• Journal of Venture Innovation
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• v.5 no.4
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• pp.109-115
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• 2022

As the 4th industrial revolution progresses, foreign countries are promoting smart manufacturing innovation through digital transformation as a priority task early on to secure a competitive edge in the manufacturing industry. In response, the Korean government is also promoting a policy to enhance the competitiveness of small and medium-sized manufacturing companies by promoting digital transformation in the corporate sector to meet the global trend of the 4th industrial revolution era. Manufacturing powerhouses such as Germany and Japan see manufacturing as a key sector in digital transformation and are leading related policies, while emerging countries such as China are also promoting manufacturing innovation strategies such as building digital infrastructure and creating a digital innovation ecosystem. Korea is promoting the 'Korean-style smart factory dissemination and expansion strategy' by transforming Germany's manufacturing innovation strategy for smart factory supply to suit the domestic situation. However, the policy to supply smart factories so far has been conducted with support from individual companies under the leadership of the government, and most of the smart factories are at the basic level, and it is evaluated that there are limitations such as the lack of manpower to operate smart factories. In addition, while the current policy focuses on expanding the supply of smart factories in SMEs, it is necessary to establish a smart manufacturing system through linkages between large and small businesses in order to achieve the original goal of establishing a smart manufacturing system. Therefore, it can be said that from the standpoint of small and medium-sized enterprises (SMEs), who are consumers of smart factories, it can be said that the digital transformation policy can achieve the expected results only when appropriate incentives are provided for the introduction of smart factories in a situation where management resources such as funds, technology, and human resources are lacking. In addition, it is judged that the uncertainty of the performance of digital investment always exists, and as long as large and small companies are maintained as an ecosystem of delivery and subcontracting, there is very little incentive for small and medium-sized manufacturing companies to voluntarily invest in or advance digital transformation. Therefore, the digital transformation policy of small and medium-sized manufacturing companies in the future has practical significance in that it suggests that there is a need to seek ways to attract SMEs' digital-related voluntary investment.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.993-1003
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• 2023

Due to the increasing greenhouse gas emissions, the global mean temperature has risen by 1.1℃ compared to pre-industrial levels, and significant changes are expected in functioning of water supply systems. In this study, we assessed impacts of climate change and instreamflow management on water supply reliability in the Geum River basin, Korea. We proposed univariate climate response functions, where mean precipitation and potential evaporation were coupled as an explanatory variable, to assess impacts of climate stress on multiple water supply reliabilities. To this end, natural streamflows were generated in the 19 sub-basins with the conceptual GR6J model. Then, the simulated streamflows were input into the Water Evaluation And Planning (WEAP) model. The dynamic optimization by WEAP allowed us to assess water supply reliability against the 2020 water demand projections. Results showed that when minimizing the water shortage of the entire river basin under the 1991-2020 climate, water supply reliability was lowest in the Bocheongcheon among the sub-basins. In a scenario where the priority of instreamflow maintenance is adjusted to be the same as municipal and industrial water use, water supply reliability in the Bocheongcheon, Chogang, and Nonsancheon sub-basins significantly decreased. The stress tests with 325 sets of climate perturbations showed that water supply reliability in the three sub-basins considerably decreased under all the climate stresses, while the sub-basins connected to large infrastructures did not change significantly. When using the 2021-2050 climate projections with the stress test results, water supply reliability in the Geum River basin was expected to generally improve, but if the priority of instreamflow maintenance is increased, water shortage is expected to worsen in geographically isolated sub-basins. Here, we suggest that the climate response function can be established by a single explanatory variable to assess climate change impacts of many sub-basin's performance simultaneously.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.85-106
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• 2023

This study reviewed and derived the success factors of overseas agricultural startups and studied their integrated research model. Agricultural startups and general startups have in common that poor resources and infrastructure exist from a resource-based perspective after startup, but a differentiated approach from general startups is required due to the nature of the primary industry of agriculture. In this study, we approach the company internal factors (human resources/vision/distribution network capacity/capital capacity/cultivated crops/physical resources/farming technology, etc.) and external factors (agricultural infrastructure/laws/regulations/relationship with surrounding society, etc.) We tried to build a research model that can be integrated by focusing on various existing research models, success factors, and entrepreneurship. Through this, it is intended to present an integrated model that is practically helpful to business performance to entrepreneurs, business-related persons, and researchers who need an integrated understanding of agricultural startups at home and abroad. made for purpose In this paper, a standard model was established through three types (existing agricultural startup, small and medium-sized business startup, multinational company, and comprehensive approach) according to size and characteristics for modeling agricultural startup success factors. Through this, a total of 9 success factors (agricultural management, external environment, manager/founder characteristics, corporate identity, business management, organizational culture, infrastructure, commercialization capability, and sustainable growth) were derived. The implication of this study is that the success factors of agricultural startups were comprehensively presented based on 'entrepreneurship' for various domestic and foreign agricultural startup cases. By confirming the systematic categorization, a standard model for future agricultural startup success factors was presented, and as a result, a foundation was presented for systematic research and practical effectiveness of related research in the future.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.73-83
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• 2024

The purpose of this study is to diagnose various problems arising around social enterprises in the sport field from the perspective of the organization and derive necessary tasks and implications. In order to achieve the purpose of the study, the study was largely divided into three stages, and the results were derived. First, the main status and characteristics of social enterprises in the sport field were examined. The current status was analyzed focusing on aspects such as background and origin, legislation and policy, organizational goals, organizational structure and procedures, and organizational characteristics. Social enterprises in the sport sector were in their early stages, and the government's social enterprise policy goal tended to focus on increasing the number of social enterprises in a short period of time through financial input. In addition, it was found that most individual companies rely on government subsidy support due to insufficient profit generation capacity. In the second stage, we focused on the situational factors that affect the functional performance of social enterprises in the sport field. As a result of reviewing the value, ideology, technology, and history of the organization, which are situational factors, it was derived that when certified as a social enterprise in the sport field and supported by the central government or local governments, political control is strong to some extent and exposure to the market is not severe. In the last third step, tasks and implications were derived to form an appropriate organization for social enterprises in the sport field. After the social enterprise ecosystem in the sport sector has been established to some extent, it is necessary to gradually move from the current "government-type" organization to the "national enterprise" organization. This is true in light of the government's limited financial level, not in the short term, but in order for the organization of social enterprises in the sports sector to survive in the long term.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.41-50
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• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.

• Journal of Life Science
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• v.34 no.1
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• pp.18-27
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• 2024

Laying hens are known to be able to 'bio-accumulate' the health-promoting ingredients of their diet into eggs. The purpose of this study was to characterize lignan-rich eggs as functional food fed with Schisandra fruit by-product (SCP). Experimental diets were formulated using yellow corn, rice bran, soybean meal, fish meal, meat bone meal, poultry meal, vitamin premix, mineral premix, CaCO₃, and supplemented Schisandra chinensis by-product. This experiment conducted a completely randomized design with 5 treatments for 5 laying hens. Levels of SCP were fed control diet or each formulated diet containing 1%, 3%, 5% and 7% SCP powder. The weight of eggs and the lignan content in white and yolk of egg were investigated every 7 days. Egg production and egg weight were not affected by diet at less than 5% SCP in the diet, but were significantly reduced when the diet was supplemented with a high concentration of 7% SCP after 3 weeks. Yolks and white in eggs were analyzed by using a high performance liquid chromatography (HPLC) to determine the lignans profile. Higher dietary SCP supplementation significantly increased gomisin N and schisandrin C in Acetonitrile (p<0.05). Gomisin N in egg white increased in a concentration-dependent manner, but shisandrin C not detected. These results indicated that the use of SCP powder in layering diets was effective in egg quality and for the production of lignans fortified eggs. In conclusion, dietary supplementation of Schisandra by-product with less than 5% can produce lignans-enrich eggs used as functional foods.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Distribution Research
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• v.17 no.2
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• pp.63-92
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• 2012

This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective responses. Information relevancy was integrated into pleasure-arousal-dominance (PAD) emotional state model in the present study as a conceptual framework. The results of an online survey of 335 mobile phone users in the U.S. indicated the positive effects of arousal and information relevancy on pleasure. In addition, there was a significant relationship between pleasure and intention to use a LBMSS. However, the relationship between dominance and pleasure was not statistically significant. The results of the present study provides insight to retailers and marketers as to what factors they need to consider to implement location-based mobile shopping services to improve their business performance. Extended Abstract : Location aware technology has expanded the marketer's reach by reducing space and time between a consumer's receipt of advertising and purchase, offering real-time information and coupons to consumers in purchasing situations (Dickenger and Kleijnen, 2008; Malhotra and Malhotra, 2009). LBMSS increases the relevancy of SMS marketing by linking advertisements to a user's location (Bamba and Barnes, 2007; Malhotra and Malhotra, 2009). This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective response. The purpose of the study was to examine the relationship among information relevancy and affective variables and their effects on intention to use LBMSS. Thus, information relevancy was integrated into pleasure-arousal-dominance (PAD) model and generated the following hypotheses. Hypothesis 1. There will be a positive influence of arousal concerning LBMSS on pleasure in regard to LBMSS. Hypothesis 2. There will be a positive influence of dominance in LBMSS on pleasure in regard to LBMSS. Hypothesis 3. There will be a positive influence of information relevancy on pleasure in regard to LBMSS. Hypothesis 4. There will be a positive influence of pleasure about LBMSS on intention to use LBMSS. E-mail invitations were sent out to a randomly selected sample of three thousand consumers who are older than 18 years old and mobile phone owners, acquired from an independent marketing research company. An online survey technique was employed utilizing Dillman's (2000) online survey method and follow-ups. A total of 335 valid responses were used for the data analysis in the present study. Before the respondents answer any of the questions, they were told to read a document describing LBMSS. The document included definitions and examples of LBMSS provided by various service providers. After that, they were exposed to a scenario describing the participant as taking a saturday shopping trip to a mall and then receiving a short message from the mall. The short message included new product information and coupons for same day use at participating stores. They then completed a questionnaire containing various questions. To assess arousal, dominance, and pleasure, we adapted and modified scales used in the previous studies in the context of location-based mobile shopping service, each of the five items from Mehrabian and Russell (1974). A total of 15 items were measured on a seven-point bipolar scale. To measure information relevancy, four items were borrowed from Mason et al. (1995). Intention to use LBMSS was captured using two items developed by Blackwell, and Miniard (1995) and one items developed by the authors. Data analyses were conducted using SPSS 19.0 and LISREL 8.72. A total of usable 335 data were obtained after deleting the incomplete responses, which results in a response rate of 11.20%. A little over half of the respondents were male (53.9%) and approximately 60% of respondents were married (57.4%). The mean age of the sample was 29.44 years with a range from 19 to 60 years. In terms of the ethnicity there were European Americans (54.5%), Hispanic American (5.3%), African-American (3.6%), and Asian American (2.9%), respectively. The respondents were highly educated; close to 62.5% of participants in the study reported holding a college degree or its equivalent and 14.5% of the participants had graduate degree. The sample represents all income categories: less than $24,999 (10.8%), $25,000-$49,999 (28.34%), $50,000-$74,999 (13.8%), and $75,000 or more (10.23%). The respondents of the study indicated that they were employed in many occupations. Responses came from all 42 states in the U.S. To identify the dimensions of research constructs, Exploratory Factor Analysis (EFA) using a varimax rotation was conducted. As indicated in table 1, these dimensions: arousal, dominance, relevancy, pleasure, and intention to use, suggested by the EFA, explained 82.29% of the total variance with factor loadings ranged from .74 to .89. As a next step, CFA was conducted to validate the dimensions that were identified from the exploratory factor analysis and to further refine the scale. Table 1 exhibits the results of measurement model analysis and revealed a chi-square of 202.13 with degree-of-freedom of 89 (p =.002), GFI of .93, AGFI = .89, CFI of .99, NFI of .98, which indicates of the evidence of a good model fit to the data (Bagozzi and Yi, 1998; Hair et al., 1998). As table 1 shows, reliability was estimated with Cronbach's alpha and composite reliability (CR) for all multi-item scales. All the values met evidence of satisfactory reliability in multi-item measure for alpha (>.91) and CR (>.80). In addition, we tested the convergent validity of the measure using average variance extracted (AVE) by following recommendations from Fornell and Larcker (1981). The AVE values for the model constructs ranged from .74 through .85, which are higher than the threshold suggested by Fornell and Larcker (1981). To examine discriminant validity of the measure, we again followed the recommendations from Fornell and Larcker (1981). The shared variances between constructs were smaller than the AVE of the research constructs and confirm discriminant validity of the measure. The causal model testing was conducted using LISREL 8.72 with a maximum-likelihood estimation method. Table 2 shows the results of the hypotheses testing. The results for the conceptual model revealed good overall fit for the proposed model. Chi-square was 342.00 (df = 92, p =.000), NFI was .97, NNFI was .97, GFI was .89, AGFI was .83, and RMSEA was .08. All paths in the proposed model received significant statistical support except H2. The paths from arousal to pleasure (H1: ${\ss}$=.70; t = 11.44), from information relevancy to intention to use (H3 ${\ss}$ =.12; t = 2.36), from information relevancy to pleasure (H4 ${\ss}$ =.15; t = 2.86), and pleasure to intention to use (H5: ${\ss}$=.54; t = 9.05) were significant. However, the path from dominance to pleasure was not supported. This study investigated consumer intention to use a location-based mobile shopping service (LBMSS) that integrates cognitive and affective responses. Information relevancy was integrated into pleasure-arousal-dominance (PAD) emotional state model as a conceptual framework. The results of the present study support previous studies indicating that emotional responses as well as cognitive responses have a strong impact on accepting new technology. The findings of this study suggest potential marketing strategies to mobile service developers and retailers who are considering the implementation of LBMSS. It would be rewarding to develop location-based mobile services that integrate information relevancy and which cause positive emotional responses.

• Journal of Animal Science and Technology
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• v.45 no.1
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• pp.69-78
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• 2003

This experiment was carried out to evaluate the value of total mixed fermentation feeds(TMFF) as completely mixed ration and to observe the effect of various kinds of TMFF on the palatability, feed intake, and milk performance in Holstein cows. The dry matter (DM) content of TMFF used in the experiment was 23.98-28.42% range, and CP, TDN, ADF and NDF were 16.2${\sim}$19.2%, 58.3-65.1%, 34.4-39.6% and 46.9${\sim}$49.9% levels, respectively. The relative feed value (RFV) in rape-, alfalfa-, grass-, oat-, corn-TMFF groups were 138.6, 133.9, 116.5, 111.8, 111.4 and 108.1, respectively. Among these groups, RFV of rye-TMFF group was lowest. Dry matter disappearance(DMD) showed 0.8${\sim}$.9% to the all kinds of TMFF groups. The pH was 3.89${\sim}$.87 and $NH_3$-N concentration was 6.93-8.66 mg/$d\ell$. The acetic acid concentration in the raw material of TMFF showed low level of 0.19${\sim}$0.57%, lactic acid showed high level of 1.17${\sim}$3.21% and butyric acid was very high as 0.03${\sim}$0.32%. Therefore, these results provide evidence that the quality of TMFF was not so bad. In the daily fresh matter intake on the alfalfa-, grass-, rape-, corn-, oats- and rye-TMFF were showed 62.85, 60.48, 58.04, 57.11, 54.61 and 45.74 kg respectively. All TMFF showed high palatability as daily dry matter intake of 1.95 to 2.90% by body weight of experimental cows. Body condition score(BCS) was gradually increased in during 60 days of the experiment term. Average daily gain(ADG) showed about 140.0${\sim}$326.7g. In alfalfa-TMFF group, the ADG was higher than in the other groups (p<0.05). Also, the increase in BCS was observed in grass-TMFF group (3.07 to 3.34) and rye-TMFF group was decreased in 3.07 to 3.34 (p<0.05). The milk yield appropriately showed a range of 16.16${\sim}$18.95 kg in all groups. Among these groups, alfalfa-TMFF group was highest(P<0.05). Average milk fat contents showed high levels of 4.06${\sim}$4.79% and the level was high in order of rape-, grass-, corn-, alfalfa-, rye- and oats-TMFF. Milk protein was highest in forage-TMFF and level of lactose in milk was approximately 4.56% in overall groups. Solid non fat(SNF) and total solid(TS) contents were 8.75% and 12.8%, respectively. However, milk composition was not significantly affected by TMFF.