• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.163-172
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• 2017

In recent days, the Non-Linear Editing is mainly used in the field of broadcasting. In comparison to conventional editing, Non-Linear Editing can immediately access the image of the desired position and facilitate the insertion and deletion of video frame. Furthermore, it directly apply a title and transition effect to video frame. Moreover, it has an advantage of preview and easy modification in title effect, transition and editing prior to export. However, students who learn Non-Linear Editing first time are not easy to learn it. In this paper, we propose a new learning model based on Reciprocal Peer Teaching (RPT), which helps NLE beginners to understand Non-Linear editing more clearly. We divide the students into two groups i.e. control group and experimental group. The control group students do not apply proposed method while experimental group performs evaluation over our model. Furthermore, we carry out the experiments, which include the overall average of the two groups, academic achievement of students with low grades, standard deviation, T-test and satisfaction surveys. The experimental group shows the superiority in performed experiments and higher satisfaction ratings than the control group.

• Journal of Microbiology and Biotechnology
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• v.34 no.7
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• pp.1522-1529
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• 2024

CRISPR-Cas system is being used as a powerful genome editing tool with developments focused on enhancing its efficiency and accuracy. Recently, the miniature CRISPR-Cas12f1 system, which is small enough to be easily loaded onto various vectors for cellular delivery, has gained attention. In this study, we explored the influence of temperature conditions on multiplex genome editing using CRISPR-Cas12f1 in an Escherichia coli model. It was revealed that when two distinct targets in the genome are edited simultaneously, the editing efficiency can be enhanced by allowing cells to recover at a reduced temperature during the editing process. Additionally, employing 3'-end truncated sgRNAs facilitated the simultaneous single-nucleotide level editing of three targets. Our results underscore the potential of optimizing recovery temperature and sgRNA design protocols in developing more effective and precise strategies for multiplex genome editing across various organisms.

• BMB Reports
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• v.55 no.6
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• pp.251-258
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• 2022

Innovative genome editing techniques developed in recent decades have revolutionized the biomedical research field. Liver is the most favored target organ for genome editing owing to its ability to regenerate. The regenerative capacity of the liver enables ex vivo gene editing in which the mutated gene in hepatocytes isolated from the animal model of genetic disease is repaired. The edited hepatocytes are injected back into the animal to mitigate the disease. Furthermore, the liver is considered as the easiest target organ for gene editing as it absorbs almost all foreign molecules. The mRNA vaccines, which have been developed to manage the COVID-19 pandemic, have provided a novel gene editing strategy using Cas mRNA. A single injection of gene editing components with Cas mRNA is reported to be efficient in the treatment of patients with genetic liver diseases. In this review, we first discuss previously reported gene editing tools and cases managed using them, as well as liver diseases caused by genetic mutations. Next, we summarize the recent successes of ex vivo and in vivo gene editing approaches in ameliorating liver diseases in animals and humans.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.201-208
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• 2018

High Efficiency Video Coding range extensions (HEVC RExt) is a kind of extension model of HEVC. HEVC RExt was specially designed for dealing the high quality images. HEVC RExt is very essential for studio editing which handle the very high quality and various type of images. There are some problems to dealing these massive data in studio editing. One of the most important procedure is re-encoding and decoding procedure during the editing. Various codecs are widely used for studio data editing. But most of the codecs have common problems to dealing the massive data in studio editing. First, the re-encoding and decoding processes are frequently occurred during the studio data editing and it brings enormous time-consuming and video quality loss. This paper, we suggest new video coding structure for the efficient studio video editing. The coding structure which is called "ultra-low delay (ULD)". It has the very simple and low-delayed referencing structure. To simplify the referencing structure, we can minimize the number of the frames which need decoding and re-encoding process. It also prevents the quality degradation caused by the frequent re-encoding. Various fast coding algorithms are also proposed for efficient editing such as tool-level optimization, multi-serve based distributed coding and SIMD (Single instruction, multiple data) based parallel processing. It can reduce the enormous computational complexity during the editing procedure. The proposed method shows 9500 times faster coding speed with negligible loss of quality. The proposed method also shows better coding gain compare to "intra only" structure. We can confirm that the proposed method can solve the existing problems of the studio video editing efficiently.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.1-9
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• 2020

In this paper, we propose a model that performs more natural facial attribute editing by utilizing mask information in the hair and hat region. STGAN, one of state-of-the-art research of facial attribute editing, has shown results of naturally editing multiple facial attributes. However, editing hair-related attributes can produce unnatural results. The key idea of the proposed method is to additionally utilize information on the face regions that was lacking in the existing model. To do this, we apply three ideas. First, hair information is supplemented by adding hair ratio attributes through masks. Second, unnecessary changes in the image are suppressed by adding cycle consistency loss. Third, a hat segmentation network is added to prevent hat region distortion. Through qualitative evaluation, the effectiveness of the proposed method is evaluated and analyzed. The method proposed in the experimental results generated hair and face regions more naturally and successfully prevented the distortion of the hat region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3685-3707
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• 2021

In recent years, facial attribute editing has been successfully used to effectively change face images of various attributes based on generative adversarial networks and encoder-decoder models. However, existing models have a limitation in that they may change an unintended part in the process of changing an attribute or may generate an unnatural result. In this paper, we propose a model that improves the learning of the attention mask by adding a spatial attention mechanism based on the unified selective transfer network (referred to as STGAN) using semi-supervised learning. The proposed model can edit multiple attributes while preserving details independent of the attributes being edited. This study makes two main contributions to the literature. First, we propose an encoder-decoder model structure that learns and edits multiple facial attributes and suppresses distortion using an attention mask. Second, we define guide masks and propose a method and an objective function that use the guide masks for multiple facial attribute editing through semi-supervised learning. Through qualitative and quantitative evaluations of the experimental results, the proposed method was proven to yield improved results that preserve the image details by suppressing unintended changes than existing methods.

• Speech Sciences
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• v.3
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• pp.119-131
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• 1998

We have developed a keyword spotting system for automatic speech editing. This system recognizes the only keyword 'MBC news' and then sends the time information to the host system. We adopted a vocabulary dependent model based on continuous hidden Markov model, and the Viterbi search was used for recognizing the keyword. In recognizing the keyword, the system uses a parallel network where HMM models are connected independently and back-tracking information for reducing false alarms and missing. We especially focused on implementing a stable and practical real-time system.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.1-8
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• 2020

Machine translation refers to a system where a computer translates a source sentence into a target sentence. There are various subfields of machine translation. APE (Automatic Post Editing) is a subfield of machine translation that produces better translations by editing the output of machine translation systems. In other words, it means the process of correcting errors included in the translations generated by the machine translation system to make proofreading. Rather than changing the machine translation model, this is a research field to improve the translation quality by correcting the result sentence of the machine translation system. Since 2015, APE has been selected for the WMT Shaed Task. and the performance evaluation uses TER (Translation Error Rate). Due to this, various studies on the APE model have been published recently, and this paper deals with the latest research trends in the field of APE.

• Journal of Microbiology and Biotechnology
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• v.28 no.12
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• pp.1955-1970
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• 2018

Several genetic strategies have been proposed for the successful transformation and expression of microbial transgenes in model and crop plants. Here, we bring into focus the prominent applications of microbial transgenes in plants for the development of disease resistance; mitigation of stress conditions; augmentation of food quality; and use of plants as "bioreactors" for the production of recombinant proteins, industrially important enzymes, vaccines, antimicrobial compounds, and other valuable secondary metabolites. We discuss the applicable and cost-effective approaches of transgenesis in different plants, as well as the limitations thereof. We subsequently present the contemporary developments in targeted genome editing systems that have facilitated the process of genetic modification and manifested stable and consumer-friendly, genetically modified plants and their products. Finally, this article presents the different approaches and demonstrates the introduction and expression of microbial transgenes for the improvement of plant resistance to pathogens and abiotic stress conditions and the production of valuable compounds, together with the promising research progress in targeted genome editing technology. We include a special discussion on the highly efficient CRISPR-Cas system helpful in microbial transgene editing in plants.

• Proceedings of the KSLP Conference
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• 1995.11a
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• pp.154-164
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• 1995

CSL, Model 4300B is a highly flexible audio processing package designed to provide a wide variety of speech analysis operations for both new and sophisticated users. Operations include 1) Data acquisition 2) File management 3) Graphics 4) Numerical display 5) Audio output 6) Signal editing 7) A variety of analysis functions, External module include 1) Input control B) Output control 3) Jacks, Software include 1) Wide range of speech display manipulation 2) Editing 3) Analysis (omitted)