• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.219-227
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• 2012

The trend is going to obtain the accurate and fast information to the development of information technology and electronic technology as an important part of corporate management. Press equipment to produce products that target is small and medium businesses. Became so economical real-time production information system(R-PIS) model has been implemented. R-PIS configure the embedded hardware and PC application software. This system is easy maintenance and upgrade that general-purpose PC and a modular hardware devices. Consists of modules such as wireless communication, LCD, Key-pad, memory control, and sensor signal. R-PIS is efficient materials and product management to maximize the productivity of the enterprise.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.803-810
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• 2007

Although synthetic aperture focusing techniques can improve the spatial resolution of ultrasound imaging, they have not been employed in a commercial product because they require a real-time N-channel beamformer with a tremendously increased hardware complexity for simultaneous beamforming along M multiple lines. In this paper, a hardware-efficient beamformer architecture for synthetic aperture focusing is presented. In contrast to the straightforward design using NM delay calculators, the proposed method utilizes only M delay calculators by sharing the same values among the focusing delays which should be calculated at the same time between the N channels for all imaging points along the M scan lines. In general, synthetic aperture beamforming requires M 2-port memories. In the proposed beamformer, the input data for each channel is first upsampled with a 4-fold interpolator and each polyphase component of the interpolator output is stored into a 2-port memory separately, requiring 4M 2-port memories for each channel. By properly limiting the area formed with the synthetic aperture focusing, the input memory buffer can be implemented with only 4 2-port memories and one short multi-port memory.

• Korean Institute of Interior Design Journal
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• v.18 no.5
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• pp.12-20
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• 2009

Memory and schema are very similar in terms of human accumulated mental and physical experiences. However, while memory has more personal aspect, schema discussed in this paper has more collective aspect. Schema has been developed through different generations and times, and has become a specific psychological or visual element(s) that can be applied to various fields, such as all, design and architecture. This study focuses on Aldo Rossi's architectural design characteristics based on his 'Autobiographical Concept' as well as personal schema. 'Autobiographical Concept' is the crucial structure supporting Aldo Rossi's distinctive formalization and spatialization. 4 case projects were comparatively analyzed by the 5 elements included in 'Autobiographical Concept'. It was not easy to relate each element to a specific design aspect because the 5 elements are somehow theoretically and conceptually inter-connected each other. Even though it is very difficult to directly relate a conceptual element with a real spatial element, it is found that the 5 elements have some differences in the spatialization process. Thus, in the conclusion, this study attempted to show the unique characteristics of the Aldo Rossi's architectural design process based on his 'Autobiographical Concept'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1301-1306
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• 2011

RTOS in the embedded system is a powerful tool for the design of multi-tasking. However, previous RTOS has large proportion in the MCU with limited memory. So it is difficult to apply RTOS. In this paper, I removed less frequently used features from the traditional RTOS, and designed lightweight RTOS that schedules and manages the resources with minimal code. I used techniques to obtain user memory using sharing stack, and to reduce the overhead at context. Considering ratio of kernel and applications, the RTOS designed in this paper is available on the MCU with more than 4KB of program memory.

• Smart Structures and Systems
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• v.18 no.4
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• pp.663-682
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• 2016

Continuum manipulators as a kind of mechanical arms are useful tools in special robotic applications. In medical applications, like colonoscopy, a maneuverable thin and flexible manipulator is required. This research is focused on developing a basic module for such an application using shape memory alloys (SMA). In the structure of the module three wires of SMA are uniformly distributed and attached to the circumference of a flexible tube. By activating wires, individually or together, different rotation regimes are provided. SMA model is used based on Brinson work. The SMA model is combined to model of flexible tube to provide a composite model of the module. Simulating the model in Matlab provided a platform to be used to develop controller. Complex and nonlinear behavior of SMA make the control problem hard especially when a few SMA actuators are active simultaneously. In this paper, position control of the two degree of freedom module is under focus. An experimental control strategy is developed to regulate a desired position in the module. The simulation results present a reasonable performance of the controller. Moreover, the results are verified through experiments and show that the continuum module of this paper would be used in real modular manipulators.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.269-277
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• 2018

NAND flash memory has widely been used because of non-volatility, low power consumption and fast access time. However, it suffers from inability to provide update-in-place and the erase cycle is limited. The unit of read/write operation is a page and the unit of erase operation is a block. Moreover erase operation is slower than other operations. We proposed the Adaptive Garbage Collection (called "AGC") policy which focuses on not only reducing garbage collection process time for real-time guarantee but also wear-leveling for a flash memory lifetime. The AGC performs better than Cost-benefit policy and Greedy policy. But the AGC does not consider the operation characteristics. So we proposed the Advanced Adaptive Garbage Collection (called "A-AGC") policy which considers the page write operation count and block erase operation count. The A-AGC reduces the write operations by considering the data update frequency and update data size. Also, it reduces the erase operations by considering the file fragmentation. We implemented the A-AGC policy and measured the performance compared with the AGC policy. Simulation results show that the A-AGC policy performs better than AGC, specially for append operation.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.149-160
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• 2017

Sentiment analysis is the process of determining whether a piece of document, text or conversation is positive, negative, neural or other emotion. Sentiment analysis has been applied for several real-world applications, such as chatbot. In the last five years, the practical use of the chatbot has been prevailing in many field of industry. In the chatbot applications, to recognize the user emotion, sentiment analysis must be performed in advance in order to understand the intent of speakers. The specific emotion is more than describing positive or negative sentences. In light of this context, we propose deep learning models for conducting multi-class sentiment analysis for identifying speaker's emotion which is categorized to be joy, fear, guilt, sad, shame, disgust, and anger. Thus, we develop convolutional neural network (CNN), long short term memory (LSTM), and multi-layer neural network models, as deep neural networks models, for detecting emotion in a sentence. In addition, word embedding process was also applied in our research. In our experiments, we have found that long short term memory (LSTM) model performs best compared to convolutional neural networks and multi-layer neural networks. Moreover, we also show the practical applicability of the deep learning models to the sentiment analysis for chatbot.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.4
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• pp.229-236
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• 2005

This paper presents a system level architecture evaluation technique that leverages transaction level modeling but also significantly extends it to the realm of system level performance evaluation. A major issue lies with the modeling effort. To reduce the modeling effort the proposed technique develops the concept of worst case scenarios. Since the memory controller is often found to be an important component that critically affects the system performance and thus needs optimization, the paper further addresses how to evaluate and optimize the memory controllers, focusing on the test environment and the methodology. The paper also presents an industrial case study using a real state-of-the-art design. In the case study, it is reported that the proposed technique has helped successfully find the performance bottleneck and provide appropriate feedback on time.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.73-82
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• 2017

Recently in-memory data stream processing has been actively applied to various subjects such as query processing, OLAP, data mining, i.e., frequent item sets, association rules, clustering. However, finding regular periodic patterns of events in an infinite data stream gets less attention. Most researches about finding periods use autocorrelation functions to find certain changes in periodic patterns, not period itself. And they usually find periodic patterns in time-series databases, not in data streams. Literally a period means the length or era of time that some phenomenon recur in a certain time interval. However in real applications a data set indeed evolves with tiny differences as time elapses. This kind of a period is called as a pseudo-period. This paper proposes a new scheme called FPMH (Finding Periods using Multiple Hash functions) algorithm to find such a set of pseudo-periods over a data stream based on multiple hash functions. According to the type of pseudo period, this paper categorizes FPMH into three, FPMH-E, FPMH-PC, FPMH-PP. To maximize the performance of the algorithm in the data stream environment and to keep most recent periodic patterns in memory, we applied decay mechanism to FPMH algorithms. FPMH algorithm minimizes the usage of memory as well as processing time with acceptable accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1792-1798
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• 2017

Event Data Recorder(Car Black-Box) with WiFi dongle have been released, and the platform of the majority is the Linux platform. This is because the platform development is possible in little investment cost by reducing the source licensing costs by taking advantage of the open source. But utilizing Linux platform has the limitations of boot-up time and consuming processing power due to the limitation of battery capacity, to be cost-competitive to minimize the use of memory. In this paper, the real-time operating system(RTOS) is utilized to optimize these portions. MP4 encoder and Muxer are developed to be about ten seconds boot up and minimized memory. It has the advantages of operating at lower power consumption than the Linux utilizing WiFi dongle. Utilizing a WiFi dongle is to provide a progressive download feature on smart phones to lower product prices. But RTOS has the weakness in WiFi. Porting TCP /IP, Web and DHCP server and combination with the USB OTG Host interface by implementing the protocol stack are developed for WiFi. And also SPI NOR flash memory is utilized for faster boot time and cost reductions, low processing power to be consume. As the results, the developed proved the 10 seconds booting time, 24 frame rate/sec. and 10% lower power consumption.