• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.641-648
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• 2023

Recently, the rapid growth of artificial intelligence among the 4th industrial revolution has progressed based on the performance improvement of semiconductor, and circuit integration. According to transistors, which help operation of internal electronic devices and equipment that have been progressed to be more complicated and miniaturized, the control of heat generation and improvement of heat dissipation efficiency have emerged as new performance indicators. The DUT(Device Under Test) Shell is equipment which detects malfunction transistor by evaluating the durability of transistor through heat dissipation in a state where the power is cut off at an arbitrary heating point applying the rating current to inspect the transistor. Since the DUT shell can test more transistor at the same time according to the heat dissipation structure inside the equipment, the heat dissipation efficiency has a direct relationship with the malfunction transistor detection efficiency. Thus, in this paper, we propose various method for PCB configuration structure to optimize heat dissipation of DUT shell and we also propose various transformation and thermal analysis of optimal DUT shell using computational fluid dynamics.

• Smart Media Journal
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• v.11 no.2
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• pp.63-69
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• 2022

As the use of various IoT devices increases, the importance of IoT platforms is also rising. Recently, artificial intelligence technology is being combined with IoT devices, and research applying a neuromorphic architecture to IoT devices with low power is also increasing. In this paper, an application scenario is proposed based on NA-IDE (Neuromorphic Architecture-based autonomous IoT application integrated development environment) with IoT devices and FPGA devices in a GUI format. The proposed scenario connects a camera module to an IoT device, collects MNIST dataset images online, recognizes the collected images through a neuromorphic board, and displays the recognition results through a device module connected to other IoT devices. If the neuromorphic architecture is applied to many IoT devices and used for various application services, the autonomous IoT application integrated development environment based on the neuromorphic architecture is expected to emerge as a core technology leading the 4th industrial revolution.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.35-41
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• 2017

With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.1-13
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• 2021

This study tried to suggest ways to improve the indicator system to strengthen the personal information protection. For this purpose, the components of indicator system are derived through domestic and foreign literature, and it was selected as main the diagnostic indicators through FGI/Delphi analysis for personal information protection experts and a survey for personal information protection officers of public institutions. As like this, this study was intended to derive an inspection standard that can be reflected as a separate index system for personal information protection, by classifying the specific IT technologies of the 4th industrial revolution, such as big data, cloud, Internet of Things, and artificial intelligence. As a result, from the planning and design stage of specific technologies, the check items for applying the PbD principle, pseudonymous information processing and de-identification measures were selected as 2 common indicators. And the checklists were consisted 2 items related Big data, 5 items related Cloud service, 5 items related IoT, and 4 items related AI. Accordingly, this study expects to be an institutional device to respond to new technological changes for the continuous development of the personal information management level diagnosis system in the future.

• Journal of Industrial Convergence
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• v.16 no.1
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• pp.21-26
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• 2018

The Seaborne Trade Volume accounts for 97% of the total. This means that the port operation management system can improve port efficiency, reducing operating costs, and the manager who manages all operations at the port needs to check and respond quickly when delays of work and equipment support is needed. Based on the real-time location information confirmation of yard automation equipment used the existing system GPS, the real-time location information confirmation system is a GPS system of the tablet, rather than a port operation system that monitors location information for the entered information, depending on the completion of the task or the start of the task. Network configurations also reduce container processing delays by using commercial LTE services that do not have shading due to containers in the yard also reduce container processing delays. Trough introduction of smart devices using Android or IOS and container processing scheduling utilizing artificial intelligence, we will build a minimum delay system with Smart Device usage of container processing applications and optimization of container processing schedule. The adoption of smart devices and the minimization of container processing delays utilizing artificial intelligence are expected to improve the quality of port services by confirming the processing containers in real time to consumers who are container information demanders.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.87-94
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• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Land and Housing Review
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• v.14 no.3
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• pp.125-135
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• 2023

In South Korea, it has been increased the necessity of supplying housing services to meet the needs and desires of various residents by reflecting various demographic and social changes. In particular, various smart device has been widely utilized in South Korea and the smart technologies, such as artificial intelligence and the Internet of Things has been developed rapidly. These smart technologies could support smart housing that allows residents to easily and comfortably employ residential services. However, it is necessary to improve the awareness of users in order to spread the smart housing residential services connected to smart technologies. For this reason, this study observed changes in users' perceptions of smart housing residential service technology using Living Lab. As a result, after experiencing the Living Lab, users' awareness of smart housing housing service increased, and it was observed that the preferred housing service technology was more detailed than before the Living Lab experience. This study shows that it is important to raise users' awareness for the dissemination of smart housing residential service technology, and that Living Lab can be an effective means for this purpose.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.470-476
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• 2020

In this paper, we present the design of modular replaceable AI server for image deep learning that separates the server from the Edge Device so as to drive the AI block and the method of data transmission and reception. The modular replaceable AI server for image deep learning can reduce the dependency between social robots and edge devices where the robot's platform will be operated to improve drive stability. When a user requests a function from an AI server for interaction with a social robot, modular functions can be used to return only the results. Modular functions in AI servers can be easily maintained and changed by each module by the server manager. Compared to existing server systems, modular replaceable AI servers produce more efficient performance in terms of server maintenance and scale differences in the programs performed. Through this, more diverse image deep learning can be included in robot scenarios that allow human-robot interaction, and more efficient performance can be achieved when applied to AI servers for image deep learning in addition to robot platforms.