• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.171-189
• /
• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.5
• /
• pp.211-220
• /
• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Korean Journal of Mineralogy and Petrology
• /
• v.34 no.4
• /
• pp.209-218
• /
• 2021

Studies of pore structure in shale gas reservoirs are essential to increase recovery rates, which is in the spotlight concerning unconventional resources. In this study, the distribution of pores in shale gas reservoir sample were observed using Scanning Electron Microscope Particle Analysis (SELPA), which is appropriate to analyze the distribution of particle or shape for sample in large area. A sample from the A-068 borehole drilled in the Liard Basin was analyzed; calcite is the main mineral. The pore size ranges from tens of nanometers to hundreds of micrometers and the contribution of each pore size to overall sample porosity was determined using SELPA. The distribution of pores was determined by observing the surface in the same area at magnifications of ×1000, ×3000 and ×5000. Pores less than 100 nm were observed at high magnifications and confirm that small-scale pore distribution can be analyzed and identified rapidly using SELPA. The method introduced in this study will be useful to understand pore structures in unconventional reservoirs.

• Membrane Journal
• /
• v.32 no.6
• /
• pp.486-495
• /
• 2022

This study presents the improved recovery efficiency of rare metal ions through the modified separation membrane wettability and hydrogen ion permeation in the anion exchange membrane (AEM) under the recovery process of combined electrodialysis and solvent extraction. Specifically, the wettability of the separator was enhanced by hydrophilic modification on one separator surface through polydopamine (PDA) and lipophilic modification on the other surface through SiO₂ or graphene oxide (GO). In addition, the modified surface of AEM with polyethyleneimine (PEI), PDA, poly(vinylidene fluoride) (PVDF), etc. reduces the water uptake and modify the pore structure for proton ions generation. The suppressed transport resulted in the reduced hydrogen ion permeation. In the characterization, the surface morphology, chemical properties and composition of membrane or AEM were analyzed with Scanning Electron Microscopy (SEM) and Fourier Transform-Infrared Spectroscopy (FT-IR). Based on the analyses, improved extraction and stripping and hydrogen ion transport inhibition were demonstrated for the copper ion recovery system.

• Journal of Platform Technology
• /
• v.11 no.2
• /
• pp.54-65
• /
• 2023

Due to the nature of electric vehicles, the batteries used for electric vehicles have a very large rated capacity. If an electric vehicle runs for a long time or an electric vehicle is abandoned due to a traffic accident, the electric vehicle battery becomes a waste battery. Even in vehicles that are being abandoned, the remaining capacity of waste batteries for electric vehicles is sufficient for other purposes. Waste batteries for automobiles are very expensive, so they need to be recycled and reused, but there was a problem that the standards for measuring the performance grade of waste batteries for recycling and reuse were insufficient. As a method for measuring the remaining capacity of waste battery, the most stable and reliable method is to measure the remaining capacity of battery using full charge and discharge. However, the inspection method by the full charging and discharging method varies depending on the capacity of the battery, but it takes more than a day to inspect, and many people are making great efforts to solve this problem. In this paper, an electric vehicle battery residual capacity analysis technique using voltage deviation between cells was studied and analyzed as a method to reduce inspection time for electric vehicle batteries. To this end, a full charging and discharging-based capacity measurement system was constructed, experimental data were collected using a nose or waste battery, and the correlation between the voltage deviation and the remaining capacity of the battery pack was analyzed to verify whether it can be used for battery inspection.

• Economic and Environmental Geology
• /
• v.55 no.6
• /
• pp.661-669
• /
• 2022

The need for miniaturization, high efficiency, and green energy resources as an energy storage device through the development of various electronic device has emerged. Accordingly, nanomaterials with excellent electrochemical properties, such as graphene and graphene hybrids, are attracting attention as promising materials. In particular, in the electric vehicle industry, cost reduction of secondary batteries is a key factor that can determine the spread of related industries, and it is most important to analyze R&D trends for battery material technology and respond to future technological development directions. Therefore, in this study, we tried to suggest a direction for R&D activities in the future by analyzing patent trends for graphene anode material technology for secondary batteries and deriving implications. As a result, in the case of anode material technology, the proportion of foreigners in the US and European patent markets was higher than in the Korean and Japanese patent markets, which means that the US and European marketability is high. In addition, Japanese applicants are filing high-level applications not only in the Japanese patent market but also in other countries suggests that Japan is leading the technology in this field. Lastly, the proportion of research institutes in the patent market of Korea and the US remains high compared to that of Japan and Europe, indicating that the commercialization of technology is still slow in those countries. Therefore research institutes and companies in Korea will have to establish their own strategies for developing and securing materials using the results of patent trends in major countries and major companies analyzed in this study.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.115-122
• /
• 2022

With the outbreak of COVID-19 a few years ago, video conferencing and electronic document work have increased, and for this reason, the proportion of computer work among modern people's daily routines is increasing. However, as more and more people work on computers in the wrong posture for a long time, the number of patients with poor eyesight and text neck is increasing. Until recently, many studies have been published to correct posture, but most of them have limitations that users may experience discomfort because they have to correct posture by wearing equipment. A posture correction sensor algorithm is proposed to prevent access to the minimum distance between a computer monitor and a person using an ultrasonic sensor device. At this time, an algorithm for minimizing false alarms among warning alarms that sound at the minimum distance is also proposed. Because the ultrasonic sensor device is used, posture correction can be performed without attaching a device to the body, and the user can relieve discomfort. In addition, experimental results showed that accuracy can be improved by reducing false alarms by removing more than half of the noise generated during distance measurement.

• Journal of Service Research and Studies
• /
• v.13 no.1
• /
• pp.127-143
• /
• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

• Journal of the Korean Society of Radiology
• /
• v.17 no.2
• /
• pp.207-213
• /
• 2023

Computed tomography (CT) images are used as the basis for proton Bragg peak position estimation and treatment plan simulation. During the Hounsfield Unit (HU) based proton stopping power ratio (SPR) estimation, small differences in the patient's density and elemental composition lead to uncertainty in the Bragg peak positions along the path of the proton beam. In this study, we investigated the potential of dual-energy computed tomography image-based proton SPRs prediction accuracy to reduce the uncertainty of Bragg peak position prediction. Single- and dual-energy images of an electron density phantom (CIRS Model 062M electron density phantom, CIRS Inc., Norfolk, VA, USA) were acquired using a computed tomography system (Somatom Definition AS, Siemens Health Care, Forchheim, Germany) to estimate the SPRs of the proton beam. To validate the method, it was compared to the SPRs estimated from standard data provided by the National Institute of Standards and Technology (NIST). The results show that the dual-energy image-based method has the potential to improve accuracy in predicting the SPRs of proton beams, and it is expected that further improvements in predicting the position of the proton's Bragg peak will be possible if a wider variety of substitutes with different densities and elemental compositions of the human body are used to predict the SPRs.

• Korea Trade Review
• /
• v.42 no.5
• /
• pp.113-136
• /
• 2017

New product preannouncement through global supply chain management and international strategic alliances is a critical issue for firm's survive and gaining the competitive advantage in the global smart-phone market. To identify the impact of exploration alliance and exploitation alliance on the short-term's Firm Performance, respectively, This study implemented the event study and the cross sectional regression analysis, focusing on the case of Galaxy Note series. Research results identified that new technologies by exploration alliance and the existing technologies through exploitation alliance have a positive effect on the short-term's performance of vendors related. Furthermore, information for the new products showed higher the excess earning rate than information related to the existing technologies. This implies the firms that provides new technologies have a stronger innovative ability than the companies serving the existing technologies, recognizing as a positive signal in the market. Finally, this study implicates that new technologies by exploration alliance enhances innovative abilities from new product preannouncement, and is a critical variable that can determines whether to survive in the market.