• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.140-145
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• 2019

With the development of IT technology, many changes are taking place in the health service environment over the past. However, even if medical technology is converged with IT technology, the problem of medical costs and management of health services are still one of the things that needs to be addressed. In this paper, we propose a model for hospitals that have established the IoT system to efficiently analyze and manage the personal information of users who receive medical services. The proposed model aims to efficiently check and manage users' medical information through an in-house IoT system. The proposed model can be used in a variety of heterogeneous cloud environments, and users' medical information can be managed efficiently and quickly without additional human and physical resources. In particular, because users' medical information collected in the proposed model is stored on servers through the IoT gateway, medical staff can analyze users' medical information accurately regardless of time and place. As a result of performance evaluation, the proposed model achieved 19.6% improvement in the efficiency of health care services for occupational health care staff over traditional medical system models that did not use the IoT system, and 22.1% improvement in post-health care for users who received medical services. In addition, the burden on medical staff was 17.6 percent lower on average than the existing medical system models.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.83-94
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• 2004

Recent researches which purport to Integrate distributed information have been concentrated on developing efficient mediator systems that not only provide a high degree of autonomy for local users but also support the flexible integration of required functions for global users. However, there has been little attention on how to evaluate a global query in a mediator. A global query is transformed into a set of its sub-queries and each sub-query is the unit of evaluation in a remote server. Therefore, it is possible to speed up the execution of a global query if the previous results of frequently evaluated sub-queries are materialized in a mediator. Since the Integration schema of a mediator can be incrementally modified and the evaluation frequency of a global query can also be continuously varied, query usage should be carefully monitored to determine the optimized set of materialized sub-queries. Furthermore, as the number of sub-queries increases, the optimization process itself may take too long, so that the optimized set Identified by a long optimization process nay become obsolete due to the recent change of query usage. This paper proposes the adaptive selection of materialized sub-queries such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a query from the past, the accumulated usage frequency of a query decays as time goes by.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.47-66
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• 2008

This study is aimed at proposing a new type of ubiquitous decision support system (u-DSS) portal which is embedded with two important mechanisms like an intelligent ontology management module (i-OMM) and multi-agent coordination mechanism (MACM). The proposed portal provides timely decision support to the involved decision entities (represented as agents) by taking advantage of the two mechanisms embedded on the portal. The most important virtue of the proposed portal is that it can resolve two problems such as semantic discordance and data confliction which are occurring very often in an ubiquitous computing environment. Frequent requests of revising the already established decision information due to the rapid changes in decision entities' requirements require the extremely flexible and intelligent u-DSS vehicle like theproposed mechanism. In this sense, the i-OMM is designed to provide support to solving the semantic discordance in the way that the i-OMM virtually integrates ontology view (IOV) to integrate heterogeneous ontology among the agents engaged inubiquitous commerce situations. Then the i-OMM sends the IOV to the MACM to resolve the conflicts among the involved agents. The proposed u-DSS portal was applied to the u-fulfillment problem in which all the involved decisionagents need their own requirements to be satisfied seamlessly and timely. The experimental results show that the proposed u-DSS portal is very robust and promising in the field of u-DSS and context modeling.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.47-59
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• 2016

Parcel service is to deliver goods from one place to the designated destination requested according to user request. Parcel operations such as sorting, distributing, etc. or the managed information are heterogeneous by the companies. Additionally, it is impossible to support interoperability between companies with unformatted data of manual processing. Most parcel package boxes attached to paper typed waybill is attached is delivered to consignee. So, security problems such as personal information leaking are occurred, or extra processing time and logistics costs are needed due to wrong or the damaged information. Business environment of parcel service is rapidly changed as introducing unmanned delivery or the advanced technology such as Internet of Things. User want to know the accurate status or steps from parcel service request to delivery. To provide these requirements, the unified and integrated waybill information for reliable transportation of parcel service is needed. This information will provide to pickup or delivery carrier, warehouse or terminal, and parcel service user per pickup, transport, and delivery stage of parcel delivery service. Therefore, this paper defines the simplified and unified information model for parcel service waybill by analyzing information systems used for logistics unit processes that is occurred to parcel service, and manual work processes, and developing the relevant information of work flows occurred between business processes or transactions with the collected or processed information by from parcel service's stages. It is possible to share these standard model between business entities, and replacing paper typed waybill will improve national life safety as preventing security threats by paper typed waybill. As a result, it will promote the public interest from the stakeholder's perspective.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.1051-1056
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• 2007

In current web-based systems, it is generally recognized that one way flow of information from providers to users can cause the static problem of document structure. Therefore, information update frequency and interaction between providers and users are quiet slow. Monopolized information can obstruct the free user's access and heterogeneous format and different protocols also make users difficult to retrieve and to collect information. To resolve these problems, in this study, we introduce the Web 2.0 to move toward the user's participation and share based on the social network and the OAI protocol to improve the free access and the interoperability on bibliographic information for Life Science and then design the bibliographic information network for life science. This network has four main functions such as: 1) Open Repository function that can make up user community for sharing and data exchange. Data such as article, seminar material, research note and research report are considered in design. 2) Open Collection function that can collect and store the metadata on distributed bibliographic information networks, 3) Open Access function that can manage the metadata in the open access environment, and 4) Administration function that can monitor the user activity and statistics and can inspect the registered data.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.113-130
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• 2010

During the decades, considerable human interventions to comprehend the web information were increased continually. The successful expansion of the web services made it more complex and required more contributions of the users. Many researchers have tried to improve the comprehension ability of computers in supporting an intelligent web service. One reasonable approach is enriching the information with machine understandable semantics. They applied ontology design, intelligent reasoning and other logical representation schemes to design an infrastructure of the semantic web. For the features, the semantic web is considered as an intelligent access to understanding, transforming, storing, retrieving, and processing the information gathered from heterogeneous, distributed web resources. The goal of this study is firstly to explore the problems that restrict the applications of web services and the basic concepts, languages, and tools of the semantic web. Then we highlight some of the researches, solutions, and projects that have attempted to combine the semantic web and business support, and find out the pros and cons of the approaches. Through the study, we were able to know that the semantic web technology is trying to offer a new and higher level of web service to the online users. The services are overcoming the limitations of traditional web technologies/services. In traditional web services, too much human interventions were needed to seek and interpret the information. The semantic web service, however, is based on machine-understandable semantics and knowledge representation. Therefore, most of information processing activities will be executed by computers. The main elements required to develop a semantic web-based business support are business logics, ontologies, ontology languages, intelligent agents, applications, and etc. In using/managing the infrastructure of the semantic web services, software developers, service consumers, and service providers are the main representatives. Some researchers integrated those technologies, languages, tools, mechanisms, and applications into a semantic web services framework. Therefore, future directions of the semantic web-based business support should be start over from the infrastructure.

• Asia pacific journal of information systems
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• v.23 no.2
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• pp.67-86
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• 2013

This study first provides a stylized model that captures the essential features of the SC (Social Commerce) business and the competition process. The model focuses on the relationship between key decision issues such as marketing inputs and market value. As more SCs join the industry, they are inevitably faced with fierce competition, which may lead to sharp increase in the total marketing and advertising expenditure. This type of competition may lead the industry away from its optimal development path, and at worst, toward a disruption of the entire industry ecosystem. Such being the case, another goal of this study is to examine the possibility that the ToC (Tragedy of the Commons) may occur in the SC industry. We build game models, each of which assumes homogeneity and heterogeneity of SC providers, respectively, and derive explicit equilibrium solutions from both models. Our basic analysis presents Nash equilibria in both models and shows that SC providers are inevitably faced with fierce competition, which may lead to sharp increase in the total marketing expenses. We also compare the game outcomes with one with a hypothetical social planner who determines the total marketing level that optimizes the entire market value. Then, ToC can be defined to describe the situation where the total marketing efforts exceed the socially optimal level of marketing efforts. In both models, we examine the possibility of the ecosystem disruption and specify the conditions under which ToC may occur. However, the chance of avoiding ToC is higher with heterogeneous players than with homogeneous players. To supplement our analytical results, we develop a simulation model which incorporates a market dynamics based on the gap between actual marketing efforts and socially optimal marketing level. Simulation experiments present some lessons and insights which also confirm out findings from equilibrium analysis. For example, heterogeneity in SC providers alleviates the severity of ToC and makes it faster for survivors to escape from the ToC trap. As a result, the degree of industrial concentration tends to increase, which also explains the 'rich-get-richer' phenomenon observed in some empirical studies on the SC industry. Lastly, based on our analytical and experimental results, we come up with some measures to avoid ToC and overcome the shortcomings intrinsic to the current business model. And further discussions provide strategic implications and policy directions to overcome the possible trap of ToC in this ecosystem, and eventually help the industry to sustainably develop itself toward the next level. To name a few examples of policy measures, regulations on the marketing activities so that the overall marketing expenses cannot go beyond the socially optimal level; institutional guidelines and rules to straightening up the distortions in the way that SC providers view the marketing costs (the current marketing costs are underestimated, thereby encouraging SC providers to increase marketing expenditure); and so on.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.980-984
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• 2010

Exploring microRNA (miRNA) and mRNA regulatory interactions may give new insights into diverse biological phenomena. Recently, miRNAs have been discovered as important regulators that play a major role in various cellular processes. Therefore, it is essential to identify functional interactions between miRNAs and mRNAs for understanding the context- dependent activities of miRNAs in complex biological systems. While elucidating complex miRNA-mRNA interactions has been studied with experimental and computational approaches, it is still difficult to infer miRNA-mRNA regulatory modules. Here we present a novel method, termed layered hypernetworks (LHNs), for identifying functional miRNA-mRNA interactions from heterogeneous expression data. In experiments, we apply the LHN model to miRNA and mRNA expression profiles on multiple cancers. The proposed method identifies cancer-specific miRNA-mRNA interactions. We show the biological significance of the discovered miRNA- mRNA interactions.