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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Amrutha muralidhar Yathindra Lakkanna Department of Computer Science and Engineering B. M. S College of Engineering Bengaluru India Department of Fashion and Lifestyle Accessory Design National Institute of Fashion Technology Bengaluru India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

In the competitive landscape of online fashion retail, understanding and responding to customer sentiments is crucial for success. Our study addresses the challenge faced by retailers in effectively analyzing diverse customer feedback data to enhance their understanding of customer sentiments. We evaluate the performance of five machine learning models using techniques like word cloud examination, sentiment distribution assessment, and Latent Dirichlet Allocation. Our findings indicate that SVm and Logistic Regression emerge as the top-performing models, with SVm demonstrating superior accuracy and overall performance compared to the others. by using these methods, online stores may improve consumer satisfaction and obtain a competitive advantage in the market. This research contributes to broader industry advancements by providing clear guidance on leveraging machine learning for sentiment analysis in the online fashion retail sector.

关键词： Support vector machines Analytical models Logistic regression Sentiment analysis Visualization Accuracy Computational modeling User-generated content Tag clouds Data models

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Enhancing Cardiovascular Risk Prediction with an Ensembled model Approach

Enhancing Cardiovascular Risk Prediction with an Ensembled M...

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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Cherukuri, Phanindra Uma, Devarakonda Nanda, Pranamita Valluru, Dinesh Kaliappan, S. Pathuri, Siva Kumar burra, Krishna Priya Guntur Engineering College Department of CSE AP Guntur India B V RAJU Institute of Technology Narsapur Department of CSBS Telangana Medak India R. M. K College of Engineering and Technology Dept of CSE RSM Nagar Puduvoyal Thiruvallur Dst TN India MLRITM Engineering College Department of IT Telangana Hyderabad India Lovely Student Professional University Division of R & D Jalandhar-Delhi G. T. Road Phagwara India Koneru Lakshmaiah Education Foundation Dept of CSE AP Vaddeswaram India Amrita Sai Institute of Science & Technology Dept of CSE AP Paritala India

ISBN: (纸本)9798331539948

Accurate risk assessment methods are crucial for early intervention and prevention, as cardiovascular diseases remain the leading cause of mortality and disability worldwide. With the advent of deep-learning techniques, the creation of predictive models using extensive medical data has significantly increased. This article provides a comprehensive overview of current deep learning applications for cardiovascular risk prediction. It begins with a summary of conventional risk assessment techniques and their shortcomings, underscoring the need for more sophisticated predictive models. So, in this article we discussed the use of ensembled techniques for predicting cardiovascular risk, and highlighting the need for more sophisticated models and also the limitations of conventional risk assessment methods which in turn tells the need for more sophisticated predictive models. The study proposes a heart attack prediction system using ensembled model along with data mining, achieving reliable results with minimal error rates. The study also introduces a novel classifier called the Ensembled Cardiovascular Disease Prediction Classifier (ECVDPC), outperformed when compared with base classifiers like Naïve bayes and Decision Tree i.e., 96%. © 2024 IEEE.

关键词： Prediction models

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Design and Numerical Investigation of FTO/TiO2/FA0.85Cs0.15Pb(I0.85br0.15)3/moO3/Au Perovskite Solar Cell

Design and Numerical Investigation of FTO/TiO2/FA0.85Cs0.15P...

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modeling, Simulation & Intelligent Computing (moSICom), International Conference on

作者： Paramita Sarkar Ashutosh Srivastava G. Narmada E.N. Nithin J. Naidu Department of ECE B.M.S. Institute of Technology and Management Bangalore India School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of ECE B V Raju Institute of Technology Narsapur India

The primary aim of the present work is to design a perovskite photovoltaic cell with higher efficacy that is suitable for practical applications. Therefore, a mixed perovskite layer composed of FA 0.85 Cs 0.15 Pb(I 0.85 br 0.15 ) 3 was used as the active layer. Along with this perovskite, TiO2 and moO3 have been used as electron and hole transport layer, respectively. The cell was optimized by varying the working temperature between 280K to 325K, absorber layer thickness between 100nm to 700nm, and bulk defect density between 1011/Cm-3 to 1016/Cm -3 . The final Optimized cell shows 1.53V open circuit voltage, 23.67mA/Cm 2 short circuit current, 85.63% of fill factor and 30.84% of efficiency at optimized temperature of 280K, optimized perovskite layer thickness of 700nm and bulk defect density of 10 11 Cm 3 . The present modeling technique is compared with the reported theoretical as well as experimental data that confirm the accuracy of the conclusions we have obtained for the proposed cell.

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Insights into the characteristics of corrosion products formed on the contact and exposed regions of C1045 steel bolt and nut fasteners exposed to aqueous chloride environments

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Journal of materials Science & technology 2023年第4期135卷 250-264页

作者： Enobong Felix Daniel Chao Li Changgang Wang Junhua Dong Inime Ime Udoh Peter Chukwuemeka Okafor Dongjiu Zhang Wenan Zhong Sheng Zhong School of Materials Science and Engineering University of Science and Technology of ChinaHefei 230026China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Environmental and Chemical Engineering Shenyang Ligong UniversityShenyang 110159China Corrosion and Electrochemistry unit Department of Pure and Applied ChemistryUniversity of CalabarP.M.B 1115 CalabarCross River StateNigeria Key Laboratory of Space Launching Site Reliability Xichang Satellite Launch CenterHainan Haikou 571126China

This study investigated the characteristics of corrosion products formed on the contact and exposed re-gions of C1045 steel bolt and nut fasteners exposed to aqueous chloride *** corroded sur-face morphology,rust compositions,and corrosion kinetics of the bolt specimen were studied by visual observation,optical microscopy(Om),scanning electron microscopy(SEm),X-Ray diffractometry(XRD),micro-Raman,electron probe micro-analyser(EPmA),and potentiodynamic polarization ***-sults obtained showed a variation in corrosion kinetics,morphology,and composition of the rust layer which were driven by differential aeration and concentration *** to the availability of sufficient dissolved oxygen,the oxyhydroxide compound,lepidocrocite(γ-FeOOH)was detected in the outer rust layer in the exposed region,whereas the inner rust layer was composed of magnetite(Fe_(3)O_(4)).How-ever,the oxygen-deficient contact surface revealed the presence of akaganeite(β-FeOOH)and magnetite(Fe_(3)O_(4))as dominant oxide *** most stable phase,goethite(α-FeOOH)was also detected in the rust formed in both regions,though in significantly low ***,owing to variation in environmental conditions,the amount and density of the rust layer varied in the different *** estimated corrosion stability values for the different regions revealed that the corrosion products formed on the steel surfaces were non-protective,suggesting the need for specific surface treatment as a protec-tive measure.

关键词： Carbon steel bolt-nut fastener Raman SEm-EDS XRD Rust characterization

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Design of P-Q Theory Controller based Solar PV System with Shunt Active Filter to Improve Power Quality 2

Design of P-Q Theory Controller Based Solar PV System with S...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Rayudu, Katuri Vijay muni, T. mustafa, mohd Subramaniam, G. Venkata Kishore, K. Lella, Venkata mahesh babu B v Raju Institute of Technology Dept. of Electrical and Electronics Engineering Telangana Narsapur India Koneru Lakshmaiah Education Foundation Dept. of Electrical and Electronics Engineering Vaddeswaram India Saveetha Institute of Medical and Technical Sciences Dept. of Electrical and Electronics Engineering Chennai India M.Kumarasamy College of Engineering Dept. of Electrical and Electronics Engineering Tamilnadu Karur India Nri Institute of Technology Dept. of Electrical and Electronics Engineering Agiripalli India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

In modern-day active filters are an excellent means of stabilizing harmonics in industrial facilities. There are many options available but no standard way to rate the active filters. SAPF's basic principles and theoretical concepts describe the filter and circuit design are allude to The power theory is used to design the PWm filter controller (p-q). A Simulink model was constructed to validate the shunt active filters. Studies have shown that the grid's power quality is verified © 2022 IEEE.

关键词： Active filters

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Study on the heat gain through a twin glass window (TGW) using an organic PCm

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materials Today: Proceedings 2022年 69卷 927-933页

作者： Sudha, D. Gopal, S. Raja Sowmiya, J.K. Kannadasan, b. Narayan, Puneet Ghosh, Tarun Department of Physics R.M.K. Engineering College Tamil Nadu Kavaraipettai 601206 India Department of Electronics & Communications Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram 522302 India Department of Civil Engineering Nehru Institute of Technology Tamil Nadu Coimbatore 641105 India Department of Civil Engineering B.S. Abdur Rahman Crescent Institute of Science and Technology Vandalur Tamil Nadu Chennai 600048 India Rajasthan 321303 India Department of Chemistry Aghorekamini Prakashchandra Mahavidyalaya West Bengal Bengai 712611 India

The glazed windowing systems are the essential components for a wide range of structures, and their heat transfer performance does have a substantial impact on increasing an human comfort as well as lowering electricity usage. The current study analyzes the heat transfer characteristics of a twin glass window (TGW) unit, under the influence of a commercially procured organic phase changing medium (PCm). The results have been compared the performance of the normal TGW without the presence of PCm and the inferences are discussed. The two TGW units had been erected in an prototype room space facing south direction in a South Indian region. Through a lengthy experimental investigation, the room space temperatures, glazing surface temperatures, transmittance of the glazing surface and the heat exchange rate across the TGW unit of both the normal TGW unit as well as PCm amalgamated TGW units were assessed. The testing findings demonstrated that amalgamating PCm is being a potential solution reduce the indoor temperature having TGW unit, without sacrifice of entering sun light inside the room space. by this way, it would help to reduce the cooling load of the air-conditioning system, which results in the reduction of total eenrgy consumption of the building space. © 2022

关键词： Glass

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Text Transmission Through Li-Fi in WSN Using Smart based Secure morse Code Algorithm

Text Transmission Through Li-Fi in WSN Using Smart Based Sec...

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2025 International Conference on multi-Agent Systems for Collaborative Intelligence, ICmSCI 2025

作者： Vasudevan, I. malathi, P. Siddik, S. Therasa, P.R. Nasurudeen, m.mohamed Charaan, R.m.Dilip Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Dept.of Cse Chennai India Saveetha College of Liberal Arts and Sciences Simats Dept of Computer Science India Pavaai Engineering College Dept.of Eee Namakkal India R.M.K Engineering College Dept.of Cse Kavaraipettai India V.S.B Engineering College Dept.of Cse Karur India

ISBN: (纸本)9798331509828

Cyber security is one the most challenging task in today's world. most of the existing Li-Fi technology in wireless sensor network is to detect the data within the short range of distance less accuracy. In this research, we proposed a Smart based Secure morse Code (SSmC) technique. Here there are two part, first is encoding and next is decoding. This proposed encoding technique takes user input in text based form and convert these text to standard morse code pattern and decoding does in the opposite direction. The transmitter parts encode the user input and send the pattern through laser module. The receiver part receives the pattern sends to microcontroller and then decodes and displays the data. In our experiment results shows that the proposed technique can transmit data over long distance with help of morse code encoding decoding algorithm. This technique takes 5ms for the whole transmission and process the transmission accurately. © 2025 IEEE.

关键词： Encoding (symbols)

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Prediction of Risk in Cardiovascular Disease using machine Learning Algorithms

Prediction of Risk in Cardiovascular Disease using Machine L...

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2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022

作者： Kurian, Nami Susan Renji, Kathu Sara Sajithra, S. Yuvasree, R. Jenefer, F. Anne Swetha, G. Rajalakshmi Institute of Technology Department of Electronics and Communication Engineering Chennai India V.S.B Engineering College Department of Biomedical Engineering Karur India R.M.K Engineering College Department of Computer Science and Engineering Tamilnadu India Panimalar Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9781665478847

Prediction of heart disease is one of the most complex tasks in medical field and prior detection of heart disease become an area of research to save patient lives. During the pandemic period, the number of cardiac arrest cases at home has drastically increased due to inaccurate predictions and delay in seeking medical attention. The health care industry works on processing of huge data and the solution for this is machine learning. Data science process large amount of data to make intelligent health care decisions thereby avoids risk and alert the patients. In this paper, a comparative analysis of different machine learning classifiers based on dataset to predict the chance of heart disease with minimal attributes. The mL algorithms used for HD prediction are K- Nearest Neighbour, Gradient boosting Classifier, Support Vector machine, Naive bayes, Logistic Regression and Random Forest algorithm. The paper also finds the correlation between different attributes and hence using them efficiently for prediction of heart attack. © 2022 IEEE.

关键词： Forecasting

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microstructure and particle size effects on selected mechanical properties of waste glass-reinforced aluminium matrix composites

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materials Today: Proceedings 2022年 62卷 4589-4598页

作者： Abiodun balogun, Oluwatosin Adewale Akinwande, Abayomi Adesoji Adediran, Adeolu Adebayo Ogunsanya, Olusegun Oladele Ademati, Akeem Saravana Kumar, m. John Erinle, Tunji Titilayo Akinlabi, Esther Department of Metallurgical and Materials Engineering Federal University of Technology Ondo State Akure Nigeria Department of Mechanical Engineering Landmark University Kwara State Omu-Aran Nigeria Department of Materials Science and Engineering Hohai University Hohai China Department of Agricultural and Resource Economics Federal University of Technology Ondo State Akure Nigeria Department of Production Engineering National Institute of Technology Tamil Nadu Tiruchirappalli India The Federal Polytechnic Mechanical Engineering Department P. M. B 5351 Ekiti State Ado-Ekiti Nigeria Directorate Pan Africa University for Life and Earth Sciences Institute Ibadan Nigeria Department of Mechanical Engineering Science University of Johannesburg South Africa

The development of new lightweight engineering materials with highly improved mechanical properties has been a thought-provoking issue of materials engineering lately. The attempt being made by the industrial and academic bodies has engendered the shift to composite materials over conventional ones. Aluminium reinforced composites are now being used in the transportation industries such as automobile and aerospace. Waste glass is a hard ceramic material which is majorly made up of silica, it is cheap, available and can serve as a replacement for costly reinforcement like silica, silicon carbide and titanium carbide. As a result, this research studied the effect of stir casting parameters (weight fraction of reinforcement and particle size) on the physical and mechanical properties of aluminium Al 6061/waste glass composites. The results obtained showed that density and fracture toughness of the samples reduced with an increase in weight fraction and particle size of waste glass. brinell hardness improved progressively with increase in the weight fraction of waste glass and a reduction in particle size. Tensile strength improved from 0 to 8 wt% after which a reduction was noted at 10 wt% for samples reinforced with −6 µm particle size while 6 wt% reinforcement had the best tensile strength for samples reinforced with −13 µm and –23 µm particles sizes. The morphology examined showed the interfacial interaction between matrix and reinforcement in relation to mechanical properties. The study established the effectiveness of the composites as compared to the pure matrix which made them better candidate materials for various engineering applications like automobiles. © 2022

关键词： Particle size

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SCAPS-1D based Analysis of Novel Absorber ASrTSe Stacked CZTS Thin Film Solar Cell

SCAPS-1D Based Analysis of Novel Absorber ASrTSe Stacked CZT...

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engineering and technology (PICET), Parul International Conference on

作者： Ashutosh Srivastava Gajendra Sharma Paramita Sarkar Payel Deb School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of ECE B.M.S. Institute of Technology and Management Bangalore India Mechanical Engineering Department PIET Parul University Gujarat India

ISBN: (数字)9798350369748

ISBN: (纸本)9798350369755

Device performance improvement of Thin Film So- lar cells (TFSC) through stacking of various absorber layers has been of great importance these days. In this paper, Novel absorber material Ag2SrSnSe4 (ASrTSe) has been stacked with existing Cu2ZnSnSe4CZTSe as a p-type absorber layer in most studied TFSC and the device performance has have been studied. For simulations, Solar Cell Capacitance Simulator (SCAPS 1-D) has been used. A promising Power Conversion Efficiency (PCE) of 21.16 % has been obtained showing an improvement from 18.06 % PCE in basic ASrTSe based solar cell.

关键词： Performance evaluation Photovoltaic cells Stacking Capacitance Power conversion

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