• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.319-325
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• 2015

While the conventional personal protective equipments (PPEs) covers a variety of devices and garments such as respirators, turnout gear, gloves, blankets and gas masks, several electronic devices such as personal alert safety system (PASS) and heads-up displays in the facepiece have become a part of firefighters personal protective equipments through past several years. Furthermore, more advanced electronic sensors including location traking sensor, thermal imaging caerma, toxic gas detectors, and even physiological monitoring sensors are being integrated into ensemble elements for better protection of firefighters from fire sites. Despite any electronic equipment placed on the firefighter must withstand environmental extremes and continue to properly function under any thermal conditions that firefighters routinely face, there are no specific criteria for these electronics to define functionability of these devices under given thermal conditions. Although manufacturers provide the specifications and performance guidelines for their products, their operation guidelines hardly match the real thermal conditions. Present study overviews firefighter's fatalities and thermal conditions that firefighters and their equipments face. Lastly, thermal packaging methods that we have developed and tested are introduced.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.111-121
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• 2008

Using variable speed limits (VSL) is a key strategy for preventing traffic accidents and alleviating traffic congestion. This study proposes an algorithm to operate VSLs on freeways for traffic safety. The proposed algorithm consists of two components based on accident likelihood estimation and analysis of safe stopping distance under various environmental conditions. A binary logistic regression technique is used for estimating accident likelihood. It is expected that the proposed algorithm would be successfully applied in practice in support of an integrated traffic and environmental condition monitoring system. Technical issues associated with the field implementation are also discussed.

• Neonatal Medicine
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• v.28 no.3
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• pp.99-107
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• 2021

Purpose: Studies have been conducted on the prevalence and infant mortality rate of congenital anomalies; however, studies on child mortality are rare. Therefore, we evaluated the characteristics of deaths associated with congenital anomalies among children born in Korea who died within 5 years of age. Methods: Birth-to-death cohort linked data of children under the age of 5 years from 2010 to 2013, and statistical data on the cause of death by age from 1999 to 2019, both provided by the Korea National Statistical Office's Microdata Integrated Service, were retrospectively investigated. We investigated the trends and characteristics of mortality associated with congenital anomalies. Results: Among 1,858,945 children, 6,510 children who died were under 5 years of age, and among them, 1,229 deaths were associated with congenital anomalies, while 5,281 deaths were due to other causes. Deaths associated with congenital anomalies accounted for 18.9% of all deaths. When comparing congenital anomalies by systems, anomalies of the cardiovascular system (52.6%) were the most common. The mortality rate associated with congenital anomalies and those of other causes showed similar declining trends in 21 years. Conclusion: The mortality rate of congenital anomalies during the first 5 years of life did not increase differently from the prevalence of congenital anomalies but rather decreased. Deaths associated with congenital anomalies accounted for 20.5% of all infant deaths and 12.1% of child deaths, since the major causes of death in infants and children are slightly different, continuous and careful monitoring is required.

• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1417-1427
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• 2019

In this study, we evaluated the performance of a commercial pixelated cadmium zinc telluride (CZT) detector for spectroscopy and identified its feasibility as a Compton camera for radiation monitoring in a nuclear power plant. The detection system consisted of a $20mm{\times}20mm{\times}5mm$ CZT crystal with $8{\times}8$ pixelated anodes and a common cathode, in addition to an application specific integrated circuit. The performance of the various radioisotopes $^{57}Co$, $^{133}Ba$, $^{22}Na$, and $^{137}Cs$ was evaluated. In general, the amplitude of the induced signal in a CZT crystal depends on the interaction position and material non-uniformity. To minimize this dependency, a drift time correction was applied. The depth of each interaction was calculated by the drift time and the positional dependency of the signal amplitude was corrected based on the depth information. After the correction, the Compton regions of each spectrum were reduced, and energy resolutions of 122 keV, 356 keV, 511 keV, and 662 keV peaks were improved from 13.59%, 9.56%, 6.08%, and 5%-4.61%, 2.94%, 2.08%, and 2.2%, respectively. For the Compton imaging, simulations and experiments using one $^{137}Cs$ source with various angular positions and two $^{137}Cs$ sources were performed. Individual and multiple sources of $^{133}Ba$, $^{22}Na$, and $^{137}Cs$ were also measured. The images were successfully reconstructed by weighted list-mode maximum likelihood expectation maximization method. The angular resolutions and intrinsic efficiency of the $^{137}Cs$ experiments were approximately $7^{\circ}-9^{\circ}$ and $5{\times}10^{-4}-7{\times}10^{-4}$, respectively. The distortions of the source distribution were proportional to the offset angle.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.255-263
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• 2021

Smart grid is a fully-automated, bi-directional, power transmission network based on the physical grid system, which combines sensor measurement, computer, information communication, and automatic control technology. Blockchain technology, with its security features, can be integrated with Smart Grids to provide secure and efficient power management and transmission. This paper dicusses the deployment of Blockchain technology in Smart Grid. It presents application areas and protocols in which blockchain can be applied to in securing smart grid. One application of each area is explored in detail, such as efficient peer-to-peer transaction, lower platform costs, faster processes, greater flexibility in power generation to transmission, distribution and power consumption in different energy storage systems, current barriers obstructing the implementation of blockchain applications with some level of maturity in financial services but concepts only in energy and other sectors. Wide range of energy applications suggesting a suitable blockchain architecture in smart grid operations, a sample block structure and the potential blockchain technicalities employed in it. Also, added with efficient data aggregation schemes based on the blockchain technology to overcome the challenges related to privacy and security in the smart grid. Later on, consensus algorithms and protocols are discussed. Monitoring of the usage and statistics of energy distribution systems that can also be used to remotely control energy flow to a particular area. Further, the discussion on the blockchain-based frameworks that helps in the diagnosis and maintenance of smart grid equipment. We have also discussed several commercial implementations of blockchain in the smart grid. Finally, various challenges have been discussed for integrating these technologies. Overall, it can be said at the present point in time that blockchain technology certainly shows a lot of potentials from a customer perspective too and should be further developed by market participants. The approaches seen thus far may have a disruptive effect in the future and might require additional regulatory intervention in an already tightly regulated energy market. If blockchains are to deliver benefits for consumers (whether as consumers or prosumers of energy), a strong focus on consumer issues will be needed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.134-143
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• 2020

With the worldwide spread of African swine fever, interest in livestock epidemics is growing. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted livestock-related vehicles' trajectory by utilizing the facility visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority and presented them as exposure indexes aggregating the link-time occupancy of each vehicle. As a result, a total of 274,519 livestock-related vehicle trajectories were extracted, and exposure values by link and zone were quantitatively derived. Through this study, it is expected that prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies would be provided.

• Journal of Platform Technology
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• v.10 no.1
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• pp.29-34
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• 2022

The emergence of new diseases such as the Covid 19 pandemic that occurs in the 21st century and the occurrence of health abnormalities according to the busy daily life of modern people are increasing. Accordingly, the importance of health care management and data-based health management is being highlighted, and in particular, interest in personal health management data based on personal health care data of patients is rapidly increasing. In this study, to solve the difficult problems of personal health management, we developed a personal health care platform incorporating IT for self-diagnosis and solution and developed an application that measures bio-signals generated in the human body and transmits them to the platform. A health management system was established. Through this, not only the health care of modern people, but also the psychological and emotional care support needs through psychological and emotional monitoring of the developmentally disabled and the vulnerable who have difficulty in expressing their opinions are to be addressed. In addition, the overall health and living environment data of the individual was integrated to develop an optimized medical and health management service for the individual.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.2
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• pp.119-128
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• 2022

Recent advancement of Internet of Things (IoT) and energy harvesting technology enable realization of flexible thermoelectric energy harvester (f-TEH), with technological prowess for use in biomedical monitoring system integrated applications. To expand a flexible thermoelectric energy harvesting platform, the f-TEH must be required for optimized flexible thermoelectric materials and device structure. In response to these demands related to thermoelectric energy harvesting, many research groups have investigated various f-TEHs applied as a power source for wearable electronics. As a key member of the f-TEH, film-based f-TEHs possess significant applicability in research to realize self-powered wearable electronics, owing to their excellent flexibility, low thermal conductivity, and convenient fabrication process. Thus, based on the rapid growth of thermoelectric film technology, this review aims to overview comprehensively the f-TEH made of various inorganic/organic thermoelectric materials including developed fabrication methods, high thermoelectric performance, and wide-range applications.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.325-335
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• 1996

Visual features are crucial for monitoring the growth state, indexing the drying performance, and grading the quality of oak mushrooms. A computer vision system with neural net information processing technique was utilized to quantize quality factors of a dried oak mushrooms distributed over the cap and gill sides. In this paper, visual feature extraction algorithm were integrated with the neural net processing to deal with various fuzzy patterns of mushroom shapes and to compensate the fault sensitiveness of the crisp criteria and heuristic rules derived from the image processing results. The proposed algorithm improved the segmentation of the skin features of each side, the identification of cap and gill surfaces, the identification of stipe states and removal of the stipe, etc. And the visual characteristics of dried oak mushrooms were analyzed and primary visual features essential to tile quality evaluation were extracted and quantized. In this study, black and white gray images were captured and used for the algorithm development.