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1st International Conference on AImL-Applications for engineering and technology, ICAET 2025

作者： Arumuganainar, Adityan Kushal Abhishek, P.D. COEP Technological University Pune India B.M.S. College of Engineering Bangalore India Vellore institute of technology Vellore India

ISBN: (纸本)9798350355611

The emergence of LLms (large language models) has proved to be an exceptional game changer for various industries as they have operated effectively and excelled across multiple domains. In this regard, the most effective approach is studied through rule-based LLms, specifically the LLms used for diagnosing hydraulic pump defects, paying special attention to triplex hydraulic pumps. As is well known, machine learning algorithms are of practical use in real-time situations only if large labeled datasets and features are available. leveraging LLms to derive and refine diagnostic rules based on descriptive data patterns, a novel, interpretable approach is proposed that significantly enhances fault classification accuracy, achieving a final accuracy of 68.25%. The approach allows the most common defects to be well recognized: blocked inlets and bearing wear as well as seal leakage and their combinations. This highlights the potential of using LLms techniques in today's intricate engineering systems for evaluation. © 2025 IEEE.

关键词： Hydraulic equipment

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Linear bit-by-bit Encoding and its Application

Linear Bit-by-Bit Encoding and its Application

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2023 IEEE International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security, iQ-CCHESS 2023

作者： mathews, Daniel B.M.S. Institute of Technology and Management Information Science Engineering Department Bengaluru India

ISBN: (纸本)9798350314946

In computer terminology, encoding is the process of placing a specific code or a sequence of characters (in the form of certain symbols, punctuation, numbers, or letters) into a specific format for storage or efficient transmission. Today, quantum computers have been pitched to deliver the computing power necessary to solve computationally complex problems, that are currently thought to be difficult for classical computers. With the arrival of quantum machine learning algorithms, it has become important to explore unique methods of encoding and compressing data with qubits. In this paper, we will explore the possibility of linear bit-by-bit data compression in the state vector of a multi-qubit system. We will achieve this, by looking at a brief introduction to the topic, a possible way by which we could encode bits in a state vector and whether this system of encoding can be applied to a real time system. We will also elaborate on a possible application through a proposed protocol for secure communication, and suggest a further line of discussion on this topic. © 2023 IEEE.

关键词： Digital storage

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machine Utilization Prediction in Cloud Using Informer model 4

Machine Utilization Prediction in Cloud Using Informer Model

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

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

ISBN: (纸本)9798331529635

This study investigates CPU utilization prediction in cloud environments using the Informer model, a deep learning framework optimized for long-sequence forecasting. by leveraging its ability to capture complex temporal patterns, the Informer model is benchmarked against GRU, LSTm, Prophet, and XGboost across diverse CPU utilization datasets. Performance is evaluated using RmSE, mSE, mAE, and mAPE metrics. Experimental results demonstrate that the Informer model significantly outperforms the comparison models, excelling in capturing both gradual trends and abrupt fluctuations. Specifically, the Informer achieved a 47.51% reduction in RmSE over GRU, 49.90% over LSTm, 67.36% over Prophet, and 50.46% over XGboost. These findings underscore the Informer model's superior adaptability and precision, making it a robust solution for dynamic resource utilization prediction in cloud environments. Its predictive accuracy is pivotal for enhancing workload management and optimizing resource allocation. © 2024 IEEE.

关键词： Prediction models

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Workability Studies on Al6061 Alloy and Al6061 metal matrix Composites Reinforced with Silicon Carbide Particles Under Cold backward Extrusion

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Journal of The Institution of Engineers (India): Series D 2023年第1期104卷 373-389页

作者： Venkatesh, R. Niranjan, C.A. Srinivas, S. Raghavendra, T. BOSCH India Limited Karnataka Bengaluru India Department of Industrial Engineering and Management Ramaiah Institute of Technology Karnataka Bengaluru India Department of Mechanical Engineering B.M.S College of Engineering Karnataka Bengaluru India Department of Mechanical Engineering National Institute of Engineering Karnataka Mysuru India

In the present work, the effect of cold backward extrusion on non-annealed and annealed Al6061 alloy and Al6061 metal matrix composites (mmCs) reinforced with SiC particles is analysed. The specimens were machined to prescribed size and subjected to cold backward extrusion. brinell hardness and Ultimate Tensile Strength (UTS) were determined before and after annealing. microstructure was examined using optical microscope. Scanning electron microscope was used to analyse specimen fracture surface. Al6061-mmCs containing 10% SiC particulates demonstrated better hardness of 62 bHN (without annealing) and 108 bHN (with annealing) compared to base Al6061 alloy. Improved hardness was observed in base alloy as well as composites after cold forging. microstructure features revealed distribution of large and small grains in Al6061 alloys and comparatively smaller grain distribution in Al6061-mmCs, Zinc stearate lubricant was applied to work piece to minimize the friction between punch and work piece. Fracture of both Al6061 alloy and mmC was observed during backward extrusion due to brittleness of material and induced stresses during casting and machining (without annealing). Some of the common defects such as centre burst and surface cracking were also observed in both as-cast alloy and composites (without annealing). Annealed base alloy and mmC demonstrated good quality of extrusion without surface defects under cold forging conditions. Overall it can be concluded that cold backward extrusion is not advisable for Al6061 alloy and composite without annealing. © 2022, The Institution of Engineers (India).

关键词： Tensile strength

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Taguchi Analysis for Wear Characteristics of Al6063 Alloy–Zirconium Silicate Composites

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Journal of The Institution of Engineers (India): Series D 2024年 1-16页

作者： Kumar, R. Vijaya Venugopal, m.m. Christiyan, K. G. Jaya balachandra, P. Raju, T. Hemanth manjunatha, b. Jagadeesha, T. Rangaswamy, Nikhil manjunath, G.A. Udayashankar, S. Aeronautical Engineering Department MVJ College of Engineering Karnataka Bengaluru560067 India Aeronautical Engineering Department Nitte Meenakshi Institute of Technology Karnataka Bengaluru560064 India Mechanical Engineering Department M S Ramaiah Institute of Technology Karnataka Bengaluru560054 India Department of Mathematics S J B Institute of Technology Karnataka Bengaluru560060 India Mechanical Engineering Department New Horizon College of Engineering Karnataka Bengaluru560103 India Mechanical Engineering Department National Institute of Technology Kerala Calicut673601 India School of Mechanical Engineering REVA University Karnataka Bengaluru560064 India Mechanical Engineering Department K. L. S. Gogte Institute of Technology Karnataka Belagavi590008 India Mechanical Engineering Department VTU Karnataka Belgaum590018 India

In this work, an analysis of the wear behaviour of composites consisting of zirconium silicate and Al6063 was attempted. This composite was fabricated using the stir casting technique. There were variations in the zirconium silicate particles in increments of 0%, 3%, 6%, 9%, and 12%. Utilising Pin-on-Disc wear testing apparatus, the wear behaviour of Al6063–Zirconium Silicate composites was investigated. The design of the tests, which was developed by applying Taguchi’s method, was followed when conducting the trials. The zirconium silicate particles are uniformly dispersed throughout the Al6063 matrix, as seen by the scanning electron micrographs of the Al6063–zirconium silicate composites. Using a universal testing machine, the tensile strength of the produced composites was evaluated. The brinell Hardness Testing apparatus was utilised in order to perform the task of determining the level of hardness possessed by the composite materials that were developed. When zirconium silicate particles are added, the composites’ tensile strength and hardness both increases. It is possible to see grooves in the SEm micrographs of the Al6063–zirconium silicate composites’ worn-out surfaces. With rise in load, the quantity of wear debris in the composite material likewise increases. The sliding distance, followed by speed, weight percentage, and load, is the most significant factor to take into account, according to the results of the Taguchi test. Automotive parts including cylinders, pistons, and brake drums are made of the created composites. © The Institution of Engineers (India) 2024.

关键词： Wear of materials

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Comparative Analysis of Drone Detection model Using YOLO Versions 6

Comparative Analysis of Drone Detection Model Using YOLO Ver...

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6th International Conference on Computational Intelligence and Communication Technologies, CCICT 2024

作者： Vashisht, Rohit Thakral, Gagan Sharma, Rahul Kumar Kaur, Gurminder Singh, Anurag KIET Group of Institutions Delhi-NCR Ghaziabad India B.M.Institute of Engineering & Technology Sonepat India G L Bajaj Institute of Technology & Management Greater Noida India

ISBN: (纸本)9798350374629

This article discusses a structured way for categorizing drones that combines deep learning with a number of other methodologies. It is impressive that this method was able to identify both fixed and moving objects with great accuracy. The You Only Look Once (YOLO) object detector is a well-liked and efficient method for object recognition. Convolutional Neural Networks (CNNs) have been developed for the analysis of visual data, automatically learning hierarchical representations of features from raw pixel inputs. The model is trained using the required dataset for 120 iterations in order to identify drones. In general, deep learning methods have transformed the field of computer vision, enabling impressive improvements in a range of tasks like picture classification, object recognition (including drone detection), segmentation, and image synthesis. To determine the optimum model for drone identification, different YOLOv7 models (YOLOv7, YOLOv7-X, YOLOv7-W6, YOLO-E6, YOLOv7-D6, and YOLO-E6E.) are compared. ©2024 IEEE.

关键词： Drones

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EmG Sensor-based Exoskeleton for Knee Injury Rehabilitation

EMG Sensor-Based Exoskeleton for Knee Injury Rehabilitation

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2024 International Conference on Smart Systems for Applications in Electrical Sciences, ICSSES 2024

作者： Harish, Prakruthi Harish, Prathiksha Krithik Raj, K. Prakash, Prajval Jisha, P. Dr. Ambedkar Institute of Technology Bengaluru Department of Medical Electronics Engineering India B.M.S. College of Engineering Bengaluru Department of Medical Electronics Engineering India

ISBN: (纸本)9798350364040

Effective rehabilitation techniques are now critically important due to the rise in the number of knee surgeries performed worldwide, including total knee arthroplasty (TKA) and anterior cruciate ligament (ACL) reconstruction. This research presents a prototypical model of a lower limb exoskeleton intended to support post-surgical recovery through precise control of leg movements and targeted muscle strengthening by addressing the notable gap in patient satisfaction caused by inadequate rehabilitation. This model aims to provide adaptive assistance that aligns with the user's physiological requirements by using: Electromyography (EmG) sensors for real-time feedback on muscle activity, mG995 servo motors for actuation, and Arduino UNO for processing. The exoskeleton guarantees compatibility with human movement dynamics by combining user-centric design principles and biomechanical considerations, such as ideal joint angles and load distribution, thereby improving the safety and efficacy of rehabilitation exercises. © 2024 IEEE.

关键词： Patient rehabilitation

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message from Program Chair: INNOCOmP 2024

Proceedings - 2024 International Conference on Emerging Inno...

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Proceedings - 2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOmP 2024 2024年 xx页

作者： mittal, Harish Kumar B M Institute of Engineering and Technology India

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machine learning facilitated the modeling of plastics hydrothermal pretreatment toward constructing an on-ship marine litter-to-methanol plant

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Frontiers of Chemical Science and engineering 2024年第10期18卷 105-117页

作者： Yi Cheng Qiong Pan Jie Li Nan Zhang Yang Yang Jiawei Wang Ningbo Gao Department of Chemical Engineering and Applied Chemistry Aston UniversityBirmingham B47ETUK Energy and Bioproducts Research Institute Aston UniversityBirmingham B47ETUK Centre for Process Integration Department of Chemical EngineeringSchool of EngineeringThe University of ManchesterManchester M139PLUK State Key Laboratory of Coal Combustion Huazhong University of Science and TechnologyWuhan 430074China School of Energy and Power Engineering Xi’an Jiaotong UniversityXi’an 710049China

An onboard facility shows promise in efficiently converting floating plastics into valuable products,such as methanol,negating the need for regional transport and land-based *** presents an effective means of processing plastics,requiring their transformation into gasification-compatible feedstock,such as *** study explores hydrochar composition modeling,utilizing advanced algorithms and rigorous analyses to unravel the intricacies of elemental composition ratios,identify influential factors,and optimize hydrochar production *** investigation begins with decision tree modeling,which successfully captures relationships but encounters overfitting ***,the decision tree vote analysis,particularly for the H/C ratio,yielding an impressive R2 of ***,the research delves into the economic feasibility of the marine plastics-to-methanol *** payback periods,driven by fluctuating methanol prices observed over a decade(ranging from 3.3 to 7 yr for hydrochar production plants),are *** factories emerge as resilient solutions,capitalizing on marine natural gas resources while striving for near-net-zero *** comprehensive study advances our understanding of hydrochar composition and offers insights into the economic potential of environmentally sustainable marine plastics-to-methanol processes.

关键词： marine plastics hydrothermal methanol machine learning technoeconomic assessment

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Shear Strength and Settlement Analysis of Stabilized Soil with GGbS and Cement

Shear Strength and Settlement Analysis of Stabilized Soil wi...

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

作者： Sekhar, Darshan C. Vinod, b.R. Raj, Anthony Shashank, S.T. Department of Civil Engineering BMS College of Engineering Bangalore India Department of Civil Engineering B M S Institute of Technology and Management Bangalore India

ISBN: (纸本)9789819925513

Construction on weak soils is difficult as it has poor bearing capacity and especially black cotton soil has high swelling or shrinking characteristics. Hence there is a need for the improvement in the soil properties, which can be addressed using stabilization of the soil. In this study, two soil types i.e., red soil and black cotton soil were replaced by different percentages of GGbS with small amount of cement. The improvement in shear properties, both in cohesion and friction of the soil was observed with all the combinations from laboratory testing. The settlements were analysed in PLAXIS 2D and was observed that within 7 days the settlement reduces by more than 60% in both the soil types with additives when compared to natural soils. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： bearing capacity

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