• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.216-219
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• 2003

Among the techniques to protect private information by adopting biometrics, speaker verification is expected to be widely used due to advantages in convenient usage and inexpensive implementation cost Speaker verification should achieve a high degree of the reliability in the verification nout the flexibility in speech text usage, and the efficiency in verification system complexity. Continuants have excellent speaker-discriminant power and the modest number of phonemes in the category, and multilayer perceptrons (MLPs) have superior recognition ability and fast operation speed. In consequence, the two provide viable ways for speaker verification system to obtain the above properties. This paper implements a system to which continuants and MLPs are applied, and evaluates the system using a Korean speech database. The results of the experiment prove that continuants and MLPs enable the system to acquire the three properties.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.249-252
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• 2023

공동 주거공간에서 생활하는 사람들은 세탁기를 공동으로 사용해야 하는데, 규칙이 엄격하게 정해져 있지 않으면 본인이 원하는 시간에 사용하기 힘들다. 본 논문에서는 이러한 문제점을 해소하고자 개발한 세탁기 예약 및 실시간 이용 현황 조회 웹사이트의 연구 내용을 기록하였다. 개발된 사이트를 통해 사용자는 예약을 하여 원하는 시간에 해당 시설을 이용할 수 있다. 또한 실시간으로 사용 현황을 조회함으로써 본인의 사용 순서를 명확하게 인지할 수 있으며 결과적으로 시간을 절약할 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.218-225
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• 1999

The purpose of this study is to investigate 1-10 year old kindergarten teachers of usage computer program in kindergarten. And the relations between the usage of computer program examined by students and kindergarten teachers were also investigated. The subjects were drawn from fifty kindergarten : 199 kindergarten teachers. The data were analyzed by frequency. percentage, $x^2$ test. The research findings were as follows: 1) There were differences in number of kindergarten teachers engaged by the computer. ( $x^2$＝ 138.486, df=36, p＜.001) 2) There were no differences in number of kindergarten teachers engaged by the kind of computer program. ($x^2$= 75.42, df=80 p＞.50) 3) There were differences in number of kindergarten teachers engaged by the kind of computer education program. ($x^2$= 519.566, df=64 p＜.001)

• The Journal of Korean Association of Computer Education
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• v.19 no.5
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• pp.55-71
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• 2016

Recently, Internet addiction problem has arised due to increasing negative effects about excessive internet use among youth. In this study, by utilizing the '11th youth health behaviors online survey data', we discuss the countermeasures for excessive internet usage of adolescence based on various analysis. we examined the effects of demographic characteristic factors, psychological factors, behavioral factors on internet usage of adolescence. As a result, it was confirmed that there were various variables that influenced adolescent internet usage which were not approached in previous researches. And through these results, we can confirm these variables. In addition, we can also provide countermeasures on excessive internet usages by that of adolescents.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.29-36
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• 2007

In the Java a profiler interface such as JVM TI is provided for communication between a Java virtual machine and a profiler. The JVM TI specification, however does not require an implementation of a profiler interface. Consequently the JVM without an implementation of a profiler interface cannot use a profiler with the JVM TI. For solving the problem, we propose a technique which analyzes heap usage without a profiler interface. This technique inserts codes to extract heap usage into source files in the Java. We implemented a code inserter to verify the proposed technique. We experimented with Java programs that are frequently used and opened. the experimental result presents the number of created objects. the maximum number of allocated objects, and the used pattern of the objects.

• Journal of IKEEE
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• v.23 no.2
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• pp.448-453
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• 2019

Under the conflicting objectives of maximum user satisfaction and fast launching, there exist great needs for automated mobile app testing. In automated app testing, detection of usage-state changes is one of the most important issues for minimizing human intervention and testing of various usage scenarios. Because conventional approaches utilizing pre-collected training examples can not handle the rapid evolution of apps, we propose a novel method detecting changes in usage-state through graph-entropy. In the proposed method, widgets in a screen shot are recognized through DNNs and 'onverted graphs. We compared the performance of the proposed method with a SIFT (Scale-Invariant Feature Transform) based method on 20 real-world apps. In most cases, our method achieved superior results, but we found some situations where further improvements are required.

• Journal of Information Technology Applications and Management
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• v.11 no.3
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• pp.89-116
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• 2004

Insurance companies are in a fierce race to catch a new customer. In this situation. sales force automation technologies are often used to support customer relationship management strategies. This study sets out a research model predicting SFA(Sales Force Automation) usage through theoretical studies. Survey data were collected from 145 salespeople across 2 firms that had implemented sales force automation tools and hypotheses were tested empirically. Data were analyzed by path-analysis method of AMOS. The major findings of this study are as follows: Computer self-efficacy, user involvement and voluntariness have a statistically significant influence on the positive perceptions of SFA. These perceptions have a statistically significant influence on user satisfaction and usage of SFA. while user satisfaction has a statistically significant influence on SFA usage. This paper concludes with the discussion of these results and their implications for academic researchers and insurance company managers.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.142-147
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• 2021

In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

• Journal of IKEEE
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• v.24 no.3
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• pp.895-900
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• 2020

In this paper, BSPE replaced the existing multiplication algorithm that consumes a lot of power. Hardware resources are reduced by using a bit-serial multiplier, and variable integer data is used to reduce memory usage. In addition, MOA resource usage and power usage were reduced by applying LOA (Lower-part OR Approximation) to MOA (Multi Operand Adder) used to add partial sums. Therefore, compared to the existing MBS (Multiplication by Barrel Shifter), hardware resource reduction of 44% and power consumption of 42% were reduced. Also, we propose a hardware architecture design for BSPE Core.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.85-91
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• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.