• Proceedings of the Korean Society of Applied Pharmacology
• /
• 1997.04a
• /
• pp.107-107
• /
• 1997

Cytochrome P450 enzymes have been intensively investigated in hepatic tissues and several mammalian cell lines. Compared to most studies about cytochrome P450 isozymes in liver in vivo and hepatic, cell lines in vitro, the study of cytochrome P450IA1 in human breast cancer cells could be very important to understand the mechanism of the regulation of CYPIA1 gene expression and cell growth. MCF-7 human breast cancer cells are well characterized to study estrogen and antiestrogen action due to the fact that they contain high level of estrogen receptor and have biological markers characterized. And also MCF-7 cells express high level of arylhydrocarbon hydroxylase activity and human cytochrome P450IA1 cDNA was cloned from MCF-7 cells. Ah receptor was characterized in many breast cancer cell lines and polycyclic aromatic hydrocarbon such as 3-MC induced the expression of CYPIA1 gene and cytochrome P450- dependent monooxygenase activity. We undertook a study to examine the effect of estrogens and other chemicals on the regulation of human CYPIA1 gene expression in MCF-7 cells via RTPCR analysis, that might help us to understand the mechanism of the regulation of CYPIA1 gene expression and MCF-7 cell growth. Expression vector containing the functional 5'-regulatory region of human CYPIA1 fused to the CAT reporter gene was transfected into estrogen receptor positive MCF-T cells or estrogen receptor negative MDA-MB-231 cells. After these cells were treated with various chemicals, RTPCR was carried out to measure both CYPIA1 mRNA and CAT mRNA levels. 1nM 3-MC increased in both P450 and CAT mRNA levels over those of control by two folds in MCF-7 cells but does not in MDA-MB-231 cells. Estrogen or tamoxifen or retinoic acid or chrysin decreased in both P450 and CAT mRNA levels that were induced by 3-MC in MCF-7 when each chemical was administered with 3-MC concomitantly. These results suggested that the level of CYPIA1 gene expression is modulated with estrogen-related molecules and make it possible to speculate that ER is related to CYPIA1 gene expression and cell growth in breast cancer cells. [Supported by grants from the Korean Ministry of Education ]

• Journal of Advanced Navigation Technology
• /
• v.27 no.2
• /
• pp.190-196
• /
• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Fisheries and Aquatic Sciences
• /
• v.26 no.3
• /
• pp.204-215
• /
• 2023

The thermolabile haemolysin (tlh) of Vibrio parahaemolyticus (Vptlh) from V. parahaemolyticus is a multiple-function enzyme, initially describes as a haemolytic factor activated by lecithin and phospholipase A2 enzymatic activity (Shinoda, 1991; Vazquez-Morado, 2021; Yanagase et al., 1970). Until now, the tlh structure has hypothesized including N-terminal and C-terminal domain, but what domain of the Vptlh structure does the haemolytic activity has not been refined yet. In this study, a 450-bp VpTLH nucleotide sequence of the entire Vptlh gene encoded the C-terminal domain cloned firstly to examine its responsibility in the activity of the Vptlh. The C-terminal domain fused with a 6-His-tag named the His-tag-VpC-terminal domain was expressed successfully in soluble form in the BL21 (DE3) PlysS cell. Remarkably, both expression and purification results confirmed a high agreement in the molecular weight of the His-tag-VpC-terminal domain was 47 kDa. This work showed the His-tag-VpC-terminal domain lysed the erythrocyte membranes in the blood agar and the phosphate buffered saline (0.9%) media without adding the lecithin substrate of the phospholipase enzyme. Haemolysis occurred at all tested diluted concentrations of His-tag-VpC-terminal domain (p < 0.05), providing evidence for the independent haemolytic activity of the His-tag-VpC-terminal domain. The content of 100 ㎍ of the His-tag-VpC-terminal domain brought the highest haemolytic activity of 80% compared to that in the three remaining contents. Significantly, the His-tag-VpC-terminal domain demonstrated not to involve the phospholipase activity in Luria-Bertani agar supplemented with 1% (vol/vol) egg yolk emulsion. All results proved the vital responsibility of the His-tag-VpC-terminal domain in causing the haemolytic activity without the required activation by the phospholipase enzyme. Raw extracts of Phellinus igniarus and Phellinus pipi at 10^-1 mg/mL inhibited the haemolytic activity of the His-tag-VpC-terminal domain from 67.7% to 87.42%, respectively. Hence applying the His-tag-VpC-terminal domain as a simple biological material to evaluate quickly potential derivatives against the Vptlh in vivo conditions will accessible and more advantageous than using the whole of the Vptlh.

• Korea Science and Art Forum
• /
• v.25
• /
• pp.463-475
• /
• 2016

As the transition to the digital age in the late 20th century, the intrinsic value of the craft, the emotional values of human, has been noticed as an alternative to overcome the adverse effects of the modernism of the industrial age. To introduce experimental tries which convergence of contemporary technologies and elements of traditional craft, and to inspire artists and present the new possibility of creation to them who want to take advantage of craft emotion as the elements of creation is the purpose of this study in the current digital technology age. First, the meaning and value of craft in modern times and digital media and hybrid creation environments are theoretically investigated based on previous studies and literature. Second, design cases produced by combining digital technology as a tool and craft elements are classified for substantial understanding of the design. Thirdly, identify the design characteristics presented through case studies and suggest the new possibility of creation. The results of the study are as follows. Reject typical types highlight the functional role and try free express conversion, e.g. form, material, texture, making process etc. Extracts the various elements that can be applied and search combining ways, because the convergence of digital technology and the craft is sufficient to activate the human emotion. Interaction between the craft and the digital medium is made actively. Craft accepts digital form, the craft appeared again as the contents of the digital. the traditional and digital method appropriately fused and utilized depending on the situation in process.

• Convergence Security Journal
• /
• v.22 no.4
• /
• pp.85-97
• /
• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• Korean Journal of Remote Sensing
• /
• v.39 no.2
• /
• pp.223-232
• /
• 2023

A widely used method for monitoring land cover using high-resolution satellite images is to classify the images based on the colors of the objects of interest. In urban areas, not only major objects such as buildings and roads but also vegetation such as trees frequently appear in high-resolution satellite images. However, the colors of vegetation objects often resemble those of other objects such as buildings, roads, and shadows, making it difficult to accurately classify objects based solely on color information. In this study, we propose a method that can accurately classify not only objects with various colors such as buildings but also vegetation objects. The proposed method uses the normalized difference vegetation index (NDVI) image, which is useful for detecting vegetation objects, along with the RGB image and classifies objects into subclasses. The subclass classification results are fused, and the final classification result is generated by combining them with the image segmentation results. In experiments using Compact Advanced Satellite 500-1 imagery, the proposed method, which applies the NDVI and subclass classification together, showed an overall accuracy of 87.42%, while the overall accuracy of the subchannel classification technique without using the NDVI and the subclass classification technique alone were 73.18% and 81.79%, respectively.

• Journal of Practical Engineering Education
• /
• v.14 no.3
• /
• pp.593-600
• /
• 2022

Various sensors such as lidar, radar, and camera are fused and used in autonomous vehicles. Rider and radar sensors are difficult to popularize because they are expensive equipment. In order to popularize autonomous vehicles, research that can replace expensive equipment is continuously being conducted. In this paper, we use a single camera that is inexpensive and can be easily mounted. We propose a method for detecting the wheels and adjacent lanes of a front-side vehicle of a driving vehicle and estimating distances. Our proposed method detects lanes and wheels from frame images after frame extraction via input images. In addition, the distance is measured and compared with the actual distance measured in the actual road environment. The distance could be calculated relatively accurately within the error range of ± 3 cm. Through this, it is expected that the camera can be used as an alternative means when the cost of autonomous vehicles is reduced or when the lidar or radar sensor fails.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1497-1503
• /
• 2023

To address challenges in classifying clouds and snow cover when calculating ground reflectance in Near-UltraViolet (UV) wavelengths, this study introduces a methodology that combines cloud data from the Geostationary Environmental Monitoring Spectrometer (GEMS) and the Advanced Meteorological Imager (AMI)satellites for snow cover analysis. The proposed approach aims to enhance the quality of surface reflectance calculations, and combined cloud data were generated by integrating GEMS cloud data with AMI cloud detection data. When applied to compute GEMS surface reflectance, this fusion approach significantly mitigated underestimation issues compared to using only GEMS cloud data in snow-covered regions, resulting in an approximately 17% improvement across the entire observational area. The findings of this study highlight the potential to address persistent underestimation challenges in snow areas by employing fused cloud data, consequently enhancing the accuracy of other Level-2 products based on improved surface reflectivity.

• Journal of Industrial Convergence
• /
• v.22 no.4
• /
• pp.1-9
• /
• 2024

Smart factories represent production facilities where cutting-edge information and communication technologies are fused with manufacturing processes, reflecting rapid advancements and changes in the global manufacturing sector. They capitalize on the integration of robotics and automation, the Internet of Things (IoT), and the convergence of artificial intelligence technologies to maximize production efficiency in various manufacturing environments. However, the smart factory environment is prone to security threats and vulnerabilities due to various attack techniques. When security threats occur in smart factories, they can lead to financial losses, damage to corporate reputation, and even human casualties, necessitating an appropriate security response. Therefore, this paper proposes a security authentication mechanism for safe communication in the smart factory environment. The components of the proposed authentication mechanism include smart devices, an internal operation management system, an authentication system, and a cloud storage server. The smart device registration process, authentication procedure, and the detailed design of anomaly detection and update procedures were meticulously developed. And the safety of the proposed authentication mechanism was analyzed, and through performance analysis with existing authentication mechanisms, we confirmed an efficiency improvement of approximately 8%. Additionally, this paper presents directions for future research on lightweight protocols and security strategies for the application of the proposed technology, aiming to enhance security.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.2
• /
• pp.41-47
• /
• 2024

When there were disparities in performance between models trained in the time and frequency domains, even after conducting an ensemble, we observed that the performance of the ensemble was compromised due to imbalances in the individual model performances. Therefore, this paper proposes a leakage detection technique to enhance the accuracy of pipeline leakage detection through a step-wise learning approach that extracts features from both the time and frequency domains and integrates them. This method involves a two-step learning process. In the Stage 1, independent model training is conducted in the time and frequency domains to effectively extract crucial features from the provided data in each domain. In Stage 2, the pre-trained models were utilized by removing their respective classifiers. Subsequently, the features from both domains were fused, and a new classifier was added for retraining. The proposed transfer learning-based feature fusion technique in this paper performs model training by integrating features extracted from the time and frequency domains. This integration exploits the complementary nature of features from both domains, allowing the model to leverage diverse information. As a result, it achieved a high accuracy of 99.88%, demonstrating outstanding performance in pipeline leakage detection.