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Thermal conductivity and rheological behavior of silica / simulated body fluid - Dispersed Hardystonite and Åkermanite nanofluids: X-ray diffraction to analyze structure and morphology of a bio-ceramic

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International Communications in Heat and Mass Transfer 2025年 165卷

作者： Liu, Shulong Saidani, Taoufik Feng, Dulong Alawi, Mohammed Jameel Hussien, Mohamed Deebani, Wejdan Anhui Province Key Laboratory of Intelligent Computing and Applications Huaibei Normal University Huaibei235000 China Anhui Province Industrial Generic Technology Research Center for Alumics Materials Huaibei Normal University Huaibei235000 China School of Physics and Electronic Information Huaibei Normal University Huaibei235000 China Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Anhui Guangbo Mechanical Electronic Manufacturing Co. Ltd. Huaibei235000 China Electrical Engineering Department College of Engineering and Architecture Umm Al-Qura University Makkah Saudi Arabia Department of Chemistry Faculty of Science King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia Department of Mathematics College of Science & Arts King Abdul Aziz University Rabigh21911 Saudi Arabia

Bioceramics are integral in biomedical applications due to their biocompatibility, bioactivity, and mechanical properties. This study compares the thermal and rheological behavior of two hybrid bio-nanofluids (bi-ns): Hardystonite/Silica and Åkermanite/Silica dispersed in simulated body fluid (SBF). Nanoparticle morphology and composition were analyzed using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM), confirming the crystalline phases of both composites. Åkermanite/Silica showed better dispersion stability, with a higher zeta potential (−16.19 mV) than Hardystonite/Silica (−7.23 mV). The addition of silica (SiO2) improved stability for both, with zeta potential increases of ∼203 % and 69 %, respectively. Thermal conductivity of both nanofluids increased with temperature and volume fraction, with Åkermanite/Silica achieving a maximum enhancement of 13.16 % (20–40 °C). However, both showed negative thermal conductivity enhancements compared to SBF, especially at higher concentrations. Hardystonite/Silica demonstrated greater thermal compatibility with SBF. Rheologically, both nanofluids exhibited shear-thinning behavior. Hardystonite/Silica showed a stronger reduction in viscosity with temperature increase—up to 43.43 % at 0.25 % volume fraction—compared to 32.74 % for Åkermanite/Silica. These results highlight the interaction between thermal and flow properties in bi-ns, indicating that Hardystonite/Silica may be better suited for applications requiring thermal compatibility and viscosity control. The findings contribute to the optimization of hybrid nanofluids for bone-related biomedical applications. © 2025 Elsevier Ltd

关键词： Medical nanotechnology

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Improving Student Engagement and Performance in computing Final Year Projects

Improving Student Engagement and Performance in Computing Fi...

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Usman Naeem Syed Islam Arish Siddiqui School of Electronic Engineering & Computer Science Queen Mary University of London London UK Department of Computer Science University College London London UK School of Architecture Computing and Engineering University of East London London UK

ISBN: (数字)9781728126654

ISBN: (纸本)9781728126661

There has been a seismic shift in the UK higher education landscape during the last decade. This has been driven by the formation of the Office for Students (OfS) and the introduction of the Teaching Excellence Framework (TEF), where the emphasis has been on programmes offering students higher value when it comes to employability, retention and overall student experience. One of the critical challenges that impacts student experience is being able to enhance student engagement within a learning environment. Final year individual projects, which are generally unstructured in nature, is a significant contributor to programmes of study, yet remains an area where this problem is exacerbated. In an attempt to address this issue, our earlier work lays the foundation for a teaching & learning framework covering computing final year projects. In this paper, we present an extension to the framework and its implementation in 2016/17 following its first trial run within a Computer Science department at a UK university in 2015/16. We discuss the two implementations in practice and provide operational guidance. A large-scale longitudinal empirical study considering the performance of 625 final year undergraduate students over a period of five years is presented to ascertain the effectiveness of the framework. The study finds a consistent and significant positive impact on both student performance and engagement as a result of the original framework and further gains from the enhancements.

关键词： Education Collaboration Monitoring Tools Computer science Lenses Proposals

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Flow Simulations of Modified Diffuser Augmented Wind Turbine

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IOP Conference Series: Materials Science and engineering 2020年第1期886卷

作者： Saravana Kannan Thangavelu Timothy Goh Leong Wan C Piraiarasi Faculty of Engineering Computing and Science Swinburne University of Technology 93300 Kuching Sarawak Malaysia Department of Architecture Thiagarajar College of Engineering Madurai 625 015 Tamilnadu India

In order for wind technology to compete with conventional sources of energy, in terms of energy production costs, researchers are working on different ways to increase the energy density in wind. Development of wind power augmentation system is one of the most promising concepts in this field. The main objective of this research is to propose a new diffuser design for Diffuser Augmented Wind Turbine (DAWT) by introducing air vents and vortex generators. This study also investigates the effect of wind velocity and air pressure on the proposed modified diffuser to develop a suitable diffuser for DAWT. The purpose of this modified diffuser is to create a low-pressure region in the centre of the diffuser to increase the inlet mass flow rate. Three modified designs were developed and were simulated using CFD techniques. Results showed an outstanding increment in wind speed, which is 8.56 m/s (2.14 times increment), over the 4 m/s initial wind speed in a modified diffuser (Model 3 Air vents with splitter). This modified diffuser is based on the parameters: rotor diameter (D) = 500 mm, diffuser length (L) = 1000 mm, diffuser open-angle (θ) = 12º, flange size = 221.73 mm and inner splitter with 14º open-angle (α).

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Functional connectivity evaluation for infant eeg signals based on artificial neural network

Functional connectivity evaluation for infant eeg signals ba...

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作者： Sharif, Mhd Saeed Naeem, Usman Islam, Syed Karami, Amin School of Architecture Computing and Engineering College of Arts Technology and Innovation UEL University Way Dockland Campus LondonE16 2RD United Kingdom

. The employment of the brain signals electroencephalography (EEG) could supply a deep intuitive understanding for infants behaviour and their alertness level within the living environment. The study of human brain through a computer-based approach has increased significantly as it aims at the understanding of infants’ mind and measures their attention towards the surrounding activities. The artificial neural network achieved a significant level of success in different fields, such as pattern classification, decision making, prediction, and adaptive control by learning from a set of data and construct weight matrices to represent the learning patterns. This research study proposes an artificial neural network based approach to predict the rightward asymmetry or leftward asymmetry which reflects higher frontal functional connectivity in the frontal right and frontal left, respectively within infant’s brain. In the traditional methods, the value of asymmetry of the frontal (FA) functional connectivity is used to determine the rightward or the leftward asymmetry while the proposed approach is trying to predict that without going through all the levels of the calculation complexity. The achieved work will supply a deep understanding into the deployment of the functional connectivity to provide information on the interactions between different brain regions. © Springer Nature Switzerland AG 2019.

关键词： Neural networks

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Efficiently Inferring Top-k Elephant Flows based on Discrete Tensor Completion

Efficiently Inferring Top-k Elephant Flows based on Discrete...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Kun Xie Jiazheng Tian Xin Wang Gaogang Xie Jigang Wen Dafang Zhang College of Computer Science and Electronics Engineering Hunan University Changsha China Department of Electrical and Computer Engineering State University of New York at Stony Brook USA State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences

Finding top- k elephant flows is a critical task in network measurement, with applications such as congestion control, anomaly detection, and traffic engineering. Traditional top- k flow detection problem focuses on using a small amount of memory to measure the total number of packets or bytes of each flow. Instead, we study a challenging problem of inferring the top- k elephant flows in a practical system with incomplete measurement data as a result of sub-sampling for scalability or data missing. The recent study shows it is promising to more accurately interpolate the missing data with a 3-D tensor compared to that based on a 2-D matrix. Taking full advantage of the multilinear structures, we apply tensor completion to first recover the missing data and then find the top- k elephant flows. To reduce the computational overhead, we propose a novel discrete tensor completion model which uses binary codes to represent the factor matrices. Based on the model, we further propose three novel techniques to speed up the whole top- k flow inference process: a discrete optimization algorithm to train the binary factor matrices, bit operations to facilitate quick missing data inference, and simplifying the finding of top- k elephant flows with binary code partition. In our discrete tensor completion model, only one bit is needed to represent the entry in the factor matrices instead of a real value (32 bits) needed in traditional tensor completion model, thus the storage cost is reduced significantly. Extensive experiments using two real traces demonstrate that compared with the state of art tensor completion algorithms, our discrete tensor completion algorithm can achieve similar data inference accuracy using significantly smaller time and storage space.

关键词： Inference algorithms Binary codes Data models Partitioning algorithms Indexes Computational modeling

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Online Internet Anomaly Detection With High Accuracy: A Fast Tensor Factorization Solution

Online Internet Anomaly Detection With High Accuracy: A Fast...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Xiaocan Li Kun Xie Xin Wang Gaogang Xie Jigang Wen Guangxing Zhang Zheng Qin Department of Electrical and Computer Engineering State University of New York at Stony Brook USA College of Computer Science and Electronics Engineering Hunan University Changsha China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences

Traffic anomaly detection is critical for advanced Internet management. Existing detection algorithms usually work off-line and cannot timely detect anomalies. They also suffer from high cost for storage and computation. Although online and accurate traffic anomaly detection is very important, it very difficult to achieve. We propose to utilize tensor model to well exploit the multi-dimensional information hidden in the traffic data for more accurate online Internet anomaly detection. We decouple the tensor recovery problem to iteratively solve two sub problems, a tensor factorization sub-problem and an anomaly detection sub-problem. To reduce the high cost for computation and storage involved in tensor factorization, we propose two lightweight techniques to effectively derive factor matrices of tensor in the current window and iteration, taking advantage of tensor decomposition results of the previous window and iteration. We have done extensive experiments using two real traffic traces to compare with three tensor based algorithms and three matrix based algorithms. The experiment results demonstrate that our online anomaly detection algorithm can achieve the same anomaly detection accuracy as that of the best offline tensor based algorithm, but at 6100 times faster speed and with very low storage cost.

关键词： Anomaly detection Monitoring Matrix decomposition Microsoft Windows Principal component analysis Data models

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Train the Neural Network by Abstract Images

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Journal of Physics: Conference Series 2021年第2期1952卷

作者： Liqun Yang Yan Liu Wei Zeng Yijun Yang School of Information Science and Computing Florida International University Miami United States College of Civil Engineering and Architecture Qingdao Agricultural University Qingdao China School of Mathematics and Statistics Xi'an Jiaotong University Xi'an China School of Computer Science and Technology Xi'an Jiaotong University Xi'an China

Like the textbook for students' learning, the training data plays a significant role in the network's training. In most cases, people intend to use big-data to train the network, which leads to two problems. Firstly, the knowledge learned by the network is out of control. Secondly, the space occupation of big-data is huge. In this paper, we use the concepts-based knowledge visualization [33] to visualize the knowledge learned by the model. Based on the observation results and information theory, we make three conjectures about the key information provided by the dataset. Finally, we use experiments to prove that the artificial abstracted data can be used in networks' training, which can solve the problem mentioned above. The experiment is designed based on Mask-RCNN, which is used to detect and classify three typical human poses on the construction site.

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Building resilience for long duration space flight: A multiple project study across multiple discipline areas with primary hosts as architecture and industrial design tertiary programs in USA and Australia 69

Building resilience for long duration space flight: A multip...

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69th International Astronautical Congress: #InvolvingEveryone, IAC 2018

作者： Alexander, Sasha Bannova, Olga Kwon, EunSook Academic Program Industrial Design School of Computing Engineering and Mathematics Western Sydney University ParramattaNSW Australia Cullen School of Engineering Sasakawa International Center for Space Architecture University of Houston HoustonTX United States Industrial Design Program Gerald D Hines College of Architecture and Design University of Houston HoustonTX United States

International cooperation on space flight project development starts on earth by way of professional introductions between prospective host organizations and collaborators with major and minor actors. Complex prior projects provide insights and the ongoing foundational knowledge from which new innovations can launch and new ideas can come from both seasoned researchers, and commercial partnerships (NASA, SpaceX), but also fresh minds as the knowledge sets are brought together and interact to form new innovative perspectives. Universities as research test-beds for capturing the imaginations of new professional generations are an exciting environment to focus discipline skills and recalibrate career ambitions and trajectories. Space exploration exemplars as the International Space Station (ISS) provides an example of an enabling platform where cooperative relations in developing, constructing human habitation systems provide evidence that national and international collaborations are core to the development of future missions and lunar habitation. Future long-duration spaceflight and exploration missions will require from the crew to perform at their maximum capacity. Habitation architecture and spacecraft design must respect habitability needs including health, functional and safety requirements, which should be addressed at every stage of the design process: â€œconsidering people to be more than an 'element' of the system but its modifier and innovatorâ€¥ (Haeuplik-Meusburger S., Bannova O., 2016). This paper presents the results of a cross disciplinary approach to habitation system development for long-duration missions (LDMs) in relation to crew health systems;and alternate activities for managing stress triggers in confined environments and explored via a project-oriented strategy. Students from involved universities and programs have advanced their design for space interactions through identifying and acquiring information and knowledge, analysing it, and synthe

关键词： Product design

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Application of Cognitive Changes Markers for Diagnostics’ Purposes and in Neurofeedback Therapy

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IFAC-PapersOnLine 2019年第27期52卷 520-523页

作者： Magda Zolubak Mariusz Pelc Michal Podpora Wojciech Chlewicki Katarzyna Cichon Aleksandra Kawala-Sterniuk Opole University of Technology - Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland West Pomeranian University of Technology in Szczecin - Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland University of Greenwich - Department of Computing and Information Systems - Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK

Thanks to the automation of diagnostic processes based on the EEG signal and the creation of classifications of various attention disorders based on the analysis of the EEG signals (as diagnostic markers) - it may be possible to refer patients to appropriate specialists and provide them with appropriate neurofeedback-based treatment. The marker method proposed by the authors of the hereof paper is based on analysis of the EEG, which signal can be widely use in screening diagnostics. The proposed solution in this work may be used for neurofeedback or Brain Computer Interfaces (BCI). In this paper the authors presented implementation of markers for the purpose of analysis of some memory disorders and short-time attention disorder. The study is still in progress. Presented results have initial-study character.

关键词： EEG neurofeedback BCI algoritms

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Behavioural Approach to Network Anomaly Detection for Resource-Constrained System – Presentation of the Novel Solution – Preliminary Study

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IFAC-PapersOnLine 2019年第27期52卷 121-126页

作者： Mariusz Pelc Dawid Galus Magda Zolubak Stepan Ozana Wojciech Chlewicki Katarzyna Cichon Michal Podpora Aleksandra Kawala-Sterniuk Opole University of Technology – Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland University of Greenwich – Department of Computing and Information Systems – Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK VSB – Technical University Ostrava – FEECS Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic West Pomeranian University of Technology in Szczecin – Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland

In this paper some preliminary results of network anomaly detection for resource-constrained systems have been presented. All described algorithms are embedded into a three-tier system application. The presented solution is a response to nowadays trends in computer/network security domain that indicate gradual shifting from signature-based anomaly detection typically based on some selected statistical measures toward systems that are based on behavioural analysis of computer systems and/or networks. The presented system requirements, explain relevant terminology as well as we include some selected results and their analysis. The solution is potentially destined for very resource-constrained systems (IoT specifically), all tests were carried out in an example network to additionally analyse their effect of the presented approach on the computer resources.

关键词： Network Anomaly Detection Behavioural Analysis Internet of Things

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