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Concentration-Induced Hetero-Valent Partial-Inverse Occupation of Infrared Phosphor

Advanced Optical Materials 2023年第14期11卷

作者： Hsu, Jia-Yu Chung, Ren-Jei Kuo, Yen-Ling Lin, Chun Che Majewska, Natalia Kreft, Dominik Mahlik, Sebastian Fang, Mu-Huai Research Center for Applied Sciences Academia Sinica Taipei10608 Taiwan Institute of Manufacturing Technology Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei10608 Taiwan Institute of Organic and Polymeric Materials National Taipei University of Technology Taipei10608 Taiwan Institute of Experimental Physics Faculty of Mathematics Physics and Informatics University of Gdańsk Gdansk Wita Stwosza 57 Gdansk80-308 Poland Institute of Ocean Engineering and Ship Technology Faculty of Mechanical Engineering and Ship Technology University of Gdańsk Gabriela Narutowicza 11/12 Gdansk80-233 Poland

Infrared luminescent materials have evoked much attention from chemists and material scientists. Although substantial progress is made in materials design, the luminescent mechanism remains ambiguous in the complex structures, presenting major barriers to developing novel infrared luminescent materials. Herein, this study aims to deliberate a complete discussion on infrared phosphors with concentration-induced hetero-valent partial-inverse occupation. High-resolution synchrotron X-ray diffraction and Raman spectroscopy reveal the subtle structural change in LiGa5(1−x)O8:5xCr3+. Besides, Cr K-edge wavelet analysis and extended X-ray absorption fine structure illustrate the impact of Cr in the second shell of another Cr ion and the practical coordination of Ga and Cr ions. Furthermore, unexpected two-center Cr3+ emissions and the Cr–Cr pair emission are observed at high Cr concentrations. Variation between the zero-phonon line and N-line at different temperatures is demonstrated. Finally, the structural and luminescent properties are comprehensively discussed, providing the origin of the unexpected Cr2 emission. This study not only provides insight into the hetero-valent partial-inverse occupation process in inorganic materials but also sheds light on developing novel infrared luminescent materials. © 2023 Wiley-VCH GmbH.

关键词： Light emitting diodes

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Line of sight visibility analysis for foreign object debris detection system 2

Line of sight visibility analysis for foreign object debris ...

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2nd International Conference on Emerging Electrical Energy, Electronics and Computing Technologies 2020, ICE4CT 2020

作者： Fizza, G. Idrus, S.M. Iqbal, F. Hassan, W.H.W. Shibagaki, N. Kashima, K. Hamzah, A. Ambran, S. Kawanishi, T. Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Quaid-e-Awam University of Engineering Science and Technology Nawabshah Pakistan Faculty of Ocean Engineering and Informatics Universiti Malaysia Terengganu Malaysia Hitachi Kokusai Electric Inc. Tokyo Japan Waseda University Japan

It is challenging to monitor busy airports' runway through visual inspection to precisely detect foreign object debris. Currently, many technologies for the detection of foreign object debris are available. It has been investigated that millimeter-wave radar technology's detection capability can be one of the most effective techniques for detecting foreign object debris as it is weather-resilient. However, the positioning and height of a millimeter-wave radar pole covering the runway area, considering the existing runway infrastructure, are challenging. The task involves finding the appropriate placement and optimum height. This paper presents a novel method of line of sight visibility for placement and height of radar pole using human factor research to ensure that each point on the runway is visible from various heights of the millimeter-wave radar pole to the runway locations. Kuala Lumpur International Airport, Malaysia runway 32L/14R, has used a case study to test the visibility analysis. The visual analytic test's successful results for different millimeter-wave radar pole locations and viewing heights under a visible and invisible line of sight conditions on the runway have been verified in the field experiment. © Published under licence by IOP Publishing Ltd.

关键词： Poles

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Examining relative variable importance (RVI) and strength of interaction effects (SIE) of particulate matter (PM10) concentrations in moving vehicles at selected route in east coast of Malaysia

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AIP Conference Proceedings 2023年第1期2484卷

作者： Y. N. Zaitun W. M. W. Nurdiyana H. Fahimah I. Zulfadhli 1Senior Lecturer Faculty of Ocean Engineering Technology and Informatics University Malaysia Terengganu Malaysia 2Researcher Faculty of Ocean Engineering Technology and Informatics University Malaysia Terengganu Malaysia

The poor indoor air quality inside the cabin of a coach can be due to indoor air pollutants or to inadequate ventilation. Exposure to surrounding airborne particulate matter inside a long hour journey may increase health risk of the coach passengers. In this study, a one-minute gaseous (carbon monoxide (CO), carbon dioxide (CO2)), physical parameters (relative humidity, airflow, temperature), coach speeds, and number of occupants’ data were gathered two days trips for each route travelled coaches via motorways and local routes. The Route 1 journey started from Terminal Kota Bharu (TKB) to Terminal Bersepadu Selatan (TBS) and Route 2 link between Terminal Kuala Terengganu (TKT) and Terminal Bersepadu Selatan (TBS). Data were analysed to understand variability of the variables by using R software and its packages were applied temporally and statistically. An advance and a computational intelligence technique named the Boosted Regression Trees (BRT) was used to examine Relative Variable Importance (RVI) and estimation the Strength of Interaction Effects (SIE) inside cabin coaches. Results demonstrates significant variation in PM10 are distance (39.19%), elevation (15.19%) temperature (10.56%) humidity (6.65%) for Route 1 and 46.7% for CO (13.77 %), humidity (8.92 %), and elevation (8.01 %) for Route 2. It was found that strength of interactions (SIE) index was determined for humidity and temperature for both routes which range between 0.23 to 0.32, followed by humidity and airflow interactions (0.05) and CO and airflow (0.18) for Route 2. Since SIE or H-values fall within range from 0 to 1 which value of zero indicates that there are no interactions between the variables, the interaction between variables will be stronger if the value is closer to 1. It appears and promises that this machine learning method in particular BRT is able to examine in cabin pollutants and physical environment data.

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Optimizing Droplet Coalescence Dynamics in Microchannels: A Comprehensive Study Using Response Surface Methodology and Machine Learning Algorithms

SSRN

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SSRN 2024年

作者： Javadpour, Seyed Morteza Kadivar, Erfan Zarneh, Zienab Heidary Kadivar, Ebrahim Gheibi, Mohammad Department of Mechanical Engineering University of Gonabad Gonabad Iran Department of Physics Shiraz University of Technology Shiraz71555-313 Iran Institute of Ship Technology Ocean Engineering and Transport Systems University of Duisburg-Essen Duisburg47057 Germany Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Liberec46117 Czech Republic Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic

Droplet coalescence in microchannels is a complex phenomenon influenced by various parameters such as droplet size, velocity, liquid surface tension, and droplet-droplet spacing. In this study, we thoroughly investigate the impact of these control parameters on droplet coalescence dynamics within a sudden expansion microchannel using two distinct numerical methods. Initially, we employ the boundary element method to solve the Brinkman integral equation, providing detailed insights into the underlying physics of droplet coalescence. Furthermore, we integrate Response Surface Methodology (RSM) to effectively optimize droplet coalescence dynamics, harnessing the power of machine learning algorithms. Our results showcase the efficacy of these computational techniques in enhancing experimental efficiency. Through rigorous evaluation utilizing Regression Coefficient and Mean Absolute Error metrics, we ascertain the accuracy of our estimations. Our findings highlight the significant influence of key parameters, specifically droplet diameter (D), viscosity (Vis), and width (W), as identified by droplet-droplet spacing (DD), velocity of the first droplet (VFD), and velocity of the second droplet (VBD), respectively. This comprehensive approach provides valuable insights into droplet coalescence phenomena and offers a robust framework for optimizing microfluidic systems. © 2024, The Authors. All rights reserved.

关键词： Coalescence

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Blood cell detection and counting in microscopy images using overlapping object recognizing model

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AIP Conference Proceedings 2023年第1期2484卷

作者： Muhamad Munawar Yusro Rozniza Ali Muhammad Suzuri Hitam 1)Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia

Computer vision is one of the most striking areas in data science. Like other fields of data science, the application of this field has also become part of our personal lives. Classifying an overlapping object in cell detection is one of the main challenges faced by researchers who work in object detection and recognition. The white and red blood cells have a significant part in controlling the human body's framework. One of the essential tests for assessing human medical issue is checking the amount of white blood cells and red blood cells, as well as platelets number in the blood. In this project, we used one of the Convolutional Neural Network (CNN) techniques which is Faster Region CNN to recognize, classify, and count the blood cell elements. Our objective is to detect blood cell images from dataset, separate between overlapping cells and other objects, and then count the number of each blood cell. The researchers used 720 images containing 1603 labelled blood cells from 10 categories to train the model. Those images were marked by clinical the Hospital Clinic of Barcelona ‘s pathologists and were obtained from the dissemination of blood drawn from patients during 2015-2019. After training steps were performed on 60 images, and blood cell detection and segmentation were performed in the next steps. The average accuracy was 97%, and the verification loss was 18.4%. By using this our Faster R-CNN framework object detection method can enhance the accuracy and speed of cell detection.

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A review on recent studies of buoyancy effect

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AIP Conference Proceedings 2023年第1期2484卷

作者： Nur Syahmi Izzati Ali Othman Sunny Goh Eng Giap 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia

Vapor buoyancy effect is the moist air that is lighter than dry air at the same volume, temperature and pressure due to the molecular weight of water which is less than that of dry air. Even though this effect is well known however, the impact on system been overlooked. Therefore, in this paper, we review articles-based the effect of buoyancy that can be one of the factors for the environmental purposes under several conditions. Therefore, the review focused on the effect of buoyancy as the factor that affect the process of the system studied by the previous researchers. The studies discussed here primarily include the effect of buoyancy based on the findings, conditions and area of the applications. The results showed that the effect of buoyancy becoming the factor that affect the whole process of the system. The review found the effect of buoyancy possibly one of the factors that cause the fundamental problem in the model prediction of water, vapor and heat flux in the soils. Future research should focus on a complete understanding of the mechanisms of the effect of buoyancy in soils by developing design guidelines for better planning of model prediction.

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Design and Implement of REST API for Data Integration

Design and Implement of REST API for Data Integration

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International Conference on engineering and Emerging Technologies (ICEET)

作者： Mohd Kamir Yusof Mustafa Man Azli Ismail Faculty of Informatics & Computing Universiti Sultan Zainal Abidin Terengganu Besut Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus Malaysia Lieos SDN BHD Lot 37744 Tingkat 1 Wisma Dataran Rimba Square Terengganu Kuala Nerus Malaysia

ISBN: (纸本)9781665491075

Data integration is currently most important to organization to integrate data from different data sources using different platform or programming languages. A suitable approach is required to allow one system send the data to another system using standard data format. REST API is one approach can used for data integration using JSON format. Three processes are involved in this approach. There are extract data, send data, received and dump data. In this approach, SAP system will be sending the data in JSON to FEMS system. FEMS system will be exploded and dump the data into database FEMS. Based the experiment, the result indicates, REST API is successfully implemented by showing less response time and CPU usage during sending and receiving the data in JSON format.

关键词： Computer languages Databases Soft sensors Standards organizations Data integration Organizations Finite element analysis

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Optimizing droplet coalescence dynamics in microchannels: A comprehensive study using response surface methodology and machine learning algorithms

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Heliyon 2025年第1期11卷 e41510页

作者： Javadpour, Seyed Morteza Kadivar, Erfan Zarneh, Zienab Heidary Kadivar, Ebrahim Gheibi, Mohammad Department of Mechanical Engineering University of Gonabad Gonabad Iran Department of Physics Shiraz University of Technology Shiraz 71555-313 Iran Institute of Ship Technology Ocean Engineering and Transport Systems University of Duisburg-Essen Duisburg 47057 Germany Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Liberec 46117 Czech Republic Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic Faculty of Mechanical Engineering Tarbiat Modares University Tehran 141171-3116 Iran

Droplet coalescence in microchannels is a complex phenomenon influenced by various parameters such as droplet size, velocity, liquid surface tension, and droplet-droplet spacing. In this study, we thoroughly investigate the impact of these control parameters on droplet coalescence dynamics within a sudden expansion microchannel using two distinct numerical methods. Initially, we employ the boundary element method to solve the Brinkman integral equation, providing detailed insights into the underlying physics of droplet coalescence. Furthermore, we integrate Response Surface Methodology (RSM) to effectively optimize droplet coalescence dynamics, harnessing the power of machine learning algorithms. Our results showcase the efficacy of these computational techniques in enhancing experimental efficiency. Through rigorous evaluation utilizing Regression Coefficient and Mean Absolute Error metrics, we ascertain the accuracy of our estimations. Our findings highlight the significant influence of key parameters, specifically the non-dimensional initial distance of the droplets (D), viscosity ratio (μ), Capillary number (Ca), and width (w), as identified by the non-dimensional final droplet-droplet spacing (DD), velocity of the first droplet (V_FD), and velocity of the second droplet (V_BD), respectively. This comprehensive approach provides valuable insights into droplet coalescence phenomena and offers a robust framework for optimizing microfluidic systems. The most influential parameters on DD are the values of A_d and D, while viscosity has the lowest influence on DD. The most influential parameters on droplet velocity are viscosity and channel width, whereas the initial distance and Ca have the least influence on droplet velocity. The comparison of different machine learning algorithms indicates that the best ones for predicting DD, V_FD, and V_BD are function, SMOreg, Lazy-IBK, and Meta-Bagging, respectively. © 2025 The

关键词： Coalescence Droplet Machine learning Microchannel Optimization

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Fixed point results via β-admissibility in fuzzy extended rectangular b-metric spaces

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AIP Conference Proceedings 2024年第1期2895卷

作者： Koon Sang Wong Zabidin Salleh Ilyani Abdullah Department of Mathematics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

As the focus of this manuscript, the notions of fuzzy β -ψ-contraction within the scope of fuzzy extended rectangular b-metric space is introduced. New fixed point property from this contraction are discussed. An example is given for the illustration of the work presented. The obtained results improvise various pre-existing results.

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River quality classification using different distances in k-nearest neighbors algorithm

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Procedia Computer Science 2022年 204卷 180-186页

作者： Nurnadiah Zamri Mohammad Ammar Pairan Wan Nur Amira Wan Azman Siti Sabariah Abas Lazim Abdullah Syibrah Naim Zamali Tarmudi Miaomiao Gao Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Besut Terengganu Malaysia Management Science Research Group Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Terengganu Malaysia Management Science Research Group Computer and Information Sciences University of Strathclyde Glasgow United Kingdom Universiti Technology MARA Johor Branch Segamat Johor Malaysia Faculty of Biology Medicine and Health School of Medical Siences University of Manchester Manchester United Kingdom

The practice of river quality classification usually uses Water Quality Index (WQI) to evaluate the WQI values of the river. However, due to huge data collection on river pollution with uncertain water quality parameter values, need to a different approach to classify the river quality. One of the supervised classification algorithms known as K-Nearest Neighbors (KNN) seems to give new approach for river quality classification where each data points are classified according to the k number or the closest data points neighbors. Therefore, the purpose of this paper is to apply different distances and distance-weighted in KNN for finding the most accurate river quality classification. The accuracy results are compared with Support Vector Machine (SVM) and Decision Tree (DT) algorithms. This KNN algorithm will give a different approach in classify the river quality.

关键词： Supervised classification k-nearest neighbors (KNN) river quality classification accuracy

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