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Hemodynamics in renal arteries with partial coverage after endovascular aneurysm repair affected by renal orientations

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Medicine in Novel Technology and Devices 2023年第2期18卷 81-90页

作者： Jun Wen Xinhui Liu Jianguo Lei Jiarong Wang Xiyang Chen Tinghui Zheng Ding Yuan School of Computer Science and Technology Southwest University of Science and TechnologyMianyang621010China Institute of Civil Engineering and Architecture Southwest University of Science and TechnologyMianyang621010China Department of Vascular Surgery West China HospitalSichuan UniversityChengdu610041China Department of Applied Mechanics Sichuan UniversityChengdu610000China

Endovascular aortic repair(EVAR)has been increasingly used to treat abdominal aortic aneurysm(AAA)due to its lower mortality and shorter recovery ***,the complications caused by renal artery coverage remained a major *** this study,three types of renal orientation and five types of partial renal coverage degree were adopted to numerically investigate the flow pattern,wall shear stress distribution,and blood perfusion during a cardiac *** results show that as for the mild partial coverage(=<30%),the renal artery with a downward orientation suffered fewer unfavorable wall shear stress(WSS)distribution and more blood *** should be noted that the renal artery with horizontal orientation suffered more unfavorable WSS *** terms of severe coverage(≥50%),all of the renal arteries displayed highly disturbed wall shear distribution,resulting in a significant reduction in blood perfusion It was interesting to note that the artery with an upward orientation had a smaller rate of reduction in blood *** can be concluded that as for the mild renal coverage after EVAR,renal arteries with downward orientation may have the advantage of reducing the possibility of renal occlusion,while renal arteries with horizontal orientation may increase the unfavorable wall shear *** the other hand,as for serious coverage(≥50%),high risk of renal ischemia remains the main concern for all types of renal arteries due to highly disturbed wall shear distribution would significantly increase regardless of renal orientation.

关键词： Hemodynamics Orientation Follow-up Numerical simulation Renal artery

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Performance Evaluation of Laser-Induced Screen Printed Electrodes for Electrochemical Detection 9

Performance Evaluation of Laser-Induced Screen Printed Elect...

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9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Hisham, Balqis Nurnadia Badrol Ralib, Aliza Aini Md Nordin, Anis Nurashikin Haotung, Lun Rahim, Rosminazuin Ab Zain, Zainiharyati Mohd Iium Kuliyyah of Engineering Department of Electrical and Computer Engineering Kuala Lumpur Malaysia Jabil Circuit Sdn. Bhd Penang Malaysia University Teknologi Mara UiTM Faculty of Applied Science Selangor Malaysia

ISBN: (纸本)9798350343380

Screen printing is a well-known technique for producing disposable and low-cost screen-printed carbon electrode (SPCE) sensor. SPCE sensors have been used in many applications such as disease detection, toxin detection, disease monitoring for the environment, and food analysis. Despite its outstanding advantages, electrochemical-based SPCE sensors have relatively low sensitivity as compared to chromatography-based and fluorimetry-based conventional sensors. A modification by improving the electrode's materials may be implemented to produce an effective and sensitive SPCE sensor. Thus, in this study, a comparison of material between laser-induced graphene screen-printed electrode (LIG-SPE) and currently existing and widely used screen-printed carbon electrode (SPCE) is presented. Cyclic Voltammetry (CV) was conducted to compare the performance of the fabricated sensors for electrochemical detection and the R2 calibration curves were performed to determine the linearity. The results shows that LIG SPE has better linearity (R2 is 0.9596) compared to SPCE. © 2023 IEEE.

关键词： Graphene

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U-Net Implementation for High Throughput Grain Boundary Detection in Bright Field TEM Micrographs: Toward In Situ Grain Growth Studies

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1581-1582页

作者： Patrick, Matthew J. Eckstein, James K. Lopez, Javier Ma, Alan J. Toderas, Silvia Levine, Stacey Barmak, Katayun Department of Applied Physics and Applied Mathematics Columbia University New York NY USA Department of Physics University of Illinois -- Urbana-Champaign Champaign IL United States Department of Mechanical Engineering Columbia University New York NY USA Department of Mathematics Columbia University New York NY USA Department of Mathematics and Computer Science Duquesne University Pittsburgh PA United States

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Load Balancing in Cloud Computing based on Ant Colony Optimization and Crow Search Algorithm 27

Load Balancing in Cloud Computing based on Ant Colony Optimi...

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27th International Conference on Advanced Communications Technology, ICACT 2025

作者： Alsheavi, Amar N. Wang, Xingfu Zhao, Wei Hawbani, Ammar Alhusaini, Naji Ahmed, Ibrahim Abdulrab Ismail, A.S. School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230027 China School of Computer Science and Technology Anhui University of Technology Anhui China School of Computer Science Shenyang Aerospace University Shenyang110136 China School of Computer and Information Engineering Chuzhou University Anhui Chuzhou239000 China Computer Department Applied College Najran University Najran66462 Saudi Arabia College of Life Sciences and Oceanography Shenzhen University Shenzhen518060 China Faculty of Science Zagazig University Zagazig44519 Egypt

ISBN: (纸本)9791188428137

With the rapid increase in cloud services and the increasing shift toward them, balancing the cloud load has become a critical research issue. The increasing demand from customers for technology services worldwide is largely due to its direct impact on performance quality. Therefore, to provide better service quality, it is essential to consider reducing response time and cost in load balancing. This paper addresses the load-balancing problem by optimizing response time and computing cost in cloud computing systems. Specifically, we first formulated the load balancing problem in cloud computing mathematically by designing an objective function that optimizes response time and cost, including constraints to ensure task assignment to a single virtual machine (VM) and resource limits are not exceeded. To solve this optimization problem, we proposed a hybrid algorithm, ACOCSA, that combines Ant Colony Optimization (ACO) and Crow Search Algorithm (CSA). We implemented the ACOCSA algorithm, evaluated the response time, cost, and load balancing metrics, and found that our algorithm performed better in terms of response time and computational cost, and showed good fairness among VMs. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Ant colony optimization

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Energy Management Strategy with a Hybrid Renewable Energy System for a Standalone House

Energy Management Strategy with a Hybrid Renewable Energy Sy...

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International Conference on applied and Theoretical Electricity (ICATE)

作者： Laurentiu-Alex Mustaţă Gheorghe-Dan Sorea Elena Helerea Electrical Engineering and Applied Physics Department Electrical Engineering and Computer Science Faculty Transilvania University Brasov Romania

ISBN: (数字)9798350388107

ISBN: (纸本)9798350388114

In the case of standalone houses, ensuring a continuous and regulated power supply from renewable sources is crucial. To address their unpredictable nature, an environmentally conscious hybrid renewable energy system combining photovoltaic panels, a battery, and a Diesel generator is considered. A software application simulates the power flow in a standalone house with common AC loads, analysing summer and winter scenarios over 24 hours. The strategy employed provides an optimal energy management by using the Diesel generator only during peak demand when PV is available and to cover loads and maintain battery life when PV is not in operation. The simulation results provide valuable insights for designing such hybrid energy systems and for enhancing system responsiveness to dynamic energy demands.

关键词： Photovoltaic systems Renewable energy sources Costs Power system dynamics Generators Hybrid power systems Batteries Energy management Optimization Load flow

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Improving Communication Systems Through Federated Learning: An Optimization of Decision-Making 6

Improving Communication Systems Through Federated Learning: ...

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6th World Symposium on Communication engineering, WSCE 2023

作者： Stergiou, Konstantinos D. Ishibashi, Yutaka Goudos, Sotirios K. Lagkas, Thomas Sarigiannidis, Panagiotis Psannis, Konstantinos E. University of Macedonia Department of Applied Informatics Thessaloniki Greece Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan Aristotle University of Thessaloniki Department of Physics Thessaloniki Greece International Hellenic University Department of Computer Science Kavala Greece University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani Greece

ISBN: (纸本)9798350339505

This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems. © 2023 IEEE.

关键词： Learning systems

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Detection of Magnetite Rust Using Circular Microstrip Patch Antenna-based Chipless RFID Sensor

Detection of Magnetite Rust Using Circular Microstrip Patch ...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Nongpromma, Sirisak Janin, Suwan Kaemarungsi, Kamol Boonpoonga, Akkarat Chudpooti, Nonchanutt Bannawat, Lakkhana King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Rajamangala University of Technology Lanna Lampang Faculty of Engineering Department of Engineering and Technology Lampang52000 Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand Rajamangala University of Technology Rattanakosin Faculty of Engineering Department of Computer Engineering Nakhon Pathom Thailand

ISBN: (纸本)9798350332360

In this paper, detection of the magnetite rust is presented by using a chipless RFID sensor based on a circular microstrip patch antenna (CMPA). The sensor is designed at the resonant frequency of 4.89 GHz by using a single-layer PCB with its dielectric constant of 4.3. Simulations were conducted to verify that the designed sensor can detect the magnetite rust through shifted resonant frequency. In simulations, the sensor was mounted on the iron with its magnetite rust. The width and depth of iron rust were varied in order to investigate the effect of iron rust on the resonant frequency. Simulation results have been shown that the proposed chipless RFID sensor and RCS' can be utilized to detect the effect of the iron rust. © 2023 IEEE.

关键词： Microstrip antennas

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Improving Smart Agriculture Through the Use of Machine Learning to Offer Tailored Crop Forecasts

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Remote Sensing in Earth Systems sciences 2024年第1期8卷 74-83页

作者： Patil, R.N. Maroor, Jnaneshwar Pai Dhanke, Jyoti A. Chunduru, Madhava Rao Singh, Mangal Jangir, Pradeep Upadhyay, Shrikant Department of Mechanical Engineering Bharati Vidyapeeth’s College of Engineering Lavale Pune India Department of Business Administration Nitte Institute of Professional Education Nitte (Deemed to Be University) Karnataka Mangaluru India Department of Engineering Science (Mathematics) Bharati Vidyapeeth’s College of Engineering Lavale Pune India Department Of Computer Science And Engineering Koneru Lakshmaiah Educational Foundation Vaddeswaram AP Guntur District India Department of Electronics and Telecommunication Engg. Symbiosis Institute of Technology Pune Campus Symbiosis International (Deemed University) Pune India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India

It is not possible to identify crop illnesses by examining each disease independently. Users may only get forecasts for the most anticipated illnesses with the use of a robust analytic methodology. This study presents a method that can collect, analyze, and identify crop health information all on one platform using an IoT and machine learning-based approach. Food security and the provision of essential raw materials for several industries are both supported by agriculture, which is the most important and basic vocation. Improved crop yields, thanks to new innovative agricultural practices, mean less water wasted and more money in the bank. An intelligent irrigation system that uses a machine learning algorithm to forecast a crop’s water needs is the suggested model. One such rapidly evolving invention is the Internet of Things (IoT), which is now spreading its wings across all geographies. Technological innovation is reaching a new level of practicality in agriculture with the rise of embedded PCs like Arduino. Soil quality monitoring using Arduino, several sensors, and an Android app is shown and accomplished in this study. Temperature, soil moisture level, ammonia, and carbon content limit soil quality in this study. Arduino is used as both a worker and an information processing device, and it is in charge of sensor security. The terminal device is an Android phone. Producers may improve agricultural yields by collecting and analyzing data on weather, soil, seed, and yields of crops, moisture, and gusts of wind in specific areas. Furthermore, a flask-built GUI was used to present crop forecasts derived from a bespoke recommender system. Because of its adaptable design, the system may one day be able to discover the suggested items of other areas. This article uses targeted agricultural data to create five machine-learning approaches that are comparable to one another and to compare and contrast them. © The Author(s), under exclusive licence to Springer Nature Swit

关键词： Decision navigation systems Internet of Things (IoT) Irrigation systems Machine learning algorithms Sensors

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Data Analytics on Eco-Conditional Factors Affecting Speech Recognition Rate of Modern Interaction Systems

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Journal of Mobile Multimedia 2022年第4期18卷 1153-1176页

作者： Kaladevi, A.C. Saravanakumar, R. Veena, K. Muthukumaran, V. Thillaiarasu, N. Kumar, S. Satheesh Department of Computer Science and Engineering Sona College of Technology Salem India Department of CSE Dayananda Sagar Academy of Technology and Management Bangalore 560082 India Department of Computer Science J.K.K.Nataraja College of Arts & Science Namakkal Dt. Komarapalayam India Department of Mathematics School of Applied Sciences REVA University Karnataka Bengaluru India School of Computing and Information Technology REVA University Bengaluru India Department of Computer Science School of Applied Sciences REVA University Bengaluru India

Speech-based Interaction systems contribute to the growing class of contemporary interactive techniques (Human-computer Interactive system), which have emerged quickly in the last few years. Versatility, multi-channel synchronization, sensitivity, and timing are all notable characteristics of speech recognition. In addition, several variables influence the precision of voice interaction recognition. However, few researchers have done a significant study on the five eco-condition variables that tend to affect speech recognition rate (SRR): ambient noise, human noise, utterance speed, and frequency. The principal strategic goal of this research is to analyze the influence of the four variables mentioned earlier on SRR, and it includes many stages of experimentation on mixed noise speech data. The sparse representation-based analyzing technique is utilized to analyze the effects. Speech recognition is not noticeably affected by a person's usual speaking pace. As a result, high-frequency voice signals are more easily recognized (∼98.12%) than low-frequency speech signals in noisy environments. By performing the experiments, the test results may help design the distributive controlling and commanding systems. © 2022 River Publishers.

关键词： ambient noise eco-conditional factors frequency human noise Interaction system recognition rate utterance speed

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SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction

arXiv

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arXiv 2023年

作者： Jayakumar, Nivetha Hossain, Tonmoy Zhang, Miaomiao Department of Electrical and Computer Engineering United States Department of Computer Science School of Engineering and Applied Science University of Virginia VA United States

3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achieved impressive performance in this area, existing deep networks often fail to effectively utilize the shape structures of objects presented in images. As a result, the topology of reconstructed objects may not be well preserved, leading to the presence of artifacts such as discontinuities, holes, or mismatched connections between different parts. In this paper, we propose a shape-aware network based on diffusion models for 3D image reconstruction, named SADIR, to address these issues. In contrast to previous methods that primarily rely on spatial correlations of image intensities for 3D reconstruction, our model leverages shape priors learned from the training data to guide the reconstruction process. To achieve this, we develop a joint learning network that simultaneously learns a mean shape under deformation models. Each reconstructed image is then considered as a deformed variant of the mean shape. We validate our model, SADIR, on both brain and cardiac magnetic resonance images (MRIs). Experimental results show that our method outperforms the baselines with lower reconstruction error and better preservation of the shape structure of objects within the images. © 2023, CC BY.

关键词： Image reconstruction

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