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Journal of Solid Waste technology and management 2022年第1期48卷 100-109页

作者： Velumani, P. Department of Civil Engineering B.M.S Institute of Technology and Management Bengaluru560064 India

In this study, Textile industry and Paper industry sludge were collected, studied, analyzed, proportioned and optimized for the production of construction materials like fly ash bricks, paver blocks, concrete blocks etc. Studies were done as per the recommendations of bIS standards. The study shows feasible waste utilization by replacing cement with two industrial sludges (textile and hypo sludge) up to 30% in different building materials like bricks, hollow concrete blocks, paver blocks and other concrete works. © 2022 Widener University School of Civil engineering. All rights reserved.

关键词： Fly ash

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Design and Feasibility Analysis of a Solar PV and biomass-based Electric Vehicle Charging Station for metropolitan Cities (India)

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Distributed Generation and Alternative Energy Journal 2022年第3期37卷 793-818页

作者： boddapati, Venkatesh Rakesh Kumar, A. Prakash, D.b. Arul Daniel, S. B.M.S College of Engineering Bangalore India National Institute of Technology Tiruchirappalli India

This paper presents the Electric Vehicle Charging Station (EVCS) design and feasibility analysis using hybrid energy sources such as Solar PV, biomass, and Diesel generators for India's metropolitan cities. The planned EVCS is precisely modelled and simulated by using HOmER software. The performance of the EVCS is analysed by adopting different configurations, and the techno-economic performance of the proposed system is presented in detail. The system's optimum configuration is analysed by considering the different case studies, and the results are compared. Further, the design and performance of the EVCS are performed for four metropolitan cities in India, such as Delhi, b.mbay, bangalore and Chennai, and the performance parameters are compared. © 2021 River Publishers.

关键词： biomass

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Comparative Study to Investigate the Suitability of Sustainable Alternatives in Enhancing Strength Characteristics of black Cotton Soil

Comparative Study to Investigate the Suitability of Sustaina...

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NProceedings of the National conference on Advances in Construction materials and management (ACmm 2022)

作者： Asha, m.N. Vinod, b.R. Anthony, R. Akshit Jain, J. Department of Civil Engineering M S Ramaiah Institute of Technology Bengaluru560054 India Department of Civil Engineering B M S Institute of Technology and Management Bengaluru560064 India

ISBN: (纸本)9789819925513

In this paper, the suitability of three different alternatives viz., sisal fiber, brick powder mix, phosphogypsum in stabilizing lime blended bC soil is investigated. bC soil used for the experiments had a maximum dry density of 1.6 g/cc at an optimum moisture content of 22%. For preparing lime blended soil, different proportions of lime have been added viz., 2%, 4%, 6%, 8%, 10%, 12%, 14% and 16%. Since the present study focus on highway application, optimum proportion of lime has been decided based on California bearing Ratio (CbR value). From the experimental studies, optimum lime content was identified as 10% and to the lime blended bC soil, sisal fiber, brick powder mix, phosphogypsum has been added at different proportions to study their effectiveness. From the experimental results its observed that addition of 10% lime doubles the CbR value of the plain bC soil. Among the different stabilizers, addition of 0.8% of sisal fiber to the lime blended bC soil, increases the CbR value by four times that of the plain bC soil. based on the CbR value and recommendations given in IRC 37: 2001, pavement cross sections are arrived at for different dosages/proportions of stabilizer. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Lime

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EfficientNet-b7 framework for anomaly detection in mammogram images

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multimedia Tools and Applications 2025年第11期84卷 8995-9021页

作者： H S, Sushma Sooda, Kavitha Karunakara Rai, b. CS & E B.M.S. College of Engineering Bull Temple Road Karnataka Bengaluru560019 India E & CE Nitte Meenakshi Institute of Technology Yelahanka Karnataka Bengaluru560064 India

At present, handling imbalanced data, deciphering complex data patterns, selecting suitable unsupervised learning algorithms, and ensuring computational efficiency are among the challenges associated with identifying anomalies in mammography images. To address these issues, the development of a robust machine learning model with effective training is imperative. This work aims to enhance accuracy and feature extraction mechanisms for the detection of abnormalities in mammogram images. It tackles these challenges and explores potential strategies to mitigate them, ensuring optimal performance of the model. The objective of the system is to employ an efficient technique for anomaly detection in mediolateral oblique (mLO) view and cranial-caudal (CC) view of 46,465 mammography images. The proposed approach introduces ensemble learning, where the ensemble members include the k-nearest neighbors (KNN) and Random Forest models. Additionally, it integrates a deep learning approach utilizing the EfficientNet-b7 architecture through transfer learning. The results of the proposed approach indicate a 18.72% reduction in memory consumption and an impressive accuracy of 98.86%. This outperforms the standalone system, where memory consumption and accuracy stand at 22.84% and 95.81%, respectively. © The Author(s), under exclusive licence to Springer Science+business media, LLC, part of Springer Nature 2024.

关键词： Anomaly detection

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Design and Robustness Analysis of a Wave-based Controller for Tethered Towing of Defunct Satellites

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 278-280页

作者： Rui Qi Yang Zhang Krishna D.Kumar the School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China IEEE the Department of Aerospace Engineering Ryerson UniversityToronto M5B 2K3Canada

Dear Editor, A microgravity environment in space, the elasticity of the tether,and complex flexible appendages make the tethered-towing system a nonlinear and underactuated system, which is sensitive and difficult to stabilize. This letter develops a controller based on wave propagation for tethered towing of defunct satellites, and carries out a robustness analysis of the controller via numerical simulation.

关键词： system elasticity letter

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multivariate Time series Forecasting for Cloud machine Utilization 3

Multivariate Time series Forecasting for Cloud Machine Utili...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Naik, Archana Sooda, Kavitha Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Bangalore India Department of Computer Science and Engineering B.M.S. College of Engineering Bangalore India

ISBN: (纸本)9798331527549

The cloud machine utilization prediction using a multivariate time series model is explored in this study. The cloud machine usage data set samples are selected with varied patterns. The long sequence forecasting model Informer is investigated for the forecasting. The model results are benchmarked against LSTm, GRU, Prophet, and XGboost across the diverse datasets. The performance is evaluated using RmSE. Experimental results show that the Prophet model performs best overall due to its ability to capture both seasonal and irregular patterns accurately. The RmSE value for Informer is 0.13, Prophet is 0.097, XGboost is 0.096, LSTm is 0.1725, and GRU is 0.1547. © 2025 IEEE.

关键词： Time series

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A Novel Deep Learning model for Effective Story Point Estimation in Agile Software Development

A Novel Deep Learning Model for Effective Story Point Estima...

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2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOmP 2024

作者： Kumar mittal, Harish Arsalan, mohd Garg, Puneet B M Institute of Engineering and Technology Deptt. of CSE NCR Sonepat India SAITM Delhi NCR Gurugram India

ISBN: (纸本)9798350376470

Effort estimation is crucial for successful software project management, with accuracy being pivotal for planning and monitoring. While traditional projects have seen extensive research in this area, agile development, particularly in estimating user stories and critical issues, lacks sufficient exploration. To address this gap, our paper introduces a tailored dataset for story points-based estimation, comprising 23,313 issues from 16 open-source projects. We propose a novel deep learning model, the Long-Deep Recurrent Neural Network (LD-RNN), combining LSTm and recurrent highway network (RHN) architectures. This end-to-end trainable system outperforms existing baselines and alternatives, enhancing accuracy in agile contexts. Our article provides a detailed analysis, covering dataset creation, LD-RNN model intricacies, experimental results, and implications for agile development. The findings contribute to the evolving landscape of agile software development, improving effort estimation through innovative deep learning methodologies. The LD-RNN model offers a promising avenue for more precise project planning and resource allocation in agile environments, addressing the unique challenges posed by user stories and issues. © 2024 IEEE.

关键词： Data accuracy

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Deep belief Network Optimization Using PSOGAA Algorithm for Efficient Crop Recommendation 5th

Deep Belief Network Optimization Using PSOGAA Algorithm for ...

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5th International Conference on Cognitive Computing and Information Processing, CCIP 2023

作者： madhuri, J. Indiramma, m. Nagarathna, N. Department of Computer Science and Engineering Bangalore Institute of Technology Bangalore India Department of Computer Science and Engineering B.M.S. College of Engineering Bangalore India

ISBN: (纸本)9783031607240

The agricultural sector plays a crucial role in the development of an emerging economy, providing employment to a significant portion of the population. Selecting the most suitable crops based on specific weather and soil conditions is vital to maximize yield and ensure profitability for farmers, contributing to global food security. In this context, this paper introduces a crop recommendation model utilizing Deep belief Networks (DbN), fine-tuned by a hybrid optimization approach combining Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Adam optimization. To enhance the efficiency of DbN-based crop recommendation model, this paper proposes the PSOGAA algorithm, a novel hybrid optimization algorithm designed to optimize the DbN’s network structure. Subsequently, genetic operators featuring self-adjusting crossover and mutation probabilities are applied to further refine the PSO and explore a global optimization solution. Ultimately, this global optimization solution is employed to construct the network structure of the crop recommendation model. Experimental results demonstrate the superior performance of the proposed algorithm compared to other DbN optimization techniques, showcasing an average classification accuracy improvement of at least 2.3%. This emphasizes the effectiveness of the PSOGAA algorithm as an efficient DbN optimization technique. Focusing on four major crops in India—rice, sugarcane, maize, and finger millet—the crop recommendation model’s outcomes are compared with those of the DbN model optimized using alternative algorithms. The experimental findings highlight that the proposed hybrid optimization algorithm surpasses other optimizers, exhibiting enhanced accuracy in crop recommendations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Crops

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Parametrized Optimization based on an Investigation of musical Similarities Using SPARK and Hadoop

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SN Computer Science 2024年第1期5卷 78页

作者： Chaudhary, Savita Karthik, V. Shankar, R. Taranum, Ayesha Naresh, E. Department of Computer Science and Engineering Sir M Visvesvaraya Institute of Technology Bengaluru Bengaluru India Department of Information Science and Engineering Ramaiah Institute of Tech B’lore India Department of Computer Science and Engineering BMS Institute of Technology and Engineering Bengaluru India Department of Computer Science and Engineering Vidyavardhaka College of Engineering Mysuru India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India

The big data processing framework Spark is used to power a parameterizable recommender system that can make recommendations for music based on a user’s individual tastes and take into account a variety of musical tonal qualities. The system as it is presently built is completely scalable, which means that additional songs can be contributed to the data, the cluster size could be increased, and new types of audio information, in addition to more cutting-edge similarity evaluations, may be included. Another issue discussed in this research paper is the parallel collection of required audio characteristics on a computer cluster. Song recommendations for a dataset including more than 114,000 songs may be created on a Spark cluster with 16 nodes in under 12 s by integrating eight distinct audio feature types and similarity assessments. After the features have been retrieved, they are sent to the Spark-based recommender system to be processed. The calculated distance was displayed, examined, and graphically depicted. by computing the distance depending on the melody, rhythmic, and timbral components of the music, the final software controls song suggestion. © 2023, The Author(s).

关键词： big data Hadoop music information retrieval Optimization Spark

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On the microstructural, mechanical, damping, wear properties of magnesium alloy AZ91-3 vol. % SiCP-3 vol. % fly ash hybrid composite and property correlation thereof

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Journal of magnesium and Alloys 2025年第5期13卷 2374-2389页

作者： Gollapalli, Prince Pant, mridul Chandra, A.R. Anil Surappa, m.K. Department of Materials Engineering Indian Institute of Science Karnataka Bangalore560012 India Department of Polymer & Process Engineering Indian Institute of Technology Roorkee Saharanpur Campus Saharanpur247001 India Department of Mechanical Engineering B.M.S. College of Engineering Karnataka Bangalore560019 India INSA Senior Scientist and Adjunct Professor National Institute of Advanced Studies Karnataka Bangalore560012 India

A combination of hard (SiCP) and soft (fly ash) particulate reinforcements could be a strategy to enhance combination of multiple properties of magnesium and its alloys which otherwise suffer from low stiffness, low wear resistance, and many other critical properties. However, at present a comprehensive and robust map correlating different properties in particle-reinforced composites is much lacking. In this work, an industrial grade AZ91 magnesium alloy reinforced with hard SiC and soft fly ash particles (with 3 vol. % each), has been prepared using stir casting followed by hot extrusion at 325 ∘C with a ratio of 21.5. microstructure of the hybrid composite was characterized using optical and scanning electron microscopes. The composite exhibited a reduction in average grain size from 13.6 to 7.1 µm, concomitantly an increase in Vickers hardness from 73 to 111 HV. The tension-compression yield asymmetry ratios of the unreinforced alloy and hybrid composite were 1.165 and 0.976, respectively indicating higher yield strength for the composite under compressive load. The composite exhibited 76% improvement in damping capacity under time sweep mode, and 28% improvement at 423 K under temperature sweep mode. The tribological characteristics of the composite under dry sliding conditions at sliding speeds and loads in the range of 0.5 to 1.5 m s-1 and 10 to 30 N, respectively showed higher wear resistance than the unreinforced alloy. The composite showed 23% improvement in sliding wear resistance at a load of 20 N and a speed of 1 m s-1. Finally, efforts have been made to understand the influence of one property on the other by developing statistical property correlation maps from the properties obtained in this study and from the literature. These maps are expected to help in the design of hybrid metal matrix Composites for a variety of targeted applications in different sectors. © 2025

关键词： magnesium alloys

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