• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.107-115
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• 2022

The purpose of this study is to identify the drivers of supply chain vulnerability and internal/external disruptive events and to verify the moderating effect of SCRM to mitigate negative disruption impacts. The analysis results of 182 SMEs are as follows. First, SC vulnerability proceeded from excessive efficiency. Second, the probability and severity of internal factors were higher than that of external factors. In particular, the priority of responding to risks arising from the supply chain process was higher than the value chain within the firm. Finally, the higher the level of risk management in the supply chain, the more positively the negative disruption impact was mitigated. This study is valuable in providing practical clues to the decision-making of a firm's managers and policymakers responding to supply chain risks.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.527-537
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• 2022

As multimedia contents demand and supply increase, internet traffic around the world increases. Several standardization groups are striving to establish more efficient compression standards to mitigate the problem. In particular, research to introduce deep learning technology into compression standards is actively underway. Despite the fact that deep learning-based technologies show high performance, they suffer from the domain gap problem when test video sequences have different characteristics of training video sequences. To this end, several methods have been made to introduce content-adaptive deep video compression. In this paper, we will look into these methods by three aspects: codec information-aware methods, model selection methods, and information signaling methods.

• Wind and Structures
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• v.36 no.2
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• pp.91-103
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• 2023

Tuned liquid dampers (TLDs) are increasingly being used as efficient dynamic vibration absorbers to mitigate wind-induced vibration in super high-rise buildings. However, the damping characteristics of screens and the control effectiveness of actual structures must be investigated to improve the reliability of TLDs in engineering applications. In this study, a numerical TLD model is developed using computational fluid dynamics (CFD) and a simulation method for achieving the coupled vibration of the structure and TLD is proposed. The numerical results are verified using shaking table tests, and the effects of the solidity ratio and screen position on the TLD damping ratios are investigated. The TLD control effectiveness is obtained by simulating the wind-induced vibration response of a full-scale structure-TLD system to determine the optimal screen solidity ratio. The effects of the structural frequency, damping ratio, and wind load amplitude on the TLD performance are further analyzed. The TLD damping ratio increases nonlinearly with the solidity ratio, and it increases with the screens towards the tank center and then decreases slightly owing to the hydrodynamic interaction between screens. Full-scale coupled simulations demonstrated that the optimal TLD control effectiveness was achieved when the solidity ratio was 0.46. In addition, structural frequency shifts can significantly weaken the TLD performance. The control effectiveness decreases with an increase in the structural damping ratio, and is insensitive to the wind load amplitude within a certain range, implying that the TLD has a stable damping performance over a range of wind speed variations.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.199-202
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• 2023

Carriage return (CR) and line feed (LF), also known as CRLF injection is a type of vulnerability that allows a hacker to enter special characters into a web application, altering its operation or confusing the administrator. Log poisoning and HTTP response splitting are two prominent harmful uses of this technique. Additionally, CRLF injection can be used by an attacker to exploit other vulnerabilities, such as cross-site scripting (XSS). Email injection, also known as email header injection, is another way that can be used to modify the behavior of emails. The Open Web Application Security Project (OWASP) is an organization that studies vulnerabilities and ranks them based on their level of risk. According to OWASP, CRLF vulnerabilities are among the top 10 vulnerabilities and are a type of injection attack. Automated testing can help to quickly identify CRLF vulnerabilities, and is particularly useful for companies to test their applications before releasing them. However, CRLF vulnerabilities can also lead to the discovery of other high-risk vulnerabilities, and it fosters a better approach to mitigate CRLF vulnerabilities in the early stage and help secure applications against known vulnerabilities. Although there has been a significant amount of research on other types of injection attacks, such as Structure Query Language Injection (SQL Injection). There has been less research on CRLF vulnerabilities and how to detect them with automated testing. There is room for further research to be done on this subject matter in order to develop creative solutions to problems. It will also help to reduce false positive alerts by checking the header response of each request. Security automation is an important issue for companies trying to protect themselves against security threats. Automated alerts from security systems can provide a quicker and more accurate understanding of potential vulnerabilities and can help to reduce false positive alerts. Despite the extensive research on various types of vulnerabilities in web applications, CRLF vulnerabilities have only recently been included in the research. Utilizing automated testing as a recurring task can assist companies in receiving consistent updates about their systems and enhance their security.

• Steel and Composite Structures
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• v.46 no.5
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• pp.689-707
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• 2023

Geopolymer concrete production is interesting as it is an alternative to portland cement concrete. However, workability, setting time and strength expectations limit the sustainable application of geopolymer concrete in practice. This study aims to improve the production of geopolymer concrete to mitigate these drawbacks. The improvement in the workability and setting time were achieved with the additional use of NaOH solution whereas an increase in the strength was gained with the addition of recycled steel fibers from waste tires. In addition, the use of 25% basalt powder instead of fly ash and the addition of recycled steel fibers from waste tires improved its environmental feature. The samples with steel fiber ratios ranging between 0.5% and 5% and basalt powder of 25%, 50% and 75% were tested under both compressive and flexure forces. The compressive and flexural capacities were significantly enhanced by utilizing recycled steel fibers from waste tires. However, decreases in these capacities were detected as the basalt powder ratio increased. In general, as the waste wire ratio increased, the compressive strength gradually increased. While the compressive strength of the reference sample was 26 MPa, when the wire ratio was 5%, the compressive strength increased up to 53 MPa. With the addition of 75% basalt powder, the compressive strength decreases by 60%, but when the 3% wire ratio is reached, the compressive strength is obtained as in the reference sample. In the sample group to which 25% basalt powder was added, the flexural strength increased by 97% when the waste wire addition rate was 5%. In addition, while the energy absorption capacity was 0.66 kN in the reference sample, it increased to 12.33 kN with the addition of 5% wire. The production phase revealed that basalt powder and waste steel wire had a significant impact on the workability and setting time. Furthermore, SEM analyses were performed.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.27-34
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• 2022

In this study, we aimed to determine which medical conditions of the stroke patients admitted for rehabilitation more than four weeks after onset affect caregiver burden. Participants diagnosed with stroke and their respective primary caregivers were enrolled and assessed after an 8-week follow-up period. The areas of evaluation for stroke patients included neurologic state, cognition, performance in daily life movements, gait, and balance, and caregivers were evaluated in the area of burden. The evaluation was conducted at the start of the rehabilitation course and eight weeks later. Patient caregivers were found to be under mild to moderate burden while providing care throughout the hospitalization period. The patient's neurologic state and cognition were correlated with caregiver burden. In the all patient and the subacute stroke patient group, multiple regression analysis confirmed that the neurologic state and balance stability were factors that influenced caregiver burden. Hence, we suggest that improvement in the patient's balance stability be emphasized during the course of rehabilitation to mitigate caregiver burden.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.221-243
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• 2023

The use of roadheaders has been increasing to mitigate the problems of noise and vibration during tunneling operations in urban area. Since lack of experience of roadheader for hard rock, the selection of appropriate machines and the evaluation of cutting rates have been challenging. Currently, empirical models developed overseas are commonly used to evaluate cutting rates, but their effectiveness has not been verified for domestic rocks. In this paper, a comprehensive literature review was conducted to assess the rock cutting force, cutterhead capacity, and cutting rate to select the appropriate machine and evaluate its performance. The cutterhead capacity was reviewed based on the literature results for the site. Furthermore, a new empirical model and simplified method for predicting cutting rates were proposed through data analysis in relation to operation time and rock strength, and compared with those of the conventional model from the manufacturer. The results show good agreement for high strength range upper 80 MPa of uniaxial compressive strength.

• Earthquakes and Structures
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• v.24 no.4
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• pp.275-288
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• 2023

Based on the crucial role of high-speed railway bridges (HSRBs) in the safety of high-speed railway operations, it is an important approach to mitigate earthquake hazards by proceeding with seismic risk assessments in their whole life. Bridge seismic risk assessment, which usually evaluates the seismic performance of bridges from a probabilistic perspective, provides technical support for bridge risk management. The seismic performance of bridges is greatly affected by the degradation of material properties, therefore, material damage plays a nonnegligible role in the seismic risk assessment of the bridge. The effect of material damage is not considered in most current studies on seismic risk analysis of bridges, nevertheless. To fill the gap in this area, in this paper, a nonlinear dynamic time-history analysis has been carried out by establishing OpenSees finite element model, and a seismic vulnerability analysis is carried out based on the incremental dynamic analysis (IDA) method. On this basis, combined with the site risk analysis, the time-dependent seismic risk analysis of an offshore three-span HSRB in the whole life cycle has been conducted. The results showed that the seismic risk probabilities of both components and system of the bridge increase with the service time, and their seismic risk probabilities increase significantly in the last service period due to the degradation of the material strength, which demonstrates that the impact of durability damage should be considered when evaluating the seismic performance of bridges in the design and service period.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.125-129
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• 2023

Age of Information (AoI) has been introduced in wireless networked control systems (WNCSs) to guarantee timely status updates. In addition, as the edge computing (EC) architecture has been deployed in NCS, EC close to sensors can be exploited to collect status updates from sensors and provide control decisions to actuators. However, when lots of sensors simultaneously deliver status updates, EC can be overloaded, which cannot satisfy the AoI requirement. To mitigate this problem, this paper uses actuators with computing capability that can directly receive the status updates from sensors and determine the control decision without the help of EC. To analyze the AoI of the actuation update via EC or directly using actuators, this paper developed an analytic model based on timing diagrams. Extensive simulation results are included to verify the analytic model and to show the AoI with various settings.