• Journal of The Korean Association of Information Education
• /
• v.11 no.3
• /
• pp.267-279
• /
• 2007

The purpose of this study is to design and practice teaching and learning method for routing algorithm among computer science principle which is difficult to be taught to elementary school students and understood by students. And we find out whether elementary school students can understand those learning contents. Intellectual area was assessed through equivalent test paper before and after the test and emotional area was assessed through students' impressions after class. The test showed that routing algorithm could be taught to children. Therefore, this study presents the learnability of routing algorithm as a learning element of elementary school computer education.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.741-742
• /
• 2013

AODV algorithm is one of the widely used algorithm for wireless ad-hoc environment In AODV, the destination node selects the route with smallest hop count. Since AODV only consider hop count, the selected route could have low capacity link, and degrade QoS. In this paper, we propose a modified AODV algorithm that consider successful transmission rate of each link. Advantage of proposed algorithm is that AODV can support QoS without significant change of the algorithm using modified hop count.

• Journal of the Semiconductor & Display Technology
• /
• v.15 no.1
• /
• pp.27-32
• /
• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

• Journal of Power Electronics
• /
• v.19 no.5
• /
• pp.1248-1258
• /
• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.5
• /
• pp.760-768
• /
• 2016

Recently, as one of the policies for carbon free operation method of independent power system replacing diesel generator with renewable energy such as wind power and photovoltaic(PV) system has been presented. Therefore, this paper proposes an operation algorithm and modeling of independent power system by considering CVCF(constant voltage constant frequency) ESS(energy storage system) for constant frequency and voltage, LC(load control) ESS for demand and supply balancing and SVC(static var compensator) for reactive power compensation. From the simulation results based on the various operation scenario, it is confirmed that proposed operation algorithm and modeling may contribute stable operation and carbon free in independent power system.

• Smart Structures and Systems
• /
• v.31 no.3
• /
• pp.247-257
• /
• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• The Mathematical Education
• /
• v.50 no.3
• /
• pp.309-327
• /
• 2011

In this paper, we extended the division algorithm for the integers to the finite decimals. Though the remainder for the finite decimals is able to be defined as various ways, the remainder could be defined as 'the remained amount' which is the result of the division and as "the remainder" only if 'the remained amount' is decided uniquely by certain conditions. From the definition of "the remainder" for the finite decimal, it could be inferred that 'the division by equal part' and 'the division into equal parts' are proper for the division of the finite decimal concerned with the definition of "the remainder". The finite decimal, based on the unit of measure, seemed to make it possible for us to think "the remainder" both ways: 1" in the division by equal part when the quotient is the discrete amount, and 2" in the division into equal parts when the quotient is not only the discrete amount but also the continuous amount. In this division context, it could be said that the remainder for finite decimal must have the meaning of the justice and the completeness as well. The theorem of the division algorithm for the finite decimal could be accomplished, based on both the unit of measure of "the remainder", and those of the divisor and the dividend. In this paper, the meaning of the division algorithm for the finite decimal was investigated, it is concluded that this theory make it easy to find the remainder in the usual unit as well as in the unusual unit of measure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.519-522
• /
• 2017

In this paper, we propose an algorithm for an alternative method using the clustering algorithm in a system that needs classification to extract individual user context information. In the conventional user classification system, the user has to input his own information. In this paper, we will research and develop a system applying a clustering algorithm which can extract user 's perceived information applying the improved algorithm for user management base. Generally, the algorithm that distinguishes users with the same data makes sure that recorded information matches the newly entered information, and then responds accordingly. However, it is troublesome to manually input information of the new user. Therefore, in this paper, we propose a method to distinguish users by using the clustering algorithm based on the analyzed data from the working memory in the accumulated system without directly inputting the user information. The study shows that the management method applied to the applied algorithm is more adaptive in environments where the number of people is different from that of the existing system (as a subjective observer test method).

• Journal of Engineering Education Research
• /
• v.19 no.6
• /
• pp.49-56
• /
• 2016

The Human Robot Interface (HRI) based on 3D depth sensor on the docent robot is developed and the localization algorithm based on extended Kalman Filter (EKFLA) are proposed through the capstone design by graduate students in this paper. In addition to this, the performance of the proposed EKFLA is also analyzed. The developed HRI system consists of the route generation and localization algorithm, the user behavior pattern awareness algorithm, the map data generation and building algorithm, the obstacle detection and avoidance algorithm on the robot control modules that control the entire behaviors of the robot. It is confirmed that the improvement ratio of the localization error in EKFLA on the scenarios 1-3 is increased compared with the localization algorithm based on Kalman Filter (KFLA) as 21.96%, 25.81% and 15.03%, respectively.

• Child Health Nursing Research
• /
• v.25 no.3
• /
• pp.324-332
• /
• 2019

Purpose: Epilepsy is the most common neurological disorder in childhood. Hospital nurses, who are the first to recognize seizures in epilepsy patients in the ward environment, possess expertise related to epilepsy and play a central role in epilepsy management. The purpose of this study was to develop an algorithm-based education program and to improve nurses' knowledge and self-efficacy related to providing nursing care to children with epilepsy. Methods: The education program consisted of lectures on the definition, cause, classification, diagnosis, treatment, and nursing of epilepsy based on a booklet, as well as practice using an algorithm for nursing interventions when a child experiences a seizure. Twenty-seven nurses working at pediatric neurological wards and a pediatric emergency room participated in the education program. The data were analyzed using descriptive statistics and the paired t-test. Results: Nurses' knowledge and self-efficacy showed a statistically significant improvement after participation in the education program on nursing care for children with epilepsy. Conclusion: The application of this education program for hospital setting is expected to improve nurses' capability to care for children with epilepsy, thereby contributing to a higher quality of nursing.