• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.365-373
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• 2003

In this paper, we design a versatle RS decoder which can decode RS codes of any block length n as well as any message length k, based on a modified Euclid's algorithm (MEA). This unique feature is favorable for a shortened RS code of any block length it eliminates the need to insert zeros before decoding a shortened RS code. Furthermore, the value of error correcting capability t can be changed in real time at every codeword block. Thus, when a return channel is available, the error correcting capability can be adaptiverly altered according to channel state. The decoder permits 4-step pipelined processing : (1) syndrome calculation (2) MEA block (3) error magnitude calculation (4) decoder failure check. Each step is designed to form a structure suitable for decoding a RS code with varying block length. A new architecture is proposed for a MEA block in step (2) and an architecture of outputting in reversed order is employed for a polynomial evaluation in step (3). To maintain to throughput rate with less circuitry, the MEA block uses not only a multiplexing and recursive technique but also an overclocking technique. The adaptive RS decoder over GF($2^8$) with the maximal error correcting capability of 10 has been designed in VHDL, and successfully synthesized in a FPGA.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Science Education
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• v.47 no.3
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• pp.225-237
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• 2023

The purpose of this study is to explore the perceptions of elementary pre-service teachers regarding their interest in science. A survey was conducted among 187 elementary pre-service teachers enrolled at Non-Metropolitan Area A University of Education. Data collection was carried out concurrently with three elementary pre-service teachers who agreed to participate in online interviews. The survey responses provided by the elementary pre-service teachers were analyzed using a qualitative text analysis method. Interest in science was observed to decrease during middle school, followed by the upper grades of elementary school and then the lower grades. The reasons for the decline in interest in science were interpreted as stemming from negative experiences with science education within the context of individual circumstances in the school setting. Strategies to address the decline and enhance interest in science were discussed across individual, family, school, teacher, local community, and national levels, considering both short-term and long-term perspectives. These strategies encompassed various inquiry activities and experiences related to the field of science, engagement in science-related activities, student-centered instruction, teacher professional development, support for elementary students and teachers, and policy measures. The multifaceted approach and efforts aimed to open avenues for positive feedback regarding science on an individual level and foster experiences related to science were interpreted as part of an effort to counteract the decline in interest in science. Lastly, given the current situation of declining interest in science and the need to enhance students' interest, it was implicitly and explicitly discussed that pre-service teachers should focus on improving their expertise in curriculum instruction. This research, by exploring the conceptual characteristics of interest in science, perceptions of changes, and educational needs related to interest in science among elementary pre-service teachers, is expected to have academic significance as foundational research data for the current status of declining interest in science.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.23 no.1
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• pp.5-20
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• 1997

War and poverty depress the consumption of cosmetics, while peace and prosperity encourage their proliferation. With the end of World War II, the US, Europe and Japan witnessed rapid growth of their cosmetic industries. The ending of the Cold War has stimulated the growth of the industry in Eastern Europe. Improved economies, and mass communication are also responsible for the fast growth of the cosmetic industries in many Asian nations. The rapid development of the cosmetic industry in mainland China over the past decade proves that changing economies and political climates can deeply affect the health of our business. In addition to war, economy, political climate and mass communication, factors such as lifestyle, religion, morality and value concepts, can also affect the growth of our industry. Cosmetics are the product of the society. As society and the needs of its people change, cosmetics also evolve with respect to their contents, packaging, distribution, marketing concepts, and emphasis. In many ways, cosmetics mirror our society, reflecting social changes. Until the early 70's, cosmetics in the US were primarily developed for white women. The civil rights movement of the 60's gave birth to ethnic cosmetics, and products designed for African-Americans became popular in the 70's and 80's. The consumerism of the 70's led the FDA to tighten cosmetic regulations, forcing manufacturers to disclose ingredients on their labels. The result was the spread of safety-oriented, "hypoallergenic" cosmetics and more selective use of ingredients. The new ingredient labeling law in Europe is also likely to affect the manner in which development chemists choose ingredients for new products. Environmental pollution, too, can affect cosmetics trends. For example, the concern over ozone depletion in the stratosphere has promoted the consumption of suncare products. Similarly, the popularity of natural cosmetic ingredients, the search of non-animal testing methods, and ecology-conscious cosmetic packaging seen in recent years all reflect the profound influences of our changing world. In the 1980's, a class of efficacy-oriented skin-care products, which the New York Times dubbed "serious" cosmetics, emerged in the US. "Cosmeceuticals" refer to hybrids of cosmetics and pharmaceuticals which have gained importance in the US in the 90's and are quickly spreading world-wide. In spite of regulatory problems, consumer demand and new technologies continue to encourage their development. New classes of cosmeceuticals are emerging to meet the demands of increasingly affluent Asian consumers as we enter the 21st century. as we enter the 21st century.

• The Korean Journal of Petroleum Geology
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• v.14 no.1
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• pp.1-11
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• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.1
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• pp.161-174
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• 1997

Omega-3 fatty acids have been major research interests in medical and nutritional science relating to life sciences since after the epidemiologic data on Green3and Eskimos reported by several researchers clearly showed fewer per capita deaths from heart diseases and a lower incidence of adult diseases. Linolenic acid(LNA) is an essential fatty acid for human beings as well as linoleic acid(LA) due to the fact that vertebrates lack an enzyme required to incorporate a double bond beyond carbon 9 in the chain. In addition the ratio of omega-6 and 3 fatty acids seems to be important in terms of alleviation of heart diseases since LA and LNA competes for the metabolic pathways of eicosanoids synthesis. High consumption of omega-3 fatty acids in seafoods may control heart diseases by reducing blood cholesterol, triglyceride, VLDL, LDL and increasing HDL and by inhibiting plaque development through the formation of antiaggregatory substances like PGI$_2$, PGI$_3$ and TXA$_3$ metabolized from LNA. Omega 3 fatty acids also play an important role in neuronal developments and visual functioning, in turn influence learning behaviors. Current dietary sources of omega-3 fatty acids are limited mostly to seafoods, leafy vegetables, marine and some seed oils and the most appropriate way to provide omega-3 fatty acids is as a part of the normal dietary regimen. The efforts to enhance the intake of omega-3 fatty acids due to several beneficial effects have been made nowadays by way of food processing technology. Two different ways can be applied: one is add Purified and concentrated omega-3 fatty acids into foods and the other is to produce foods with high amounts of omega-3 fatty acids by raising animals with specially formulated feed best for the transfer of omega-3 fatty acids. Recently, items of manufactured and marketed omega-3 fatty acids fortified foodstuffs are pork, milk, cheese, egg, formula milk and ham. In domestic food market, many of them are distributed already, but problem is that nutritional informations on the amounts of omega-3 fatty acids are not presented on the labeling, which might cause distrust of consumers on those products, result in lower sales volumes. It would be very much wise if we consume natural products, result in lower sales volumes. It would be very much wise if we consume natural products high in omega-3 fatty acids to Promote health related to many types of adult diseases rather than processed foods fortified with omega-3 fatty acids.

• Journal of the Korean Magnetics Society
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• v.14 no.2
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• pp.76-82
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• 2004

Crystallographic and magnetic properties for Brownmillerite-type oxides $Ca_{1-x}$Sr$_{x}$FeO$_{2.5}$ (x = 0, 0.3, 0.5, 0.7, 1.0) were investigated using x-ray diffraction (XRD) and Mossbauer spectroscopy. Polycrystalline samples were prepared by conventional solid-state reaction method. Information on exact crystalline structures, lattice parameters, bond lengths and bond angles were obtained by refining their XRD profiles using a Rietveld method. The crystal structures were found to be all orthorhombic with space group Icmm (x = 0, 0.3) and Icmm (x = 0.5, 0.7, 1.0) The lattice parameters increased monotonically with increasing Sr concentration. Both the tetrahedral and the octahedral sites were considerably distorted and elongated along b-axis. While bond lengths and bond angles O-Fe-O tend to increase minutely with the increase of Sr content, bond angles Fe-O-Fe decreased accordingly. The Mossbauer spectra showed two sets of sharp sextets originating from ferric ions occupying the tetrahedral and the octahedral sites under the magnetic transition temperature T$_{N}$. Regardless of the compositions x, the electric quadrupole splittings were -0.3 mm/s and 0.4 mm/s for the octahedral and the tetrahedral site, respectively. Above T$_{N}$, the Mossbauer spectra showed the paramagnetic doublets whose electric quadrupole splittings were about 1.6 mm/s, irrespective of compositions x. T$_{N}$ was found to decrease monotonically with the increase of Sr concentration. Ratios of absorption area for the two sites were almost 1:1 up to as high as 0.95 T$_{N}$ for all x. The result of the Debye temperature indicated that the inter-atomic binding force for the Fe atoms in the tetrahedral site was stronger than that for the octahedral site.hedral site.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.156-158
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• 2009

Purpose: Since radiopharmaceuticals are intended for human administration, it is imperative that we should undergo quality control very strictly. Now almost all the PET laboratories have adopted Bacterial Endotoxin Test as the stand quality control method to monitor whether pyrogen is free or not in the product vial containing crude solution. The aim of this study is to find out the reason why false positive result is observed when using commercially available test vial. Materials and Methods: For this experiment, we used commercially available single test kit (Associates of Cape Code. Inc. USA) and we made pH samples by mixing each buffer whose pH ranges are 1.0 to 12.0. Otherwise we made Ethanol samples diluted with distilled water. After making test samples, it added 0.2 mL to the test vial. Assay mixture in the test vial was incubated in a water bath (Chang Shin Co. KOR) for 60 min at $35{\pm}2^{\circ}C$. Results: After incubation period ($60{\pm}1^{\circ}C$), we inverted the test vial about $180^{\circ}$ To know what pH and how many percentage of Ethanol (Fisher Scientific Korea. Ltd) will affect the reaction. With pH buffer, false positive result was observed at pH 1.0 to 5.0 and 7.7 to 12.6 but at pH 5.2 to.7.5, the test results show negative. It's very strange that we couldn't observe negative test result with Tris buffer at pH 8.4, 8.6, 8.8, 9.0. in other case Ethanol, the test result was seen with 5 to 10% Ethanol. But to my surprise we could see very thick gel formation with 100% Ethanol. Conclusions: In this study, we could notice that pH which is too much acidic or alkalic or high concentrated Ethanol would affect Bacterial Endotoxin Test result. As you know, LAL test is sensitive and very reliable method. Therefore, we are needed to elicit the accurate test result as possible as we can.