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Efficient Clustered Mean Forecasting for Time Series with Head-Based Aggregation 5th

Efficient Clustered Mean Forecasting for Time Series with He...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Anand, Piyush Ramesh, T. Agarwal, Trapty Preethi, D. Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Luknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

Green Clustered mean Forecasting (ECMF) for Time series is a novel forecasting approach that is capable of efficaciously aggregating the underlying additives of a time collection through combining the top-primarily based Aggregation (HBA) technique alongside the mean Forecasting (MF) method. ECMF may be utilized to detect and become aware of companies of time collection intently associated with every other, therefore taking into account extra correct and reliable forecasts. By way of counting on HBA to discover any patterns in the information and then imposing MF to generate forecasts from the ones styles, ECMF can offer more accurate and reliable forecasts than the prevailing strategies. Moreover, this technique is computationally green, due to the hierarchical shape of the data, which reduces the quantity of forecasting experiments wanted. The ensuing forecasts are also easier to examine, as they may be generated from a standard head-based totally version. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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Investigating Time Series Clustering Algorithms for Hyper Spectral Image Analysis 5th

Investigating Time Series Clustering Algorithms for Hyper Sp...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Mahalakshmi, R. Agarwal, Trapty Kudari, Jayashree M. Mehra, Ritika School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Time collection clustering algorithms (TSCAs) are of increasing significance within the evaluation and interpretation of hyper spectral image (HSI) facts. TSCAs are being used to become aware of spatiotemporal styles of spectral characteristics in HSI records by identifying areas of interest (ROIs) which can be associated with physical techniques and mapping the ones ROIs to clusters. One-of-a-kind clustering algorithms may be used to analyze HSI statistics and tease out diffused spatiotemporal modifications. This paper investigates the software of two exceptional TSCAs, particularly okay-method clustering and Self-Organizing Maps (SOMs) to HSI *** SOM set of rules changed into additionally capable of phase the hyperspectral facts into meaningful clusters primarily based on their spectral traits. The accuracy of the SOM results was also assessed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Self organizing maps

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Estimating Chlorophyll Content of Vegetation in Hyper Spectral Surface Images 5th

Estimating Chlorophyll Content of Vegetation in Hyper Spectr...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Kannagi, A. Adhikari, Manoj S. Manjula, H.M. Agarwal, Trapty Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

The Estimating Chlorophyll content material of vegetation in Hyper Spectral floor photos aims to create an automatic approach to accurately degree the concentration of chlorophyll in plant life using hyperspectral floor pix. This studies makes use of spectral evaluation and feature extraction techniques, mixed with machine studying techniques, to discover and quantify the awareness of chlorophyll from photosynthetic plants. The experimental results show that the approach has an amazing capability to discover plant life chlorophyll concentrations. This approach has correct accuracy and is beneficial inside the subject of precision agriculture for tracking the fertilizer software and nutrient imbalance of crop. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Concentrations Evaluation Photosynthetic

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Analysis of Applied Cryptography for Secure VoIP Communications 5th

Analysis of Applied Cryptography for Secure VoIP Communicati...

引用

5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： P, Anitha Agarwal, Trapty D, Ganesh Anand, Piyush School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

This paper presents an evaluation of the utility of cryptography for at ease Voice over net Protocol (VoIP) verbal exchange. It covers the fundamentals of secure conversation as well as elements of public key cryptography for at ease authentication and encryption. It also covers the hooked up consultation Protocol (ESP), a protocol utilized in VoIP for encryption and authentication in cozy communications. Subsequently, this paper examines the advantages of the usage of cryptographic techniques in VoIP as well as related safety challenges. The evaluation of the utility of cryptography for comfortable VoIP communications offers a foundation for the assessment of cozy communique protocols in VoIP implementations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication Protocol

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Adapting Existing Industrial Machines to the Internet of Things Paradigm 5th

Adapting Existing Industrial Machines to the Internet of Thi...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Bargavi, Manju Bhatt, Rahul K, Rama Krishna Agarwal, Trapty Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Adapting current business machines to the internet of things (Iota) paradigm offers many possibilities for commercial procedures to grow to be greater efficient, dependable, and cost-powerful. This paper offers a high-level review of ways existing business machines can be adapted to the Iota paradigm. by utilizing mounted communication protocols and rising technology which includes business net of things (Eliot) packages, commercial machines may be geared up with the potential to talk and interact with different gadgets within the network, creating a unified device of linked additives, which may be used to enhance procedure manage. Sooner or later, extending the scope of these structures via superior analytics and system getting to know can free up new possibilities in predictive preservation and wise automation that may further improve the adapted industrial machines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive analytics

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Optimal Location Based Fuzzy Logic Model for Underwater Communications 5th

Optimal Location Based Fuzzy Logic Model for Underwater Comm...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Agrawal, Jaishree Kalaiarasan, C. Agarwal, Trapty Ojha, Ananta Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India

ISBN: (纸本)9789819780426

The most beneficial location based totally fuzzy good judgment model for Underwater Communications is an advanced and innovative solution for conditions consisting of underwater navigation and verbal exchange, which requires cautious attention of various environmental factors. This version combines 3 special procedures for finding underwater items: the bushy C-method (FCM) technique for clustering, a fuzzy mapping method for locating and tracking gadgets, and a fuzzy common sense method for controlling. The FCM approach is used to create wonderful clusters of objects primarily based on attributes such as salinity, water temperature, and so forth. After which the bushy mapping technique is used to decide the nearest cluster to an object. Sooner or later, the bushy good judgment technique uses input from those clusters to generate top-rated navigation paths for the item being tracked. All 3 elements of this approach paintings together to allow more than one gadgets being tracked on the same time, and it can also make certain the item is constantly headed in the direction of the most fulfilling navigation path. This version gives stepped forward efficiencies in underwater communications and can help provide real-time situational recognition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mapping

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Navigating the Blockchain Landscape with a Comprehensive Survey of Smart Contracts, Ethereum, and Consensus Mechanisms 4

Navigating the Blockchain Landscape with a Comprehensive Sur...

引用

4th IEEE International Conference on Data Engineering and Communication Systems, ICDECS 2024

作者： Suresh Kumar, N. Dolly Brinthakumari, S. Partheeban, N. School of Computer Science and Engineering Ramanagara India Jagan Institute of Management Studies Department of Information Technology Delhi India New Horizon Institute of Technology and Management Department of Computer Engineering Thane India Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9798350393354

In the dynamic landscape of blockchain technology, this research paper meticulously explores and contrasts two pivotal paradigmsSmart Contracts and Traditional Contractswithin the overarching framework of decentralized agreements. In the pursuit of this, the research diligently examines the subtle differentiations inherent in the various aspects of execution, intermediaries, trust, transparency, speed, costs, flexibility, security, and enforceability. While Smart Contracts, executed automatically through code on blockchain platforms such as Ethereum, offer unprecedented efficiency and transparency, Traditional Contracts, reliant on manual execution and potential intermediaries like lawyers, maintain a familiar yet potentially more cumbersome approach. The research extends its focus to Ethereum, a groundbreaking blockchain platform, spotlighting its instrumental role in upholding data security and integrity. The subsequent challenge under consideration is Ethereum's key aspects, such as decentralization, immutability, cryptography, smart contracts, consensus mechanisms, transparent ledger, tamper resistance, encryption, and permissioned access. A pivotal facet of this study centers on the comprehensive examination and comparison of consensus mechanisms employed in blockchain systems. This research assesses and compares key parameters of prominent blockchain consensus mechanisms, emphasizing factors like accuracy, time efficiency, scalability, and energy efficiency. The research culminates in a robust conclusion that synthesizes key findings, emphasizing Ethereum's role in ensuring data security and integrity, and the intricate landscape of consensus mechanisms. © 2024 IEEE.

关键词： Smart contract

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CurMIM: Curriculum Masked Image Modeling

CurMIM: Curriculum Masked Image Modeling

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liu, Hao Wang, Kun Han, Yudong Wang, Haocong Hu, Yupeng Wang, Chunxiao Nie, Liqiang School of Software Shandong University Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences Jinan China School of Computer Science and Technology Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798350368741

Masked Image Modeling (MIM), following "mask-and-reconstruct" scheme, is a promising self-supervised method to learn scalable visual representation. Studies indicate that selecting an effective mask strategy is vital for MIM. However, existing approaches often rely on static pre-defined priors, which limit their ability to adapt mask strategies dynamically for network optimization. In this paper, we focus on the learning process of the network and introduce human-like curriculum into MIM for dynamic representation refinement, and propose an end-to-end framework Curriculum Masked Image Modeling (CurMIM). CurMIM consists of two components: Mask Priority Measurer, which acts as a curriculum learner to determine mask priority values using the network's intrinsic state information, and Dual Adaptive Selector, which serves as a curriculum scheduler to create effective masks based on these values. With negligible extra parameters, our curriculum-based method consistently establishes noticeable improvements across varying model sizes and benchmarks, showing effectiveness and generalization. © 2025 IEEE.

关键词： Curriculum Learning Image Representation Masked Image Modeling Visual Pre-training

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An In-depth Analysis of Spectroscopic Unmixing for Target Identification in Hyper Spectral Images 5th

An In-depth Analysis of Spectroscopic Unmixing for Target Id...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Yashaswini, K.A. Mishra, Awakash Zaidi, Taskeen Sumit School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

This summary offers an in-intensity evaluation of a system getting-to-know approach, particularly Spectroscopic Unmixing, for target identity in hyperspectral images. This parametric and pixel-smart linear decomposition technique generates spectral functions for each pixel, allowing the identity and extraction of various fabric signatures. The method is applied by fitting the information into a mathematical version, similarly used for unmixing. Different spectral fashions used within the literature have additionally been discussed. The research specializes in implementing the method and its applications for extracting items or substances in complex situations, including city, agricultural, or maritime imaging. Subsequently, the benefits and barriers of Spectroscopic Unmixing have been highlighted. The conclusion provides an insight into the performance of the technique for specific imaging eventualities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Pixels

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Wavelet-Based Time Series Forecasting for Wireless Sensor Networks 5th

Wavelet-Based Time Series Forecasting for Wireless Sensor Ne...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Murugan, R. Arya, Rakesh Kokila, S. Mishra, Awakash Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Wavelet-primarily based time series forecasting has been an effective device for Wi-Fi sensor network (WSN) packages. This approach has proven to provide correct forecasts for a selection of situations whilst enabling strength performance through decreased statistics storage and transmission bandwidth necessities. By means of extracting the vital time-related functions from sensor facts streams, records compression is executed at the same time as retaining the accuracy of the forecasts. Furthermore, with the aid of taking advantage of the multi resolution decomposition belongings of wavelets, this method can appropriately seize the temporal dynamics of the authentic signal. This permits better approximation of the underlying signal’s temporal correlations while as compared to other kinds of forecasting strategies. Additionally, wavelet-primarily based methods permit robust and green adaptation of the prediction fashions to changing sensor records, for this reason adapting the overall performance of the forecasts to exclusive situations. All these homes make wavelet-based time series forecasting an appealing choice for WSN programs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wireless sensor networks

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