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International Conference on Computing and Networking Technology (ICCNT)

作者： Agus Pratondo Astri Novianty Budi Laksono Putro Siska Komala Sari Department of Multimedia Engineering School of Applied Sciences Telkom University Bandung Indonesia Department of Computer Engineering School of Electrical Engineering Telkom University Bandung Indonesia Department of Computer Science Education Indonesia University of Education Bandung Indonesia Diploma Program of Information System School of Applied System Telkom University Bandung Indonesia

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice.

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Kinetic Monte Carlo Simulations of Sodium Ion Transport in NaSICON Electrodes

arXiv

引用

arXiv 2023年

作者： Wang, Ziliang Mishra, Tara P. Xie, Weihang Deng, Zeyu Gautam, Gopalakrishnan Sai Cheetham, Anthony K. Canepa, Pieremanuele Department of Materials Science and Engineering National University of Singapore 9 Engineering Drive 1 117575 Singapore Department of Materials Engineering Indian Institute of Science Karnataka Bengaluru560012 India Singapore-MIT Alliance for Research and Technology 1 CREATE Way 10-01 CREATE Tower Singapore138602 Singapore Materials Department and Materials Research Laboratory University of California Santa BarbaraCA93106 United States Department of Electrical & Computer Engineering University of Houston HoustonTX77204 United States

The development of high-performance sodium (Na) ion batteries requires improved electrode materials. The energy and power densities of Na superionic conductor (NaSICON) electrode materials are promising for large-scale energy storage applications. However, several practical issues limit the full utilization of the theoretical energy densities of NaSICON electrodes. A pressing challenge lies in the limited sodium extraction in low Na content NaSICONs, e.g., Na1VIVVIV(PO4)3 ↔ VVVIV(PO4)3 + 1e− + 1Na+. Hence, it is important to quantify the Na-ion mobility in a broad range of NaSICON electrodes. Using a kinetic Monte Carlo approach bearing the accuracy of first-principles calculations, we elucidate the variability of Na-ion transport vs. Na content in three important NaSICON electrodes, NaxTi2(PO4)3, NaxV2(PO4)3, and NaxCr2(PO4)3. Our study suggests that Na+ transport in NaSICON electrodes is almost entirely determined by the local electrostatic and chemical environment set by the transition metal and the polyanionic scaffold. The competition with the ordering-disordering phenomena of Na-vacancies also plays a role in influencing Na-transport. We identify the Na content providing the highest room-temperature diffusivities in these electrodes, i.e., Na2.7Ti2(PO4)3, Na2.9V2(PO4)3, and Na2.6Cr2(PO4)3. We link the variations in the Na+ kinetic properties by analyzing the competition of ligand field stabilization transition metal ions and their ionic radii. We interpret the limited Na-extraction at x = 1 observed experimentally by gaining insights into the local Na-vacancy interplay. We propose that targeted chemical substitutions of transition metals disrupting local charge arrangements will be critical to reducing the occurrence of strong Na+-vacancy orderings at low Na concentrations, thus, expanding the accessible capacities of these electrode materials. Copyright © 2023, The Authors. All rights reserved.

关键词： Metal ions

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Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Deep Learning Technologies

Enhancing Acute Ischemic Stroke Diagnosis Using IoMT and Dee...

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Telecommunications Conference (ITC-Egypt), International

作者： Mohamed M. El-Sheikh Aya Bayoumy Nada M. Ahmed Amany Mohamed Eldeeb Fatma I. Rabea Amira A. Nawar Mohamed G. Khattap Hend Galal Eldeen Mohamed Ali Hassan Mariam Mostafa Nayra Ibrahim Reem Ramadan Yomna Refaat Mennatallah Khaled Ali Maher Mohamed Abd Elaziz Ahmed Gamal Abdellatif Ibrahim Radiology and Medical Imaging Faculty of Applied Health Sciences Galala University Suez Egypt Biomedical Informatics Faculty of Computer Science and Engineering Galala University Suez Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez Egypt Department of Electronics and Electrical Communications Engineering Air Defense College Alexandria Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique utilizes EfficientNet, a deep learning model, designed to extract features from MRI images thereby enhancing the detection of acute ischemic infarctions. The performance of EfficientNet is compared against two other models, CNN and MobileNet, demonstrating its superior efficacy through metrics such as accuracy, precision, recall, and F1-score, which stand at 92.31%, 92.28%, 92.33%, and 92.30%, respectively.

关键词： Deep learning Accuracy Magnetic resonance imaging Soft sensors Medical services Feature extraction Regulation

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Retracted: Effect of Types and Gap on Spark Plugs on Exhaust Emissions on the 110CC Double Wheel Vehicles and Its Dissemination Using Website

Retracted: Effect of Types and Gap on Spark Plugs on Exhaust...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Ginting, Tinus Manurung, Hotler Harahap, Astro Julida Ongko, Erianto Hartono, H. Abdullah, Dahlan Erliana, Cut Ita Saddhono, Kundharu Sriadhi, S. Supriyono, S. Iskandar, Akbar Saleh, A.A. Sudarsana, I. Ketut Department of Mechanical Engineering Akademi Teknologi Industri Immanuel Indonesia Department of Informatics Akademi Teknologi Industri Immanuel Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Religious Education Institut Hindu Dharma Negeri Denpasar Denpasar Indonesia

Based on the formulation of the problem to be discussed by the writer is to know: the influence of 0.4 mm spark gap variation, and standard spark plug type, to CO and HC, the influence of 0.5 mm spark plug gap variation, and variation of platinum spark plug on CO and HC, influence of spark gap variation 0,6mm, and variation of iridium spark plug type to CO and HC emission Method used to obtain data needed to support the writer that is research method with experiment, literature study method or literature study The result of this research concludes that there is spark gap influence 0.4 mm, with variations of standard plug, platinum and iridium spark plugs against CO and HC emissions, where the lowest CO value is 0.27% and HC 98 ppm, 0.5 mm spark plug with lowest CO 0.15% and HC 46 ppm, 0.6 mm spark plug gap the lowest CO value of 0.19% and HC 24 ppm. The results of this research will be disseminated using the website. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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Cross-plane thermal conductivity of (Ti,W)N/(Al,Sc)N metal/semiconductor superlattices

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Physical Review B 2016年第4期93卷 045311-045311页

作者： Bivas Saha Yee Rui Koh Jonathan Comparan Sridhar Sadasivam Jeremy L. Schroeder Magnus Garbrecht Amr Mohammed Jens Birch Timothy Fisher Ali Shakouri Timothy D. Sands School of Materials Engineering Purdue University West Lafayette Indiana 47907 USA Birck Nanotechnology Center Purdue University West Lafayette Indiana 47907 USA School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47907 USA School of Mechanical Engineering Purdue University West Lafayette Indiana 47907 USA Thin Film Physics Division Department of Physics Chemistry and Biology (IFM) Linköping University SE-581 83 Linköping Sweden Bradley Department of Electrical and Computer Engineering and Department of Materials Science and Engineering Virginia Tech Blacksburg Virginia 24061 USA

Reduction of cross-plane thermal conductivity and understanding of the mechanisms of heat transport in nanostructured metal/semiconductor superlattices are crucial for their potential applications in thermoelectric and thermionic energy conversion devices, thermal management systems, and thermal barrier coatings. We have developed epitaxial (Ti,W)N/(Al,Sc)N metal/semiconductor superlattices with periodicity ranging from 1 nm to 240 nm that show significantly lower thermal conductivity compared to the parent TiN/(Al,Sc)N superlattice system. The (Ti,W)N/(Al,Sc)N superlattices grow with [001] orientation on the MgO(001) substrates with well-defined coherent layers and are nominally single crystalline with low densities of extended defects. Cross-plane thermal conductivity (measured by time-domain thermoreflectance) decreases with an increase in the superlattice interface density in a manner that is consistent with incoherent phonon boundary scattering. Thermal conductivity values saturate at 1.7Wm−1K−1 for short superlattice periods possibly due to a delicate balance between long-wavelength coherent phonon modes and incoherent phonon scattering from heavy tungsten atomic sites and superlattice interfaces. First-principles density functional perturbation theory based calculations are performed to model the vibrational spectrum of the individual component materials, and transport models are used to explain the interface thermal conductance across the (Ti,W)N/(Al,Sc)N interfaces as a function of periodicity. The long-wavelength coherent phonon modes are expected to play a dominant role in the thermal transport properties of the short-period superlattices. Our analysis of the thermal transport properties of (Ti,W)N/(Al,Sc)N metal/semiconductor superlattices addresses fundamental questions about heat transport in multilayer materials.

关键词： Phonon Heat transport transport properties Transportation models Interfaces Thermal Conductivity extended defects Thermal barrier coatings superlattices Interface

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Distributed feedback laser biosensor incorporating a titanium dioxide nanorod surface

Distributed feedback laser biosensor incorporating a titaniu...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Chun Ge Meng Lu Wei Zhang Brian T. Cunningham Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA Department of Materials Science and Engineering University of Illinois Urbana-Champaign Urbana IL USA Department of Bioengineering University of Illinois Urbana-Champaign Urbana IL USA

A 6.6× enhancement in surface sensitivity of DFB laser biosensors is demonstrated by a device incorporating a porous titanium dioxide nanorod layer on the sensor surface, while a Q-factor of over 25, 000 is maint... 详细信息

ISBN: (纸本)9781557528896

关键词： Distributed feedback devices Laser feedback Biosensors Titanium Surface emitting lasers Optical surface waves Vertical cavity surface emitting lasers Optical sensors Optical feedback Optical films

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Long-range transport of 2D excitons in dynamic acoustic lattice

arXiv

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arXiv 2021年

作者： Peng, Ruoming Ripin, Adina Ye, Yusen Zhu, Jiayi Wu, Changming Lee, Seokhyeong Li, Huan Taniguchi, Takashi Watanabe, Kenji Cao, Ting Xu, Xiaodong Li, Mo Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Department of Physics University of Washington SeattleWA98195 United States Department of Material Science and Engineering University of Washington SeattleWA98195 United States Research Center for Functional Materials National Institute for Materials Science Tsukuba Japan

Excitons are elementary optical excitation in semiconductors. The ability to manipulate and transport these quasiparticles would enable excitonic circuits and devices for quantum photonic technologies. Recently, interlayer excitons in 2D semiconductors have emerged as a promising candidate for engineering excitonic devices due to long lifetime, large exciton binding energy, and gate tunability. However, the charge-neutral nature of the excitons leads to a weak response to the in-plane electric field and thus inhibits transport beyond the diffusion length. Here, we demonstrate the directional transport of interlayer excitons in bilayer WSe2 driven by the dynamic potential lattice induced by surface acoustic waves (SAW). We show that at 100 K, the SAW-driven excitonic transport is activated above a threshold acoustic power and reaches a distance at least ten times longer than the diffusion length, only limited by the device size. Temperature-dependent measurement reveals the transition from the diffusion-limited regime at low temperature to an acoustic field-driven regime at elevated temperature. Our work shows that acoustic waves are an effective, contact-free means to control exciton dynamics and transport, promising for realizing 2D materials-based excitonic devices such as exciton transistors, switches, and transducers. © 2021, CC BY.

关键词： Acoustic surface wave devices

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Strain-driven disproportionation at a correlated oxide metal-insulator transition

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Physical Review B 2020年第12期101卷 121105(R)-121105(R)页

作者： T. H. Kim T. R. Paudel R. J. Green K. Song H.-S. Lee S.-Y. Choi J. Irwin B. Noesges L. J. Brillson M. S. Rzchowski G. A. Sawatzky E. Y. Tsymbal C. B. Eom Department of Materials Science and Engineering University of Wisconsin–Madison Madison Wisconsin 53706 USA Department of Physics and Astronomy and Nebraska Center for Materials and Nanoscience University of Nebraska Lincoln Nebraska 68588 USA Quantum Matter Institute Department of Physics and Astronomy University of British Columbia Vancouver British Columbia Canada V6T 1Z4 Department of Physics and Engineering Physics University of Saskatchewan Saskatoon Saskatchewan Canada S7N 5E2 Materials Modeling and Characterization Department Korea Institute of Materials Science Changwon 51508 Republic of Korea Department of Materials Science and Engineering Pohang University of Science and Technology Pohang 37673 Republic of Korea Department of Physics University of Wisconsin–Madison Madison Wisconsin 53706 USA Departments of Physics and Electrical & Computer Engineering The Ohio State University Columbus Ohio 43210 USA

Metal-to-insulator phase transitions in complex oxide thin films are exciting phenomena which may be useful for device applications, but in many cases the physical mechanism responsible for the transition is not fully understood. Here we demonstrate that epitaxial strain generates local disproportionation of the NiO6 octahedra, driven through changes in the oxygen stoichiometry, and that this directly modifies the metal-to-insulator phase transition in epitaxial (001) NdNiO3 thin films. Theoretically, we predict that the Ni-O-Ni bond angle decreases, while octahedral tilt and local disproportionation of the NiO6 octahedra increases resulting in a small band gap in an otherwise metallic system. This is driven by an increase in oxygen vacancy concentration in the rare-earth nickelates with increasing in-plane biaxial tensile strain. Experimentally, we find an increase in pseudocubic unit-cell volume and resistivity with increasing biaxial tensile strain, corroborating our theoretical predictions. With electron-energy-loss spectroscopy and x-ray absorption, we find a reduction of the Ni valence with increasing tensile strain. These results indicate that epitaxial strain modifies the oxygen stoichiometry of rare-earth perovskite thin films and through this mechanism affects the metal-to-insulator phase transition in these compounds.

关键词： Metal-insulator transition Vacancies Oxides Strongly correlated systems Thin films Epitaxy

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Ocelot: A wireless sensor network and computing engine with commodity palmtop computers

Ocelot: A wireless sensor network and computing engine with ...

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International Green Computing Conference

作者： Haifeng Xu Melissa M. Bilec Laura A. Schaefer Amy E. Landis Alex K. Jones Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA USA Department of Civil and Environmental Engineering University of Pittsburgh Pittsburgh PA USA Department of Mechanical Engineering and Materials Science University of Pittsburgh Pittsburgh PA USA School of Sustainable Engineering and the Built Environment Arizona State University Tempe AZ USA

ISBN: (纸本)9781479906215

The embedded class processors found in commodity palmtop computers continue to become increasingly capable while retaining an energy-efficient footprint. Palmtop computers themselves, including smartphones and tablets, provide a small form factor system integrating wireless communication and non-volatile storage with these energy-efficient processors. In this paper, we present Ocelot, a grid-like computing environment that leverages palmtop computers in place of traditional workstation or server class machines to compute highly parallel light to medium-weight tasks in an energy efficient manner. Ocelot is motivated to be used in a wireless sensor network environment where palmtop computers with onboard or attached sensors form nodes to obtain and process sensor data. Using a centralized server/dashboard, data processing jobs and managed and distributed to these palmtop computers to compute the results in parallel. Our results demonstrate that these palmtop machines provide significant energy advantage-average of 67% in our case study-over energy-optimized desktop, high-performance workstation and server class machines.

关键词： Servers Wireless sensor networks Personal digital assistants Sensors Batteries Androids

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Recent Advancements in Nanophotonics for Optofluidics

arXiv

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arXiv 2024年

作者： Yang, Sen Hong, Chuchuan Zhu, Guodong Anyika, Theodore Hong, Ikjun Ndukaife, Justus C. Institute of Physics Chinese Academy of Sciences Beijing National Laboratory for Condensed Matter Physics Beijing100190 China Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37240 United States

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently, driven by the concerted efforts of researchers across various scientific disciplines, notably for its successful applications in biomedical science. In this review, we explore a range of optofluidic architectures developed over the past decade, with a primary focus on mechanisms for precise control of micro and nanoscale biological objects and their applications in sensing. Regarding nanoparticle manipulation, we delve into mechanisms based on optical nanotweezers using nanolocalized light fields and light-based hybrid effects with dramatically improved performance and capabilities. In the context of sensing, we emphasize those works that used optofluidics to aggregate molecules or particles to promote sensing and detection. Additionally, we highlight emerging research directions, encompassing both fundamental principles and practical applications in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Flow of fluids

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