• The Journal of Information Systems
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• v.15 no.1
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• pp.1-20
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• 2006

Peer-to-peer systems (P2P) are rapidly growing in importance on the Internet environment, quickly extending the range of their usage. However, peer-to-peer systems have not been widely applied in electronic commerce because they have not been established as an appropriate business model. Therefore, we firstly review the previous research relevant to peer-to-peer systems, and then analyze the business models for P2P systems presented by previous researchers. Furthermore, this study categorizes major issues in terms of the technical and business model aspects. On the basis of these reviews, we develop P2P electronic commerce systems based on the file sharing method between users, focusing on user interface friendliness. A developed P2P electronic commerce systems are programmed by using the C# based on the Microsoft.net solution. A database is implemented using the MSSQL2000. A main application technology is designed that P2P electronic commerce systems make it possible. for user to extend into BtoB Solution by using WSDL (Web Services Description Language), UDDI (Universal Description, Discovery, and Integration) and the XML that is a document for users. User interface is made as form of Internet messenger for a user's convenience and is possible to develop into a commodity transaction system based on XML. In this study, it is possible for the P2P electronic commerce system to have extended application to fields such as Internet shopping mall and property transaction in a nonprofit organization, a public institution and a large scale nonprofit institution that have a similar structure as compared with a structure of a nonprofit educational institution.

• International Journal of Fluid Machinery and Systems
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• v.2 no.3
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• pp.197-205
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• 2009

Since large-scale commercial wind turbine generator systems such as MW-class wind turbines are becoming widely operated, the vibration and distortion of the blade are becoming larger and larger. Therefore the soft structure design instead of the solid-design is one of the important concepts to reduce the structural load and the cost of the wind turbine rotors. The objectives of the study are development of the fluid-structure coupled analysis code and evaluation of soft rotor-blade design to reduce the unsteady structural blade load. In this paper, fluid-structure coupled analysis for the HAWT rotor blade is performed by free wake panel method coupled with hinge-spring blade model for the flapwise blade motion. In the model, the continuous deflection of the rotor blade is represented by flapping angle of the hinge with one degree of freedom. The calculation results are evaluated by comparison with the database of the NREL unsteady aerodynamic experiment. In the analysis the unsteady flapwise moments in yawed inflow conditions are compared for the blades with different flapwise eigen frequencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.8
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• pp.181-188
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• 2016

Recently, as the amount of spatial information increases, an interest in the study of spatial information processing has been increased. Spatial database systems extended from the traditional relational database systems are difficult to handle large data sets because of the scalability. SpatialHadoop extended from Hadoop system has a low performance, because spatial computations in SpationHadoop require a lot of write operations of intermediate results to the disk, resulting in the performance degradation. In this paper, Spatial Computation Spark(SC-Spark) is proposed, which is an in-memory based distributed processing framework. SC-Spark is extended from Spark in order to efficiently perform the spatial operation for large-scale data. In addition, SC-Spark based on the GPGPU is developed to improve the performance of the SC-Spark. SC-Spark uses the advantage of the Spark holding intermediate results in the memory. And GPGPU-based SC-Spark can perform spatial operations in parallel using a plurality of processing elements of an GPU. To verify the proposed work, experiments on a single AMD system were performed using SC-Spark and GPGPU-based SC-Spark for Point-in-Polygon and spatial join operation. The experimental results showed that the performance of SC-Spark and GPGPU-based SC-Spark were up-to 8 times faster than SpatialHadoop.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• The Journal of Society for e-Business Studies
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• v.6 no.3
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• pp.209-225
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• 2001

This paper Proposes the individual roles for developing small web application systems based on the Client/Server architecture with the activities and artifacts of each role and cooperation. The roles of Web Server part (i.e. User Interface Designer, Web Designer, HTML Writer), the roles of Application Server part (i.e. Domain Expert, Application Developer, Tester) and the roles of DB Server part (i.e. Database Administrator, Data Designer) are described. Furthermore, the role of the Development Leader that participates in development and manages all works in project and finds the solutions of problems in project, is also discussed. The Domain Expert analyzes the domain of the application in order to send the artifacts to the Application Developer. Then the Application Developer analyzes, designs and implements the application based on the artifacts of the Domain Expert and integrates the implemented program modules. Roles are related each other in this way, and cooperate until the application development is completed. Finally, we analyzed and compared these roles with the roles of RUP(Rational Unified process) and web wave. Suggested roles in this paper turned out to be efficient compared to the roles of the existing large-scale methodology.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.84-89
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• 2007

In order to guarantee the safety of the facility systems, one of the essential components is information on mechanical properties of materials used for the construction. However, acquisition or accumulation of the mechanical property data in industrial fields is limited because this operation does not yield profit, excepting few materials production companies. Corresponding to the urgent needs and poor economical features, the MOCIE has founded the National Center for Standard Reference Data in the KRISS and also designated the Data Center of Mechanical Properties for Metallic Materials (DCMP) as a principal operating section. The DCMP plays roles of collection, edition and evaluation of the mechanical data and development of reference standards. In this study, several functions of the DCMP and standardization procedures of mechanical properties data will be introduced the prospective of standard reference researches will be discussed based on active feedbacks from industrial fields.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2785-2799
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• 2020

We propose a novel speaker adaptation method using acoustic model clustering. The similarity of different speakers is defined by the cosine distance between their i-vectors (intermediate vectors), and various efficient clustering algorithms are applied to obtain a number of speaker subsets with different characteristics. The speaker-independent model is then retrained with the training data of the individual speaker subsets grouped by the clustering results, and an unknown speech is recognized by the retrained model of the closest cluster. The proposed method is applied to a large-scale speech recognition system implemented by a hybrid hidden Markov model and deep neural network framework. An experiment was conducted to evaluate the word error rates using Resource Management database. When the proposed speaker adaptation method using i-vector based clustering was applied, the performance, as compared to that of the conventional speaker-independent speech recognition model, was improved relatively by as much as 12.2% for the conventional fully neural network, and by as much as 10.5% for the bidirectional long short-term memory.

• Genomics & Informatics
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• v.11 no.4
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• pp.186-190
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• 2013

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1410-1429
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• 2017

Mobility arises naturally in the Internet of Things networks, since the location of mobile objects, e.g., mobile agents, mobile software, mobile things, or users with wireless hardware, changes as they move. Tracking their current location is essential to mobile computing. To overcome the scalability problem, hierarchical architectures of location databases have been proposed. When location updates and lookups for mobile objects are localized, these architectures become effective. However, the network signaling costs and the execution number of database operations increase particularly when the scale of the architectures and the numbers of databases becomes large to accommodate a great number of objects. This disadvantage can be alleviated by a location caching scheme which exploits the spatial and temporal locality in location lookup. In this paper, we propose a hierarchical location caching scheme, which acclimates the existing location caching scheme to a hierarchical architecture of location databases. The performance analysis indicates that the adjustment of such thresholds has an impact on cost reduction in the proposed scheme.