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Prediction of Pavement Maintenance Cost for Rural Roads at Network Level

Journal of The Institution of Engineers (India): Series A 2025年第2期106卷 489-509页

作者： Arun, V. Suresha, S.N. Department of Civil Engineering National Institute of Technology Karnataka Surathkal Karnataka Mangalore575025 India

Predicting pavement maintenance cost is an important factor for planning the budgetary requirements of any road agency at the network level. Pavement condition prediction models play a vital role in predicting pavement maintenance costs. Road agencies in developing countries like India still need pavement condition prediction models. The present study proposes an approach to help road agencies predict pavement conditions and annual maintenance costs. The proposed method was developed on rural roads of Shimoga district, Karnataka, India. The pavement condition data were collected using the Online Management Monitoring and Accounting System (OMMAS) database and by field visual inspection survey. A homogeneous Markov model was developed to predict the future pavement condition and estimate the rural road network's annual pavement maintenance cost. The study results indicated that 59% of the road network would come to a reconstruction state at a 10-year duty cycle if no maintenance is provided. Consequently, the annual maintenance cost predicted for 2031 was Indian Rupee (INR) 751.6 million, with an increase of 17% on average with each duty cycle. The model was validated along with the sensitivity analysis. The sensitivity analysis indicated improved pavement performance reduces maintenance costs and vice versa. The validation of the model was reliable, with a Pearson’s correlation R value of 0.92 and R square value of 0.86 at 95% confidence level. Hence, with this proposed approach, road agencies can predict the annual pavement maintenance cost so that they can plan their budget accordingly for an effective maintenance strategy at a network level. © The Institution of Engineers (India) 2025.

关键词： Markov processes

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Electro-discharge machining of microholes on 3d printed Hastelloy using the novel tool-feeding approach

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International Journal of Lightweight Materials and Manufacture 2025年第2期8卷 157-164页

作者： Korgal, Akash Shettigar, Arun Kumar P, Navin Karanth Kumar, Nishanth J, Bindu Madhavi Department of Mechanical Engineering National Institute of Technology Karnataka Surathkal 575025 India Central Research Facility National Institute of Technology Karnataka Surathkal 575025 India Department of Mechatronics Engineering Mangalore Institute of Technology and Engineering Karnataka 574225 India

Hastelloy, a nickel-based superalloy renowned for its exceptional resistance to corrosion at high temperatures, is widely used in sectors such as nuclear, aerospace, chemical processing, and pharmaceuticals. Microelectrical discharge machining (μ-EDM) is crucial for generating microholes and channels on Hastelloy. Since it effectively addresses difficulties like work hardening, high strength & wear resistance, and low thermal conductivity in traditional machining. Microholes play a major role in many critical components for precise control of fluids in fuel injectors, managing heat in turbine blades, controlled gas exchange, etc. The current research investigates the drilling of 8:1 aspect ratio microholes machined by 400 μm diameter electrodes. This study investigated the influence of tool material (tungsten carbide, carbide drill bit, and brass) on μ-EDM performance. Compared to tungsten carbide and carbide drill bits, brass exhibited significantly lower electrode wear, leading to more precise microholes with reduced overcut and taper angle. However, brass also required a substantially longer machining time. Carbide drill bits offered a balance between wear resistance, machining time, and overcut/taper angle. © 2024 The Authors

关键词： High temperature corrosion

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technology Interventions in Rural India by an Academic institute: Challenges and Mitigation Strategies

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Journal of Mechanical Design 2025年第7期147卷 071402页

作者： Prasad, Yashwant Bhat, Suraj Saha, Subir Kumar Ravi, M.R. Khadilkar, Pramod Department of Mechanical Engineering Indian Institute of Technology Delhi New Delhi110016 India Department of Mechatronics Engineering Mangalore Institute of Technology and Engineering Moodabidri574225 India Department of Design Indian Institute of Technology Delhi New Delhi110016 India

Industries often prioritize markets with high sales volumes and profit margins, showing little interest in developing technologies for low-income communities where demand and purchasing power are both low. More often, designers and researchers from various academic institutions voluntarily invest part of their professional engagements in developing technologies to enhance the livelihoods of low-income communities. However, academic professionals face several challenges, primarily due to their limited bandwidth in terms of their time and expertise. In this research, a methodology called action research was employed to identify the challenges faced by the above professionals in developing technologies for low-income communities and to propose strategies to address them. Seven identified challenges were classified under the four categories based on design projects spanning over nine years (2014–2022). As a result, a design framework comprising 12 strategies, grouped into four broad categories, is proposed. All 12 strategies were validated through their implementations in one of the projects of the Rural technology Action Group. Copyright © 2025 by ASME.

关键词： Product design

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Acoustic Event and Scene Classification: A Review

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SN Computer Science 2025年第1期6卷 1-17页

作者： Mulimani, Manjunath Venkatesh, Spoorthy Koolagudi, Shashidhar G. Department of Computer Science and Engineering National Institute of Technology Karnataka Karnataka Surathkal Mangalore 575025 India

This paper gives deeper insight into the range of recent approaches developed and reported in the literature specifically for monophonic acoustic event classification (AEC), polyphonic acoustic event detection (AED) and acoustic scene classification (ASC) concerning datasets, features and classifiers. A list of datasets used for monophonic AEC, polyphonic AED and ASC is introduced. The features and classifiers used for monophonic AEC, polyphonic AED and ASC are reviewed with their success and failures. A list of the research issues is derived from the critical review of the available literature at the end of the paper. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Acoustic scene classification Classifiers Fused features Monophonic acoustic even classification Polyphonic acoustic event detection

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A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems with Renewables and Plug-in Hybrid Electric Vehicles

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IEEE Access 2025年 13卷 74032-74046页

作者： Yarramsetty, Chiranjeevi Moger, Tukaram Jena, Debashisha Rao, Veeranki Srinivasa National Institute of Technology Surathkal Department of Electrical and Electronics Engineering Karnataka Mangalore575025 India Aditya University Department of Electrical and Electronics Engineering Surampalem Kakinada533437 India

This paper proposes a novel hybrid framework that integrates machine learning (ML) techniques with Sequential Monte Carlo Simulation (SMCS) to enhance the reliability assessment of modern power systems incorporating renewable energy resources (RER) and plug-in hybrid electric vehicle (PHEVs) integration. While PHEVs can leverage RER to significantly reduce greenhouse gas emissions, the increased energy demand from large PHEVs fleets poses potential challenges to power system reliability. To address these issues, this research presents an advanced mixed-integer linear programming (MILP)-based algorithm for optimizing EV charging. The algorithm prioritizes clean energy utilization through intelligent power allocation strategies while considering cost-revenue trade-offs. A probabilistic model is developed to account for factors such as driving distance, charging times, locations, battery state of charge, and charging needs of PHEVs. The proposed approach is tested on the IEEE RTS-79 test system and evaluates multiple ML architectures, including Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Transformer models, often combined with boosting algorithms, across three scenarios: base case, uncontrolled charging, and intelligent charging. Results highlight that ML-based approaches, particularly the Transformer model, achieve computational time reductions of up to 49% compared to traditional SMCS methods while maintaining comparable accuracy. The Transformer model identified 1,788 loss-of-load states compared to 1,510 actual instances, requiring only 176 minutes of computation. Among all models, the BiLSTM with Adaptive Boosting (BiLSTM+AB) achieved the lowest overestimation, exceeding actual instances by just 256 states. Performance metrics such as Loss of Load Probability (LOLP) and Expected Demand Not Supplied (EDNS) validate the effectiveness of the proposed ML approaches in balancing accuracy and computational efficiency. © 2013 IEEE.

关键词： Plug-in hybrid vehicles

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Effect of burnishing strategies on surface integrity, microstructure and corrosion performance of wire arc additively manufactured AZ31 Mg alloy

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International Journal of Lightweight Materials and Manufacture 2025年第3期8卷 355-373页

作者： Manjhi, Shambhu Kumar R, Oyyaravelu Bontha, Srikanth Balan, A.S.S. Department of Mechanical Engineering National Institute of Technology Karnataka Surathkal Srinivasanagar Karnataka Mangalore575 025 India School of Mechanical Engineering VIT University Vellore632014 India

AZ31 Mg alloy is an emerging material that has received considerable attention in aerospace, automotive, and temporary biodegradable implant applications owing to its attractive properties, such as low density, high specific strength, and biodegradability. Nevertheless, some shortcomings in Mg alloys are their low ductility, which is associated with challenging its manufacturing, and poor corrosion resistance associated with unreliable components. Therefore, a cold metal transfer wire arc additive manufacturing (CMT-WAAM) process is used to manufacture AZ31 Mg alloy and achieved 29.4 % ductility by controlling the gas porosity, keyhole porosity, and internal cracks. Further, severe plastic deformation is induced on the surface of deposited parts by low plasticity burnishing (LPB) with parallel and cross-pattern burnishing to modulate their surface to slow down the kinetics of the corrosion damage. The average surface roughness (Sa) of the cross-burnishing pattern is 0.235 μm, which is 123.6 % lower than the parallel burnished and 261.7 % lower than the milled specimens. The residual stress (RS) of WAAM is 40 MPa with a tensile nature;however, it is drastically reduced and develops compressive RS of 45 MPa under a parallel burnishing pattern and 62 MPa under a cross-burnishing pattern. Moreover, LPB with cross pattern deformed ∼395 μm depth of WAAMed AZ31 workpiece, which is ∼45 % higher than deformed depth (∼272 μm) by parallel pattern burnishing. The electrochemical corrosion rate of the WAAM specimen is 9.71 mm/year, and it is reduced to 1.82 mm/year under LPB caused by compressive residual stress and grain refinement. © 2024 The Authors

关键词： Magnesium alloys

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Water Level Monitoring and Mapping Seasonal Changes in the Reservoir Body Using Altimetry Data: A Case Study of Shivsagar/Koyna Reservoir 28th

Water Level Monitoring and Mapping Seasonal Changes in the R...

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28th International Conference on Hydraulics, Water Resources, River and Coastal engineering, HYDRO 2023

作者： Nalluri, A. Ramesh, H. Senior Research Scholar Department of Water Resources and Ocean Engineering National Institute of Technology Karnataka Mangalore India Professor Department of Water Resources and Ocean Engineering National Institute of Technology Karnataka Mangalore India

ISBN: (纸本)9789819774739

Water is essential to human existence, and current research emphasizes the need to monitor freshwater bodies. A considerable segment of India is presently struggling with a condition of water stress. Monitoring of rivers, reservoirs and lakes is always a booming question in a field of research where it comes to a question of minimal cost and time. Gauging stations are disappearing because of the high maintenance cost of Indian Reservoirs. The use of satellite data can help to aid in minimizing all these parameters with effective results. Monitoring of smaller reservoirs is highly unlikely to occur. Satellite altimetry has been successful in monitoring inland water bodies for the past three decades. The current study emphasizes using SARAL/Altika, one of India’s high-frequency satellites in the field of altimetry, to monitor water levels (WL) of Koyna Reservoir, which is located over the Koyna River in the state of Maharashtra, India. The seasonal water spread of the reservoir is mapped with the use of Landsat-8 imaging satellite, 30 m resolution, which has a particular band to monitor water. BRAT (Broad view radar altimetry toolbox) is used for processing SARAL. Bias correction is observed while calculating water level from altimetry which is mainly caused due to geography of the reservoir. The normalized differential water index (NDWI) is employed to derive the water spread area of the reservoir. A capacity survey of the reservoir is quantified, and a loss of reservoir storage over the years is calculated using a mathematical approach. SARAL/Altika and Landsat-8 data’s which are freely available and downloaded and processed from April 2013 to May 2016. SARAL/Altika derived WL has validated against the field WL. The coefficient of determination, R2 is 0.9 for all the years, and the root-mean-square error (RMSE) is found to be less than 0.3. Additionally, altimetry studies can be employed for deriving bathymetry information, monitoring river systems, reservoir operat

关键词： Rivers

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Enhancement in Loop Prevention Protocols: Dynamic Per-VLAN Multi-shortest Path Bridging (DV-MPB)

Enhancement in Loop Prevention Protocols: Dynamic Per-VLAN M...

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International Conference on Smart Systems and Wireless Communication, SSWC 2024

作者： Nagabhushanam, N. Abhishek Kumar, P. Pramod Chaitanya, D. Chandavarkar, B.R. Department of Computer Science and Engineering National Institute of Technology Karnataka Mangalore Surathkal India

ISBN: (纸本)9789819613472

Loops in a network pose significant challenges in modern communication systems, leading to congestion, performance degradation, and potential system failures. Additionally, loops can cause broadcast storms, impacting the network performance. While traditional loop prevention mechanisms like the Spanning Tree Protocol (STP) have been effective, the evolving complexity of network environments demands more efficient solutions. This paper provides a comprehensive review of loop prevention protocols, including STP, Rapid Spanning Tree Protocol (RSTP), Multiple Spanning Tree Protocol (MSTP), Shortest Path Bridging (SPB), and Per-VLAN Spanning Tree (PVST). Further, this paper introduces Dynamic VLAN - Multi-Shortest Path Bridging (DV-MPB) as a potential solution to enhance loop prevention efficiency. DV-MPB combines the strengths of SPB and PVST to achieve dynamic traffic optimization and reduce convergence time in loop prevention protocols. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： HTTP

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Advanced Breast Cancer Detection Using Spatial Attention and Neural Architecture Search (SANAS-Net)

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SN Computer Science 2025年第1期6卷 1-12页

作者： Souza, Melwin D. Ananth Prabhu, G. Kumara, Varuna Department of Computer Science & Engineering Sahyadri College of Engineering & Management Mangalore India Department of Electronics and Communication Engineering Moodlakatte Institute of Technology Kundapura India

This paper introduces a novel spatial attention neural architecture search network (SANAS-Net), which incorporates a spatial attention mechanism to enhance the model’s ability to focus on critical regions within mammograms. By utilizing multi-head attention within transformer blocks, the model captures diverse spatial relationships and interactions between features. Positional embeddings are incorporated into the transformer blocks, further enriching the model’s capacity to understand global spatial context. Extensive experiments were conducted to validate the proposed methodology. SANAS-Net was shown to successfully identify attentive networks that demonstrate high performance in distinguishing malignant from benign breast cancer cases. The model achieved a test accuracy of 89.95%, significantly surpassing the performance of previously proposed algorithms for breast cancer detection using mammography images. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Breast cancer detection Deep learning Mammography Neural architecture search Spatial attention

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Performance insights into multi-channel underwater optical wireless communication leveraging OFDM and alamouti diversity coding

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Optical and Quantum Electronics 2025年第1期57卷 1-21页

作者： Hemanth, C. Sangeetha, R.G. Krishnan, Prabu Singh, RudraPratap Tharun, P. Pankaj, S. Ramasubramanian, V. Kesavan, R. School of Electronics Engineering Vellore Institute of Technology Chennai India Department of ECE NITK Surathkal Mangalore India University of Victoria VictoriaBC Canada

Optical communication is increasingly studied for underwater communication owing to its potential for high data transfer rates, low latency, and energy efficiency compared to traditional acoustic methods. It can transmit data over shorter distances at much higher speeds, making it ideal for underwater exploration, environmental monitoring, and military operations. However, challenges like attenuation, absorption, and scattering limit its range and applicability. This paper presents the performance evaluation and design study of an underwater optical communication system for two water channels: river water and seawater. The performance of the channels was studied by considering underwater turbulence effects like attenuation, absorption, turbulence, salinity, temperature, and phase shift, which are known to degrade communication quality. This study deploys Differential Phase Shift Keying (DPSK) modulation, coherent detection, and Orthogonal Frequency Division Multiplexing (OFDM) to make the communication system even more robust under unfavourable circumstances. The DPSK modulation is used to encode the 16-bit input data sequence. This converts binary signals into two parallel sets of symbols from an M-ary constellation, allowing efficient data transmission. The Optical OFDM modulator then processes the encoded signals and combines them into a single signal for transmission. DPSK effectively handles phase shifts without reference signals, making it ideal for challenging environments like underwater communication. Diversity techniques such as Alamouti coding used for space-time block coding enhance signal strength by reflecting spatial diversity. Further, it combats fading and other impairments typically encountered in underwater channels. In this study, we leveraged this coding strategy in conjunction with DPSK and OFDM to improve the performance metrics of the communication system. Thus, Alamouti-coded modulation techniques were investigated to improve the performance

关键词： Orthogonal frequency division multiplexing

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