• Journal of the Korean Society of Food Science and Nutrition
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• v.21 no.2
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• pp.213-218
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• 1992

The reaching time to the freezing point was to be fast in the order of 2% agar gel, 5% agar gel, 20% gelatin gel, pork, respectively. The freezing time and the passing time through the zone of the maximum ice crystal formation had linear relationship with the coolant temperature. The average diameter d$_{p}$ of ice crystal in a soybean protein gel and the moving of freezing front were represented an inverse proportion, and the moving velocity of freezing front was shown as 3.4$\times$10$^{-6}$ $\textrm{cm}^2$/sec from predicted theoretical formula. This value was very close to experimental results. The storage temperature did not give any influences for the growth of ice crystal in inside soybean protein gels during freezing conservation. The relationship between freezing condition and structure of freezing front was as follows : (moving velocity of freezing front) : (mass transfer rate of water at freezing point)$\times$(surface area of freezing front).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.323-338
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• 2003

The main memory database systems (MMDBMS) efficiently supports various database applications that require high performance since it employs main memory rather than disk as a primary storage. Recently, it has been increased needs that have the fast data processing as well as the efficient modeling of application requiring for a complicated structure, and conformity to applications that need the strict dta consistency. In MMDBMS, because all the data is located in the main memory, it can support the usable expression methods of data satisfying their needs without performance overhead. The method has the operation to manipulate the data and the constraint such as referential integrity in more detail. The data model consists of this methods is an essential component to decide the expression power of DBMS. In this paper, we discuss about various requests to provide the communication services and propose the data model that support it. The mainly discussed issues are 1) definition of the relationship between tables using the pointer, 2) navigation of the data using the relationship, 3) support of the referential integrity for pointer, 4) support of the uniform processing time for the join, 5) support of the object-oriented concepts, and 6) sharing of an index on multi-tables. We discuss the pointer-based data model that designed to include these issues to efficiently support complication environments.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.412-427
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• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.399-404
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• 2002

Along the evolution of information and communication technologies, manufacturing embedded systems such as PDA (personal digital assistant), HPC (hand -held PC), settop box. and information appliance became realistic. And RTOS (real-time operating system) and filesystem have been played essential re]os within the embedded systems as well. For the filesystem of embedded systems, flash memory has been used extensively instead of traditional hard disk drives because of embedded system's requirements like portability, fast access time, and low power consumption. Other than these requirements, nonvolatile storage characteristic of flash memory is another reason for wide adoption in industry. However, there are some technical challenges to cope with to use the flash memory as an indispensable component of the embedded systems. These would be relatively slow cleaning time and the limited number of times to write-and-clean. In this paper, a new cleaning policy is proposed to overcome the problems mentioned above and relevant performance comparison results will be provided. Ranking cleaning policy(RCP) decides when and where to clean within the flash memory considering the cost of cleaning and the number of times of cleaning. This method will maximize not only the lifetime of flash memory but also the performance of access time and manageability. As a result of performance comparison, RCP has showed about 10 ~ 50% of performance evolution compared to traditional policies, Greedy and Cost-benefit methods, by write throughputs.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.19-27
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• 2015

Due to the advantages of fast read/write operation and low power consumption, SSD(Solid State Drive) is now widely adopted as storage device of smart phone, laptop computer, server, etc. However, the shortcomings of SSD such as limited number of write operations and asymmetric read/write operation lead to the problem of shortened life span of SSD. Therefore, the block replacement policy of SSD used as cache for HDD is very important. The existing solutions for improving the lifespan of SSD including the LARC scheme typically employ the LRU algorithm to manage the SSD blocks, which may increase the miss rate in SSD due to the replacement of frequently used block instead of rarely used block. In this paper we propose a novel block replacement scheme which considers the block reuse interval to effectively handle various data read/write patterns. The proposed scheme replaces the block in SSD based on the recency decided by reuse interval and age along with hit ratio. Computer simulation using workload trace files reveals that the proposed scheme consistently improves the performance and lifespan of SSD by increasing the hit ratio and decreasing the number of write operations compared to the existing schemes including LARC.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.2
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• pp.245-261
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• 2019

Radioactive contaminant from a nuclear facility moves to the ecosystem by run-off or groundwater flow. Among the two mechanisms, contaminant plume through a river can be easily detected through a surface water monitoring system, but radioactive contaminant transport in groundwater is difficult to monitor because of lack of information on flow path. To understand the contaminant flow in groundwater, understanding of the geo-environment is needed. We suggest a method to decide on monitoring location and points around an imaginary nuclear facility by using the results of site characterization in the study area. To decide the location of a monitoring well, groundwater flow modeling around the study area was conducted. The results show that, taking account of groundwater flow direction, the monitoring well should be located at the downstream area. Also, monitoring sections in the monitoring well were selected, points at which groundwater moves fast through the flow path. The method suggested in the study will be widely used to detect potential groundwater contamination in the field of oil storage caverns, pollution by agricultural use, as well as nuclear use facilities including nuclear power plants.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.126-132
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• 2022

Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• Journal of Yeungnam Medical Science
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• v.14 no.1
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• pp.137-154
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• 1997

The aim of the present investigation has, been to evaluate the depletion pattern of the supercompensated glycogen of hindlimb muscles during strenous exercise in rats. The plan of the maximizing muscle glycogen stores is based on the fact that a glycogen-depleted muscle by exercise will have an increased avidity for glycogen when exposed to a high carbohydrate diet. The glycogen concentration of soleus, red gastrocnemius and plantaris muscle, and liver was measured at 0, 30 and 60 minutes during treadmill exercise. The experimental animals were divided into 5 group - Normal(N), Control(C), 1Hour(1HR:after 1hour of glucose ingestion), 2Hour(2HR:after 2hour of glucose ingestion) and Exercise-1Hour(EX-1HR:glucose ingestion after 1 hour of preloading treadmill exercise)group - for glycogen storage study. The glycogen concentration of soleus, red gastrocnemius and plantaris muscles in N group was $4.57{\pm}0.34$, 5.11+0.24 and $6.55{\pm}0.20mg/gm\;wet\;wt.$, respectively. The glycogen concentration of soleus and red gastrocnemius in EX-1HR group were about 1.9 and 1.8 times than that of N group, respectively, but the concentration of plantaris was not higher than that of N group. The glycogen concentration of liver in N group was $41.0{\pm}1.47mg/gm\;wet\;wt.$ and the concentration of the overnight fasted C group was only 2.9% of the value of N group. The level of glycogen concentration of liver in the other glucose ingested groups(1HR, 2HR, including EX-1HR) was within 19 - 32% of that of N group. The blood glucose concentration of EX-1HR group was higher than that of N group, the plasma free fatty acid concentration of C and 2HR group was higher than that of N group, and the plasma insulin concentration of EX-1HR group was higher than that of N group. The concentrations of supercompensated glycogen of soleus and red gastrocnemius were rapidly decreased during 30 minutes of exercise but there was almost no changes of the concentration during the other 30 minutes of continuing exercise. The concentration of N group during 30 minutes of exercise was decreased but more slowly than those of EX-1HR group. The remaining level of glycogen after 60 minutes of exercise in EX-1HR group was higher than that of N group. Taken together, the mobilization of endogenous muscle glycogen at the first stage of exercise was proportioned to the initial level of glycogen concentration, and later on, when exercise continued, the muscle glycogen level was stabilized. And the remaining level of supercompensated muscle glycogen after 60 minutes of exercise was higher than that of normally stored glycogen level. The mobilization of the glycogen stroed in slow and fast oxidative muscle fibers is faster than in the fast glycolytic muscle fibers during strenous exercise.

• Korean Journal of Poultry Science
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• v.43 no.4
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• pp.197-206
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• 2016

This work was carried out to investigate effects of the freezing/thawing method on duck meat kept in a freezer for a month. The meats used were breast muscle collected from Korean native ducks (KND) that were fed for 8 weeks (2.8 kg of live weight). Forty-five samples were used after being frozen in storage for one month and were then divided into 5 treatments (3 replications/treatment, 3 samples/replication). Five treatments (CON, FFFT, FFST, SFFT and SFST) were control groups (CON) and four were experimental groups, using $2{\times}2$ complex factors with two freezing methods (fast freezing, FF, $-50^{\circ}C$ in a deep freezer; slow freezing, SF, $-20^{\circ}C$ in a common freezer) and two thawing methods (fast thawing, FT, 5 h $12^{\circ}C$ with flow water; slow thawing, ST, 24 h $5^{\circ}C$ in a refrigerator). Lightness of KND meat in FF and FT groups was lower than that of control (P<0.05). Yellowness of KND meat of the ST group was higher than that of control (P<0.05). Cooking loss (CL) and water holding capacity (WHC) of KND meat in the control were lower than those of the freezing and thawing groups (P<0.01, P<0.05), but shear force (SF) of the control was higher than that of other groups (P<0.01). Moisture content of the ST group was higher than that of the FT group (P<0.05), and protein content of the FF group was higher than that of control (P<0.05). Stearic acid (C18:0) of the SF group was higher than that of the FF group (P<0.05). Arachidonic acid (C20:4n6) of control was higher than that of the SF and ST groups (P<0.01, P<0.05). Alanine, aspartic acid, glutamic acid, serine, and tyrosine content of the control were lower than that of the freezing and thawing groups (P<0.05). These results show that freezing and thawing methods affect meat color, shear force, cooking loss, and WHC-related water content.