• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.1
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• pp.81-88
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• 2020

Flight data recorder is a equipment that records data required for investigation of aircraft accidents and should be developed in compliance with the ED-112A standard. Unlike general data storage device, flight data recorder must be able to recover data after an aircraft accident, requiring a housing and a memory board to protect data in extreme environments. To attain this performance, we designed a housing that can withstand the test by analyzing the physical environment of the impact, shear/tensile, penetration resistance and static crush test of the crash survival test and minimized the size and weight compared to the existing one in consideration of the installation of the aircraft in this paper. Insulation material and thermal block material were applied to endure high and low temperature fire so that the internal temperature does not rise above 150℃ even in 260℃, 10 hour environment. In addition, the memory board is designed to minimize the size and we devise a hoping programming method to prevent continuous data loss of more than 16 seconds. Through this, Crash protected memory module that satisfies ED-112A was completed.

• The KIPS Transactions:PartA
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• v.14A no.3 s.107
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• pp.173-184
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• 2007

Garbage collection in the Java virtual machine is a core function that relieves application programmers of difficulties related to memory management. In this paper, we evaluate and analyze the performance of GenGC and GenRGC, garbage collectors for embedded Java virtual machines. For performance evaluation, we employ CVM, a real embedded Java virtual machine developed by Sun Microsystems, Inc., as a platform and also use a widely-used SpecJVM98 as a set of benchmark programs. To compare the performance of GenGC and GenRGC, we first evaluate the time of garbage collection and the delay time caused by garbage collection. Second, for more detailed performance analysis of GenRGC, we evaluate the time of garbage collection and the delay time caused by garbage collection while changing the sizes of a block and a frame. Third, we analyze the size of storage space required for performing GenRGC, and show GenRGC to be suitable for embedded environment with a limited mont of memory. Since CVM is the most representative one of embedded Java virtual machines, this performance study is quite meaningful in that we can predict the performance of garbage collectors in real application environments more accurately.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.362-362
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• 2010

Today, vast attention has been paid to periodic arrays of nanostructures due to their potential for applications such as memory with huge storage density. Such application requires large-scale fabrication of well ordered nano-sized structures. One of the most widely used methods for the ordered nanostructures is lithography. This top-down process, however, has the limit to reduce size. Here the promising alternative is the self-organization of ordered nano-sized structures such as large scale 2d carbon-induced reconstructions on W(110). In the present study, we report on the first well-resolved atomic resolution STM studies of the well-known R($15{\times}3$) and R($15{\times}12$) carbon induced reconstruction of the W(110). From the atomic image of R($15{\times}3$) for different values of tunneling gap resistance, we can tell there are no missing atoms in unit cells of R($15{\times}3$) and some atomic displacements are substantial from the clean W(110), even though not all the imaged position of atoms correspond to tungsten, but may include those of carbon. We are considering two cases; First case is related to lattice deformation, or top layer of W(110) is deformed in the process of relief of strain caused by random inserting of carbon atoms possibly in the interstitial position. In the second case, R($15{\times}3$) unit cell results from a coincidence lattice between clean W(110) substrate and tungsten carbide overlayer which has rectangular atomic arrangement and giving R($15{\times}3$) coincidence lattice. beta-W2C showing rectangular unit cell should be a candidate. Further, we report on new reconstructions. Unlike the well-known R($15{\times}12$) consisting of two parts, two inner structures between two "Backbone" structures. The new reconstruction, which we found for the first time, contains more parts between the "Backbone"s. Sometimes we can observe the reconstruction consists of only inner parts without "Backbone" parts. Thus, the observed reconstruction can be built by constructing of two types of "Lego"-like block. Moreover, the rectangle shape of "Backbone" transform to parallelogram-like shape over time, the so-called wavy-R($15{\times}12$). Adsorption of hydrogen can be the reason for this transformation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.36-42
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• 2019

Europe and North America are paying attention to residential ESS(Energy Storage System) that can manage energy efficiently. The ESS is a system that stores and manages the electric power by charging and discharging the battery. The ESS is generally used in conjunction with photovoltaic systems. The ESS supplies the load of the power generation time and stores the remaining PV power to supply the load at the non-power generation time. However, due to the high price of residential ESS, low electric rates and increasing block rates, there is no market of residential ESS in Korea. This paper reviews the price condition and the capacity for applying PV and residential ESS to household of apartments using HOMER in Korea.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.91-106
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• 2022

Cryptocurrency, stood out the sharp cost rising of Bitcoin has been spotlighted by means of the solution for stagflation because it is decentralized with an existing currency differently. Especially getting into 4th industrial revolution, technologies using block chain and internet of things have been used in the many fields, and the power of influence is also widespread. Nevertheless like a remark of Elon Musk of Tesla CEO, the problems of environmental contamination for cryptocurrency have been pointed out continuously and the most representative of them is an enormous electric usage as the use of fossil fuels. Also the amount generated of carbon dioxide result in the acceleration of global warming mainly based on the climate changes of earth if the existing mining method is continued. On the other hand, review researches have been conducted restrictively as the connection with environmental contamination as the mining of cryptocurrency. In this study, it intended to review problems for environmental contamination as the diversification of ecological system of cryptocurrency concretely. Upon investigation existing prior documents on the putting recent data first, the mining of cryptocurrency has affected on the environmental contamination conflicting with carbon neutrality as increasement of the electric usage and electronic wastes. And POS method without the mining process appeared, but it had a demerit collapsing a decentralization and then we met turning point on appearing various environmental-friendly cryptocurrency. Finally the appearance of cryptocurrency using new renewable energy acted on the opportunity of the usage maximization of energy storage apparatus and the birth of national government intervention. Based on these results, we mention clearly that hereafter cryptocurrency will regress if not go abreast the value of currency as well as environmental approach.

• Korean Journal of Agricultural Science
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• v.9 no.1
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• pp.357-370
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• 1982

Recent concern regarding price and availability of fossil fuels has spurred the interest in alternative sources for farm crop drying. Among the available options such as biomass energy, wind power, nuclear energy and solar energy etc., the increasing attention is being directed to the utilization of heat from solar energy especially for farm crop drying. Even though solar energy is dispersed over a large land area and only a relatively small amount of energy can be simply collected, the advantages of solar energy is that the energy is free, non-polluting. The study reported here was designed to help supply the informations for the development of simple and relatively inexpensive solar warehouse for farm crop drying and storage. Specifically, the objectives of this study were to determine the performance of the solar collector fabricated, to compare solar supplemented heat drying with natural air drying and to develop a simulation model of temperature in stored grain, which can be used to study the effects due to changes in ambient air temperature. For those above objectives, solar collector was fabricated from available materials. Corrugated steel galvanized sheet, painted flat black, was used as absorbers and clear 0.2mm polyethylene sheet was the cover material. The warehouse for rough rice drying and storage was constructed with concrete block, and the solar collector was used as the roof of warehouse instead of original roofing system of it. The results obtained in this study were as follows: 1. The thermal efficiency of the solar collector was average 26 percent and the overall heat transfer coefficient of the collector was approximately $25kJ/hr.m^2\;^{\circ}K$. 2. Solar heated air was sufficient to dry one cubic meter of rough rice from 23.5 to 15.0 percent in 7 days and natural air was able to dry the same amount of rough rice from 20.0 to 5 percent in l2 days. 3. Drying with solar heat reduced the required drying time to dry the same amount of rough rice into a half compared to natural air drying, but overdrying problems of the bottom layer were so severe that these problems should be thoroughly analyzed. 4. Simulation model of temperature in stored grain was developed and the results of predicted temperature agreed well with test results. 5. Based on those simulated temperature, changes in the grain-temperature were a large at the points of the wallside and the damage of the grain would be severe at the contact area of wall.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Korean Journal of Poultry Science
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• v.38 no.1
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• pp.29-35
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• 2011

An experiment was conducted to investigate the effects of dietary supplementation of a silicate mineral (D Lite) on growth performance, nutrient retention, carcass characteristics and meat quality in broiler chicks. A total of 640 broiler chicks were randomly allotted to four dietary treatments in a randomized complete block design. Each treatment had four replicates comprising 40 broilers in each replicate. Dietary treatments were as follows: control (0% D Lite), and diets supplemented with 0.15%, 0.30% and 0.45% of D Lite. The starter and finisher diets were fed from d 0 to 21 and d 21 to 35, respectively. Body weight gain during starter (p<0.05), finisher (p=0.057) and overall (p<0.001) experimental period and feed intake (p<0.05) during starter period decreased quadratically with increasing dietary D Lite levels. The birds fed 0.15% D Lite showed the greatest (p<0.05) overall weight gain, feed intake and retention of gross energy and calcium. There were no differences (p>0.05) in carcass characteristics, organ weights and breast meat composition. However, as the level of D Lite was increased in the diet there was a linear decrease in the TBARS values of breast meat (p<0.05) at d 12 of storage. These results suggest that D Lite supplementation at the level of 0.15% is shown to be effective in improving performance and nutrient retention in broilers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.3-16
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• 2008

A Wireless Sensor Network (WSN for short) is a wireless network consisting of distributed small devices which are called sensor nodes or motes. Recently, there has been an extensive research on WSN and also on its security. For secure storage and secure transmission of the sensed information, sensor nodes should be equipped with cryptographic algorithms. Moreover, these algorithms should be efficiently implemented since sensor nodes are highly resource-constrained devices. There are already some existing algorithms applicable to sensor nodes, including public key ciphers such as TinyECC and standard block ciphers such as AES. Stream ciphers, however, are still to be analyzed, since they were only recently standardized in the eSTREAM project. In this paper, we implement over the MicaZ platform nine software-based stream ciphers out of the ten in the second and final phases of the eSTREAM project, and we evaluate their performance. Especially, we apply several optimization techniques to six ciphers including SOSEMANUK, Salsa20 and Rabbit, which have survived after the final phase of the eSTREAM project. We also present the implementation results of hardware-oriented stream ciphers and AES-CFB fur reference. According to our experiment, the encryption speeds of these software-based stream ciphers are in the range of 31-406Kbps, thus most of these ciphers are fairly acceptable fur sensor nodes. In particular, the survivors, SOSEMANUK, Salsa20 and Rabbit, show the throughputs of 406Kbps, 176Kbps and 121Kbps using 70KB, 14KB and 22KB of ROM and 2811B, 799B and 755B of RAM, respectively. From the viewpoint of encryption speed, the performances of these ciphers are much better than that of the software-based AES, which shows the speed of 106Kbps.

• Composites Research
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• v.34 no.3
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• pp.192-198
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• 2021

Due to enormous market growing of electric vehicles without combustion engine, reducing unwanted BSR (buzz, squeak, and rattle) noise is highly demanded for vehicle quality and performance. Particularly, innerbelt weatherstrips which not only block wind noise, rain, and dust from outside, but also reduce noise and vibration of door glass and vehicle are required to exhibit high damping properties for improved BSR performance of the vehicle. Thermoplastic elastomers (TPEs), which can be recycled and have lighter weight than thermoset elastomers, are receiving much attention for weatherstrip material, but TPEs exhibit low material damping and compression set causing frictional noise and vibration between the door glass and the weatherstrip. In this study, high damping EPDM (ethylene-propylene-diene monomer)/PP (polypropylene) thermoplastic vulcanizates (TPV) were investigated by varying EPDM/PP ratio and ENB (ethylidene norbornene) fraction in EPDM. Viscoelastic properties of TPV materials were characterized by assuming that the material damping is directly related to the viscoelasticity. The optimum material damping factor (tanδ peak 0.611) was achieved with low PP ratio (14 wt%) and high ENB fraction (8.9 wt%), which was increased by 140% compared to the reference (tanδ 0.254). The improved damping is believed due to high fraction of flexible EPDM chains and higher interfacial slippage area of EPDM particles generated by increasing ENB fraction in EPDM. The stick-slip test was conducted to characterize frictional noise and vibration of the TPV weatherstrip. With improved TPV material damping, the acceleration peak of frictional vibration decreased by about 57.9%. This finding can not only improve BSR performance of electric vehicles by designing material damping of weatherstrips but also contribute to various structural applications such as urban air mobility or aircrafts, which require lightweight and high damping properties.