• Journal of Radiation Protection and Research
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• v.26 no.2
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• pp.51-58
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• 2001

In the low level radioactivity measurement, such as environmental radioactivity, there were used commonly cylindrical and Marinelli type beakers by means of measurement container. If there are differences in the matrix density or sample height between standard source and sample, it must be determined full energy peak efficiency considering self absorption effect. In this paper, we compared measured efficiency with calculated full energy peak efficiencies in the HPGe detector using the Monte Carlo method. For cylindrical container, we calculated the variation of the efficiency with sample height. Also, we calculated the variation of the detection efficiency with apparent density in the cylindrical and Marinelli container. It was seen that it need to be corrected for self absorption in the energy range of below 1000keV. Also, in order to verify the validity of calculation, we compared the calculated value with reference value using NIST SRM 4353 reference soil.

• Convergence Security Journal
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• v.23 no.5
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• pp.81-89
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• 2023

Kubernetes is a representative open-source software for container orchestration, playing a crucial role in monitoring and managing resources allocated to containers. As container environments become prevalent, security threats targeting containers continue to rise, with resource exhaustion attacks being a prominent example. These attacks involve distributing malicious crypto-mining software in containerized form to hijack computing resources, thereby affecting the operation of the host and other containers that share resources. Previous research has focused on detecting resource depletion attacks, so technology to respond when attacks occur is lacking. This paper proposes a reinforcement learning-based dynamic resource management framework for detecting and responding to resource exhaustion attacks and malicious containers running in Kubernetes environments. To achieve this, we define the environment's state, actions, and rewards from the perspective of responding to resource exhaustion attacks using reinforcement learning. It is expected that the proposed methodology will contribute to establishing a robust defense against resource exhaustion attacks in container environments

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.435-444
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• 2023

Purpose: To attain advanced performance certification, safety aspects along with functionality and performance are essential. Hence, this study suggests radiation leakage assessment methods for aviation security equipment during its performance certification. Methods: Detection technology guided the choice of radiation leakage assessment targets. We then detailed measurement and evaluation methods based on equipment type and operation mode. Equipment was categorized as container or box types for establishing measurement procedures. Results: We've developed specific radiation leakage assessment procedures for different types of aviation security equipment, crucial for ensuring airport safety. Using these procedures allows efficient evaluation of compliance with radiation leakage standards. Conclusion: The suggested radiation leakage assessment method aims to enhance aviation security and reliability. Future research will focus on identifying risks in novel aviation security equipment detection technologies and establishing safety standards.

• KSBB Journal
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• v.21 no.5
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• pp.341-346
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• 2006

This study was carried out to establish the optimum condition for cell disruption with a sonificator in the detection of the gram negative bacteria, E. coli for the purpose of developing automatic fluorometer. The efficiency of sonification on the E. coli disruption was greatly dependent on the diameter of sonificator probe tip. The larger sonificator probe diameter showed greater disruption effect. Sonificator probe of 13 mm diameter was the most efficient one for E. coli when sonificated for 20 seconds. The efficiency of the E. coli disruption differed greatly according to the depth of sonificator probe tip sank in the sample solution. The shorter the distance between probe tip end and the bottom of the container, the higher the disruption efficiency. The detection limit of E. coli was $5{\times}10^5CFU/m{\ell}$ when sample was sonificated for 20 seconds with a sonificator probe of 13 mm diameter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.1024-1030
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• 2015

Safety and security system have been internationally enhanced in a field of shipping logistics. Accordingly, techniques for safety and security have been studied steadily. The need of portable radiation detection device is increasing by the search of the container is enhanced. In this paper, we propose a study to improve the life of the system and the realization of portable radiation detection device based on Cortex-A9. Configuration of a portable radiation detection device is configured largely to an analog board and the digital platform and the sensor module. The power used in each stage of the analog board is varied. Uses a switching regulator to use various power supply thereby to generate an error result and cause the switching noise. It is proposed to reduce the power consumption reducing technique for the study.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1236-1249
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• 2020

In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.18-24
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• 2011

This paper proposes fault diagnosis system which is able to diagnose the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. For this all kinds of ship's engine room monitored data are classified with combustion subsystem, heat exchange subsystem and electric motor and pump subsystem by analyzing ship's operation data. To extract dynamic characteristics of these subsystems, log book data of container ship of H shipping company are used.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.950-952
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• 2003

This paper have been studied fabrication and characteristics of disposable pH sensor using MEMS technology. The sensor has two open-well structure, the container for the internal electrolyte and electrode were formed by anisotropically etching a silicon substrate. unlike currently used KCI saturated solution, the structure was introduced hydrogel which take an advantage of miniaturization, bulk product, a low price. PU and CA/TP used to measurement ion detection, one is reference membrane and the other is pH. fabricated sensor is encapsulated entirely with epoxy, finally sensor was estimated various ion sorts and pH ranges.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.337-338
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• 2023

컨테이너 해상 유실 사고는 매해 적지 않은 수로 발생하고 있으나 기존에는 사후적 대응, 사전 대응 관점의 대응책들이 대부분이다. 그렇기에 항해 간 컨테이너 유실에 대한 모니터링이 필요한데, 선원들이 항해하는 선박에 적재된 수천 개의 컨테이너를 일일이 들여다보거나 모든 곳에 센서를 부착해 감지하는 것에는 물리적, 경제적 한계가 존재한다. 본 연구는 선박에 적재된 컨테이너들을 3차원 좌표 화하여 선박의 경사시험에서 모티브를 가져와 일정 정도의 기울기를 선박에 적용하였을 때, 기울기 중심을 기준으로 회전운동이 가장 큰 좌표에 해당하는 컨테이너들을 K-평균 군집화를 통해 최적화 위치로 선정하여 센서 위치를 최적화시켜 효율적인 컨테이너 유실 감지를 위한 기반을 마련한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.298-301
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• 2024

클라우드 환경에서 컨테이너 사용이 증가하면서 컨테이너 환경을 대상으로 하는 여러 보안 위협이 증가하고 있다. 대표적인 악성 컨테이너는 크립토재킹 컨테이너로, 인스턴스 소유자의 승인 없이 리소스를 탈취하여 암호화폐를 채굴하는 공격이다. 이러한 공격은 리소스 낭비를 초래할 뿐 아니라 자원을 공유하는 정상 컨테이너나 호스트 인프라에까지도 영향을 미칠 수 있다. 따라서 본 논문에서는 크립토재킹 컨테이너를 탐지하기 위한 앙상블 기반의 크립토재킹 컨테이너 탐지 프레임워크 설계를 제안한다. 또한, 앙상블 모델 학습을 위한 데이터 수집에 있어 크립토재킹 컨테이너의 동적 특징을 나타내는 시스템 콜 및 네트워크 플로우 기반의 특성 활용 가능성을 사례 연구를 통해 분석하였다.