• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.649-654
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• 2007

Eavesdropping prevention performance is evaluated on a commercial window shaker, which is used to prevent a glass window from eavesdropping. Speech transmission index (STI) is introduced in order to estimate quantitatively the speech intelligibility of the sound detected on the glass window. Objective test by IEC standard using modulation transfer function (MTF) is performed to determine STI. Using Maximum Length Sequency (MLS) signal as a sound source, MTF is measured by accelerometers and laser doppler vibrometer. STI under different level of disturbing wave are compared to confirm the disturbing effect on the speech intelligibility.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.171-178
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• 2016

An aircraft in flight and ATC(: Air Traffic Controllers) working in the Ground Control Center carry out a voice communication using the radio. Voice signal to be transmitted from the aircraft is received to a plurality of terrestrial sites around the country at the same time. The ATC receives the various quality of voice signal from the aircraft depending on the distance, speed, weather conditions and adjusted condition of the antenna and the radio. The ATC carries out a voice communication with aircraft in the optimal conditions finding the best voice signal. However, the present system chooses the values of the CD(: Carrier Dectect) which is determined to be superior to, based on the input voice level, as optimal channel. Thus this system can not be seen to select the optimal channel because it doesn't consider the effect of the noise which influences on the communication quality. In this paper, after removing the noise in the voice signal, we could give the digitized information and an improved voice signal quality, so that users can select an optimal channel. By using it, when operating the training eavesdropping system or the aircraft control, we can expect prevention accident and improvement of training performance by selecting the improved quality channel.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.