• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.239-247
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• 2008

In a resource-limited wireless communication environment, various approaches to meet the ever growing application requirements in an efficient and transparent manner, are being researched and developed. Amongst many approaches, cross layer technique is by far one of the significant contributions that has undoubtedly revolutionized the way conventional layered architecture is perceived. In this paper, we propose a Universal Cross Layer Framework based on vertical layer architecture. The primary contribution of this paper is the functional architecture of the vertical layer which is primarily responsible for cross layer interaction management and optimization. The second contribution is the use of optimization cycle that comprises awareness parameters collection, mapping, classification and the analysis phases. The third contribution of the paper is the decomposition of the parameters into local and global network perspective for opportunistic optimization. Finally, we have shown through simulations how parameters' variations can represent local and global views of the network and how we can set local and global thresholds to perform opportunistic optimization.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.3
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• pp.199-210
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• 2012

The recent researches on the automatic berthing control problems have used various kinds of tools as a control method such as expert system, fuzzy logic controllers and artificial neural network (ANN). Among them, ANN has proved to be one of the most effective and attractive options. In a marine context, the berthing maneuver is a complicated procedure in which both human experience and intensive control operations are involved. Nowadays, in most cases of berthing operation, auxiliary devices are used to make the schedule safer and faster but none of above researches has taken into account. In this study, ANN is applied to design the controllers for automatic ship berthing using assistant devices such as bow thruster and tug. Using back-propagation algorithm, we trained ANN with set of teaching data to get a minimal error between output values and desired values of four control outputs including rudder, propeller revolution, bow thruster and tug. Then, computer simulations of automatic berthing were carried out to verify the effectiveness of the system. The results of the simulations showed good performance for the proposed berthing control system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1512-1520
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• 2000

The wireless communication network is evolving toward IMT-2000 for providing various multimedia services. In order to accomplish this ultimate goal the effective schemes are required which can dynamically utilize the limited wireless resources based on different traffic characteristics of various services. This paper proposes a novel bandwidth allocation and call admission control scheme to transmit multimedia traffic based on the bandwidth reservation procedure using direction estimation in the IMT-2000 This scheme estimates the position of mobiles based on the mliticriteria decision making in which uncertain parameters such as RSS(Received Signal Strength), the distance between mobile and base station the moving direction and the previous location are participated in the decision process using aggregation function in fuzzy set theory. Its effectiveness is investigated by simulation.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.431-438
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• 2019

Fileless malware uses memory injection attacks to hide traces of payloads to perform malicious works. During the memory injection attack, an attack named "process hollowing" is a method of creating paused benign process like system processes. And then injecting a malicious payload into the benign process allows malicious behavior by pretending to be a normal process. In this paper, we propose a method to detect the memory injection regardless of whether or not the malicious action is actually performed when a process hollowing attack occurs. The replication process having same execution condition as the process of suspending the memory injection is executed, the data set belonging to each process virtual memory area is compared using the fuzzy hash, and the similarity is calculated.

• Journal of Distribution Science
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• v.19 no.7
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• pp.61-73
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• 2021

Purpose: This study offers suggestions to e-commerce companies for increasing shoppers' repurchase intention by considering the effect of distribution information in online shopping. It applies complexity theory to incorporate habitual information search behavior and shopper characteristics into the Stimulus-Organism-Response model and indicates how these complex factors work together in online shopping. Research design, data, and methodology: This study used an interview survey of 158 Vietnamese consumers with an experience of online shopping. A fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to examine the relationship between antecedents and outcomes depending on complex conditions in the given contexts. Results: The results (1) indicate the importance of observing information search patterns and investigating their influence on online distribution, and (2) clarify what kind of configurations, under what conditions, predict a high or low outcome; this provides evidence and hints for the development of frameworks for future studies. Conclusions: The findings suggest that shoppers' unconscious, habitual behavior can work with conscious attitude factors, such as satisfaction, to increase their repurchase intention. Hence, e-commerce companies should consider how to present useful distribution information and create functions that allow shoppers to engage with a variety of information while increasing their repurchase intention on the site.

• Asia-Pacific Journal of Business
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• v.11 no.1
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• pp.93-114
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• 2020

Purpose -The purpose of this study is to analyze how the accreditation system affect the selection of business strategies in social enterprises, which create social value rather than maximize profits. Design/methodology/approach - This study collected survey data from 40 accredited and 53 non-accredited social enterprises. This research employs a Fuzzy-set/qualitative comparative analysis to compare the combinations of factors that affect a social enterprise's performance Findings - The results show that for accredited enterprises organizational capabilities are significantly more important than networking capabilities, whereas for non-accredited enterprises internal communication, governance capacities and networking competencies are most important capabilities to improving their social performance. And also The accreditation systems for social enterprises would entice social enterprise away from business strategies based on with local society, which is differentiated with commonly accepted social enterprise model. Research implications or Originality - This research suggests that the accreditation system for social enterprises should be redesigned for enticing social enterprises in Korea to be more localized to meet local needs in terms of positive changes of local society.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.201-220
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• 2022

Lateral vibrations of footbridges may induce synchronization between pedestrians and structure itself, resulting in amplification of such vibrations, a phenomenon identified by lock-in. However, investigations about accelerations and frequencies of the structural movement that are related to the occurrence of synchronization are still incipient. The aim of this paper is to investigate conditions that could lead to avoidance of synchronization among pedestrians themselves and footbridge, expressed in terms of peak acceleration. The focus is on the low acceleration range, employed in some guidelines as a criterion to avoid synchronization. An experimental campaign was carried out, employing a prototype footbridge that was set into oscillatory motion through a pneumatic exciter controlled by a fuzzy system, with controlled frequency and amplitude. Test subjects were then asked to cross the oscillating structure, and accelerations were simultaneously recorded at the structure and at the subject's waist. Pattern and phase differences between these signals were analysed. The results showed that test subjects tended to keep their walking patterns without synchronization induced by the vibration of the structure, for structural peak acceleration values up to 0.18 m/s², when frequencies of oscillation were around 0.8 to 0.9 Hz. On the other hand, for frequencies of oscillation below 0.7 Hz, structural peak accelerations up to 0.30 m/s² did not induce synchronization.

• Advances in nano research
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• v.14 no.2
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.