• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.96-105
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• 2019

Ocean reverberation is the most limiting factor in designing realistic and real-time system for sonar simulator. The simulation for an ocean reverberation requires a lot of computational loads, so it is hard to embed program and generate real-time signal in the sonar simulator. In this study, we simulate a time-domain bottom reverberation signal based on Harrison's energy-flux bottom reverberation model by applying Doppler effects as ship maneuvering and autoregressive model. Finally, the bottom reverberation signal with realistic characteristics could be generated for the simulation of ONR reverberation modeling workshop-I problem XI and East Sea ocean environments.

• Journal of Advanced Marine Engineering and Technology
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• v.11 no.4
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• pp.33-40
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• 1987

Arc power is consumed energy per unit time between welding electrodes. The relations between consumed energy and electrode distance, current, voltage are nonlinear characteristics. Therefore commercial A.C. wattmeter cannot be used for measurement of the arc power. Most of arc energy measuring systems are developed for relay contact arc measurement. Relaly arc requires integrated instantaneous power because relay arc finishes in a short instant. But most of welding powers are continually consumed powers, therefore instantaneous power must be continually indicated in the form of averagy value. The author propose a new measurement method of power in which the current and voltage of welding electrode is multiplied and the resultant signal is passed to low pass filter in order to remove higher order frequency components. After integrating, the signal is devided by the integral interval and the results are stored in a computer memory.

• ETRI Journal
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• v.29 no.1
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• pp.27-35
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• 2007

Energy savings in orthogonal frequency division multiplexing (OFDM) systems is an active research area. In order to achieve a solution, we propose a new cooperative relaying scheme operated on a per subcarrier basis. This scheme improves the bit error rate (BER) performance of the conventional signal-to-noise ratio (SNR)-based selection relaying scheme by substituting SNR with symbol error probability (SEP) to evaluate the received signal quality at the relay more reliably. Since the cooperative relaying provides spatial diversity gain for each subcarrier, thus statistically enhancing the reliability of subcarriers at the destination, the total number of lost subcarriers due to deep fading is reduced. In other words, cooperative relaying can alleviate error symbols in a codeword so that the error correction capability of forward error correction codes can be fully exploited to improve the BER performance (or save transmission energy at a target BER). Monte-Carlo simulations validate the proposed approach.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.12-23
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• 2004

In the present study a new measurement technique has been developed, which uses an ultrasonic transmission signal in order to identify the vertical two phase flow pattern. The ultrasonic measurement system developed in the present study not only provides the information required for the identification of vertical two phase flow patterns but also makes real time identification possible. Various vertical two phase flow patterns such as bubbly, slug, churn, annular flow etc. have been accurately identified with the present ultrasonic measurement system under atmospheric condition. In addition, the present test apparatus can practically simulate the ultrasonic propagation characteristics under high temperature and high pressure systems. Therefore, it is expected that the present ultrasonic flow pattern identification technique could be applicable to the vertical two phase flow systems under high temperature and high pressure conditions.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.374-379
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• 2018

The piezocomposite transducer is widely used because it is highly efficient in transforming electric energy into mechanical energy, and its frequency range is broader than that of other types of ultrasound transducers. A general piezocomposite transducer is composed of an acoustic lens, impedance matching layers, piezoelectric materials, and backing layers. When an input voltage is applied to a piezoelectric material as an active material, it generates sound waves while vibrating. At that time, an impedance matching layer helps the sound waves to propagate forward while reducing the impedance mismatch that may occur at the interface between the active material and its front material. The impedance mismatch has a negative effect on the signal of an ultrasound transducer; thus, it is important to design a matching layer to overcome the issue. In this study, an optimized feature of a matching layer with gradient properties is studied. An objective function is defined to minimize both the average and the deviation of the reflection coefficients that are functions of the frequencies. As a result, an improvement in the signal characteristics with respect to the sensitivity and bandwidth is reported.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1106-1112
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• 2017

As the Internet of Things (IOT) is evolving into an industry-wide service and expanded to the concept of Internet of Everything (IoE), services using IoT devices are easily accessible in everyday life. IoT requires more devices to collect information and is expected to increase the number of devices by 50 billion by 2020, and is about the number of devices currently available. Gradually, the number of mobile devices, smart devices, and Internet devices is increasing, and energy resources are required to operate such a large number of Internet devices, and the energy consumed by each device is small. In this paper, we consider the number of devices to be increased and generate a signal irrespective of transmission information so that power other than the energy required for signal transmission is consumed. When transmission information is generated and near to a receiver to receive information, The method to be used as an analysis is designed through experiments.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.119-122
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• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.169-174
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• 2013

Speech recognition, the problem of performance degradation is the difference between the model training and recognition environments. Silence features normalized using the method as a way to reduce the inconsistency of such an environment. Silence features normalized way of existing in the low signal-to-noise ratio. Increase the energy level of the silence interval for voice and non-voice classification accuracy due to the falling. There is a problem in the recognition performance is degraded. This paper proposed a robust speech detection method in noisy environments using a silence feature normalization and voice energy maximize. In the high signal-to-noise ratio for the proposed method was used to maximize the characteristics receive less characterized the effects of noise by the voice energy. Cepstral feature distribution of voice / non-voice characteristics in the low signal-to-noise ratio and improves the recognition performance. Result of the recognition experiment, recognition performance improved compared to the conventional method.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.184-197
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• 2015

This paper builds on a recent method, chain routing with even energy consumption (CREEC), for designing a wireless sensor network with chain topology and for scheduling the communication to ensure even average energy consumption in the network. In here a new suboptimal design is proposed and compared with the CREEC design. The chain topology in CREEC is reconfigured after each group of n converge-casts with the goal of making the energy consumption along the new paths between the nodes in the chain as even as possible. The new method described in this paper designs a single near-optimal Hamiltonian circuit, used to obtain multiple chains having only the terminal nodes different at different converge-casts. The advantage of the new scheme is that for the whole life of the network most of the communication takes place between same pairs of nodes, therefore keeping topology reconfigurations at a minimum. The optimal scheduling of the communication between the network and base station in order to maximize network lifetime, given the chosen minimum length circuit, becomes a simple linear programming problem which needs to be solved only once, at the initialization stage. The maximum lifetime obtained when using any combination of chains is shown to be upper bounded by the solution of a suitable linear programming problem. The upper bounds show that the proposed method provides near-optimal solutions for several wireless sensor network parameter sets.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.