• Journal of Industrial Convergence
• /
• v.20 no.6
• /
• pp.37-45
• /
• 2022

With the development of the Internet of Things (IoT), related network infrastructures require new technologies to protect against threats such as external hacking. This study proposes an L-PBFT consensus algorithm that can protect IoT networks based on a blockchain consensus algorithm. We designed a blockchain (private) model suitable for small networks, tested processing performance for ultra-small/low-power IoT devices, and verified stability. As a result of performance analysis, L-PBFT proved that at least the number of nodes complies with the operation of the consensus algorithm(minimum 14%, maximum 29%) and establishes a trust network(separation of secure channels) different from existing security protocols. This study is a 4th industry convergence research and will be a foundation technology that will help develop IoT device security products in the future.

• Applied Chemistry for Engineering
• /
• v.33 no.1
• /
• pp.96-102
• /
• 2022

Reactants of PEMFC are hydrogen and oxygen in gas phases and fuel cell overpotential could be reduced when reactants are smoothly transported. Numerous studies to modify cathode flow field design have been conducted because oxygen mass transfer in high current density region is dominant voltage loss factor. Among those cathode flow field designs, a block in flow field is used to forced supply reactant gas to porous gas diffusion layer. In this study, the block was installed on a simple fuel cell model. Using computational fluid dynamics (CFD), effects of forced convection due to blocks on a polarization curve and local current density contour were studied when different air flow rates were supplied. The high current density could be achieved even with low air supply rate due to forced convection to a gas diffusion layer and also with multiple blocks in series compared to a single block due to an increase of forced convection effect.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.2
• /
• pp.19-25
• /
• 2023

In this paper, we propose a method for improving raw images captured in a low light condition based on deep learning considering the image signal processing. In the case of a smart phone camera, compared to a DSLR camera, the size of a lens or sensor is limited, so the noise increases and the reduces the quality of images in low light conditions. Existing deep learning-based low-light image processing methods create unnatural images in some cases since they do not consider the lens shading effect and white balance, which are major factors in the image signal processing. In this paper, pixel distances from the image center and channel average values are used to consider the lens shading effect and white balance with a deep learning model. Experiments with low-light images taken with a smart phone demonstrate that the proposed method achieves a higher peak signal to noise ratio and structural similarity index measure than the existing method by creating high-quality low-light images.

• Journal of Adhesion and Interface
• /
• v.24 no.2
• /
• pp.60-63
• /
• 2023

The AlGaN/GaN heterostructure has high electron mobility due to the two-dimensional electron gas (2-DEG) layer, and has the characteristic of high breakdown voltage at high temperature due to its wide bandgap, making it a promising candidate for high-power and high-frequency electronic devices. Despite these advantages, there are factors that affect the reliability of various device properties such as current collapse. To address this issue, this paper used metal-organic chemical vapor deposition to continuously deposit AlGaN/GaN heterostructure and SiN passivation layer. Material and electrical properties of GaN HEMTs with/without SiN cap layer were analyzed, and based on the results, low-frequency noise characteristics of GaN HEMTs were measured to analyze the conduction mechanism model and the cause of defects within the channel.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.2
• /
• pp.97-103
• /
• 2023

Since most of the information is transmitted through the network, eavesdropping and interception by a third party may occur. Appropriate measures are required for effective, secure and confidential communication in the network. Steganography is a technology that prevents third parties from detecting that confidential information is hidden in other media. Due to structural vulnerabilities, information protected by encryption and steganography techniques can be easily exposed to illegitimate groups. In order to improve the limitations of LSB where the simplicity and predictability of the hiding method exist, I propose a technique to improve the security of the message to be hidden based on PRNG and recursive function. To enhance security and confusion, XOR operation was performed on the result of selecting a random bit from the upper bits of the selected channel and the information transformed by the RS-box. PSNR and SSIM were used to confirm the performance of the proposed method. Compared to the reference values, the SSIM and PSNR of the proposed method were 0.9999 and 51.366, respectively, confirming that they were appropriate for hiding information.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.79-86
• /
• 2024

In this paper, a novel visual tracking method which can utilize the context of object regions is presented. Conventional methods have the inherent problem of treating all candidate regions independently, where the tracker could not successfully discriminate regions with similar appearances. This was due to lack of contextual modeling in a given scene, where all candidate object regions should be taken into consideration when choosing a single region. The goal of the proposed method is to encourage feature exchange between candidate regions to improve the discriminability between similar regions. It improves upon conventional methods that only consider a single region, and is implemented by employing the MLP-Mixer model for enhanced feature exchange between regions. By implementing channel-wise, inter-region interaction operation between candidate features, contextual information of regions can be embedded into the individual feature representations. To evaluate the performance of the proposed tracker, the large-scale LaSOT dataset is used, and the experimental results show a competitive AUC performance of 0.560 while running at a real-time speed of 65 fps.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.4
• /
• pp.401-407
• /
• 2009

In this paper, we propose a novel method for the cross-correlation based double-talk detection (DTD), which employing the Gaussian Mixture Model (GMM) in the frequency domain. The proposed algorithm transforms the cross correlation coefficient used in the time domain into 16 channels in the frequency domain using the discrete fourier transform (DFT). The channels are then selected into seven feature vectors for GMM and we identify three different regions such as far-end, double-talk and near-end speech using the likelihood comparison based on those feature vectors. The presented DTD algorithm detects efficiently the double-talk regions without Voice Activity Detector which has been used in conventional cross correlation based double-talk detection. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional schemes. especially, show the robustness against detection errors resulting from the background noises or echo path change which one of the key issues in practical DTD.

• Journal of Internet of Things and Convergence
• /
• v.10 no.4
• /
• pp.43-53
• /
• 2024

Tomatoes are rich in nutrients like lycopene, β-carotene, and vitamin C. However, they often suffer from biological and environmental stressors, resulting in significant yield losses. Traditional manual plant health assessments are error-prone and inefficient for large-scale production. To address this need, we collected a comprehensive dataset covering the entire life span of tomato plants, annotated across 5 health states from 1 to 5. Our study introduces an Attention-Enhanced DS-ResNet architecture with Channel-wise attention and Grouped convolution, refined with new training techniques. Our model achieved an overall accuracy of 80.2% using 5-fold cross-validation, showcasing its robustness in precisely classifying the health states of tomato plants.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.1-31
• /
• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• Land and Housing Review
• /
• v.7 no.1
• /
• pp.9-18
• /
• 2016

This research aims to build a total information system that systematizes existing sporadic information, which may lead to revitalization and efficiency of overseas urban development. To achieve this, this study firstly analyses the current information systems for urban development in foreign countries and information from the private sector. The results show that the information system that operates in the domestic agencies, are less likely to involve the contents related to information sharing, social network building and business process. However, that used in agencies ordering the overseas urban development projects, mostly provides the information of professionals, project participants and their business. Second, this research selects the information to be provided by the integrated information system and proposes a data collection plan. The information, required to push forward urban development in abroad, is classified into seven categories. Third, this study establishes a target model of comprehensive information system and makes suggestions for institutional improvement. For doing this, it categorizes overseas urban development information, links to classified information, organizes the system into three stages to services through informational channels, and then suggests a target model. Furthermore, it proposes institutional improvement to achieve efficiency of information systems through a comprehensive review of the similar cases such as administrative system of architecture(Seumter) and land information system.