• International Journal of High-Rise Buildings
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• v.10 no.4
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• pp.251-263
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• 2021

Fire safety engineering is a critical specialization to include in the design of a tall building yet is often excluded from the Building Information Model (BIM) and integrated design process. The design of fire safety systems is interdependent with building/structural geometry, HVAC, mechanical, and electrical systems. A BIM is a 3D visual representation that stores data on these kinds of systems. The compatibility between BIM and fire safety design seems obvious yet has received a dearth of attention in structural (fire) engineering literature. The authors herein have reviewed over 40 recent papers on utilizing BIM for fire safety engineering, focusing on contemporary literature to obtain a more up-to-date review of the state-of-the-art. The resulting trends, technologies, research gaps, and methodologies are presented in this paper. Adoption of BIM in fire safety engineering is slow and behind other disciplines which may be improved if research involved more industry partners. For BIM technology to reach its potential, industry manufacturers need to provide high LOD fire BIM objects, fire engineers and researchers need to collaborate on future advancements, and building owners/management need to be educated on how to use the benefits provided.

• Advances in Computational Design
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• v.4 no.1
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• pp.43-52
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• 2019

Variation Analysis (VA) is used to simulate final product variation, taking into consideration part manufacturing and assembly variations. In VA, all the manufacturing and assembly processes are defined at the product design stage. Process Capability Data Bases (PCDB) provide information about measured variation from previous products and processes and allow the designer to apply this to the new product. A new challenge to this traditional approach is posed by the Industry 4.0 (I4.0) revolution, where Smart Manufacturing (SM) is applied. The manufacturing intelligence and adaptability characteristics of SM make present PCDBs obsolete. Current tolerance analysis methods, which are made for discrete assembly products, are also challenged. This paper discusses the differences expected in future factories relevant to VA, and the approaches required to meet this challenge. Current processes are mapped using I4.0 philosophy and gaps are analysed for potential approaches for tolerance analysis tools. Matching points of simulation capability and I4.0 intents are identified as opportunities. Applying conditional variations, incorporating levels of adjustability, and the un-suitability of present Monte Carlo simulation due to changed mass production characteristics, are considered as major challenges. Opportunities including predicting residual stresses in the final product and linking them to product deterioration, calculating non-dimensional performances and extending simulations for process manufactured products, such as drugs, food products etc. are additional winning aspects for next generation VA tools.

• Journal of Navigation and Port Research
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• v.45 no.5
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• pp.231-237
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• 2021

Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• Child Health Nursing Research
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• v.28 no.3
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• pp.197-207
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• 2022

Purpose: The purpose of this study was to investigate how pediatric intensive care unit (PICU) nurses and the mothers of hospitalized children perceived their partnership and identify the detailed differences in the common domains of partnership between them. Methods: A qualitative descriptive design with semi-structured and open-ended interviews was used. Interviews with mothers of hospitalized children and nurses in the PICU were conducted at a national university hospital in South Korea. Results: Five integrated categories were identified concerning nurses' and mothers' perceptions of partnership. Five common domains were derived by merging the partnership categories perceived by each PICU mother and nurse: expectation of trust, sharing and communication, participation in care, equality in the relationship, and coordination of opinion However, there were significant differences in the composition of the categories of these common domains. Conclusion: These results may facilitate more effective partnerships between parents and PICU nurses. Efforts should be taken to promote the formation of trust between nurses and parents and create an environment that is conductive to regular open communication in particular, steps should be taken to reduce gaps in awareness concerning this partnership and information sharing, nursing methods, and decision-making.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• Journal of Distribution Science
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• v.20 no.2
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• pp.55-64
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• 2022

Purpose: This research is aimed to study the level of the intellectual potential distribution, as well as the correlation between economic growth and key indicators of intellectual potential in each region of Kazakhstan. A review of the conceptual framework shows that there is a large body of research evaluating the level of intellectual potential in different ways based on different factors. Research design, data, and methodology: The research methodology is divided into two groups the integral index method using the normalization of indicators, weighting, and ranking; the method of correlation analysis. By the proposed methodological approaches, were calculated a set of factors affect the distribution of the intellectual potential. Statistics are taken for indicators of development of the intellectual potential for 2011-2020 from the Bureau of National Statistics. Results: Ranking results showed gaps between regions in Kazakhstan by the level of intellectual potential. Correlation analysis results revealed a statistically significant relationship on expenditures on R&D, computer literacy, innovative products, number of PhD students, and cultural and leisure indicators. Conclusions: Based on the obtained results of the intellectual potential level development there were given recommendations for the reproduction and regulation of the intellectual potential in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Journal of Distribution Science
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• v.22 no.1
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• pp.37-46
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• 2024

Purpose: This study aims to address the overlooked micro-level aspects within Smart Manufacturing (SM) research, rectifying the misalignment in manufacturing firms' estimation of their technological adoption capabilities. Drawing upon the Social-Technical Systems (STS) theory, this paper utilises innovation capability as a mediating variable, constructing a human-centric organizational model to bridge this research gap. Research design, data and methodology: This study collected data from 233 Chinese manufacturing firms via online questionnaires. Introducing innovation capability as a mediating variable, it investigates the impact of social-technical system dimensions (work design, social subsystems, and technical subsystems) on SM adoption willingness. Smart PLS 4.0 was employed for data analysis, and Structural Equation Modelling (SEM) validated the theoretical model's assumptions. Results: In direct relationships, social subsystems, technical subsystems, and work design positively influence firms' innovation capabilities, which, in turn, positively impact SM adoption. However, innovation capability does not mediate the relationship between technical subsystems and SM adoption. Conclusions: This study focuses on the internal micro-level of organisational employees, constructing a human-centric framework that emphasises the interaction between organisations and technology. The study fills empirical gaps in Smart Manufacturing adoption, providing organisations with a means to examine the integration of employees and the organisational social-technical system.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.88-97
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• 2024

This study performed the analysis on an economic feasibility of each marine fuel, potential fuel pathways and the relevance of compliance measures to ensure compliance with the FuelEU Maritime regulation. Additionally, it identified certain regulatory gaps to encourage the use of alternative marine fuels. Regarding GHG emissions calculations, the existing GHG regulations for ships applies the Tank-to-Wake (TtW) method, whereas FuelEU Maritime applies the Well-to-Wake (WtW) method. The main results present that important information to establish response strategy for FuelEU Maritime including the costs and benefits of each marine fuel, the minimum blending ratio of alternative fules, and compliance impacts of measures. For the regulatory costs and benefits of marine fuels following the implementation of the FuelEU Maritime from 2025, our findings indicate that while most fossil fuels incur regulatory costs from 2025, most of biofuels and RFNBO fuels do not incur costs until 2050. This will play a role to narrow the price gap between fossil fuels and alternative fuels.