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2nd International Conference on Electronics and Renewable Systems, ICEARS 2023

作者： Prabakaran, P. Shalini, R. Hariharan, N. Marieswari, S. Kumar, Kallakunta Ravi Apoorva, Maturi Gayatri Lakshmi Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Department of Computer Applications Chennai India Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Department of Bca and It Chennai India R.M.K. College of Engineering and Technology Science and Humanities - Eee Thiruvallur601206 India P. S. R. Engineering College Biomedical Engineering India Koneru Lakshmaiah Education Foundation Department of Ece Vaddeswaram India Amrita School of Engineering Ece Department India

ISBN: (纸本)9798350346640

Wireless sensor network (WSN) contains millions of small, low-power gadgets with a lack of resources are memory and battery power. Such gadgets were deployed in a dispersed manner and were often utilized to monitor and sense applications. Owing to constraints and limited resources of WSNs, routing can be a great difficulty. Routing in WSN was the process of choosing the optimal path for data to travel from a source node to a destination node. The goal of routing in WSN offer dependable and effective transmission while minimizing network overhead and energy consumption. This study designs an Energy Efficient Colliding Bodies Optimization based Routing Protocol (EECBO-RP) for WSN. The end goal of the EECBO-RP algorithm lies in the optimal election of routes to a destination. For achieving reasonable results for the minimization of energy exploitation, the EECBO-RP system derives the fitness function using the following variables: residual energy, distance to BS, and node degree. The EECBO-RP technique chooses the relay nodes so that a way that the overall efficiency of the WSN gets maximized. The simulation values of the EECBO-RP system are tested under several dimensions and the outcomes pointed out the betterment of the EECBO-RP technique. © 2023 IEEE.

关键词： Energy efficiency

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Analysing various algorithms applied to Alzheimer's disease dataset to help the Future Generation 2

Analysing various algorithms applied to Alzheimer's disease ...

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Athinarayanan, S. Navaz, K. Tamilselvi, P. Shajeena, J. Vishwa Priya, V. Joel, M. Robinson School of Computing Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai Tamil Nadu Avadi600062 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai600062 India Vels Institute of Science Technology and Advanced Studies Department of Computer Science Chennai600117 India Vels Institute of Science Technology and Studies Department of Computer Science Chennai India Kings Engineering College Department of Information Technology Chennai India

ISBN: (纸本)9798350306415

A sort of brain illness that affects the brain is Alzheimer's. Nowadays, older adults are more likely to have these ailments. People who have this illness have very poor memories and decreased memory. Additionally, their brain isn't working correctly. As a result, their regular practice is progressively beginning to decline. Alzheimer's is a kind of dementia for which there is no definitive treatment. This essay will help us learn more about Alzheimer's illness. We shall learn more about its causes, symptoms, and remedies. Additionally, we investigate several illness prediction methods employing Graph Neural Networks denoted as GNNs. Decision Tree, Random Forest algorithms, and more. However, the Random forest classifier gave good results with 86% accuracy and good recall values. © 2024 IEEE.

关键词： Alzheimer dementia GNN Graph Neural Network Prediction

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A Model for the Analytical Performance of Data Lake in Stock Market Analysis with Databricks Delta Lake

A Model for the Analytical Performance of Data Lake in Stock...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Kamalakkannan, S. Yasmin, A. Arunkumar, R. Kavitha, P. School of Computing Sciences Vels Institute of Science Technology & Advanced Studies Department of Information Technology Chennai Pallavaram India Jbas College for Women Department of Computer Science Chennai India University of South Wales Faculty of Computing Engineering and Science Treforest/Newport Campus United Kingdom School of Computing Sciences Vels Institute of Science Technology & Advanced Studies Department of Computer Applications Chennai Pallavaram India

ISBN: (纸本)9798350300857

Stock market investments are highly rewarding but also high in risk. Modern investors use variety of tools to take informed investment decisions. In the current era of digital world, financial service industry has generated huge volume and immense verities of data with extreme speed. Due to the rapid growth in data collection and the heterogeneous nature and complexity of the data, there is a need for Big Data analytical solution that would be able to deal with the stock market data. Large volumes of unstructured, heterogeneous raw data can be stored in a massively scalable manner using data lakes, which are the ideal solution to the big data storage conundrum. The ability of a data lake to preserve data in its original format while processing it at runtime using a schema on-read technique is its key feature. The challenge faced in the data lake is performing analytics which is a significant tool to calculate and analyze the stock market. The proposed architecture of Azure Databricks DeltaLake (ADDL) with Azure DataLake Storage Generation 2 (ADLSG2) is used for analytical processes like Fibonacci retracement for better stock analysis, which aid in forecasting the market price for better investment. As a result, the research focus is to produce a storage having read as well as write capabilities by taking into consideration the Extract-Load-Transform (ELT) operation on the datasource. In this experimental databricks implementation, runtime is performed using open source of Apache Spark API and a highly improved execution engine, which results in a significant performance improvement when comparing to the standard source of Apache Spark available on the ADLS platform. Additionally, the Fibonacci retracement level calculation is achieved with the analytics and forecasting of test close price with various ML and DL techniques such as KNN, LSTM are compared with original price of the test data for better prediction of forecast close price. © 2023 IEEE.

关键词： Big data

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Elevated temperature-driven coordinative reconstruction of an unsaturated single-Ni-atom structure with low valency on a polymer-derived matrix for the electrolytic oxygen evolution reaction

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Nanoscale 2024年第15期16卷 7467-7479页

作者： Patil, Rahul Rajput, Anubha Matsagar, Babasaheb M. Chen, Norman C. R. Ujihara, Masaki Salunkhe, Rahul R. Yadav, Praveen Wu, Kevin C.-W. Chakraborty, Biswarup Dutta, Saikat Electrochemical Energy & Sensor Research Laboratory Amity Institute of Click Chemistry Research & Studies Amity University Noida India Department of Chemistry Indian Institute of Technology New Delhi India Department of Chemical Engineering National Taiwan University Taipei10617 Taiwan Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taiwan National Taiwan University Taiwan Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Materials Research Laboratory Department of Physics Indian Institute of Technology Jammu India Synchrotron X-ray Facility Raja Ramanna Centre for Advanced Technology Rajendra Nagar Madhya Pradesh 452013 Indore India

A high-temperature pyrolysis-controlled coordination reconstruction resulted in a single-Ni-atom structure with a Ni-Nx-C structural unit (x = N atom coordinated to Ni). Pyrolysis of Ni-phen@ZIF-8-RF at 700 °C resulted in NiNP-NC-700 with predominantly Ni nanoparticles. Upon elevating the pyrolysis temperature from 700 to 900 °C, a coordination reconstruction offers Ni-Nx atomic sites in NiSA-NC-900. A combined investigation with X-ray absorption spectroscopy, X-ray photoelectron spectroscopy, and soft X-ray L3-edge spectroscopy suggests the stabilization of low-valent Niδ+ (0 −2 was achieved. The cell potential recorded with Pt(−)/(+)NiSA-NC-900/NF was much lower than that obtained for other cells, i.e., Pt(−)/NF and NF(−)/(+)NF, which enhances the potentials of low-valent NiSAs for insightful understanding of the OER. At a constant applied potential of 1.61 V (vs. RHE) for 12 h, an small increase in current for initial 0.6 h followed by a constant current depicts the fair stability of catalyst for 12 h. Our results offer an insightful angle into the OER with a coordinatively reconstructed single-Ni-atom structure at lower valency ( © 2024 The Royal Society of Chemistry.

关键词： Reaction kinetics

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Highly spectra-stable pure blue perovskite light-emitting diodes based on copper and potassium co-doped quantum dots

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Nano Research 2023年第5期16卷 7654-7660页

作者： Fang Chen Wenjie Ming Yongfei Li Yun Gao Lea Pasquale Kexin Yao Boyuan Huang Qiuting Cai Guochao Lu Jizhong Song Mirko Prato Xingliang Dai Haiping He Zhizhen Ye School of Materials Science and Engineering State Key Laboratory of Silicon MaterialsZhejiang UniversityHangzhou 310027China Wenzhou Key Laboratory of Novel Optoelectronic and Nano Materials Institute of WenzhouZhejiang UniversityWenzhou 325006China Wenzhou XINXINTAIJING Tech.Co.Ltd. Wenzhou 325006China Shanxi‐Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030000China Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Multi-scale Porous Materials Center Institute of Advanced Interdisciplinary Studies&School of Chemistry and Chemical EngineeringChongqing UniversityChongqing 400044China Materials Characterization Facility Istituto Italiano di TecnologiaGenova 16163Italy School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450052China

Halide perovskite light emitting diodes(LEDs)have gained great progress in recent ***,mixed-halide perovskites for blue LEDs usually suffer from electroluminescence(EL)spectra shift at a high applied voltage or current density,limiting their *** this work,we report a strategy of using single-layer perovskite quantum dots(QDs)film to tackle the electroluminescence spectra shift in pure-blue perovskite LEDs and improve the LED efficiency by co-doping copper and potassium in the mixed-halide perovskite *** a result,we obtained pure-blue halide perovskite QD-LEDs with stable EL spectra centred at 469 nm even at a current density of 1,617 mA·cm^(−2).The optimal device presents a maximum external quantum efficiency(EQE)of 2.0%.The average maximum EQE and luminance of the LEDs are 1.49%and 393 cd·m^(−2),increasing 62%and 66%compared with the control *** study provides an effective strategy for achieving spectra-stable and highly efficient pure-blue perovskite LEDs.

关键词： light-emitting diode blue LED perovskite quantum dot stable electroluminescence spectra metal doping

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Smart Crutch: A Boon for Rehabilitative Patients

Smart Crutch: A Boon for Rehabilitative Patients

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Computer, Communication and Control (IC4), International Conference on

作者： A. Josephin Arockia Dhivya R. J. Hemalatha Jaya Rubi Department of Biomedical Engineering Vels Institute of ScienceTechnology and Advanced Studies Chennai Tamil Nadu India

In the last decade, physiotherapists have a remedy or a solution for elders and rehabilitative patients easily in a rapid manner, which makes the physiotherapists get to a conclusion rapidly; previous studies clearly show that when the patients excessively exercise or rehabilitation process, it affects the health of the elders extensively. Walkers play a very important role in the field of rehabilitation. Clinical decisions should be taken rapidly, effectively, and efficiently. These walking aids are highly recommended and suggested for elders suffering from back pain, spondylitis, and sports injury. This smart crutch is used to guide the patients properly so they do not get any pain due to excessive usage. Our device alerts the user in the form of a haptic when he/she is applying excessive force on the walker. This reduces the overuse of the device, which leads to severe pain. Our main motive is to enhance the patient’s life by designing a Smart crutch that alerts them if they overuse it. We also implemented a few parameters, such as a body posture management system where the user gets notified when his body bends too forward or backward. Also, it provides automatic lighting when the user is in a dark background. The user will be notified in terms of sound buzzer or light. Our ultimate goal is to help the patients and elders facing issues using rehabilitation aids. Although varicose veins are a prevalent condition, they disproportionately impact individuals who endure extended periods of standing or reclining. One potential treatment for varicose veins is vibration therapy, which involves applying vibration to the affected area to improve blood flow and reduce pain and swelling. The accelerometer sensor will detect the angle of the leg, and the Arduino will process the data and send it to the Node MCU. The Node MCU will be responsible for triggering the vibration therapy based on the angle of the leg detected by the accelerometer.

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Ultraclean transfer of graphene by mechanically exfoliating polymer with modified crosslink density

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Nano Research 2024年第8期17卷 6795-6802页

作者： Qi Lu Jiawei Yang Chaofan Zhou Zhaoning Hu Saiyu Bu Bingbing Guo Yixuan Zhao Junhao Liao Mingpeng Shang Ge Chen Kaicheng Jia Jianbo Yin Qiang Zeng Li Lin Zhongfan Liu College of Science China University of Petroleum(Beijing)Beijing 102249China School of Materials Science and Engineering Peking UniversityBeijing 100871China Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular ScienceCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China Beijing Graphene Institute Beijing 100095China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China Department of Electronics Peking UniversityBeijing 100871China Second Clinical Division National Engineering Laboratory for Digital and Material Technology of StomatologyPeking University School and Hospital of StomatologyBeijing 100081China

The transfer of graphene from metallic substrates onto application-specific substrates is usually inevitable for the applications of high-quality graphene films derived from chemical vapour deposition(CVD)*** used to support the graphene films during the transfer,the coating of the polymer would produce the surface contaminations and hinder the industrially compatible *** this work,through the thermal imidization of polyamide acid(PAA)to polyimide(PI)and tuning of the concentration of dangling chains,we achieved the ultraclean and crack-free transfer of graphene wafers with high electronic *** resulting contamination-free and hydrophilic surface also enabled the observed improved cell viability in a biomedical *** avoiding aqueous etching or the usage of strong bases,our proposed transfer method is industrially compatible for batch transfer of graphene films towards the real applications.

关键词： chemical vapour deposition(CVD)graphene films graphene transfer ultraclean transfer transfer medium crosslink density cell viability assay

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Development of stability-preserving time-limited model reduction framework for 2-D and 1-D models with error bound

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Control Theory and technology 2022年第3期20卷 371-381页

作者： Muhammad Imran Syeda Hira Ambreen Syed Nooh Hamdani Muhammad Imran Muhammad Ejaz Naveed Maria Siddiqui Department of Electrical Engineering Military College of Signals(MCS)National University of Sciences and Technology(NUST)Islamabad43000Pakistan Department of Electrical Engineering Sir Syed(Center For Advanced Studies)Institute of Technology(SSCASE)Islamabad43000Pakistan College of Science and Humanities Rumah Majmaah UniversityRumahKingdom of Saudi Arabia

Due to their complex structure,2-D models are challenging to work with;additionally,simulation,analysis,design,and control get increasingly difficult as the order of the model ***,in particular time intervals,Gawronski and Juang’s time-limited model reduction schemes produce an unstable reduced-order model for the 2-D and 1-D *** revealed some stability preservation solutions to address this key flaw which ensure the stability of 1-D reduced-order systems;nevertheless,these strategies result in large approximation ***,to the best of the authors’knowledge,there is no literature available for the stability preserving time-limited-interval Gramian-based model reduction framework for the 2-D discrete-time *** this article,2-D models are decomposed into two separate sub-models(i.e.,two cascaded 1-D models)using the condition of minimal *** reduction procedures are conducted on these obtained two 1-D sub-models using limited-time *** suggested methodology works for both 2-D and 1-D ***,the suggested methodology gives the stability of the reduced model as well as a priori error-bound expressions for the 2-D and 1-D *** results and comparisons between existing and suggested methodologies are provided to demonstrate the effectiveness of the suggested methodology.

关键词： Model reduction Weighted Gramian Limited interval Gramian Minimal realization Approximation error Error bound

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An Improved Deep Forest Classification and Intelligent Segmentation for skin Cancer Prediction Technique Inspired by Whale Optimization

An Improved Deep Forest Classification and Intelligent Segme...

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Advances in Modern Age Technologies for Health and engineering Science (AMATHE), International Conference on

作者： Siva Prasad Reddy K.V S. Meera Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Pallavaram Chennai

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

Fast malignant melanoma tumor identification is vital for successful therapy. Melanoma has now been universally acknowledged to be the most lethal form of malignancy over all else since, even if not caught and addressed promptly, it possesses a substantially higher propensity to migrate towards remaining regions of physique. Definitive presentation of various disorders relies largely on quasi therapeutic machine vision / procuring of disorders scanned pics. These methods offer a tool for autonomous image enhancement that allows for a quick and precise appraisal of the abscess. Deficiency of vast samples constitutes one of primary hurdles for designing a trustworthy autonomous classification scheme. This research suggests integrating Deep—learning & Image—processing to develop an algorithm for artificially recognizing melanoma. This survey's phase involves amassing a repository of dermoscopy pics, pre—Processing, separation utilizing hybridized Fuzzy-C-Means, and weighted enhancement employing the whale-optimization-algo. Following the subdivision of the dermoscopic imagery, the chapped skin cellular membranes traits are captured utilizing extraction of features. For the layering of the retrieved attributes, Long -shortterm -memory {LsTm}, bidirectional LsTm && Deep-Forest predictors are deployed. After using freely searchable sample group, the reported classifier reliability was Ninety Seven Percent && the segmentation effectiveness reached ninety three percent.

关键词： Hair Training Object segmentation Melanoma Feature extraction Solids Skin

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An Efficient Framework Classification for Diabetic Retinopathy Using MobileNetV2

An Efficient Framework Classification for Diabetic Retinopat...

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Jayaprakash Venugopal Kalaivani Kathirvelu Department of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Diabetes is a disorder marked by unregulated glucose levels in the body, potentially causing retinal damage and leading to irreversible visual impairment or loss. Diabetes affects the eyes, resulting in diabetic retinopathy, a prevalent medical disorder, especially among the elderly. Consequently, timely and precise diabetic retinopathy screening is essential for disease prediction. Nonetheless, conventional manual detection is labor-intensive and often results in misdiagnosis for several individuals. In this study, we devised a deep learning (DL) model using transfer learning from the MobileNetV2 architecture, accompanied with an innovative color version preprocessing approach. It decreased the training duration and achieved an average accuracy of 0.93 when applied to the new Kaggle dataset “APTOS 2019 Blindness Detection.” Furthermore, to mitigate the issue of overfitting in the long term, we used Stratified K-fold cross-validation.

关键词： Training Deep learning Diabetic retinopathy Accuracy Visual impairment Transfer learning Computer architecture Color Blindness Overfitting

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