• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.4
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• pp.400-403
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• 2008

In this work, an individual trespassing detector using a PIR sensor to detect infrared rays only between the range of $9.4{\sim}10.4{\mu}m$ radiated from the body is proposed. This detector using FIR sensor detects not insect or object but human body, It doesn't restrict the inhabitant's behavior because the filter of pm sensor is designed to have face angle and the detector only detects the window area. The existing wide angle filter, RIR sensor, detects $30^{\circ}$ angle while the face angle filter sensor on this paper detects $11^{\circ}$ angle with 3cm of face angle filter from 2m of detecting distance. In case of interruption of electric power, 250mAh of lithium-ion battery has worked for 10 hours consuming 22mA in normal state. Meanwhile, in case of interruption of electric power, 250mAh of battery has worked for 4 hours consuming 60mA in trespassing detecting state. Projector, receptor, controller and alarm are put on one PCB in order to make it convenient to install without any special installation skill.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2161-2166
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• 2015

This paper analyzes the straight line detection using the principal component analysis (PCA) and proposes its improved algorithm to which two new functions are added. The first function removes invalid pixels through the detected straight line and detects a line again. The second function detects lines from non-overlapped blocks, selects valid line candidates, and detects a valid line from pixels adjacent to each line candidate. The proposed algorithm detects a more accurate straight line with a low computation in comparison with the conventional algorithm in an image with somewhat refined lines.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.229-232
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• 2002

This paper describes the development of robot's finger 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously fur stably grasping an unknown object. In order to safely grasp an unknown object using the robot's fingers, they should detect the force of gripping direction and the force of gravity direction, and perform the force control using the detected farces. The 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously should be used for accurately detecting the weight of an unknown object of gravity direction. Thus, in this paper, robot's finger for stably grasping an unknown object is developed. And, the 3-axis farce sensor that detects the Fx, Fy, and Fz simultaneously fur constructing a robot's finger is newly modeled using several parallel-plate beams, and is fabricated. Also, it is calibrated, and evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.539-542
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• 2005

This paper contains studies which are Cruise speed control which is made by PID algorithm and automated steering system for avoiding the obstacle coming from the front which is using Fuzzy algorithm. This mobile car uses DC motor whose speed is detected by encoder. Ultrasonic Waves Sensor established in the front detects the obstacle and the curve. And the sensor established in the side detects the distance of the space of the road. If the sensor detects the obstacle or the curve, the car is controlled by using Fuzzy algorithm. The Fuzzy algorithm calculates the speed and steering angle by using the value which is obtained from sensor.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.3
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• pp.11-22
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• 1997

This paper presents the design and implementation of an efficient algorithm for detecting untestable paths in multi-level circuits. Transforming multi-level circuit into a multiplexor-based one through BDD(binary decision diagram)construction, the proposed algorithm detects untestable paths in the transformed circuits. By constructing ENF (equivalent normal form) only for reconvergent paths, the proposed system detects and removes untestable paths efficiently in terms of the run-time and memory usage. Experimental results for MCNC/ISCAS benchmark circuits show that the system efficiently detects and removes untestable paths. The run-time and memory usage have been reduced by 37.7% and 60/9%, respectively, comapred to the previous methods.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.202-205
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• 2000

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.223-226
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• 2000

In this paper, we report detects system algorithm, adapted a perimetric mask and a generalized symmetry system, to detect a transformable material and find out a minute error cannot be noticed by a naked eye. In this thesis, supposed a stable detecting system applied a general image processing theory and perimetric mash algorithm to detect badness. And finally, detected some vague errors with the application of symmetry transform algorithm that accumulate a symmetry of minute error and put stress on it.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.178-184
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• 2016

This paper proposes a new path-finding scheme using viewpoint-invariant landmarks. The scheme introduces the concept of landmark detection in images captured with a vision sensor attached to a mobile robot, and provides landmark clues to determine a path. Experiment results show that the scheme efficiently detects landmarks with changes in scenes due to the robot's movement. The scheme accurately detects landmarks and reduces the overall landmark computation cost. The robot moves in the room to capture different images. It can efficiently detect landmarks in the room from different viewpoints of each scene. The outcome of the proposed scheme results in accurate and obstacle-free path estimation.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.128-132
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• 2007

Thermal Imaging systems are reported to be crucial for fire fighting and beginning to be used by fire fighters. The performance of thermal imaging system is determined by both the radiation of infrared from the target and the attenuation of infrared signal in the optical path by the absorption, scattering, diffraction and reflection. In the scene of fire, water drops with various sizes such as vaporized water, wafer mist from sprinkler, and wafer to suppress the fire reside with various gas generated by burning. To measure the transmission of infrared radiation in the scene of fire, fire simulating system and thermal imagers with cooled detector which detects $3{\sim}5{\mu}m$ infrared and uncooled detector fabricated by the MEMS technology which detects $8{\sim}12{\mu}m$ infrared. are made. With thermal imagers and Ire simulating system, the change of thermal image with respect to the change of visibility controlled with the burned fas was measured. It was found that the transmission of infrared was not reduced by the burned gas, which could be explained by the long wavelength of infrared ray compared with visible ray. However, the transmission of infrared ray was largely reduced by the combination of burned gas and water mist supplied by sprinkler. This is contrary to the results of calculated transmission through the pure water mist and shows that the transmission of infrared ray is mostly affected by the compounds of water mist and burned gas. In this case, it was found that the uncooled detector which detects $8{\sim}12{\mu}m$ infrared ray is better than cooled detector which detects $3{\sim}5{\mu}m$ infrared ray for fire fighting.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.137-142
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• 2021

Although the internet has gained many conveniences and benefits, it is causing economic and social damage to users due to intelligent malware. Most of the signature-based anti-virus programs are used to detect and defend this, but it is insufficient to prevent malware variants becoming more intelligent. Therefore, we proposes a model that detects and defends the intelligent malware that is pouring out in the paper. The proposed model learns by imaging the characteristics of malware based on deeplearning, and detects newly detected malware variants using the learned model. It was shown that the proposed model detects not only the existing malware but also most of the variants that transform the existing malware.