• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.901-908
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• 2012

In an intelligent automated manufacturing environment, an administrator may use M2M (Machine-to-Machine) communication to recognize machine movement and the environment, as well as to respond to any potential dangers. However, commonly used wireless protocols for this purpose such WLAN (Wireless Local Area Network), ZigBee, and Bluetooth use the same ISM (Industrial Science Medical) band, and this may cause frequency interference among different devices. Moreover, an administrator is frequently exposed to dangerous conditions as a result of being surrounded by densely distributed moving machines. To address this issue, we propose in this paper to employ a location-based frequency interference management using fingerprinting scheme in industrial environments and its advanced localization schemes based on k-NN (Nearest Neighbor) algorithms. Simulation results indicate that the proposed schemes reduce distance error, frequency interference, and any potential danger may be responded immediately by continuous tracing of the locations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.936-942
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• 2022

While indoor vehicle navigation is an essential component in large-scale parking garages of major cities, technical limitations and challenging propagation environments considerably degrade the accuracy of existing localization techniques. This paper proposes a proximity detection scheme using low-cost beacons where a handheld mobile device within a moving vehicle autonomously detects its approximate position and moving direction by only observing Received Signal Strength (RSS) values of beacon signals. The proposed approach essentially exploits the differential RSS technique of multi-directional beams to reduce the impact of the environment, vehicle, and mobile device. A low-cost multi-directional beacon prototype is developed using Bluetooth technology. The localization performance is evaluated using 96 beacons in an underground parking garage within an area of 394.8m×304.3m. Experimental results show that the 90th percentile of the average proximity detection error is 0.8m. Furthermore, our proposed scheme provides robust proximity detection performance with various vehicles and mobile devices.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.8
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• pp.750-757
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• 2011

Wireless Sensor Network is composed of a lot of sensor nodes that are densely deployed in a field. So generally this sensor nodes are spreaded using Helicopter or Fixed wing. Each node delivers own location and acquired information to user when it detects specific events. In this paper, we propose localization algorithm without range information in wireless sensor network using helicopter. Helicopter broadcasts periodically beacon signal for sensor nodes. Sensor nodes stored own memory this beacon signal until to find another beacon point(satisfied special condition). This paper develops a localization mechanism using the geometry conjecture(perpendicular bisector of a chord) to know own location. And the simulation results demonstrate that our localization scheme outperforms Centroid, APIT in terms of a higher location accuracy.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.228-233
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• 2010

In this paper, the iteration localization algorithm that NLOS signal is iteratively removed to get the exact location in the wireless sensor network is proposed. To evaluate the performance of the proposed algorithm, TDOA location estimation method is used, and readers are located on every 150m intervals with rectangular shape in $300m{\times}300m$ searching field. In that searching field, the error distance is analyzed according to increasing the number of iteration, sub-blink and the estimated sensor node locations which are located in the iteration range. From simulation results, the error distance is diminished according to increasing the number of the sub-blink and iteration with the proposed location estimation algorithm in NLOS environment. Therefore, to get more accurate location information in wireless sensor network in NLOS environments, the proposed location estimation algorithm removing NLOS signal effects through iteration scheme is suitable.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.280-285
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• 2011

Recently, with the development of service robots and the concept of ubiquitous, the position estimation of mobile objects has received great interest. Some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter. The RFID receiver gets the synchronization signal from the mobile robot and the ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can acquire the ultrasonic signals from only one or two beacons, due to the obstacles located along the moving path. In this paper, a position estimation scheme using fewer than three sensors is developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.510-522
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• 2018

As the major source of information, digital images play an indispensable role in our lives. However, with the development of image processing techniques, people can optionally retouch or even forge an image by using image processing software. Therefore, the authenticity and integrity of digital images are facing severe challenge. To resolve this issue, the fragile watermarking schemes for image authentication have been proposed. According to different purposes, the fragile watermarking can be divided into two categories: fragile watermarking for tamper localization and fragile watermarking with recovery ability. The fragile watermarking for image tamper localization can only identify and locate the tampered regions, but it cannot further restore the modified regions. In some cases, image recovery for tampered regions is very essential. Generally, the fragile watermarking for image authentication and recovery includes three procedures: watermark generation and embedding, tamper localization, and image self-recovery. In this article, we make a review on self-embedding fragile watermarking methods. The basic model and the evaluation indexes of this watermarking scheme are presented in this paper. Some related works proposed in recent years and their advantages and disadvantages are described in detail to help the future research in this field. Based on the analysis, we give the future research prospects and suggestions in the end.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.23-34
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• 2005

Increased usage of AUVs has led to the development of alternative navigational methods that use the acoustic beacons and dead reckoning. This paper describes a concurrent mapping and localization (CML) scheme that uses range sonars mounted on SNUUV­I, which is a small test AUV developed by Seoul National University. The CML is one of such alternative navigation methods for measuring the environment that the vehicle is passing through. In addition, it is intended to provide relative position of AUV by processing the data from sonar measurements. A technique for CML algorithm which uses several ranging sonars is presented. This technique utilizes an extended Kalman filter to estimate the location of the AUV. In order for the algorithm to work efficiently, the nearest neighbor standard filter is introduced as the algorithm of data association in the CML for associating the stored targets the sonar returns at each time step. The proposed CML algorithm is tested by simulations under various conditions. Experiments in a towing tank for one dimensional navigation are conducted and the results are presented. The results of the simulation and experiment show that the proposed CML algorithm is capable of estimating the position of the vehicle and the object and demonstrates that the algorithm will perform well in the real environment.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.309-317
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• 2022

In this paper, we propose a machine learning-based copy-move forgery detection network with dual branches. Because the rotation or scaling operation is frequently involved in copy-move forger, the conventional convolutional neural network is not effectively applied in detecting copy-move tampering. Therefore, we divide the input into rotation-invariant and scaling-invariant features based on the wavelet coefficients. Each of the features is input to different branches having the same structure, and is fused in the combination module. Each branch comprises feature extraction, correlation, and mask decoder modules. In the proposed network, VGG16 is used for the feature extraction module. To check similarity of features generated by the feature extraction module, the conventional correlation module used. Finally, the mask decoder model is applied to develop a pixel-level localization map. We perform experiments on test dataset and compare the proposed method with state-of-the-art tampering localization methods. The results demonstrate that the proposed scheme outperforms the existing approaches.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.8-14
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• 2008

In this paper, I have presented a new approach which can track moving objects in unknown environments. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. I have proved that given an artificial measurement and track's configuration, proposed scheme converges to a proper plot in a finite number of iterations. In this light, even if the performance is enhanced by using the relaxation, I also note that the difficulty in tuning the parameters of the relaxation scheme is critical aspect of this suggestion.