• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.14-15
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• 2005

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.1
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• pp.9-16
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• 2005

A series of experiments was conducted to evaluate the effects of temperature on the survival, growth and sensitivity of the benthic amphipods, Mandibuluphoxus mai and Monocnrophium acherusicum, which have been recently developed as new sediment toxicity testing species in Korea. The biological performance for each amphipod species was determined by the survival and growth rates at different water temperatures. The influence of temperature on the sensitivity to reference toxicant, Cd, was determined by the comparison of survival rates of amphipods exposed to control and Cd-spiked seawater at different temperatures. Temperature significantly influenced on the survival, growth and Cd sensitivity of both amphipods. Tolerable ranges of temperature for the >80％ individuals of both M. mai and M. acherusicum with sediment substrates were mostly overlapped (13 to 22℃). The daily growth rates of M. mai and M. acherkisicum increased proportionally with temperature up to 20℃ and 25℃. respectively. Similarly, the sensitivities of M. mai and M. acheyusicum to Cd increased with temperature up to 20℃ and 15℃, respectively. Overall results showed that temperature is a substantially important factor potentially influencing the results of lethal and sublethal bioassays using the amphipods. Therefore, defining the adequate ranges of experimental temperature for the toxicity testing species is the pre-requisite for the development of standardized bioassay protocols.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.690-693
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• 2002

According to the growth of communication biz, embedded market rapidly developing in domestic and overseas. Embedded system can be used in various way such as wire and wireless communication equipment or information products. There are lots of developing performance applying speech recognition to embedded system, for instance, PDA, PCS, CDMA-2000 or IMT-2000. This study implement minimum memory of speech recognition engine and DB for apply real time embedded system. The implement measure of speech recognition equipment to fit on embedded system is like following. At first, DC element is removed from Input voice and then a compensation of high frequency was achieved by pre-emphasis with coefficients value, 0.97 and constitute division data as same size as 256 sample by lapped shift method. Through by Levinson - Durbin Algorithm, these data can get linear predictive coefficient and again, using Cepstrum - Transformer attain feature vectors. During HMM training, We used Baum-Welch reestimation Algorithm for each words training and can get the recognition result from executed likelihood method on each words. The used speech data is using 40 speech command data and 10 digits extracted form each 15 of male and female speaker spoken menu control command of Embedded system. Since, in many times, ARM CPU is adopted in embedded system, it's peformed porting the speech recognition engine on ARM core evaluation board. And do the recognition test with select set 1 and set 3 parameter that has good recognition rate on commander and no digit after the several tests using by 5 proposal recognition parameter sets. The recognition engine of recognition rate shows 95%, speech commander recognizer shows 96% and digits recognizer shows 94%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.