• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.61-70
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• 2020

The 4th Industrial Revolution is a revolutionary change through intelligence, big fusion and personalization, and the importance of sensor technology that is the basis of core technology is emerging. This study empirically analyzes the derivation of national strategy for R&D of sensor technology, and draws out the effect of technology internalization effort through strategic R&D activities on technical performance and further on national economy. The research and development results are calculated for each type of technology internalization, and the results of the research and development are verified to establish a structure that contributes to the national economic performance. As a national technology internalization strategy, considering its own R&D investment and joint research and development, we examine the impact of each factor on patents and GDP, focusing on causality and ripple effects. For causality analysis, Grandeur causality analysis shows that R&D investment and joint research and development in all countries have mutual causal relationship with GDP. The implications are as follows. First, it is necessary to establish the policy of national economic development through the internalization of technology and knowledge. Second, it is necessary to establish policies according to the type of knowledge internalization. Third, it will be necessary to create an ecosystem environment based on a virtuous relationship between knowledge internalization and national technology and economic development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.909-937
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• 2011

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.355-360
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• 1998

A small package of plasma instruments, Space Physics Sensor, will monitor the space environment and its effects on microelectronics in the low altitude region as it operates on board the KOMPSAT-1 from 1999 over the maximum of the solar cycle 23. The Space Physics Sensor (SPS) consists of two parts: the Ionospheric Measurement Sensor (IMS) and the High Energy Particle Detector (HEPD). IMS will make in situ Measurements of the thermal electron density and temperature, and is expected to provide a global map of the thermal electron characteristics and the variability according to the solar and geomagnetic activity in the high altitude ionosphere of the KOMPSAT-t orbit. HEPD will measure the fluxes of high energy protons and electrons, monitor the single event upsets caused by these energetic charged particles, and give the information of the total radiation dose received by the spacecraft. The continuous operation of these sensors, along with the ground measurements such as incoherent scatter radars, digital ionosondes and other spacecraft measurements, will enhance our understanding of this important region of practical use for the low earth orbit satellites.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.23-27
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• 2007

Fruition for a diverse uIT(Ubiquitous Information Technology) service is currently required through the convergence of what is known as ubiquitous computing technology. In recent years, with the rapid growth of the need for information services, heavier demands have been made upon the supply of high-quality multimedia services that require a high bandwidth. Today, various home network solutions have been proposed to manage these service smoothly and a system able to deal with various types of network traffic without delays. In addition, in established home network environments that mix wired and wireless networks, along with the steady evolution of wireless network technology and the earnest development of ubiquitous computing technology, sensor-based wireless networks have emerged as a core solution for home networks. In this paper, a sensor network-based home control system supporting the next generation home gateway system for ubiquitous home environments is designed and implemented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.5-24
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• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.359-364
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• 2003

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1083-1097
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• 2018

This paper presents a novel range-free localization algorithm based on quantum particle swarm optimization. The proposed algorithm is capable of estimating the distance between two non-neighboring sensors for multi-hop heterogeneous wireless sensor networks where all nodes' communication ranges are different. Firstly, we construct a new cumulative distribution function of expected hop progress for sensor nodes with different transmission capability. Then, the distance between any two nodes can be computed accurately and effectively by deriving the mathematical expectation of cumulative distribution function. Finally, quantum particle swarm optimization algorithm is used to improve the positioning accuracy. Simulation results show that the proposed algorithm is superior in the localization accuracy and efficiency when used in random and uniform placement of nodes for heterogeneous wireless sensor networks.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.349-354
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• 2007

This paper presents characteristics of surface acoustic wave (SAW) gas sensor for detecting volatile gases such as ethanol gas by measuring the phase shift of output signal. A delay-line with a center frequency of 400 MHz was fabricated on $128^{\circ}$ Y-Z $LiNbO_{3}$ substrates. Experimental results, which showed the phase change of the output signal under the absorption of volatile gas on sensor surface, were presented. The sensitivities of SAW delay lines coated with polyurethane films were greatly increased compared to those for uncoated devices. This SAW gas sensor system may be well suited for a high sensitivity electronic nose system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.79-82
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• 2008

A method is described for ideally reconstructing the profile from a surface profiling measurement containing a reasonable amount of null measurement data. The proposed method can conjecture lost information and rectify irregular data that result due to bad measuring environments, signal transmission noise, or instrument-induced errors, The method adopts the concept of computer graphics and consists of several processing steps. First, a search for valid data in the neighborhood of the null data is performed. The valid data are then grouped and their contours are extracted. By analyzing these contours, a bounding box can be obtained and the general distribution of the entire area encompassing the valid and null data is determined Finally, an ideal surface model is overlaid onto the measurement results based on the bounding box, generating a complete reconstruction of the calculations, A surface-profiling task on a liquid crystal display photo spacer is used to verify the proposed method. The results are compared to those obtained through the use of a scanning electron microscope to demonstrate the accuracy of the proposed method.