• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.185-188
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• 2005

This paper proposes a new peak-windowing algorithm with window-length adaptation for peak-to-average power reduction (PAPR) of orthogonal frequency division multiplexing (OFDM) systems. Conventional peak windowing algorithm has advantages, such as moderate system complexity with good spectral shape. However, adjacent peak signals within the length of window functions produce the distortion of signal amplitude since window functions might overap with each other. These undesired characteristics of conventional peak windowing algorithm result in the degradation of BER performance. The proposed algorithm outperforms the conventional one with the aid of window-length adaptation. Simulation results show the efficiency of the proposed algorithm under the environments of WiBro downlink systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.703-719
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• 2011

In multi-user wireless communication systems, adaptive modulation and scheduling are promising techniques for increasing the system throughput. However, a mass of wireless recourse will be occupied and spectrum efficiency will be decreased to feedback channel quality indication (CQI) of all users in every subcarrier or chunk for adaptive orthogonal frequency division multiplexing (OFDM) systems. Thus numerous limited feedback schemes are proposed to reduce the system overhead. The recently proposed compressive sensing (CS) theory provides a new framework to jointly measure and compress signals that allows less sampling and storage resources than traditional approaches based on Nyquist sampling. In this paper, we proposed two novel CQI feedback schemes based on general CS and subspace CS, respectively, both of which could be used in a wireless OFDM system. The feedback rate with subspace CS is greatly decreased by exploiting the subspace information of the underlying signal. Simulation results show the effectiveness of the proposed methods, with the same feedback rate, the throughputs with subspace CS outperform the discrete cosine transform (DCT) based method which is usually employed, and the throughputs with general CS outperform DCT when the feedback rate is larger than 0.13 bits/subcarrier.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.827-844
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• 1995

Total Quality Management (TQM) is the aggregated management philosophy for quality including production, operation, human resource, leadership, marketing, and etc. TQM is the advanced concept and philosophy rather than traditional "Quality Control" or "Quality Assurance". Nowadays, downstream costs has been increased, that made cost accountants' attention to costs of quality. Many countries have developed their own quality awards system in order to improve overall national quality level. The Deming Prize of Japan and Malcolm Baldrige National Quality Award (MBNQA) of United States are two representatives of quality prizes. We compared the two awards by means of their history, objective, coverage, and judging criteria. Deming Prize has a longer history than MBNQA. Deming Prize selects five winners a year, while MBNQA has two or three areas. The biggest difference is judgement criteria. The Deming Prizes focuses on statistical control which is a traditional quality control method, while MBNQA concentrates on modem business concept such as customer satisfaction. The suggestions to these awards are: evaluate more on information of quality; evaluate more on inter-functional relationship between quality control function and other link more financial success.e financial success.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.1-24
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• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• Information Systems Review
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• v.9 no.3
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• pp.45-65
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• 2007

As digital economy era and knowledge society advent, division of the industry has been indistinctive and complex. This change of business environment has leaded todifficulty in operations of firms consisted of continuous decision making. To develop effective SDSS needs systematic strategic decision making process, efficient problem solving techniques, information of good quality, efficiently information system, and analysis ability of problem solver. This research develop SDSS framework combined strategic decision making process with various problem solving techniques for designing SDSS. Finally, this paper developed the technique recommendation system by selected the criterions of technique assortment.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.45-55
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• 2012

This paper suggests a way to construct an information management system for manufacturing process not by modifying existing solutions but by designing and developing its own solution, then examines its effects. To solve problems of existing systems, objects to be managed are organized and coded hierarchically so that a management system becomes more flexible and efficient in handling user's various needs and changes of equipments. We also provide user-customized reporting function where reporting forms are dynamically constructed depending on user's need. To validate our approach, we implement a real system and illustrate some useful examples.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.39-46
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• 2012

In this paper, for the cloud system by explaining how the forensic aspects of the investigation. Smartphone Growth Entering a variety of applications were developed which cloud systems of personal information and information assets sharing applications as during incidents on the case evidence collection, an important factor, whereas such systematic investigative methods, born in the course of my investigation of the can be confusing. This paper on the forensic aspects of the cloud system by proposing a crime scene investigation procedures, investigative support, and aiding in the systematic collection of data to support evidence.

• Asia pacific journal of information systems
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• v.15 no.1
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• pp.135-152
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• 2005

In order to explore a relationship among KM context, KM effects, and sustainability of competitive advantage of organizations, a contingency model of KM, which is based on resource-based as well as knowledge-based theory, is developed from the information systems and strategic management literature. To put it concretely, our motivation for this paper was to answer the following questions: (1) What factors affect the degree to which an organization achieves KM effects? (2) Is there a positive relationship between KM effects and organizational performance achieved by linking KM to competitive advantage? A detailed exploratory analysis of survey responses from 79 Korean companies provides the following significant findings: (1) This study found support for the proposed research model. (2) The organization's degree of process and organizational outcomes of KM effects is determined by technical and social resources and its capabilities. Furthermore, the influence of technical and social resources of KM context on process and organizational outcomes of KM effects is controlled by different types of organizational perspectives on KM. (3) There is a relationship between process and organizational outcomes of KM effects and organizational performance enhanced by linking KM to competitive advantage.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.71-85
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• 2008

The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. In this research, we propose a CF-based recommender system for bloggers to find their similar bloggers or preferable virtual community without burdensome search effort. For such a purpose, we apply the "Interest Value" to CF recommender systems. The Interest Value is the quantity value about users' transaction data in virtual community, and can measure the opinion of users accurately. Based on the Interest Value, the neighborhood group is generated, and virtual community list is recommended using the Community Likeness Score (ClS). Our experimental results upon real data of Korean Blog site show that the methodology is capable of dealing with the information overload issue in virtual community space. And Interest Value is proved to have the potential to meet the challenge of recommendation methodologies in virtual community space.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.133-141
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• 2008

Social Web is turning current Web into social platform for knowing people and sharing information. This paper takes major social tagging systems as examples, namely delicious, flickr and youtube, to analyze the social phenomena in the Social Web in order to identify the way of mediating and linking social data. A simple Tag Ontology (TO) is proposed to integrate different social tagging data and mediate and link with other related social metadata. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tag ontology is also suggested as an applying field.