• Smart Structures and Systems
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• v.6 no.5_6
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• pp.561-578
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• 2010

This study proposes a multi-level damage localization strategy to achieve an effective damage detection system for civil infrastructure systems based on wireless sensors. The proposed system is designed for use of distributed computation in a wireless sensor network (WSN). Modal identification is achieved using the frequency-domain decomposition (FDD) method and the peak-picking technique. The ASH (angle-between-string-and-horizon) and AS (axial strain) flexibility-based methods are employed for identifying and localizing damage. Fundamentally, the multi-level damage localization strategy does not activate all of the sensor nodes in the network at once. Instead, relatively few sensors are used to perform coarse-grained damage localization; if damage is detected, only those sensors in the potentially damaged regions are incrementally added to the network to perform finer-grained damage localization. In this way, many nodes are able to remain asleep for part or all of the multi-level interrogations, and thus the total energy cost is reduced considerably. In addition, a novel distributed computing strategy is also proposed to reduce the energy consumed in a sensor node, which distributes modal identification and damage detection tasks across a WSN and only allows small amount of useful intermediate results to be transmitted wirelessly. Computations are first performed on each leaf node independently, and the aggregated information is transmitted to one cluster head in each cluster. A second stage of computations are performed on each cluster head, and the identified operational deflection shapes and natural frequencies are transmitted to the base station of the WSN. The damage indicators are extracted at the base station. The proposed strategy yields a WSN-based SHM system which can effectively and automatically identify and localize damage, and is efficient in energy usage. The proposed strategy is validated using two illustrative numerical simulations and experimental validation is performed using a cantilevered beam.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4044-4062
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• 2016

We investigate the optimization of energy consumption in Mobile Cloud environment in this paper. In order to optimize the energy consumed by the CPUs in mobile devices, we put forward using the asymptotic time complexity (ATC) method to distinguish the computational complexities of the applications when they are executed in mobile devices. We propose a multi-scale scheme to quantize the channel gain and provide an improved dynamic transmission scheduling algorithm when offloading the applications to the cloud center, which has been proved to be helpful for reducing the mobile devices energy consumption. We give the energy estimation methods in both mobile execution model and cloud execution model. The numerical results suggest that energy consumed by the mobile devices can be remarkably saved with our proposed multi-scale scheme. Moreover, the results can be used as a guideline for the mobile devices to choose whether executing the application locally or offloading it to the cloud center.

• Smart Structures and Systems
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• v.14 no.1
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• pp.55-70
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• 2014

The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2959-2973
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• 2021

In wireless sensor and actuator networks (WSANs), the network lifetime is an important criterion to measure the performance of the WSAN system. Generally, the network lifetime is mainly affected by the energy of sensors. However, the energy of sensors is limited, and the batteries of sensors cannot be replaced and charged. So, it is crucial to make energy consumption efficient. WSAN introduces multiple actuators that can be regarded as multiple collectors to gather data from their respective surrounding sensors. But how to deploy actuators to reduce the energy consumption of sensors and increase the manageability of the network is an important challenge. This research optimizes actuators deployment by a proposed probabilistic mutation multi-layer particle swarm optimization algorithm to maximize the coverage of actuators to sensors and reduce the energy consumption of sensors. Simulation results show that this method is effective for improving the coverage rate and reducing the energy consumption.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.910-917
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• 2016

Sensors have limited resources in sensor networks, so efficient use of energy is important. Representative clustering methods, LEACH, LEACHC, TEEN generally use direct transmission methods from cluster headers to the sink node to pass collected data. However, the communication distance of the sensor nodes at low cost and at low power is not long, it requires a data transfer through the multi-hop to transmit data to the sink node. In the existing cluster-based sensor network studies, cluster process and route selection process are performed separately in order to configure the routing path to the sink node. In this paper, in order to use the energy of the sensor nodes that have limited resources efficiently, a cluster-based multi-hop routing protocol which merges the clustering process and routing process is proposed. And the proposed method complements the problem of uneven cluster creation that may occur in probabilistic cluster methods and increases the energy efficiency of whole sensor nodes.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.193-200
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• 2009

In this paper, the raid and fire preventable system using Zibee module with IEEE 802.15.4 wireless communication standard and multi-sensor was developed displaying raid and firing condition with wireless network. The raid preventable system is designed using a ultrasonhe waves sensor and infrared sensor. The fire preventable system is designed using a thermistor. The datas for raid and firing condition are communicated from enddevice to coordinator with wireless network and are displayed on PC monitor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1098-1104
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• 2010

Recently, a variety of research of multi-hop routing protocol have been done to balance the sensor node energy consumption of WSN(wireless sensor network) and to improve the node efficiency for extending the life of the entire network. Especially in multi-hop protocol, a variety of models have been concerned to improve energy efficiency and apply in the reality. In multi-hop protocol, we assumption that energy consumption can be adjusted based on the distance between the sensor nodes. However, according to the physical property of the actual WSN, it's hard to establish this assumption. In this dissertation, we propose low-power sub-cluster protocol to improve the energy efficiency based on the spread of distance. Compared with the previous protocols, this proposed protocol can be effectively used in the wireless sensing networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.855-862
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• 2009

The path key establishment phase in the wireless sensor network is vulnerable to Byzantine attack. Huang and Hedhi proposed a Byzantine resilient multi-key establishment scheme using a systematic RS code, which has shortcomings of exposing a part of message symbols and inefficient transmission. In this paper, we propose a new Byzantine resilient multi-path key establishment scheme in which direct message symbols are not exposed to an adversary and are more efficiently transmitted the RS-encoded symbols to the destination node. In the Proposed scheme, a non-systematic RS code is used to transmit a generated indirect secret key and each encoded symbol is relayed through available paths between two sensor nodes. If enough symbols are collected at the destination node, it is possible to reconstruct the secret message through RS decoding.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.289-295
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• 2012

Routing technique of wireless sensor network that is presented to improve effectiveness of consumption in energy at the previous study is existing in various ways, however for routing, its own location data and nodes' location data close to with 1-hop distance should be kept. And it uses multi-hop transmission method that transmits data to BS node via several nodes. This technique makes electronic consumption of sensor node and entire network's energy consumption so that it makes effective energy management problem. Therefore, this paper suggests location based 1-hop routing technique of BS node that satisfies distance $d{\pm}{\alpha}$ with source node using RSSI and radio wave range of sensor node.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.77-85
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• 2008

The objective of the study is to construct a sensor fusion system for tool-condition monitoring (TCM) that will lead to a more efficient and economical drill usage. Drill-wear monitoring has an important attribute in the automatic machining processes as it can help preventing the damage of tools and workpieces, and optimizing the drill usage. In this study, we present the architectures of a multi-layer feed-forward neural network with Levenberg-Marquardt training algorithm based on sensor fusion for the monitoring of drill-wear condition. The input features to the neural networks were extracted from AE, vibration and current signals using the wavelet packet transform (WPT) analysis. Training and testing were performed at a moderate range of cutting conditions in the dry drilling of steel plates. The results show good performance in drill- wear monitoring by the proposed method of sensor fusion and neural network analysis.