• Korean Journal of Environmental Biology
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• v.30 no.2
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• pp.77-89
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• 2012

With the advent of the genomics era powered by DNA sequencing technologies, life science is being transformed significantly and biological research and development have been accelerated. Environmental biology concerns the relationships among living organisms and their natural environment, which constitute the global biogeochemical cycle. As sustainability of the ecosystems depends on biodiversity, examining the structure and dynamics of the biotic constituents and fully grasping their genetic and metabolic capabilities are pivotal. The high-speed high-throughput next-generation sequencing can be applied to barcoding organisms either thriving or endangered and to decoding the whole genome information. Furthermore, diversity and the full gene complement of a microbial community can be elucidated and monitored through metagenomic approaches. With regard to human welfare, microbiomes of various human habitats such as gut, skin, mouth, stomach, and vagina, have been and are being scrutinized. To keep pace with the rapid increase of the sequencing capacity, various bioinformatic algorithms and software tools that even utilize supercomputers and cloud computing are being developed for processing and storage of massive data sets. Environmental genomics will be the major force in understanding the structure and function of ecosystems in nature as well as preserving, remediating, and bioprospecting them.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.147-152
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• 2018

Recently, as the demand for transmission of ultra-high quality media data such as UHD, AR, and VR increases, various technologies for this have been actively developed and IEEE 802.11ad standard have been commercialized. In this paper, a test bed is constructed to analyze the indoor wireless environment using the IEEE 802.11ad standard based on mmWave, and the experimental results of various indoor wireless environments are introduced and analyzed. We compared the data from the module by data transmission, such as signal to noise ratio(SNR) and throughput. And we measured the beam pattern and width of the module and compared the effects on the indoor environment of the corridor and the office. This shows that the signal reflection of the wall shows higher SNR values and is more suitable to use for indoor than outdoor. It is confirmed that the loss when not in line of sight(LoS) is not enough to compensate the wall reflected signal. As a result, it is judged to be suitable for the indoor use of the mmWave LAN and can be usefully used for further experiments.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8041-8046
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• 2014

In-depth analysis of how TRAIL signals through death receptors to induce apoptosis in cancer cells using high throughput technologies has added new layers of knowledge. However, the wealth of information has also highlighted the fact that TRAIL induced apoptosis may be impaired as evidenced by experimental findings obtained from TRAIL resistant cancer cell lines. Overwhelmingly, increasing understanding of TRAIL mediated apoptosis has helped in identifying synthetic and natural compounds which can restore TRAIL induced apoptosis via functionalization of either extrinsic or intrinsic pathways. Increasingly it is being realized that biologically active phytochemicals modulate TRAIL induced apoptosis, as evidenced by cell-based studies. In this review we have attempted to provide an overview of how different phytonutrients have shown efficacy in restoring apoptosis in TRAIL resistant cancer cells. We partition this review into how the TRAIL mediated signaling landscape has broadened over the years and how TRAIL induced signaling machinery crosstalks with autophagic protein networks. Subsequently, we provide a generalized view of considerable biological activity of coumarins against a wide range of cancer cell lines and how coumarins (psoralidin and esculetin) isolated from natural sources have improved TRAIL induced apoptosis in resistant cancer cells. We summarize recent updates on piperlongumine, phenethyl isothiocyanate and luteolin induced activation of TRAIL mediated apoptosis. The data obtained from pre-clinical studies will be helpful in translation of information from benchtop to the bedside.

• Journal of KIISE
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• v.44 no.2
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• pp.208-212
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• 2017

Flash SSDs have many advantages over the existing hard disks such as energy efficiency, shock resistance, and high I/O throughput. For these reasons, in combination with the emergence of innovative technologies such as 3D-NAND and V-NAND for cheaper cost-per-byte, flash SSDs have been rapidly replacing hard disks in many areas. However, the existing database engines, which have been developed mainly assuming hard disks as the storage, could not fully exploit the characteristics of flash SSDs (e.g. internal parallelism). In this paper, in order to utilize the internal parallelism intrinsic to modern flash SSDs for faster query processing, we implemented a prefetching method using asynchronous input/output as a new functionality for secondary index scans in MySQL InnoDB engine. Compared to the original InnoDB engine, the proposed prefetching-based scan scheme shows three-fold higher performance in the case of 16KB-page sizes, and about 4.2-fold higher performance in the case of 4KB-page sizes.

• Development and Reproduction
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• v.14 no.4
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• pp.215-223
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• 2010

The construction of transgenic mouse using embryonic stem (ES) cells has been crucial in the functional studies of gene on mouse genome. Gene knockout mice have been powerful for elucidating the function of genes as well as a research model for human diseases. Gene targeting and gene trapping mathods have been the representative technologies for making the knockout mice by using ES cells. Since the gene targeting and the gene trapping methods were independently developed about 20 years ago, it's efficiency and productivity has been improved with a advance of molecular biology. Conventional gene targeting method has been changes to high throughput conditional gene targeting. The combination of the advantage of gene targeting and gene tapping elements allows to extend a spectrum of gene trapping and to improve the efficiency of gene targeting. These advance should be able to produce the mutant with various phenotype to target a certain gene, and in postgenome era they have served as crucial research tools in understanding the functional study of whole genome in mouse.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.4
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• pp.274-279
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• 2002

ATM packet switching technologies for the purpose of the B-ISDN service are focused on high performance which represents good qualities on throughput, packet loss, and packet delay. ATM switch designs on a class of parallel interconnection network have been researched. But these are based on the self-routing function of it. It leads to conflict with each other, and to lose the packets. Therefore, this paper proposes the method based on Sort-Banyan network should be adopted for optimal routing algorithm. It is difficult to expect good hardware complexity. For good performance, a switch design based on the development of new routing algorithm is required. For the design of switch network, the packet distributor and multiplane are proposed. They prevent each packet from blocking as being transmitted selectively by two step distributed decision algorithm. This switch will be proved to be a good performance switch network that internal blocking caused from self-routing function is removed. Also, it is expected to minimize the packet loss and decrease the packet delay according to packet transmission.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.34 no.4
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• pp.245-258
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• 2008

We describe here how we can use microfluidic technologies for fabricating functional materials that could be potentially utilized in cosmetics; these include void structures, functional particulate materials, shell materials, and multi-layered colloids. We can obtain these functional materials as microfluidic approaches provide precise control over both outer dimensions and inner morphology of emulsion drops in picoliter-volume scales with high throughput. We have confirmed that this technique has a great potential to fabricate novel particles and capsules with a variety of chemical compositions as well as higher orders of layers. This microfluidic approach will allow us to develop a lot of new techniques that are useful for a variety of applications, including delivery systems, chemical separations, bio-sensing, actuators, and so on. We do believe that these new techniques will help cosmetic industry not only give rise advanced functional materials and systems but also widen its product categories.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.311-316
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• 2014

Social network server due to the popularity of smart phones, and data stored in a big usable access data services are increasing. Big Data Big Data processing technology is one of the most important technologies in the service, but a solution to this minor security state. In this paper, the data services provided by the big -sized data is distributed using a double hash user to easily access to data of multiple distributed hash chain based data processing technique is proposed. The proposed method is a kind of big data data, a function, characteristics of the hash chain tied to a high-throughput data are supported. Further, the token and the data node to an eavesdropper that occurs when the security vulnerability to the data attribute information to the connection information by utilizing hash chain of big data access control in a distributed processing.

• Molecules and Cells
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• v.27 no.3
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• pp.271-277
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• 2009

Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.