Institution
Mokpo National University
Education•Muan, South Korea•
About: Mokpo National University is a education organization based out in Muan, South Korea. It is known for research contribution in the topics: Welding & Extraction (chemistry). The organization has 1276 authors who have published 3086 publications receiving 54257 citations.
Topics: Welding, Extraction (chemistry), Catalysis, Apoptosis, Adsorption
Papers published on a yearly basis
Papers
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TL;DR: The most promising nanoscale fillers are layered silicate nanoclays such as montmorillonite and kaolinite as mentioned in this paper, which can provide active and/or smart properties to food packaging systems.
1,461 citations
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TL;DR: A deep-learning-based approach to detect diseases and pests in tomato plants using images captured in-place by camera devices with various resolutions, and combines each of these meta-architectures with “deep feature extractors” such as VGG net and Residual Network.
Abstract: Plant Diseases and Pests are a major challenge in the agriculture sector. An accurate and a faster detection of diseases and pests in plants could help to develop an early treatment technique while substantially reducing economic losses. Recent developments in Deep Neural Networks have allowed researchers to drastically improve the accuracy of object detection and recognition systems. In this paper, we present a deep-learning-based approach to detect diseases and pests in tomato plants using images captured in-place by camera devices with various resolutions. Our goal is to find the more suitable deep-learning architecture for our task. Therefore, we consider three main families of detectors: Faster Region-based Convolutional Neural Network (Faster R-CNN), Region-based Fully Convolutional Network (R-FCN), and Single Shot Multibox Detector (SSD), which for the purpose of this work are called "deep learning meta-architectures". We combine each of these meta-architectures with "deep feature extractors" such as VGG net and Residual Network (ResNet). We demonstrate the performance of deep meta-architectures and feature extractors, and additionally propose a method for local and global class annotation and data augmentation to increase the accuracy and reduce the number of false positives during training. We train and test our systems end-to-end on our large Tomato Diseases and Pests Dataset, which contains challenging images with diseases and pests, including several inter- and extra-class variations, such as infection status and location in the plant. Experimental results show that our proposed system can effectively recognize nine different types of diseases and pests, with the ability to deal with complex scenarios from a plant's surrounding area.
832 citations
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TL;DR: Mechanical and barrier properties of chitosan films were affected through intercalation of nanoparticles, that is, tensile strength increased by 7-16%, whereas water vapor permeability decreased by 25-30% depending on the nanoparticle material tested.
Abstract: Four different types of chitosan-based nanocomposite films were prepared using a solvent-casting method by incorporation with four types of nanoparticles, that is, an unmodified montmorillonite (Na-MMT), an organically modified montmorillonite (Cloisite 30B), a Nano-silver, and a Ag-zeolite (Ag-Ion). X-ray diffraction patterns of the nanocomposite films indicated that a certain degree of intercalation was formed in the nanocomposite films, with the highest intercalation in the Na-MMT-incorporated films followed by films with Cloisite 30B and Ag-Ion. Scanning electron micrographs showed that in all of the nanocomposite films, except the Nano-silver-incorporated one, nanoparticles were dispersed homogeneously throughout the chitosan polymer matrix. Consequently, mechanical and barrier properties of chitosan films were affected through intercalation of nanoparticles, that is, tensile strength increased by 7−16%, whereas water vapor permeability decreased by 25−30% depending on the nanoparticle material teste...
815 citations
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TL;DR: In this review, recent advances in the preparation of natural biopolymer-based films and their nanocomposites, and their potential use in packaging applications are addressed.
Abstract: Concerns on environmental waste problems caused by non-biodegradable petrochemical-based plastic packaging materials as well as the consumer's demand for high quality food products has caused an increasing interest in developing biodegradable packaging materials using annually renewable natural biopolymers such as polysaccharides and proteins. Inherent shortcomings of natural polymer-based packaging materials such as low mechanical properties and low water resistance can be recovered by applying a nanocomposite technology. Polymer nanocomposites, especially natural biopolymer-layered silicate nanocomposites, exhibit markedly improved packaging properties due to their nanometer size dispersion. These improvements include increased modulus and strength, decreased gas permeability, and increased water resistance. Additionally, biologically active ingredients can be added to impart the desired functional properties to the resulting packaging materials. Consequently, natural biopolymer-based nanocomposite packaging materials with bio-functional properties have a huge potential for application in the active food packaging industry. In this review, recent advances in the preparation of natural biopolymer-based films and their nanocomposites, and their potential use in packaging applications are addressed.
677 citations
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TL;DR: In this paper, the authors used the Brunauer Emmett Teller (BET), temperature programmed reduction (TPR), X-ray diffraction (XRD) and Xray photoelectron spectroscopy (XPS) to study catalytic combustion of volatile organic compounds (VOCs): benzene and toluene.
Abstract: Catalytic combustion of volatile organic compounds (VOCs: benzene and toluene) was studied over manganese oxide catalysts (Mn3O4, Mn2O3 and MnO2) and over the promoted manganese oxide catalysts with alkaline metal and alkaline earth metal. Their properties and performance were characterized by using the Brunauer Emmett Teller (BET), temperature programmed reduction (TPR), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The sequence of catalytic activity was as follows: Mn3O4 > Mn2O3 > MnO2, which was correlated with the oxygen mobility on the catalyst. Each addition of potassium (K), calcium (Ca) and magnesium (Mg) to Mn3O4 catalyst enhanced the catalytic activity of Mn3O4 catalyst. Accordingly, K, Ca and Mg seemed to act as promoters, and the promoting effect might be ascribed to the defect-oxide or a hydroxyl-like group. A mutual inhibitory effect was observed between benzene and toluene in the binary mixture. In addition, the order of catalytic activity with respect to VOC molecules for single compound is benzene > toluene, and the binary mixture showed the opposite order of toluene > benzene.
602 citations
Authors
Showing all 1282 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jinsook Kim | 75 | 261 | 48618 |
Hyun Jin Park | 71 | 322 | 17875 |
Jong-Whan Rhim | 64 | 253 | 13916 |
Curtis L. Weller | 48 | 136 | 9526 |
Zita Vale | 46 | 775 | 9635 |
Shiv Shankar | 39 | 96 | 9182 |
Rajendra Karki | 34 | 68 | 4267 |
Jung-Hyun Shim | 33 | 226 | 4077 |
Ashraf F. Ashour | 33 | 157 | 3745 |
Yong-Seo Park | 32 | 77 | 3081 |
In-Soo Yoon | 29 | 120 | 2843 |
Min-Suk Bae | 27 | 106 | 2928 |
Man Seung Lee | 27 | 209 | 2726 |
Eun Jung Kim | 26 | 101 | 2155 |
Keun-Hyeok Yang | 26 | 224 | 3380 |