• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.23-35
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• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.

• Clean Technology
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• v.20 no.4
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• pp.375-382
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• 2014

This work investigated the plasma-catalytic decomposition of isopropyl alcohol (IPA) and the behavior of the byproduct compounds over monolith-supported metal oxide catalysts. Iron oxide ($Fe_2O_3$) or copper oxide (CuO) was loaded on a monolithic porous ${\alpha}-Al_2O_3$ support, which was placed inside the coaxial electrodes of plasma reactor. The IPA decomposition efficiency itself hardly depended on the presence and type of metal oxides because the rate of plasma-induced decomposition was so fast, but the behavior of byproduct formation was largely affected by them. The concentrations of the unwanted byproducts, including acetone, formaldehyde, acetaldehyde, methane, carbon monoxide, etc., were in order of $Fe_2O_3/{\alpha}-Al_2O_3$ < $CuO/{\alpha}-Al_2O_3$ < ${\alpha}-Al_2O_3$ from low to high. Under the condition (flow rate: $1L\;min^{-1}$; IPA concentration: 5,000 ppm; $O_2$ content: 10%; discharge power: 47 W), the selectivity towards $CO_2$ was about 40, 80 and 95% for ${\alpha}-Al_2O_3$, $CuO/{\alpha}-Al_2O_3$ and $Fe_2O_3/{\alpha}-Al_2O_3$, respectively, indicating that $Fe_2O_3/{\alpha}-Al_2O_3$ is the most effective for plasma-catalytic oxidation of IPA. Unlike plasma-alone processes in which tar-like products formed from volatile organic compounds are deposited, the present plasma-catalyst hybrid system did not exhibit such a phenomenon, thus retaining the original catalytic activity.

• Korean Journal of Environment and Ecology
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• v.27 no.1
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• pp.113-126
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• 2013

This study was performed to introduce ecological education program as for reporting the current vegetation state within the remaining trees as ecological golf course and to provide basic data. The survey site was S Golf course, which is located in Woonseodong, Incheon city. Its total area was about $3,298,428m^2$, but the relict forest was about $225,143m^2$. Existing landuse, topological structure, the flora, actual vegetation, and plants community structure survey were performed within the relict forest. As result of comparing and analyzing the existing land use, the relict forest was distributed in the forested areas (89.2%) and around the area (10.8%) which had been bare land and SAMMOK earthen ramparts. There were two courses (Ocean and Hanul) with the relict forests. The ocean course was compared of a natural forest, such as Quercus spp. mixed forest, Quercus acutissima forest, Pinus thunbergii forest within the rock fields, and an artificial forest (Ailanthus altissima-Robinia pseudoacacia forest, Robinia pseudoacacia forest) and Quercus acutissima - Elaeagnus umbellata forest. On the Hanul course, Pinus rigida forest and Robinia pseudoacacia forest were the main vegetation, which were artificial forest. It was the contrast aspect of vegetation species in a natural forest, a restoration forest and an artificial forest, which were Q. spp. mixed forest 26~28 species in a natural forest within the vegetation type per investigation area, 3 Pinus thunbergii forest species, and 5~7 artificial forest species on the Hanul course. Based on these vegetation status, the Ocean course was designed into ecological theme spaces named 'Quercus spp.' indigenous forest, 'Pinus thunbergii' restoration forest and ecological story of 'SAMMOK earthen ramparts'. The Hannul course was designed into an artificial forest observation area of 'Robinia pseudoacacia' and 'Pinus rigida' and a fragrance forest area of 'Robinia pseudoacacia'. At the time of the discussion about the introduction of eco-friendly approval system of golf course, it would be estimated that this survey would work as a major material not only raising awareness of the golf course on the ecological environment but also providing programs that can contribute to the community.

• Clean Technology
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• v.27 no.4
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• pp.359-366
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• 2021

Halloysite nanotubes (HNTs), the multiwalled clay mineral with the composition of Al₂Si₂O₅(OH)₄·nH₂O, have been highlighted as a low-cost adsorbent for the removal of dyes from wastewater. Although a powder of halloysite presents a high specific surface area, forming media are significantly considered due to sludge-clogging induced by the water-bound agglomeration. However, higher firing temperature to achieve the structural durability of the media and lower utilization rate due to longer penetration depth into the media act as hurdles to increase the dye-adsorption capacity. In this work, the retention of the adsorption capacity of halloysite was evaluated with methylene blue solution after the heat treatment at 750 ℃. In order to improve the utilization rate, tubular media were fabricated by extrusion. The images taken by transmission electron microscopy show that HNTs present excellent structural stability under heat treatment. The HNTs also provide superb capacity retention for MB adsorption (93%, 18.5 mg g^-1), while the diatomite and Magnesol^® XL show 22% (7.65 mg g^-1) and 6% (11.7 mg g^-1), respectively. Additionally, compositing with lignin enhances adsorption capacity, and the heat treatment under the hydrogen atmosphere accelerates the adsorption in the early stage. Compared to the rod-type, the tubular halloysite media rapidly increases methylene blue adsorption capacity.

• Sijohaknonchong
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• v.44
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• pp.197-236
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• 2016

The aim of this study is to discover the distinctive aspects of Sijo in the 17th Century through five old music scores, "梁琴新譜Yangqeumsinbo", "白雲庵琴譜 baekwoonamgeumbo", "增補古琴譜jeungbogogeumbo", "延世大學校所藏琴譜geumbo in Yonsei University", "琴譜古geumbogo", which were compiled in this time period. First, four Sijo works are found from the "梁琴新譜Yangqeumsinbo" and one of them is noteworthy because it was sung as 中大葉Jungdaeyeop, 初中大葉 Chojungdaeyeop, 二中大葉Yijungdaeyeop and showed signs to fit the Sijo format type since the 17th century. In "白雲庵琴譜baekwoonamgeumbo", there are three Sijo works (one has recorded music scores and two don't) and one of them is discovered with last phrase being omitted. In "延世大學校所藏琴譜geumbo in Yonsei University", there are 9 Sijo works performed with 中大葉Jungdaeyeop. In "增補古琴譜 jeungbogogeumbo", there are three works performed with 數大葉Sakdaeyeop and one of them is noteworthy as a clue about the relations between Sijo and Goryeosokyo because it is a modified work which adapted the Goryeosokyo "Gasiri" according to the Sijo format. In 琴譜古geumbogo, there are three works with high possibility that repertoire with 中大葉Jungdaeyeop were already set up at this time. Based on these five music scores, it can be mentioned that a lot of Geumbos were compiled in 17th century, not for the purpose of enlightening discourse at the national level but for referencing for music lovers by themselves to memorize songs individually. It is also discovered that Sijo was performed with only 平調pyeong-jo out of 羽調woo-jo, 羽調界面調woojokyemyen-jo, 平調pyeong-jo, 平調界面調pyeongjokyemyun-jo in early 17th century, but it was performed with other three and 數大葉Sakdaeyeop as well after the mid-17th century. On the other hand, despite the change in the musical tunes, lyrics do not show a significant change at this time because it is estimated repertoire with specific piece of music was already formed in 17th Century. However, performing itself would give a certain impact on change and loss of lyrics because it tends to focus on communication and emotional connection between singers and audience. Clarifying characteristics in Sijo from old music scores is meaningful in that Sijo can be understood better not only as written poetry but also as oral poetry and overcome bias of previous researches which have been proceeded mainly on Sijo lyrics collection(歌集).

• Clean Technology
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• v.25 no.1
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• pp.91-97
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• 2019

Oxidative desulfurization (ODS) has received much attention in recent years because refractory sulfur compounds such as dibenzothiophenes can be oxidized selectively to their corresponding sulfoxides and sulfones, and these products can be removed by extraction and adsorption. In this work, The oxidative desulfurization of marine diesel fuel was performed in a batch reactor with hydrogen peroxide ($H_2O_2$) in the presence of various supported heteropoly acid catalysts. The catalysts were characterized by XRD, XRF, XPS and nitrogen adsorption isotherm techniques. Based on the sulfur removal efficiency of promising silica supported heteropoly acid catalysts, the ranking of catalytic activity was: $30\;H_3PW_{12}/SiO_2$ > $30\;H_3PMo_{12}/SiO_2$ > $30\;H_4SiW_{12}/SiO_2$, which appears to be related with their intrinsic acid strength. The $30\;H_3PW_{12}/SiO_2$ catalyst showed the highest initial sulfur removal efficiency of about 66% under reaction conditions of $30^{\circ}C$, $0.025g\;mL^{-1}$ (cat./oil), 1 h reaction time. However, through the recycle test of the $H_3PW_{12}/SiO_2$ catalyst, significant deactivation was observed, which was attributed to the elution of the active component $H_3PW_{12}$. By introducing cesium cation ($Cs^+$) into the $H_3PW_{12}/SiO_2$ catalyst, the stability of the catalyst was improved with changing the solubility, and the $Cs^+$ ion exchanged catalyst could be recycled for at least five times without severe elution.

• Journal of Nutrition and Health
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• v.45 no.6
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• pp.541-551
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• 2012

In our previous work, we reported consumers' perceptions of body shape and weight control. In an ongoing effort, we analyzed the purchasing behavior, intake patterns, future purchasing decisions, and degree of satisfaction in individuals consuming dietary formula for weight control (DF) or heath/functional foods (HFFs) by using the same survey questions. Portfolio analysis for marketing strategy was also investigated. Subjects were divided into two groups according to consumption of DF or HFF during the previous year : DF group (n = 89) and HFF group (n = 110). Average intake frequency was $1.7{\pm}0.7$ per day for HFFs and $1.5{\pm}0.9$ per day for the DF, and the most prevalent form was pill (58.2%) for HFFs and bar (42.7%) for DF. Duration of intake was $3.1{\pm}2.3$ months for HFFs versus $3.9{\pm}3.5$ months for DF. The average degree of satisfaction was $3.6{\pm}0.6$ on a 5-point scale, meaning 'relatively satisfied'. For the weight control method to be used in the future, 44.5% of the HFF group selected 'HFFs' while 47.2% of the DF group selected 'DF', showing a tendency to use the current product type in the future. The average planned period for the intake was $3.8{\pm}3.7$ months for HFFs and $3.0{\pm}2.4$ months for DF (p < 0.05). The HFF group emphasized efficacy, functional ingredients of the products, reliable products, and higher satisfaction, whereas the DF group emphasized the added materials in addition to weight control effects.

• Horticultural Science & Technology
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• v.17 no.5
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• pp.572-577
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• 1999

Research was initiated to evaluate plant growth regulator effects on the vertical shoot growth of Korean lawngrass and to determine desirable growth regulator and its rate. The experiments were conducted twice at different sites in 1995. All the tested growth regulators inhibited the growth, but the inhibition period was variable among the product in Experiments I and II. During the first week after treatment, there was approximately 10 to 20% growth reduction in most of the treated plots. In the amidochlor-treated plots, growth suppression was effective for 3 to 4 weeks at low to medium rates ($0.60mL{\cdot}m^{-2}$). A Type II growth regulator, trinexapac-ethyl exceeding the medium rate of $0.08mL{\cdot}m^{-2}$ consistently tended to suppress vertical shoot growth for 8 weeks, being above 35% reduction in both experiments. In the plots applied with mefluidide, growth suppression appeared with foliar discoloration 3 or 4 days earlier than the other growth regulators and continued to work till the 8 weeks after treatment. Suppression intensity on vertical shoot growth increased with time after treatment up to a certain period of time, depending on growth regulators. Generally, the higher the application rate, the greater the suppression intensity. Seasonal variation of activity and effectiveness of growth regulators was observed, resulting in lower suppression intensity in July than in June. It is expected to reduce mowing requirements by 30 to up to 60% for a certain period with a specific growth regulator. In low to medium maintenance of Korean lawngrass turf, a long-term suppression may be more effectively accomplished with trinexapac-ethyl rather than mefluidide and amidochlor in terms of vertical shoot growth inhibition. Therefore, turf managers will need to select proper growth regulator and determine optimum rate of application for turfgrass management, based on a defined period of mowing reduction.

• Journal of Science and Technology Studies
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• v.19 no.3
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• pp.247-289
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• 2019

By examining the experiences of three social economy organizations who participated in the social problem-solving R&D projects, we discuss the conditions which may encourage the participation of civil society in national R&D programs in South Korea. By calling for the inclusion of social economy organizations along with the living-lab, the social problem-solving R&D projects introduced a new type of civic participation in the national R&D programs. It is the requirement in the RFP of the social problem-solving R&D which led PIs to inviting social economy organizations into their projects. But the invites occurred rather abruptly and accidently without adequate mutual understanding between scientific experts and social economy organizations. While helping social economy organizations participate in R&D processes, this form of institutional arrangement also led them into a position in subordination to scientific experts. Social economy organizations were supposed to coordinate the living lab in the social problem-solving R&D projects which they felt familiar as an extension of what they have been doing. In contrast, they felt administrative work such as accounts following complicate administrative rules as the most unfamiliar challenge. The difference in their emphases between scientific experts and social economy organizations was also evident. Social economy organizations viewed that, while they and ordinary people are primarily interested in a practical use of the developed products or services, scientific experts tend to focus on research and development. Not only did such difference produce a friction in the R&D processes but also it had social economy organizations view the R&D projects they participated in as unsuccessful. Nevertheless, all these experiences provided a great opportunity for the social economy organizations for learning and growing as a new actor in the national R&D.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.