• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.87-94
• /
• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

• Journal of Broadcast Engineering
• /
• v.13 no.6
• /
• pp.849-858
• /
• 2008

In this paper, a no-reference perceptual metric is proposed for image quality assessment. It measures the amount of overall blockiness and blurring of the image and evaluates the amount of ringing, staircase, and mosaic noises around the strong edges. Finally, the individual scores are combined by a fuzzy integral to generate the final quality score of the image. The quality scores obtained by the proposed algorithm show strong relationship with the MOS(Mean Opinion Score) values by experts.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.244-250
• /
• 2003

In this paper, the relationship between a slave robot and the uncertain remote environment is modeled as the impedance to generate the virtual force to feed back to the operator. For the control of a tele-operated mobile robot equipped with camera, the tele-operated mobile robot take pictures of remote environment and sends the visual information back to the operator over the Internet. Because of the limitation of communication bandwidth and narrow view-angles of camera, it is not possible to watch the environment clearly, especially shadow and curved areas. To overcome this problem, the virtual force is generated according to both the distance between the obstacle and robot and the approaching velocity of the obstacle. This virtual force is transferred back to the master over the Internet and the master(two degrees of freedom joystick), which can generate force, enables a human operator to estimate the position of obstacle in the remote environment. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. This force reflection improves the performance of a tele-operated mobile robot significantly.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.2
• /
• pp.101-106
• /
• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.3
• /
• pp.19-25
• /
• 2017

Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2401-2403
• /
• 2002

Given a certain target point, the mobile robot's navigation could be mainly considered about two areas, 'how fast and accurate' and 'how safe'. Such problems regarding the velocity and stability possess close relationship with the path in which the mobile robot navigates in. Thus, the system proposed in this research paper was constructed so the mobile robot can obtain the optimum path by utilizing the information according to the environmental map, based on the Global Path Planning. Also by inducing the Local Path Planning method, it was constructed so that the robots can avoid the obstacles, which were not shown in the environmental map on-line. Particularly, by fusing the Local and Global Path Planning together, it is possible for the robots to plan similar path. At the same time, the focus was on the materialization of effective mobile robot's navigation. It was made possible by utilizing the Fuzzy Logic Control. Also, the validity of the algorithm proposed was proven through the trial experiment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.4
• /
• pp.194-201
• /
• 2012

Because the difference between products and services are getting less and less, service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs under today's competitive market environment. The value of services depends on service reliability that is identified by satisfaction derived from the relationship between customer needs and service providers. In this paper, we extend concepts from the fault tree analysis for reliability analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using service blueprint and FTA. We can identify the failure mode of service in a service delivery process with a service blueprint. The fuzzy membership function is used to characterize the probability of failure based on linguistic terms. FTA is employed to estimate the reliability of service delivery processes with risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.1
• /
• pp.33-39
• /
• 2017

Purpose - The main purpose of the current study is to examine the impact of accounting information quality and information asymmetry on the underinvestment phenomenon among the listed companies on the Tehran Stock Exchange (TSE). Research design, data, and methodology - The population includes 94 firms selected through systematic sampling. The data is collected from the audited financial statements of the firms provided by TSE's website from 2010 to 2015. Accounting information quality and information asymmetry is considered as independent variables, and their impact is examined on the dependent variable (underinvestment). Results - The statistical results, based on data collected from 94 listed companies on the TSE during 2010-2015, revealed positive impact of accounting information quality and positive impact of information asymmetry on underinvestment. There was a significant relationship between accrual quality (AQ) and underinvestment, and spread and underinvestment. The results also showed that information asymmetry is the main factor in the creation underinvestment. Conclusions - Findings of this article can assist accounting researchers and theoreticians in comparing Real world facts with hypotheses developed with respect to accounting information quality, information asymmetry and underinvestment. However, the results of fuzzy regression analysis indicate significant relationships between the independent variable except underinvestment.

• Journal of IKEEE
• /
• v.21 no.3
• /
• pp.309-319
• /
• 2017

The research investigates the inhibition of fatty acid biosynthesis of the human Acetyl-CoA Carboxylase enzyme by the aromatic-structure inhibitors (also known as ligands) containing variables of substituents, contributing an important role in the treatment of fatty-acid metabolic syndrome expressed by the group of cardiovascular risk factors increasing the incidence of coronary heart disease and type-2 diabetes. The effective interoperability between ligand and enzyme is characterized by a 50% concentration of enzyme inhibitor ($IC_{50}$) which was determined by experiment, and the factor of geometry structure of the ligands which are modeled by quantum mechanical methods using HyperChem 8.0.10 and Gaussian 09W softwares, combining with the calculation of quantum chemical and chemico-physical structural parameters using HyperChem 8.0.10 and Padel Descriptor 2.21 softwares. The result data are processed with the combination of classical statistical methods and modern bioinformatics methods using the statistical softwares of Department of Pharmaceutical Technology - Jadavpur University - India and R v3.3.1 software in order to accomplish a model of the quantitative structure - activity relationship between aromatic-structure ligands inhibiting fatty acid biosynthesis of the human Acetyl-CoA Carboxylase.

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