• Genomics & Informatics
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• v.13 no.4
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• pp.132-136
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• 2015

Studies of cancer heterogeneity have received considerable attention recently, because the presence or absence of resistant sub-clones may determine whether or not certain therapeutic treatments are effective. Previously, we have reported G64, a co-regulated gene module composed of 64 different genes, can differentiate tumor intra- or inter-subpopulations in lung adenocarcinomas (LADCs). Here, we investigated whether the G64 module genes were also expressed distinctively in different subpopulations of other cancers. RNA sequencing-based transcriptome data derived from 22 cancers, except LADC, were downloaded from The Cancer Genome Atlas (TCGA). Interestingly, the 22 cancers also expressed the G64 genes in a correlated manner, as observed previously in an LADC study. Considering that gene expression levels were continuous among different tumor samples, tumor subpopulations were investigated using extreme expressional ranges of G64-i.e., tumor subpopulation with the lowest 15% of G64 expression, tumor subpopulation with the highest 15% of G64 expression, and tumor subpopulation with intermediate expression. In each of the 22 cancers, we examined whether patient survival was different among the three different subgroups and found that G64 could differentiate tumor subpopulations in six other cancers, including sarcoma, kidney, brain, liver, and esophageal cancers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.139-144
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• 2023

Recently, many manufacturing companies are paying more attention to energy efficiency due to increased energy costs. Energy-efficient scheduling of production systems is a good method for energy efficiency improvement and cost reduction. In this research, we assumed the tire production problem and aim to construct a production scheduling considering specific shape module types, ordered amount for each tire, number of production modules, and the production time for each type. To facilitate effective production scheduling, we considered the types and number of shape modules currently available, and tire types that can be selected to be produced in the next stage were used as additional inputs, In addition to that, additional production was permitted to reduce the halt of production processing. Thus, an average production module utilization rate of about 62 percent was obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1545-1559
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• 2023

In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.559-561
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• 2022

인공지능 시대에 들어서면서 개인 맞춤형 환경을 제공하기 위하여 사람의 감정을 인식하고 교감하는 기술이 많이 발전되고 있다. 사람의 감정을 인식하는 방법으로는 얼굴, 음성, 신체 동작, 생체 신호 등이 있지만 이 중 가장 직관적이면서도 쉽게 접할 수 있는 것은 표정이다. 따라서, 본 논문에서는 정확도 높은 얼굴 감정 식별을 위해서 Convolution Block Attention Module(CBAM)의 각 Gate와 Residual Block, Skip Connection을 이용한 Identity- CBAM Module을 제안한다. CBAM의 각 Gate와 Residual Block을 이용하여 각각의 표정에 대한 핵심 특징 정보들을 강조하여 Context 한 모델로 변화시켜주는 효과를 가지게 하였으며 Skip-Connection을 이용하여 기울기 소실 및 폭발에 강인하게 해주는 모듈을 제안한다. AI-HUB의 한국인 감정 인식을 위한 복합 영상 데이터 세트를 이용하여 총 6개의 클래스로 구분하였으며, F1-Score, Accuracy 기준으로 Identity-CBAM 모듈을 적용하였을 때 Vanilla ResNet50, ResNet101 대비 F1-Score 0.4~2.7%, Accuracy 0.18~2.03%의 성능 향상을 달성하였다. 또한, Guided Backpropagation과 Guided GradCam을 통해 시각화하였을 때 중요 특징점들을 더 세밀하게 표현하는 것을 확인하였다. 결과적으로 이미지 내 표정 분류 Task에서 Vanilla ResNet50, ResNet101을 사용하는 것보다 Identity-CBAM Module을 함께 사용하는 것이 더 적합함을 입증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2987-3002
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• 2023

In 2015, the number of senior citizens aged 65 and over in Korea was 6,662,400, accounting for 13.1% of the total population. Along with these social phenomena, risk information related to the elderly is increasing every year. In particular, a fall accident caused by a fall can cause serious injury to an elderly person, so special attention is required. Therefore, in this paper, we implemented a system that monitors fall accidents and informs them in real time to minimize damage caused by falls. To this end, beacon-based indoor location positioning was performed and biometric information based on an integrated module was collected using various sensors. In other words, a multi-functional sensor integration module was designed based on Arduino to collect and monitor user's temperature, heart rate, and motion data in real time. Finally, through the analysis and prediction of measurement signals from the integrated module, damage from fall accidents can be reduced and rapid emergency treatment is possible. Through this, it is possible to reduce the damage caused by a fall accident, and rapid emergency treatment will be possible. In addition, it is expected to lead a new paradigm of safety systems through expansion and application to socially vulnerable groups.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.65-70
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• 2024

Tool wear is considered an important issue in manufacturing and engineering, as worn tools can negatively impact productivity and product quality. Given that the wear status of tools plays a decisive role in the production process, measuring tool wear is a key task. Consequently, there is significant attention in manufacturing fields on the precise measurement of tool wear. Current domestic methods for measuring wear are limited in terms of speed and efficiency, with traditional methods being time-consuming and reliant on subjective evaluation. To address these issues, we developed a measurement module implementing the DeepContour algorithm, which uses image processing technology for rapid measurement and evaluation of tool wear. This algorithm accurately extracts the tool's outline, assesses its condition, determines the degree of wear, and proves more efficient than existing, subjective, and time-consuming methods. The main objective of this paper is to design and apply in practice an algorithm and measurement module that can measure and evaluate tool wear using image processing technology. It focuses on determining the degree of wear by extracting the tool's outline, assessing its condition, and presenting the measured value to the operator.

• Current Photovoltaic Research
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• v.7 no.4
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• pp.111-120
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• 2019

The output power of a crystalline silicon (c-Si) photovoltaic (PV) module is not directly the sum of the powers of its unit cells. There are several losses and gain mechanisms that reduce the total output power when solar cells are encapsulated into solar modules. Theses factors are getting high attention as the high cell efficiency achievement become more complex and expensive. More research works are involved to minimize the "cell-to-module" (CTM) loss. Our paper is aimed to focus on electrical losses due to interconnection and mismatch loss at PV modules. Research study shows that among all reasons of PV module failure 40.7% fails at interconnection. The mismatch loss in modern PV modules is very low (nearly 0.1%) but still lacks in the approach that determines all the contributing factors in mismatch loss. This review paper is related to study of interconnection loss technologies and key factors contributing to mismatch loss during module fabrication. Also, the improved interconnection technologies, understanding the approaches to mitigate the mismatch loss factors are precisely described here. This research study will give the approach of mitigating the loss and enable improvement in reliability of PV modules.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.498-498
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• 2013

Atmospheric Pressure Plasmas have pioneered a new field of plasma for biomedical application bridging plasma physics and biology. Biological and medical applications of plasmas have attracted considerable attention due to promising applications in medicine such as electro-surgery, dentistry, skin care and sterilization of heat-sensitive medical instruments [1]. Traditional approaches using electronic devices have limits in heating, high voltage shock, and high current shock for patients. It is a great demand for plasma medical industrial acceptance that the plasma generation device should be compact, inexpensive, and safe for patients. Microwave-excited micro-plasma has the highest feasibility compared with other types of plasma sources since it has the advantages of low power, low voltage, safety from high-voltage shock, electromagnetic compatibility, and long lifetime due to the low energy of striking ions [2]. Recent experiment [2] shows three-log reduction within 180-s treatment of S. mutans with a low-power palm-size microwave power module for biomedical application. Experiments using microwave plasma are discussed. This low-power palm-size microwave power module board includes a power amplifier (PA) chip, a phase locked loop (PLL) chip, and an impedance matching network. As it has been a success, more compact-size module is needed for the portability of microwave devices and for the various medical applications of microwave plasma source. For the plasma generator, a 1.35-GHz coaxial transmission line resonator (CTLR) [3] is used. The way of reducing the size and enhancing the performances of the module is examined.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.4
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• pp.303-310
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• 2017

Pressure retarded osmosis(PRO) has attracted much attention as potential technology to reduce the overall energy consumption for reverse osmosis(RO) desalination. The RO/PRO hybrid process is considered as the most logical next step for future desalination. The PRO process aims to harness the osmotic energy difference of two aqueous solutions separated by a semipermeable membrane. By using the concentrated water(RO brine) discharged from existing RO plants, the PRO process can effectively exploit a greater salinity gradient to reduce the energy cost of processing concentrated water. However, in order to use RO brine as the draw solution, PRO membrane must have high water flux and enough mechanical strength to withstand the high operational pressure. This study investigates the development of a thin film composite PRO membrane and spiral wound module for high power density. Also, the influence of membrane backing layer on the overall power density was studied using the characteristic factors of PRO membranes. Finally, the performance test of an 8-inch spiral wound module was carried out under various operating conditions(i.e. hydraulic pressure, flow rate, temperature). As the flow rate and temperature increased under the same hydraulic pressure, the PRO performance increased due to the growth of water permeability coefficient and osmotic pressure. For a high performance PRO system, in order to optimize the operating conditions, it is highly recommended that the flow pressure be minimized while the flow rate is maintained at a high level.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.563-570
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• 2022

Industrialized and modular construction is a growing construction technique that can transfer a large portion of the construction process to off-site fabrication yards. This method of construction often involves the fabrication, pre-assembly, and transportation of massive and long volumetric modules. The module weight keeps increasing as the modules become more complete (with infill) to minimize the work at the site and, as higher productivity can be achieved at the fabrication shop. Thus, a volumetric module delivery gets more challenging and risky. Despite its importance, past research paid relatively insufficient attention to the problem related to the lifting of heavy modules. This can be a complex and time-consuming problem with multiple lifting for transportation-and-installation operations both in fabrication yard and jobsite, and require complex crane operations (sometimes, more than one crane) due to crane load capacity and load balance/stability. This study investigates this problem by focusing on the structural perspective of lifting such long volumetric modules through simulation studies. Various scenarios of lifting a weighty module from the top using four lifting cables attached to crane hooks (either a single crane or double crane) are simulated in SAP software. The simulations account for various factors pertaining to structural indices, e.g., bending stress and deflection, to identify a proper method of module lifting from a structural point of view. The method can identify differences in structural indices allowing identification of structural efficiency and safety levels during lifting, which further allows the selection of the number of cranes and location of lifting points.