• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.31-43
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• 1999

The main goal of this paper is to design a high performance SVP(Stack based Video Processor) for network applications. The SVP is a comprehensive scheme; 'better' in the sense that it is an optimal selection of previously proposed enhancements of a stack machine and a video processor. This can process effectively object-based video data using a S-RISC(Stack-based Reduced Instruction Set Computer) with a semi -general-purpose architecture having a stack buffer for OOP(Object-Oriented Programming) with many small procedures at running programs. And it includes a vector processor that can improve the MPEG coding speed. The vector processor in the SVP can execute advanced mode motion compensation, motion prediction by half pixel and SA-DCT(Shape Adaptive-Discrete Cosine Transform) of MPEG-4. Absolutors and halfers in the vector processor make this architecture extensive to a encoder. We also designed a VLSI stack-oriented video processor using the proposed architecture of stack-oriented video decoding. It was designed with O.5$\mu\textrm{m}$ 3LM standard-cell technology, and has 110K logic gates and 12 Kbits SRAM internal buffer. The operating frequency is 50MHz. This executes algorithms of video decoding for QCIF 15fps(frame per second), maximum rate of VLBV(Very Low Bitrate Video) in MPEG-4.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.438-448
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• 2005

This paper proposes an adaptive tutoring system that provides learning materials dynamically according to the learners' teaming character and ability. Our system, in which a learning phase and a test phase are linked together, supports the personalized instruction-learning by providing the teaming materials by level in the learning phase according to the teaming ability estimated in the test phase. We design and implement a tutoring system consisted of an evaluation component and a learning component. An evaluation component uses a computerized adaptive test(CAT) based on item response theory to evaluate learners' ability while a learning component employs fuzzy level set theory so that teaming contents are provided to learners according to learners' level.

• Journal of The Korean Association For Science Education
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• v.17 no.3
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• pp.323-332
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• 1997

In order to use analog more systematically in science class, an instructional model was designed on the basis of analogical reasoning processes (encoding, inference, mapping, application, and response) in the Sternberg's component process theory. The model has five phases (introducing target context, cue retrieval of analog context, mapping similarity and drawing target concept, application, and elaboration), and the instructional effects of using the model upon students' comprehension of science concepts and motivation level of learning were investigated. The treatment and control groups (1 class each) were selected from 8th-grade classes and taught about chemical change and chemical reaction for the period of 10 class hours. The treatment group was taught with the materials based on the model, while the control group was taught in traditional instruction without using analog. Before the instructions, modified versions of the Patterns of Adaptive Learning Survey and the Group Assessment of Logical Thinking were administered, and their scores were used as covariates for students' conceptions and motivational level of learning, respectively. Analogical reasoning ability test was also administered, and its score was used as a blocking variable. After the instructions, students' conceptions were measured by a researcher-made science conception test, and their motivational level of learning was measured by a modified version of the Instructional Materials Motivation Scale. The results indicated that the adjusted mean score of the conception test for the treatment group was significantly higher than that of the control group at .01 level of significance. No significant interaction between the instruction and the analogical reasoning ability was found. Although the motivational level of learning for the treatment group was higher than that for the control group, the difference was found to be statistically insignificant. Educational implications are discussed.

• Journal of The Korean Association For Science Education
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• v.19 no.1
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• pp.128-136
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• 1999

The effects of computer-assisted instruction (CAl) using molecular-level animation and worksheet upon students' achievement, conceptual understanding, and learning motivation were investigated. Treatment and control groups (2 classes) were selected from a girls' high school in Seoul, and taught about dissolution for 3 class hours. Before the instructions, the Patterns of Adaptive Learning Survey (PALS) was administered, and the grade for a previous science course was obtained. The PALS score was used as a covariate, and the other as a blocking variable. After the instructions, the achievement test, the conceptions test, and the Instructional Materials Motivation Scale (lMMS) were administered. Two-way ANCOVA results revealed that the scores of the CAl group in the achievement and the conceptions tests were significantly higher than those of the control group. The CAl group also performed better in all subtests of the IMMS except the subtest of relevance.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.325-331
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• 2015

In this study, we investigated the effects of individualized learning adapted to students' conceptions using smart devices in science instruction upon students' conceptual understanding, the retention of conception, achievement, learning motivation, enjoyment of science lessons, and perception about individualized learning using smart devices. Four seventh-grade classes at a coed middle school in Seoul were assigned to a control group and a treatment group. Students were taught about molecular motions for seven class periods. Two-way ANCOVA results revealed that the scores of a conception test, the retention of the conception test, a learning motivation test, and an enjoyment of science lessons test for the treatment group were significantly higher than those for the control group. Although the score of the treatment group was higher than that of the control group in the achievement test, the difference was not statistically significant. Students' perceptions about individualized learning using smart devices were also found to be positive.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.662-665
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• 2013

ITS(Intelligent Tutoring System) is a system that provides active and flexible tutoring conditions to learners, having adopted artificial intelligence to overcome the limitations of CAI(Computer Assisted Instruction). However, the existing ITS has a few problems; the system provides the same contents to every learner, not considering main variants of their learning and achievement, characters and levels, and therefore, it does not generate satisfactory results; the system does not offer a properly designed course schedule. Therefore, this thesis proposes ARS(Adaptive Recommendation System), founded on ITS, that provides contents designed based on the characters and levels of learners. To catch the characters of learners, the important variant for successful learning, ARS applies and embodies a module of self-assessment test. Also, it puts weighs according to the areas of learning which is different from the simplified assessment that asks for short and mechanical answers for the purpose of knowing the levels of the learners.

• The Journal of Korean Association of Computer Education
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• v.12 no.5
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• pp.87-94
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• 2009

This paper presents a Web-based interactive and adaptive learning system that helps students learn the pumping lemma for the family of regular languages. Our system allows the students to proceed with their learning according to their individual differences through Web-Based Instruction and gives them opportunities for the interaction so that they can practice exercise related to the learning and gain feedbacks on the results of the exercises immediately. Especially, the system provides adaptive scaffolding that helps learners understand each step for the proof of the pumping lemma. Unlike existing systems that support learning the pumping lemma, the proposed system defines possible errors in advance and provides appropriate messages for corresponding errors. In addition, the system allows the learners to decompose a string into three parts so that they can understand the pumping lemma precisely.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.292-298
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• 2017

The complexity of image compression algorithms has increased in order to improve image compression efficiency. One way to resolve high computational complexity is parallel processing. However, entropy coding, which is lossless compression, does not fit into the parallel processing form because of the correlation between consecutive symbols. This paper proposes a new application-specific instruction set processor (ASIP) platform by adding new context-adaptive binary arithmetic coding (CABAC) instructions to the existing platform to quickly process a variety of entropy coding. The newly added instructions work without conflicts with all other existing instructions of the platform, providing the flexibility to handle many coding standards with fast processing speeds. CABAC software is implemented for High Efficiency Video Coding (HEVC) and the performance of the proposed ASIP platform was verified with a field programmable gate array simulation.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.81-89
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• 2011

Cyber-home Learning aims to extend learning space from the classroom to real-life situations, and teachers of research schools on Cyber-home learning have indicated the importance of connection with school instruction in order to improve students' performance. The goal of this study is to evaluate the influence of the instructional method( blended-learning vs just cyber learning) and the learning styles by Kolb's LSI on Cyber-home learning. We carried out the experiment using two similar classes in the social and math subjects for 1 semester. The results statistically shows the instructional method is the most influence on learning score and the next element is the learning styles. Therefor this study proved again Cyber-home learning is effective when connecting with school instruction and also the more various contents on learning styles could be supportive to students. In other words teacher's role and the adaptive learning contents by learning styles are essential for Cyber-home Learning's success.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1158-1165
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• 1999

조건부 분기 명령어(conditional branch instruction)의 잘못된 분기 예측(branch misprediction)은 프로세서의 성능 향상에 심각한 장애 요인이 되고 있다. 특히 시분할(time-sharing) 시스템과 같이 문맥 교환(context switch)이 발생하는 멀티프로그래밍 환경(multiprogramming environment)에서는 더욱 낮은 분기 예측 정확성(branch prediction accuracy)을 보인다. 본 논문에서는 문맥 교환이 발생하는 멀티프로그래밍 환경에서 높은 분기 예측 정확성을 보이는 중첩 분기 예측표 교환(Overlapped Predictor Table Switch, OPTS) 기법을 소개한다. 분기 예측표(predictor table)를 분할하여 각각의 프로세스(process)에 할당하는 OPTS 기법은 문맥 교환의 영향을 최소화함으로써 높은 분기 예측 정확성을 유지하는 분기 예측 방법이다.Abstract There is wide agreement that one of the most important impediments to the performance of current and future pipelined superscalar processors is the presence of conditional branches in the instruction stream. Accurate branch prediction is required to overcome this performance limitation. Many branch predictors have been proposed to help to alleviate this problem, including the two-level adaptive branch predictor, and more recently, hybrid branch predictor. In a less idealized environment, such as a time-sharing system, code of interest involves context switches. Context switches, even at fairly large intervals, can seriously degrade the performance of many of the most accurate branch prediction schemes. In this study, we measure the effect of context switch on the branch prediction accuracy in various situation and show the feasibility of our new mechanism, OPTS(Overlapped Predictor Table Switch), which save and restore branch history table at every context switch.