• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.31-40
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• 2016

Wireless sensor networks have been used in many applications such as marine environment, army installation, etc. The sensor data is very important, because all these applications depend on sensor data. The possibility of communication failures becomes high since the surrounding environment of a wireless sense network has an sensitive effect on its communications. In particular, communication failures in underwater communications occur more frequently because of a narrow bandwidth, slow transmission speed, noises from the surrounding environments and so on. In cases of communication failures, the sensor data can be lost in the sensor data delivery process and these kinds of sensor data losses can make critical huge physical damages on human or environments in applications such as fire surveillance systems. For this reason, although a few of studies for storing and compressing sensor data have been proposed, there are lots of difficulties in actual realization of the studies due to none-existence of the framework using network communications. In this paper, we propose a framework for reducing loss of the sensor data and analyze its performance. The our analyzed results in non-framework application show a decreasing data recovery rate, T/t, as t time passes after a network failure, where T is a time period to fill the storage with sensor data after the network failure. Moreover, all the sensor data generated after a network failure are the errors impossible to recover. But, on the other hand, the analyzed results in framework application show 100% data recovery rate with 2~6% data error rate after data recovery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1295-1304
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• 2010

This paper proposes a fault-tolerant data aggregation which provides energy efficient and reliable data collection in wireless sensor networks. The traditional aggregation scheme does not provide the countermeasure to packet loss or the countermeasure scheme requires a large amount of energy. The proposed scheme applies caching and re-transmission based on the track topology to the adaptive timeout scheduling. The proposed scheme uses a single-path routing based on the traditional tree topology at normal, which reduces the dissipated energy in sensor nodes without any countermeasure against packet loss. The proposed scheme, however, retransmits the lost packet using track topology under event occurrences in order to fulfill more accurate data aggregation. Extensive simulation work under various workloads has revealed that the proposed scheme decrease by 8% in terms of the dissipated energy and enhances data accuracy 41% when the potential of event occurrence exists as compared with TAG data aggregation. And the proposed scheme decrease by 53% in terms of the dissipated energy and shows a similar performance in data accuracy when the potential of event occurrence exists as compared with PERLA data aggregation.

• ETRI Journal
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• v.39 no.3
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• pp.345-352
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• 2017

Traffic management is a highly beneficial mechanism for satisfying quality-of-service requirements and overcoming the resource scarcity problems in networks. This paper introduces an optimal connection admission control mechanism to decrease the packet loss ratio and end-to-end delay in cognitive radio sensor networks (CRSNs). This mechanism admits data flows based on the value of information sent by the sensor nodes, the network state, and the estimated required resources of the data flows. The number of required channels of each data flow is estimated using a proposed formula that is inspired by a graph coloring approach. The proposed admission control mechanism is formulated as a semi-Markov decision process and a linear programming problem is derived to obtain the optimal admission control policy for obtaining the maximum reward. Simulation results demonstrate that the proposed mechanism outperforms a recently proposed admission control mechanism in CRSNs.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.5
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• pp.278-285
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• 2006

A micro hotplate for micro gas sensor was fabricated by MEMS technology. In order to heat up the gas sensing material to a target temperature, a micro hotplate was built on the gas sensor. The sensing material was deposited on the heater and electrodes, and did not contact with the silicon base to minimize the heat loss to the silicon base. The electric power to heat up the gas sensor was measured. The temperature distribution of micro gas sensor was analyzed by a CFD program. The predicted electric power to heat up th sensing material showed a good agreement with the measured data. The design of micro gas sensor could be modified to increase the temperature uniformity and to decrease the electric power consumption by optimizing the layout of micro hotplate and electrodes.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.293-298
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• 2023

The military is facing a continuous decrease in personnel, and in order to cope with potential accidents and challenges in operations, efforts are being made to reduce the direct involvement of personnel by utilizing the latest technologies. Recently, the use of various sensors related to Manned-Unmanned Teaming and artificial intelligence technologies has gained attention, emphasizing the need for flexible utilization methods. In this paper, we propose four dataset construction methods that can be used for effective training of robots that can be deployed in military operations, utilizing not only RGB image data but also data acquired from IR image sensors. Since there is no publicly available dataset that combines RGB and IR image data, we directly acquired the dataset within buildings. The input values were constructed by combining RGB and IR image sensor data, taking into account the field of view, resolution, and channel values of both sensors. We compared the proposed method with conventional RGB image data classification training using the same learning model. By employing the proposed image data fusion method, we observed improved stability in training loss and approximately 3% higher accuracy.

• Journal of IKEEE
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• v.23 no.1
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• pp.22-28
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• 2019

This paper presents the monitoring method of machining error and quality check to improve the productivity of boring manufacturing process. Machining error usually appears as the offset of spatial location of actual cutting path compared to ideal cutting path. In order to monitor an error of workpiece, multiple factors affecting quality of boring, such as distortion of workpiece, clamping error, radial rotation error of the spindle and motion error of machine tools, were took into account. To verify the productive quality, we propose the quality check system. The system based on IT convergence analyzes the process error rate and saves the analyzed data in memory. Also, these play important roles in detecting an inferior production goods and can decrease the production cost and loss of bearing.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1166-1178
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• 2016

In Internet of Things (IoT) environments, billions of interconnected devices and multimedia sensors generate a huge amount of multimedia traffic. Since the environment are in general deployed as a server-centric architecture wireless sensor networks could be bottlenecks between IoT gateways and IoT devices. The bottleneck causes high power consumption of the device and triggers very heavy network overload by transmission of sensing data. The deterioration could decrease the quality of multimedia streaming service due to delay, loss, and waste of device power. Thus, in this paper, we propose a context-based adaptive multimedia streaming scheme to support enhanced QoS and low power consumption in IoT environments. The goal of the scheme is to increase quality score per voltage of the streaming service, given an adaptation algorithm with context that are classified network and hardware such as throughput, RTT, and CPU usage. From the both context, the quality score per voltage is used in the comparison of a only network context-based adaptive multimedia streaming scheme, a fixed multimedia streaming and our scheme. As a result, we achieves a high improvement that means the quality score per voltage is increased up to about 4, especially in case of resolution change.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.197-211
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• 2007

The power of semiconductor, Korea is continuously constructing semiconductor production line for keeping a front-runner status. however, studies and data about potential risks in semiconductor factory are still short. If fire does not initially suppressed, the fire causes a great damage. To decrease fire risk factors, in addition to fire fighting safety equipment, more important thing is how to design and construct fire protection system. The current fire protection codes about semiconductor factory come under functional law, and this law is short of consideration about particularity of factory. The existing prescriptive fire codes depending on experience compose without evident engineering verifications, thus equipments which is created by the current prescriptive fire code may bring about a variety of problems. For example, the design under the current regulation can not cope with the excessive investments, low efficiencies, and the diversifying construction designs and be applied to the quick changes of new technologies. Ergo, an optimal design for fire protection is to equip fire protection arrangements with condition and environment of production field. Manufacturing factory of semiconductors is a windowless airtight space. And for cleanliness, there exists strong flow of cooperation. Therefore, there is a need for fire safety design that meets the characteristic of a clean room. Accordingly, we are to derive smoke flow according to cooperation process within a clean room and construction plan of an optimal sensor system. In this study, in order to confirm the performance of proposed smoke-exhaust equipment and suggest efficient smoke exhaust device when there is a fire of 1MW of methane in the clean room of company H, we have implemented fire simulation using fluid dynamics computation.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.423-434
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• 2009

The Arctic environment is sensitive to change of sea-ice distribution. The increase and decrease of sea ice work to an index of globe warming progress. In order to predict the progress of hereafter earth global warming, continuous monitoring regarding a change of the sea ice area in the Arctic should be performed. The remote sensing based on an artificial satellite is most effective on the North Pole. The sea ice observation using a passive microwave sensor has been continued from 1970's. The determination of sea ice extent and ice type is one of the great successes of the passive microwave imagers. In this paper, to investigate the seasonal and inter-annual variation of sea-ice distribution we used here the sea ice data from July 2002 to May 2009 around the Arctic within $60^{\circ}N$ for the AMSR-E 12.5km sea-ice concentration, a passive microwave sensor. From an early analysis of these data, the arctic sea-ice extent has been steadily decreasing at a rate of about 3.1%, accounting for about $2{\times}10^5\;km^2$, which was calculated for the sea-ice cover reaching its minimum extent at the end of each summer. It is also revealed that this trend corresponds to a decline in the multi-year ice that is affected mainly by summer sea surface and air temperature increases. The extent of younger and thinner (first-year) ice decreased to the 2007 minimum, but rapidly recovered in 2008 and 2009 due to the dramatic loss in 2007. Seasonal variations of the sea-ice extent show significant year-to-year variation in the seasons of January-March in the Barents and Labrador seas and August-October in the region from the East Siberian and Chukchi seas to the North Pole. The spatial distribution of multi-year ice (7-year old) indicates that the perennial ice fraction has rapidly shrunk recently out of the East Siberian, Laptev, and Kara seas to the high region of the Arctic within the last seven years and the Northeast Passage could become open year-round in near future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.344-352
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• 2019

Drought stress caused by global climate change is a serious problem for rice cultivation. Increasingly frequent abnormal weather occurrences could include severe drought, which could cause water stress to rice during the seedling stage. This experiment was conducted to clarify the effects of drought during the seedling period on yield and quality of rice. Drought conditions were created in a rain shelter house facility. The drought treatment was conducted at 3, 10, and 20 days after transplanting. Soil water content was measured by a soil moisture sensor during the whole growth stage. In this study, we have chosen 3 rice cultivars which are widely cultivated in Korea: 'Haedamssal' (Early maturing), 'Samkwang' (Medium maturing), and 'Saenuri' (Mid-late maturing). The decrease in yield due to drought treatment was most severe 3 days after transplanting because of the decrease in the number of effective tillers. The decrease in grain quality due to drought treatment was also most severe 3 days after transplanting because of the increased protein content and hardness of the grains. The cultivar 'Haedamssal' was the most severely damaged by water stress, resulting in about a 30% yield loss. Drought conditions diminished the early vigorous growth period and days to heading in early-maturing cultivars. The results show that drought stress affects yield components immediately after transplanting, which is a decisive factor in reducing yield and grain quality. This study can be used as basic data to calculate damage compensation for drought damage on actual rice farms.