• Journal of Surface Science and Engineering
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• v.56 no.6
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• pp.437-442
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• 2023

This research aims to enhance the efficiency of Pt/C catalysts due to the limited availability and high cost of platinum in contemporary fuel cell catalysts. Nano-sized platinum particles were distributed onto a carbon-based support via the polyol process, utilizing the metal precursor H₂PtCl₆·6H₂O. Key parameters such as pH, temperature, and RPM were carefully regulated. The findings revealed variations in the particle size, distribution, and dispersion of nano-sized Pt particles, influenced by temperature and pH. Following sodium hydroxide treatment, heat treatment procedures were systematically executed at diverse temperatures, specifically 120, 140, and 160 ℃. Notably, the thermal treatment at 140 ℃ facilitated the production of Pt/C catalysts characterized by the smallest platinum particle size, measuring at 1.49 nm. Comparative evaluations between the commercially available Pt/C catalysts and those synthesized in this study were meticulously conducted through cyclic voltammetry, X-ray diffraction (XRD), and field-emission scanning electron microscopy-energy dispersive X-ray spectroscopy (FE-SEM EDS) methodologies. The catalyst synthesized at 160 ℃ demonstrated superior electrochemical performance; however, it is imperative to underscore the necessity for further optimization studies to refine its efficacy.

• Current Photovoltaic Research
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• v.12 no.2
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• pp.37-40
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• 2024

One of the current innovation trends in the solar industry is the increase in the size of silicon wafers. As the wafer size increases, the series resistance of the module rises, highlighting the need for research on methods for cutting and bonding solar cells. Among these, the Infrared (IR) laser scribing technique has been extensively researched. However, there is still insufficient optimization research regarding the thermal damage caused by lasers on the Transparent Conductive Oxide (TCO) layer of Heterojunction (HJT) solar cells. Therefore, in this study, we systematically varied conditions such as IR laser scribing speed, frequency, power, and the number of scribes to investigate their impact on the performance of cut cells under each condition. Additionally, we conducted a comparative analysis of thermal damage effects on the TCO layer based on varying scribing depths.

• Smart Media Journal
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• v.13 no.3
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• pp.36-44
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• 2024

Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.4
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• pp.62-67
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• 2024

In this paper, we developed and optimized a chitosan-based polymer microbial bead carrier that is cell-friendly, has a high moisture absorption rate, and effectively provides the conditions for microbial biomineral formation as an optimal microbial carrier that protects microorganisms in concrete, and evaluated the self-healing performance of mortar using it. In order to incorporate circular-shaped microbial endospores, a circular-shaped microbial bead carrier was developed by combining chitosan and alginate polymers, and the amount of calcium carbonate produced could be actively controlled by adjusting the composition of the carrier. The amount of biominerals formed and the size of crystals were maximized in the hydrogel bead carrier containing chitosan, and in the case of mortar cracks using this, it was confirmed that self-healing of cracks with a maximum crack width of 0.3mm was achieved within 96 hours after crack generation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.95-103
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• 2024

The diversity of smart EV(electric vehicle)-related industries is increasing due to the growth of battery-based eco-friendly electric vehicle component material technology, and labor-intensive industries such as logistics, manufacturing, food, agriculture, and service have invested in and studied automation for a long time. Accordingly, various types of robots such as autonomous mobile robots and collaborative robots are being utilized for each process to improve industrial engineering such as optimization, productivity management, and work management. The technology that should accompany this unmanned automobile industry is unmanned automatic charging technology, and if autonomous mobile robots are manually charged, the utility of autonomous mobile robots will not be maximized. In this paper, we conducted a study on the technology of unmanned charging of autonomous mobile robots using charging terminal docking and undocking technology using an unmanned charging system composed of hardware such as a monocular camera, multi-joint robot, gripper, and server. In an experiment to evaluate the performance of the system, the average charging terminal recognition rate was 98%, and the average charging terminal recognition speed was 0.0099 seconds. In addition, an experiment was conducted to evaluate the docking and undocking success rate of the charging terminal, and the experimental results showed an average success rate of 99%.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.67-76
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• 2024

In this study, we address the problem of target detection using multiple agents. Specifically, the detection problem involving mobile agents necessitates additional strategies for path planning. The objective is to maximize the total utility derived from the detection process over a specific period. This detection problem incorporates realistic utility values by considering a stochastic process based on the Poisson process, which accounts for the changing probability of target event occurrence over time. The objective function is nonlinear and is classified as an NP-hard problem. To identify an effective solution within an efficient computation time, this study demonstrates that the objective function possesses the characteristic of submodularity. Using this property, we propose a heuristic algorithm designed to obtain a reasonable strategy with relatively low computational time. The proposed algorithm shows solution performance and the ability to generate solutions within an appropriate computation time through theoretical and experimental results.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.143-151
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• 2024

This study proposes a guide to activate regional resource-based start-up projects by analyzing program planning, consultation, promotion, recruitment, operation, support, and performance measurement. It provides insights into effective methods for engaging prospective entrepreneurs interested in local brands.The study categorized 100 local start-up communities on platforms like YouTube and Instagram, identified suitable message characteristics for each channel, and measured conversion rates after distributing seven types of messages. Over four weeks, the messages received over 57,000 views, achieved a 13% conversion rate, and attracted about 100 applicants. This evaluation identified the most effective message types, offering key policy implications and insights into early-stage entrepreneurs' awareness and the entrepreneurial ecosystem. The researchers also revealed that cooperation with local communities and regional innovation centers is an important success of a local startup.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3740-3749
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• 2024

To reduce the losses caused by aging failure of insulation gate bipolar transistor (IGBT), which is the core components of nuclear power plant rod position indicating and rod control (RPC) system. It is necessary to conduct studies on its life prediction. The selection of IGBT failure characteristic parameters in existing research relies heavily on failure principles and expert experience. Moreover, the analysis and learning of time-domain degradation data have not been fully conducted, resulting in low prediction efficiency as the monotonicity, time correlation, and poor anti-interference ability of extracted degradation features. This paper utilizes the advantages of the stacked denoising autoencoder(SDAE) network in adaptive feature extraction and denoising capabilities to perform adaptive feature extraction on IGBT time-domain degradation data; establishes a long-short-term memory (LSTM) prediction model, and optimizes the learning rate, number of nodes in the hidden layer, and number of hidden layers using the Gray Wolf Optimization (GWO) algorithm; conducts verification experiments on the IGBT accelerated aging dataset provided by NASA PCoE Research Center, and selects performance evaluation indicators to compare and analyze the prediction results of the SDAE-LSTM model, PSOLSTM model, and BP model. The results show that the SDAE-LSTM model can achieve more accurate and stable IGBT life prediction.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.59-73
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• 2005

Caching query results and reusing them in processing of subsequent queries is an important query optimization technique. Materialized view and view indexing are the representative examples of such a technique. The two schemes had received much attention for relational databases, and have been investigated for XML data since XML emerged as the standard for data exchange on the Web. In XML view indexing, XML view xv which is the result of an XML query is represented as an XML view index(XVI), a structure containing the identifiers of xv's underlying XML elements as well as the information on xv. Since XVI for xv stores just the identifiers of the XML elements not the elements themselves, when xv is requested, its XVI should be materialized against xv's underlying XML documents. In this paper, we address the problem of integrating an XML view index management system with an RDBMS based XML storage system. The proposed system was implemented in Java on Windows 2000 Server with each of two different commercial RDBMSs, and used in evaluating performance improvement through XML view indexing as well as its overheads. The experimental results revealed that XML view indexing was very effective with an RDBMS based XML storage system while its overhead was negligible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.