• Preventive Nutrition and Food Science
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• v.17 no.1
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• pp.14-21
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• 2012

The purpose of this study was to investigate the anti-allergy activities of persimmon leaf extract (PLE) on a phthalic anhydride (PA)-induced allergic mouse model. A human leukemic mast cell line (HMC-1) was used to examine the inhibitory activity of PLE on the histamine release by human leukemic mast cells. PLE inhibited histamine release from HMC-1 cells in response to cross-linkage of high-affinity IgE receptor-${\alpha}$ ($Fc{\varepsilon}RI{\alpha}$). Additionally, a PA-induced allergic mouse model was used to investigate the effects of PLE in vivo. Mice were orally administrated with or without PLE of single dose (250 mg/kg/day) for 31 days. Oral intake of PLE significantly inhibited passive cutaneous reactions. Oral administration of PLE to PA-induced allergic mice also led to a striking suppression of the development of contact dermatitis, ear swelling and lymph node weight. In addition, PA-specific IL-4 production of draining lymph node cells was markedly diminished by PLE oral administration, but not IFN-${\gamma}$. Furthermore, PLE treatment suppressed PA-induced thymus and activation-regulated chemokine (CCL17) and cutaneous T cell-attracting chemokine (CCL27) expressions in ear tissues. Based on these results, we suggest that PLE may have therapeutic potential as an effective material for management of irritant contact dermatitis or related inflammatory diseases.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.139-146
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• 2007

Many researches had been gone about method to track moving object using wireless sensor network. We examined tradeoffs that exist between quantity of energy and correctness of tracking, and we confirmed that can get more energy sayings through improved motion prediction method. The consumed energy in the tracking is used by sensor node for sensing the object, and tracking correctness is a differ once of actual object position from calculated value by sensing. Some tracking methods and controlling parameters causes a variation of tracking correctness and energy consuming, we can get best energy effectiveness by motion prediction algorithm. Furthermore, we get better tracking quality and energy effectiveness through using a motion prediction algorithm that consider acceleration. By the simulation, we know that if we use an accurate motion prediction algorithm, node activation range that is used for target's predicted position should be restricted to sensing range of sensor is better.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3437-3441
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• 2012

Background: Oncogenic Bmi-1 (B-lymphoma Moloney murine leukemia virus insertion region-1) belongs to the Polycomb-group (PcG) family of proteins and plays an important role in the regulation of proliferation, senescence, cell cycle and apoptosis, chromosome stability, activation of gene transcription. Methods: To clarify the roles of Bmi-1 in tumourigenesis and progression of gastric carcinomas, it was examined by immunohistochemistry (IHC) and real-time RT-PCR in gastric carcinomas, dysplasia, intestinal metaplasia (IM), and gastritis with a comparison of its expression with clinicopathological parameters of carcinomas. Results: There was gradually increased Bmi-1 protein expression from gastritis, IM, dyplasia to carcinoma (p<0.001). Bmi-1 expression was positively linked to tumor size, depth of invasion, lymph node metastasis and worse prognosis of carcinomas (p<0.001), but not to age or sex of carcinoma patients (p>0.05). There was higher Bmi-1 protein expression in intestinal-type carcinomas than diffuse-type ones (p<0.001). At mRNA level, Bmi-1 protein expression was increased from gastritis, IM, dysplasia and carcinoma (p<0.001). Bmi-1 overexpression was observed in gastric carcinoma with larger diameter, deeper invasion, lymph node metastasis, and intestinal-type carcinoma (p<0.05). Conclusion: These findings indicate that up-regulated Bmi-1 expression is positively linked to pathogenesis, growth, invasion, metastasis and differentiation of gastric carcinomas. It was considered as a promising marker to indicate the aggressive behaviors and prognosis of gastric carcinomas.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.6
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• pp.47-52
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• 2002

The wavelet functions are originated from scaling functions and can be used as activation function in the hidden node of the network by deciding two parameters such as scale and center. In this paper, we would like to propose the mixed structure. When we compose the WNN using wavelet functions, we propose to set a single scale function as a node function together. The properties of the proposed structure is that while one scale function approximates the target function roughly, the other wavelet functions approximate it finely. During the determination of the parameters, the wavelet functions can be determined by the global search algorithm such as genetic algorithm to be suitable for the suggested problem. Finally, we use the back-propagation algorithm in the learning of the weights.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.48-54
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• 2021

Purpose In ¹⁸F-FDG PET/CT, the absorption of ¹⁸F-FDG due to the activation of Brown Adipose Tissue (BAT) greatly interferes with the discrimination of lymph node malignant metastasis. Warming the patient's body temperature before and after injection of ¹⁸F-FDG to prevent FDG absorption by BAT is a safe and non-pharmacological approach. The purpose of this study was to identify and select patients with a high potential for BAT activation in advance, and to investigate whether BAT can inhibit FDG absorption when the body temperature is raised for a short time by directly applying heat to the target patient. Materials and Methods Among the patients who underwent ¹⁸F-FDG PET/CT at the National Cancer Center from January 2020 to December 2020, 825 female patients (415 in the thermal group, 410 in the non-thermal group) under 50 years old were included. The thermal group was administered heat for 10 minutes before injection of ¹⁸F-FDG. For statistical analysis, the Z test comparing the ratios between the two groups was used, and logistic regression analysis was performed to correct for important variables (BMI, outdoor temperature, blood sugar) according to the results of the previous retrospective study. Results Among 825 patients, 19 patients with BAT activated (Thermal group: 5(1.2%), Non-thermal group: 14(3.41%)) accounted for 2.3% of the total. As a result of performing the Z test to compare the ratios between the two groups, the activation of BAT in the thermal group was significantly decreased (P=0.034). In the univariate logistic regression analysis, the activation of BAT was also decreased in the thermal group (OR: 0.34, P<0.05). In the multivariate results, BAT activation increased in patients younger than 45 years old (OR: 4.46, P<0.05) and outdoor temperature less than 13.2 degrees (OR: 9.97, P<0.05). BAT activation tended to decrease in the thermal group, but there was no significant difference (OR: 0.37, P=0.066). Conclusion We confirmed that the activation of BAT tends to decrease by 62.5% in the group subjected to the thermal method, and it will be of great help in preventing FDG absorption of BAT more effectively in the future.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.103-108
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• 2007

Neural network is used in many fields of control systems currently. However, It is not easy to obtain input-output pattern when neural network is used for the system of a single feedback controller and it is difficult to get satisfied performance with neural network when load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object in place of activation function of Neural Network output node. As the Neural Network self adaptive control system is designed in simple structure neural network input-output pattern problem is solved naturally and real tin Loaming becomes possible through general back propagation algorithm. The effect of the proposed Neural Network self adaptive control algorithm was verified in a test of controlling the speed of a A.C. servo motor equipped with a high speed computing capable DSP (TMS320C32) on which the proposed algorithm was loaded.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.

• Molecules and Cells
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• v.43 no.4
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• pp.408-418
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• 2020

The sinus node (SN) is located at the apex of the cardiac conduction system, and SN dysfunction (SND)-characterized by electrical remodeling-is generally attributed to idiopathic fibrosis or ischemic injuries in the SN. SND is associated with increased risk of cardiovascular disorders, including syncope, heart failure, and atrial arrhythmias, particularly atrial fibrillation. One of the histological SND hallmarks is degenerative atrial remodeling that is associated with conduction abnormalities and increased right atrial refractoriness. Although SND is frequently accompanied by increased fibrosis in the right atrium (RA), its molecular basis still remains elusive. Therefore, we investigated whether SND can induce significant molecular changes that account for the structural remodeling of RA. Towards this, we employed a rabbit model of experimental SND, and then compared the genome-wide RNA expression profiles in RA between SND-induced rabbits and sham-operated controls to identify the differentially expressed transcripts. The accompanying gene enrichment analysis revealed extensive pro-fibrotic changes within 7 days after the SN ablation, including activation of transforming growth factor-β (TGF-β) signaling and alterations in the levels of extracellular matrix components and their regulators. Importantly, our findings suggest that periostin, a matricellular factor that regulates the development of cardiac tissue, might play a key role in mediating TGF-β-signaling-induced aberrant atrial remodeling. In conclusion, the present study provides valuable information regarding the molecular signatures underlying SND-induced atrial remodeling, and indicates that periostin can be potentially used in the diagnosis of fibroproliferative cardiac dysfunctions.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.21 no.2
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• pp.139-148
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• 1999

Oral cancer is a common neoplasm in humans and etiologic mechanism is not well known, so treatment and evaluation of oral cancer is difficult problem. Traditional TNM classification between prognosis of tumors and classification of histopathologic differentiation has problem like lack of objectivity through operators. In molecular biology, cancer is developed by alteration of activation of oncogene and/or inactivation of tumor suppressor gene. The p53 gene, one of the tumor suppresor genes, is believed to play an important role through mutation and overexpression in the progression of human cancers. The p53 mutation is most frequent genetic disorder in humans. The Cyclin D1 has tumor suppresion activity by regulation of cell cycle. The Cyclin D1 regulate activity of Rb tumor suppresor gene by stimulation of CDK4 The purpose of this study was to observe the expression of p53 protein and Cyclin D1 in oral squamous cell carcinoma, and to get expectation of the malignancy and prognosis of oral squamous cell carcinoma. Using the 15 cases of squamous cell carcinoma and the microscopic H&E and immunohistochemical stain. We divided it into 3 groups according to the stain extent, clinical stage and histologic differentiation. The results were as follows1.In the features of immunohistochemical stain of 15 cases of squamous cell carcinoma, positive reaction of p53 was identified in 8 cases (53.3%) and positive reaction of cyclin D1 was identified in 3 cases (20%). Both positive reaction of p53 protein and Cyclin D1 was show in only one case. 2.8 of p53 positive cases were linked in 87.5% of the end stage tumor, 62.5% of neck node involvement, 87.5% of poorly and moderately histopathplogic differentiation. 3. All 3 of Cyclin D1 positive cases were linked in the end stage tumor, neck node involvement, poorly and moderately histopathologic differentiation. From above results, expression of p53 protein was identified in 53.3% of 15 cases and these results mean oral squamous cell carcinoma was drived by mutation of p53 protein. Especially, highly positive reaction of p53 protein and Cyclin D1 was identified in cases that involvement of neck lymph node and the end stage tumors and it means that the evaluation of p53 protein and Cyclin D1 was useful for evaluation of malignant tumor as specific tumor marker.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.144-150
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• 2020

Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.