• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.291-298
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• 2012

In automatic target recognition(ATR) systems, target extraction techniques are very important because ATR performance depends on segmentation result. So, this paper proposes a multi-sensor image fusion method based on adaptive weights. To incorporate the FLIR image and CCD image, we used information such as the bi-modality, distance and texture. A weight of the FLIR image is derived from the bi-modality and distance measure. For the weight of CCD image, the information that the target's texture is more uniform than the background region is used. The proposed algorithm is applied to many images and its performance is compared with the segmentation result using the single image. Experimental results show that the proposed method has the accurate extraction performance.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.510-517
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• 2015

For the self-directed rehabilitation of upper extremity hemiplegia patients, in this paper we propose an interface method capable of doing bilateral exercises in rehabilitation robotics. This is a method for estimating information of movements from the unaffected-side, and projects it to the affected-side in order. That the affected-side is followed the movements of the unaffected-side. For estimation of the unaffected-side movements information, gyro sensor data and acceleration sensor data were fused. In order to improve the measurement error in data fusion, a HDR filter and a complementary filter were applied. Estimated motion information is derived the one side of the drive input of rehabilitation robot. In order to validate the proposed method, experimental equipment is designed to be similar to the body's joints. The verification was performed by comparing the estimation angle data from inertial sensors and the encoder data which were attached to the mechanism.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.703-713
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• 2004

This paper presents the new obstacle avoidance method that is composed of vision and sonar sensors, also a navigation algorithm is proposed. Sonar sensors provide poor information because the angular resolution of each sonar sensor is not exact. So they are not suitable to detect relative direction of obstacles. In addition, it is not easy to detect the obstacle by vision sensors because of an image disturbance. In This paper, the new obstacle direction measurement method that is composed of sonar sensors for exact distance information and vision sensors for abundance information. The modified splitting/merging algorithm is proposed, and it is robuster for an image disturbance than the edge detecting algorithm, and it is efficient for grouping of the obstacle. In order to verify our proposed algorithm, we compare the proposed algorithm with the edge detecting algorithm via experiments. The direction of obstacle and the relative distance are used for the inputs of the fuzzy controller. We design the angular velocity controllers for obstacle avoidance and for navigation to center in corridor, respectively. In order to verify stability and effectiveness of our proposed method, it is apply to a vision and sonar based mobile robot navigation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.811-819
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• 2014

Activity recognition is a key component in identifying the context of a user for providing services based on the application such as medical, entertainment and tactical scenarios. Instead of applying numerous sensor devices, as observed in many previous investigations, we are proposing the use of smartphone with its built-in multimodal sensors as an unobtrusive sensor device for recognition of six physical daily activities. As an improvement to previous works, accelerometer, gyroscope and magnetometer data are fused to recognize activities more reliably. The evaluation indicates that the IBK classifier using window size of 2s with 50% overlapping yields the highest accuracy (i.e., up to 99.33%). To achieve this peak accuracy, simple time-domain and frequency-domain features were extracted from raw sensor data of the smartphone.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.224-232
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• 2003

In this paper, efficient deployment method of sensors and target positioning performance with respect to measurement error are dealt with. Active sonar can be categorized into Monostatic, Bistatic, Multistatic sonar, and characteristics of respective sonar are different. Assuming that each sensor can receive range and angular information, we compare the performance of Monostatic, Bistatic, and Multistatic systems. And we suggest Weighted least square (WLS) which gives the weight to former case, LS. In particular. adopting suggested method we investigate the target positioning performance according to number of sensor, distance from transmitter to receiver, and propose efficient arrangement rule for Multistatic sonar configurations. According to the experimental results, RMSE of Multistatic sonar is found to be superior to Monostatic and Bistatic by 35.98%. 37.45% respectively, and WLS is superior to LS approximately by 7.4% in average. Furthermore, as the difference of respective sensor's variance is large, it is observed that the improvement ratio of target positioning performance is increased.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2143-2148
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• 2016

Recently due to development of IT technology, ideas and technology that blend with environment have evolved. This technology can help people's living environment and in the future it is an essential component of the connected society. In this paper, we propose WiT(WiFI Trashcan) which takes advantage of the IT technology fusion and environmental factors at the same time to create a more pleasant environment. WiT provides a free WiFi when trash is disposed in the trash can. WiT detects whether a user disposes trash, determines the volume of the trash and provides free WiFi. To detect trash we use ultrasonic sensor and trash weight is measured by using weight sensor. Also by using Phython programming the measured sensor value is transmitted to Raspberry Pie and WiFi delivery time is determined. We used Arduino and Raspberry Pi to design and implement WiT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.362-364
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• 2011

To build ubiquitous agriculture environment successfully, development of core technology for agriculture, such as sensor node H/W, sensor node middleware platform, routing protocol and agricultural environment application service is essential. With the application of u-IT technologies to traditional agriculture area, fusion complex technologies become a source to raise value-added agriculture product and its productivity. However, it is imperative to expand horticulture industry area and improve infrastructure for utility-based horticulture. This paper proposes an agriculture product growth environment management system that utilizes environmental factor monitoring sensors and biological information sensors in greenhouse to specifically manage botany growth environment management.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.273-280
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• 2008

In WSN(Wireless Sensor Network) many routing algorithms such as LEACH, PEGASIS and PEDEP consisting of sensor nodes with limited energy have been proposed to extend WSN lifetime. Under the assumption of perfect fusion, these algorithms used convergecast that periodically collects sensed data from all sensor nodes to a base station. But because these schemes studied less energy consumption for a convergecast as well as fairly energy consumption altogether, the minimum energy consumption for a convergecast was not focused enough nor how topology influences to energy consumption. This paper deals with routing topology and energy consumption for a single convergecast in the following ways. We chose major WSN topology as MSC(Minimum Spanning Chain)s, MSTs, PEGASIS chains and proposed LECSEN chains. We solved the MSC length by Linear Programming(LP) and propose the LECSEN chain to compete with MST and MSC. As a result of simulation by Monte Carlo method for calculation of the topology length and standard deviation of link length, we learned that LECSEN is competitive with MST in terms of total energy consumption and shows the best with the view of even energy consumption at the sensor nodes. Thus, we concluded LECSEN is a very useful routing topology in WSN.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.9-16
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• 2011

Due to the development and proliferation of ubiquitous technologies and services, various sensor network applications are being appeared on the stage. The needs for algorithms requiring sensor data fusion and complex signal processing with a high-performance processor such as a digital signal processor are also increased. However, it is difficult to use such processor for the low-power sensor network operating with a battery because of power consumption. This paper proposes a hybrid-type sensor module architecture supporting wakeup/sleep software framework for the wireless sensor node and shows the implemented sensor node platform and performances focused on the energy consumption and wakeup time.