• Environmental Analysis Health and Toxicology
• /
• v.25 no.3
• /
• pp.223-228
• /
• 2010

Neocaridina denticulata is a small freshwater shrimp indigenous to Korea. As an indigenous species has long-adapted to particular water environments, the species can be a suitable indicator to assess environmental risks caused by hazard chemicals in the particular site. Thus Neocaridina denticulata, a small freshwater shrimp indigenous to Korea, is worth considering for a test species for such purpose. N. denticulata were exposed to pentachlorophenol sodium salt, sodium azide and potassium dichromate using automatic flow-through system for 96 hours. The 96 hr lethal concentrations ($LC_{50}$) of these chemicals were calculated as $0.53{\pm}0.09\;mg/L$, $2.40{\pm}0.61\;mg/L$ and $1.21{\pm}0.09\;mg/L$ respectively and showed relatively small deviation from repetitive test results. When compared with the toxicity values of other species for each chemical, N. denticulata had moderate or high sensitivity to the toxicity of these chemicals. It can be concluded that N. denticulata is a good test species to evaluate acute toxicity of various hazardous chemicals.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.16 no.5
• /
• pp.494-502
• /
• 2011

Bimodal tram is designed to run on a dedicated path in automatic mode using a magnetic track system in order to realize a combination of the accessibility of a bus and the constant regularity of a railroad. This paper presents design and test results of the series hybrid propulsion system of the bimodal tram on both test track and public road, which uses CNG (Compressed Natural Gas) engine and Lithium polymer battery pack. This paper describes the real-time data measuring equipment for the series hybrid propulsion system of the bimodal tram. Using this measurement equipment, the performance of the prototype vehicle's driving on test track and public road was verified and the fuel consumption and the efficiency of CNG engine have been investigated.

• Korean Journal of Clinical Laboratory Science
• /
• v.43 no.1
• /
• pp.1-5
• /
• 2011

The infection rate of syphilis is still increasing in the world especially in developing countries and the infection is often seen in large amounts of clinical specimens. For the diagnosis of this disease, Rapid Plasma Reagin (RPR)/Venereal Disease Research Laboratory (VDRL) has still been used as one of major primary methods to diagnose syphilis even though the test readings are somewhat subjective with high false positive rates. Recently, the automatic ARCHITECT Syphilis TP, which is based on the detection of the TP-specific antibodies, has been introduced in many laboratories. Therefore, the clinical assessment of the method is needed to provide primary diagnosis of syphilis at the moment. We evaluated 3 different manual rapid kits and ARCHITECT Syphilis TP comparing with RPR/FTA-ABS and analysed their diagnostic properties. From February 2006 to April 2008, 203 positive and 250 negative specimens, obtained from Chungbuk National University Hospital were used for the evaluation. In the evaluation between manual rapid kits, their specificities were as high as 99.2 ~ 99.6% while their sensitivities were observed with little differences; 98.0% (199/203) for Kit A, 96.6% (196/203) for Kit B, and 97.4% (197/203) for Kit S. In the case of ARCHITECT Syphilis TP test, it showed 100% specificity (250/250) and 98.5% sensitivity (249/250). Kappa values comparing with RPR/FTA-ABS were 0.978 for Kit A, 0.964 for Kit B and Kit S, and 0.987 for ARCHITECT Syphilis TP. From our evaluation, we found out that manual rapid tests and ARCHITECT Syphilis TP have very good clinical accuracies and high kappa agreements with RPR/FTA-ABS. Due to its automation and quick simultaneous diagnosis with another serological markers, we suggest that the ARCHITECT Syphilis TP is one of best suitable method for the primary diagnosis of syphilis and that it might be able to replace RPR method in the laboratories.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.3
• /
• pp.98-105
• /
• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• International Journal of Advanced Culture Technology
• /
• v.9 no.2
• /
• pp.100-105
• /
• 2021

Contactless service is rapidly emerging as a new growth strategy due to consumers who are reluctant to the face-to-face situation in the global pandemic of coronavirus disease 2019 (COVID-19), and various technologies are being developed to support the fast-growing contactless service market. In particular, the restaurant industry is one of the most desperate industrial fields requiring technologies for contactless service, and the representative technical case should be a kiosk, which has the advantage of reducing labor costs for the restaurant owners and provides psychological relaxation and satisfaction to the customer. In this paper, we propose a solution to the restaurant's store operation through the unmanned kiosk using a state-of-the-art artificial intelligence (AI) technology of image recognition. Especially, for the products that do not have barcodes in bakeries, fresh foods (fruits, vegetables, etc.), and autonomous restaurants on highways, which cause increased labor costs and many hassles, our proposed system should be very useful. The proposed system recognizes products without barcodes on the ground of image-based AI algorithm technology and makes automatic payments. To test the proposed system feasibility, we established an AI vision system using a commercial camera and conducted an image recognition test by training object detection AI models using donut images. The proposed system has a self-learning system with mismatched information in operation. The self-learning AI technology allows us to upgrade the recognition performance continuously. We proposed a fully automated payment system with AI vision technology and showed system feasibility by the performance test. The system realizes contactless service for self-checkout in the restaurant business area and improves the cost-saving in managing human resources.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.2
• /
• pp.320-326
• /
• 2021

AVTE(Air Vehicle Test Equipment) is an equipment to inspect and check the status of on-board aircraft LRUs(Line Replacement Units) before and after flight for performing successful UAV(Unmanned Aerial Vehicle) missions. This paper suggests utilization of the AVTE as an operation support-equipment by implementing several critical functions for UAV-operation on the AVTE. The AVTE easily sets initialization(default) data and compensates for the installation and position errors of the LRUs which provide critical mission data and situation image with pilots without additional individual operation support-equipment. Major fault list and situation image data could be downloaded after flight using the AVTE in the event of UAV emergency situation or unusual occurrence on duty as well. We anticipate the suggested operational approach of the AVTE could dramatically reduce the cost and man power for design and manufacture of additional operation support equipment and effectively diminish workload of the operator.

• Korean Journal of Cognitive Science
• /
• v.26 no.2
• /
• pp.147-165
• /
• 2015

Through short-answer questions, we can reflect the depth of students' understanding and higher-order thinking skills. Scoring for short-answer questions may take long time and may be an issue on consistency of grading. To alleviate such the suffering, automated scoring systems are widely used in Europe and America, but are in the initial stage in research in Korea. In this paper, we propose a semi-automatic scoring system for short Korean free-text responses using semi-supervised learning. First of all, based on the similarity score between students' answers and model answers, the proposed system grades students' answers and the scored answers with high reliability have been included in the model answers through the thorough test. This process repeats until all answers are scored. The proposed system is used experimentally in Korean and social studies in Nationwide Scholastic Achievement Test. We have confirmed that the processing time and the consistency of grades are promisingly improved. Using the system, various assessment methods have got to be developed and comparative studies need to be performed before applying to school fields.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.5
• /
• pp.47-53
• /
• 2020

The purpose of this study was to increase product reliability by improving the durability of the breech block for a 30mm Automatic Gun. The breech block is a key component of a gun that functions as chambering, closing, and extracting. The breech block requires high reliability, which needs to be improved because cracks of a breech block can occur early in operation. Cause analysis confirmed that the crack is caused by repeated impacts. Therefore, the following improvement measures were studied, and the effects were demonstrated using a firing test. The energy of impact absorption was increased by changing the material, and the stress concentration was mitigated by increasing the value of R. In addition, the fatigue life was increased by adding Shot-peening, deleting chromium plating, and changing the forging method. The firing test did not show firing trouble for up to 5,000 rounds. The start timing of the crack was delayed, and the depth was small. Therefore, the improved product was more durable than the existing product. This study can be used as a useful reference when assessing the improvement of the durability of similar products, life study, and criteria for crack acceptance.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.4
• /
• pp.153-163
• /
• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• Korean Journal of Environment and Ecology
• /
• v.29 no.2
• /
• pp.174-183
• /
• 2015

We have conducted a verification test of correlation between bird community indices and bird sound recording results in order to use the equipment which deals with the automatic sound collecting system, the song meter. The study areas include four sites which are Gombaeryoung and Zochimryoung in Jeombongsan Mountain and Jookryoung and Gochiryoung in Sobaeksan National Park. We collected the bird sound data five times using a sound recorder and field survey results in the same place of the study site. As a result of the sound recording from the field survey, the species recorded by three researchers of sound analyst include common resident species or species which have a relatively conspicuous call and song. On the contrary, the species recorded by only one researcher are a relatively rare or inconspicuous species or was familiar with the personal experiences of each researcher. The number of species recorded by only one researcher totaled fourteen species (36.8 %), and that of two researchers totaled twelve species (31.6 %), and that of three researchers totaled twelve species (31.6 %). The correlations of the number of species among three researchers was not significant in some results, but the sum or maximum count of the number of species was useful to estimate a significant correlation between the result of researchers and the indices of field surveys. As a result of correlation analysis by using sound recordings, the maximum number of species among the three researchers significantly correlated with the number of species, the species diversity index and the species abundance index in the field survey at the same site, however it did not correlate with the number of individuals and species evenness index. As a result of sound analysis collected from the stationary sound recording system; song meter, the number of frequencies in bird songs and calls correlated with the number of species in the field survey at the same site. The number of calls and songs decreased as time went by. Finally, we could test the active time range and change the activity strength by using a sound recording system. In particular, that sound recording system is able to collect data in same time and site, so it is expected so that the equipment not only replenish a shortage of researchers and survey periods in field research in a short term monitoring survey, but also be able to acquire statistical objectivity.