• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3599-3619
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• 2019

In human activity recognition system both static and motion information play crucial role for efficient and competitive results. Most of the existing methods are insufficient to extract video features and unable to investigate the level of contribution of both (Static and Motion) components. Our work highlights this problem and proposes Static-Motion fused features descriptor (SMFD), which intelligently leverages both static and motion features in the form of descriptor. First, static features are learned by two-stream 3D convolutional neural network. Second, trajectories are extracted by tracking key points and only those trajectories have been selected which are located in central region of the original video frame in order to to reduce irrelevant background trajectories as well computational complexity. Then, shape and motion descriptors are obtained along with key points by using SIFT flow. Next, cholesky transformation is introduced to fuse static and motion feature vectors to guarantee the equal contribution of all descriptors. Finally, Long Short-Term Memory (LSTM) network is utilized to discover long-term temporal dependencies and final prediction. To confirm the effectiveness of the proposed approach, extensive experiments have been conducted on three well-known datasets i.e. UCF101, HMDB51 and YouTube. Findings shows that the resulting recognition system is on par with state-of-the-art methods.

• 한국연안방재학회지
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• 제4권3호
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• pp.133-137
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• 2017

The Arctic region remains surrounded by sea ice during most of the period of the year. In the Arctic Ocean the Northern Sea Route (NSR) has been used as an important route for shipping. The arctic sea ice is decreasing since 1979; hence needs to be monitored. In this research work sea ice concentration in the recent years and sea ice concentration anomalies of few months with long term sea ice concentration are studied. The climatology of long term ice concentration data from various satellites, and the recent sea ice concentration data from Advanced Microwave Scanning Radiometer 2 (AMSR2) were used. The results show that sea ice concentration and sea ice extent in the Arctic region decreased by around 5% from 2015 to 2016, but in 2017 increased again in smaller amount in some areas like around Novaya Zemlya, and parts of the sea in between Greenland and Longyearbyen, and around Banks Island. The percentages of sea ice area in NSR for July 7 in 2015 to 2017 were 37%, 39% and 33%, respectively, indicating a large area (around ten thousand $km^2$) become ice free in 2017 compared to the previous year.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.73-80
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• 2021

Nowadays microblogs have become the most popular platforms to obtain and spread information. Twitter is one of the most used platforms to share everyday life event. However, rumors and misinformation on Arabic social media platforms has become pervasive which can create inestimable harm to society. Therefore, it is imperative to tackle and study this issue to distinguish the verified information from the unverified ones. There is an increasing interest in rumor detection on microblogs recently, however, it is mostly applied on English language while the work on Arabic language is still ongoing research topic and need more efforts. In this paper, we propose a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to detect rumors on Twitter dataset. Various experiments were conducted to choose the best hyper-parameters tuning to achieve the best results. Moreover, different neural network models are used to evaluate performance and compare results. Experiments show that the CNN-LSTM model achieved the best accuracy 0.95 and an F1-score of 0.94 which outperform the state-of-the-art methods.

• BMB Reports
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• 제56권9호
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• pp.488-495
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• 2023

Mitochondrial transplantation is a promising therapeutic approach for the treatment of mitochondrial diseases caused by mutations in mitochondrial DNA, as well as several metabolic and neurological disorders. Animal studies have shown that mitochondrial transplantation can improve cellular energy metabolism, restore mitochondrial function, and prevent cell death. However, challenges need to be addressed, such as the delivery of functional mitochondria to the correct cells in the body, and the long-term stability and function of the transplanted mitochondria. Researchers are exploring new methods for mitochondrial transplantation, including the use of nanoparticles or CRISPR gene editing. Mechanisms underlying the integration and function of transplanted mitochondria are complex and not fully understood, but research has revealed some key factors that play a role. While the safety and efficacy of mitochondrial transplantation have been investigated in animal models and human trials, more research is needed to optimize delivery methods and evaluate long-term safety and efficacy. Clinical trials using mitochondrial transplantation have shown mixed results, highlighting the need for further research in this area. In conclusion, although mitochondrial transplantation holds significant potential for the treatment of various diseases, more work is needed to overcome challenges and evaluate its safety and efficacy in human trials.

• The Journal of Korean Physical Therapy
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• 제34권6호
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• pp.304-311
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• 2022

Purpose: The purpose of this study was to investigate the knowledge, awareness and performance of COVID-19 infection control among physical therapists and to identify the impact factors on performance Methods: Data were collected from March 16th to March 24th in 2022 from the physical therapist's in Busan. Data analysis was conducted on 170 surveys, after excluding 27 surveys that were found to be unsuitable for data analysis. Results: When correlating the study variables, knowledge and awareness were found to have a positive, meaningful correlation with performance. Performance of COVID-19 personal infection control regression analysis showed that the working department (clinic and long-term care hospital), clinical experience, the more knowledgeable, the awareness (personal), and the more clinical experience had significant positive impacts on the performance of COVID-19 infection control. Performance of COVID-19 treatment room infection control regression analysis showed that the working department (long-term care hospital), educational experience, the awareness (treatment room) had significant positive impacts on the performance of COVID-19 infection control Conclusion: The results of this study may be used as basic data for educating physical therapist's working at the COVID-19 response department. This study suggests that physical therapist's need educational programs to improve their knowledge and awareness and performance of infection control against infectious diseases such as COVID-19. Differentiated physical therapists practice education curricula must be developed and provided after understanding the varying characteristic of physical therapist's with different levels of work experience.

• Nuclear Engineering and Technology
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• 제55권3호
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• pp.839-849
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• 2023

The development of automation technology to reduce human error by minimizing human intervention is accelerating with artificial intelligence and big data processing technology, even in the nuclear field. Among nuclear power plant operation modes, the startup and shutdown operations are still performed manually and thus have the potential for human error. As part of the development of an autonomous operation system for startup operation, this paper proposes an action coordinating strategy to obtain the optimal actions. The lower level of the system consists of operating blocks that are created by analyzing the operation tasks to achieve local goals through soft actor-critic algorithms. However, when multiple agents try to perform conflicting actions, a method is needed to coordinate them, and for this, an action coordination strategy was developed in this work as the upper level of the system. Three quantification methods were compared and evaluated based on the future plant state predicted by plant parameter prediction models using long short-term memory networks. Results confirmed that the optimal action to satisfy the limiting conditions for operation can be selected by coordinating the action sets. It is expected that this methodology can be generalized through future research.

• Geomechanics and Engineering
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• 제34권1호
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• pp.43-49
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• 2023

Knowledge of minimum horizontal stress (S_hmin) is a significant step in determining full stress tensor. It provides crucial information for the production of sand, hydraulic fracturing, determination of safe mud weight window, reservoir production behavior, and wellbore stability. Calculating the S_hmin using indirect methods has been proved to be awkward because a lot of data are required in all of these models. Also, direct techniques such as hydraulic fracturing are costly and time-consuming. To figure these problems out, this work aims to apply the long-short-term memory (LSTM) algorithm to S_hmin time-series prediction. 13956 datasets obtained from an oil well logging operation were applied in the models. 80% of the data were used for training, and 20% of the data were used for testing. In order to achieve the maximum accuracy of the LSTM model, its hyper-parameters were optimized significantly. Through different statistical indices, the LSTM model's performance was compared with with other machine learning methods. Finally, the optimized LSTM model was recommended for S_hmin prediction in the well logging operation.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2020년도 가을 학술논문 발표대회
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• pp.188-189
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• 2020

In the field of architecture, concrete and steel bars are the most common and popular combinations. The relationship between the two in a structure is a complementary good that increases in utility when consuming both materials at the same time. However, the combination of the two, which has been perceived as semi-permanent, often faces repairs or reconstruction without its lifespan reaching decades. There are a number of deterioration factors at work for the reason for this phenomenon. Among them, the neutralization of concrete in particular refers to the process in which calcium hydroxide inside concrete reacts with carbon dioxide and loses alkalinity, which creates a corrosive environment for rebars inside concrete, causing serious damage to concrete. In this study, we intend to use a multi-physical analysis program using finite element analysis method to analyze the degree of carbonation according to the internal temperature and concentration of carbon dioxide in concrete, thereby contributing to the prediction of long-term neutralization of concrete and the research related to measures for neutralization of concrete.

• Wind and Structures
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• 제36권6호
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• pp.379-392
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• 2023

Structural health monitoring is used to ensure the well-being of civil structures by detecting damage and estimating deterioration. Wind flow applies external loads to high-rise buildings, with the horizontal force component of the wind causing structural displacements in high-rise buildings. This study proposes a deep learning-based predictive model for measuring lateral displacement response in high-rise buildings. The proposed long short-term memory model functions as a sequence generator to generate displacements on building floors depending on the displacement statistics collected on the top floor. The model was trained with wind-induced displacement data for the top floor of a high-rise building as input. The outcomes demonstrate that the model can forecast wind-induced displacement on the remaining floors of a building. Further, displacement was predicted for each floor of the high-rise buildings at wind flow angles of 0° and 45°. The proposed model accurately predicted a high-rise building model's story drift and lateral displacement. The outcomes of this proposed work are anticipated to serve as a guide for assessing the overall lateral displacement of high-rise buildings.

• 한국과학교육학회지
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• 제28권3호
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• pp.241-252
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• 2008

The purpose of this study is to investigate the impacts of a science gifted education program. 155 students who experienced the SNU science gifted education program were interviewed. The interview questions consisted of eligible questions from 'Interview Protocol of Hertzog' (2003) based on 'Recommended Practice in Gifted Education (Shore, Cornell, & Ward, 1991)'. All interviews were immediately transcribed and analyzed qualitatively. It was found that scientifically gifted students had similar concepts of the gifted to what scholars consider as the gifted. Comparing the programs to school education program, the students agreed that the science gifted education program provided more experiments opportunities, higher and deeper level of contents, and more active interactions. Regarding long-term effects, it was found that program influenced on students' decisions for the future, stimuli and expansion of horizons, school work and entrance examinations. Students gained self-confidence and became more interested in science. Some pointed out that they felt greater stimulated, although some indicated an elevated level of self conceit. Implications of science gifted education were found based on these results.