• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.139-166
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• 2022

Ethical Issues increase when people engage in smart technological systems such as 5G, IoT, Cloud computing services and AI applications. Range of this research is comparison of various literacy concepts and its ethical issues in considering of 5G features and UX. 86 research papers and reports which have been published within the recent 5 years (2017-2022), relating the research subject, are investigated and analyzed. Two results show that various literacies can be grouped into four areas and that some of common issues among those areas as well as unique issues of each area are identified. Based on the literature analysis, an Operational Definition of Ethics-Literacy is presented and the model of ethics-literacy curriculum supporting ethical behavior of 5G information professionals is developed and suggested.

• Journal of Animal Reproduction and Biotechnology
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• v.38 no.2
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• pp.77-83
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• 2023

Background: Serotonin receptors can be divided into seven different families with various subtypes. The serotonin 1A (5-HT1A) receptor is one of the most abundant subtypes in animal brains. The expression of 5-HT1A receptors in the brain has been reported in various animals but has not been studied in horses. The 5-HT1A receptor functions related to emotions and behaviors, thus it is important to understand the functional effects and distribution of 5-HT1A receptors in horses to better understand horse behavior and its associated mechanism. Methods: Brain samples from seven different regions, which were the frontal, central, and posterior cerebral cortices, cerebellar cortex and medulla, thalamus, and hypothalamus, were collected from six horses. Western blot analysis was performed to validate the cross-reactivity of rabbit anti-5-HT1A receptor antibody in horse samples. Immunofluorescence was performed to evaluate the localization of 5-HT1A receptors in the brains. Results: The protein bands of 5-HT1A receptor appeared at approximately 50 kDa in the frontal, central, and posterior cerebral cortices, cerebellar cortex, thalamus, and hypothalamus. In contrast, no band was observed in the cerebellar medulla. Immunofluorescence analysis showed that the cytoplasm of neurons in the cerebral cortices, thalamus, and hypothalamus were immunostained for 5-HT1A receptors. In the cerebellar cortex, 5-HT1A was localized in the cytoplasm of Purkinje cells. Conclusions: In conclusion, the study suggests that 5-HT and 5-HT1A receptor systems may play important roles in the central nervous system of horses, based on the widespread distribution of the receptors in the horse brain.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.729-740
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• 2022

Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. It is a matter of great interest for the streaming service providers to preview their service infrastructure and streaming strategy in order to provide new streaming services. Hence, the first part of the paper presents a detailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers. To understand the streaming strategy of these service providers, the second part of the paper deduces a common quality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standard deviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of these services. This study concluded that the streaming behaviors of all these services are similar as they all use Dynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that they download in the buffering state and steady-state vary, resulting in different progressive download ratios, rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in different QoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors of these services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The survey results indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Prime and YouTube. Our approach can be used to compare and contrast the streaming services' strategies and finetune their ABR and flow control mechanisms.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.543-550
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• 2009

The traditional simple extrapolation type short term quantitative rainfall forecast can not realize the evolution of rainfall generating weather system. To overcome the drawback of the linear extrapolation type rainfall forecasting model, the history of a weather system from sequential weather radar information and a polynomial regression technique were used to generate forecast fileds of x-directional, y-directional velocities and radar reflectivity which considered the nonlinear behavior related to the evolution of weather systems. Results demonstrated that test statistics of forecasts using the developed model is better than that of 2-CAPPI forecast. However there is still a large room to improve the forecast of spatial and temporal evolution of local storms since the model is not based on a fully physical approach but a statistical approach.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.389-400
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• 2023

Technological advancements in the field of information and communication have led to the advent and usage of various types of smart devices, which have significantly altered people's usage behaviors and environments. This change has also been applied to the learning environment, where various smart devices are appearing and the learning behavior of learners is changing accordingly. In this study, we investigate learners' perceptions of digital note-taking behaviors focusing on the recently emerged learning media, tablet PCs and digital pens. Drawing upon the expectancy-confirmation model, we conduct a study on the factors affecting the (dis)confirmation and (dis)satisfaction of undergraduate students with tablet PCs and digital pens by comparing their expectations with their actual use experiences. An open-ended survey was conducted among students at C University in Korea, and the responses were analyzed through qualitative content analysis to derive four factors of expectation-confirmation and satisfaction and three factors of expectation-disconfirmation and dissatisfaction. Based on these findings, we provide academic and educational implications.

• Convergence Security Journal
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• v.23 no.3
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• pp.37-47
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• 2023

The growth of the metaverse has been accelerated by the increased demand for non-face-to-face interactions due to COVID-19 and advancements in technologies such as blockchain and NFTs. However, with the emergence of various metaverse platforms and the corresponding rise in users, criminal cases such as ransomware attacks, copyright infringements, and sexual offenses have occurred within the metaverse. Consequently, the need for artifacts that can be utilized as digital evidence within metaverse systems has increased. However, there is a lack of information about artifacts that can be used as digital evidence. Furthermore, metaverse security evaluation and forensic analysis are also insufficient, and the absence of attack scenarios and related guidelines makes forensics challenging. To address these issues, this paper presents artifacts that can be used for user behavior analysis and timeline analysis through dynamic analysis of Roblox, a representative metaverse gaming solution. Based on analyzing interrelationship between identified artifacts through memory forensics and log file analysis, this paper suggests the potential usability of artifacts in metaverse crime scenarios. Moreover, it proposes improvements by analyzing the current legal and regulatory aspects to address institutional deficiencies.

• Advances in nano research
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• v.16 no.2
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• pp.111-125
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• 2024

Recently, a lot of research has been done on the analysis of axial vibrations of homogeneous and FG nanotubes (nanorods) with various aspects of vibrations that have been fully mentioned in history. However, there is a lack of investigation of the dynamic internal resonances of FG nanotubes (nanorods) between them. This is one of the essential or substantial characteristics of nonlinear vibration systems that have many applications in various fields of engineering (making actuators, sensors, etc.) and medicine (improving the course of diseases such as cancers, etc.). For this reason, in this study, for the first time, the dynamic internal resonances of FG nanorods in the simultaneous presence of large-amplitude size dependent behaviour, inertial and shear effects are investigated for general state in detail. Such theoretical patterns permit as to carry out various numerical experiments, which is the key point in the expansion of advanced nano-devices in different sciences. This research presents an AFG novel nano resonator model based on the axial vibration of the elastic nanorod system in terms of derivation from large-amplitude size dependent internal modals interactions. The Hamilton's Principle is applied to achieve the basic equations in movement and boundary conditions, and a harmonic deferential quadrature method, and a multiple scale solution technique are employed to determine a semi-analytical solution. The interest of the current solution is seen in its specific procedure that useful for deriving general relationships of internal resonances of FG nanorods. The numerical results predicted by the presented formulation are compared with results already published in the literature to indicate the precision and efficiency of the used theory and method. The influences of gradient index, aspect ratio of FG nanorod, mode number, nonlinear effects, and nonlocal effects variations on the mechanical behavior of FG nanorods are examined and discussed in detail. Also, the inertial and shear traces on the formations of internal resonances of FG nanorods are studied, simultaneously. The obtained valid results of this research can be useful and practical as input data of experimental works and construction of devices related to axial vibrations of FG nanorods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.71-78
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• 2008

In the case of the railway bridges, uplift forces were occurred at the edge of the segments when vehicular loads were applied. These forces caused the compressive and tensile forces in the fastening system. In the past, a structural analysis has been performed to investigate the safety of fastening system which was modeled with one directional spring elements based on the compressive test of fastening system. In this case, the stiffness of the spring element was obtained from experimental study which was conducted by compressive load. Therefore, to perform rational and exact structural analysis, the translational stiffness of the fastening system obtained from the experimental study applied the tensile load and the rotational stiffness should be considered because it was occurred the tensile force as well as the compressive force in fastening system. In this study, an elastic and inelastic experimental study was performed for six specimens. The translational stiffness along the vertical axis of rail and the rotational stiffness along the strong axis of rail were investigated, also structural behavior of the fastening system was analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2665-2691
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• 2024

The philosophy of Zero Trust in cybersecurity lies in the notion that nothing assumes to be trustworthy by default. This drives defense organizations to modernize their cybersecurity architecture through integrating with the zero-trust principles. The enhanced architecture is expected to shift protection strategy from static and perimeter-centric protection to dynamic and proactive measures depending on the logical contexts of users, assets, and infrastructure. Given the domain context of defense environment, we aim three challenge problems to tackle and identify four technical approaches by the security capabilities defined in the Zero Trust Architecture. First approach, dynamic access control manages visibility and accessibility to resources or services with Multi Factor Authentication and Software Defined Perimeter. Logical network separation approach divides networks on a functional basis by using Software Defined Network and Micro-segmentation. Data-driven analysis approach enables machine-aided judgement by utilizing Artificial Intelligence, User and Entity Behavior Analytics. Lastly, Security Awareness approach observes fluid security context of all resources through Continuous Monitoring and Visualization. Based on these approaches, a comprehensive study of modern technologies is presented to materialize the concept that each approach intends to achieve. We expect this study to provide a guidance for defense organizations to take a step on the implementation of their own zero-trust architecture.