• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.237-240
• /
• 2007

이 논문에서는 수정된 Sequential Algorithmic Schema를 이용해서 여러 장소를 이동하면서 찍은 디지털 이미지를 효율적으로 분류할 수 있는 방법을 제안한다. 제안하는 방법은 이웃 패턴들과 특징 정보의 연속성, 유사성을 가지며 들어오는 입력 패턴에 대해 기존의 모든 군집과 유사도를 비교하는 방법이 아니라 이전 군집의 정보와 유사도를 비교하여 군집에 포함시키거나 동적으로 군집을 생성하는 효율적인 군집화 방법이다. 제안한 방법은 실험을 통해서 기존의 군집화 기법에 성능 및 속도의 효율성을 증명하였다.

• The Mathematical Education
• /
• v.39 no.1
• /
• pp.49-58
• /
• 2000

The purpose of this study is to investigate how to teach algorithms in mathematics class. Until recently, traditional school mathematics was primarily treated as drill and practice or memorizing of algorithmic skills. In an attempt to shift the focus and energies of mathematics teachers toward problem solving, conceptual understanding and the development of number sense, the recent reform recommendations do-emphasize algorithmic skills, in particular, paper-pencil algorithms. But the development of algorithmic thinking provides the foundation for student's mathematical power and confidence in their ability to do mathematics. Hence, for learning algorithms meaningfully, they should be taught with problem solving and conceptual understanding.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.12
• /
• pp.20-27
• /
• 1997

In this paper, a multiplying digital-to-analog converter (MDAC) circuit for low-power high-resolution CMOS algorithmic A/D converters (ADC's) is proposed. The proposed MDAC is designed to operte properly at a supply at a supply voltge between 3 V and 5 V and employs an analog0domain power reduction technique based on a bias switching circuit so that the total power consumption can be optimized. As metal-to-metal capacitors are implemented as frequency compensation capacitors, opamps' performance can be varied by imperfect process control. The MDAC minimizes the effects by the circuit performance variations with on-chip tuning circuits. The proposed low-power MDAC is implementd as a sub-block of a 10-bit 200kHz algorithmic ADC using a 0.6 um single-poly double-metal n-well CMOS technology. With the power-reduction technique enabled, the power consumption of the experimental ADC is reduced from 11mW to 7mW at a 3.3V supply voltage and the power reduction ratio of 36% is achieved.

• The Journal of Korean Association of Computer Education
• /
• v.11 no.4
• /
• pp.1-12
• /
• 2008

This paper proposes basic algorithmic thinking based problem models applicable immediately without additional learnings and it problems basic problems and evaluation methods using material factors in an elementary course of mathematics For these purposes, an algorithmic thinking based problem model and it's basic problem models are proposed based on flowchart design methods with 5 degrees of difficulties. And algorithmic thinking based basic problems are developed by applying the proposed basic problem models into material domain in an elementary course of mathematics. And this paper proves the validity of developed basic problems in defining then as algorithmic thinking based basic problems through experiments and statistical analyses. The experimental results are analyzed in views of variety and effectiveness evaluation of answer algorithms and suitability of allocating 5 degrees of difficulties to the developed basic problems.

• Journal of The Korean Association For Science Education
• /
• v.26 no.1
• /
• pp.1-8
• /
• 2006

This study investigated the causal relationships between high school student multiple-choice algorithmic chemistry problem solving and 1) the motivational variables of achievement goal (task goal/performance goal/performance-avoidance) and perceived ability, and 2) the cognitive variables of learning strategy (deep learning/surface learning) and self-regulation. Path analysis supported a causal model in which perceived ability and task goal were found to positively influence algorithmic chemistry problem-solving ability via self-regulation. In particular it was found that perceived ability directly influenced algorithmic chemistry problem-solving ability. Moreover, deep learning was found to have been influenced by perceived ability and task goal, while surface learning was influenced by performance-avoidance goal. Lastly, there did not appear to be any causal relationship between learning strategy and algorithmic chemistry problem-solving ability.

• The KIPS Transactions:PartA
• /
• v.11A no.1
• /
• pp.97-108
• /
• 2004

This paper proposes to use an algorithmic debugging technique for locating logical errors in Java programs. The algorithmic debugging is a semi-automated debugging technique that builds an execution tree from a source program and locates logical errors, if any, included in the program from the execution tree with top-down method. So, it is very important to build a suitable execution tree from the various programming languages. In this paper we propose the method for building an execution tree iron Java programs and walk through an example. This approach could reduce the number of interactions between a user and a debugging system than the traditional step-wise debugging technique.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.1
• /
• pp.11-17
• /
• 2002

This paper describes on a position detection method for the motors which have repetitive operations using the Algorithmic State Machine(ASM), one of the digital logic design methods. With analyses for the incremental encoder output patterns, state diagram and state table are constructed and a digital circuit which can detect the changing point of direction of motor rotation is designed. To verify the validity of the designed circuit, simulations for all cases in which the direction of motor rotation is changed, are performed. Simulation results show the designed digital circuit can detect the direction of motor rotation accurately for all cases.

• Journal of The Korean Association For Science Education
• /
• v.20 no.2
• /
• pp.214-220
• /
• 2000

The difference (bias) between self-efficacy and chemistry problem-solving ability was investigated for 96 (male: 48, female: 48) high school students. A self-efficacy instrument was administered, which asked the confidence in solving algorithmic and conceptual problems successfully. Their chemistry problem-solving ability was then assessed with 10 algorithmic and 10 conceptual problems as same in the self-efficacy instrument. Although students had higher scores in the algorithmic problems, no significant difference was found in the self-efficacy to solve the two different forms of problems. Therefore, the bias scores in the conceptual problems were higher than those in the algorithmic problems. Two-way ANOVA results for the bias in the algorithmic problems revealed a significant interaction between gender and the previous achievement level. Analysis of simple effects indicated that the bias scores of high-achieving boys were significantly higher than those of high-achieving girls. While most high-achieving boys were in the overconfident category, high-achieving girls were more likely to be in the underconfident category.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.10
• /
• pp.855-868
• /
• 2004

There are several types of singularities in controlling robotic manipulators: kinematic singularity, algorithmic singularity, semi-kinematic singularity, semi-algorithmic singularity, and representation singularity. The kinematic and algorithmic singularities have been investigated intensively because they are not predictable or difficult to avoid. The problem with these singularities is an unnecessary performance reduction in non-singular region and the difficulty in performance tuning. Tn this paper, we propose a method of avoiding kinematic and algorithmic singularities by applying a task reconstruction approach while maximizing the task performance by calculating singularity measures. The proposed method is implemented by removing the component approaching the singularity calculated by using singularity measure in real time. The outstanding feature of the proposed task reconstruction method (TR-method) is that it is based on a local task reconstruction as opposed to the local joint reconstruction of many other approaches. And, this method has dynamic task priority assignment feature which ensures the system stability under singular regions owing to the change of task priority. The TR-method enables us to increase the task controller gain to improve the task performance whereas this increase can destabilize the system for the conventional algorithms in real experiments. In addition, the physical meaning of tuning parameters is very straightforward. Hence, we can maximize task performance even near the singular region while simultaneously obtaining the singularity-free motion. The advantage of the proposed method is experimentally tested by using the 7-dof spatial manipulator, and the result shows that the new method improves the performance several times over the existing algorithms.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.652-655
• /
• 1997

An exploration for an intelligence paradigm has been delineated. Artificial intelligence and artificial life paradigms seem to fail to show the whole picture of human intelligence. We may understand the human intelligence better by adding the emotional part of human intelligence to the intellectual part of human intelligence. Emotional intelligence is investigated in terms of composing machine as a modern abstract art. Various algorithmic composition and performance concepts are currently being investigated and implemented. Intelligent mapping algorithms restructure the traditional predetermined composition algorithms. Music based on fractals and neural networks is being composed. Also, emotional intelligence and aesthetic aspects of Korean traditional music are investigated in terms of fractal relationship. As a result, this exploration will greatly broaden the potentials of the intelligence research. The exploration of art in the view of intelligence, information and structure will restore the balanced sense, of art and science which seeks happiness in life. The investigations of emotional intelligence will establish the foundations of intelligence, information and control technologies.