• Smart Structures and Systems
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• v.26 no.1
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• pp.117-134
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• 2020

Over recent years, the interest for vegetables and fruits in all seasons and places has much increased, from where diverse countries have directed to the commercial production in greenhouse. In this article, we propose an algorithm based on wireless sensor network technologies that monitor the microclimate inside a greenhouse and linear equations model for optimization plant production and material cost. Moreover, we also suggest a novel design of an intelligent greenhouse. We validate our algorithms with simulations on a benchmark based on experimental data made at lNRA of Montfavet in France. Finally, we calculate the statistical estimators RMSE, TSSE, MAPE, EF and R². The results obtained are promising, which shows the efficiency of our proposed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.193-197
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• 2015

Recently, the new issues for the safety and the information delivery system in the ship are raised. The deployment and the efficient algorithms of deploying the wireless sensor networks instead of using the built-in wired networks or the setup of the new wired networks is more desirable than the deployment of the wired networks in a ship after its final production since it can reduce the cost and the time of the brand new wired networks by reshaping some of the internal structure of the ship. In this paper, the shipboard signal propagation measurement system based on the signature sequence-three way slave mode are designed and its measureed data are analysed after measuring the signal propagation characteristics. Consequently, it is expected that the reliable and cost-effective signal measurement system with the three way algorithm for the deployment of the shipboard wireless networks can be achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.183-186
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• 2015

Recently, the demand for the safety and the information delivery system in the ship increases. The deployment of the wireless sensor networks instead of using the built-in wired networks or the setup of the new wired networks is more desirable than the deployment of the wired networks in a ship after its final production since it can reduce the cost and the time of the brand new wired networks by deforming some of the internal structure of the ship. In this paper, the shipboard signal propagation measurement system based on the signature sequence-two way slave mode are designed and its measurement data are analysed after measuring the signal propagation characteristics. Consequently, it is expected that the reliable and cost-effective signal measurement system for the deployment of the shipboard wireless networks can be built.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.1-23
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• 2021

This study introduces novel research using Practice Context Models supported by Knowledge Networks and Percolation Theory with the aim to contribute to knowledge management in Proof-of-Concept (PoC) activities. The authors envision this proposal as a potential instrument to identify network structures based on a percolation (propagation) threshold and to analyze the importance of nodes (e.g., practitioners, practices, competencies, movements, and scenarios) during the percolation of knowledge in PoC activities. After thirty months immersed in the natural PoC habitat, acting as observers and practitioners, and supported by an ethnographic exercise and a designer-research mindset, the authors identified the production of meaning in PoC activities occurring in a hermeneutic circle characterized by the presence of several knowledge networks; thus, discovering the 'natural knowledge' in PoC as a spectrum of cognitive development spread throughout its network, as each node could produce and disseminate certain knowledge that flows and influences other nodes. Therefore, this research presents the use of Practice Context Models 'connected' to Knowledge Networks and Percolation Theory as a potential and feasible proposal to be built using the attribution of values (weights) to the nodes (e.g., practitioners, practices, competencies, movements, scenarios, and also knowledge) in the context of PoC with the aim to allow the players (e.g., PoC practitioners) to have more flexibility in building alliances with other players (new nodes); that is, focusing on those nodes with higher value (focus on quality) in collaboration networks, i.e., alliances (connections) with the aim to contribute to knowledge management in the context of PoC.

• Animal Bioscience
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• v.34 no.4
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• pp.770-782
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• 2021

Objective: The aim of the present study was to compare the effectiveness of three approaches (the seasonal auto-regressive integrated moving average [SARIMA] model, the nonlinear autoregressive exogenous [NARX] artificial neural networks and Wood's model) to the prediction of milk yield during lactation. Methods: The dataset comprised monthly test-day records from 965 Polish Holstein-Friesian Black-and-White primiparous cows. The milk yields from cows in their first lactation (from 5 to 305 days in milk) were used. Each lactation was divided into ten lactation stages of approximately 30 days. Two age groups and four calving seasons were distinguished. The records collected between 2009 and 2015 were used for model fitting and those from 2016 for the verification of predictive performance. Results: No significant differences between the predicted and the real values were found. The predictions generated by SARIMA were slightly more accurate, although they did not differ significantly from those produced by the NARX and Wood's models. SARIMA had a slightly better performance, especially in the initial periods, whereas the NARX and Wood's models in the later ones. Conclusion: The use of SARIMA was more time-consuming than that of NARX and Wood's model. The application of the SARIMA, NARX and Wood's models (after their implementation in a user-friendly software) may allow farmers to estimate milk yield of cows that begin production for the first time.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.22-25
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• 2002

The Mass production of ceramic heater has encountered with the estimation for the proper parameters of the printing conditions. This paper presents a method to estimate the squeegee pressure. It uses resistance distribution from the trial run with approximate squeegee pressure which comes from statistical process control (SPC). Then, the resistance distribution and its total resistance are input to the backpropagation neural networks that can recognize resistance's distribution patterns. The value of output network derived from the input value can identify to the appropriate squeegee pressure. The experimental results are demonstrated In ensure the efficiency and the reliability of this method with the accuracy 96.75 percent. Indeed, embedded on this method will aid us to reduce the loss from the normal mass production.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.607-612
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• 2000

Microprecision agriculture for a fully controlled plant factory is proposed in this paper. Microprecision agriculture can be attained by using plant factories to realize profitable alternative agriculture. A closed, fully controlled, plant-growing factory is far better in terms of minimizing all sorts of waste. The limit and optimum design concept has to be applied to establish an economically feasible, fully controlled, plant-growing factory. To achieve this objective, microprecision technologies have to be developed. Microprecision technologies should be involved in sensing, modeling, controlling, and collecting information for the mechatronics for plant production. Basic technologies for microprecision are already available; they are SPA (speaking plant approach to environmental control), AI (artificial intelligence: expert systems, neural networks, genetic algorithms, photosynthetic algorithms etc.), bioinstrumentation, non-invasive measurement, biomechatronics, and biorobotics. A microprecision irrigation system for plug production is an example of a microprecision technology that has actually been implemented in a plug seedling production factory.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.2066-2073
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• 2021

The use of nuclear reactors is a large studied possible solution for thermochemical water splitting cycles. Nevertheless, there are several problems that have to be solved. One of them is to increase the efficiency of the cycles. Hence, in this paper, a thermal energy optimization of a Sulfur-Iodine nuclear hydrogen production cycle was performed by means a heuristic method with the aim of minimizing the energy targets of the heat exchanger network at different minimum temperature differences. With this method, four different heat exchanger networks are proposed. A reduction of the energy requirements for cooling ranges between 58.9-59.8% and 52.6-53.3% heating, compared to the reference design with no heat exchanger network. With this reduction, the thermal efficiency of the cycle increased in about 10% in average compared to the reference efficiency. This improves the use of thermal energy of the cycle.

• Animal Bioscience
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• v.37 no.4_spc
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• pp.775-785
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• 2024

Pork production is a significant agricultural enterprise in the United States and Canada. The United States is the third-largest global producer of pork and Canada ranks seventh in pork production. The North American Free Trade Agreement and its successor, the U.S.-Mexico-Canada Agreement, have facilitated trade and integration between the two countries. The majority of production systems are modern and intensive, characterized by large vertically integrated farms using advanced technologies. Both nations benefit from their status as major producers of feed grains, with the United States leading in corn and soybeans, while Canada excels in canola and barley production. The regulatory frameworks for food safety, animal welfare, and environmental stewardship differ slightly, with the FDA and USDA overseeing these aspects in the United States, and Health Canada and the Canada Food Inspection Agency in Canada. The United States and Canada also have well-established distribution networks for pork products, relying on both domestic and international markets. Export markets play a crucial role, with the United States being a major importer of Canadian pigs, and both countries exploring opportunities in Asia. Despite a rise in global demand, domestic pork consumption trends differ, with per capita consumption remaining stable in the USA and declining in Canada. Changing consumer preferences, including a demand for ethically raised and locally sourced pork, may influence production practices. Future trends in pig production include a focus on consumer concerns, sustainability, disease prevention, reduction of antimicrobial use, and advancements in technology. The industry is adapting to challenges such as disease outbreaks and changing regulations, with a strong emphasis on animal welfare. Labor and workforce considerations, along with advancements in technology and automation, are expected to shape the efficiency of pork production in the future.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.117-124
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• 2010

Recently, according to development of wired and wireless networks, contents production of user-defined changes a environment producing contents that it get out of manufactured contents offered by mobile telecommunication company. This paper propose a system proposing and registering a contents service provider of mobile telecommunication company for user-defined mobile contents production and transmission. We propose a system using web hosting service for user-defined mobile contents production and solution for system and transmission for contents production of a person and enterprises.