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检索条件"任意字段=5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023"

共 2622 条记录，以下是161-170 订阅

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Optimizing Wireless Sensor Network Connectivity Using Math Modeling Techniques 5th

Optimizing Wireless Sensor Network Connectivity Using Math M...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Gobi, N. Bhatnagar, Gunjan Bhavana, A. Mishra, Awakash Karnataka Bangalore India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon 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

Wi-Fi sensor networks (WSNs) are extensively deployed in various programs and have an increasing significance within the net of things (Iota). However, their connectivity remains a chief challenge, especially in large-scale networks, as it's far crucial for reliable communication and green statistics aggregation. To address this project, this paper presents a unique method to optimize the connectivity of WSNs through utilizing mathematical modeling techniques. Mainly, nonlinear optimization methods are hired to acquire a surest deployment sample for a given community configuration that maximizes the connectivity metric. the proposed method is proven to provide better connectivity outcomes than conventional solutions and is analyzed each theoretically and empirically with extensive simulations. Simulation outcomes additionally show that the method is robust to various node deployment techniques. Furthermore, it is evaluated using exceptional styles of environments and a huge variety of community configurations. the offered outcomes demonstrate the versatility and scalability of the proposed optimization method in optimizing the connectivity of WSNs. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sensor nodes

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the Smart and Secured Communication Using Applied Cryptography Algorithms 5th

The Smart and Secured Communication Using Applied Cryptograp...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Agarwal, Trapty Jebakumari, S. Adlin Hemlata Ayesha, Amreen Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Department of Computer Science & Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

this paper describes the implementation of a at ease communication device the usage of an implemented cryptography algorithm. the gadget is designed to provide comfy statistics and voice communique between endpoints using techniques consisting of encryption and digital signature. the applied cryptography set of rules includes primary components, the symmetric and the uneven algorithms. the symmetric algorithms, along with AES and DES, are used for statistics encryption, even as the uneven algorithms, which include RSA and DSA, are used for virtual signature. the proposed gadget additionally focuses on security of physical places to defend the important thing exchange by means of the use of physical access control measures which include biometric identification. the system additionally employs advanced safety strategies together with message authentication codes and protection protocols like SSL/TLS. the device is examined for robustness and safety using real communique experiments. the results confirm that the proposed machine is cozy and green in supplying comfortable communication among endpoints. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Implementing Cryptographic Algorithms for Securing Online Transactions 5th

Implementing Cryptographic Algorithms for Securing Online Tr...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Bhuvana, J. Bhatt, Rahul Metre, Prakash B. 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

Cryptographic algorithms are critical in securing online transactions. they provide relaxed verbal exchange channels for fairly touchy statistics that wishes to be reliably transmitted among a couple of remote events. Cryptographic algorithms permit for at ease authentication, confidentiality, non-repudiation, and integrity amongst events for their virtual activities. Implementing those algorithms is a complex procedure, however, due to the ever-changing nature of security threats, acquiring an expertise of the way to properly implement cryptographic algorithms becomes critical. this paper makes a speciality of how to correctly enforce cryptographic algorithms for securing on-line transactions. Precise topics consist of excellent practices for deciding on an appropriate algorithms, fine techniques for key distribution, necessary gadget necessities for cozy on line communications, the process for implementing them, and the importance of securely storing encryption keys. Via expertise the specified procedures and strategies, developers and users might be capable of correctly and securely make on-line transactions. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Examining Unsupervised learning Techniques for Economic Forecasting 5th

Examining Unsupervised Learning Techniques for Economic Fore...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Negi, Bichitra Singh Minish, T. N. Sterlin Mishra, Awakash Karthikeyan, M. Department of Civil 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 Bengaluru India

ISBN: (纸本)9789819780426

this newsletter examines a ramification of unsupervised mastering strategies for financial forecasting. the number one consciousness has been using strategies inclusive of k-suggest clustering and principal thing evaluation (PCA) to derive meaning from facts and generate forecasts for macroeconomic indicators consisting of gross home product (GDP) and stability of bills. We also discuss using neural networks (NNs) as software for unsupervised learning for monetary forecasting. Via a sequence of empirical experiments, we analyze and examine the forecasts generated through every unsupervised, gaining knowledge of methods for various macroeconomic indicators. the outcomes of the experiments suggest that NNs and PCA are most effective for monetary forecasting and discover that PCA is a promising tool for making forecasts with more excellent accurate effects than okay-manner. Moreover, the results offer insights on a way to use unsupervised learning for financial forecasting and suggest ability ways in which to enhance the accuracy of those forecasts. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decentralized finance

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Improving Medical Image Classification through Transfer learning and Meta learning 5th

Improving Medical Image Classification Through Transfer Lear...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Arora, Sonia Jebakumari, S. Adlin Singh, Vaishali Kharbas, Vikas Kumar Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India

ISBN: (纸本)9789819780426

this paper presents an observation of improving clinical picture classification via transfer getting to know and meta-studying. Switching getting-to-know and meta-learning methods are usually employed in medical imaging class tasks. Transfer studying objectives to switch information and illustration from a properly-trained version and mildew that expertise to higher healthy the problem at hand, while meta-gaining knowledge is a version of switch gaining knowledge of which targets to seize and adapt the generalizable expertise of a project domain, and to allow a progressed impact for the goal tasks. Inside the clinical imaging scenario, the two procedures can dig deeper into the several layers which might be involved in gaining deep knowledge of algorithms. the authors compare the effectiveness of the proposed strategies in five publicly available medical imaging datasets. Effects have shown that the proposed techniques notably advanced the usual type accuracy for a few datasets. Furthermore, it was found that the 2-step technique showed higher performance than the one-step technique. this study presents a higher understanding of the efficacy of transfer learning and meta-mastering techniques for clinical photo-type tasks. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive learning

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Distributed and Cooperative Security Mechanisms for Networked applications 5th

Distributed and Cooperative Security Mechanisms for Networke...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Kamalraj, R. Singh, Vaishali Bhambu, Pawan Wadhwa, Bhawna Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Engineering Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

Cutting-edge applications rely heavily on conversation via PC networks to provide improved functionality, multiplied interactivity, and more to get admission to sources. Cozy verbal exchange and gain control access should be enforced to shield information and different assets. Distributed and cooperative protection mechanisms enable exceptional components of a networked utility to collaborate for you to get the right of entry to resources responsibly, proportion records securely, and authenticate customers. Such mechanisms are regularly designed to offer automated authorization and authentication, secure conversation channels, and a cozy records garage. In addition, they usually include additives, which have users, roles, and permissions to assist in controlling access. Utility developers and IT directors can ensure that networked packages remain cozy no matter the ever-converting safety landscape by adopting allotted and cooperative safety mechanisms. Distributed and Cooperative security Mechanisms (DCSM) are community security mechanisms designed to provide a layered method to defend in opposition to cyber-attacks on networked applications. the use of DCSM permits a shift from traditional networks to an agile and resilient system structure that can react speedily to a capacity chance, mitigating the damaging effect of malicious attacks. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computer viruses

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Exploring Multi-Task learning for Transfer learning Based Active learning in Medical Image Segmentation 5th

Exploring Multi-Task Learning for Transfer Learning Based Ac...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Yadav, Surjeet Kumar, Arvind Kannagi, A. Sahoo, Girija Shankar Department of Mechanical Engineering Vivekananda Global University Jaipur India Department of Biotechnology Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Present methods for medical photograph segmentation have enabled clinical practitioners and researchers to apprehend and create unique interpretations ultra-modern clinical snap shots. But, there is nonetheless tons that may be stepped forward upon. Switch brand new-based energetic modern-day has been proposed to improve the accuracy cutting-edge deep today’s-based scientific photograph segmentation but the consequences are limited. Multi-project modern day, a contemporary transfer modern day, can further enhance the accuracy and robustness modern day segmentation. this research makes a specialty of exploring the efficacy contemporary multi-challenge learning, combined with switch present day based lively contemporary, in scientific image segmentation. In the long run, these research pursuits to take cutting-edge expertise associated with transfer cutting-edge based energetic latest and scientific photo segmentation and make bigger upon it to discover novel methods to improve average accuracy and robustness modern day clinical image segmentation. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Active learning

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Optimizing C-Band Antenna Performance through Integration with Frequency Selective Surfaces: Design and HFSS Analysis 5th

Optimizing C-Band Antenna Performance Through Integration wi...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Jyothi, N. Krishna Anusha, Chilupuri Department of Electronics and Communication Engineering G. Narayanamma Institute of Technology and Science Telangana Hyderabad India

ISBN: (纸本)9789819780426

this research focuses on the design and optimization of antennas tailored for C-band frequency applications, spanning the microwave range of 4GHz to 8GHz. Two distinct antennas are meticulously crafted to cater to specific advantages within this frequency band: one emphasizes superior bandwidth, while the other prioritizes enhanced return loss and minimized Voltage Standing Wave Ratio (VSWR) values. the integration of Frequency-Selective Surfaces (FSS) is employed to further enhance the performance parameters of these antennas. the entire design process, encompassing conceptualization, modeling, and simulation, is executed using the HFSS software—an advanced platform renowned for its capabilities in simulating and analyzing complex electromagnetic interactions. the antenna’s construction employs an FR4 epoxy substrate, featuring a dielectric constant of 4.4 and a substrate thickness measuring 1.6mm. Similarly, the FSS unit cell utilizes a substrate thickness of 1.6mm. the antenna is meticulously engineered to operate within the microwave C-band, spanning frequencies from 4GHz to 8GHz. Its primary design emphasis centers on highlighting the impact of Frequency-Selective Surfaces (FSS) on antenna performance. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Frequency selective surfaces

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Comparing Time Series Assist Vector machines and Recurrent Neural Networks for Hyper Spectral Image Popularity 5th

Comparing Time Series Assist Vector Machines and Recurrent N...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Goswami, Shubhashish Pasha, Afroz Mishra, Awakash Krishnamoorthy, Ramkumar Department of Computer Science & 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 Karnataka Bangalore India

ISBN: (纸本)9789819780426

this paper examines the overall performance of two system mastering models, Time series help Vector machines (SVMs) and Recurrent Neural Networks (RNNs), on classification of Hyper Spectral photographs (HSIs). the fashions are in comparison based totally on their recognition accuracy which includes the time requirements to build fashions. the paper additionally evaluates two varieties of preprocessing techniques: minimum Redundancy maximum Relevancy (MRMR) and precept aspect evaluation (PCA). the effects of the experiments highlight that SVMs and RNNs perform considerably distinct for HSI class and that counting on one version simplest may lead to exclusive type performance. Moreover, the experiments show that with increasing complexity, the quantity of time required to assemble the RNNs will increase significantly. the comparisons in the paper allow further exploration in the discipline and help the choice of the high-quality model with the aid of capacity practitioners and developers. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Recurrent neural networks

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Innovative Image Processing Techniques for Automating Cosmetic Inspection 5th

Innovative Image Processing Techniques for Automating Cosmet...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Panwar, Govind Singh Murthy, D.H.R. Agarwal, Trapty Jaison, Feon Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University 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

Progressive photograph processing techniques were developed for automating the technique of beauty inspection. these techniques make use of the wealthy, unique image records of the inspected objects to hastily become aware of diverse product defects. Specifically, object features including coloration, texture, size, shape, and location are first extracted from the photograph, and every function is then evaluated to come across cosmetic defects. Following the detection technique, the extracted capabilities are used to at once alter the manufacturing technique, enabling faster production turnaround times and progressed product quality. the strategies are designed to make certain rapid and accurate product inspection and also provide a bendy adjustment of parameters for various types of cosmetic merchandise. With these techniques, producers are capable of reduce cosmetically based totally product defects and supply improved great merchandise in a shorter time frame. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Inspection

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