• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.212-213
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• 2015

Data aggregation is a fundamental problem in wireless sensor networks that has attracted great attention in recent years. On constructing a robust algorithm for minimizing data aggregation delay in wireless sensor networks, we consider limited transmission range sensors and approximate the minimum-delay data aggregation tree which can only be built in networks of unlimited transmission range sensors. The paper proposes an adaptive method that can be applied to maintain the network structure in case of a sensor node fails. The data aggregation tree built by the proposed scheme is therefore self-healing and robust. Intensive simulations are carried out and the results show that the scheme could adapt well to network topology changes compared with other approaches.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.431-443
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• 2010

In this paper, we propose a range-free localization method that can improve the estimation accuracy of Approximate Point in Triangle(APIT), which is the representative localization method for low cost wireless sensor networks. Specifically, we propose extended-APIT(e-APIT) method, which minimizes the error in deciding whether an object is in an area formed by three beacons. We also propose a way to improve the localization by narrowing down the potential localization area using the signals from neighboring beacons. According to the simulation performed, the proposed e-APIT method demonstrated noticeable accuracy improvement over the conventional APIT method.

• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.69-75
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• 2018

In this study, we propose a multichannel interdigitated capacitor (IDC) sensor for detecting the bitterness of coffee. The operating principle of the device is based on the variation in capacitance of a sensing membrane in contact with a bitter solution. Four solvatochromic dyes, namely, Nile red, Reichardt's dye, auramine-O, and rhodamine-B, were mixed with polyvinylchloride (PVC) and N,N-dimethylacetamide (DMAC), to create four different types of bitter-sensitive solutions. These solutions were then individually inserted into four interdigitated electrodes (IDEs) using a spin coater, to prepare four distinct IDC sensors. The sensors are capable of detecting bitterness-inducing chemical compounds in any solution, at concentrations of approximately $1{\mu}M$ to 1 M. The sensitivity of the IDC bitterness sensor containing the Reichardt's dye sensing-membrane was approximately 1.58 nF/decade. The multichannel sensor has a response time of approximately 6 s, and an approximate recovery time of 5 s. The proposed sensor offers a stable sensing response and linear sensing performance over a wide measurement range, with a correlation coefficient ($R^2$) of approximately 0.972.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1738-1741
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• 1997

This paper addresses the issue fo target classification and localization with a SONAR for mobiler robot indoor navigation. In particular, multiple refetions of SONAR sound are used actively and interntionally. As for the SONAR sensor, the multiple reflection has been generally considered as one of the noisy phenomena, which is inevitable in the indoor environments. However, these multiple reflections can be a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. This paper develops a new SONAR sensor module with a reflection plane which can actively create the multiple refection. This paper also intends to suggest a new target classification emthod which uses the multiple refectiions. We approximate the world as being two dimensional and assume that the targets consisting of the indoor environment are pland, corner, and edge. Multiple reflection paths of an acoustic bean by a SONAR are analyzed, by simulations and the patterns of the TOPs (Time Of Flight) and angles of multiple reflections from each target are also analyzed. In addition, a new algorithm for target classification and localization is proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4804-4822
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• 2017

Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.465-472
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• 2017

Security has become one of the most important requirements for various devices for multi-sensor based embedded systems. The AES (Advanced Encryption Standard) algorithm is widely used for security, however, it requires high computing power. In order to reduce the CPU power for the data encryption of images, we propose a new image encryption module using hardware memoization, which can reuse previously generated data. However, as image pixel data are slightly different each other, the reuse rate of the simple memoization system is low. Therefore, we further apply an approximate concept to the memoization system to have a higher reuse rate by sacrificing quality. With the novel technique, the throughput can be highly improved by 23.98% with 14.88% energy savings with image quality loss minimization.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.84-92
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• 2000

Recently, the progress of industrialization has been taken concern of material handling automation. So for, the conveyor belt has been popular for material handling. However, this system has many disadvantages such as the space, cost, etc. In this paper, a new navigation algorithm using fuzzy is introduced. The mobile robot follows a line installed on the roads. These informations are inputted with three approximate sensors. These obtained informations are analyzed with fuzzy control technique fur autonomous steering. Therefore, unlike existing systems, high reliability is guaranteed under bad environment conditions. The installation and maintenance of a line is easily made at lower cost. This developed mobile robot can be applied to material handling automation in manufacturing system, hospital, inter-office document del ivory.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.98-107
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• 2009

In this paper, we propose a novel centralized energy-efficient clustering algorithm, called "MCCA : Max k-Cut based Clustering Algorithm for Wireless Sensor Networks." The algorithm does not use location information and constructs clusters via a distributive Max k-Cut based cluster-head election method, where only relative and approximate distance information with neighbor nodes is used and nodes, not having enough energy, are excluded for cluster-heads for a specific period. We show that the energy efficiency performance of MCCA is better than that of LEACH, EECS and similar to BCDCP's by simulation studies.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.3
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• pp.141-146
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• 2016

The AMR(automatic meter reading) system has been increasingly and widely used for its efficient and intelligent management, which is a technology that automatically collects consumption data from a water meter or energy metering device. The digital meter instead of the mechanical meter should be used in the system. Up to now, various types of sensor to measure the water flow rate have been used in the digital water meter, for example, reed switch, photo IR approximate sensor, ultrasonic sensor, electromagnetic sensor, etc. In this paper, a new sensing technology, where a variable capacitor and digital circuit were used for sensing the water flow rate, was proposed. The circuit was designed and verified by Pspice simulation. And a PCB board for the circuit was fabricated. After then, a prototype of digital water meter using a variable capacitor to measure the water flow rate was fabricated. The function tests of the fabricated digital water meter were performed, and it was found that the meter worked properly. Since the new technology has much better properties in terms of cost and power consumption compared to conventional technologies, it should be one of the major digital water meter technologies in the future.