• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.85-91
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• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

• Smart Media Journal
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• v.9 no.4
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• pp.60-65
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• 2020

The monopulse tracking algorithm can estimate the location of a partner station based on an RF (Radio Frequency) signal. The location of the partner station is estimated based on the monopulse ratio curve (MR-C), which is calculated based on the sum and difference signal patterns of an antenna. Therefore, the range in which the estimated location can be calculated with high accuracy increases in proportion to the linear region of MR-C. In this paper, we proposed a method to extend the linear region of the MR-C curve using the beamforming technique for the tracking antenna system using the active phased array antenna. Simulation results based on the same antenna system, it was confirmed that the linear region of MR-C was enlarged by about twice as much as the general case where the proposed method was not applied.

• Smart Media Journal
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• v.11 no.11
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• pp.92-98
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• 2022

Identifying defects in textiles is a key procedure for quality control. This study attempted to create a model that detects defects by analyzing the images of the fabrics. The models used in the study were deep learning-based VGGNet and ResNet, and the defect detection performance of the two models was compared and evaluated. The accuracy of the VGGNet and the ResNet model was 0.859 and 0.893, respectively, which showed the higher accuracy of the ResNet. In addition, the region of attention of the model was derived by using the Grad-CAM algorithm, an eXplainable Artificial Intelligence (XAI) technique, to find out the location of the region that the deep learning model recognized as a defect in the fabric image. As a result, it was confirmed that the region recognized by the deep learning model as a defect in the fabric was actually defective even with the naked eyes. The results of this study are expected to reduce the time and cost incurred in the fabric production process by utilizing deep learning-based artificial intelligence in the defect detection of the textile industry.

• Smart Media Journal
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• v.11 no.1
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• pp.46-57
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• 2022

In this paper, multi-region based Radial Graph Convolutional Network (MRGCN) algorithm which can perform end-to-end action recognition using the optical flow and gradient of input image is described. Because this method does not use information of skeleton that is difficult to acquire and complicated to estimate, it can be used in general CCTV environment in which only video camera is used. The novelty of MRGCN is that it expresses the optical flow and gradient of the input image as directional histograms and then converts it into six feature vectors to reduce the amount of computational load and uses a newly developed radial type network model to hierarchically propagate the deformation and shape change of the human body in spatio-temporal space. Another important feature is that the data input areas are arranged being overlapped each other, so that information is not spatially disconnected among input nodes. As a result of performing MRGCN's action recognition performance evaluation experiment for 30 actions, it was possible to obtain Top-1 accuracy of 84.78%, which is superior to the existing GCN-based action recognition method using skeleton data as an input.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.102-112
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• 2020

Smart City's goal is to solve urban problems through smart city's component technology, thereby developing eco-friendly and sustainable economies and improving citizens' quality of life. Until now, smart cities have evolved into component technologies, but it is time to focus attention on the needs and participation of citizens in smart cities. In this paper, we present a big data procedure for solving smart city problems based on citizens' needs and participation. To this end, we examine the smart city project market by region and major industry. We also examine the development stages of the smart city market area by sector. Additionally it understands the definition and necessity of each sector for citizen participation, and proposes a method to solve the problem through big data in the seven-step big data problem solving process. The seven-step big data process for solving problems is a method of deriving tasks after analyzing structured and unstructured data in each sector of smart cities and deriving policy programs accordingly. To attract citizen participation in these procedures, the empathy stage of the design thinking methodology is used in the unstructured data collection process. Also, as a method of identifying citizens' needs to solve urban problems in smart cities, the problem definition stage of the design sinking methodology was incorporated into the unstructured data analysis process.

• Spatial Information Research
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• v.19 no.5
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• pp.87-96
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• 2011

Recently mobile users can access to internet using smart phone at any place and any time, through which they can search and share information. In addition, as the sensors with high-tech functions become cheaper and miniaturized along with the development of MEMS (micro-electo mechanical systems) technology, the extent to utilize smart phone is increasing. Smart phone is equipped with various sensors such as high-resolution camera, GPS, gyroscope and magnetic sensor, which is an appropriate system configuration for remote monitoring research using camera. The remote monitoring system requires camera for video and internet network to send video, for which it has a limitation that it is influenced by the monitoring location. This study is aimed to design and develop the monitoring app. which can be remotely monitored using smart phone technology. The developed monitoring app was designed to take images of ROI (region of interest) within the specified time and to automatically send the images to the server. The developed app. is also possible to be remotely controlled by SMS (short message service). The monitoring proposed in this study can take high-resolution images using CMOS built in the smart phone and send the images and information to the server automatically at any place and any time using 3G and Wi-Fi networks.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.229-236
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• 2017

This paper presents an efficient object-based color image-retrieval algorithm that is suitable for the classification and retrieval of images from small to mid-scale datasets, such as images in PCs, tablets, phones, and cameras. The proposed method first finds salient regions by using regional feature vectors, and also finds several dominant colors in each region. Then, each salient region is partitioned into small sub-blocks, which are assigned 1 or 0 with respect to the number of pixels corresponding to a dominant color in the sub-block. This gives a binary map for the dominant color, and this process is repeated for the predefined number of dominant colors. Finally, we have several binary maps, each of which corresponds to a dominant color in a salient region. Hence, the binary maps represent the spatial distribution of the dominant colors in the salient region, and the union (OR operation) of the maps can describe the approximate shapes of salient objects. Also proposed in this paper is a matching method that uses these binary maps and which needs very few computations, because most operations are binary. Experiments on widely used color image databases show that the proposed method performs better than state-of-the-art and previous color-based methods.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.3
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• pp.148-159
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• 2013

An analysis of the throughput and stability region of random access systems is currently of interest in research and industry. This study evaluated the performance of a multiuser random access channel with a retransmission gain. The channel was composed of a media access control (MAC) determined by the transmission probabilities and a multiuser communication channel characterized by the packet reception probabilities as functions of the number of packet transmissions and the collision status. The analysis began with an illustrative two-user channel, and was extended to a general multiuser channel. For the two-user channel, a sufficient condition was derived, under which the maximum throughput was achieved with a control-free MAC. For the channel with retransmission gain, the maximum steady throughput was obtained in a closed form. The condition under which the random access channel can acquire retransmission gain was also obtained. The stability region of the general random access channel was derived. These results include those of the well-known orthogonal channel, collision channel and slotted Aloha channel with packet reception as a special instance. The analytical and numerical results showed that exploiting the retransmission gain can increase the throughput significantly and expand the stability region of the random access channel. The analytical results predicted the performance in the simulations quite well.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.93-98
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• 2011

In this paper, we propose the surveillance and combat robot framework for remote monitoring and robot control on the smart phone, which is implemented with the fusion technology called RITS(Robot technology & Information Technology System). In our implemented system, the camera phone mounted on the robot generates signals to control the robot and sends images to the smart phone of the operator. Therefore, we can monitor the surrounding area of the robot with the smart phone. Besides the control of the movement of the robot, we can fire the weapons armed on the robot by sending the fire command. From experimental results, we can conclude that it's possible to control the robot and monitor the surrounding area of the robot and fire the weapons in real time in the region where the 3G(Generation) mobile communication is possible. In addition, we controlled the robot using the 2G mobile communication or wired phone when the robot is in the visual range.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.52-70
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• 2008

Using MD Property View database on 15 counties in Maryland in the U.S., this study attempts to explore the estimation process on the housing development capacity under the Maryland's urban growth management policy known as the Smart Growth Initiatives. This study also seeks to draw the implications of the estimated development capacity by individual counties on successful implementation of the urban growth management policy. The finding shows that this region has land for residential use enough to accommodate growth for the next 30 years. However, contrary to the goal of the Smart Growth Initiatives, a majority of development capacity is located not only outside the Priority Funding Area designated by the Smart Growth Initiatives but also at counties that are located far away from the major metropolitan area. In addressing this problem, the state does not need to either abolish or immediately expand the Priority Funding Area. Rather, the state requires local governments to include housing elements in their comprehensive planning, to provide periodic estimates on housing and employment capacity, and to establish and manage database on the location and the capacity of developable land.