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5th International Conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Anandkumar, V. Diwakaran, M. Sivabalan, K.N. Balakrishna, R. Sri Krishna College of Engineering and Technology Department of Information Technology Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering India

ISBN: (纸本)9781665415712

The internet has become an integral part of our daily lives, and it is the medium that connects everyone on the planet, allowing individuals to exchange their opinions, knowledge, and experience. Because this entire network of individuals is connected via the internet, they might be referred to as the 'internet of people'. What if the diurnal devices use by humans can also share their experiences with other things, communicate with us and work according to our commands using the internet as the medium. This whole idea is being realized under Internet of Things (IOT) technology. So, all the IOT devices or networks are developed to attain the above functionality and they are also equipped with three different layers of technologies namely Sensor, Communication and computational or processing technologies. This integrated network of various technologies is being developed to sort out the key human adversities such as water wastage, pollution, depletion of energy resources, health issues etc., and this paves way to establish a balance between the growing population and resources. © 2021 IEEE.

关键词： Internet of things

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MPEC: Manifold-Preserved EEG Classification via an Ensemble of Clustering-Based Classifiers

MPEC: Manifold-Preserved EEG Classification via an Ensemble ...

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International CSI Computer Conference, CSICC

作者： Shermin Shahbazi Mohammad–Reza Nasiri Majid Ramezani Department of Electrical and Computer Engineering University of Zanjan Zanjan Iran Department of Computer Science and Information Technology Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan Iran

ISBN: (数字)9798331523114

ISBN: (纸本)9798331523121

Accurate classification of EEG signals is crucial for brain-computer interfaces (BCls) and neuroprosthetic applications, yet many existing methods fail to account for the non-Euclidean, manifold structure of EEG data, resulting in suboptimal performance. Preserving this manifold information is essential to capture the true geometry of EEG signals, but traditional classification techniques largely overlook this need. To this end, we propose MPEC (Manifold-Preserved EEG Classification via an Ensemble of Clustering-Based Classifiers), that introduces two key innovations: (1) a feature engineering phase that combines covariance matrices and Radial Basis Function (RBF) kernels to capture both linear and non-linear relationships among EEG channels, and (2) a clustering phase that employs a modified K-means algorithm tailored for the Riemannian manifold space, ensuring local geometric sensitivity. Ensembling multiple clustering-based classifiers, MPEC achieves superior results, validated by significant improvements on the BCI Competition IV dataset 2a.

关键词： Manifolds Geometry Support vector machines Technological innovation Accuracy Sensitivity Brain modeling Electroencephalography Brain-computer interfaces Reliability

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Signal-to-noise ratio enhancement of Φ-OTDR based on Block-matching and 3D filtering

Signal-to-noise ratio enhancement of Φ-OTDR based on Block-...

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2023 Opto-Electronics and Communications Conference, OECC 2023

作者： Zhang, Jingming Yan, Yaxi Liu, Shuaiqi Lau, Alan Pak Tao Yu, Changyuan Shao, Liyang The Hong Kong Polytechnic University Department of Electronic and Information Engineering Hong Kong Hong Kong Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China The Hong Kong Polytechnic University Department of Electrical Engineering Hong Kong Hong Kong Hangzhou Institute of Advanced Studies Zhejiang Normal University Hangzhou China

ISBN: (纸本)9781665462136

Aiming at successful vibration extraction of Φ-OTDR under the condition of low signal-to-noise ratio (SNR), a differential intensity image denoising scheme based on Block-matching and 3D filtering (BM3D) is proposed. The correlation of data in time domain and space domain was utilized for denoising, which reduces noise significantly while retaining rich details. Distributed vibration sensing with a spatial resolution of 20 m over a 50 km distance was realized in the experiment. The SNR at the end of the optical fiber was increased from close to 0 dB to 37.2 dB. © 2023 IEEE.

关键词： Motion compensation

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Smart Educational Ecosystems: Tailoring Employee Training With Ai and Iot in the Industry 5.0 Landscape

Smart Educational Ecosystems: Tailoring Employee Training Wi...

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Technological Advancements in Computational Sciences (ICTACS), International Conference on

作者： Arnima Pathak Mani Shivhare Durgesh Kumar Information and Communication Technology Tecnia Institute of Advanced Studies Delhi India Computer Science and Engineering with Data Science G.L. Bajaj Institute of Technology and Management Noida India Computer Science and Engineering Sharda University Noida India

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

This study investigates the transformational potential of combining the Internet of Things with artificial intelligence to build intelligent educational ecosystems for Industry 5.0 worker training. Seeing the need for tailored learning experiences to match changing skill requirements, the research looks into how AI and IoT may transform workforce education. Using a mixed-methods approach that includes expert interviews, case study analysis, and literature evaluation, the research identifies and evaluates the essential elements of AI- and IoT-driven training systems. The results show that real-time data gathering and feedback enabled by IoT in conjunction with AI-powered tailored learning greatly enhances organizational flexibility, employee engagement, and learning outcomes. The report specifically notes gains in information retention, skill development speed, and training cost savings. The study also tackles issues which include reluctance to technology adoption and worries about data privacy. It emphasizes a human-centric strategy that strikes a balance between technology improvements and ethical issues for enterprises making the transition to Industry 5.0. It also provides useful insights and suggests an implementation structure.

关键词： Training Industries Ethics Ecosystems Transforms Real-time systems Internet of Things Fifth Industrial Revolution Artificial intelligence Interviews

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Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

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Acta Pharmaceutica Sinica B 2024年第2期14卷 623-634页

作者： Jiacheng Xiong Rongrong Cui Zhaojun Li Wei Zhang Runze Zhang Zunyun Fu Xiaohong Liu Zhenghao Li Kaixian Chen Mingyue Zheng Drug Discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China College of Computer and Information Engineering Dezhou UniversityDezhou 253023China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215000China Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China State Key Laboratory of Pharmaceutical Biotechnology Nanjing UniversityNanjing 210023China

Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other ***-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic *** models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism *** this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated *** integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both *** significantly outperformed the benchmark methods in both cross-validation and external *** AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro ***,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://***.

关键词： Drugmetabolism Aldehyde oxidase Transferlearning Graph neural network Kinase inhibitor

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Performance Analysis Of Insulation Resistance Test And Cable Laying Installation In Library Block

Performance Analysis Of Insulation Resistance Test And Cable...

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Global Power, Energy and Communication Conference (GPECOM)

作者： B. Rubini R. Karthick Kalaiarasi G S. Saranya S. Pradeep Kumar M. Suganiya Department of Electrical and Electronics Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Department of Electrical and Electronics Engineering C.K.College of Engineering and Technology Cuddalore India Department of Advanced Computer Science and Engineering Vignan’s Foundation for Science Technology & Research (Deemed to be University) Guntur India Department of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Trichy India Department of Computing Technologies SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798350351088

ISBN: (纸本)9798350351095

The process of installing electrical cables physically in a specific location inside a library block is widely considered as an electrically equipped place. It involves planning the particular route, securing the cables and ensuring technical support and proper protection. In a library block, the process of installing electrical wires can provide power and electrical connectivity to various devices and systems. An insulation resistance tests were conducted a high voltage flow to the insulation and measures the resistance ratio to the actual current flow after cable installation. Testing of measurements given in table. Algorithms help to identify all kinds of weaknesses and faults in the insulation that could lead to any electrical leakages or short circuits. The insulation resistance test is primarily important to ensure the safety and reliability of electrical systems. It is particularly needed in an environment like a library. Libraries are filled with books made of papers that are easily flammable in nature. So, we should give top priority to electrical safety in libraries. Minimum constrained non-linear minimization solver is used to identify the iteration levels and verified with best function values and first order optimality values. This paper shows performance analysis of Insulation resistance test and Cable laying installation in a Library block.

关键词： Resistance Insulation Current measurement Wires Libraries Performance analysis Electrical resistance measurement

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Geological Time Series Analysis for Spatial Seismic Forecasting in Japan

Geological Time Series Analysis for Spatial Seismic Forecast...

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Artificial Intelligence and Emerging technology (Global AI Summit), International Conference on

作者： Prerit Sharma Bhawna Saxena Rhythm Rajat Khandelwal Adwitiya Sinha Department of Computer Science and Engineering & Information Technology Jaypee Institute of Information Technology Noida Uttar Pradesh India Natural & Applied Sciences TERI School of Advanced Studies Delhi India

ISBN: (数字)9798350379716

ISBN: (纸本)9798350379723

Earthquakes pose significant threats to lives and infrastructure worldwide, underscoring the critical need for effective prediction models. Our study represents a meticulous examination of seismic data sourced from the United States Geological Survey, encompassing earthquake occurrences in Japan over five years. Employing a refined zoning approach based on historical seismicity, we tailored our analysis to account for regional variations in earthquake frequency and intensity. By integrating these discoveries into the ARIMA model, we aim to fortify earthquake prediction frameworks, thereby fostering more effective disaster mitigation strategies on a global scale. Furthermore, our analysis using SMA, EMA, and ARIMA models demonstrated that the EMA model provided superior performance. Leveraging the predictive capabilities of the EMA model, we identified twelve geographic coordinates in Japan with a higher likelihood of future earthquakes. This study underscores the potential of EMA in earthquake prediction and provides a foundational approach for integrating machine learning with geospatial analysis for natural disaster forecasting.

关键词： Surveys Analytical models Geology Disasters Earthquakes Time series analysis Machine learning Predictive models Data models Forecasting

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Structural Modification of Plant Derived Galactomannan and Synergistic Integration of Mxene to Produce Multifunctional Nanocomposites with Antibacterial and Osteogenic Properties

SSRN

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SSRN 2024年

作者： Krishnakumar, Gopal Shankar Elangovan, Sinduja Malarkodi Paul, Riza Shanmugam, Parthiban Department of Biotechnology Bannari Amman Institute of Technology Sathyamangalam Tamil Nadu Erode India Advanced Materials and Devices Laboratory PSG Institute of Advanced Studies Peelamedu Tamil Nadu Coimbatore India Department of physics Centre for Research and Development KPR Institute of Engineering and Technology Tamil Nadu Coimbatore India Department of Bioscience and Engineering National Institute of Technology Kerala Calicut India

This study proposes to combine plant-derived galactomannan and MXene to form an organic-inorganic hydrogel network with integrative antibacterial and osteogenic properties. Oxidized galactomannan (OxGa) was blended with N-succinyl chitosan (NSC) and varying amount of MXene owing to its high reactivity and biocompatibility. The results indicated that MXene loaded OxGa/NSC scaffolds exhibited biomimetic topography, adequate mechanical features and excellent physicochemical properties with strong antibacterial properties against E. coli and S. aureus. The cell culture experiments showed a dose dependency cytotoxic behavior. An optimized MXene content of ≤ 4 mg/ml revealed no cytotoxicity and augmented the proliferation of osteoblast cells. Similar results were obtained in gene expression analysis where ALP, COL1A1, RUNX2, and SOX2 genes showed up-regulation. In addition, the chorioallantoic membrane (CAM) assay also illustrated augmentation of angiogenesis without any toxicity. The overall results highlight the dual performance of OxGa/NSC-MXene scaffolds to exhibit anti-infection with simultaneous osteogenic property is purely determined by the concentration of MXene. Therefore, regulating MXene concentration can serve as a chemical switch in imparting adequate antibacterial functions with ability to allow new osseous generation. Our findings on the newly designed MXene loaded OxGa/NSC scaffolds can be a promising biomaterial for bone related infections with concurrent ability to promote osteogenesis. © 2024, The Authors. All rights reserved.

关键词： Bone

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Principal component regression approach for measuring the impact of built environment variables on multiple air pollutants in Delhi

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Discover Atmosphere 2025年第1期3卷 1-18页

作者： Jain, Deepty Bhatnagar, Smriti Rathi, Vanshika Sachdeva, Kamna Tewani, Ankush Sharma, Gautam Transportation Research and Injury Prevention Centre Indian Institute of Technology Delhi New Delhi India Department of Sustainable Engineering TERI School of Advanced Studies Delhi India Department of Natural and Applied Sciences TERI School of Advanced Studies Delhi India Delhi Skill and Entrepreneurship University Delhi India Central Pollution Control Board Delhi India

Air pollution will likely increase as cities continue to intensify urban activities and expand their infrastructure. Delhi is one of the most polluted cities in the world. Yet, there is a lack of understanding of how the built environment (BE) strategies can address local air quality levels for the city. Additionally, the existing studies use the land use regression (LUR) technique, assuming independence between BE variables. We assessed the impact of BE variables measured at various spatial scales on Delhi's air pollutants (PM2.5, PM10, CO, NO2 and O3). This study used the Principal Component Regression (PCR) approach to account for the multicollinearity between BE variables. As per the analysis, PCR provided better estimates for PM10, PM2.5, and CO concentrations. LUR was found better for modelling NO2 and O3. The findings show that as built-up percentage and the metro station density increases the PM10 and CO levels are also likely to increase, while increasing green percentage is likely to result in decreasing pollutant concentrations. We also identify BE variables that affect a particular pollutant. Percentage institutional within 700 m buffer radii affects PM10, distance to CBD affects CO levels, and distance to the bus depot is affects both CO and NO2 levels. The PCR helped measure the joint effect of BE variables on pollutant concentrations in Delhi. Simultaneously modelling multiple air pollutants can help develop a better urban development strategy for addressing air pollution.

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advanced Schedulability Testing for Adaptive Mixed-Criticality Systems under Weakly Hard Real-Time Constraints

Advanced Schedulability Testing for Adaptive Mixed-Criticali...

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CSI Symposium on Real-Time and Embedded Systems and Technologies (RTEST)

作者： Hossein Rabbiun Jamal Mohammadi Mahmoud Shirazi Mehdi Kargahi Department of Computer Science and Information Technology Institute for Advanced Studies in Basic Sciences (IASBS) Zanjan Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (数字)9798331529284

ISBN: (纸本)9798331529291

This paper advances the schedulability analysis of the Adaptive Mixed-Criticality for Weakly Hard Real-Time Systems (AMC-WH) which allows a specified number of consecutive low-criticality (LO) jobs of tasks to be skipped when the system operates in the high-criticality (HI) mode. The current AMC-WH schedulability test, based on the skip-over model, in which low tasks are guaranteed to meet m − s out of m consecutive deadlines, where s is the number of allowed skips and m is the cycle length, only calculates the worst-case response times (WCRT) for low tasks under a fixed execution pattern post-mode switch. To address this limitation, we propose a new sufficient schedulability test for AMC-WH using the (m,k)-firm model, which allows various execution patterns for low tasks after a mode switch, enhancing the flexibility and applicability. Additionally, we develop an exact schedulability test for AMC-WH based on response time analysis (RTA). This test modifies the existing exact tests for the AMC algorithm, incorporating updates to state-space exploration and pruning rules to account for low task execution after a mode switch. Simulation results validate the effectiveness of our tests, demonstrating enhanced schedulability analysis and optimized resource allocation.

关键词： Adaptation models Adaptive systems Scheduling algorithms Simulation Switches Cyber-physical systems Real-time systems Time factors Resource management Testing

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