• Clinical and Experimental Reproductive Medicine
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• v.49 no.4
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• pp.225-238
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• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.19-27
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• 2011

WiBro is a wireless mobile communication system which supports a high data rate and high mobility in anywhere and anytime. Although WiBro system provides multimedia service including data, audio and video services, customers require better service quality in WiBro system. But, many researches have theoretically evaluated the performance of WiBro system without systematic studies by simulation. Therefore, in this paper, we evaluate a performance of WiBro system using OPNET simulator. We analyze system performance according to various modulation and coding schemes, and propose Adaptive Modulation and Coding (AMC) profile to support quality of services for user requirements. Also we evaluate the performance of WiBro system using AMC and Hybrid-Automatic Repeat Request (H-ARQ) technologies, and confirm that the proposed AMC profile can be applied to WiBro system with high performance.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.223-236
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• 2012

We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.77-83
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• 2015

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.283-302
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• 2000

The firms aim to acquire services and costs advantage from logistics outsourcing strategy. But it is very important to select optimum service provider. A checklist of the criteria for the evaluation of service providers follows : service quality, low cost, logistics information system, service network, financial stability, investments in plant and equipment, management attitude and lookout for the future strategic fit, cultural and psychological barriers etc. Also, a 8-step implement of logistics outsourcing strategy will be of help for maximizing benefits of logistics outsourcing. It follows : 1-step : logistics environment analysis, 2-step : check service provider availability, 3-step : logistics outsourcing determinant analysis, 4-step : select of optimum service provider, 5-step : contract with optimum service provider, 6-step : identify of remaining barriers, 7-step : performance of logistics outsourcing, 8-step : evaluation.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.685-692
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• 2012

B frame bi-directional predictions and the DIRECT mode coding of the H.264 video compression standard necessitate a complex mode decision process, resulting in a long computation time. To make H.264 feasible, this paper proposes an image backtrack-based fast (IBFD) algorithm and evaluates the performances of two promising fast algorithms (i.e., AFDM and IBFD). Evaluation results show that an image backtrack-based fast (IBFD) algorithm can determine DIRECT mode macroblocks with 13% higher accuracy, as compared with the AFDM. Furthermore, IBFD is shown to reduce the motion estimation time of B frames by up to 23% with a negligible quality degradation.

• ETRI Journal
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• v.43 no.1
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• pp.82-94
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• 2021

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR-E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linear-predictive-coding-based speech analysis-synthesis system and their performance has been compared in terms of the percentage of the voiced/unvoiced classification accuracy, speech quality, and computation time. The results of the percentage of the voiced/unvoiced classification accuracy and speech quality show that the NN-based speech classifier performs better than the ACF-, AMDF-, cepstrum-, WACF- and ZCR-E-based speech classifiers for both clean and noisy environments. The computation time results show that the AMDF-based speech classifier is computationally simple, and thus its computation time is less than that of other speech classifiers, while that of the NN-based speech classifier is greater compared with other classifiers.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1171-1179
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• 2013

Interactive audio service provide with audio generating and editing functionality according to user's preference. A spatial audio object coding (SAOC) scheme is audio coding technology that can support the interactive audio service with relatively low bit-rate. However, when the SAOC scheme remove the specific one object such as vocal object signal for Karaoke mode, the scheme support poor quality because the removed vocal object remain in the SAOC-decoded background music. Thus, we propose a new SAOC vocal harmonic extranction and elimination technique to improve the background music quality in the Karaoke service. Namely, utilizing the harmonic information of the vocal object, we removed the harmonics of the vocal object remaining in the background music. As harmonic parameters, we utilize the pitch, MVF(maximum voiced frequency), and harmonic amplitude. To evaluate the performance of the proposed scheme, we perform the objective and subjective evaluation. As our experimental results, we can confirm that the background music quality is improved by the proposed scheme comparing with the SAOC scheme.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.381-396
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• 2017

In this paper, the perceptual rate control algorithm is studied for HEVC (High Efficiency Video Coding) encoder with bit allocation based on perceived visual quality. This paper proposes perceptual rate control algorithm which could consider perceived quality for HEVC encoding method. The proposed rate control algorithm employs adaptive bit allocation for frame and CTU level using the perceived visual importance of each CTU. For performance evaluation of the proposed algorithm, the proposed algorithm was implemented on HM 16.9 and tested for sequences in Class B under the CTC (Common Test Condition) RA (Random Access) case. Experimental results show that the proposed method reduces the bitrate of 3.12%, and improves BD-PSNR of 0.08dB and bitrate accuracy of 0.07% on average. And also, we achieved MOS improvement of 0.16 with the proposed method, compared with the conventional method based on DSCQS (Double Stimulus Continuous Quality Scale).