• 에너지공학
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• 제26권1호
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• pp.68-75
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• 2017

Global warming affects water supply and water resources throughout the world. In many countries, climate change affects significantly on the fresh water resources. Vietnam is exposed mainly, to landslides and floods triggered by tropical storms and monsoon rains, although storm surge, whirlwind, river bank and coastal line erosion, hail rain. In addition to the prevalent drought, there are many major water challenges, including water availability, stress, scarcity and accessibility, because of poor resource management. Fast growth of urbanization, industrialization and population growth, agricultural activities and climate change cause heavy pressure on water quality. Both domestic and industrial wastewater, as well as storm water shares the same drainage. The common facilities for wastewater treatment are not available. Therefore, wastewater is treated only superficially and then discharged directly into rivers and lakes causing serious pollution of surface water environment. In this paper, we reported the severe water crisis and massive green algal blooms formation in Vietnam rivers and lakes. This is the biggest evidence of climate change variations in Vietnam.

• 한국환경농학회:학술대회논문집
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• 한국환경농학회 2011년도 30주년 정기총회 및 국제심포지엄
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• pp.196-204
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• 2011

Abiotic stress is the primary cause of crop loss worldwide, reducing average yields for most major crop plants by more than 50%. In addition, future agricultural production and management will encounter multifaceted challenges from global climate change. Therefore, it is necessary to study the molecular response of crop plants to the stresses in order to develop appropriate strategies to sustain food production under adverse environmental conditions. We carried out a large scale proteomic analysis of soybean plants in response to various abiotic stresses, including drought, salinity, waterlogging and their interactions. Proteins were analyzed by two dimensional polyacrylamide gel electrophoresis followed by matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry. The identified proteins are involved in a wide range of cellular functions. In addition to the well known stress-associated proteins, we identified several novel proteins, which were not reported before. In many cases our proteomic data bridges the gap between mRNA and metabolite data. Our studie provides new insights into identification of abiotic stress responsive proteins in soybean, and demonstrates the advantages of proteomic analysis in dissecting metabolic and regulatory networks.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.198-198
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• 2017

Climate change causes unpredictable and erratic climatic patterns which affects crop production in agriculture and threatens public health. To cope with the challenges of climate change, sustainable and sound growth environment for crop production should be secured. Recent attention has been given to the development of smart irrigation system using sensors and wireless network as a solution to achieve water conservation as well as improvement in crop yield and quality with less water and labor. This study developed the smart irrigation technique for farmlands by monitoring the soil moisture contents and real-time climate condition for decision-making support. Central to this design is micro-controller which monitors the farm condition and controls the distribution of water on the farm. In addition, a series of laboratory studies were conducted to determine the optimal irrigation pattern, one time versus plug time. This smart technique allows farmers to reduce water use, improve the efficiency of irrigation systems, produce more yields and better quality of crops, reduce fertilizer and pesticide application, improve crop uniformity, and prevent soil erosion which eventually reduce the nonpoint source pollution discharge into aquatic-environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2732-2753
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• 2019

With the application of wireless sensor networks in the fields of ecological observation, defense military, architecture and urban management etc., the security problem is becoming more and more serious. Characteristics and constraint conditions of wireless sensor networks such as computing power, storage space and battery have brought huge challenges to protection research. Inspired by the danger theory in biological immune system, this paper proposes an intrusion detection model for wireless sensor networks. The model abstracts expressions of antigens and antibodies in wireless sensor networks, defines meanings and functions of danger signals and danger areas, and expounds the process of intrusion detection based on the danger theory. The model realizes the distributed deployment, and there is no need to arrange an instance at each sensor node. In addition, sensor nodes trigger danger signals according to their own environmental information, and do not need to communicate with other nodes, which saves resources. When danger is perceived, the model acquires the global knowledge through node cooperation, and can perform more accurate real-time intrusion detection. In this paper, the performance of the model is analyzed including complexity and efficiency, and experimental results show that the model has good detection performance and reduces energy consumption.

• 대한원격탐사학회지
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• 제35권1호
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• pp.93-115
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• 2019

The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

• Animal Bioscience
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• 제35권2_spc호
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• pp.347-355
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• 2022

Among edible insects, black soldier fly (Hermetia illucens), yellow mealworm (Tenebrio molitor), and common housefly (Musca domestica) have been considered as an alternative protein source for pigs. Because they are easy to breed and grow in the organic wastes, and they have well-balanced nutritional value as a protein source for pigs. The black soldier fly larvae and mealworm could replace the fish meal in the diets for weaned pigs without adverse effects on growth performance and nutrient digestibility. Black soldier fly could also be included in the finishing pig's diet without any negative effects on the growth performance and pork quality of the market pigs. Insect products showed a greater standardized ileal digestibility value of amino acids than conventional animal proteins in growing pigs. Due to the limited amount of insect products used for pig feeding study, most previous pig studies have been conducted in weaned pigs. Thus, further study is needed about the optimal inclusion level of insect products in every phase diet from weaned pigs to sows. The use of insect products in swine diets has some challenges in terms of cost, supply, and safety. Lastly, intrinsic differences among insect species, processing method, and feeding phase should be taken into consideration for the use of insect products in the swine diets.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.271-281
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• 2022

Manual seed classification challenges can be overcome using a reliable and autonomous seed purity identification and classification technique. It is a highly practical and commercially important requirement of the agricultural industry. Researchers can create a new data mining method with improved accuracy using current machine learning and artificial intelligence approaches. Seed classification can help with quality making, seed quality controller, and impurity identification. Seeds have traditionally been classified based on characteristics such as colour, shape, and texture. Generally, this is done by experts by visually examining each model, which is a very time-consuming and tedious task. This approach is simple to automate, making seed sorting far more efficient than manually inspecting them. Computer vision technologies based on machine learning (ML), symmetry, and, more specifically, convolutional neural networks (CNNs) have been widely used in related fields, resulting in greater labour efficiency in many cases. To sort a sample of 3000 seeds, KNN, SVM, CNN and CNN-SVM hybrid classification algorithms were used. A model that uses advanced deep learning techniques to categorise some well-known seeds is included in the proposed hybrid system. In most cases, the CNN-SVM model outperformed the comparable SVM and CNN models, demonstrating the effectiveness of utilising CNN-SVM to evaluate data. The findings of this research revealed that CNN-SVM could be used to analyse data with promising results. Future study should look into more seed kinds to expand the use of CNN-SVMs in data processing.

• 공업화학
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• 제33권2호
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• pp.133-144
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• 2022

Fast-paced industrial and agricultural development generates large quantities of hazardous heavy metals (HMs), which are extremely damaging to individuals and the environment. Research in both academia and industry has been spurred by the need for HMs to be removed from water bodies. Advanced materials are being developed to replace existing water purification technologies or to introduce cutting-edge solutions that solve challenges such as cost efficacy, easy production, diverse metal removal, and regenerability. Water treatment industries are increasingly interested in activated carbon because of its high adsorption capacity for HMs adsorption. Furthermore, because of its huge surface area, abundant functional groups on surface, and optimal pore diameter, the modified activated carbon has the potential to be used as an efficient adsorbent. Metal-organic frameworks (MOFs), a novel organic-inorganic hybrid porous materials, sparked an interest in the elimination of HMs via adsorption. This is due to the their highly porous nature, large surface area, abundance of exposed adsorptive sites, and post-synthetic modification (PSM) ability. This review introduces PSM methods for MOFs, chemical modification of activated carbons (ACs), and current advancements in the elimination of Pb²⁺, Hg²⁺, and Cd²⁺ ions from water using modified MOFs and ACs via adsorption.

• 한국축산식품학회지
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• 제42권5호
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• pp.723-743
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• 2022

Beef muscles from mature cows and bulls, especially those originating from the extremities of the carcass, are considered as underutilized due to unsatisfactory palatability. However, beef from culled animals comprises a substantial proportion of the total slaughter in the US and globally. Modern consumers typically favor cuts suitable for fast, dry-heat cookery, thereby creating challenges for the industry to market inherently tough muscles. In general, cull cow beef would be categorized as having a lower extent of postmortem proteolysis compared to youthful carcasses, coupled with a high amount of background toughness. The extent of cross-linking and resulting insolubility of intramuscular connective tissues typically serves as the limiting factor for tenderness development of mature beef. Thus, numerous post-harvest strategies have been developed to improve the quality and palatability attributes, often aimed at overcoming deficiencies in tenderness through enhancing the degradation of myofibrillar and stromal proteins or physically disrupting the tissue structure. The aim of this review is to highlight existing and recent innovations in the field that have been demonstrated as effective to enhance the tenderness and palatability traits of mature beef during the chilling and postmortem aging processes, as well as the use of physical interventions and enhancement.

• 한국경제지리학회지
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• 제25권1호
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• pp.109-130
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• 2022

베트남 정부는 농업구조개혁을 위해 새로운 협동조합을 통한 계약농업을 추진하고 있으며, 베트남 농민은 정책에 따른 구조 전환의 영향을 직접적으로 받고 있다. 따라서 정책 과정에 따른 농민들의 토지이용 및 생존전략을 이해하는 것은 이러한 농업개발정책에 있어 필수적이라 할 것이다. 이 연구는 중부 베트남의 전형적인 농촌 마을 중 하나인 빈다오사(社)(Binh Dao commune)를 대상으로 이루어졌다. 이 논문에서는 먼저 GIS을 이용한 토지이용 변화 분석 및 190명의 농민과의 심층 인터뷰를 통해 계약농업 도입 전후의 농촌 노동력 구조와 생업활동의 변화와 그 원인을 분석하였다. 그 결과, 새로운 협동조합을 통한 계약농업은 농민-협동조합-농산물판매회사로 이어지는 수직적 가치사슬을 형성하고, 기계화를 통한 효율적 토지이용에 기여하여, 생산성을 향상시키고 농산물 시장가격의 리스크로 부터 농민들을 보호하는 순효과를 가져왔다는 것이 밝혀졌다. 한편, 이러한 긍정적인 효과에도 불구하고, 베트남의 협동조합을 통한 계약농업은 애초에 의도했던 농촌 노동력을 비농업부문으로 재배치하지는 못한 것으로 나타났다. 오히려 빈다오사(社)의 농민들은 농업구조개혁 과정에서 경작면적을 늘리려는 경향이 있었다. 즉, 베트남 농촌지역의 제한적인 농외 취업기회로 인해, 빈다오사(社)의 농민들은 기계화와 생산성 향상으로 생긴 잉여 가족노동력을 역설적으로 농업부문에 집중시키는 생존전략을 선택한 것으로 보여된다. 그 결과 빈다오사(社)의 농민들은 협동조합의 계약농업을 통한 농업구조개혁에도 불구하고 여전히 가족노동력에 의존한 소농체제에 머물러 있다.