• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.17-24
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• 2009

Increasing use of information system has led to larger amount of developing expenses and demands on software. Until recent days, the model using regression analysis based on statistical algorithm has been used. However, Machine learning is more investigated now. This paper estimates the software cost using SVR(Support Vector Regression). a sort of machine learning technique. Also, it finds the best set of parameters applying immune algorithm. In this paper, software cost estimation is performed by SVR based on immune algorithm while changing populations, memory cells, and number of allele. Finally, this paper analyzes and compares the result with existing other machine learning methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1076-1087
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• 2010

Together with a new advent of embedded processor developed to support specific application area and it evolution, a new research of software development to support the embedded processor and its commercial challenge has been revitalized. Retargetability is typically achieved by providing target machine information, ADL, as input. The ADLs are used to specify processor and memory architectures and generate software toolkit including compiler, simulator, assembler, profiler, and debugger. The EXPRESSION ADL follows a mixed level approach-it can capture both the structure and behavior supporting a natural specification of the programmable architectures consisting of processor cores, coprocessors, and memories. And it was originally designed to capture processor/memory architectures and generate software toolkit to enable compiler-in-the-loop exploration of SoC architecture. In this paper, we designed the class-based ADL based on the EXPRESSION ADL to promote the write-ability, extensibility and verified the validation of grammar. For this works, we defined 6 core classes and generated the EXPRESSION's compiler and simulator through the MIPS R4000 description.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.503-506
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• 2015

In accordance with IoT(Internet of Things) commercialization, the need to design SoC-based hardware platform with wireless communication is increasing. This paper therefor proposes an SoC platform architecture with Smart Frame System inter-communicating between devices. Wireless communication functions and high-performance real-time image processing hardware structure was applied to existing digital photo frame. We developed a smart phone application to control the smart frame through Bluetooth communication. The SoC platform hardware consists of CIS controller, Memory controller, ISP(Image Signal Processing) module for image scaling, Bluetooth Interface for inter-communicating between devices, VGA/TFT-LCD controller for displaying video. The Smart Frame System to support the IoT services was implemented and verified using HBE-SoC-IPD test board equipped with Virtex4 XC4VLX80 FPGA. The operating frequency is 54MHz.

• 한국노년학
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• v.31 no.2
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• pp.401-417
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• 2011

The life review means a process of appraising life of oneself and it is essential for finding the meaning of life in old age. The memoir writing is a kind of method of life review. The memoir writing program used in this study focused especially on enhancing the cognitive skills by providing priming and retrieval support for memory performance in reminiscing past experiences. All fourteen participants were healthy and normal community dwellers and attended four-month long programof memoir writing classes which are consisted of different themes for each week. The aim of this study was to examine if the memoir writing program would render the positive effect on mental health and cognitive ability of the elderly. The results were that quality of life, life satisfaction, ego integrity of the participants showed positive change and the level of depression was significantly reduced compared to that of the control group. The findings in the present study suggest that the memoir writing can serve as one of the community initiative program to the growing population of the elderly for their emotional and cognitive challenges that they face everyday. To warrant the validity of the program, further study is needed for other sectors of elderly population, such as elderly living alone or those with both physical and/or cognitive disadvantages.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.4
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• pp.232-243
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• 2002

There are many methods for improving TLB (translation lookaside buffer) performance, such as increasing the number of entry in TLB, supporting large page or multiple page sizes. The best way is to support multiple page sizes, but any operating system doesn't support multiple page sizes in user mode. So, we propose the new structure of TLB supporting two pages to obtain the effect of multiple page sizes with high performance and at low cost without operating system support. we propose a new TLB structure supporting two page sizes dynamically and selectively for high performance and low cost design without any operating system support. For high performance, a promotion-TLB is designed by supporting two page sizes. Also in order to attain low power consumption, a banked-TLB is constructed by dividing one fully associative TLB space into two sub-fully associative TLBs. These two banked-TLB structures are integrated into a banked-promotion TLB as a low power and high performance TLB structure for embedded processors. According to the results of comparison and analysis, a similar performance can be achieved by using fewer TLB entries and also power consumption can be reduced by around 50% comparing with the fully associative TLB.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.721-732
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• 2000

Multimedia communication systems require not only high-performance computer hardwares and high-speed networks, but also a buffer management mechanism to process many data efficiently. Two buffer handling methods, Push and Pull, are commonly used. In the Push method, a server controls the flow of dat to a client, while in the Pull method, a client controls the flow of data from a server. Those buffering schemes can be applied to the data transfer between the packet receiving buffer, which receives media data from a network server, and media playout devices, which play the recived media data. However, the buffer management mechanism in client-sides mainly support either one of the Push or the Pull method. Consequently, they have some limitations to support various media playout devices. Futhermore, even though some of them support both methods, it is difficult to use since they can't provide a unified structure. To resolved these problems, in this paper, we propose an efficient and flexible Push/Pull buffer management mechanism at client-side. The proposed buffer management scheme supports both Push and Pull method to provide various media playout devices and to support buffering function to absorb network jitter. The proposed scheme can support the various media playback devices using a single buffer space which in consequence, saves memory space compared to the case that a client keeps tow types of buffers. Moreover, it facilitates the single buffer as a mechanism for the absorbing network jitter effectively and efficiently. The proposed scheme has been implemented in an existing multimedia communication system, so called ISSA (Integrated Streaming Service Architecture), and it shows a good performance result compared to the conventional buffering methods in multimedia communication environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1998-2004
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• 2009

Recently, due to technical developments of various storage devices and networks, the amount of data increases rapidly. The large volume of data streams poses unique space and time constraints on the data mining process. The continuous characteristic of streaming data necessitates the use of algorithms that require only one scan over the stream for knowledge discovery. Most of the researches based on the support are concerned with the frequent itemsets, but ignore the infrequent itemsets even if it is crucial. In this paper, we propose an efficient method WSFI-Mine(Weighted Support Frequent Itemsets Mine) to mine all frequent itemsets by one scan from the data stream. This method can discover the closed frequent itemsets using DCT(Data Stream Closed Pattern Tree). We compare the performance of our algorithm with DSM-FI and THUI-Mine, under different minimum supports. As results show that WSFI-Mine not only run significant faster, but also consume less memory.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.4
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• pp.143-154
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• 2020

Purpose : This study aims to investigate the effect of instrument-activities daily living training through client-centered home visitation on the cognitive functions, occupational performance, and instrument-activities daily living of elderly at the cognitive support grade(Grade6). Methods : The subject of this study was a 66-year-old woman living in G Metropolitan City, who has been diagnosed with Alzheimer's and mild dementia. The study period was from March 17, 2020 through June 12, 2020, and the A-B-A' design, among the individual case experiments, was adopted as the study design. For the data analysis, descriptive statistic and visual analysis using graph were used for the change of cognitive functions, occupational performance, and instrument-activities daily living. Results : The instrument-activities daily living provided through client-centered home visitation improved the subject's cognitive functions, occupational performance(performance, satisfaction) and instrument-activities daily living. Conclusion : This study showed that daily life training through client-centered home visitation can help elderly people at the cognitive support grade select for themselves the problems of daily life caused by cognitive decline and practice specific action plans, thereby enabling them to maintain and improve the cognitive functions necessary for the performance of activities, such as comprehension, memory, and thinking skills. In addition, it is thought that the activities based on the subject's preferences, performance, and sense of importance assured the subject of feelings of motivation and the possibility of participation, and had a positive effect on the subject's performance speed and rate. With the above in mind, Instrument-activities daily living client-centered home visitation is proposed as a potential practical intervention program for individuals. It can help elderly people at cognitive support grade to maintain and improve their functions, thereby delaying the progress of their condition to severe dementia.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.144-150
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• 2020

Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.