• Korean Journal of Agricultural Science
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• 제49권4호
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• pp.749-760
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• 2022

Omics-driven synthetic biology is a multidisciplinary research field that creates new artificial life by employing genetic components, biological devices, and engineering technique based on genetic knowledge and technological expertise. It is also utilized to make valuable biomaterials with limited production via current organisms faster, more efficient, and in huge quantities. As the bioeconomic age begins, and the global synthetic biology market becomes more competitive, investment in research and development (R&D) and associated sectors has grown considerably. By overcoming the constraints of present biotechnologies through the merging of big data and artificial intelligence technologies, huge ripple effects are envisaged in the pharmaceutical, chemical, and energy industries. In agriculture, synthetic biology is being used to solve current agricultural problems and develop sustainable agricultural systems by increasing crop productivity, implementing low-carbon agriculture, and developing plant-based, high-value-added bio-materials such as vaccines for diagnosing and preventing livestock diseases. As international regulatory debates on synthetic biology are now underway, discussions should also take place in our country for the growth of bioindustries and the dissemination of research findings. Furthermore, the system must be improved to facilitate practical application and to enhance the risk evaluation technology and management system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.I
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• pp.1-30
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• 2000

The higher stage of development of plant factory is discussed, that involves technologies such as process control for the plant growth environment, mechanization for material handling, system control for production and computer applications. Further, the advantages of a plant factory include production stabilization, higher production efficiency, and better quality management of products through a shortened growing period, better conditions, lower labor requirements, and easier application of industrial concepts. Finally, to realize the ultimate plant factory using both solar and artificial light, the intelligent approach from control engineering, physiological ecology and artificial intelligence(AI) may be inevitable and introduced based on some works done by authors.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.359-365
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• 2022

Scholars are paying increasingly close attention to brain research and the creation of biological neural networks, artificial neural networks, artificial intelligence, neurochips, brain-computer interfaces, prostheses, new research instruments and methods, methods of treatment, as well as the prevention of neurodegenerative diseases based on these data. The authors of the study propose their hypothesis on the understanding of the phenomenon of consciousness that answers questions concerning the criteria of consciousness, its localization, and principles of operation. In the study of the hard problem of consciousness, the philosophical and scientific categories of consciousness, and prominent hypotheses and theories of consciousness, the authors distinguish "the area of the conscious mind", which encompasses several states of consciousness united by the phenomenon of integrated consciousness. According to the authors, consciousness is a kind of executor of the phenomenological idea of the "chalice", so the search for it should be conducted deeper than the processes in the power of thought consciousness and transconsciousness, to which integrated consciousness can act as a lever. However, integrated consciousness may have the capacity to transcend into lower states of consciousness, which requires further study.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.159-165
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• 2019

'4th Industrial Revolution' is accelerating as a core part of creating new growth engines and enhancing competitiveness of businesses. The fourth industrial revolution means the transformation of society and industries that are brought by IoT (Internet of Things), big data analysis, AI (Artificial Intelligence), and robot technology. Information and Communication Technology (ICT), which is a major factor, is affecting production and manufacturing systems and as ICT technologies become more advanced, intelligent information technology is generally utilized in all areas of society, leading to hyper-connected society where new values are created and developed. ICT technology is not just about connecting devices and systems and making smart, it is about constantly converging and harmonizing new technologies in a number of fields and driving innovation and change. It is no exception to the agro-fisheries trade. In particular, ICT technology is applied to the agricultural sector, reducing labor, providing optimal environment for crops, and increasing productivity. Due to the nature of agriculture, which is a labor-intensive industry, it is predicted that the ripple effects of ICT technologies will become bigger. We are expected to use the Smart Concentration using ICT convergence technology as a useful resource for changing smart farms, and to help develop new service markets.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.229-238
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• 2022

Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.

• Journal of Information Processing Systems
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• 제20권1호
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• pp.13-23
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• 2024

Music brings pleasure and relaxation to people. Therefore, it is necessary to classify musical genres based on scenes. Identifying favorite musical genres from massive music data is a time-consuming and laborious task. Recent studies have suggested that machine learning algorithms are effective in distinguishing between various musical genres. However, meeting the actual requirements in terms of accuracy or timeliness is challenging. In this study, a hybrid machine learning model that combines a deep residual auto-encoder (DRAE) and support vector machine (SVM) for musical genre recognition was proposed. Eight manually extracted features from the Mel-frequency cepstral coefficients (MFCC) were employed in the preprocessing stage as the hybrid music data source. During the training stage, DRAE was employed to extract feature maps, which were then used as input for the SVM classifier. The experimental results indicated that this method achieved a 91.54% F1-score and 91.58% top-1 accuracy, outperforming existing approaches. This novel approach leverages deep architecture and conventional machine learning algorithms and provides a new horizon for musical genre classification tasks.

• Journal of Environmental Science International
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• 제33권7호
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• pp.547-552
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• 2024

Satellite technology has emerged as a powerful tool in modern agriculture, offering capabilities for Earth observation, land-use pattern analysis, crop productivity assessment, and natural disaster prevention. This mini-review provides a concise overview of the applications and benefits of satellite technologies in agriculture. It discusses how satellite imagery enables the monitoring of crop health, identification of land-use patterns, evaluation of crop productivity, and mitigation of natural disasters. Farmers and policymakers can make informed decisions to optimize agricultural practices, enhance food security, and promote sustainable agriculture by leveraging satellite data. Integrating satellite technology with other advancements, such as artificial intelligence and precision farming techniques, holds promise for further revolutionizing the agricultural sector. Overall, satellite technology has immense potential for improving agricultural efficiency, resilience, and sustainability in the face of evolving environmental challenges.

• Research in Plant Disease
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• 제26권3호
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• pp.121-133
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• 2020

Climate change, increased extreme weather and climate events, and rapidly changing socio-economic environment threaten agriculture and thus food security of our society. Therefore, it is urgent to shift from conventional farming to smart agriculture using big data and artificial intelligence to secure sustainable growth. In order to efficiently manage plant diseases through smart agriculture, agricultural big data that can be utilized with various advanced technologies must be secured first. In this review, we will first learn about agrometeorological big data consisted of meteorological, environmental, and agricultural data that the plant pathology communities can contribute for smart plant disease management. We will then present each sequential components of the smart plant disease management, which are prediction, monitoring and diagnosis, control, prevention and risk management of plant diseases. This review will give us an appraisal of where we are at the moment, what has been prepared so far, what is lacking, and how to move forward for the preparation of smart plant disease management.

• Journal of Biosystems Engineering
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• 제22권3호
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• pp.343-350
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• 1997

In farm management, many factors should be considered to select optimum farm machinery Some factors such as fm size can be quantified, but other factors such as working experience can not be. Futhermore, as several factors are missed and assumptions are made for the selection using conventional computer programs, the result is sometimes questionable. This problem can be solved using artificial intelligent techniques such as expert system. In this study, an expert system was developed to select optimum machinery by considering available working days, machinery to on, farming environments, labor cost, population, etc. It also took into account the characteristics of machinery, turning radius, easiness of operation, subsidy, loan to purchase, asset. farmers age, Rest Metabolic Rate, and working experience, etc. Expertise and experience of human experts were utilized to develop the expert system. The developed expert system was evaluated by the human experts and others, and it was proved to be practically useful fir farmers.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
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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.