This paper studied the post-processing process of the fused deposition modeling (FDM) process, one of the most widely used 3D printing technologies recently, in prototyping, which is a leading step in the development of various IoT products. The proposed post-treatment process is warm isostatic pressing (WIP), which can improve the mechanical properties and waterproof function of parts made by the FDM process. There are various process parameters in the WIP process, but in this study, the experiment was planned with the holding time of temperature and cooling ways as important variables. The specimens were manufactured in a direction that showed the most dramatic WIP effect, and in order to determine the effect of the WIP process, specimens without WIP treatment were manufactured and tested in the same manner. The experimental results confirmed that the WIP process improved mechanical properties and waterproofing effects. In addition, the temperature holding time did not affect the mechanical properties, and the mechanical change due to the difference in cooling method showed a 5% difference.
Hot data is frequently used data that affects the performance and lifespan of a storage system. Therefore, classifying and managing the identified hot data is important for the performance and lifetime of storage devices, especially for NAND flash memory, which is characterized by rapid degradation after repeated intensive write operations to specific blocks. In this paper, we design a hot data classifier and management scheme for an efficient resource management in flash memory-based storage devices by benchmarking traces extracted from enterprise servers. Also, we propose a method to measure the frequency of hot data using multiple hashes, and to improve the performance and lifetime of the storage system by classifying the identified hot data and managing it on degradation-resistant media. Finally, we demonstrate the effectiveness of the proposed method by measuring the increased performance and lifetime through experiments.
Wheelchairs currently come in two types: electric and manual. However, even electric wheelchairs require some degree of muscle control for operation. Individuals with limited muscle control often rely on someone else to push their wheelchair, depriving them of the independence that everyone desires. Consequently, there is a need for wheelchairs that individuals without muscle control can operate independently. The brainwave-based omnidirectional mobility Mecanum wheel analyzes frequency components similar to those of a stimulator in the occipital lobe (O1, O2, P7, P8) of the user, utilizing an SVM model for control. Equipped with cameras and ultrasonic sensors, the device can detect objects and distances, allowing it to halt and prevent falls at elevated thresholds. Moreover, the camera can provide the caregiver with a front view of the user's surroundings, while GPS enables more accurate real-time monitoring of the user's location, ensuring the user's safety and facilitating caregiver monitoring. This technology aims to enhance the quality of life for individuals with limited muscle control and their caregivers, enabling greater freedom of movement for the disabled and easier monitoring for caregivers.
This paper studied the post-processing process of the fused deposition modeling (FDM) process, one of the most widely used 3D printing technologies recently, in prototyping, which is a leading step in the development of various IoT products. The proposed post-treatment process is warm isostatic pressing (WIP), which can improve the mechanical properties and waterproof function of parts made by the FDM process. There are various process parameters in the WIP process, but in this study, the experiment was planned with the holding time of temperature and cooling ways as important variables. The specimens were manufactured in a direction that showed the most dramatic WIP effect, and in order to determine the effect of the WIP process, specimens without WIP treatment were manufactured and tested in the same manner. The experimental results confirmed that the WIP process improved mechanical properties and waterproofing effects. In addition, the temperature holding time did not affect the mechanical properties, and the mechanical change due to the difference in cooling method showed a 5% difference.
The purpose of this study is to develop an educational content system for early childhood artificial intelligence education. For the purpose of the study, FGI was conducted on five early childhood education and artificial intelligence experts. The experts' claims were analyzed using the semantic interpretation method. The meaning interpretation method uses meaning compression - meaning categorization - meaning structuring. The experts' claims were condensed into 43 meanings. The 43 meanings were composed of 12 contents ranging from 'Human thinking process, computing ability, Principles and history of AI, Utilization of AI technology, Concept of data, Creative expression of AI, AI hardware configuration for creative convergence problem solving, Exploration and use of AI tools for creative and convergent problem solving, Creation of AI for creative and convergent problem solving, Interest in AI, Living with AI, Ethical use and attitudes of AI' using categorization. The 12 contents were organized into four categories, ranging from semantic structuring to Computational Thinking, AI and data, Creative convergence Problem solving, AI ethics. The results of this study are valuable in that they can serve as a basis for constructing artificial intelligence education in the field of early childhood education.
In this paper, we propose a artificial intelligence-based parking system that efficiently uses existing parking lot rather than creating new parking sites.To this end, parking spaces through CCTV, parking space information provides parking spaces information, and intuitive interface design, and intuitive interface design.In addition, there are strong security and personal information protection functions to overcome the limit of existing parking pipe platform.In this study, intelligent parking tube system implementation system improves user convenience and parking problems of the city design and implementation of the city design and implementation of the system design and implementation of system design and implementation.
This study aims to share a case of periodontal management practical training conducted through ICT learning, with the purpose of investigating the relationships among learning attitudes, affective experience, and academic achievement according to application blended learning. Eighty-nine dental hygiene students participated in this study. Theory classes conducted online and in face-to-face classes, quizzes were conducted to check prior learning, supplementary explanations for content that was lacking in understanding, and theoretical content was practiced in the form of practice. The results of this study showed that the learning attitude was 3.47, affective experience was 3.88, academic achievement was 3.42. The analysis of correlations among the variables showed that learning attitude has a positive correlation with affective experience(r=0.482, p<0.01) and academic achievement(r=0.400, p<0.01), and affective experience has a positive correlation with academic achievement(r=0.236, p<0.05). Therefore, the blended learning is considered to be applicable to classes that cover theory and practice.
The purpose of this study is to construct competency factor and sub-factor for early childhood artificial intelligence education. Literature analysis and expert Delphi survey were used to achieve the purpose of the study. For literature analysis, data were searched, and 4 domestic and 3 international data were collected. The collected data was analyzed. And 4 factor and 25 sub-factor were composed. The first constructed factor are understanding artificial intelligence (5 sub-factor), thinking about artificial intelligence (6 sub-factor), utilizing artificial intelligence (8 sub-factor), and value of artificial intelligence (6 sub-factor). The initially constructed factor were verified through expert Delphi, and the experts suggested that the competency element and sub-factor were at an acceptable level, but that the sub-factor should be supplemented. Accordingly, this study was revised by collecting opinions from experts. The revised factor are understanding artificial intelligence (6 sub-factor), thinking about artificial intelligence (2 sub-factor), utilizing artificial intelligence (6 sub-factor), and value artificial intelligence (6 sub-factor). The revised factor were verified as valid through an expert Delphi survey. Accordingly, this study proposed the revised factor as the final factor. The results of this study have many implications in that they provide important evidence for constructing an early childhood artificial intelligence curriculum.
The promotion of intelligent security community construction has greatly enhanced the intelligence and safety of residential areas. In order to further establish a security-oriented community, this paper proposes the utilization of facial recognition based on community surveillance footage to identify suspicious individuals. To address the difficulties in capturing facial images caused by factors such as low pixel resolution and varying shooting angles in surveillance footage, the following optimization strategies are proposed in this paper : Firstly, a lightweight global search facial detection network is designed based on convolutional modules and Vision Transformer modules. The Vision Transformer module is introduced to enhance the global retrieval capability of the network. Secondly, the structure of the Vision Transformer module is optimized by adding pooling layers in the feature block extraction and segmentation stage to reduce the number of module parameters. The feature blocks are mapped and computed with the feature maps to improve the corresponding feature correlation. Thirdly, in the face alignment stage, an Anchor Free mechanism is adopted to generate elliptical face localization regions for more accurate fitting of faces and reducing interference from other background information in the final identity recognition stage. Finally, the similarity between faces is calculated using Euclidean space distance to determine corresponding personnel identities. Through relevant experiments and tests on the self-built facial identity dataset in this paper's residential surveillance system, the proposed facial detection network achieves an average improvement of 3.11% in detection accuracy compared to other detection networks, reaching 97.19%. In terms of facial identity recognition, the designed model achieves an average improvement of 3.43% with a recognition accuracy of 95.84.
PKI(Public Key Infrastructure) is used to enforce legal binding forces to the Internet services. The PKI certificate is the legal certification of the user's public key and is issued by the trustworthy CA(Certificate Authority) designated by the government. Therefore, users can create legally binding signatures based on PKI certificates. Because biometric data is unique to each person, biometric authentication can legally prove one's identity without the help of PKI system. As users participating in Internet services such as social media are not subject to regional restrictions, thus it is not easy to implement Internet services based on PKI. Blockchain is a technology that stores data that cannot be modified or deleted, and does not require the help of a trusted third party. The block to add is determined by consensus of users participating in the blockchain network. In this study, we propose the undeniable biometric signature scheme based on Ethereum smart contracts. The proposed scheme consists of biometric template registration, undeniable signature generation, and verification protocolss. The Undeniable signature cannot be verified without the help of the signer. The signer uses a challenge-response protocol to show the legitimacy of the signature only to the desired verifier. The proposed scheme can be extended to a multi-signature scheme by modifying the El-Gamal signature scheme and can increase the reliability of blockchain-based Internet services.
With the interest in the Internet of Things and the rapid development of e-commerce, the emergence of new service O2O service experience stores is increasing. In the study, the characteristics of the online and offline combined service model O2O service were identified. The marketing model of China's O2O service experience store was analyzed and compared. In particular, a survey was conducted on female consumers in their 20s~40s in Shanghai, China, a leading fashion city, to study O2O service consumption behavior and conduct data analysis. The survey period was conducted from April 8, 2023 to April 18, 2023, and 506 were used as final analysis data. SPSS26.0 and AMOS26.0 structural equation model analysis were used. The empirical analysis results of this study showed that, first, online and offline experiences have a positive effect on brand value. Second, as a result of analyzing the impact of brand value on brand commitment on O2O service experience store experience, it was found that brand value had a positive effect on brand commitment. Third, it was found that the experience of the 020 service experience store affects brand value, which has a positive effect on brand Repeat-Using Intention. Fourth, it was found that the brand commitment to the O2O service experience store experience had a positive effect on brand repeat-using intention.
In the IoT environment, various efforts for sustainability are underway based on ESG. ESG is important in today's business operations and strategies, covering a wide range of issues affecting people and communities as well as the environment. In particular, information security education in the field of information and data security belongs to the social domain of ESG. This shows that protecting sensitive information, user privacy, and digital rights is an important part of an organization's social responsibility. In order to strengthen security based on ESG in the Internet of Things environment, a training course that takes into account the characteristics of the Internet of Things environment is needed. In this paper, we proposed an ESG-based information security education model in the Internet of Things environment. The proposed education model was designed as an information security education course for ESG for sustainability of the Internet of Things environment. The proposed curriculum model was implemented at three institutions and the effectiveness of the curriculum was confirmed through a survey of training participants.
In order to proactively respond to increasingly intelligent and sophisticated cyber-attacks targeting heterogeneous IoT systems, there is a need for techniques that efficiently share threat information collected when intrusion incidents occur. Techniques should be presented for generating various IoC(Indicators of Compromise) information from various digital forensic artifacts collected from various IoT devices, and for sharing this information through CTI(Cyber Threat Intelligence) systems such as MISP. In this study, when various artifacts are collected upon intrusion incidents in IoT devices, we propose a method for generating detailed attack information as IoCs and sharing threat information efficiently by applying the Hub & Spoke model in CTI systems like MISP. The application of the proposed threat information sharing model is expected to enhance response time and detection performance in the cyber incident analysis process, thus improving the ability to detect and respond to intelligent cyber-attacks targeting IoT devices.