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Comparative analysis of various oxygen production techniques using multi-criteria decision-making methods

International Journal of Thermofluids 2023年 17卷

作者： Aljaghoub, Haya Alasad, Shamma Alashkar, Adnan AlMallahi, Maryam Hasan, Ranem Obaideen, Khaled Alami, Abdul Hai Department of Industrial Engineering and Engineering Management University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Department of Mechanical and Aerospace Engineering United Arab Emirates University Al Ain City United Arab Emirates Department of Sustainable and Renewable Energy Engineering University of Sharjah Sharjah United Arab Emirates Sustainable Energy and Power Systems Research Center RISE University of Sharjah Sharjah United Arab Emirates Center for Advanced Materials Research University of Sharjah Sharjah United Arab Emirates

The current pandemic has adversely affected oxygen production and supply chain, where oxygen treatment is essential for the emergency treatment protocol of patients infected by the virus. This work reports on various techniques of oxygen generation methods, as well as the challenges facing its production, storage, and transportation. Moreover, this study offers a comparative analysis of various oxygen production techniques using Multi-Criteria Decision-Making Methods (MCDM). Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), in addition to the weighting methodologies, Multiplicative Exponential Weighting (MEW) and Simple Additive Weighting (SAW) are chosen as tools to carry out the statistical analysis and rank the oxygen production methods. The ranking criteria includes cost, performance, environmental impact and safety. Moreover, this paper utilizes the Entropy Weight Method (EWM), Criteria Importance Through Inter-criteria Correlation (CRITIC) method, and the Stochastic Dominance (SD) method to distribute the criteria weights. The results show thar oxygen production using membrane technologies is the optimal technique based on all the provided tools and criteria. as it attained the maximum Entropy and Sd values of 0.548 through the TOPSIS method, and the highest CRITIC value through SAW and MEW methods which were 0.260 and 0.236, respectively. © 2022 The Author(s)

关键词： Stochastic systems

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A comprehensive review on natural convection in trapezoidal cavities with mono and hybrid nanofluids

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International Journal of Thermofluids 2025年 27卷

作者： Rashid, Farhan Lafta Alkhekany, Zainab Abdul Karim Eleiwi, Muhammad Asmail Bouabidi, Abdallah Ahmad, Shabbir Chibani, Atef Kezzar, Mohamed Kadhim, Saif Ali Askar, Ali Habeeb Hammoodi, Karrar A. Department of Petroleum Engineering College of EngineeringmUniversity of Kerbala Karbala56001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbala56001 Iraq Electromechanical Engineering Department College of Engineering University of Samarra Samarra Iraq University of Gabes Avenue of Omar Ib-Elkhattab Gabes Zrig6023 Tunisia Graduate Program of Ocean Engineering School of Engineering Universidade Federal do Rio Grande Italia Avenue km 8 Rio Grande96201-900 Brazil Institute of Geophysics and Geomatics China University of Geosciences Wuhan430074 China Research Center in Industrial Technologies CRTI P.O.Box 64 Algiers Cheraga16014 Algeria Department of Mechanical Engineering University of 20 Aout 1955 El Hadaiek Road B. O. 26 Skikda21000 Algeria Technology Department Faculty of Technology 20 Aout 1955 University of Skikda PO Box 26 Skikda21000 Algeria Mechanical Engineering Department University of Technology- Iraq Baghdad Iraq Department of Fluid and Heat Engineering University of Miskolc Miskolc Hungary Institute of Physics and Electrical Engineering University of Miskolc Miskolc Hungary College of Engineering University of Al Maarif Al Anbar Iraq

This review synthesises advancements in natural convection within trapezoidal cavities using mono- and hybrid nanofluids, emphasising their geometric advantages for thermal management. Trapezoidal cavities promote asymmetric flow patterns that enhance heat transfer compared to conventional geometries, as demonstrated in applications like solar absorbers and electronic cooling. Through analysis of 50+ previous studies, the review identifies key trends: Hybrid nanofluids like Cu-Al₂O₃/water consistently outperform mono nanofluids in Nusselt number improvement, with gains exceeding 20 %. Inclined walls mitigate stagnant flow zones, though exact reduction rates vary with aspect ratio and nanoparticle concentration. Magnetic fields and porous media further modulate thermal performance, but trade-offs emerge between conductivity enhancement and viscosity penalties. This review provides a framework to optimise trapezoidal cavities with nanofluids for industrial deployment. © 2025 The Author(s)

关键词： Natural convection

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Resistive-pulse sensing tumor-derived exosome detection device for resrouce-limited settings 21

Resistive-pulse sensing tumor-derived exosome detection devi...

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21st International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2017

作者： Carey, Thomas R. Yu, Connie W. Sohn, Lydia L. UC Berkeley-UCSF Graduate Program in Bioengineering United States UC Berkeley Bioengineering United States UC Berkeley Mechanical Engineering United States

ISBN: (纸本)9780692941836

We present the theory, design, and initial characterization of a tumor-derived exosome detection platform based on resistive-pulse sensing to enable cost-effective, point-of-care cancer screening. Our platform detects exosomes displaying a specific surface antigen by electronically measuring the effective size increase that occurs when exosomes bind to colloids functionalized with a specific antibody. We have demonstrated that our device can distinguish antibody-functionalized colloids from similar colloids incubated with SKBR3-derived exosomes. © 17CBMS-0001.

关键词： Colloids

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Multiplexed resistive-pulse sensing through coded node⇓pore channel geometry 24

Multiplexed resistive-pulse sensing through coded node⇓pore...

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24th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2020

作者： Cotner, Kristen L. Sohn, Lydia L. UC Berkeley - UCSF Graduate Program in Bioengineering Berkeley and San Francisco United States UC Berkeley Department of Mechanical Engineering Berkeley United States

ISBN: (纸本)9781733419017

Node-pore sensing (NPS) is a versatile label-free microfluidic platform to measure a variety of cell phenotypes. Yet the single-channel nature of NPS limits throughput and precludes integration with components such as cell sorting. Here we demonstrate a novel multichannel NPS design by encoding the channels with Barker and Gold codes to modulate the current pulse. Particle events are detected through matched-filter detection and successive interference cancellation (SIC), resolving overlapping signals in the same channel and across separate channels. © 2020 CBMS-0001

关键词： Matched filters

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Thickness, Annealing, and Surface Roughness Effect on Magnetic and Significant Properties of Co40Fe40B10Dy10 Thin Films

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Materials 2023年第17期16卷 5995页

作者： Liu, Wen-Jen Chang, Yung-Huang Chiang, Chia-Chin Chen, Yuan-Tsung Wang, Yu-Zhi Wu, Chueh-Lin Lin, Shih-Hung Ou, Sin-Liang Department of Materials Science and Engineering I-Shou University Kaohsiung84001 Taiwan Bachelor Program in Industrial Technology National Yunlin University of Science and Technology 123 University Road Section 3 Douliou64002 Taiwan Department of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Graduate School of Materials Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou64002 Taiwan Department of Electronic Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Douliou64002 Taiwan Bachelor Program for Design and Materials for Medical Equipment and Devices Da-Yeh University Changhua51591 Taiwan

In this study, Co40Fe40B10Dy10 thin films were deposited using a direct current (DC) magnetron sputtering technique. The films were deposited on glass substrates with thicknesses of 10, 20, 30, 40, and 50 nm, and heat-treated in a vacuum annealing furnace at 100, 200, and 300 °C. Various instruments were used to examine and analyze the effects of roughness on the magnetic, adhesive, and mechanical properties. From the low frequency alternating current magnetic susceptibility (χac) results, the optimum resonance frequency is 50 Hz, and the maximum χac value tends to increase with the increase in the thicknesses and annealing temperatures. The maximum χac value is 0.18 at a film thickness of 50 nm and an annealing temperature of 300 °C. From the four-point probe, it is found that the resistivity and sheet resistance values decrease with the increase in film deposition thicknesses and higher annealing temperatures. From the magnetic force microscopy (MFM), the stripe-like magnetic domain distribution is more obvious with the increase in annealing temperature. According to the contact angle data, at the same annealing temperature, the contact angle decreases as the thickness increases due to changes in surface morphology. The maximal surface energy value at 300 °C is 34.71 mJ/mm2. The transmittance decreases with increasing film thickness, while the absorption intensity is inversely proportional to the transmittance, implying that the thickness effect suppresses the photon signal. Smoother roughness has less domain pinning, more carrier conductivity, and less light scattering, resulting in superior magnetic, electrical, adhesive, and optical performance. © 2023 by the authors.

关键词： Thin films

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Pick and Place Robot Using Visual Feedback Control and Transfer Learning-Based CNN 17

Pick and Place Robot Using Visual Feedback Control and Trans...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Nagata, Fusaomi Miki, Kohei Otsuka, Akimasa Yoshida, Kazushi Watanabe, Keigo Habib, Maki K. Sanyo-Onoda City University Graduate School of Science Engineering Sanyo-Onoda Japan Okayama University Division of Industrial Innovation Sciences Graduate School of Natural Science and Technology Department of Intelligent Mechanical Systems Okayama Japan American University in Cairo School of Sciences Engineering Mechanical Engineering Department Cairo Egypt

ISBN: (纸本)9781728164151

Artificial neural network (ANN) which has four or more layers structure is called deep NN (DNN) and it is recognized as one of promising machine learning techniques. Convolutional neural network (CNN) is widely used and powerful structure for image recognition and/or defect inspection. It is also known that support vector machine (SVM) has a superior ability for binary classification in spite of only having two layers. The authors already have developed a CNN SVM design and training tool for defect detection of resin molded articles, while the effectiveness and the validity have been proved through several CNNs design, training and evaluation. The tool further enables to facilitate the design of a CNN model based on transfer learning concept. In this paper, a pick and place robot is introduced while implementing a visual feedback control and a transfer learning-based CNN. The visual feedback control enables to omit the complicated calibration between image and robot coordinate systems, also the transfer learning-based CNN allows the robot to estimate the orientation of target objects for dexterous picking operation. The usefulness and validity of the system is confirmed through pick and place experiments using a small articulated robot named DOBOT. © 2020 IEEE.

关键词： Convolutional neural networks

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Contribution of Virtual Reality Technology to Increase Student Interest in Vocational High Schools

Contribution of Virtual Reality Technology to Increase Stude...

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2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021

作者： Maulana, Fairuz Iqbal Pangestu, Gusti Sano, Albert Verasius Dian Purnomo, Agung Rahmadika, Sandi Widartha, Vandha Pradwiyasma Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia Graduate School Pknu Pukyong National University Interdisciplinary Program of Information Security Busan Korea Republic of Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia

ISBN: (纸本)9781665428477

This research investigates the feasibility of school-based learning using Virtual Reality technology in Electric Power Generation learning during the COVID-19 pandemic. This research employs a qualitative approach. Vocational High School Nurul Jadid Paiton Probolinggo is the site of this study. Data was gathered through observation, literature review, and interviews. In the Electrical engineering section, interviews were conducted with a teaching instructor. Triangulation was used to investigate the data's authenticity, in addition to further interviews with the curriculum staff and instructors at the school. The teacher's assessment of learning media using Virtual Reality application technology shows valid criteria with an average value of 3.6. In comparison, after using the Virtual Reality application learning media, the assessment of students obtained an average value of 3.77 compared to conventional assessments with an interval of 2.71. The use of Virtual Reality technology has proven that it can help and facilitate student learning. The use of technologies of Virtual Reality as a means of learning in classrooms will also be an alternate option for virtual laboratories during the COVID-19 pandemic. © 2021 IEEE.

关键词： Virtual reality

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Machine learning techniques in bank credit analysis of companies: A case study of a Brazilian bank 49

Machine learning techniques in bank credit analysis of compa...

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49th International Conference on Computers and industrial engineering, CIE 2019

作者： Assef, F.M. Steiner, M.T.A. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Brazil

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, not always did the best accuracy represent the best technique for the assessment of this problem. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study. © 2019, Computers and industrial engineering. All rights reserved.

关键词： Support vector machines

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An Approach to Semantic Interoperability for Product Development Through Automatic Requirement Extraction and Semantic Reconciliation 16th

An Approach to Semantic Interoperability for Product Develop...

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16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： Canciglieri, Matheus Beltrame de Moura Leite, Athon Francisco Curi Staben Szejka, Anderson Luis Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

The strong competitiveness challenges manufacturing industry to rationalize different ways of bringing new products to the market in the shortest time with competitive prices while ensuring higher quality. Industries need to effectively share product requirements, which comes from various sources and are heterogeneous in nature, during the Product Development Process (PDP) to stay competitive. However, problems with misinterpretation of such requirements have been identified during its sharing due to semantic interoperability obstacles related to the process of automatically gathering requirements and their translation and reuse. This research proposes an approach to automatically gather product requirements, extracting its knowledge and translate it for further use and reuse along PDP. The research structure consisted of firstly studying the current issues of the topic, secondly by exploring an approach, to be validated in an experimental case. Current issues point out to gaps related to the process of semantic reconciliation and knowledge extraction perspectives, giving it a multi-dimensional panorama where semantic issues are intertwined among different perspectives. The later solution presents an approach which considers raw information being processed into product features, refining knowledge during PDP and making it reusable in different cycles. The approach brings a new view on practical methods for automatically collect product requirements, extract its knowledge and translate it into product features, based on knowledge extraction methods and by using semantic reconciliation as means for translating product’s requirements. Further research will focus on expanding the approach and including more features to increasingly complex cases, to explore the full potential of the approach. © 2019, IFIP International Federation for Information Processing.

关键词： Product design

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Computer Vision with Cognitive Learning to Improve the Decision-Making During the Sales Process in Physical Stores 16th

Computer Vision with Cognitive Learning to Improve the Decis...

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16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： da Silva Ramalho, Vinícius Szejka, Anderson Luis Rudek, Marcelo Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

In a world where the information is obtained faster than ever seem, new methods to process that high volume of data are being developed frequently. This is more notorious in a virtual ambient where the data is generated in a manner that is faster and easier to analyze than in the real world. This is very evident in the retail field, where virtual stores have easy access to all the advertisement a user visited and simple to obtain user profile, on the other hand physical stores are limited to basically create a register in a database when there is a purchase. In an attempt to improve the retailers experience from physical stores to manage their business this document has the objective to develop a computational tool that will analyze the people flux going in the establishment, trying to inform the retailer the amount of people and their gender to help the sales process in physical stores. To this end, computational vision methods and algorithms were raised, which after selection, theoretical conception and tool’s implementation it was tested with benchmarks to operate locally and in real time by accessing the cameras installed strategically in a real scenario. Two scenarios were tested: static ambient light and dynamic light. Two tests were conducted: YOLOv2 against background subtraction-based counter;gender classification using full body features. Even though the results were not as positive as needed for commercial use, the tool demonstrated potential and space for improvements. © 2019, IFIP International Federation for Information Processing.

关键词： Computer vision

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