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In recent, ISM (Industrial Scientific Medical) band that is 2.4GHz band authorized free of charge is being widely used for smart phone, notebook computer, printer and portable multimedia devices. Accordingly, studies have been continuously conducted on the possibility of coexistence among nodes using ISM band. In particular, the interference of IEEE 802.11b based Wi-Fi device using overlapping channel during communication among IEEE 802.15.4 based wireless sensor nodes suitable for low-power, low-speed communication using ISM band causes serious network performance deterioration of wireless sensor networks. This paper examined a method of identifying channel status to avoid interference among wireless communication devices using IEEE 802.11b (Wi-Fi) and other ISM bands during communication among IEEE 802.15.4 based wireless sensor network nodes in ISM band. To identify channels occupied by Wi-Fi traffic, various studies are being conducted that use the RSSI (Received Signal Strength Indicator) value of interference signal obtained through ED (Energy Detection) feature that is one of IEEE 802.15.4 transmitter characteristics. This paper examines an algorithm that identifies the possibility of using more accurate channel by mixing utilization of interference signal and RSSI mean value of interference signal by wireless sensor network nodes. In addition, it verifies such algorithm by using OPNET Network verification simulator.
In this paper, a web-based 3D virtual reality (VR) pavillion of Korean Traditional Music was implemented. The VR pavillion is used for the virtual demonstration and experience of Korean Traditional Music, which provides the information as well as multimedia experience on eight instuments to users through internet. It provides eight web-pages and one an audio-visual classroom on the instruments.
Vehicle license plate recognition system is not generalized in Malaysia due to the loose character layout rule and the varying number of characters as well as the mixed capital English characters and italic English words. Because the italic English word is hard to segmentation, a separate method is required to recognize in Malaysian license plate. In this paper, we propose a mixed character level and word level English license plate recognition algorithm using deep learning neural networks. The difference of Gaussian method is used to segment character and word by generating a black and white image with emphasized character strokes and separated touching characters. The proposed deep learning neural networks are implemented on the LPR system at the gate of a building in Kuala-Lumpur for the collection of database and the evaluation of algorithm performance. The evaluation results show that the proposed Malaysian English LPR can be used in commercial market with 98.01% accuracy.
In case of reading passport using a smart phone in contrast with a dedicated passport reading system, MRZ(Machine Readable Zone) character recognition can be hard when the character strokes were broken, touched or blurred according to the lighting condition, and the position and size of MRZ character lines were varied due to the camera distance and angle. In this paper, the effective recognition algorithm of the passport MRZ information using a combined neural network recognizer of CNN(Convolutional Neural Network) and ANN( Artificial Neural Network), is proposed under the various sized and skewed passport images. The MRZ line detection using connected component analysis algorithm and the skew correction using perspective transform algorithm are also designed in order to achieve effective character segmentation results. Each of the MRZ field recognition results is verified by using five check digits for deciding whether retrying the recognition process of passport MRZ information or not. After we implement the proposed recognition algorithm of passport MRZ information, the excellent recognition performance of the passport MRZ information was obtained in the experimental results for PC off-line mode and smart phone on-line mode.
In this paper, we propose a strategy of charging by analyzing the difference of path coefficient according to whether consumers are free or not, rather than presenting strategies for charging. Mobile devices have become so popular that they are called necessities. Companies have to adapt to the mobile environment and respond to the situation, and have to expand market opportunities strategically. In this study, we extend the technology acceptance model to analyze the incentives of consumers' behavior by analyzing the difference in the effect consumers perceive as a moderating variable, whether paid or free. Efforts to maximize company's inherent profit continue, and in particular, charging is a strategy that all companies should pursue in the mobile environments. It is necessary to grasp the degree of the consumer's response to free and charge. The model of satisfaction with the continuous use and the word-of-mouth intention, which is the behavior intention, is presented by adding parameters of satisfaction to the technology acceptance model. In addition, we try to derive implications by analyzing the influence of moderating effects of whether free or not.
The inverse Rayleigh model distribution and Rayleigh distribution model were widelyused in the field of reliability station. In this paper applied using the finite failure NHPPmodels in order to growth model. In other words, a large change in the course of thesoftware is modified, and the occurrence of defects is almost inevitable reality. Finite failure NHPP software reliability models can have, in the literature, exhibit eitherconstant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Inthis paper, proposes the inverse Rayleigh and Rayleigh software reliability growth model,which made out efficiency application for software reliability. Algorithm to estimate theparameters used to maximum likelihood estimator and bisection method, model selectionbased on mean square error (MSE) and coefficient of determination(R²), for the sake ofefficient model, were employed. In order to insurance for the reliability of data, Laplacetrend test was employed. In many aspects, Rayleigh distribution model is more efficient than the reverse-Rayleighdistribution model was proved. From this paper, software developers have to consider thegrowth model by prior knowledge of the software to identify failure modes which can helped.
In this paper, it is studied anti-collision algorithm based on the transmission protocol for RFID baseband system of the ISO/IEC 18000-6 Type-C regulation and designed the baseband part of RFID reader system using FPGA. To compensate this weak point of the slot random aloha algorithm which must have a long time to be dumped before deciding an appropriate slot size according to the number of surrounding tag, we suggested how to apply Bit By Bit algorithm to be able to recognize the tag when the tag is clashing. The design of the baseband part in the RFID reader system is accomplish by use of the ISE9.1i and I made an experiment on it targeting Spartan2. Construction verification is measured each block through Logic Analyzer and I can verify it has no error. I also compared and analyzed the performance between proposed algorithm and past algorithm and verified the improvement of performance.
The emergence of social network services, is changing the foundation of human relationship formation and method of communication of individuals through sharing of free information. Social network service is a service to support or facilitate an on-line extension of off-line network among people by helping them to share personal profile. History of social network services very short. But users of the various layers is increasing rapidly and ripple effect social as a result is very large. The focus of existing research was mainly devoted to motivation of use and acceptance of social network services. Currently the use of SNS was maturing. Thus, in-depth research on the use pattern of SNS users is needed. The purpose of this study is that, for Facebook in social network services, to analyze the changes in the initial stage of use, medium-term, usage patterns at the current time. Results of the study by analyzing the characteristics of the change in the pattern of usage of user of Facebook, it can be used as basic materials for SNS researchers and service provider.
In recent years, smartphone is the most widely used ubiquitous functionality. People do not want to just call other people any more by using a cellular phone; they want to connect to the Internet and use various applications. Hence, cellular phones need to become smart. A smartphone has an operating system and many applications. Specifically the goals of this research are; (1) to suggest theory framework of acceptance about smartphone based on TAM, (2) to examine relationships between exogenous variables. The research model and hypotheses were developed based on the theories of technology acceptance model. Questionnaire was used to collect data. The analysis of this study is designed as individual level to examine the causal relationship among variables. The the reliability and validity of data was tested by explanatory factor analysis, Cronbach’s alpha coefficient, confirmatory factor analysis, and correlation analysis. Also, the structural equation model(SEM) analysis was performed to test the usefulness of the model. The analysis results revealed that social norms and individual innovation are major influential variables on the perceived usefulness of smartphone. Also, social norms are influential variables on the perceived enjoyment of smartphone.
In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errorsdetected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.