• Journal of Appropriate Technology
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• v.6 no.2
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• pp.151-162
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• 2020

Education is one of the priority sectors specified in Tanzania, and it has committed to provide 11 years of compulsory free basic education for all from pre-primary to lower secondary level. Despite the Government's efforts to provide free basic education to all children, there are 2.0 million (23.2 per cent) out of 8.5 million children at the primary school age of 7-13, who are out of school in Tanzania. The ICT class should be offered as a regular class in all secondary schools in Tanzania, recommended by the ministry of education. However, many schools are struggling to implement this mandate. Most of schools offer the ICT class with theory without any real hardware. Some schools were given with computers but they were not maintained for operation. There is a huge task to make ICT education universal. Main issues include: remoteness (off-grid area), lack of ICT teachers, lack of resources such as hardware, infrastructure, and lack of practical lessons or projects to be used at schools. An innovative blended ICT/STEM education program is being conducted not only for Tanzanian public and private/international schools, but also for out-of-school adolescents through institutions, NGO centers, home visits and at the E3 Empower academy center. For effective STEM education to take place and remain sustainable, more practical curriculum, and close-up teacher support need to be accompanied concurrently. Practical, project-based simple coding lessons have been developed and employed that students experience true learning. The effectiveness of the curriculum has been demonstrated in various project centers, and it showed that students are showing new interests in exploring new discovery, even though this was a totally new area for them. It has been designed for an easy replication, thus students who learned can repeat the lessons themselves to other students. The ultimate purpose of this project is to have IT education offered as universally as possible throughout the whole Tanzania. Quality education for all children is a key for better future for all. Previously it was hoped that education with discipline will improve the active learning. But now more than ever, we believe that children have the ability to learn on their own with given proper STEM education tools, guidelines and environment. This gives promising hope to all of us, including those in the developing countries.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Korean journal of applied entomology
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• v.56 no.3
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• pp.301-308
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• 2017

Locusts, Locusta migratoria (Orthoptera: Acrididae) are periodical unpredictable agricultural pests worldwide and cause serious damage to crop production; however, little consideration has been given to the management of this pest. Herein, we constructed a locust-pathogenic fungal library and confirmed that some fungi could be used as resources for locust management. First, the entomopathogenic fungi were collected from sampled soils using a Tenebrio molitor-based baiting system. For the locust assay, a locust colony was obtained from the National Institute of Agricultural Science and Technology. A total of 34 entomopathogenic fungal granules, which were produced by solid cultures, were placed in the plastic insect-rearing boxes (2 g/box) and nymphs of locust were contained in the box. In 3-7 days, mycosis was observed on the membranous cuticles of the head, abdomen, and legs of locusts. In particular, Metarhizium anisopliae, M. lepidiotae, and Clonostachys rogersoniana exhibited high virulence against the locust. Given that the 34 isolates could be used in field applications, their conidial production and stability (thermotolerance) were further characterized. In the thermotolerance assay, Paecilomyces and Purpureocillium isolates had higher thermotolerance than the other isolates. Most of the fungal isolates produced ca. >$1{\times}10^8conidia/g$ on millet grain medium. In a greenhouse trial, the granular application of M. anisopliae isolate on the soil surface resulted in 85.7% control efficacy. This work suggests that entomopathogenic fungi in a granular form can be effectively used to control the migratory locust.

• Korean Journal of Oriental Medicine
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• v.3 no.1
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• pp.1-15
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• 1997

${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$(1445) is a book compiled the medical achievements of China and Choseon in those times and it's our source of pride to have it In this country. It also deserves careful investigation since this book can provide some clues of features of missing books in China and Korea. The extent of accuracy of xylographica of old books determines the possiblity of in depth further study. So authors attempted to investigate the xylographica of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ one of the 3 main books in Korea. Previous investigation done by Miki Sakae and Kim Doo Jong are noticeable. On the basis of their respective works, we analyzed 'Annals of the Choseon Dynasty' to find records related with ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ and estimated the situation of its publication. We tried figure the situation of those times of China, Japan and Korea(including North Korea) and tried to estimate the book's original xylographica as much as we could. By King Sejong's command, the first draft of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ consisted of 365 books was made by collaboration of civil officials and medical officers during the period from 1443 to 1445. And then from 1451(first year of Moonjong's reign) to 1464(l0th year of Sejo's reign) lots of manpowers were employed and through the process of countless erasure, proofreading, arrangement and rearrangement revised version of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ which is called by Sejo text was completed. After 3 years of wood engraving work, the first printed form of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ (alternately called Seongjong text) in folding case consisted of 266 chapters, 264 volumes came into the world in 1477.(8th year of Seongjong's reign). This was 32 years after the initial completion of the edition. So ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ exists in three forms as Sejong text, Sejo text and Seongjong text respectively. Since those texts were plundered during the Japanese invasion of Korea in 1592, none of the original copy remains within korea. The texts were constantly moved to kadeungcheongieong, to Kongdeungpyeongio, Jesookoan of Edo, to East University of department of classic books, to Cheoncho archives, to the Imperial Museum and finally is kept in the royal palace at present. (Doseoryo text Eulhae printing type) Reduced-size republication books of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ in wooden type were imported at the time of 'Byeongja Korea-Japan Treaty in 1876' and of those 2 books, one copy was treasured in the Royal Household of the Yi Dynasty and than was lost during the Korean War circa 1950. The other remaining copy has been kept succesively by Kojong's imperial grant, Royal doctor Hong Cheol Bo, Hong Taek Joo, Hong Ik Pyo the book agent, and now is kept In Yonsei University Library and this is the only existing copy in Korea at present. In 1965, Dongyang Medical college published the transcription version of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ consisting of 11 books and then in 1981 after edition and arrangement by Choonghoa(中華) publishing company, photoprint copy of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ was published in Keumgang(金剛) publishing company In 1991, October Yeokang(驛江) publishing company producd photocopies of ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ which were previously translated into Korean by North Korea Institute of Oriental Medicine and then issued by medical publishing company. In China, two institutes, Zhejiang Institute of Traditional Chinese Medicine and Huzhou Traditional Chinese Medical Hospital cooperated to publish a revised and marked text consiting of 11 books by adding marking points to japanse Edohakhoondang text which were used as a reference. Both the korean and chinese texts issued were grounded by the ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ kept in the royal palace. Any further study concerning ${\ulcorner}$Classified Collection of Medical Prescriptions${\lrcorner}$ can acquire its accuracy and objectivity when the japanese text kept in the royal palace is taken as an original copy.

• Radiation Oncology Journal
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• v.17 no.2
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• pp.151-157
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• 1999

Purpose : By sequencing the Erpressed Sequence Tags of human 걸ermal papilla CDNA library, we identified a clone named K872 of which the expression decreased during differentiation of HL6O cell line. Materials and Methods : K872 plasmid DNA was isolated according to QIA plasmid extraction kit (Qiagen GmbH, Germany). The nucleotide sequencing was performed by Sanger's method with K872 plasmid DNA. The most updated GenBank EMBL necleic acid banks were searched through the internet by using BLAST (Basic Local Alignment Search Tools) program. Nothern bots were performed using RNA isolated from various human tissues and cancer cell lines. The gene expression of the fusion protein was achieved by His-Patch Thiofusicn expression system and the protein product was identified on SDS-PAGE. Results : K872 clone is 1006 nucleotides long, and has a coding region of 675 nucleotides and a 3' non-coding region of 280 nucleotides. The presumed open reading frame starting at the 5' terminus of K872 encodes 226 amino acids, including the initiation methionine residue. The amino acid sequence deduced from the open reading frame of K872 shares $70\%$, identity with that of rat glutathione 5-transferase kappa 1 (rGSTKl). The transcripts were expressed in a variety of human tissues and cancer cells. The levels of transcript were relatively high in those tissues such as heart, skeletal muscle, and peripheral blood leukocyte. It is noteworthy that K872 was found to be abundantly expressed in coloreetal cancer and melanoma cell lines. Conclusion : Homology search result suggests that K872 clone is the human homolog of the rGSTK1 which is known to be involved in the resistance of cytotoxic therapy. We propose that meticulous functional analysis should be followed to confirm that.

• Journal of the Daesoon Academy of Sciences
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• v.27
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• pp.201-243
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• 2016

This paper analyzes the research trends from 358 scholarly articles published in the Journal of Daesoon Academy of Sciences from the first published journal in 1996 to the most recent journal published on the 25^th of 2015 and proposes ideas for improvement. First of all, "The Journal of Daesoon Academy of Sciences" does not meet the standards required by the National Research Foundation, falling short of the most important conditions for the registration such as the periodicity and punctuality expected from academic journals. Furthermore, in terms of the Bibliometrical analysis, the number of articles published by the journal is decreasing and the consistency, with regards to rules and principles regulating publication details and bibliography formats, is nonexistent. Although various authors seemed to be meeting these criteria on the surface, the ratio of co-authored articles is too small. Securing researchers specializing in Daesoon Thought for expanding the size of the journal is important, but it is also important to diversify the research topics through exchanging ideas among researchers from various organizations. Here are some ideas for the improvement of the Journal of Daesoon Academy of Sciences: First, in order to meet the standards for punctuality and periodicity, it would be best to publish the journal twice a year with 12 to 15 articles. Second, the journal must become searchable through the creation of a database. Third, the key words and abstracts of articles must be written in Korean and English to facilitate the sharing of articles among researchers. Fourth, the journal must have a diverse and outstanding editorial board which takes into account the geographical situations of its board members. Fifth, the Journal must include articles on relevant topics that reflect the core topics of the Daesoon Thought and other studies. Sixth, articles must have a front page that contains bibliographical items to convey information to the reader. Seventh, it is essential that the journal have a clear publication date detailing the year, month, and day as well as a standard numbering scheme (i.e, Vol. and no).

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.3-4
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• 2004

Results will be presented from two field studies that evaluated the in-situ treatment of chlorinated aliphatic hydrocarbons (CAHs) using aerobic cometabolism. In the first study, a cometabolic air sparging (CAS) demonstration was conducted at McClellan Air Force Base (AFB), California, to treat chlorinated aliphatic hydrocarbons (CAHs) in groundwater using propane as the cometabolic substrate. A propane-biostimulated zone was sparged with a propane/air mixture and a control zone was sparged with air alone. Propane-utilizers were effectively stimulated in the saturated zone with repeated intermediate sparging of propane and air. Propane delivery, however, was not uniform, with propane mainly observed in down-gradient observation wells. Trichloroethene (TCE), cis-1, 2-dichloroethene (c-DCE), and dissolved oxygen (DO) concentration levels decreased in proportion with propane usage, with c-DCE decreasing more rapidly than TCE. The more rapid removal of c-DCE indicated biotransformation and not just physical removal by stripping. Propane utilization rates and rates of CAH removal slowed after three to four months of repeated propane additions, which coincided with tile depletion of nitrogen (as nitrate). Ammonia was then added to the propane/air mixture as a nitrogen source. After a six-month period between propane additions, rapid propane-utilization was observed. Nitrate was present due to groundwater flow into the treatment zone and/or by the oxidation of tile previously injected ammonia. In the propane-stimulated zone, c-DCE concentrations decreased below tile detection limit (1 $\mu$g/L), and TCE concentrations ranged from less than 5 $\mu$g/L to 30 $\mu$g/L, representing removals of 90 to 97%. In the air sparged control zone, TCE was removed at only two monitoring locations nearest the sparge-well, to concentrations of 15 $\mu$g/L and 60 $\mu$g/L. The responses indicate that stripping as well as biological treatment were responsible for the removal of contaminants in the biostimulated zone, with biostimulation enhancing removals to lower contaminant levels. As part of that study bacterial population shifts that occurred in the groundwater during CAS and air sparging control were evaluated by length heterogeneity polymerase chain reaction (LH-PCR) fragment analysis. The results showed that an organism(5) that had a fragment size of 385 base pairs (385 bp) was positively correlated with propane removal rates. The 385 bp fragment consisted of up to 83% of the total fragments in the analysis when propane removal rates peaked. A 16S rRNA clone library made from the bacteria sampled in propane sparged groundwater included clones of a TM7 division bacterium that had a 385bp LH-PCR fragment; no other bacterial species with this fragment size were detected. Both propane removal rates and the 385bp LH-PCR fragment decreased as nitrate levels in the groundwater decreased. In the second study the potential for bioaugmentation of a butane culture was evaluated in a series of field tests conducted at the Moffett Field Air Station in California. A butane-utilizing mixed culture that was effective in transforming 1, 1-dichloroethene (1, 1-DCE), 1, 1, 1-trichloroethane (1, 1, 1-TCA), and 1, 1-dichloroethane (1, 1-DCA) was added to the saturated zone at the test site. This mixture of contaminants was evaluated since they are often present as together as the result of 1, 1, 1-TCA contamination and the abiotic and biotic transformation of 1, 1, 1-TCA to 1, 1-DCE and 1, 1-DCA. Model simulations were performed prior to the initiation of the field study. The simulations were performed with a transport code that included processes for in-situ cometabolism, including microbial growth and decay, substrate and oxygen utilization, and the cometabolism of dual contaminants (1, 1-DCE and 1, 1, 1-TCA). Based on the results of detailed kinetic studies with the culture, cometabolic transformation kinetics were incorporated that butane mixed-inhibition on 1, 1-DCE and 1, 1, 1-TCA transformation, and competitive inhibition of 1, 1-DCE and 1, 1, 1-TCA on butane utilization. A transformation capacity term was also included in the model formation that results in cell loss due to contaminant transformation. Parameters for the model simulations were determined independently in kinetic studies with the butane-utilizing culture and through batch microcosm tests with groundwater and aquifer solids from the field test zone with the butane-utilizing culture added. In microcosm tests, the model simulated well the repetitive utilization of butane and cometabolism of 1.1, 1-TCA and 1, 1-DCE, as well as the transformation of 1, 1-DCE as it was repeatedly transformed at increased aqueous concentrations. Model simulations were then performed under the transport conditions of the field test to explore the effects of the bioaugmentation dose and the response of the system to tile biostimulation with alternating pulses of dissolved butane and oxygen in the presence of 1, 1-DCE (50 $\mu$g/L) and 1, 1, 1-TCA (250 $\mu$g/L). A uniform aquifer bioaugmentation dose of 0.5 mg/L of cells resulted in complete utilization of the butane 2-meters downgradient of the injection well within 200-hrs of bioaugmentation and butane addition. 1, 1-DCE was much more rapidly transformed than 1, 1, 1-TCA, and efficient 1, 1, 1-TCA removal occurred only after 1, 1-DCE and butane were decreased in concentration. The simulations demonstrated the strong inhibition of both 1, 1-DCE and butane on 1, 1, 1-TCA transformation, and the more rapid 1, 1-DCE transformation kinetics. Results of tile field demonstration indicated that bioaugmentation was successfully implemented; however it was difficult to maintain effective treatment for long periods of time (50 days or more). The demonstration showed that the bioaugmented experimental leg effectively transformed 1, 1-DCE and 1, 1-DCA, and was somewhat effective in transforming 1, 1, 1-TCA. The indigenous experimental leg treated in the same way as the bioaugmented leg was much less effective in treating the contaminant mixture. The best operating performance was achieved in the bioaugmented leg with about over 90%, 80%, 60 % removal for 1, 1-DCE, 1, 1-DCA, and 1, 1, 1-TCA, respectively. Molecular methods were used to track and enumerate the bioaugmented culture in the test zone. Real Time PCR analysis was used to on enumerate the bioaugmented culture. The results show higher numbers of the bioaugmented microorganisms were present in the treatment zone groundwater when the contaminants were being effective transformed. A decrease in these numbers was associated with a reduction in treatment performance. The results of the field tests indicated that although bioaugmentation can be successfully implemented, competition for the growth substrate (butane) by the indigenous microorganisms likely lead to the decrease in long-term performance.