• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.137-137
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• 2010

Copper electroplating is a very popular and important technology for depositing high-quality conductor interconnections, especially in through silicon via (TSV). As this advanced packaging technique developing, a mass of copper and chemical solution are used, so attention to these chemical materials into the utilization and costs can not be ignored. An economical and practical real-time chemical solution monitoring has not been achieved yet. Either Red-green-blue (RGB) or optical emission spectroscopy (OES) color sensor can successfully monitor the color condition of solution during the process. The reaction rate, uniformity and quality can map onto the color changing. Hidden Semi Markov model (HSMM) can establish mapping from the color change to upper indicators, and artificial neural network (ANN) can be integrated to comprehensively determine its targets, whether the solution inside the container can continue to use.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.563-572
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• 2002

Wireless mobile networks tend to drop a large portion of packets due to propagation errors rather than congestion. To Improve reliability over noisy wireless channels, wireless networks can employ forward error correction (FEC) techniques. Static FEC algorithms, however, can degrade the performance by poorly matching their overhead to the degree of the underlying channel error, especially when the channel path loss rate fluctuates widely. This paper investigates the benefits of an adaptable FEC mechanism for wireless networks with severe packet loss by analytical analysis or measurements over a real wireless network called sensor network. We show that our adaptive FEC named FECA (FEC-level Adaptation) technique improves the performance by dynamically tuning FEC strength to the current amount of wireless channel loss. We quantify these benefits through a hybrid simulation integrating packet-level simulation with bit-level details and validate that FECA keeps selecting the appropriate FEC-level for a constantly changing wireless channel.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.863-866
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• 2010

무선 센서 네트워크의 규모가 커짐에 따라 대규모의 센서 네트워크의 활용에 대한 기대가 커지고 있다. 기존 IEEE 802.15.4 를 이용한 네트워크의 규모에 따른 한계를 극복하기 위해 듀얼 라디오 센서 네트워크에 대한 많은 연구가 진행되고 있다. 듀얼 라디오 센서 네트워크는 단일 라디오를 내장한 전통적인 센서 노드(싱글 라디오 노드)에 듀얼 라디오 인터페이스(IEEE 802.11g, IEEE 802.15.4)를 내장한 센서(듀얼 라디오 노드)를 포함하여 클러스터를 구성한다. 본 논문에서는 이러한 듀얼 라디오 환경에서 효과적으로 동작하는 라우팅 프로토콜을 제안한다. 듀얼 라디오 노드는 네트워크 상에서 클러스터 헤드 역할을 하고 상위 계층을 이루며, 일반 노드는 클러스터 멤버 역할을 하는 하위 계층을 이룬다. 본 논문에서는 각 계층의 네트워크가 나타내는 특징을 이동성이 적거나 높은 네트워크의 특징으로 대입하여, 상위 계층에는 Pro-Active 프로토콜, 하위 계층에는 Re-active 프로토콜이 효과적임을 설명한다. 이를 바탕으로 듀얼 라디오 센서 네트워크에 적합한 라우팅 프로토콜로써 Pro-Active 프로토콜을 대표하는 DSDV 와 Re-Active 프로토콜을 대표하는 AODV 를 조합한 하이브리드 라우팅 프로토콜을 제안한다. 제안한 프로토콜의 성능을 확인하기 위해 센서네트워크 테스트베드를 구성하여 라우팅 복구 시간과 패킷 전송 안정성에 대한 성능을 입증한다.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.105-116
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• 2011

With recent spotlight on the, uniquitous computing technology, the need for object of indentification and location infrastructure has increased. Such GPS technolgy must utilize IEEE 802.15.4 Zigbee used for existing wireless sensor network infra as a basice element for user's context-awareness in a uniquitous environement, for effectiveness.Such real-time GPS service is provided in the internal environment where the user would actually are and most high-rise buildlings apply. Underthe assumption, the real-time GPS technology is seperated by each floor, and signals do not get transmitted to other floors, the application on one floor within the high-rise buildling was conducted. This study intends to suggest a floor detection algorithm using IEE 802.15.3/Zigbee's RSSI which supports the accuracy within a couple of meters for the user's the movement between the floors in high-rise buildings in a complex environment. It proposes an floor detection algorithm using IEEE 802.15.4/Zigbee's RSSI which provides accuracy within a radius of few meters for the users movement between the floors for real-time location tracking within high-rise building in a cmoplex environment. Furthermore, for more accurate real-time location tracking, it suggests an algorithm for real-time location tracking using IEEE 802.15.4a/Zigbee's CSS technology based on triangulation. Based on the suggested algorithm, it designs a hybrid real-time location tracking service system in a high-rise buildling and test its functions.

• Journal of KIISE
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• v.42 no.3
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• pp.320-327
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• 2015

Although service robots in various fields are being commercialized, most of them have problems that depend on explicit commands by users and have difficulty to generate robust reactions of the robot in the unstable condition using insufficient sensor data. To solve these problems, we modeled mirror neuron and theory of mind systems, and applied them to a robot agent to show the usefulness. In order to implement quick and intuitive response of the mirror neuron, the proposed intention-response model utilized behavior selection networks considering external stimuli and a goal, and in order to perform reactions based on the long-term action plan of theory of mind system, we planned behaviors of the sub-goal unit using a hierarchical task network planning, and controled behavior selection network modules. Experiments with various scenarios revealed that appropriate reactions were generated according to external stimuli.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1373-1392
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• 2015

Placing sensors at appropriate locations is an important task in the design of an efficient structural health monitoring (SHM) system for a large-scale civil structure. In this paper, a hybrid optimization algorithm called virus monkey algorithm (VMA) based on the virus theory of evolution is proposed to seek the optimal placement of sensors. Firstly, the dual-structure coding method is adopted instead of binary coding method to code the solution. Then, the VMA is designed to incorporate two populations, a monkey population and a virus population, enabling the horizontal propagation between the monkey and virus individuals and the vertical inheritance of monkey's position information from the previous to following position. Correspondingly, the monkey population in this paper is divided into the superior and inferior monkey populations, and the virus population is divided into the serious and slight virus populations. The serious virus is used to infect the inferior monkey to make it escape from the local optima, while the slight virus is adopted to infect the superior monkey to let it find a better result in the nearby area. This kind of novel virus infection operator enables the coevolution of monkey and virus populations. Finally, the effectiveness of the proposed VMA is demonstrated by designing the sensor network of the Canton Tower, the tallest TV Tower in China. Results show that innovations in the VMA proposed in this paper can improve the convergence of algorithm compared with the original monkey algorithm (MA).

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.1-8
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• 2016

Current sensors are used widely in the fields of current control, monitoring, and measuring. They have become more popular with the increasing demand for smart grids in a power network, generation of renewable energy, electric cars, and hybrid cars. Although open loop Hall effect current sensors have merits, such as low cost, small size, and weight, they have low accuracy. This paper describes the design and fabrication of a 300A open loop current sensor that has high accuracy and temperature performance. The core of the current sensor was calculated numerically and the signal conditioning circuits were designed using circuit analysis software. The characteristics of the manufactured open loop current sensor of 300 A class was measured at currents up to 300 A. According to the test of the current sensor, the accuracy error and linearity error were 0.75% and 0.19%, respectively. When the temperature compensation was carried out with the relevant circuit, the temperature coefficients were less than $0.012%/^{\circ}C$ at temperatures between $-25^{\circ}C$ and $85^{\circ}C$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1004-1013
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• 2012

The legacy voice broadcast systems are used to broadcast the voice over an entire space or a specific zone. these broadcast systems generate unnecessary noise and waste of resources. In this paper, we propose a ubiquitous voice message broadcast system called uPaging, by combining the technique of location-awareness and the voice message delivery service in ubiquitous sensor network environment. In uPaging system, the wire/wireless hybrid network is used to implement the network system. Also, in order to actualize the location-awareness service, we use the Bidirectional Location ID-Exchange protocol was suggested by our previous research. the uPaging system can deliver the voice to a selected user or the location in which the user is present by this location awareness.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.6
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• pp.758-766
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• 2017

In this paper, we propose a robust duality of CNN(Du-CNN) method which can classify the target and clutter in coastal environment for IR Imaging Sensor. In coastal environment, there are various clutter that have many similarities with real target due to diverse change of air temperature, water temperature, weather and season. Also, real target have various feature due to the same reason. Thus, the proposed Du-CNN method adopts human's multiple personality utilization and CNN technique to learn and classify target and clutter. This method has an advantage of the real time operation. Experimental results on sampled dataset of real infrared target and clutter demonstrate that the proposed method have better success rate to classify the target and clutter than general CNN method.