• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.55-62
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• 2024

In this paper, we propose a thin-film hydroponic plant cultivator using HMI display and IoT technology. Existing plant cultivators were difficult to manage due to soil-based cultivation, and it was difficult to optimize environmental conditions due to the open cultivation environment. In addition, there are problems with plant cultivation as immediate control is difficult and growth of plants is delayed. To solve this problem, a cultivation environment was established by connecting the MCU and sensors, and the environment information could be checked and quickly controlled by linking with the HMI display. Additionally, a case was applied to minimize changes in environmental information. Implementation of a thin-film hydroponic cultivation system made soil management easier, improved functionality through operation and control, and made it easy to understand environmental information through the display. The effectiveness of rapid growth was confirmed through crop cultivation experiments in existing growers and hydroponic growers. Future research directions will include optimizing growth information by transmitting and storing cultivation environment information and linking and comparing growth information using vision cameras. It is expected that this will enable efficient and stable plant cultivation.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1199-1206
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• 2021

Accordingly, attention is also being paid to the agricultural use of remote sensing technique that non-destructively and continuously detects the growth and physiological status of crops. However, when remote sensing techniques are used for crop monitoring, it is possible to continuously monitor the abnormality of crops in real time. For this, standard growth information of crops is required and relative growth considering the cultivation environment must be identified. With the relationship between GDD (Growing Degree Days), which is the cumulative temperature related to crop growth obtained from ideal cultivation management, and the vegetation index as standard growth information, compared with the vegetation index observed with the spectralreflectance sensor(SRS_NDVI & SRS_PRI) in each rice paddy treated with standard cultivation management and non-fertilized, it was quantitatively identified as a time series. In the future, it is necessary to accumulate a database targeting various climatic conditions and varieties in the standard cultivation management area to establish a more reliable standard growth information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1077-1084
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• 2015

Security issues such as an illegal acquisition of personal information and identity theft happen due to using game bots in online games. Game bots collect items and money unfairly, so in-game contents are rapidly depleted, and honest users feel deprived. It causes a downturn in the game market. In this paper, we defined the growth types by analyzing the growth processes of users with actual game data. We proposed the framework that classify hard-core users and game bots in the growth patterns. We applied the framework in the actual data. As a result, we classified five growth types and detected game bots from hard-core users with 93% precision. Earlier studies show that hard-core users are also detected as a bot. We clearly separated game bots and hard-core users before full growth.

• Information Systems Review
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• v.19 no.1
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• pp.185-202
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• 2017

Most studies based on production function theory have concluded that economic growth is a result of information technology (IT) capital use. However, some studies have indicated that economic growth is a determinant of IT investment. To determine if these results also hold at the industry level, we use the Granger causality test to analyze bidirectional causality with industry-level data for 1977~2007 from the United States. The results generally reveal that IT investment causes economic growth in many industries under the concept of Granger causality, that economic growth causes IT investment in some industries, and that IT investment is not associated with economic growth in some industries. In the country-level time-series data made by summing up the IT capital and gross output for each industry, the results do not show any causality between IT investment and economic growth. However, they show bi-directional causality between IT investment and economic growth in the panel data. These results may be a source of IT productivity paradox.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.155-162
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• 2020

The paper aims to examine the association between information and communication technology (ICT), economic growth and population health based on health production model in Malaysia. This theoretical health production function is represented as follows: where the output is an individual health outcome, and the inputs are determinants of health, such as income, education, health care costs, medical facilities, the environment, and lifestyle. The development of information and communication technologies are represented as of mobile cellular subscriptions (per 100) and fixed telephone subscriptions (100) using time series data from 1993-2017 from the World Bank database. Using the bound testing technique of cointegration, this study finds that ICT affects population health significantly and positively in the long- and short-run. This is because ICT inclusion improves human health and longevity. Whereas, economic growth has no significant impact on the population's health both in the short- and long-run. The findings indicate that a weak global economy affects Malaysia's economic growth and reduces the health expenditure per capita. The results of this study suggest that policymakers must develop policies that improves public health by increasing health literacy, disseminating health information and facilitating medical facilities. This study also suggests that health care systems should to concentrate on digital inclusion.

• Agribusiness and Information Management
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• v.7 no.1
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• pp.1-9
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• 2015

The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

• IE interfaces
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• v.16 no.1
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• pp.103-110
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• 2003

Growth curves are widely used in forecasting the market demand. When there are only a few data points available, the estimated model parameters have a low confidence. In this case, if some expert opinions are available, it would be better for predicting future demand to adjust the model parameters using these information. This paper proposes the methodology for re-estimation of model parameters in growth curves when adjusting market potential and/or time of maximum sales. We also provide the detailed procedures for five growth curves including Bass, Logistic, Gompertz, Weibull and Cumulative Lognormal models. Applications to real data are also included.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.220-234
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• 2002

This study examined the impact of preventive environmental management practices on sales growth, manufacturing and environmental performance of the US chemical manufacturing companies. In order to investigate the impact, this study examined the relationship between the degree of preventive environmental programs and sales growth, manufacturing and environmental performances. Using a cross-sectional research design to test three hypotheses. a survey questionnaire was mailed to chemical companies in the USA. To investigate the relationship between the degree of Preventive environmental programs and sales growth, manufacturing and environmental performances. t-tests were used. According to the results of t-tests the higher preventive implementation programs achieved better manufacturing and environmental performances than lower preventive or reactive strategies. But there was no difference in sales growth between tow groups.

• Asia pacific journal of information systems
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• v.26 no.4
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• pp.542-560
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• 2016

This study determines whether or not firms can achieve high productivity growth through external technology acquisition. It also identifies the key factors affecting adopting firms' productivity growth by employing the Malmquist productivity index (MPI) methodology, which features computational ease, low data dependency, and decomposition of productivity growth into technical efficiency change and technical change. Results showed that the effects of productivity growth arising from technology transfer became stronger over time. Moreover, patent transfer guaranteed firms' productivity growth, but no evidence was found that factors such as age and size could increase productivity. Finally, cultural similarity could be another factor conditioning the effectiveness of technology transfer in the productivity of adopting firms.