• Journal of Digital Convergence
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• v.13 no.7
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• pp.177-182
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• 2015

In a MPC(Multi-Pulse Coding) using excitation source of voiced and unvoiced, it would be a distortion of voice waveform. This is caused by normalization of synthesis speech waveform of voiced in the process of restoration. To solve this problem, this paper present APC-MPC of amplitude-position compensation in a multi-pulses each pitch interval in order to reduce distortion of synthesis waveform. Also, I was implemented that the APC-MPC in coding system. And I evaluate the SNRseg of APC-MPC in 8kbps coding condition of convergence system. As a result, SNRseg of APC-MPC was 13.9dB for female voice and 14.3dB for male voice respectively. And so, I expect to be able to this method for cellular phone and smart phone using excitation source of low bit rate.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.30 no.2
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• pp.141-147
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• 2024

The objective of this study was carried to compare the effects of different packaging and loading materials and types on the cold storage of onions. The research was conducted for over a period of six months. Onions were divided into three groups based on the packaging materials and types: mesh bag (control), ton bag (TB), and wire mesh pallet (WMP). Parameters such as moisture content (%), total soluble solids (ºBrix), Hunter-color value, rotting rate (%), and hardness (g/force) were measured and analyzed. The results of the experiment demonstrated that there was no significant differences in onions' quality between TB and WMP and the control, respectively. This study showed that TB and WMP can be used as an alternative to controls to extend the storage-life of onions and keeping quality during long-term cold storage. Furthermore, WMP packing and loading type could be replaced to conventional storage method with better efficiency in logistics of smart APC (agricultural product processing center).

• Smart Media Journal
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• v.12 no.5
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• pp.65-72
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• 2023

Smart Farm means creating new value in various fields related to agriculture, including not only agricultural production but also distribution and consumption through the convergence of agriculture and ICT. In Korea, a rental smart farm is created to spread smart agriculture, and a smart farm big data platform is established to promote data collection and utilization. It is pushing for digital transformation of agricultural products distribution from production areas to consumption areas, such as expanding smart APCs, operating online exchanges, and digitizing wholesale market transaction information. As such, although agricultural data is generated according to characteristics from various sources, it is only used as a service using statistics and standardized data. This is because there are limitations due to distributed data collection from agriculture to production, distribution, and consumption, and it is difficult to collect and process various types of data from various sources. Therefore, in this paper, we analyze the current state of domestic agricultural data collection and sharing for digital agriculture and propose a data collection and linkage method for artificial intelligence services. And, using the proposed data, we propose a deep learning-based environmental factor recommendation method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.1-7
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• 2018

This paper present an 8kbps ACLMS-MPC(Amplitude Compensation and Least Mean Square - Multi Pulse Coding) coding method integrated with ACFBD-MPC(Amplitude Compensation Frequency Band Division - Multi Pulse Coding) and LMS-MPC(Least Mean Square - Multi Pulse Coding) used V/UV/S(Voiced / Unvoiced / Silence) switching, compensation in a multi-pulses each pitch interval and Unvoiced approximate-synthesis by using specific frequency in order to reduce distortion of synthesis waveform. In integrating several methods, it is important to adjust the bit rate of voiced and unvoiced sound source to 8kbps while reducing the distortion of the speech waveform. In adjusting the bit rate of voiced and unvoiced sound source to 8 kbps, the speech waveform can be synthesized efficiently by restoring the individual pitch intervals using multi pulse in the representative interval. I was implemented that the ACLMS-MPC method and evaluate the SNR of APC-LMS in coding condition in 8kbps. As a result, SNR of ACLMS-MPC was 15.0dB for female voice and 14.3dB for male voice respectively. Therefore, I found that ACLMS-MPC was improved by 0.3dB~1.8dB for male voice and 0.3dB~1.6dB for female voice compared to existing MPC, ACFBD-MPC and LMS-MPC. These methods are expected to be applied to a method of speech coding using sound source in a low bit rate such as a cellular phone or internet phone. In the future, I will study the evaluation of the sound quality of 6.9kbps speech coding method that simultaneously compensation the amplitude and position of multi-pulse source.