• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.1
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• pp.95-103
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• 2000

In this paper, a novel indirect rotor position sensing method is proposed to improve the performClIlce of sensorless drive of brushless DC motors. The fast mode change to the sensorless operation is difficult in the existing indirect rotor position sensing methods because a precise rotor position can not be obtained when an excessive input is applied to the drive during synchronous operation mode. To cope with this problem, the relationship between terminal voltage and back-emf waveform is analyzed in this paper, also a novel indirect position sensing method which can detect a precise rotor position at low speed range is proposed. The effectiveness of the proposed method is verified through the experimental results.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.60-67
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• 2007

The spectrum sensing is important for decision of using frequency band. It checks the frequency band for cognitive radio system. In this paper, we apply autocorrelation function to the energy detection method. We use the autocorrelation function to improve the performance of spectrum sensing method based on the energy detection method. This method is different from cyclostationary process method where parameters such as the mean or the autocorrelation function are time-varying periodically. And we propose improved method that is robust in poor radio environment. If the proposed method applies for sensing in the cognitive radio system, it will have the structural simplicity and the fast computation of spectrum sensing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.10
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• pp.912-917
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• 2007

Many electrochemical power devices such as solid state batteries and solid oxide fuel cell have been studied and developed for solving energy and environmental problems. An amperometric gas sensor usually generates sensing signal of electric current along the proportion of the concentration of target gas under the condition of limiting current. For narrow variations of gas concentration, the amperometric gas sensor can show higher precision than a potentiometric gas sensor does. In additional, cross sensitivities to interfering gases can possibly be mitigated by choosing applied voltage and electrode materials properly. In order to improve the sensitivity to $NO_2$, the device was attached with Au reference electrode to form the amperometric gas sensor device with three electrodes. With the fixed bias voltage being applied between the sensing and counter electrodes, the current between the sensing and reference electrodes was measured as a sensing signal. The response to $NO_2$ gas was obviously enhanced and suppressed with a positive bias, respectively, while the reverse current occurred with a negative bias. The way to enhance the sensitivity of $NO_2$ gas sensor was thus realized. It was shown that the response to $NO_2$ gas could be enhanced sensitivity by changing the bias voltage.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.394-405
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• 2015

This paper considers a wideband cognitive radio network which can simultaneously sense multiple narrowband channels and thus aggregate the detected available channels for transmission and proposes a novel cognitive radio system that exhibits improved sensing throughput and can save power consumption of secondary user (SU) compared to the conventional cognitive radio system studied so far. More specifically, under the proposed cognitive radio system, we study the problem of designing the optimal sensing time and power allocation strategy, in order to maximize the ergodic throughput of the proposed cognitive radio system under two different schemes, namely the wideband sensing-based spectrum sharing scheme and the wideband opportunistic spectrum access scheme. In our analysis, besides the average interference power constraint at primary user, the average transmit power constraint of SU is also considered for the two schemes and then a subgradient algorithm is developed to obtain the optimal sensing time and the corresponding power allocation strategy. Finally, numerical simulations are presented to verify the performance of the two proposed schemes.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.517-524
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• 2015

The fast and accurate spectrum sensing over an ultra-wide bandwidth is a big challenge for the radio environment cognition. Considering sparse signal feature, two novel compressed sensing schemes are proposed, which can reduce compressed sampling rate in contrast to the traditional scheme. One algorithm is dynamically adjusting compression ratio based on modulation recognition and identification of symbol rate, which can reduce compression ratio. Furthermore, without priori information of the modulation and symbol rate, another improved algorithm is proposed with the application potential in practice, which does not need to reconstruct the signals. The improved algorithm is divided into two stages, which are the approaching stage and the monitoring stage. The overall sampling rate can be dramatically reduced without the performance deterioration of the spectrum detection compared to the conventional static compressed sampling rate algorithm. Numerous results show that the proposed compressed sensing technique can reduce sampling rate by 35%, with an acceptable detection probability over 0.9.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.376-383
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• 2011

Since the first arrival path may not be the strongest path of UWB(Ultra Wide Band) multipath channels, this makes ToA(Time-of-Arrival) estimation becomes a challengeable issue. Furthermore, because of ultra bandwidth of received signals, the compressed sensing theory is employed to reduce the complexity caused by very high Nyquist sampling rate in coherent UWB receivers. In this paper, we propose a ToA estimation scheme which provides precise estimation performance, while exploiting the benefits of compressed sensing-based UWB receivers. Simulation results show that the proposed scheme can outperform other low complexity schemes in a wide range of signal-to-noise ratios.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.160-165
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• 2004

MPA (Multi-Point Averaging) flow element is a new type of differential pressure (DP) flow-sensing device that was developed by Seojin Instech to improve the operating characteristics of the conventional Averaging Pilot Tube (APT) flow elements. Operating characteristics of a flowmeter in general can be defined in terms of measurement accuracy and range. Improvement of accuracy and expanding the range of flow measurement were the two main objectives of the development. To achieve these dual objectives several upstream and downstream pressure-sensing holes were placed in MPA flow element. During the course of the development it was found that certain arrangements of the pressure-sensing holes improved measurement accuracy but did not expand operating flow range of Averaging Pilot Tubes. Development tests were performed with water between Reynolds number of 50,000 and 1,000,000 in the four-inch test line at the Alden Research Laboratory, U.S.A. Purpose of this paper is to present the relationship between the various locations of the pressure-sensing holes and the performance characteristics of MPA flow element. Furthermore, the operating characteristics of the best performing MPA are compared with those of typical orifice and APT.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.1-17
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• 2014

Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce radio spectrum resources. However, most of CSS schemes assume all secondary users (SU) are honest, and thus offering opportunities for malicious SUs to launch the spectrum sensing data falsification attack (SSDF attack). To combat such misbehaved behaviors, recent efforts have been made to trust schemes. In this paper, we argue that powering CSS with traditional trust schemes is not enough. The rational SSDF attack is found in this paper. Unlike the simple SSDF attack, rational SSDF attackers send out false sensing data on a small number of interested primary users (PUs) rather than all PUs. In this case, rational SSDF attackers can keep up high trustworthiness, resulting in difficultly detecting malicious SUs in the traditional trust schemes. Meanwhile, a defense scheme using a novel trust approach is proposed to counter rational SSDF attack. Simulation results show that this scheme can successfully reduce the power of rational SSDF, and thus ensure the performance of CSS.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.