• Journal of Korea Game Society
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• v.13 no.5
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• pp.55-62
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• 2013

Since large terrain data can not be loaded on the GPU or CPU memory at once, out-of-core methods which read necessary part from the secondary storage such as a hard disk are commonly used. However, long delay may occur due to limited bandwidth while loading the data from the hard disk to memory. We propose efficient rendering method of large terrain data, which compresses the data with wavelet technique and save its coefficients in RGBA channel of an image us, then decompresses that in rendering stage. Entire process is performed in GPU using Direct Compute. By reducing the amount of data transfer, performing wavelet computations in parallel and doing decompression quickly on the GPU, our method can reduce rendering time effectively.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.174-174
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• 2014

Memristor devices are one of the most promising candidate approaches to next-generation memory technologies. Memristive switching phenomena usually rely on repeated electrical resistive switching between non-volatile resistance states in an active material under the application of an electrical stimulus, such as a voltage or current. Recent reports have explored the use of variety of external operating parameters, such as the modulation of an applied magnetic field, temperature, or illumination conditions to activate changes in the memristive switching behaviors. Among these possible choices of signal controlling factors of memristor, photon is particularly attractive because photonic signals are not only easier to reach directly over long distances than electrical signal, but they also efficiently manage the interactions between logic devices without any signal interference. Furthermore, due to the inherent wave characteristics of photons, the facile manipulation of the light ray enables incident light angle controlled memristive switching. So that, in the tautological sense, device orienting position with regard to a photon source determines the occurrence of memristive switching as well. To demonstrate this position controlled memory device functionality, we have fabricated a metal-semiconductor-metal memristive switching nanodevice using ZnO nanorods. Superhydrophobicity employed in this memristor gives rise to illumination direction selectivity as an extra controlling parameter which is important feature in emerging. When light irradiates from a point source in water to the surface treated device, refraction of light ray takes place at the water/air interface because of the optical density differences in two media (water/air). When incident light travels through a higher refractive index medium (water; n=1.33) to lower one (air; n=1), a total reflection occurs for incidence angles over the critical value. Thus, when we watch the submerged NW arrays at the view angles over the critical angle, a mirror-like surface is observed due to the presence of air pocket layer. From this processes, the reversible switching characteristics were verified by modulating the light incident angle between the resistor and memristor.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.453-458
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• 2002

Recently, the number of hacking, that use buffer overflow vulnerabilities, are increasing. Although the buffer overflow Problem has been known for a long time, for the following reasons, it continuos to present a serious security threat. There are three defense method of buffer overflow attack. First, allow overwrite but do not allow unauthorized change of control flow. Second, do not allow overwriting at all. Third, allow change of control flow, but prevents execution of injected code. This paper is for allowing overwrites but do not allow unauthorized change of control flow which is the solution of extending compiler. The previous defense method has two defects. First, a program company with overhead because it do much thing before than applying for the method In execution of process. Second, each time function returns, it store return address in reserved memory created by compiler. This cause waste of memory too much. The new proposed method is to extend compiler, by processing after compiling and linking time. To complement these defects, we can reduce things to do in execution time. By processing additional steps after compile/linking time and before execution time. We can reduce overhead.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1992.05a
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• pp.91-96
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• 1992

The nonvolatile SNOSFET EEPROM memory devices with the channel width and iength of 15[$\mu\textrm{m}$]${\times}$15[$\mu\textrm{m}$], 15[$\mu\textrm{m}$]${\times}$1.5[$\mu\textrm{m}$] and 1.9[$\mu\textrm{m}$]${\times}$1.7[$\mu\textrm{m}$] were fabricated by using the actual CMOS 1 [Mbit] process technology. The charateristics of I$\_$D/-V$\_$D/, I$\_$D/-V$\_$G/ were investigated and compared with the channel width and length. From the result of measuring the I$\_$D/-V$\_$D/ charges into the nitride layer by applying the gate voltage, these devices ere found to have a low conductance state with little drain current and a high conductance state with much drain current. It was shown that the devices of 15[$\mu\textrm{m}$]${\times}$15[$\mu\textrm{m}$] represented the long channel characteristics and the devices of 15[$\mu\textrm{m}$]${\times}$1.5[$\mu\textrm{m}$] and 1.9[$\mu\textrm{m}$]${\times}$1.7[$\mu\textrm{m}$] represented the short channel characteristics. In the characteristics of I$\_$D/-V$\_$D/, the critical threshold voltages of the devices were V$\_$w/ = +34[V] at t$\_$w/ = 50[sec] in the low conductance state, and the memory window sizes wee 6.3[V], 7.4[V] and 3.4[V] at the channel width and length of 15[$\mu\textrm{m}$]${\times}$15[$\mu\textrm{m}$], 15[$\mu\textrm{m}$]${\times}$1.5[$\mu\textrm{m}$], 1.9[$\mu\textrm{m}$]${\times}$1.7[$\mu\textrm{m}$], respectively. The positive logic conductive characteristics are suitable to the logic circuit designing.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.169-178
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• 2010

Agent based simulation is an approach for the analysis of a system's long term behavior where the entities in the system behave independently by their own judgement and memory, but influence each other to cope with given environment. In this paper we developed an agent based simulation model for the analysis of behavioral mechanism of team formation. In the process of team formation members' mutual preference is an important factor although each member can join up with one's own will. Also a team performance can vary by the member's own experience. We implemented the developed model using Netlogo 4.1, and verified the model by simulation. From the simulation results we found that the model successfully performed necessary functions using behavioral rules, judgments, and evolutionary processes by memory. As a further study we will be able to apply the model for analyzing various ecological behavior of team formation.

• 한국노년학
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• v.31 no.2
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• pp.401-417
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• 2011

The life review means a process of appraising life of oneself and it is essential for finding the meaning of life in old age. The memoir writing is a kind of method of life review. The memoir writing program used in this study focused especially on enhancing the cognitive skills by providing priming and retrieval support for memory performance in reminiscing past experiences. All fourteen participants were healthy and normal community dwellers and attended four-month long programof memoir writing classes which are consisted of different themes for each week. The aim of this study was to examine if the memoir writing program would render the positive effect on mental health and cognitive ability of the elderly. The results were that quality of life, life satisfaction, ego integrity of the participants showed positive change and the level of depression was significantly reduced compared to that of the control group. The findings in the present study suggest that the memoir writing can serve as one of the community initiative program to the growing population of the elderly for their emotional and cognitive challenges that they face everyday. To warrant the validity of the program, further study is needed for other sectors of elderly population, such as elderly living alone or those with both physical and/or cognitive disadvantages.

• Journal of the Korean Chemical Society
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• v.55 no.6
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• pp.1042-1055
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• 2011

The purpose of this study was to compare the conceptual and algorithmic problem solving ability on Boyle's law and Charles's law according to cognitive levels and characteristics of students in middle school 1st grade students. For this study, questionnaire items of conceptual and algorithmic problem solving ability were developed. and the problem solving ability according to cognitive levels and characteristics of students was compared. The long-term memory effect in conceptual and algorithmic problem solving ability according to cognitive levels was investigated, and problem solving process were analyzed by questionnaire items. In the results of this study, conceptual problem solving ability was higher than algorithmic problem solving ability in all cognitive levels. There was statistically significant difference in concrete operational period and transitional period students. In comparison of the long-term memory effect in conceptual and algorithmic problem solving ability, formal operational period students had the long-term memory effect. There was no statistically significant difference in the conceptual and algorithmic problem solving ability according to private education among the characteristics of students. But there was statistically significant difference in the problem solving ability according to experiences of the scientific activities and hopes to related scientific careers. From results of analysis of problem solving process, it is known that the students had a tendency to just remember macroscopic phenomena and to solve the problems without understanding the concepts. Therefore, teaching and learning strategy is necessary to replace unscientific concepts by the scientific concepts through identifying students's unscientific concepts in advance.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.387-396
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• 2009

The life and performance of lithium battery are greatly influenced by the formation process which is essential in the process of manufacture. Charge/discharge system for the lithium battery are required for the formation process. To simulate such a system in a conventional method takes very long time and requires huge memory space to save data files. So the simulation may be impossible with a general-purpose PC. In this paper, the lithium battery is modelled to a resistor-capacitor serial circuit and the lithium battery charge/discharge system is analyzed and simulated by using state space averaging method. As a result, the simulation time is reduced dramatically and the simulation of the lithium battery charge/discharge system becomes possible on a general-purpose PC within 3 hours. Also, both the charge/discharge characteristics and the time required to charge/discharge of the lithium battery charge/discharge system can be observed. To verify the propriety of resistor-capacitor serial circuit modeling method for lithium battery and the validity of the analysis and simulation based on state space averaging, the lithium battery charge/discharge system is composed and experimentations are carried out.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.150-150
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• 2023

기작기반의 역학적 모델과 자료기반의 딥러닝 모델은 수질예측에 다양하게 적용되고 있으나, 각각의 모델은 고유한 구조와 가정으로 인해 장·단점을 가지고 있다. 특히, 딥러닝 모델은 우수한 예측 성능에도 불구하고 훈련자료가 부족한 경우 오차와 과적합에 따른 분산(variance) 문제를 야기하며, 기작기반 모델과 달리 물리법칙이 결여된 예측 결과를 생산할 수 있다. 본 연구의 목적은 주요 상수원인 댐 저수지를 대상으로 수심별 수온과 탁도를 예측하기 위해 기작기반과 자료기반 모델의 장점을 융합한 PGDL(Process-Guided Deep Learninig) 모델을 개발하고, 물리적 법칙 만족도와 예측 성능을 평가하는데 있다. PGDL 모델 개발에 사용된 기작기반 및 자료기반 모델은 각각 CE-QUAL-W2와 순환 신경망 딥러닝 모델인 LSTM(Long Short-Term Memory) 모델이다. 각 모델은 2020년 1월부터 12월까지 소양강댐 댐 앞의 K-water 자동측정망 지점에서 실측한 수온과 탁도 자료를 이용하여 각각 보정하고 훈련하였다. 수온 및 탁도 예측을 위한 PGDL 모델의 주요 알고리즘은 LSTM 모델의 목적함수(또는 손실함수)에 실측값과 예측값의 오차항 이외에 역학적 모델의 에너지 및 질량 수지 항을 제약 조건에 추가하여 예측결과가 물리적 보존법칙을 만족하지 않는 경우 penalty를 부가하여 매개변수를 최적화시켰다. 또한, 자료 부족에 따른 LSTM 모델의 예측성능 저하 문제를 극복하기 위해 보정되지 않은 역학적 모델의 모의 결과를 모델의 훈련자료로 사용하는 pre-training 기법을 활용하여 실측자료 비율에 따른 모델의 예측성능을 평가하였다. 연구결과, PGDL 모델은 저수지 수온과 탁도 예측에 있어서 경계조건을 통한 에너지와 질량 변화와 저수지 내 수온 및 탁도 증감에 따른 공간적 에너지와 질량 변화의 일치도에 있어서 LSTM보다 우수하였다. 또한 역학적 모델 결과를 LSTM 모델의 훈련자료의 일부로 사용한 PGDL 모델은 적은 양의 실측자료를 사용하여도 CE-QUAL-W2와 LSTM 보다 우수한 예측 성능을 보였다. 연구결과는 다차원의 역학적 수리수질 모델과 자료기반 딥러닝 모델의 장점을 결합한 새로운 모델링 기술의 적용 가능성을 보여주며, 자료기반 모델의 훈련자료 부족에 따른 예측 성능 저하 문제를 극복하기 위해 역학적 모델이 유용하게 활용될 수 있음을 시사한다.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.39-48
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• 2002

long with the rapid spread of the Internet, a new class of commercial applications which process transactions with respect to electronic dictionaries become popular Typical examples are Internet search engines. In this paper, we present a new approach to achieving high performance electronic dictionaries. Different from the conventional approach which use Trie data structures for the implementation of electronic dictionaries, our approach used multi-dimensional binary trees. In this paper, we present the implementation of our electronic dictionary ED-MBT(Electronic Dictionary based on Multidimensional Binary Tree). Exhaustive performance study is also presented to assess the performance impact of ED-MBT on the real world applications.