• Journal of Electrochemical Science and Technology
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• v.12 no.4
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• pp.458-464
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• 2021

Lithium ion batteries (LIBs) is a kind of rechargeable secondary battery, developed from lithium battery, lithium ions move between the positive and negative electrodes to realize the charging and discharging of external circuits. Zeolitic imidazolate frameworks (ZIFs) are porous crystalline materials in which organic imidazole esters are cross-linked to transition metals to form a framework structure. In this article, ZIF-67 is used as a sacrificial template to prepare nano porous carbon (NPC) coated cobalt nanoparticles. The final product Co/NPC composites with complete structure, regular morphology and uniform size were obtained by this method. The conductive network of cobalt and nitrogen doped carbon can shorten the lithium ion transport path and present high conductivity. In addition, amorphous carbon has more pores that can be fully in contact with the electrolyte during charging and discharging. At the same time, it also reduces the volume expansion during the cycle and slows down the rate of capacity attenuation caused by structure collapse. Co/NPC composites first discharge specific capacity up to 3115 mA h/g, under the current density of 200 mA/g, circular 200 reversible capacity as high as 751.1 mA h/g, and the excellent rate and resistance performance. The experimental results show that the Co/NPC composite material improves the electrical conductivity and electrochemical properties of the electrode. The cobalt based ZIF-67 as the precursor has opened the way for the design of highly performance electrodes for energy storage and electrochemical catalysis.

• Molecules and Cells
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• v.45 no.5
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• pp.306-316
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• 2022

Chronic stress contributes to the risk of developing depression; the habenula, a nucleus in epithalamus, is associated with many neuropsychiatric disorders. Using genome-wide gene expression analysis, we analyzed the transcriptome of the habenula in rats exposed to chronic restraint stress for 14 days. We identified 379 differentially expressed genes (DEGs) that were affected by chronic stress. These genes were enriched in neuroactive ligand-receptor interaction, the cAMP (cyclic adenosine monophosphate) signaling pathway, circadian entrainment, and synaptic signaling from the Kyoto Encyclopedia of Genes and Genomes pathway analysis and responded to corticosteroids, positive regulation of lipid transport, anterograde trans-synaptic signaling, and chemical synapse transmission from the Gene Ontology analysis. Based on protein-protein interaction network analysis of the DEGs, we identified neuroactive ligand-receptor interactions, circadian entrainment, and cholinergic synapse-related subclusters. Additionally, cell type and habenular regional expression of DEGs, evaluated using a recently published single-cell RNA sequencing study (GSE137478), strongly suggest that DEGs related to neuroactive ligand-receptor interaction and trans-synaptic signaling are highly enriched in medial habenular neurons. Taken together, our findings provide a valuable set of molecular targets that may play important roles in mediating the habenular response to stress and the onset of chronic stress-induced depressive behaviors.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3879-3891
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• 2021

A heat pipe residual heat removal system is proposed to be incorporated into the reactor driven subcritical (RDS) facility, which has been proposed by MIT Nuclear Reactor Laboratory for testing and demonstrating the Fluoride-salt-cooled High-temperature Reactor (FHR). It aims to reduce the risk of the system operation after the shutdown of the facility. One of the main components of the system is an air-cooled heat pipe heat exchanger. The alkali-metal high-temperature heat pipe was designed to meet the operation temperature and residual heat removal requirement of the facility. The heat pipe model developed in the previous work was adopted to simulate the designed heat pipe and assess the heat transport capability. 3D numerical simulation of the subcritical facility active zone was performed by the commercial CFD software STAR CCM + to investigate the operation characteristics of this proposed system. The thermal resistance network of the heat pipe was built and incorporated into the CFD model. The nominal condition, partial loss of air flow accident and partial heat pipe failure accident were simulated and analyzed. The results show that the residual heat removal system can provide sufficient cooling of the subcritical facility with a remarkable safety margin. The heat pipe can work under the recommended operation temperature range and the heat flux is below all thermal limits. The facility peak temperature is also lower than the safety limits.

• Journal of the Korean institute of surface engineering
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• v.56 no.1
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• pp.104-114
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• 2023

Three dimensional (3D) porous structures consisting of Cu@CoO core-shell-type nano-dendrites were synthesized and tested as the anode materials in lithium secondary batteries. For this purpose, first, the 3D porous films comprising Cu@Co core-shell-type nano-dendrites with various thicknesses were fabricated through the electrochemical co-deposition of Cu and Co. Then the Co shells were selectively anodized to form Co hydroxides, which was finally dehydrated to get Cu@CoO nanodendrites. The resulting electrodes exhibited very high reversible specific capacity almost 1.4~2.4 times the theoretical capacity of commercial graphite, and excellent capacity retention (~90%@50^th cycle) as compared with those of the existing transition metal oxides. From the analysis of the cumulative irreversible capacity and morphology change during charge/discharge cycling, it proved that the excellent capacity retention was attributed to the unique structural feature of our core-shell structure where only the thin CoO shell participates in the lithium storage. In addition, our electrodes showed a superb rate performance (70.5%@10.8 C-rate), most likely due to the open porous structure of 3D films, large surface area thanks to the dendritic structure, and fast electron transport through Cu core network.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.43-50
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• 2010

Recently, the Internet telephony has been used rather than the traditional telephony by many Internet users, with low cost. Session Initiation Protocol(SIP) is the standard of application layer protocol for establishment and disconnection of the session for Internet telephony. SIP mainly runs over the UDP for transport. So in case of the loss of the INVITE request message, the message is retransmitted by an appropriate timer for reliable transmission of the UDP message. Though the retransmission is useful for ensuring the reliability of SIP messages sent by the users, it may cause the overload traffic in the SIP proxy server. The overload in SIP proxy servers results in the loss of many input messages. This paper presents a non-linear overload control algorithm to resolve the overload condition of the server. we simulate our proposed algorithm using the network simulator ns-2. The simulation results show that the throughput of the server with the proposed algorithm have been improved about 12% compared to the existing linear control algorithm.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• Korea Trade Review
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• v.46 no.5
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• pp.65-81
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• 2021

The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• Advances in nano research
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• v.16 no.3
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• pp.231-249
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• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.