• 보존과학연구
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• s.17
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• pp.161-182
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• 1996

In natural atmosphere, copper and copper alloy have been used to make buddha statues and ornaments of historic buildings since the abovementioned metals have corrosion resistance in some extent, and the patinaformed on the surface of the metals has provided the people aesthetic satisfaction with its beauty. But in atmosphere polluted by $SO_x$and $NO_x$, the patina layer does not work as a protective film, and it allows damages of the metal. Since 1992, Tokyo National Research Institute of Cultural Properties(TNRICP)has conducted studies on the influence of atmospheric pollution on metal cultural property held under open air. The Great Buddha Image which is located in Kamakura about 50km west from Tokyo, has been selected as one of the objects to study because it is made by copper alloy and it has stood exposed in the air for about a few hundreds years. Furthermore it is also the reason to study on it that there are many cultural properties in the surroundings of it. We have analysed the components and the structure of the corrosion products formed on the surface of the Buddha, have carried out exposure tests using the alloy samples which have simulated the components of the Great Image, and have observed climated and polluted air in order to discuss the relation between corrosion of metals in open air and conditions of the atmosphere. In this paper, the authors have described the components and the structure of the corrosion product formed on the surface of the Great Image by means of X-ray fluorescence spectroscopy and X-ray diffraction. The conclusions are as follows. (1) Sulfate patina composed mainly with brochantite were detected on the all sides of the Image and the amount of the patina is found more on the back of the Image facing to north. (2) Antlerite were detected on the back and a park of the left side facing to west, and formation of it was considered to have close relation with malignant atmosphere. (3) A big amount of chloride patina which mainly composed of atacamite were observed on the front facing to south. (4) Carbonate patina mainly composed of malachite were detected on the area where brochantite was often detected as well. It suggested that malachite had been transformed into brochantite by deteriorated atmosphere. (5) On the all sides of the Image, patina were observed together with copper oxides mainly composed of cuprous oxide. It showed that the surface layer of the Image consists of two layers : inner layer of oxide and outer layer of patina. (6) Corrosion products of lead which was a component of copperalloy were detected on the all sides : the main lead product found on the front was chlorophosphate whereas the one on the back was sulfate.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of Soil and Groundwater Environment
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• v.11 no.3
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• pp.43-51
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• 2006

Generally abandoned mine soils have serious problems for introducing vegetation such as nutrient deficiency, poor physical properties, and phytotoxicity due to high levels of heavy metals. It is required to improve soil amenity for revegetation. One of its strategies is using organic materials such as compost manure and sludge. The pot experiments was conducted to evaluate the effects of pig manure and municipal sewage sludge on revegetation of mining area soil surface with Artemisia princeps and Zoysia japonica. Application rate of pig manure and municipal sewage sludge was $75{\sim}225$ Mg/ha and $150{\sim}450$ Mg/ha, respectively. The results showed that the application of manure and sludge increased organic matter about two-fold and total nitrogen contents about five-fold of mine soil and improved the growth of plants in all treatments compared to the control. The result of plant tissue analysis showed that both plants accumulate Cd, Cu and Zn in root tissue rather than shoot tissues. Increased sludge application reduced Zn accumulation in both plant tissue. Sequential extraction results indicated that addition of soil amendment induced increment of organically bound fractions of Cu and Zn. Organically bound fraction of Zn was significantly increased from 7.84% to 13.58% in Artemisia princeps planted soil and from 7.84% to 14.16% in Zoysia japonica planted soil, thereby bioavailability of heavy metals was reduced. The results suggested that application of organic materials to mine soil can reduce phytotoxicity of heavy metals and be helpful in introducing successful revegetation.

• Economic and Environmental Geology
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• v.52 no.2
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• pp.129-139
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• 2019

This study investigates the spectral response of red lettuce (Lactuca sativa var crispa L.) to Zn concentration. The control group and the experimental groups treated with 1 mM(ZnT1), 5 mM(ZnT2), 10 mM(ZnT3), 50 mM(ZnT4), and 100 mM(ZnT5) were prepared for a pot experiment. Then, Zn concentration and spectral reflectance were measured for the different levels of Zn concentration in red lettuce. The Zn concentration of the control group had the range of 134-181 mg/kg, which was within the normal range of Zn concentration in uncontaminated crops. However, Zn concentration in the experimental group gradually increased with an increase in concentration of Zn injection. The spectral reflectance of red lettuce showed high peak in the red band due to anthocyanin, high reflectance in the infrared band due to the scattering effect of the cell structure, and absorption features associated with water. As Zn concentration in red lettuce leaves increased, the reflectance increased in the green and red bands and the reflectance decreased in the infrared band. The correlation analysis between Zn concentration and spectral reflectance showed that the reflectance of 700-1300 nm had a significant negative correlation with Zn concentration. The spectral band is a wavelength region closely related to the cell structure in the leaf, indicating possible cell destruction of leaf structure due to increased Zn concentration. In particular, 700-800 nm reflectance of the infrared band showed the strongest correlation with the Zn concentration. This study could be used to investigate the heavy metal contamination in soil around mining and agriculture area by spectroscopically recognizing heavy metal pollution of plant.

• Korean Journal of Heritage: History & Science
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• v.51 no.1
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• pp.4-31
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• 2018

The Neolithic pottery excavated from the Jungsandong site has been classified into four types of pottery (I: feldspar type, II: mica type, III: talc type and IV: asbestos type) according to their mineral composition. These four types of potteries generally appear to have undergone incomplete firing, while the level of oxidation in the type I pottery objects, which have a relatively higher clay content, was found to be particularly low. The type III objects, which have a high talc content, are judged to have been somewhat slow in removing carbon because they contain saponite belonging to the smectite group. Of the four types of pottery, type IV showed the highest redness and the most uniform characteristics, thus indicating a good level of oxidation. In particular, fixed carbide (C; 33.7 wt.%) with a thickness of about 1mm, and originating from organic substances, was detected inside the walls of the type I pottery, while the deep radial cracks in the outer surfaces of the pottery are thought to have been caused by repeated thermal shocks. Given that all of the pottery except for the type I artifacts are considered to be have been made for storage purposes, those containing talc and tremolite are easy to done liquid storing vessels based on an analysis of their material characteristics. As for the type II relics, which are composed of various minerals and exhibit poor physical properties, they seem to have been used for simple storage purposes. As domestic talc and asbestos mines were concentrated in the areas of Gyeonggi, Gangwon, Chungbuk, and Chungnam, it seems likely that talc and tremolite were produced as contiguous minerals. Considering the distance between the remains in Jungsandong and these mines and their geographical distribution, there is a possibility - albeit somewhat slight - that these mines were developed for the mining of various minerals. Although ultramafic rock masses - such as serpentine capable of generating talc and tremolite - have not been found in the Jungsandong area, limestone and biotite granite containing mica schist have been identified in the northwestern part of Yeongjong Island, indicating that small rock masses might have formed there in the past. Therefore, it is judged necessary to accumulate data on pottery containing talc and tremolite, other than the remains in Jungsandong, and to investigate the rocks and soils in the surrounding area with greater precision. The firing temperatures of the pottery found at the Jungsandong site were interpreted by analyzing the stability ranges of the mineral composition of each type. As a result, they have been estimated to range from 550 to $800^{\circ}C$ for the type I artifacts, and from 550 to $700^{\circ}C$ for the type I, II and IV artifacts. However, these temperatures are not the only factors to have affected their physical properties and firing temperature, and the types, particle sizes, and firing time of the clay should all be taken into consideration.

• Economic and Environmental Geology
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• v.54 no.6
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• pp.689-698
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• 2021

Since the mine reclamation scheme was implemented from 2007 in Korea, various remediation programs have been decontaminated the pollution associated with mining and 254 mines were managed to reclamation from 2011 to 2015. However, as the total amount of contaminated mine drainage has been increased due to the discovery of potential hazards and contaminated zone, more efficient and economical treatment technology is required. Therefore, in this study, the adsorption properties of arsenic was evaluated according to the adsorbents which were derived from water treatment sludge(Alum based adsorbent, ABA-500) and granular ferric hydroxide(GFH), already commercialized. The alum sludge and GFH adsorbents consisted of aluminum, silica materials and amorphous iron hydroxide, respectively. The point of zero charge of ABA-500 and GFH were 5.27 and 6.72, respectively. The result of the analysis of BET revealed that the specific surface area of GFH(257 m²·g^-1) was larger than ABA-500(126~136 m²·g^-1) and all the adsorbents were mesoporous materials inferred from N₂ adsorption-desorption isotherm. The adsorption capacity of adsorbents was compared with the batch experiments that were performed at different reaction times, pH, temperature and initial concentrations of arsenic. As a result of kinetic study, it was confirmed that arsenic was adsorbed rapidly in the order of GFH, ABA-500(granule) and ABA-500(3mm). The adsorption kinetics were fitted to the pseudo-second-order kinetic model for all three adsorbents. The amount of adsorbed arsenic was increased with low pH and high temperature regardless of adsorbents. When the adsorbents reacted at different initial concentrations of arsenic in an hour, ABA-500(granule) and GFH could remove the arsenic below the standard of drinking water if the concentration was below 0.2 mg·g^-1 and 1 mg·g^-1, respectively. The results suggested that the ABA-500(granule), a low-cost adsorbent, had the potential to field application at low contaminated mine drainage.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.69-79
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• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.457-473
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• 2023

Asbestos has been produced, imported and used in various industries in Korea over the past decades. Since asbestos causes fatal diseases such as malignant mesothelioma and lung cancer, the use of asbestos has been generally banned in Korea since 2009. However, there are still many asbestos-containing materials around us, and safe management is urgently needed. This study aims to examine asbestos-related trend changes using major asbestos-related keywords based on the asbestos trend analysis using big data for the past 32 years (1991 to 2022) in Korea. In addition, we reviewed both domestic trends related to the production, import, and use of asbestos before 1990 and asbestos-related policies from 2023 to 2027. From 1991 to 2000, main keywords related to asbestos were research, workers, carcinogens, and the environment because the carcinogenicity of asbestos was highlighted due to domestic production, import, and use of asbestos. From 2001 to 2010, the main keywords related to asbestos were lung cancer, litigation, carcinogens, exposure, and companies because lawsuits were initiated in the US and Japan in relation to carcinogenicity due to asbestos. From 2011 to 2020, the high ranking keywords related to asbestos were carcinogen, baseball field, school, slate, building, and abandoned asbestos mine due to the seriousness of the asbestos problem in Korea. From 2021 to present (2023), the main search keywords related to asbestos such as school, slate (asbestos cement), buildings, landscape stone, environmental impact assessment, apartment, and cement appeared.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.