• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.251-256
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• 2005

There is few study which automatically diagnose the fault from ship's monitored signal. The bigger control and monitoring system is, the more important fault diagnosis and maintenance is to reduce damage brought forth by system fault. This paper proposes fault diagnosis system using a correlation analysis algorithm which is able to diagnose and forecast the fault and is composed to fault detection knowledge base and fault diagnosis knowledge base. 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 verifying capability of fault detection, diagnosis and prediction, Fault Management System(FMS) is developed by C++. Simulation experiment by FMS is carried out with population data set made by log book data of 2 months duration from a large full container ship of H shipping company.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.321-332
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• 1999

It is important to detect objects movement for obstacle recognition and path searching of UCT(unmanned container transporters) with vision sensor. This paper shows the method to draw out objects and to trace the trajectory of the moving object using a CCD camera and it describes the method to recognize the shape of objects by neural network. We can transform pixel points to objects position of the real space using the proposed viewport. This proposed technique is used by the single vision system based on floor map.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.8
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• pp.1134-1143
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• 2012

The aims of this study were to investigate some macrominerals (Na, Ca, P, K, Mg) in 207 beverages, 19 liquid teas, and 24 liquid coffees. The samples were digested by microwave and determinations of macrominerals were carried out by an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). The elements, listed in order of mean value of macromineral content, were potassium $208.4{\pm}298.2mg/L$ ($72.2{\pm}169.8mg/container$)> calcium $89.0{\pm}161.0mg/L$ ($26.0{\pm}57.7mg/container$)> sodium $71.2{\pm}75.0mg/L$ ($20.9{\pm}27.9mg/container$)> phosphorus $55.6{\pm}91.9mg/L$ ($17.9{\pm}33.8mg/container$)> magnesium $6.1{\pm}18.4mg/L$ ($2.4{\pm}10.1mg/container$). All 250 samples contained sodium and potassium, and the detection rate of calcium, phosphorus and magnesium was 88.4%, 93.2%, and 20.4%. The mean ratio of phosphorus to calcium in beverages, liquid teas, and liquid coffees was $4.2{\pm}16.0$ (ND~164.4), and sports drinks showed the highest mean ratio ($48.5{\pm}75.6$) significantly (p<0.05). In case of sodium, detected content exceeding labeling regulations (less then 120%) was observed in 12 samples (5.5%).

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.712-718
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• 2006

In order to investigate the analytical uncertainties associated with sampling and analysis of major greenhouse gaseous pollutants(carbon dioxide and methane), we attempted to quantify their adsorptive loss due to the contact with the container wall(such as Tedlar bag and vial). Using the GC/FID method, some basic experimental parameters(such as reproducibility and method detection limit) have been evaluated as part of the essential QA/QC The reproducibilities of carbon dioxide and methane were estimated as 2.02 and 0.2%, respectively. In addition, method detection limits were measured as 0.61 and 0.06 ng, respectively. A test of sample loss rate has also been made for Tedlar bag and vial by assessing the absolute amount of sample loss on the wall. By transferring the samples contained in Tedlar bag to various sizes of Tedlar bags, we measured differences in the absolute loss quantity due to such transfer. In addition, we also examined such loss mechanism as a function of elapsed time and light penetration rate for vial. As results, carbon dioxide and methane have shown about 2% of sample loss due to such contact. It is also noticed that the amount of loss with vial surface is lower than that of Tedlar bag. Therefore, field collection of greenhouse gases using various container types should be made more cautiously to minimize the possibility of sample loss and bias related to such loss.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.499-505
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• 2018

Shipping and logistics safety, security system is strengthening worldwide, the development of shipping and logistics safety security core technology for national security logistics system construction has been carried out. In addition, it is necessary to localize the Array Detection System, which is a core component of the container search machine, to cope with the 100% pre-inspection of the container scheduled for 2018 in the United States. In this research, we propose a test software program developed by using TI-RTOS (Texas Instruments - Real Time Operating System) with a test digital signal processing board which is developed self development. We have developed a program that can test GPIO, SRAM, TCP/IP, and SDcard using M4 MCU. Also we propose a study on a self-developed Digital Signal Processing Board among the array detection systems that replace foreign products. We have developed a test board that can test M4 MCU and developed an X-Ray Detector Digital Signal Processing Board that combines MCU and FPGA.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.23-31
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• 2022

This study analyzed the actual frozen container operation data of Starcool provided by H Shipping. Through interviews with H's field experts, only Critical and Fatal Alarms among the four failure alarms were defined as failures, and it was confirmed that using all variables due to the nature of frozen containers resulted in cost inefficiency. Therefore, this study proposes a method for detecting failure of frozen containers through characteristic importance and PCA techniques. To improve the performance of the model, we select variables based on feature importance through tree series models such as XGBoost and LGBoost, and use PCA to reduce the dimension of the entire variables for each model. The boosting-based XGBoost and LGBoost techniques showed that the results of the model proposed in this study improved the reproduction rate by 0.36 and 0.39 respectively compared to the results of supervised learning using all 62 variables.

• Journal of Ocean Engineering and Technology
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• v.21 no.4
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• pp.45-54
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• 2007

In the context of auto-landing containers from a container ship to a truck or automatic guided vehicle and vice versa, this research investigates three schemes, one in Part I and two in Part II, for measuring the absolute position of a container. Coordinate transformations between the reference-coordinate, sensor-coordinate, and body-coordinate systems are briefly discussed. The scheme explored in Part I aims the use of three laser-slit sensors, which are relatively inexpensive. In this case, nine nonlinear equations are formulated for six unknown variables (three for orientation and three for position), so a closed-form solution is not available. Instead, an approximate solution through linearization was derived. An advantage of the method in Part I is its ability to measure an absolute position in 3D space, while a disadvantage is the computation time required to obtain pseudo-inverses and the approximate nature of the obtained solution. Numerical examples are provided.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.151-157
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• 2018

This paper presents an implementation of a smart plant pot which can supply light and water automatically according to the result of detection on current temperature, humidity and illumination, and deliver the images of the plant realtime by using a camera installed in the pot. We designed a container of the plant pot divided into five layers, printed each of them with a 3D printer, and then assembled them. Inside of the container, we installed sensors, a pump, and a camera. We developed an Android application so that the user can control the plant pot and monitor its state. In communication between the Android application and the Raspberry Pi, MQTT protocol was utilized.

• 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