• Advances in nano research
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• v.12 no.4
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• Advances in nano research
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• v.14 no.1
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• pp.17-25
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• 2023

Gold nanoparticles have recognized a promising drug carriers in many diseases. These nanoparticles could carry anti-inflammatory drugs in the case of muscle injury and for fatigue relief. On the other hand, specific surface of this kind of nanoparticles could be critical in amount of drug they could carry. Therefore, in this study, we explore different methodology and influencing parameters on the specific surface of gold nanoparticles. After specifying the main parameters, different machine learning and artificial neural network are adopted to model the effects of different parameters. Furthermore, response surface methodology is utilized to obtain a quadrilateral relationship between different parameters and specific surface. The results indicate that concentration of the gold salt solution is the most important parameter in increasing the size of gold nanoparticle and, as a consequence, increasing specific surface. Moreover, the ability of gold nanoparticles in prolonging retention of the drugs is discussed in detail.

• Proceedings of the KIEE Conference
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• summer
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• pp.202-204
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• 2004

This paper presents a neural network technology for the detection and classification of the various types of power quality disturbances. Power quality phenomena are short-time problems and of many varieties. Particularly, the transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting ·md classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. We test two neural network and compare the results of Backpropagation Neural (BPN) network with Radial basis function network (RBFN). RBFN is more useful to detect and classify than BPN. The configuration of the hardware of PQ-DAS and some case studies are described.

• Advances in nano research
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• v.12 no.6
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• pp.549-566
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• 2022

Mining of ore minerals (sfalerite, cinnabar, and chalcopyrite) from the old mine has led in significant environmental effects as contamination of soils and plants and acidification of water. Also, nanoparticles (NP) have obtained global importance because of their widespread usage in daily life, unique properties, and rapid development in the field of nanotechnology. Regarding their usage in various fields, it is suggested that soil is the final environmental sink for NPs. Nanoparticles with excessive reactivity and deliverability may be carried out as amendments to enhance soil quality, mitigate soil contaminations, make certain secure land-software of the traditional change substances and enhance soil erosion control. Meanwhile, there's no record on the usage of Nano superior substances for mine soil reclamation. In this study, five soil specimens have been tested at 4 sites inside the region of mine (<100 m) to study zeolites, and iron sulfide nanoparticles. Also, through using Artificial Neural Network (ANN) and Extreme Learning Machine (ELM), this study has tried to appropriately estimate the mechanical properties of soil under the effect of these Nano particles. Considering the RMSE and R2 values, Zeolite Nano materials could enhance the mine soil fine through increasing the clay-silt fractions, increasing the water holding capacity, removing toxins and improving nutrient levels. Also, adding iron sulfide minerals to the soils would possibly exacerbate the soil acidity problems at a mining site.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.271-272
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• 2007

• Polymer(Korea)
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• v.29 no.1
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• pp.1-7
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• 2005

Interpenetrating polymer network (PN) is a mixture of network polymers. The characteristics of IPN material is the control of morphology during the IPN synthesis. By controlling the relative kinetics of chemical reaction (as well as gellation) and phase separation, the morphology of IPN can be controlled to obtain materials with nano-scale domain and also the co-continuous phase. Other important advantage is the fact that the morphology is permanent due to the presence of the physical interlocking between the networks. The combination of hydrophilic polyurethane and hydrophobic polystyrene in IPN form provides enhanced blood compatibility due to the co-existence of the hydrophilic and hydrophobic domains in nano-scale on the surface. The reaction temperature, reaction pressure and the degree of crosslinking were varied during the IPN synthesis and the morphology and blood compatibility of the resulting IPN materials were studied.

• Applied Microscopy
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• v.46 no.4
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• pp.171-175
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• 2016

A distinctive neuronal network in the brain is believed to make us unique individuals. Electron microscopy is a valuable tool for examining ultrastructural characteristics of neurons, synapses, and subcellular organelles. A recent technological breakthrough in volume electron microscopy allows large-scale circuit reconstruction of the nervous system with unprecedented detail. Serial-section electron microscopy-previously the domain of specialists-became automated with the advent of innovative systems such as the focused ion beam and serial block-face scanning electron microscopes and the automated tape-collecting ultramicrotome. Further advances in microscopic design and instrumentation are also available, which allow the reconstruction of unprecedentedly large volumes of brain tissue at high speed. The recent introduction of correlative light and electron microscopy will help to identify specific neural circuits associated with behavioral characteristics and revolutionize our understanding of how the brain works.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.109-112
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• 2020

Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.4
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• pp.339-343
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• 2006

We observed the application possibility of inductive coupler for the underground high-voltage power line communication by means of analysis of signal transmission characteristics and magnetic properties on annealing temperatures for high-permeability Fe-base amorphous alloys. The best electromagnetic and transmission characteristics were shown in nano-crystalline precipitated alloy annealed at temperature $510^{\circ}C$. The transmission characteristics in the low-frequency band depend on permeability of magnetic core materials and its properties of high-frequency band can be improved by impedance matching. Using the high pass filter embedded in the coupler, other noise signal band except for communication signals could be cut off.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.221-227
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• 2015

The polarization characteristics of nano-scale grating-assisted polarization-insensitive coupler (GA-PIC) consisted of double sandwiched rib-type layers are evaluated in detail by using modal transmission-line theory (MTLT) based on equivalent network. To obtain the polarization-insensitive condition of GA-PIC, the coupling lengths as a function of the refractive index and thickness of sandwiched rib-type layer as well as the grating thickness and period are analyzed for quasi-TE and quasi-TM modes. The numerical results show that the GA-PIC with hundreds of nanometer scale is realized by properly choosing structural and material parameters of double sandwiched layers and grating.