• Molecules and Cells
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• v.41 no.1
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• pp.18-26
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• 2018

Mitochondrial quality control systems are essential for the maintenance of functional mitochondria. At the organelle level, they include mitochondrial biogenesis, fusion and fission, to compensate for mitochondrial function, and mitophagy, for degrading damaged mitochondria. Specifically, in mitophagy, the target mitochondria are recognized by the autophagosomes and delivered to the lysosome for degradation. In this review, we describe the mechanisms of mitophagy and the factors that play an important role in this process. In particular, we focus on the roles of mitophagy adapters and receptors in the recognition of damaged mitochondria by autophagosomes. In addition, we also address a functional association of mitophagy with mitochondrial dynamics through the interaction of mitophagy adaptor and receptor proteins with mitochondrial fusion and fission proteins.

• Annual Conference on Human and Language Technology
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• 1992.10a
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• pp.555-566
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• 1992

본 논문은 한글 주소의 오인식 수정에 관한 연구로서, 필기자의 다양한 필기 형태와 입력 장치의 특성으로 인하여 문자 인식 단계에서 발생할 수 있는 혼동을 줄이고 오류를 효율적으로 수정하는 후처리 알고리즘을 소개한다. 특히, 주소의 행정 구역부에 대해서는 정합해야 할 문자 모델의 범위를 줄여줌으로써 높은 인식률과 처리 속도를 기록하였으며, 문자 인식의 결과에 임계값과 백트랙킹 방법을 도입한 후처리 알고리즘을 적용하여 더욱더 높은 인식률을 나타낼 수 있었다. 번지부와 건물부에 대한 오인식도 제안된 각각의 알고리즘을 적용함으로써 효과적으로 수정할 수 있었다. 우리나라의 25,000여 행정 구역을 바탕으로 작성 가능한 주소들 중에서 임의의 150개 주소 데이타에 대하여 제안된 후처리 방법을 포함한 다양한 후처리 방법으로 실험한 결과, 행정 구역부에 대하여 98%이상의 높은 인식률을 보임으로써, 제안된 후처리 알고리즘이 효과적임을 알 수 있었다.

• Clean Technology
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• v.4 no.1
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• pp.24-34
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• 1998

Eco-labelling programs contributed to the promotion of international trade of environmentally friendly products. However, it has potential trade implications. From the WTO's point of view, environmental measures relevant to eco-labelling should not discriminate between home produced goods and imported goods. Transparency should be guaranteed in preparation, adoption and application of eco-labelling. Developed countries address that eco-labelling of non-product PPM criteria is included in the provisions of TBT of WTO. However, there are more general afraids that non-product PPM-based eco-labelling can be unfairly discriminately trade measures without transparency Thus, transparency of procedures of eco-labelling, harmonization and mutual recognition of eco-labelling criteria, and technical assistance should be recommended in order to reduce trade-discriminating effects of eco-labelling.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.524-534
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• 2022

In this paper, we produce Trash Object Detection (TOD) dataset to solve trash detection problems. A well-organized dataset of sufficient size is essential to train object detection models and apply them to specific tasks. However, existing trash datasets have only a few hundred images, which are not sufficient to train deep neural networks. Most datasets are classification datasets that simply classify categories without location information. In addition, existing datasets differ from the actual guidelines for separating and discharging recyclables because the category definition is primarily the shape of the object. To address these issues, we build and experiment with trash datasets larger than conventional trash datasets and have more than twice the resolution. It was intended for general household goods. And annotated based on guidelines for separating and discharging recyclables from the Ministry of Environment. Our dataset has 10 categories, and around 33K objects were annotated for around 5K images with 1280×720 resolution. The dataset, as well as the pre-trained models, have been released at https://github.com/jms0923/tod.

• Journal of Digestive Cancer Research
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• v.11 no.1
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• pp.35-40
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• 2023

Distress in patients with digestive cancers can considerably impact not only their treatment adherence but also their health-related quality of life. Early distress recognition in patients, appropriate interventions by the oncology team, or referral to mental health professionals, can enhance the treatment efficiency. This review aims to provide an overview of distress evaluation and its management in patients with cancer, specifically digestive cancers, and to address the psychological responses and distress that occur in those patients during treatment. Furthermore, the review will introduce possible psychological interventions for patients with digestive cancers who experience significant distress, depending on the duration and planning of the treatment.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.115-121
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• 2013

A number of urban renewal projects are currently being implemented around the world. Current project management tools are limited in effectively dealing with numerous issues regarding management of these projects (e.g., simultaneous execution of multiple projects). As an effort to address this deficiency, an Intelligent Program Management Information System (i-PgMIS) was developed for effective management of urban renewal projects. The i-PgMIS is a web-based system consisting of various modules including cost management, schedule management, risk management, change management, eco-value engineering (EVE) and so on. Based on the recognition of increasing awareness of creating sustainable built environment, this paper focuses on the EVE module that can support eco-value analysis at program-level management. The EVE module is expected to enhance value and sustainability of construction processes throughout the whole 'program' lifecycle and further to support program feasibility study based on life cycle costing.

• Educational Technology International
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• v.16 no.2
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• pp.249-272
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• 2015

This study is a theoretical exploration of project-based service-learning and its application in designing pre-dental curricula. As a response to the limitation of community service courses, service-learning has been implemented as pedagogy in higher education practices. Service-learning connects service and learning by engaging students in activities that address community needs with intentionally designed learning opportunities while adding value to and transforming both service and learning. Project-based service-learning is an extended and more active version of service-learning. Whereas service activities are arranged by instructors in the original service-learning, project-based service-learning provides students with opportunities for exploring problems and root causes on site and then devising and implementing solutions of their own using their talents and creativity. This study proposes a theoretical approach to project-based service-learning and suggests six design components, namely, related curriculum, reflection, reciprocity, service and community engagement, evaluation and recognition, and creative problem solving. Based on the components, 20 design strategies are formulated. The exploration is aimed to provide design guides for professionals attempting to implement project-based service-learning in higher education.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.551-560
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• 2023

Recently, there has been significant research into the recognition of human activities using three-dimensional sequential skeleton data captured by the Kinect depth sensor. Many of these studies employ deep learning models. This study introduces a novel feature selection method for this data and analyzes it using machine learning models. Due to the high-dimensional nature of the original Kinect data, effective feature extraction methods are required to address the classification challenge. In this research, we propose using the first four moments as predictors to represent the distribution of joint sequences and evaluate their effectiveness using two datasets: The exergame dataset, consisting of three activities, and the MSR daily activity dataset, composed of ten activities. The results show that the accuracy of our approach outperforms existing methods on average across different classifiers.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.310-313
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• 2024

Rust has gained recognition for its emphasis on and commitment to providing memory safety. However, seamlessly integrating it with Foreign Function Interfaces (FFIs) written in unsafe languages remains a significant challenge towards achieving complete memory safety. To address this challenge, researchers have proposed Foreign Function Isolation as a potential solution, leading to emergence of various approaches in this domain. This paper critically evaluates existing solutions and illuminates the gaps that need to be addressed to realize practical foreign function isolation in Rust.