• Journal of Bio-Environment Control
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• v.23 no.2
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• pp.123-130
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• 2014

Oriental melon (Cucumis melo var. makuwa) should be cultivated on the soil and be harvested. It is difficult to find because it is covered with leaves, and furthermore, it is very hard to grip it due to its climbing stems. This study developed and tested oriental melon harvesting robots such as an end-effector, manipulator and identification device. The end effector is divided into a gripper for harvest and a cutter for stems. In addition, it was designed to control the gripping and cutting forces so that the gripper could move four fingers at the same time and the cutter could move back and forth. The manipulator was designed to realize a 4-axis manipulator structure to combine orthogonal coordinate-type and shuttle-type manipulators with L-R type model to rotate based on the central axis. With regard to the identification device, oriental melon was identified using the primary identification global view camera device and secondary identification local view camera device and selected in the prediction of the sugar content or maturity. As a result of the performance test using this device, the average harvest time was 18.2 sec/ea, average pick-up rate was 91.4%, average damage rate was 8.2% and average sorting rate was 72.6%.

• The korean journal of orthodontics
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• v.51 no.2
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• pp.77-85
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• 2021

Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.4
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• pp.97-105
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• 2001

Rubber bearings may exhibit a significant cold temperature effect and some velocity dependency(strain rate effect). Both of these attributes which affect non-linear behavior must be accounted for when accurately modeling the bearings behavior, therefore, an analytical models is proposed to consider the effects of the cold temperature and strain rate on both rubber and lead. From the results of an experimental investigation where the frozen bearings were tested under lateral cyclic loading with constant axial load, a non-linear system identification with least squares procedure was applied to determine the material properties of rubber and lead. It is demonstrated that the proposed analytical model is able to simulate the reversed cyclic loading behavior of elastometric and lead-rubber bearings.

• International Journal of Highway Engineering
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• v.16 no.6
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• pp.181-189
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• 2014

PURPOSES : Ambiguous decision on whether rural or urban area for road design can increase the construction cost and restrict the land use of surrounding area. However, administrative classification on rural and urban area is not directly related to road design because of this classification is not based on the engineering viewpoint, so method which can explain the road design context is required. METHODS : Method which enables to identify the area for road design is suggested based on the deceleration expected to be experienced by drivers who use the road section concerned. Deceleration rate corresponding to the area such as rural or urban suggested in Road Design Guideline is used as the criteria to identify the area by comparing this value with the estimated deceleration rate at the road section concerned. Speed profile method is utilized to derive the deceleration rate, and speed estimation way for reflecting both road geometry and intersection is suggested using stopping sight distance concept. RESULTS : The procedure of the method application is suggested, and the design example utilizing the method is provided. CONCLUSIONS : The method is expected to be used to identify the area for road design with engineering viewpoint, and design consistency among the roads with similar driving environment can be made.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.166-170
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• 1999

The identification of quantitative trait loci (QTL) has the potential to enhance the efficiency of im- proving food processing traits of soybean. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W$_1$ and T) were used to identify QTL associated with food processing traits of soybean for sprout in 83 F$_2$-derived lines from a cross of ＇Pureun＇ x ＇Jinpum 2＇. The genetic map consisted of 76 loci which covered about 760 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected for hypocotyl length, abnormal seedling rate, and sprout yield seven days after seed germination at 2$0^{\circ}C$. Based on the single-factor analysis of variance, eight independent markers were associated with hypocotyl length. Four of seven markers associated with abnormal seedling rate were identified as independent. Seven loci were associated with sprout yield. For three different traits, much of genetic variation was explained by the identified QTL in this population. Several RFLP markers in linkage group (LG) Bl were detected as being associated with three traits, providing a genetic explanation for the biological correlation of sprout yield with hypocotyl length (r=OA07＊＊＊) and with abnormal seedling rate (r=-406＊＊＊).

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.1-8
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• 2015

Wear leveling techniques have been studied to prolong the lifetime of NAND flash memory. Most of studies have used Program/Erase(P/E) cycles as wear index for wear leveling. Unfortunately, P/E cycles could not predict the real lifetime of NAND flash blocks. Therefore, these algorithms have the limited performance from prolonging the lifetime when applied to the SSD. In order to apply the real lifetime, wear leveling algorithms, which use raw Bit Error Rate(rBER) as wear index, have been studied in recent years. In this paper, we propose CrEWL(Cold data identification using raw Bit error rate in Wear Leveling), which uses rBER as wear index to apply to the real lifetime. The proposed wear leveling reduces an overhead of garbage collections by using HBSQ(Hot Block Sequence Queue) which identifies hot data. In order to reduce overhead of wear leveling, CrEWL does not perform wear leveling until rBER of the some blocks reaches a threshold value. We evaluate CrEWL in comparison with the previous studies under the traces having the different Hot/Cold rate, and the experimental results show that our wear leveling technique can reduce the overhead up to 41% and prolong the lifetime up to 72% compared with previous wear leveling techniques.

• Biomedical Science Letters
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• v.27 no.2
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• pp.105-110
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• 2021

Short Tandem Repeats (STR) analysis which characterized by genetic polymorphism has been widely used in the forensic genetic fields. Unfortunately, mutation occurred in various STR loci could make it difficult to interpret STR data. Thus, the mutation rate of STR loci plays an important role for the data interpretation in human identification and paternity test. To verify the mutation of the STR loci in the Korean population, 545 trio sets (father, mother, and child) were analyzed with two commercial STR kits that include the 23 autosomal STR loci (D1S1656, TPOX, D2S441, D2S1338, D3S1358, FGA, D5S818, CSF1PO, D7S820, D8S1179, D10S1248, TH01, D12S391, VWA D13S317, D16S539, D18S51, D19S433, D21S11, D22S1045, SE33, Penta E and Penta D). As a result, 36 mutations were observed in 14 STR loci. The types of mutation were also classified by the increase or decrease of the alleles. The overall mutation rate was 1.4×10^-3, and the paternal mutation rate was four times higher than that of the maternal. This study will provide more detailed criterion for human identification by the mutation rate of STR loci in the Korean population.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.6
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• pp.1113-1118
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• 2011

In this paper, when a physician make a diagnosis of the pattern identification (PI) in Korean stroke patients, the development methods of the PI classification function is considered by diagnostic questionnaire of the PI for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PI subtypes diagnosed by two physicians with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PI using Korean Stroke Syndrome Differentiation Standard was consist of the 44 items (Fire heat(19), Qi deficiency(11), Yin deficiency(7), Dampness-phlegm(7)). Using the 44 items, we took diagnostic and prediction accuracy rate through of discriminant model. The overall diagnostic and prediction accuracy rate of the PI subtypes for discriminant model was 74.37%, 70.88% respectively.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.142-155
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• 2000

A MIMO model reference control scheme incorporating the variable structure theory for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of continuous-time nonlinear dynamics with known or unknown uncertainties. The scheme employs an neural network to identify the plant systems, where the neural network estimates the nonlinear dynamics of the plant. By the Lyapunov direct method, the algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed and it is not necessary to know the exact structure of the system. With the resulting identification model which contains the neural networks, it does not need higher degrees of freedom vehicle model than 3 degree of freedom model. Th proposed scheme is applied to the active four wheel system and shows the validity is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the reduction of yaw rate overshoot of a typical mid-size car improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response and smaller side angle than the 2WS case.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.365-374
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• 2010

This paper is about the personal identification algorithm using an ECG that has been studied by a few researchers recently. Previously published algorithm can be classified as two methods. One is the method that analyzes ECG features and the other is the morphological analysis of ECG. The main characteristic of proposed algorithm uses together two methods. The algorithm consists of training and testing procedures. In training procedure, the features of all recognition objects' ECG were extracted and the PCA was performed for morphological analysis of ECG. In testing procedure, 6 candidate ECG's were chosen by morphological analysis and then the analysis of features among candidate ECG's was performed for final recognition. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 90.96% heartbeat recognition rate and 100% ECG recognition rate.