• 한국어정보학회:학술대회논문집
• /
• 2016.10a
• /
• pp.119-121
• /
• 2016

최근 사람과 컴퓨터가 대화를 하는 채팅시스템 연구가 활발해지고 있다. 컴퓨터가 사람의 말에 적절한 응답을 하기 위해선 그 의미를 분석할 필요가 있다. 발화에 대한 의미 분석의 기본이 되는 연구로 감정분석과 화행분석이 있다. 그러나 이 둘은 서로 밀접한 연관이 있음에도 불구하고 함께 분석하는 연구가 시도되지 않았다. 본 연구에서는 Long Short-term Memory(LSTM)를 이용하여 대화체 문장의 감정과 화행, 서술자를 동시에 분석하는 통합 대화 분석모델을 제안한다. 사랑 도메인 데이터를 사용한 실험에서 제안 모델은 감정 58.08%, 화행 82.60%, 서술자 62.74%의 정확도(Accuracy)를 보였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.548-551
• /
• 2003

JSize is a Java equivalent of the Unix size program. The Unix size program analyses an executable file and estimates the size of code and data segment when the file is loaded on memory. Likewise, JSize analyze a Java class file and estimates the size of class area when the file is loaded on memory. This paper presents the principles necessary to estimate the class area size with the information obtained from a class file. An experimental result is included to show the accuracy of estimation the JSize provides.

• Annual Conference on Human and Language Technology
• /
• 2016.10a
• /
• pp.119-121
• /
• 2016

최근 사람과 컴퓨터가 대화를 하는 채팅시스템 연구가 활발해지고 있다. 컴퓨터가 사람의 말에 적절한 응답을 하기 위해선 그 의미를 분석할 필요가 있다. 발화에 대한 의미 분석의 기본이 되는 연구로 감정분석과 화행분석이 있다. 그러나 이 둘은 서로 밀접한 연관이 있음에도 불구하고 함께 분석하는 연구가 시도 되지 않았다. 본 연구에서는 Long Short-term Memory(LSTM)를 이용하여 대화체 문장의 감정과 화행, 서술자를 동시에 분석하는 통합 대화 분석모델을 제안한다. 사랑 도메인 데이터를 사용한 실험에서 제안 모델은 감정 58.08%, 화행 82.60%, 서술자 62.74%의 정확도(Accuracy)를 보였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.21-23
• /
• 2013

Static Random Access Memory (SRAM) using CMOS technology has many advantages. It does not need to refresh every certain time, as a result, the speed of SRAM is faster than Dynamic Random Access Memory (DRAM). This is the reason why SRAM is widely used in almost processors and system on chips (SoC) which require high processing speed. Two basic operations of SRAM are read and write. We consider two basic factors, including the accuracy of read and write operations and the speed of these operations. In our paper, we propose the read and write assist circuits for SRAM. By adding a power control circuit in SRAM, the write operation performed successfully with low error ratio. Moreover, the value in memory cells can be read correctly using the proposed pre-charge method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.409-410
• /
• 2022

This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification. This method will become an important way to optimize the model and improve the performance of the model.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.10 no.4
• /
• pp.97-103
• /
• 2001

The study on the high-speed machine tool is very important for the improvement of productivity since it can shortens cutting and non-cutting time. Especially, high speed of feed drive system is the major research field. In the industries of the advanced countries, the feed drive systems at the speed of 60 m/min have been already developed based on the high lead ball screws. In this study, a high speed feed drive system at the speed of 60 m/ min has been developed, and its movements characteris-tics are investigated. As the movement characteristics, positioning accuracy, angular accuracy, straightness and micro step-response are measured. Thermal characteristics of the system is also discussed. For measuring the movement characteris-tics, a laser interferometer, a memory-based Hi-coder and a cooling device are used. The experimental results confirm that the movement characteristics and the thermal behavior of the system are satisfactory in the aspect of accuracy and stability.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.5
• /
• pp.350-354
• /
• 2009

To optimize the performance of software programs, it is important to know certain hardware parameters such as the CPU speed, the cache size, the number of TLB entries, and the parameters of the memory subsystem. There exist several ways to obtain the values of various hardware parameters. Firstly. the values can be taken from the hardware manual. Secondly, the parameters can be obtained by calling functions provided by the operating systems. Finally, hardware detection programs can find the desired values. Such programs are usually executed on PC or server systems and report the CPU speed, the cache size, the number of TLB entries, and so on. However, they do not sufficiently detect the parameters of one of the most important parts of the computer concerning performance, namely the memory bank layout in the memory subsystem. In this paper, we present an algorithm to detect the memory bank parameters. We run an implementation of our algorithm on various embedded systems and compare the detected values with the real hardware parameters. The results show that the presented algorithm detects the cache size, the number of TLB entries, and the memory bank layout with high accuracy.

• KIISE Transactions on Computing Practices
• /
• v.20 no.9
• /
• pp.519-524
• /
• 2014

The operating systems in the system architecture, which is integrated several applications and modular electronic devices in the same computing device, demand partitioning technology for safety. Thus, operation system requires partition scheduler for partition scheduling. When we design partition scheduler in embedded system, which has small memory and low performance, such as space system, we must consider not only performance but also memory. In this paper, we introduces a linux-based memory efficient partition scheduler using partition bitmap. This partition scheduler demands small memory space and produce low partition switching overhead. The prototype was executed on a LEON4 processor, which is the Next Generation Multicore Processor (NGMP) in the space sector. In evaluation, this prototype shows accuracy, additional memory space and low partition switching overhead.

• Korean Journal of Audiology
• /
• v.25 no.4
• /
• pp.178-188
• /
• 2021

Background and Objectives: The influence of musical aptitude on cognitive test performance in musicians is a long-debated research question. Evidence points to the low performance of nonmusicians in visual and auditory cognitive tasks (working memory and attention) compared with musicians. This cannot be generalized to all nonmusicians, as a sub-group in this population can have innate musical abilities even without any formal musical training. The present study aimed to study the effect of musical aptitude on the working memory and selective attention. Subjects and Methods: Three groups of 20 individuals each (a total of 60 participants), including trained-musicians, nonmusicians with good musical aptitude, and nonmusicians with low musical aptitude, participated in the present study. Cognitive-based visual (Flanker's selective attention test) and auditory (working memory tests: backward digit span and operation span) tests were administered. Results: MANOVA (followed by ANOVA) revealed a benefit of musicianship and musical aptitude on backward digit span and Flanker's reaction time (p<0.05). Discriminant function analyses showed that the groups could be effectively (accuracy, 80%) segregated based on the backward digit span and Flanker's selective attention test. Trained musicians and nonmusicians with good musical aptitude were distinguished as one cluster and nonmusicians with low musical aptitude formed another cluster, hinting the role of musical aptitude in working memory and selective attention. Conclusions: Nonmusicians with good musical aptitude can have enhanced working memory and selective attention skills like musicians. Hence, caution is required when these individuals are included as controls in cognitive-based visual and auditory experiments.

• Journal of Audiology & Otology
• /
• v.25 no.4
• /
• pp.178-188
• /
• 2021

Background and Objectives: The influence of musical aptitude on cognitive test performance in musicians is a long-debated research question. Evidence points to the low performance of nonmusicians in visual and auditory cognitive tasks (working memory and attention) compared with musicians. This cannot be generalized to all nonmusicians, as a sub-group in this population can have innate musical abilities even without any formal musical training. The present study aimed to study the effect of musical aptitude on the working memory and selective attention. Subjects and Methods: Three groups of 20 individuals each (a total of 60 participants), including trained-musicians, nonmusicians with good musical aptitude, and nonmusicians with low musical aptitude, participated in the present study. Cognitive-based visual (Flanker's selective attention test) and auditory (working memory tests: backward digit span and operation span) tests were administered. Results: MANOVA (followed by ANOVA) revealed a benefit of musicianship and musical aptitude on backward digit span and Flanker's reaction time (p<0.05). Discriminant function analyses showed that the groups could be effectively (accuracy, 80%) segregated based on the backward digit span and Flanker's selective attention test. Trained musicians and nonmusicians with good musical aptitude were distinguished as one cluster and nonmusicians with low musical aptitude formed another cluster, hinting the role of musical aptitude in working memory and selective attention. Conclusions: Nonmusicians with good musical aptitude can have enhanced working memory and selective attention skills like musicians. Hence, caution is required when these individuals are included as controls in cognitive-based visual and auditory experiments.