• Structural Engineering and Mechanics
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• v.45 no.3
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• pp.323-336
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• 2013

With the ongoing development in the computer science areas of artificial intelligence and computational intelligence, researchers are able to apply them successfully in the construction industry. Given the complexities indeep beam behaviour and the difficulties in accurate evaluation of its deflection, the current study has employed the Adaptive Network-based Fuzzy Inference System (ANFIS) as one of the modelling tools to predict deflection for high strength self compacting concrete (HSSCC) deep beams. In this study, about 3668measured data on eight HSSCC deep beams are considered. Effective input data and the corresponding deflection as output data were recorded at all loading stages up to failure load for all tested deep beams. The results of ANFIS modelling and the classical linear regression were compared and concluded that the ANFIS results are highly accurate, precise and satisfactory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1585-1609
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• 2013

Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.4
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• pp.189-199
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• 2002

This study is intended to propose a systematic procedure for the development of the conditional assessment based on the safety of structures and the cost effective performance criteria for designing and upgrading of bridge structures. As a result, a set of cost function models for a life cycle cost analysis of bridge structures is proposed and thus the expected total life cycle costs (ETLCC) including initial (design, testing and construction) costs and direct/indirect damage costs considering repair and replacement costs, human losses and property damage costs, road user costs, and indirect regional economic losses costs. Also, the optimum safety indices are presented based on the expected total cost minimization function using only three parameters of the failure cost to the initial cost (${\tau}$), the extent of increased initial cost by improvement of safety (${\nu}$) and the order of an initial cost function (n). Through the enough numerical invetigations, we can positively conclude that the proposed optimum design procedure for bridge structures based on the ETLCC will lead to more rational, economical and safer design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3690-3713
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• 2019

According to the main group key management schemes logical key hierarchy (LKH), exclusion basis systems (EBS) and other group key schemes are limited in network structure, collusion attack, high energy consumption, and the single point of failure, this paper presents a group key management scheme for wireless sensor networks based on Lagrange interpolation polynomial characteristic (AGKMS). That Chinese remainder theorem is turned into a Lagrange interpolation polynomial based on the function property of Chinese remainder theorem firstly. And then the base station (BS) generates a Lagrange interpolation polynomial function f(x) and turns it to be a mix-function f(x)' based on the key information m(i) of node i. In the end, node i can obtain the group key K by receiving the message f(m(i))' from the cluster head node j. The analysis results of safety performance show that AGKMS has good network security, key independence, anti-capture, low storage cost, low computation cost, and good scalability.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.125-134
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• 2022

Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.307-319
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• 2021

Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.1-21
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• 2017

Business Intelligence (BI) system is a strategic tool that presents an analytical perspective about business and external environments. Even though its strategic value was well known, users often avoid using it or adopt it ceremonially. In fact, over 50 per cent of BI projects worldwide are reported to end in failure. Such an unexpectedly lower success rate has been a key issue in BI studies. In order to enhance a proper use of information systems, MIS field provided a number of theoretical constructs. One example is Goodhue & Thompson's Task-Technology Fit (TTF). In addition, internalization, the degree to which people make their own effort to modify behavior, was recently suggested as another important determinant of use. Though in MIS community both TTF and internalization proved to be a key determinant of system use, there has been not much study aiming to discover antecedents influencing these constructs. In this study we assert that user participation should be highlighted in BI projects. Especially, we emphasize user participation at the phase of feasibility study that is mainly conducted to determine whether a BI system is essentially necessary and practicable. Our research model employs participative feasibility study as a major antecedent for TTF and internalization that consequently will lead to user satisfaction and actual use. This model was empirically tested on 121 BI system users. The result shows that user participation in feasibility study is positively associated with TTF and internalization, each being related to user satisfaction and system use. It implies that, if an organization has BI users get involved in strategic feasibility study phase, the BI system would turn out to fit users' tasks and, furthermore, users would put more efforts spontaneously in order to use it properly.

• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.23-30
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• 2004

Modern production systems are very complex by request of automation, and failure modes that occur in thisautomatic system are very various and complex. The efficient fault diagnosis for these complex systems is essential for productivity loss prevention and cost saving. Traditional fault diagnostic system which perforns sequential fault diagnosis can cause catastrophic failure during diagnosis when fault propagation is very fast. This paper describes the Real-time Intelligent Multiple Fault Diagnosis System (RIMFDS). RIMFDS assesses current machine condition by using sensor signals. This system deals with multiple fault diagnosis, comprising of two main parts. One is a personal computer for remote signal generation and transmission and the other is a host system for multiple fault diagnosis. The signal generator generates various faulty signals and image information and sends them to the host. The host has various modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault modules and agents for efficient multiple fault diagnosis. A SUN workstation is used as a host for multiple fault diagnosis and graphic representation of the results. RIMFDS diagnoses multiple faults with fast fault propagation and complex physical phenomenon. The new system based on multiprocessing diagnoses by using Hierarchical Artificial Neural Network (HANN).

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.1-12
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• 2024

As the service robot market grows among the food technology industry, the quality of robot service that affects consumer behavioral intentions in the restaurant industry has become important. Serving robots, which are common in restaurants, reduce employee work through order and delivery, but because they do not respond to service failures, they increase customer dissatisfaction as well as increase employee work. In order to improve the quality of service beyond the simple function of receiving and serving orders, functions of recovery effort, fairness, empathy, responsiveness, and certainty of the process after service failure, such as serving employees, are also required. Accordingly, we assumed the type of failure of restaurant serving service as two internal and external factors, and developed a serving robot with a vocational ethics module to respond with a professional ethical attitude when the restaurant serving service fails. At this time, the expression and action of the serving robot were developed by adding a failure mode reflecting failure recovery efforts and empathy to the normal service mode. And by recruiting college students, we tested whether the service robot's response to two types of service failures had a significant effect on evaluating the robot. Participants responded that they were more uncomfortable with service failures caused by other customers' mistakes than robot mistakes, and that the serving robot's professional ethical empathy and response were appropriate. In addition, unlike the robot's favorability, the evaluation of the safety of the robot had a significant difference depending on whether or not a professional ethical empathy module was installed. A professional ethical empathy response module for natural service failure recovery using generative artificial intelligence should be developed and mounted, and the domestic serving robot industry and market are expected to grow more rapidly if the Korean serving robot certification system is introduced.