Among 150 questionnaires, 127 collected data were analyzed excluding incomplete 23 data. Statistical methods used in this study were frequency analysis, factor analysis, reliability analysis, t-test, ANOVA, path analysis, Scheffe test and Sobel test with Amos 18.0. and SPSS 21.0. The analytical results are as follows. First, the more the reliability, information share, continuous transaction, effects on the social business are getting higher, the interdependence has little impact on it. Second, the impact on the outcome of SCM, partnerships between companies, showed a significant influence the reliability, the share of information, the continuous transaction, but the interdependence was analysed as an uninfluential factor. Third, the social business is analyses to have a mediator effect in relationship between the partnership and the outcome of SCM.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.177-188
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• 2018

The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.205-210
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• 2014

This is concerned with the technology to display the design on Porcelain and adjust malfunction for moving effect and light intensity by curator. More precisely, the technology makes it possible that the porcelain is connected to Light module which is the device for controlling light emission and rotating rolling plate, etc that are connected to LED light module, optical fiber and controller that is for scenario from the given storytelling. In addition, with a WiFi portable device (Smart-phone, other mobile device). equipped with a scenario programs, information for operation, failure and malfunction can be obtained and analyzed in real-time, and menu color and alarm is alerted when the displaying design is in abnormal status, which makes the early reactions to the status. Furthermore, the collected data can be sent through WiFi network to the device and PC managed by the curator specialized in managing the design on the Porcelain, thus the technology could help the curator who have less knowledge about moving pattern on the Porcelain. There is always a possibility of malfunction due to various condition that are caused by wring-harness when modules are wired-connected. In this research, in order to overcome this problem, we propose a system configuration that can do monitoring and diagnosis with a device for collecting data from LED control module, Light emission sensor and a personal WiFi device. Also, we performed connection between optical Fiber and LED and interlock for the system defined by the definition for information and storytelling scenario.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.649-658
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• 2006

Recently, Software Development was applied to new-approach methods as a various form : client-server system and web-programing, object-orient concept, distributed development with a network environments. On the other hand, it be concerned about the distributed development technology and increasing of object-oriented methodology. These technology is spread out the software quality and improve of software production, reduction of the software develop working. Futures, we considered about the distributed software development technique with a many workstation. In this paper, we discussed optimal release problem based on a stochastic differential equation model for the distributed Software development environments. In the past, the software reliability applied to quality a rough guess with a software development process and approach by the estimation of reliability for a test progress. But, in this paper, we decided to optimal release times two method: first, SRGM with an error counting model in fault detection phase by NHPP. Second, fault detection is change of continuous random variable by SDE(stochastic differential equation). Here, we decide to optimal release time as a minimum cost form the detected failure data and debugging fault data during the system test phase and operational phase. Especially, we discussed to limitation of reliability considering of total software cost probability distribution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.514-520
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• 2018

Presence service provides various information about users such as locations, status of on/offline and network access methods, and number of presence resources required by each users increases largely in mobile environment. Therefore an effective method which can reduce load of presence servers is needed. In this paper, a large scale distributed presence service system which can distribute effectively total presence system load of presence servers using message control session has been presented. This large scale distributed presence service system provides various presence information for massive volumes of users. In this study, a new message control session architecture which can dynamically distribute loads of the presence servers to multiple servers has been presented, and a new presence information data architecture for controlling load of the presence servers has been designed. In this architecture, each presence server can exchange current load level in real time to get variance of the total system load change according to user numbers, and can distribute system load to maintain load level of each server evenly. The performance of the proposed large scale distributed presence service system has been analysed by experiments. The results has been showed that average presence resource subscription processing time reduced from 42.6% to 73.6%, and average presence notification processing time reduced from 37.6% to 64.8%.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

• Smart Structures and Systems
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• v.30 no.5
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• pp.521-535
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• 2022

Efficient management of deteriorating civil infrastructure is one of the most important research topics in many developed countries. In particular, the remote displacement measurement of bridges using linear variable differential transformers, global positioning systems, laser Doppler vibrometers, and computer vision technologies has been attempted extensively. This paper proposes a remote displacement measurement system using closed-circuit televisions (CCTVs) and a computer-vision-based method for in-situ bridge bearings having relatively large displacement due to temperature change in long term. The hardware of the system is composed of a reference target for displacement measurement, a CCTV to capture target images, a gateway to transmit images via a mobile network, and a central server to store and process transmitted images. The usage of CCTV capable of night vision capture and wireless data communication enable long-term 24-hour monitoring on wide range of bridge area. The computer vision algorithm to estimate displacement from the images involves image preprocessing for enhancing the circular features of the target, circular Hough transformation for detecting circles on the target in the whole field-of-view (FOV), and homography transformation for converting the movement of the target in the images into an actual expansion displacement. The simple target design and robust circle detection algorithm help to measure displacement using target images where the targets are far apart from each other. The proposed system is installed at the Tancheon Overpass located in Seoul, and field experiments are performed to evaluate the accuracy of circle detection and displacement measurements. The circle detection accuracy is evaluated using 28,542 images captured from 71 CCTVs installed at the testbed, and only 48 images (0.168%) fail to detect the circles on the target because of subpar imaging conditions. The accuracy of displacement measurement is evaluated using images captured for 17 days from three CCTVs; the average and root-mean-square errors are 0.10 and 0.131 mm, respectively, compared with a similar displacement measurement. The long-term operation of the system, as evaluated using 8-month data, shows high accuracy and stability of the proposed system.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Information Systems Review
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• v.20 no.2
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• pp.21-37
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• 2018

Under ubiquitous work environment, innovative changes occur in work process with ICT. The work process for collaboration through mobile devices and network should be investigated. The research model consists of two major antecedents: autonomy and interdependence as a task characteristic and job satisfaction as ultimate consequence followed by work design theory. To elaborate work design theory, smartwork application (app) use, communication extent, and work-life balance were reviewed from the literature. Data were collected from three ICT firms, which adopted certain smartwork app, and a partial least squares analysis was made on 175 data points. The analysis results show that task interdependence exerts a statistically significant effect on the level of smartwork app usage. Communication extent directly affects job satisfaction and work-life balance. The remarkable point is that smartwork app usage does not affect employees' work-life balance; the former can only affect the latter indirectly by increasing communication extent. This study attempts to explain the organizational impact by considering smartwork app and the effects simultaneously. We proposed and empirically tested the extended work design theory including information technology and its environment. Based on the results, other theoretical and practical contributions are discussed at the end with limitations and further studies.