• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.1-8
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• 2015

Wear leveling techniques have been studied to prolong the lifetime of NAND flash memory. Most of studies have used Program/Erase(P/E) cycles as wear index for wear leveling. Unfortunately, P/E cycles could not predict the real lifetime of NAND flash blocks. Therefore, these algorithms have the limited performance from prolonging the lifetime when applied to the SSD. In order to apply the real lifetime, wear leveling algorithms, which use raw Bit Error Rate(rBER) as wear index, have been studied in recent years. In this paper, we propose CrEWL(Cold data identification using raw Bit error rate in Wear Leveling), which uses rBER as wear index to apply to the real lifetime. The proposed wear leveling reduces an overhead of garbage collections by using HBSQ(Hot Block Sequence Queue) which identifies hot data. In order to reduce overhead of wear leveling, CrEWL does not perform wear leveling until rBER of the some blocks reaches a threshold value. We evaluate CrEWL in comparison with the previous studies under the traces having the different Hot/Cold rate, and the experimental results show that our wear leveling technique can reduce the overhead up to 41% and prolong the lifetime up to 72% compared with previous wear leveling techniques.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.1-8
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• 2017

In this paper, we propose a new hybrid wear leveling technique for NAND Flash memory, called Time-Aware Wear Leveling (TAWL). Our proposal prolongs the lifetime of NAND Flash memory by using dynamic wear leveling technique which considers the wear level of hot blocks as well as static wear leveling technique which considers the wear level of the whole blocks. TAWL also reduces the overhead of garbage collection by separating hot data and cold data using update frequency rate. We showed that TAWL enhanced the lifetime of NAND flash memory up to 220% compared with previous wear leveling techniques and our technique also reduced the number of copy operations of garbage collections by separating hot and cold data up to 45%.

• Journal of the Korean Society of Costume
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• v.52 no.2
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• pp.139-150
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• 2002

The purpose of this study was to explore the effects of meteorological factors on sales of apparel products. Basic fiat came out daily meteorological data and sales data of apparel products in department store from 1998 to 2000. Four factors(the average temperature, rainfall, wind velocity, sunshine duration) from the nine meteorological factors were selected and were collected with Korea Meteorological Administration. Sales data were collected with business strategy department of H (department store in Seoul. The sales data were divided into six classifications, which are woman's wear, men's wear, children's wear, golf wear, sports wear, and inner wear. The results of this study were as follows: 1) Sales of apparel products were significantly correlated with the average temperature, rainfall, wind velocity, sunshine duration. Among the meteorological factors, temperature turned out to be the most influential in apparel sales and then the amount of rainfall, sunshine duration affected sales according to apparel classifications differently. 2) There were some differences among the apparel classifications in the effect of meteorological factors on the sales of apparel. In the spring. the higher the temperature was, the higher the sales of women's wear and golf wear were, but the lower the sales of children's wear, sports wear and inner wear were. In the summer, The higher the amount of rainfall was, the lower the sales of all the apparel classification were. The higher the temperature was, the higher the sales of sports wear were. In the fall, the lower the temperature was, the higher the sales of all the apparel classification except snorts wear were. In the winter, the meteorological factors had little effect on the sales of women's wear, men's wear and children's wear. The higher the temperature was, the higher the sales of golf wear were. The lower the temperature was, the higher the sales of sports wear were.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.299-300
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• 2007

In this paper, slip wear phenomenon of train was studied by traction force of acceleration and braking force of deceleration. First, the slip wear phenomenon on train operation mode was analyzed when powering, coasting and braking each and then rail wear was analyzed from the slip wear data. Especially, the data proved correlation between slip wear and deceleration rather than acceleration. Second, If velocity of a train is constant, even though the velocity is high, ATO logging data and measurement data proved that the rail wear is not serious. It will help for efficient braking force operation providing fundamental data to braking step control.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• KSTLE International Journal
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• v.6 no.1
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• pp.21-27
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• 2005

A technique for a wear volume calculation is improved and verified in this research. The wear profile data measured by a surface roughness tester is used. The present technique uses a data flattening, the FFT and the windowing procedure, which is used for a general signal processing. The measured value of an average roughness of an unworn surfnce is used for the baseline of the integration for the volume calculation. The improvements from the previous technique are the procedures of the data flattening and the determination of a baseline. It is found that the flattening procedure efnciently manipulates the raw data when the levels of it are not horizontal, which enables us to calculate the volume reasonably well and readily. By comparing it with the weight loss method by using artificial dents, the present method reveals more volume by aroung 3~10%. It is attributed to the protruded region of the specimen and the inaccuracy and data averaging during the weght loss measurement. From a thorough investigation, it is concluded that the present technique can provide an accurate wear volume.

• Journal of Fashion Business
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• v.25 no.2
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• pp.110-126
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• 2021

This study aims to explore consumers' perception regarding "one-mile wear" and "home wear" fashion, an emerging trend during the Coronavirus disease (COVID-19) pandemic, and to identify the changes in consumers' perception of this style before and after the pandemic. The data collection period was set as one year before and after the outbreak as of January 1, 2020, and blog posts with keywords "one-mile wear" and "home wear" were collected. Further, textual data crawled and refined using Python 3.7 libraries, and centralities were measured and visualized through NodeXL 1.0.1 and Ucinet 6. According to the results, first, consumers' perception regarding one-mile wear fashion was divided into the following eight categories: wearing situation, expected attribute, style, item, color, textile, shape, and target wearer. Second, before the pandemic, home wear was recognized as pajamas or indoor wear; after the pandemic, home wear was recognized as one-mile wear, outdoor wear, and daily wear. Moreover, keywords, such as "telecommuting", "social distancing", "untact", and "upper body", appeared after the pandemic. It was confirmed that consumers' perception of home wear was affected by the pandemic.

• Tribology and Lubricants
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• v.23 no.6
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• pp.301-305
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• 2007

The wear particle analysis has been known as very effective method to foreknow and decide a moving situation and a damage of machine parts by using the digital computer image processing. But it was not laid down and trusted to calculate shape parameters of wear particle and wear volume. In order to apply image processing method in the foreknowledge and decision of lubricated condition, it needs to verify the reliability of the calculated data by the image processing and to lay down the number of images and the amount of wear particle in one image. In this study, the lubricated friction experiment was carried out in order to establish the optimum image capture with the SM45C specimen under experiment condition. The wear particle data were calculated differently according to the number of image and the amount of wear particle in one image.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.5-12
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• 2004

The erosion wear of gun barrel occurs due to heat and chemical reactions. The high pressure and temperature in chamber increase the erosion wear. It is known that the metal phase transfer is the primary wear factor in a gun barrel under high temperature. In this paper, the tool of wear prediction in high pressure gun tube has been developed. The program developed has three modules such as DIRECT(interior ballistics analysis module), INVERSE(gun design module), and WEAR(wear prediction module). The prediction of wear was compared with the experimental data which was collected in the field unit. The prediction results shows good trend with the collected data.