• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.891-898
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• 2009

This paper suggests producer/consumer-based Data Binder enabling applications and biomedical devices developed by mutually different vendors to transfer data dynamically. Data Binder is implemented as a bundle of OSGi platform providing component-based programming model and service-oriented operation architecture. Data Binder complements the disadvantage of OSGi WireAdmin service enabling static data delivery between a producer and a consumer of data. Data Binder normalizes an application requirement as an application descriptor and a device capability as a device descriptor so that it enables dynamic data delivery by making data producer/consumer pair in runtime. Therefore, Data Binder can be used as a connection management of a data link between a data producer and a data consumer in sensor-based application development. The object of this paper is to provide the facility of the healthcare service development by separating a data producer such as a biomedical device from a data consumer such as a healthcare application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.72-80
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• 2018

With the ever increasing advances in computers and their computing power, computational fluid dynamics(CFD) has become an essential engineering tool in the design and analysis of engineering applications. Accordingly, many universities have developed and implemented a course on CFD for undergraduate students. On the other hand, many professors have used industrial examples supplied by computational analysis software companies as CFD examples. This makes many students think of CFD as difficult and confusing. This paper presents a simple CFD example used in the department of mechanical design engineering of Kangwon National University and shows its effectiveness. Most students answered that a simple CFD example is more comprehensive than an industrial example. Therefore, it is necessary to develop simple computational analysis problems in the engineering education field.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.285-299
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• 2013

To enable hard real-time systems to take advantage of multicore processors, it is crucial to obtain the worst-case execution time (WCET) for programs running on multicore processors. However, this is challenging and complicated due to the inter-thread interferences from the shared resources in a multicore processor. Recent research used the combined cache conflict graph (CCCG) to model and compute the worst-case inter-thread interferences on a shared L2 cache in a multicore processor, which is called the CCCG-based approach in this paper. Although it can compute the WCET safely and accurately, its computational complexity is exponential and prohibitive for a large number of cores. In this paper, we propose three counter-based approaches to significantly reduce the complexity of the multicore WCET analysis, while achieving absolute safety with tightness close to the CCCG-based approach. The basic counter-based approach simply counts the worst-case number of cache line blocks mapped to a cache set of a shared L2 cache from all the concurrent threads, and compares it with the associativity of the cache set to compute the worst-case cache behavior. The enhanced counter-based approach uses techniques to enhance the accuracy of calculating the counters. The hybrid counter-based approach combines the enhanced counter-based approach and the CCCG-based approach to further improve the tightness of analysis without significantly increasing the complexity. Our experiments on a 4-core processor indicate that the enhanced counter-based approach overestimates the WCET by 14% on average compared to the CCCG-based approach, while its averaged running time is less than 1/380 that of the CCCG-based approach. The hybrid approach reduces the overestimation to only 2.65%, while its running time is less than 1/150 that of the CCCG-based approach on average.

• KIISE Transactions on Computing Practices
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• v.23 no.2
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• pp.122-127
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• 2017

The data link layer operates reliable internode communication in the OSI reference model. Generally, the forward error correction (FEC) method is used in the data link layer of the wireless sensor network (WSN) environment that has a high frequency of errors. However, the FEC method consumes a significant amount of energy due to its high error correction rate, which negatively affects the networks' lifespan. In contrast with battery-based technology, energy is regularly recharged in the solar-powered WSN to meet higher energy needs than required for basic operation of existing nodes. By efficiently utilizing this surplus energy, the proposed energy-aware FEC method can reduce the data loss rate with no decrement of the network lifetime. The method employs a trade-off relationship between the energy and data loss rate by adjusting the parity length in the FEC method to the energy state in each node. The performance of the proposed scheme was verified through a simulation.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.577-585
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• 2009

Various studies on individual health-care application services have been lively going on due to recent development of information and communication technology and improvement of life quality. Moreover, U-health care area is emerging as a new growth industry as the demand of U-health care service for a quality life grows with the development of medical technology and ubiquitous environment. U-health care system for crew members on ships, who need to spend much time on sea far from their families, is especially needed because they find their job much more stressful not only physically but also mentally than any other people in different jobs do and have less chance to get proper medical services in time. In this paper, we suggested how to get more accurate and objective U-health wellbeing index by complementing SF-36, the general heath care index model in order to managing health of crew. Also we designed the U-health wellbeing index service system which can provide appropriate sports programs or diet contents according to health index.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.5
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• pp.496-505
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• 2000

Clusters of workstations (COW) are becoming an attractive option for parallel scientific computing, a field formerly reserved to the MPPs, because their cost-performance ratio is usuallybetter than that of comparable MPPS, and their hardware and software can be easily enhanced to thelatest generations. In this paper we present the design and implementation of our runtime library forclusters of workstations, called "Collective I/O Clustering". The library provides a friendlyprogramming model for the I/O of irregular applications on clusters of workstations, being completelyintegrated with the underlying communication and I/O system. In the collective I/O clustering, two I/Oconfigurations are possible. In the first I/O configuration, all processors allocated can act as I/Oservers as well as compute nodes. In the second I/O configuration, only a subset of processors canact as I/O servers, The compression and software caching facilities have been incorporated into thecollective 1/0 clustering to optimize the communication and I/O costs. All the performance results wereobtained on the IBM-SP machine, located at Argonne National Labs.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.300-310
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• 2007

The Session Initiation Protocol (SIP) is one of the major protocols used in call-setup over IP telephony. The SIP-signaled calls use many-sided states according to a request of user. In this paper, we suggest seven states and some events that help developers to design and implement new applications efficiently. And they enable an object-oriented design of the system. If you design the call-setup procedure only by the processing model suggested in RFC 3261 over commercial network, a fatal error may occur in the system because of heavy data traffic or unpredicted exception cases. However, according to the suggested seven states, if they are predefined events in the current system state, the standardized processing routine is executed. Otherwise, they can be processed by the exception routine in system. All event processing routines are designed and implemented using Finite State Machine (FSM).

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.531-540
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• 2010

In this paper, we present a two-phase shallow semantic parsing method based on a maximum entropy model. The first phase is to recognize semantic arguments, i.e., argument identification. The second phase is to assign appropriate semantic roles to the recognized arguments, i.e., argument classification. Here, the performance of the first phase is crucial for the success of the entire system, because the second phase is performed on the regions recognized at the identification stage. In order to improve performances of the argument identification, we incorporate syntactic knowledge into its pre-processing step. More precisely, boundaries of the immediate clause and the upper clauses of a predicate obtained from clause identification are utilized for reducing the search space. Further, the distance on parse trees from the parent node of a predicate to the parent node of a parse constituent is exploited. Experimental results show that incorporation of syntactic knowledge and the separation of argument identification from the entire procedure enhance performances of the shallow semantic parsing system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.606-610
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• 2010

In order to provide effective studies in accordance with the shifts in learning paradigms, an LD Publication engine, which is the former engine from the Learning Design (LD) based learning management system, was designed and implemented. The LD Publication engine analyzes the learning contents packages that have been prepared based on the LD and analyzes the constructions and meanings of the information files that describe learning activities in order to model them. The modeled data are fragmentized into effective and accessible forms from in the learning management systems and are then put into the database. LD based learning management systems provide learning effects and learner convenience designed to provide learners with a high performance learning platform. In addition, they will activate the development of content through the reproduction, reuse and sharing of the learning content, which will contribute to the expansion of infrastructures. These systems are also designed to enable linkages among learners' competences, preferences and portfolio, and thus the systems can be easily expanded.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.928-932
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• 2009

Most diseases are caused by complex processes of various factors. Although previous researches have tried to identify the causes of the disease, there are still lots of limitations to clarify the complex factors. Here, we present a disease classification model based on an evolutionary learning approach of combinatorial features using the data sets from the genetics and cohort studies. We implemented a system for finding the combinatorial risk factors and visualizing the results. Our results show that the proposed method not only improves classification accuracy but also identifies biologically meaningful sets of risk factors.