• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.8B
• /
• pp.1444-1455
• /
• 1999

In the standard location strategy such as IS-41 and GSM, Home Location Register(HLR) and Visitor Location Register(VLR) databases are used to manage the location of mobile terminals. The primary goal that location management schemes investigate is to reduce the cost of database access and the traffic for signaling network. When mobile terminals move frequently, one of problems in the standard location management scheme is that HLR database is highly updated and the traffic in signaling network can be occurred significantly due to high message transfer rate between HRL and VLR. As a solution to these problems, this paper proposes the location management scheme using VLR Gateway(VG) to reduce the both traffics of HLR update and signaling network which are resulted from location registration requirements of mobile terminals whenever they cross their registration area boundary. VG is a kind of database that is placed between HLR and VLR. It integrates one or more registration area defined in a system into one group and plays a role on behalf of HLR in a integrated registration scope so that the call delivery and the movement of mobile terminals are possible without HLR access in the scope. In order to evaluate performance of IS-41 and proposed scheme, we simulate two schemes based on wide range of call to mobility ratio. Its experiment result shows that in the proposed scheme total database cost increased slightly whereas HLR and signaling traffic decreased remarkably.

• Journal of Digital Convergence
• /
• v.14 no.1
• /
• pp.371-377
• /
• 2016

In the area of mobile game, the job of data analysis is very important. As the mobile game market is being expanded, the characteristics of the market have been so much changed, that the contents updating and marketing strategy should be built on thorough understanding and analysis result of the gamers' needs and their play pattern. Thus the importance of the mobile game management system can not be overemphasized. However, in practice, most of the mobile game companies are small scale, and they have intrinsic problem to provide successful game service to user with a dedicated operating team. To overcome these problems, this paper suggests an efficient mobile game management system based on our already developed mobile game. And the effectiveness of our system is illustrated by our case examples such as prompt response to user question or refund request. Our proposed system also played an important role to plan additional contents update, providing scientific data analysis result on user's play pattern and purchase trend.

• Journal of Digital Convergence
• /
• v.12 no.11
• /
• pp.329-338
• /
• 2014

Today, one of the important factors that determine the university rating is the employment rate. The jobseekers are using online or offline recruiting services in order to get the desired job information. There are lots of employment supporting systems as like web-based employment agencies and University's job centers, but they are focusing more on providing job information rather than on managing the employment support. In addition, those are insufficient to support business process associated with MOU companies, industry field training, mentoring processors, etc., and to continue to manage and to update the information (resume, personal statement, etc.) about the students which the companies want, and the information about the companies which jobseekers want. Therefore, it is required that the employment supporting system which not only storages the initial data (student and corporate information), but also assist the career placement. In this paper, we considered the specific employment rights management features of the existing employment support system, it could receive real-time job information in the smart phone, we presented the design and construction of the system linked to the Bachelor Information System.

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

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.1
• /
• pp.367-373
• /
• 2016

The construction of National Spatial Data Infrastructure (NSDI) started from 2008 and was completed at 2012, with the aim of co-utilizing public agencies' national spatial information by integrating and linking. Despite the existence of the NSDI, an update of spatial data is not fully reflected because the spatial information has not been updated simultaneously by NSDI and public agencies. By examining the public agencies' services using the spatial information, a national budget is wasted because the re-usable similar services are duplicated. These issues could be solved by adopting a cloud system, whose concept is co-utilizing IT resources, to the NSDI. This study examined the service cloud based expansion and development plan for NSDI. The plan included an implementation strategy for a spatial information service cloud system and an establishment plan for a governance system. The service scenarios, concept diagram, and service functions for the system were derived in a system implementation plan. For the service functions, the unit functions of two modules were proposed and specific functions were derived. In the establishment of a governance system, the business roles and business processes were defined for organizations managing service cloud based NSDI. The business role and process were defined and derived by each service life-cycle step. With the proposed system implementation plan, a detail system design and composition of the organization could be possible, and a service cloud-based NSDI system could be implemented.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.3
• /
• pp.121-129
• /
• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• Journal of Digital Convergence
• /
• v.20 no.4
• /
• pp.147-157
• /
• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Radiation Oncology Journal
• /
• v.22 no.2
• /
• pp.77-90
• /
• 2004

Purpose: The purpose of this review Is to provide an update on novel radiation treatments for head and neck cancer Recent Findings: Despite the remarkable advances In chemotherapy and radiotherapy techniques, the management of advanced head and neck cancer remains challenging. Epidermal growth factor receptor (EGFR) Is an appealing target for novel therapies In head and neck cancer because not only EGFR activation stimulates many important signaling pathways associated with cancer development and progression, and importantly, resistance to radiation. Furthermore, EGFR overexpression Is known to be portended for a worse outcome in patients with advanced head and neck cancer. Two categories of compounds designed to abrogate EGFR signaling, such as monoclonal antibodies (Cetuxlmab) and tyrosine kinase inhibitors (ZD1839 and 051-774) have been assessed and have been most extensively studied In preclinical models and clinical trials. Additional TKIs In clinical trials include a reversible agent, Cl-1033, which blocks activation of all erbB receptors. Encouraging preclinical data for head and neck cancers resulted In rapid translation Into the clinic. Results from Initial clinical trials show rather surprisingly that only minority of patients benefited from EGFR inhibition as monotherapy or In combination with chemotherapy. In this review, we begin with a brief summary of erbB- mediated signal transduction. Subsequently, we present data on prognostic-predictive value of erbB receptor expression in HNC followed by preclinlcal and clinical data on the role of EGFR antagonists alone or in combination with radiation In the treatment of HNC. Finally, we discuss the emerging thoughts on resistance to EGFR biockade and efforts In the development of multiple-targeted therapy for combination with chemotherapy or radiation. Current challenges for investigators are to determine (1 ) who will benefit from targeted agents and which agents are most appropriate to combine with radiation and/or chemotherapy, (2) how to sequence these agents with radiation and/or cytotoxlc compounds, (3) reliable markers for patient selection and verification of effective blockade of signaling in vivo, and (4) mechanisms behind intrinsic or acquired resistance to targeted agents to facilitate rational development of multi-targeted therapy, Other molecuiar-targeted approaches In head and neck cancer were briefly described, Including angloenesis Inhibitors, farnesyl transferase inhibitors, cell cycle regulators, and gene therapy Summary: Novel targeted theraples are highly appealing in advanced head and neck cancer, and the most premising strategy to use them Is a matter of intense Investigation.

• Journal of Intelligence and Information Systems
• /
• v.27 no.4
• /
• pp.73-95
• /
• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.