• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.277-283
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• 2022

Email phishing has become very prevalent especially now that most of our dealings have become technical. The victim receives a message that looks as if it was sent from a known party and the attack is carried out through a fake cookie that includes a phishing program or through links connected to fake websites, in both cases the goal is to install malicious software on the user's device or direct him to a fake website. Today it is difficult to deploy robust cybersecurity solutions without relying heavily on machine learning algorithms. This research seeks to detect phishing emails using high-accuracy machine learning techniques. using the WEKA tool with data preprocessing we create a proposed methodology to detect emails phishing. outperformed random forest algorithm on Naïve Bayes algorithms by accuracy of 99.03 %.

• Geomechanics and Engineering
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• v.38 no.3
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• pp.231-247
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• 2024

The use of lime stabilization and geosynthetic reinforcement is a common approach to improve the performance of fine-grained soils in geotechnical applications. However, the impact of this combination on the soil-geosynthetic interaction remains unclear. This study addresses this gap by evaluating the interface efficiency and soil-geosynthetic interaction parameters of lime-stabilized clay (2%, 4%, 6%, and 8% lime content) reinforced with geotextile or geogrid using direct shear tests at various curing times (1, 7, 14, and 28 days). Additionally, machine learning algorithms (Support Vector Machine and Artificial Neural Network) were employed to predict soil shear strength. Findings revealed that lime stabilization significantly increased soil shear strength and interaction parameters, particularly at the optimal lime content (4%). Notably, stabilization improved the performance of soil-geogrid interfaces but had an adverse effect on soil-geotextile interfaces. Furthermore, machine learning algorithms effectively predicted soil shear strength, with sensitivity analysis highlighting lime percentage and geosynthetic type as the most significant influencing factors.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.552-563
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• 2005

In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of the wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of a mobile robot via the gradient descent (GD) method. In addition, an approach that uses adaptive learning rates for training of the WFNN controller is driven via a Lyapunov stability analysis to guarantee fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control results of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.64-71
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• 1999

In this paper, two degree of freedom parallelogram link mechanism is used as DD(Direct-drive) robot mechanism. In parallelogram link mechanism, two motors being established in each base frame, the mass of motor itself is not loaded to anther motor; the number of links are increased, the mass of arm being lighter; with the estabilishment of link parameter, nonlinearity such as the centrifugal force disappears; at the same time anti-interference between motors can be realized. And to realize highy-accurate drive of parallelogram link DD robot manipulator, to improve the learning speed through the design of leaning control system using neural network, to raise adapting power to the varied work objects; the learning control algorithm is composed of neural network and feedback controller in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• The Mathematical Education
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• v.46 no.2 s.117
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• pp.173-192
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• 2007

We define mathematical learning as a process of overcoming framing difference of teachers and students, two main subjects in a mathematics class. We have reached this definition to the effect that we can grasp a mathematical classroom per so and understand students' mathematical learning in the context. We could clearly understand the process in which the framing differences are overcome by analyzing mutual negotiation of informants in specific cultural models, both in its form as well as in its meaning. We review both of the direct and indirect forms of negotiation while keeping track of 'evolution of subject' in terms of content of negotiation. More specifically, we discuss direct negotiation briefly and review indirect negotiation from three distinct themes of (1) argument structure, (2) revoicing, and (3) development patterns and narrative structure of proof. In addition, we describe the content of negotiation under the title of 'Evolution of Subject.' We found that major modes of mutual negotiation are inter-reference and appropriation while the product of continued negotiation is inter-resemblance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.8-16
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• 2013

Determining relative importance among many quality attributes under financial constraints is an important task. The weighted value of an attribute particularly in QFD, will influence on engineering characteristics and this will eventually influence the whole manufacturing process such as parts deployment, process planning, and production planning. Several scholars have suggested weighting formulas using CSC (Customer Satisfaction Coefficient) in the Kano model. However, previous research shows that the validity of the CSC approaches has not been proved systematically. The aim of the present study is to address drawbacks of CSC and to develop APC (Average Potential Coefficient), a new approach for weighting of quality attributes. For this, the current study investigated 33 quality attributes of e-learning and conducted a survey of 375 university students for the results of APC, the Kano model, and the direct importance of the quality attributes. The results show that the proposed APC is better than other approaches based on the correlation analysis with the results of direct importance. An analysis of e-leaning's quality perceptions using the Kano model and suggestions for improving e-learning's service quality are also included in this study.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2687-2698
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• 2020

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.4
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• pp.20-38
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• 2017

Purpose - this study analyzes the impact of restaurant startup education on transfer effects in learning and entrepreneurial intentions based on previous research. Also, problems and ways to provide effective business startup education for a restaurant founder will be proposed based on the result. Research design, data, methodolog - this study collected surveys by conducting direct investigation. From July 20th of 2016 to September 20th of 2016 (approximately 60 days), the survey was collected. Out of 540 surveys, 520 were collected. And excepting 9 surveys which were untrustworthily conducted, total 511 surveys were used for the analysis. Results - First, as a result of the impact of which factor of a restaurant founder's startup education has a positive impact on transfer effect in learning (the satisfaction of startup education and learning transfer), law education, entrepreneurship education and business district analysis education and practical education have turned out be positively related variables. Secondly, as a result of the impact of a restaurant founder's startup education satisfaction on transfer in learning, it has been identified that startup education has a positive impact. Lastly, by conducting an analysis to find out which factor from a restaurant founder's transfer effect in learning has an impact on entrepreneurial intention, all variables, including startup education satisfaction and transfer effect in learning, are positively influencing factors. Conclusions - as startup education satisfaction of a restaurant founder is increasing, there is a higher level of transfer effect in learning. Moreover, as transfer effect of startup business is getting higher, it has an impact on entrepreneurial intention.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.269-278
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• 2009

This study was conducted to provide standards for the development of contents and systems for digital textbooks by examining the learners' satisfaction from digital textbooks, which are now being distributed to schools, in terms of ubiquitous learning, and by verifying the moderation effect of learners' computer self efficacy and digital textbook usage. SPSS win 13.0 was used for technical statistics, Cronbach's $\alpha$ coefficient calculation and correlation analysis for empirical analysis, and the MMR (moderated multiple regression) analysis was conducted for the hypothesis test. The following principal results were obtained from the hypothesis tests. First, the ubiquitous learning features had direct effects on the learning satisfaction from the digital textbooks. Second, when the ubiquitous learning features had positive effects on the learning satisfaction from digital textbooks, both the computer self efficacy and digital textbook usage reacted with the ubiquitous learning feature and showed moderation effects. These results were statistically significant.