• Korean Journal of Food Science and Technology
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• v.35 no.5
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• pp.980-987
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• 2003

In this report, we investigated the detoxication effects of Saururus chinenis, Geranium nepalense, Lonicera japonica, Cassia obtusifolia, Glycyrrhiza uralensis, or their mixtures by employing acute toxicity tests for nicotine and dioxin. When fatal doses $(LD_{100}\;=\;42\;mg/kg)$ of nicotine were injected into the abdominal cavities of ICR mice, those treated with OHEM showed delayed paralysis, half the duration of hyperactivity, and a 73 % survival rate. The results revealed the strong detoxicating effects of the mixtures. We also measured the amount of the degradation product of nicotine and cotinine in humans. Consumption of OHEM promoted (he more specific) the metabolic pathways of nicotine, increasing continine excretion by 1.5 times. As a result the amount of cotinine in urine was reduced to less than 5% after treatment with OHEM. In order to test the toxicity of dioxin, we used TcnN(SD)BR rats exposed to TCDD. While TCDD treatment reduced the blood levels of hemoglobin and platelet, OHEM consumption relieved these effects and, furthermore, helped to recover the number of platelet to the normal level (p<0.05). Moreover, neutrophils (%) and monocytes (%), which were reduced by the injection of TCDD, recovered to normal levels upon treatment with OHEM. The amount albumin reduced by TCDD (p<0.05) normalized, while the activities of GOT and GTP increased by TCDD were reduced. Increases in total cholesterol and neutral fatty acids induced by TCDD were also reduced by OHEM injection (p<0.05). In the kidney, TCDD-induced rises in creatinine were suppressed by OHEM treatment, while decreases in iron levels from TCDD were raised to normal. The treatment of TCDD had more toxic effects in the blood and pancreas than on the liver, kidney and heart. On the other hand, the detoxication of OHEM had significant effects on the liver and pancreas. The normalization by OHEM of various clinical abnormalities induced by TCDD demonstrates the detoxicating effect of OHEM that ameliorates systemic metabolism not properly functioning.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.3
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• pp.294-301
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• 2008

This study was carried out to investigate the protective effects and detoxification of oriental herb extracts mixture (Saururus chinensis, Taraxacum platycarpum, Ulmus macrocarpa, Glycyrrhiza glabra, Rhynchosia nulubilis) on TCDD-induced oxidative stress. Thirty five male rats were divided into 5 groups: normal control group received saline; vehicle control group received DMSO and acetone; only TCDD-treated group received multiple intraperitoneal injection of TCDD ($100{\mu}g/kg$) and saline; post-treated group of OHEM (400 mg/kg/day) received oral administration for 5 weeks after TCDD treatment; and pre-treated group of OHEM (400 mg/kg/day) received oral administration for 6 weeks from 1 week before TCDD treatment. The elevated serum activities of alanine transaminase (AST), aspartate transaminase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH) and atherorganic index due to TCDD were significantly decreased by the treatment of OHEM (p<0.05); the pre-treatment of OHEM was especially effective. Hydropic lesions and cytoplasmic vacuolizations in the liver of TCDD-treated rats were inhibited by the treatment of OHEM. Also, OHEM treatment reduced edemas in small intestine villus of TCDD-treated rats. These results suggest that OHEM from various oriental herb extracts might be a useful protective and detoxification agent against TCDD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.50-56
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• 2020

With the rapid development of deep neural network theory and application research, the effect of face detection has been improved. However, due to the complexity of deep neural network calculation and the high complexity of the detection environment, how to detect face quickly and accurately becomes the main problem. This paper is based on the relatively simple model of the MTCNN model, using FDDB (Face Detection Dataset and Benchmark Homepage), LFW (Field Label Face) and FaceScrub public datasets as training samples. At the same time of sorting out and introducing MTCNN(Multi-Task Cascaded Convolutional Neural Network) model, it explores how to improve training speed and Increase performance at the same time. In this paper, the dynamic image pyramid technology is used to replace the traditional image pyramid technology to segment samples, and OHEM (the online hard example mine) function in MTCNN model is deleted in training, so as to improve the training speed.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.659-666
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• 2021

With the continuous development of deep learning, human behavior recognition algorithms have achieved good results. However, in a multi-person recognition environment, the complex behavior environment poses a great challenge to the efficiency of recognition. To this end, this paper proposes a multi-person pose estimation model. First of all, the human detectors in the top-down framework mostly use the two-stage target detection model, which runs slow down. The single-stage YOLOv3 target detection model is used to effectively improve the running speed and the generalization of the model. Depth separable convolution, which further improves the speed of target detection and improves the model's ability to extract target proposed regions; Secondly, based on the feature pyramid network combined with context semantic information in the pose estimation model, the OHEM algorithm is used to solve difficult key point detection problems, and the accuracy of multi-person pose estimation is improved; Finally, the Euclidean distance is used to calculate the spatial distance between key points, to determine the similarity of postures in the frame, and to eliminate redundant postures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.421-441
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• 2021

Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

• 재활복지
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• v.20 no.4
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• pp.55-78
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• 2016

This society faces problems from unequal access to quality education which eventually lead to unequal distribution on wealth. Specifically, those youths with disabilities have a higher risk of living in poverty and becoming marginalized. First established in 2009, the Dodream program has addressed the issue of poverty fixation by establishing long-term supports for households of youths or adults with disabilities through case management. This study analyzes the effectiveness of Dodream program for youths with or youths whose parents are with disabilities on low-income households. The results of the study indicate that the Dodream program leads to improvements in self-concepts and career consciousness among youth. The program was particularly effective in improving the career preparedness of those who were involved. By establishing connections and collaborating with regional case management base institutions and cooperation centers, the program secured various social support resources. Finally the study presents plans on vitalizing the youth support by thoroughly investigating the cases of each study and establishing the program as long-term Human Capital Investment Model.