• Computers and Concrete
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• v.24 no.5
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• pp.469-488
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• 2019

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.139-144
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• 2022

The smart cities are evolving constantly and are responsible for the current transformation of cities and countries into a completely connected network of information and technology This interconnected network of a huge number of smart devices is capable of exchanging complex information and provides tremendous support including enhanced quality of life within urban locations. Unfortunately this set-up is vulnerable to security attacks and requires the widespread ubiquitous network to authorize access through privacy and thus offer security in order to ensure civilian participation in a country. The smart network should benefit the individuals of the country by developing potential strategies to protect the smart cities and their participating entities from the unauthorized attacks. Trustworthy data sharing strategies based on the utilization of advanced technology features via smart communication network could solve some issues of privacy and security. This paper presents the challenges and issues related to protection and highlights the important aspects of securing the smart cities and its components. It also presents the role of cloud security for building a secure smart city.

• The Journal of Information Systems
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• v.31 no.2
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• pp.137-158
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• 2022

Purpose As artificial intelligence voice agents (AIVA) have been widely adopted in services, diverse forms of their voices, which are the main interface with users, have been experimented. The purpose of this study is to examine how users evaluate vocal characteristics (gender, voice pitch, and voice pace) of AIVA, depending on prior research on human voice attractiveness. Design/methodology/approach This study employed an experimental survey which 516 participated in. Each participant was randomly assigned into one of eight situations (e.g., male - higher pitch - faster pace) and listened a AIVA voice sample, which introduce weather information. Next, a participant answered three consequence factors (attractiveness, trust, and anthropomorphism). Findings The results reveal that female voices of AIVA were perceived as more attractive and trustworthy than male voices. As far as voice pitch goes, while lower-pitch voices were preferred in female voices, higher-pitch voices were preferred in male voices. Finally, faster voices of AIVA were more attractive than slower voices.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.627-630
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• 2022

Over the past few years, fake news has become one of the most significant problems. Since it is impossible to prevent people from spreading misinformation, people should analyze the news themselves. However, this process takes some time and effort, so the routine part of this analysis should be automated. There are many different approaches to this problem, but they only analyze the text and messages, ignoring the images. The fake news problem should be solved using a complex analysis tool to reach better performance. In this paper, we propose the approach of training an Artificial Intelligence using an unsupervised learning algorithm, combined with online data parsing tools, providing independence from subjective data set. Therefore it will be more difficult to spread fake news since people could quickly check if the news or article is trustworthy.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.485-496
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• 2023

Precise construction cost estimation is paramount to determining the total construction expense of a project prior to the initiation of the construction phase. Despite this, manual quantification and cost estimation methods, which continue to be widely used, may result in imprecise estimation and subsequent financial loss. Given the fast-paced and efficiency-demanding nature of the construction industry, trustworthy quantity and cost estimation is essential. To mitigate these obstacles, this research is focused on establishing an automated quantity estimation algorithm, particularly designed for the main rebar of beams which are recognized for their complicated reinforcement configurations. The exact quantity derived from the proposed algorithm is compared to the manually approximated quantity, reflecting a variance of 10.27%. As a result, significant errors and impending financial loss can be averted. The implementation of the findings from this research holds the potential to significantly assist construction firms in quickly and accurately estimating rebar quantities while adhering strictly to applicable specifications and regulatory requirements.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.129-140
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• 2019

In the IoT environment, there is a huge amount of heterogeneous devices with limited capacity. Existing trust evaluation methods are not adequate to accommodate this requirement due to the limited storage space and computational resources. In addition, since IoT devices are mainly human operated devices, the trust evaluation should reflect the social relations among device owners. There is also a need for a mechanism that reflects the tendency of the trustor and environmental factors. In this paper, we propose an adaptable trust evaluation method for SOA-based IoT system to deal with these issues. The proposed model is designed to minimize the confidence bias and to dynamically respond to environmental changes by combining direct evaluation and indirect evaluation. It is expected that it will be possible to secure trust through quantitative evaluation by providing feedback based on social relationships.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.501-508
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• 2024

Organizational citizenship behavior refers to the behavior of faithfully performing one's duties and being faithful to other roles. Firefighters' awareness of organizational citizenship behavior is closely related to national and individual safety and is very important. The smooth communication and cooperative attitude of fire department employees means organic unity at the disaster site. The purpose of this study was to analyze the awareness of organizational citizenship behavior among firefighters. As a result of analyzing the overall level of organizational citizenship behavior of firefighters, the average score was 3.83 points (out of 5). In particular, significant implications emerged regarding work-related appointment times and words and actions between co-workers. In the future, we hope that firefighting policy authorities will make a lot of efforts and academic research by subsequent generations will be conducted to make firefighting more trustworthy to the public.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.64-69
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• 2024

Blockchain is a decentralized network in which data blocks are linked. Through a decentralized peer-to-peer network, users can create shared databases, resulting in a trustworthy and aggregated database known as a blockchain that enhances reliability and security. The distributed nature of the blockchain enables data to be stored on multiple nodes, eliminating the need for a central server or platform. This disintermediation significantly reduces the transaction and administrative costs. The blockchain is particularly valuable in applications where reliability and stability are critical because it establishes an open database that ensures data integrity, making it virtually impossible to tamper with or falsify data. This study explores the diverse applications of the blockchain technology in virtual assets, such as cryptocurrency, decentralized finance, central bank digital currency, nonfungible tokens, and metaverses. In addition, it analyzes the potential prospects and developments driven by these innovative technologies.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.74-85
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• 2024

The advent of 6G mobile communication technologies promises to surpass the capabilities of existing 5G by offering ultra high-speed data transmission, ultra low latency, and extensive connectivity, enabling a new wave of digital transformation across various fields. However, the openness and decentralized nature of 6G systems, which enhance their flexibility and scalability, can expand the attack surface and increase security threats from cyber-attacks. In this article, we analyze the current research trends related to security in the 6G mobile communication landscape.