Journal of the Institute of Electronics Engineers of Korea SC
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v.49
no.3
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pp.82-89
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2012
This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.
The Journal of the Institute of Internet, Broadcasting and Communication
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v.17
no.3
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pp.29-45
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2017
Ad hoc sensor network is characterized by decentralized structure and ad hoc deployment. Sensor networks have all basic features of ad hoc network except different degrees such as lower mobility and more stringent energy requirements. Existing protocols provide different tradeoffs among some desirable characteristics such as fault tolerance, distributed computation, robustness, scalability and reliability. wireless protocols suggested so far are very limited, generally focusing on communication to a single base station or on aggregating sensor data. The main reason having such restrictions is due to maximum lifetime to maintain network activities. The network lifetime is an important design metric in ad hoc networks. Since every node does a router role, it is not possible for other nodes to communicate with each other if some nodes do not work due to energy lack. In this paper, we suggest an experimental ad-hoc on-demand distance vector routing protocol to optimize the communication of energy of the network nodes.The load distribution avoids the choice of exhausted nodes at the route selection phase, thus balances the use of energy among nodes and maximizing the network lifetime. In transmission control phase, there is a balance between the choice of a high transmission power that lead to increase in the range of signal transmission thus reducing the number of hops and lower power levels that reduces the interference on the expense of network connectivity.
Purpose - A growing demand for sustainability reporting has placed pressure on firms with non-financial information that affects firm valuation, growth, and development. In particular, a number of researchers have investigated various topics in Corporate Social Responsibility (CSR), non-financial information. Prior studies suggest that CSR may affect corporate outcomes like corporate reporting, financial performance, and disclosures. However, the results from prior studies are not clear whether CSR affects corporate outcomes. This is partially due to the measurement issues with CSR. In this study, we examine whether CSR affects the quality of corporate reporting, one of the popular measures in corporate outcomes. We find an evidence that CSR positively affects the quality of corporate reporting. Research design, data, and methodology - In this study, we collected a unique dataset of CSR from MSCI. Total 169 firms listed in the Korean Stock Exchange from 2011 to 2014 were collected and analysed with the detailed CSR reports. Using a correlation test, we found a weak association between CSR and the quality of corporate reporting. However, the regression tests provided a strong relationship between CSR and the quality of corporate reporting after controlling for other variables that may affect the quality of corporate reporting. Additionally, we calculated the t-statistics based on heteroskedaticity-consistent standard errors (White, 1980). Results - Before we run the regression test, we sort the measures of the two dependent variables into each rating of CSR (from AAA to CCC). The results indicate that the quality of corporate reporting measured by discretionary accruals and performance-matched discretionary accruals monotonically decrease as the CSR ratings increase. This supports our hypothesis. In the regression tests, the coefficient on MJDA (PMDA) is -0.183 (-0.173) and significant at the 5% level. We can interpret the results as CSR affecting the quality of corporate reporting in positive ways. Other coefficients on control variables are consistent with prior studies. For example, the coefficients on both LOSS and LEV are positive and significant at conventional level, meaning that firms with financial difficulty may harm their quality of corporate reporting. Conclusion - We found an evidence that CSR is positively associated with the quality of corporate reporting. This study contributes to the literature in various ways. First, this study extends the line of CSR research by providing additional evidence in the setting of ethical behaviors by managements. This is consistent with the hypothesis and supports the results of prior studies. Second, to the best of my knowledge, this is the first study using the MSCI CSR ratings. In contrast with prior studies using different measures of CSR, the MSCI CSR ratings allow us to provide in-depth analysis. Third, the additional measure of dependent variable (PMDA) allows us to improve the robustness of our results. Overall, the results provided this study to extend the findings in prior studies by providing incremental evidence.
There have been worldwide research and development efforts to automate various processes of bio-production and those efforts will be expanded with priority given to tasks which require high intensive labor or produce high value-added product and tasks under hostile environment. In the field of bio-production capabilities of the versatility and robustness of automated system have been major bottlenecks along with economical efficiency. This paper introduces a new concept of automation based on tole-operation, which can provide solutions to overcome inherent difficulties in automating bio-production processes. Operator(farmer), computer, and automatic machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. Among processes of greenhouse watermelon cultivation tasks such as pruning, watering, pesticide application, and harvest with loading were chosen based on the required labor intensiveness and functional similarities to realize the proposed concept. The developed system was composed of 5 major hardware modules such as wireless remote monitoring and task control module, wireless remote image acquisition and data transmission module, gantry system equipped with 4 d.o.f. Cartesian type robotic manipulator, exchangeable modular type end-effectors, and guided watermelon loading and storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. The proposed system showed practical and feasible way of automation in the field of volatile bio-production process.
Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.
In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).
Jin, Moon Yong;Park, Jong Bin;Lee, Dong Suk;Park, Dong Sun
KIPS Transactions on Software and Data Engineering
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v.3
no.9
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pp.361-368
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2014
The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.
Kim, Sung-Un;Seo, Sang-Bo;Song, Seung-Mi;Jo, Chan-Hyo;Hwang, Jong-Gyu;Jo, Hyun-Jeong
Journal of the Korean Society for Railway
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v.11
no.4
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pp.349-356
/
2008
Put Safety-critical systems related to the railway communications are currently undergoing changes. Mechanical and electro-mechanical devices are being replaced by programmable electronics that are often controlled remotely via communication networks. Therefore designers and operators now not only have to contend with component failures and user errors, but also with the possibility that malicious entities are seeking to disrupt the services provided by theirs systems. Recognizing the safety-critical nature of the types of communications required in rail control operations, the communications infrastructure will be required to meet a number of safety requirements such as system faults, user errors and the robustness in the presence of malicious attackers who are willing to take determined action to interfere in the correct operation of a system. This paper discusses the safety strategies employed in the railway communications and proposes a security mechanism for Korean railway communication system. We present the developed communication safety evaluation tool based on the proposed security mechanism and also evaluate its protecting capability against the threats of masquerading, eavesdropping, and unauthorized message manipulation.
Kim Jung-Gi;Min Kyong-Pil;Chun Jun-Chul;Choi Yong-Gil
Journal of Internet Computing and Services
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v.7
no.2
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pp.23-35
/
2006
This work presents o novel method which extract facial region und features from motion picture automatically and controls the 3D facial expression in real time. To txtract facial region and facial feature points from each color frame of motion pictures a new nonparametric skin color model is proposed rather than using parametric skin color model. Conventionally used parametric skin color models, which presents facial distribution as gaussian-type, have lack of robustness for varying lighting conditions. Thus it needs additional work to extract exact facial region from face images. To resolve the limitation of current skin color model, we exploit the Hue-Tint chrominance components and represent the skin chrominance distribution as a linear function, which can reduce error for detecting facial region. Moreover, the minimal facial feature positions detected by the proposed skin model are adjusted by using edge information of the detected facial region along with the proportions of the face. To produce the realistic facial expression, we adopt Water's linear muscle model and apply the extended version of Water's muscles to variation of the facial features of the 3D face. The experiments show that the proposed approach efficiently detects facial feature points and naturally controls the facial expression of the 3D face model.
KIPS Transactions on Computer and Communication Systems
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v.3
no.10
/
pp.357-364
/
2014
The first mission for the IoT based hyper-connectivity communication is developing a device-to-device communication technique in infra-less low-power and lossy networks. In a low-power and lossy wireless network, IoT devices and routers cannot keep the original path toward the destination since they have the limited memory. Different from the previous light-weight routing protocols focusing on the reduction of the control messages, the proposed scheme provides the light-weight IPv6 address auto-configuration, IPv6 neighbor discovery and routing protocol in a IoT capable infra-less wireless networks with the bloom filer and enhanced rank concepts. And for the first time we evaluate our proposed scheme based on the modeling of various probability distributions in the IoT environments with the lossy wireless link. Specifically, the proposed enhanced RPL based light-weight routing protocol improves the robustness with the multi-paths locally established based on the enhanced rank concepts even though lossy wireless links are existed. We showed the improvements of the proposed scheme up to 40% than the RPL based protocol.
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