• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.180-190
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• 2011

Efficient energy consumption is a critical factor for deployment and operation of wireless sensor networks (WSNs). To achieve energy efficiency there have been several hierarchical routing protocols that organize sensors into clusters where one sensor is a cluster-head to forward messages received from its cluster-member sensors to the base station of the WSN. In this paper, we propose a self-organized clustering method for cluster-head selection and cluster based routing for a WSN. To select cluster-heads and organize clustermembers for each cluster, every sensor uses only local information and simple decision mechanisms which are aimed at configuring a self-organized system. By these self-organized interactions among sensors and selforganized selection of cluster-heads, the suggested method can form clusters for a WSN and decide routing paths energy efficiently. We compare our clustering method with a clustering method that is a well known routing protocol for the WSNs. In our computational experiments, we show that the energy consumptions and the lifetimes of our method are better than those of the compared method. The experiments also shows that the suggested method demonstrate properly some self-organized properties such as robustness and adaptability against uncertainty for WSN's.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.901-904
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• 2005

Testing of mixed-signal circuit has become a difficult task for test engineers and efficient test solution to these problems are needed. In this paper a new specification-based mixed-signal test method called TSS(Time Slot Specification) using high performance current sensors and a novel test point selection technique without heavy computational overhead are proposed. External output and power nodes are used for test points and accessed by the current sensors in the ATE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.608-614
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• 2009

In wireless sensor networks, there are hundreds to thousands of small battery powered devices which are called sensors. As sensors have a limited energy resources, there is a need to use it effectively. A clustering based routing protocol forms clusters by distributed algorithm. Member nodes send their data to their cluster heads then cluster heads integrate data and send to sink node. In this paper we propose an energy efficient cluster-head selection algorithm. We have used some factors(a previous cluster head experience, a existence of data to transmit and an information that neighbors have data or not) to select optimum cluster-head and eventually improve network lifetime. Our simulation results show its effectiveness in balancing energy consumption and prolonging the network lifetime compared with LEACH and HEED algorithms.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.408-417
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• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.5
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• pp.303-310
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• 2020

In this study, a method for selection of the location and number of monitoring sensors in a building structure using artificial neural networks is proposed. The acceleration-history values obtained from the installed accelerometers are defined as the input values, and the mass and stiffness values of each story in a building structure are defined as the output values. To select the installation location and number of accelerometers, several installation scenarios are assumed, artificial neural networks are obtained, and the prediction performance is compared. The installation location and number of sensors are selected based on the prediction accuracy obtained in this study. The proposed method is verified by applying it to 6- and 10-story structure examples.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.391-399
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• 2021

The conformal array sensor has different sub-array depending on different beam steering directions. According to the method to effective the sensor, the performance of the conformal array sensor can be different, where the sub-array selects an effective sensor. Also, due to the figure of the conformal array sensor, the figure of the sub-array can be different each other, which results in different performance on directivity index, beam width and etc. In this paper, two methods to select sub-array which is the criteria for each sensors position vector and directive vector were proposed. For two sub-array selection methods, the performance of the directivity index, horizontal and vertical beam width were compared with the average and variance. In addition, this comparison was conducted when the number of sensors was fixed. When the number of sensors was not fixed, the directional vector method mainly results in high performance, but the performance of vertical beam width was lower or equal. When the number of sensors was fixed, the performance of two methods is similar, but the performance of variance was deteriorated.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.229-236
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• 2009

Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.