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Physique- Based Human Activity Recognition Using Deep Learning Approaches and Smartphone Sensors

Physique- Based Human Activity Recognition Using Deep Learni...

International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Sakkayaphop Pravesjit Ponnipa Jantawong Anuchit Jitpattanakul Sakorn Mekruksavanich Department of Information Technology School of Information and Communication Technology University of Phayao Phayao Thailand Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Thailand Department of Mathematics Intelligent and Nonlinear Dynamic Innovations Research Center Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok Thailand

Understanding human actions via the analysis of sensor data captured by wearable sensors is the goal of the complex subject of study known as sensor-based human activity recognition (S-HAR). Human participants' characteristics are only periodically included in deep learning (DL) approaches to S-HAR. Recognizing people was challenging for these DL methods because of the variety of physical characteristics people have. To address this challenge, we introduce a physique-based S-HAR architecture that could support deep learning networks to achieve higher identification a ccuracies a nd F1-scores. The HARSense dataset, a publicly available benchmark S-HAR dataset that compiles raw sensor data acquired from smartphones, was employed to build and evaluate five DL networks. A ccording to the experiments, the five models' detection performance improves dramatically when given access to biological data.

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Floquet-Mode Traveling-Wave Parametric Amplifiers

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PRX Quantum 2022年第2期3卷 020306-020306页

作者： Kaidong Peng Mahdi Naghiloo Jennifer Wang Gregory D. Cunningham Yufeng Ye Kevin P. O’Brien Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA

Simultaneous ideal quantum measurements of multiple single-photon-level signals would advance applications in quantum information processing, metrology, and astronomy but require the first amplifier to be simultaneously broadband, quantum limited, and directional. However, conventional traveling-wave parametric amplifiers support broadband amplification at the cost of increased added noise and are not genuinely directional due to non-negligible nonlinear backward-wave generation. In this work, we introduce a new class of amplifiers that encode the information in the Floquet modes of the system. Such Floquet-mode amplifiers prevent information leakage and overcome the trade-off between quantum efficiency (QE) and bandwidth. Crucially, Floquet-mode amplifiers strongly suppress the nonlinear forward-backward wave coupling and are therefore genuinely directional and readily integrable with qubits, clearing another major obstacle toward broadband ideal quantum measurements. Furthermore, Floquet-mode amplifiers are insensitive to out-of-band impedance mismatch, which otherwise may lead to gain ripples, parametric oscillations, and instability in conventional traveling-wave parametric amplifiers. Finally, we show that a Floquet-mode Josephson traveling-wave parametric amplifier implementation can simultaneously achieve >20dB gain and a QE of η/ηideal>99.9% of the quantum limit over more than an octave of bandwidth. The proposed Floquet scheme is also widely applicable to other platforms, such as kinetic inductance traveling-wave amplifiers and optical parametric amplifiers.

关键词： Metamaterials Quantum information with solid state qubits Quantum metrology Superconducting quantum optics Superconducting devices Superconducting qubits

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Performance of Vertical Bifacial 2T and 3T Perovskite/Silicon Tandem Solar Farms

Performance of Vertical Bifacial 2T and 3T Perovskite/Silico...

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IEEE Conference Photovoltaic Specialists (PVSC)

作者： Syed Usama Bin Afzal Hassan Imran Suleman Sami Qazi Muhammad Ashraful Alam Nauman Zafar Butt Department of Electrical Engineering School of Science and Engineering LUMS Lahore Pakistan Department of Electrical Engineering School of Engineering and Applied Science GIFT Gujranwala Pakistan Department of Electrical Engineering University of Engineering and Technology Lahore Pakistan School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Tandem solar cells based on Silicon Heterojunction (SHJ) and Perovskite (PVK) are being widely explored for high efficiency solar modules beyond the thermodynamic/practical limits of single junction solar cell. While a two terminal tandem (2TT) cell configuration is generally the most convenient in terms of fabrication, the performance is hampered by the current-matching constraint for the series connected sub-cells. A four terminal tandem (4TT), on the other hand, is affected by contact shading and fabrication challenges. The three terminal tandem (3TT) cell with the bottom Interdigitated Back Contact (IBC) is an attractive choice as it avoids isolation between sub-cells and the lateral current collection. Recently, there has been a number of studies on PVK/IBC tandem cells and farm level configurations, but their performance has not been explored for vertical solar farms which are attractive due to their morning/afternoon peaks and for agrivoltaic applications. Here, we present a detailed computational study on vertical bifacial solar farms made of 2TT and 3TT PVK/IBC tandem cells and their relative performance as compared to the vertical farms made of single junction HIT solar cells. We show that the annual energy production for East/West faced 3TT PVK/IBC vertical farm is 37% more as compared to 2TT series connected PVK/HIT vertical farm and 16% more as compared to single junction bifacial HIT vertical farm for the latitude of 31. 5° N at Lahore.

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Twitter Sentiment Analysis in Covid-19 Pandemic 12

Twitter Sentiment Analysis in Covid-19 Pandemic

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12th IEEE Annual Information technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Madanian, Samaneh Airehrour, David Samsuri, Nabilah Ahmad Cherrington, Marianne Auckland University of Technology Department of Computer Science and Software Engineering Auckland New Zealand School of Applied Business Unitec Institute of Technology Auckland New Zealand Auckland University of Technology Department of Mathematical Sciences Auckland New Zealand School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (纸本)9781665400664

We have yet to realise the full capability of social media as an innovative information platform during emergencies and crisis response and management. Sentiment analysis can systematically identify, extract, and scrutinise emotional states and subjective information in social media data. Exploring reactions and perceptions to response messaging is invaluable and proved especially useful for a pandemic response as it can demonstrate general population reaction to the pandemic and governments response actions. This can be further analysed to identify the gap between government response actions and communications and citizens' perceptions. In this paper, an analysis of Twitter data explores population reaction towards COVID-19 health messaging. A Natural Language Processing Python tool is known as TextBlob was used to discover general data sentiment. Data were divided into three sentiments and text extraction of health messages was conducted to explore subsequent tweets in predefined categories. Our findings show the outcome of Tweets analysis could help us to identify the general population concerns and their reactions to COVID-19 to give a better understanding of the situation to governments and support them in implementing appropriate policies. © 2021 IEEE.

关键词： Sentiment analysis

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Learning the solution operator of two-dimensional incompressible Navier-Stokes equations using physics-aware convolutional neural networks

arXiv

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arXiv 2023年

作者： Grimm, Viktor Heinlein, Alexander Klawonn, Axel Department of Mathematics and Computer Science University of Cologne Weyertal 86-90 Köln50931 Germany Center for Data and Simulation Science University of Cologne Köln50923 Germany Delft Institute of Applied Mathematics Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands

In recent years, the concept of introducing physics to machine learning has become widely popular. Most physics-inclusive ML-techniques however are still limited to a single geometry or a set of parametrizable geometries. Thus, there remains the need to train a new model for a new geometry, even if it is only slightly modified. With this work we introduce a technique with which it is possible to learn approximate solutions to the steady-state Navier–Stokes equations in varying geometries without the need of parametrization. This technique is based on a combination of a U-Net-like CNN and well established discretization methods from the field of the finite difference method. The results of our physics-aware CNN are compared to a state-of-the-art data-based approach. Additionally, it is also shown how our approach performs when combined with the data-based *** Codes 35Q30, 68T07, 68T10, 65N22 Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Sensing property of Ga2O3-based extended-gate field-effect transistors for a living cell viability sensor

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Sensors and Actuators A: Physical 2023年 349卷

作者： Chou, Hsin-Yu Chiang, Jung-Lung Yu, Chang-Tze Ricky Chen, Jo-Mei Maureen Wuu, Dong-Sing Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung411030 Taiwan Department of Applied Chemistry National Chi-Nan University Nantou54561 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan

In this study, gallium oxide (Ga2O3) nanorods were deposited onto an indium tin oxide (ITO) glass substrate to develop a real-time living cell viability sensor. Ga2O3 nanorods had characteristics of cell population sensing based on cellular metabolism to detect cell viability. The pH sensing characteristics of Ga2O3-based extended-gate field-effect transistors (EGFETs) with and without the annealing process were measured from pH 1–11. Three different sensor heads, ITO/glass, GaOOH/ITO/glass, and Ga2O3/ITO/glass, were produced as EGFETs and immersed into a pH standard buffer and high-glucose Dulbecco's modified Eagle's medium (DMEM) to investigate hydrogen ion sensing. Results showed that the Ga2O3/ITO/glass probe had the best hydrogen ion sensing sensitivity and stability in different sample buffers. In contrast, GaOOH/ITO/glass had instability and lower sensitivity due to interference with other components in the medium. The drift characteristic of sensors was analyzed to detect long-term stability. The Ga2O3/ITO/glass probe showed lower drift properties, which can potentially monitor the DMEM situation in real-time for a long-term period. During in vitro detection, the Ga2O3/ITO/glass probe revealed a 70 μA/cells change in IDS-VDS analysis and a 10 μV/cells change in IDS-VGS analysis, which was superior linearly dependent within 10,000 cells. The biocompatibility of the Ga2O3/ITO/glass probe was also detected by 3-(4,5-dimethylthiazol-2-yl)− 2,5-diphenyltetrazolium bromide assay and showed no cytotoxicity. Overall, the Ga2O3/ITO/glass EGFET sensor has potential applications as a living cell viability device in microenvironmental studies in the future. © 2022 Elsevier B.V.

关键词： Nanorods

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Deep Neural Quality of Service Prediction for Unmanned Aircraft System Communications

Deep Neural Quality of Service Prediction for Unmanned Aircr...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Patrick Purucker Christian Reil Alfred Höß Björn W. Schuller Department of Electrical Engineering Media Technology and Computer Sciences University of Applied Sciences Amberg-Weiden Amberg Germany CHI MRI Technical University of Munich Germany Munich Data-Science Institute (MDSI) Germany Munich Center for Machine Learning (MCML) Germany GLAM Imperial College London UK

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Commercial Unmanned Aircraft Systems (UAS) have a wide range of applications, including package delivery, inspection and search and rescue missions. For the operation of Unmanned Aircraft Vehicles (UAV) Beyond Visual Line of Sight (BVLOS), reliable long-range communication is essential. The cellular network is one possible solution, but there are issues such as signal loss and frequent handovers at higher altitudes. To mitigate these issues, our work proposes the use of two cellular links from different providers prioritised according to Quality of Service (QoS) prediction. We evaluate multiple AI-based model architectures for the prediction, and find that the model consisting of Gated Recurrent Units (GRU) and convolutional layers outperforms the others. The models are trained and tested on real-world data and show a reduction in latency peaks, thereby increasing connection resilience. Moreover, the prediction pipeline is designed to be executable on the UAV side and is not limited to a specific geographical area, making it applicable to real-world scenarios. Finally, we present a pre-flight path planning algorithm that takes QoS into account when calculating the flight path in order to further improve communication. To support the research community, we publicly share the dataset used to obtain our results.

关键词： Adaptation models Heuristic algorithms Quality of service computer architecture Predictive models Autonomous aerial vehicles Modems

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Identification of potential plant secondary metabolites targeting begomovirus-associated betasatellite virulence factor βC1 protein through molecular docking, simulation and MM-PBSA studies

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Discover Plants 2025年第1期2卷 1-21页

作者： Hiremath, Shridhar Bharath, M. Muttappagol, Mantesh Kumar, H. D. Vinay Kumar, T. L. Mohan Shankarappa, K. S. Venkataravanappa, V. Basha, C. R. Jahir Reddy, C. N. Lakshminarayana Department of Plant Pathology College of Agriculture University of Agricultural Sciences GKVK Bangalore India Centre for Infectious Diseases CSIR-North East Institute of Science and Technology Jorhat India Department of Agricultural Statistics Applied Mathematics and Computer Science College of Agriculture University of Agricultural Sciences GKVK Bangalore India Department of Plant Pathology College of Horticulture University of Horticultural Sciences Bengaluru India Division of Crop Protection ICAR-Indian Institute of Horticultural Research Bangalore India

The βC1 protein encoded by begomoviruses plays a key role in counteracting plant defense mechanisms, making it a prime target for antiviral compounds. Here, we investigated the role of plant secondary metabolites for their antiviral potential. Initially, the tertiary structure of βC1 protein was predicted and docked to 2851 plant secondary metabolites along with positive controls ribavirin and ningnanmycin. Additionally, 43 analogues of the ligand with highest dock score were created and assessed against the βC1 protein to see if they offered better binding energy than the initial compound. To check the protein–ligand complex's stability, we performed a 100 ns molecular dynamics (MD) simulation, then measured the change in Gibbs free energy (ΔG) using the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) approach. Our study found that Anonaine, a bioactive compound, had a high binding score of − 6.0 kcal/mol, with its analogues a33 and a41 scoring − 6.8 kcal/mol and − 6.6 kcal/mol, respectively. Molecular dynamics simulations for these complexes showed stable interactions, with minimal changes in root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values. Additionally, the protein–ligand complexes showed consistent hydrogen bond formation, with negligible changes in the radius of gyration (Rg) and solvent-accessible surface area (SASA). The binding free energy (ΔG) calculations revealed estimated values of − 16.99 ± 2.16, − 18.29 ± 1.91, and − 27.26 ± 2.11 for the βC1-Anonaine, βC1-a33, and βC1-a44 protein–ligand complexes, respectively. In silico toxicity predictions suggest top ligands are less toxic, making them ideal for biopesticide development. Overall, these findings reveal the potential of plant secondary metabolites as promising agents in controlling begomovirus infections.

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Customer Service Support System by ITIL version 3 Operating Framework with the Geographic Information System

Customer Service Support System by ITIL version 3 Operating ...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Tawan Thanamatee Thittaporn Ganokratanaa Patiyuth Pramkeaw Narumol Chumuang Mahasak Ketcham Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Department of Digital Media Technology Muban Chombueng Rajabhat University (MCRU) Thailand Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand

The purpose of this research was to develop a power consumer service support system, a case study of the Provincial Electricity Authority, Chumphon Province. By applying the ITIL version 3 operating framework to be applied in conjunction with the geographic information system, the efficiency of the application of the geographic information system was assessed, the quality of the system was assessed by experts and the satisfaction of general users was assessed. This system was developed to increase the efficiency and accuracy of electricity consumer services. receive follow-up notifications request for service and service complaints Able to display statistical reports in geographic information formats resulting in standardized customer service management. Evaluation results of the efficiency of the system in finding and displaying the coordinates of service locations have an average overall efficiency of F-Measure of 92 percent and the quality assessment of experts at a good level with an average of 4.17 deviations. The standard was 0.51 and the satisfaction assessment results of general users were at a good level with an average of 4.35 and a standard deviation of 0.42 from both groups of assessors. It can be concluded that the developed system can be applied to real work efficiently and effectively

关键词： Heart Technological innovation Customer services Standards organizations Government Quality assessment Information technology

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IoT Malware Detection Tool with CNN Classification for Small Devices

IoT Malware Detection Tool with CNN Classification for Small...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Gunjan Bhatnagar Yogendra Kumar Rajoria Md. Sakeel M. Vigenesh G. Premananthan Deepika Dongre School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India Department of Mathematics School of Basic & Applied Sciences K. R. Mangalam University Gurugram India Department of Computer Applications Invertis University Bareilly India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Department of Electronics and Communication Engineering Karpagam College of Engineering Coimbatore India AI & Ds Vishwakarma Institute of Information Technology Pune India

Since the number of linked devices continues to grow quickly, the Web of Everything (IoT) is being employed change today in more industries. More issues in regards to safety, stability, and supportability are brought on by an increase in smart devices, particularly as it relates to 5G technology. We are concentrating on the safety component of IoT systems in just this article because it is a relatively new field. For varied purposes, such as cost savings or a desire to forego the use of generation system, many Internet device manufacturers need not take security into account when designing their products. The opponent may use those potentially dangerous technologies to carry out several destructive assaults. As a result, we created a device capable of recognizing malicious activity from a particular IoT networks node. They are capable to offer detection methods for IoT utilizing a primary key that may be put inside the system using a multilayer brain networks for identification and surveillance. The accomplishment dispels any misconceptions about methods for deep training while demonstrating how that systems can be simply adapted and deployed to every system.

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