• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.388-395
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• 2009

Surveillance Radar System for naval vessels is a primary core sensor for command and fire control, and provides CFCS(Command and Fire Control System) information for 3-D surveillance and fire control. It's composed of Antenna, Transmitter/Receiver, Signal Processor, and Air drier, which are installed on and under deck. They should be designed and produced in order to endure at any operating circumstances. This paper analyzes load of a driving part for driving the antenna considering factors under external operating circumstances, and proposes a condition of load for maintaining fixed RPM through analyzing internal load of the driving part, and how to reduce the load to meet the condition. This paper is verified through experimental studies.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.614-619
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• 2014

In WSN (Wireless Sensor Networks) based surveillance system, it needs to know the occurrence of events or objects and their locations, because the data have no meaning without location information. Using traditional 2D localization mechanisms provide good accuracy where altitude is fixed. But the mapping the position estimated by 2D localization to the real world can cause an error. Even though 3D localization mechanisms provide better accuracy than 2D localization, they need four reference nodes at least and high processing overhead. In our surveillance system, it is needed to estimate the height of the detected object in order to determine if the object is human. In this paper, we propose a height estimation mechanism which does not require many reference nodes and high complexity. Finally, we verify the performance of our proposed mechanism through various experiments.

• Journal of the Microelectronics and Packaging Society
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• v.6 no.1
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• pp.81-89
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• 1999

The fabrication process for miniaturizing the Electronic Article Surveillance (EAS) sensor was studied using micromachining technique. Two types of sensor structure, free standing membrane type and diving beard type, were proposed and researched for establishing the fabrication process. The membrane type structure was easy to change the sensor shape but had the limitation for miniaturizing, because the size of the sensor depends on the silicon substrate thickness. The diving board type structure has the advantage of miniaturization and of free motion. Since the elastic modulus is not trio high, SiN film is expected to be adequate for the supporting membrane of magnetic sensor. The selectivity of $H_2O_2$for sputtered W with respect to Fe-B-Si, which was studded for magnetic sensor materials, was high enough to be removed after using as a protection layer. Therefore, the diving board type process using the silicon nitride film for the supporter of the sensor material and the sputtered W for protection layer is expected to be useful fur miniaturizing the Electronic Article Surveillance (EAS) sensor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.699-701
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• 2010

For the development of surveillance Multi Sensor and IFOG, development of integrated surveillance camera for day and night time of its system Control Unit design and navigation device interlocking system was made. Control Unit analysis of integrated ship system began with selection of control unit related to feasible navigation device list.After sorting navigation equipment list, applications, features, connection methods, communication methods, data type of control unit and data direction between navigation equipments and the data types of each navigation equipment is sorted to observe its performance.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.237-246
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• 2013

Maintenance Access Hatches are used to ensure urban safety and aesthetics while facilitating the management of power lines, telecommunication lines, and gas pipes. Such facilities necessitate affordable and effective surveillance. In this paper, we propose a FiCHS (Fixed Cluster head centralized Hierarchical Static clustering) routing protocol that is suitable for underground maintenance hatches using WSN (Wireless Sensor Network) technology. FiCHS is compared with three other protocols, LEACH, LEACH-C, and a simplified LEACH, based on an ns-2 simulation. FiCHS was observed to exhibit the highest levels of power and data transfer efficiency.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.127-138
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• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.394-398
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• 2016

In this paper, a fire detection system based on quantitative risk estimation is presented. Multiple sensors are used to build a comprehensive indicator that represents the risk of fire quantitatively. The proposed fire risk estimation method consists of two stages which determines the occurrence of fire and estimates the toxicity of the surveillance area. In the first stage, fire is reliably detected under diverse fire scenarios. The risk of fire is estimated in the second stage. Applying Purser's Fractional Effective Dose (FED) model which quantitates harmfulness of toxic gases, the risk of the surveillance area and evacuation time are calculated. A fire experiment conducted using four different types of combustion materials for the verification of the system resulted in a maximum error rate of 12.5%. By using FED calculation and risk estimation methods, the proposed system can detect various signs of fire faster than conventional systems.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.45-47
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• 2009

Wireless Sensor Network(WSN) has been very popular in unattended surveillance systems recently. For Applying WSN into Building Automation system(BAS), a novel hierarchial network structure and static routing algorithm which eliminates the scalability limitation of Zigbee are proposed in this paper. The static routing algorithm relying on the hierarchial network address reduces the computational complexity to a great extent and has a real-time performance which satisfies urgent applications well.