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Hybrid β Ω-indexing based fractal antenna for multi-band wireless applications

Multimedia Tools and Applications 2025年第11期84卷 9537-9554页

作者： Sindhuja, N. M. Mary Department of Electronics and Communication Engineering Kamaraj College of Engineering & Technology Virudhunagar India

This research revolves around the design challenge of creating a compact, low-profile slotted fractal antenna with the capability to resonate across multiple frequency bands, thereby fulfilling the diverse requirements of modern wireless applications. In this novel research, we introduce a compact and low-profile slotted fractal antenna design, employing an inset-fed βΩ-space-filling curve, tailored for multi-band wireless applications and narrow-band operations. Through comprehensive fabrication and testing, we demonstrate excellent agreement between measured results—comprising reflection coefficient and E-plane and H-plane gain radiation patterns—and corresponding simulations. The antenna resonates at five distinct frequencies, each falling within narrow bands: 1.91GHz, 3.12GHz, 5.56GHz, 10.75GHz, and 13.94GHz. This broad resonance spectrum makes the antenna well-suited for various applications, including PCS-1900, rail mobile radio, DCS-IMT gap, WCDMA, X-band, and Ku-band services. By halving the ground length, we significantly enhance antenna parameters such as gain, directivity, and efficiency. Our innovative design also achieves excellent impedance matching via inset feeding with a 50Ω port, particularly notable at the operating frequency of 3.1GHz, where the antenna achieves a gain of 2.94dBi. Notably, we employ a hybrid βΩ-space-filling curve, a novel approach in slotted fractal antenna design. Fabricated on FR4 substrate, the antenna boasts compact dimensions of 39.05mm x 32.25mm x 1.6mm, ensuring practicality and versatility across diverse wireless applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Fractals

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An Experimental Investigation of Maximization of Output Power for the Different Position of Photovoltaic Panel with Minimal Area 3

An Experimental Investigation of Maximization of Output Powe...

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3rd IEEE International Conference on Power electronics, Intelligent Control and Energy Systems, ICPEICES 2024

作者： Babu, B. Gurukarthik Gobinath, M. Ramkumar, M. Vijay, K. Prabhu, R.Harihara Winston, D. Prince Kamaraj College of Engineering and Technology Department of Electrical and Electronics Engineering Madurai India Kamaraj College of Engineering and Technology Department of Electrical and Electronics Madurai India

ISBN: (纸本)9798350387193

This study focuses on the integrative experiment to explores the innovative strategies for maximizing the output power of photovoltaic panels through varied positions, coupled with a reduced panel area. By employing diverse orientations and controlled experiments, we aim to identify optimal configurations that balance energy efficiency with reduced spatial requirements. The research delves into the synergies between panel positioning and area reduction, offering insights into sustainable and creative approaches for enhancing the performance of photovoltaic systems in diverse environmental conditions. © 2024 IEEE.

关键词： Photovoltaics

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Sliding mode observer-based fault detection for helicopter system

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Journal of Control and Decision 2023年第4期10卷 465-475页

作者： M.Raghappriya S.Kanthalakshmi Department of Electronics and Instrumentation Engineering Government College of TechnologyCoimbatoreIndia Department of Electrical and Electronics Engineering PSG College of TechnologyCoimbatoreIndia

Fault detection of non-linear systems is of great importance in control systems *** faults could lead to irreparable *** paper deals with fault diagnosis of helicopter system in the presence of uncertainties and *** deal with sensor,actuator and component faults,the observer-based diagnosis scheme which employs sliding mode observer is *** are modelled as an additive and multiplicative fault which is introduced as an abrupt and intermittent fault into the *** inequality constraints and gain matrices are solved using a Lyapunov-based *** results display the effectiveness of the designed observer and the ability to handle faults.

关键词： Fault diagnosis sliding mode observer sensor actuator and component faults residual generation

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Evaluation of optimal responses in Monel 400 alloy using computer based unconventional machining process

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Interactions 2025年第1期246卷 1-11页

作者： Manohar, Gunaselvi Chandrasekar, G. Radhakrishnan, G. Raj, P. Anantha Christu Ram, S. Department of Electronics and Instrumentation Engineering Easwari Engineering College Chennai India Department Mechanical Engineering PSNA College of Engineering and Technology Dindigul India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Tamilnadu Coimbatore India Division of Robotics Engineering Karunya Institute of Technology and Sciences Tamilnadu Coimbatore India Department of Mechanical Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

The unconventional machining is an essential role in metal forming process. The dimensional accuracy and super finish are the main features of modern machining methods. Electric discharge machining is a competent process to any materials and composites. In this article is used to machining characteristics of Monel 400 alloy with monitored by computer networks. The response variables are mainly depending on input variables and their levels. Taguchi method is utilized to evaluate the optimal control factors. The mean and SN ratio is evaluated by based on the criteria of the responses. The involvement of control variables to the responses have been validated by variance analysis. The best possible MR was attained at a discharge current of 40 A, pulse on time of 140µs, and spark voltage of 25 *** finest RTW and SR was occurred at a discharge current of 40 A, pulse on time of 140µs, and spark voltage of 20 V. The scope of the work is to maximize the metal removal and minimize the tool wear. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Metal forming

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Skin lesion classification using transfer learning

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Soft Computing 2024年第20期28卷 12337-12343页

作者： Nivedhitha, G. Kalpana, P. Sidthik, A. Sheik Rani, V. Anusha Singh, Ajith B. Rajagopal, R. Department of Computer Science and Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering VSB College of Engineering and Technical Campus Tamilnadu Coimbatore642109 India Department of Electronics and Instrumentation Engineering Saveetha Engineering College Tamilnadu Chennai India Department of Electrical and Electronics Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering Francis Xavier Engineering College Tirunelveli India

This work presents an essential module for the Transfer Learning approach's classification of melanoma skin lesions. Melanoma, a highly lethal form of skin cancer, poses a significant health threat globally. Image analysis plays a crucial role in enhancing the accuracy of malignant skin lesion classification. Although neural networks trained on extensive datasets have emerged as the latest solution, their scalability remains a challenge. This study proposes an efficient method for classifying skin lesions utilizing labelled data from open sources, leveraging EfficientNet as the foundational model to robustly capture discriminative features from diverse visual perspectives. Validation of the proposed algorithms relies on the classifier's capacity to distinguish between classes is measured by the Area Under the Receiver Operating Characteristic (AUC-ROC) curve. AUC-ROC score greater than zero denotes better classification performance. Our proposed model achieves an impressive score of 98.65%. In contrast to existing approaches, our method demonstrates swift and accurate identification and segmentation of melanoma skin lesions, showcasing its efficacy in advancing the field of skin lesion classification. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Dermatology

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A Repository based Criminal Identification - Evolution in Forensics using Deep Learning 2

A Repository based Criminal Identification - Evolution in Fo...

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2nd IEEE International Conference on Contemporary Computing and Communications, InC4 2024

作者： Nancy Deborah, R. Alwyn Rajiv, S. Vinora, A. Soundarya, M. Vigneswaran, S. Shiivadhanush, K.V. Velammal College of Engineering and Technology Department of Information Technology Madurai India Kamaraj College of Engineering and Technology Department of Electronics and Communication Engineering Madurai India

ISBN: (纸本)9798350383652

Suspecting the criminal is a critical process during the early stages of the investigation at the crime scene. The forensic examiner should start the difficult process of thorough examination with the evidence collected from the crime location in order to imagine the circumstances leading up to the incident. A meticulously planned crime scene investigation with advancement technology is required here. Even though forensic science has made substantial progress, more investigation is needed to discover whether these advancements have any additional benefits for addressing criminal cases. By building and maintaining a database of criminals, the proposed model enables the police department to identify criminals using evidence gathered from crime scenes and a 'matching mechanism' to match the evidence with the database details. Maintaining a digital database of the relevant criminals' information and offering a simple matching mechanism via soft computing techniques would help police officials to identify the proper criminals more quickly and effectively. The database should contain the data on the 'face' information (used to access the identity) of the criminals. This database has a lot of potential that can be realized in order to help avoid crimes, deceit, and aid with surveillance, among other things. Our suggested model, 'CrimeNet,' is comprised of two layers: an EfficientNetv2b0 layer and a Data Augmentation layer. This model identifies whether the given image matches with previous criminal record. © 2024 IEEE.

关键词： Database systems

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Ocular Artifacts realization through optimized scheme

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13269-13283页

作者： Sahoo, Santosh Kumar Mohapatra, Sumant Kumar Department of Electronics & Instrumentation Engineering CVR College of Engineering Telangana Hyderabad India Department of Electronics and Telecommunication Engineering Trident Academy of Technology Odisha Bhubaneswar India

Brain Computer Interface (BCI) recommended for online real-time processing of EEG signals. Hence, the recording system’s accuracy improved by nullifying of developed artifacts. The goal of the proposed work is to develop an optimized model for detecting and minimizing ocular artifacts. In the proposed work, Discrete Wavelet Transform (DWT) and Pisarenko harmonic decomposition are used for decomposing the signals. Then the features are extracted by Principal Component Analysis (PCA) and Independent Component Analysis (ICA) techniques. After feature collection, an Optimized Deformable Convolutional Network (ODCN) is used for the recognition of ocular artifacts from EEG input signals. When artifacts are sensed, the moderation method is executed by applying Empirical Mean Curve Decomposition (EMCD) followed by ODCN for noise optimization in EEG signals. Conclusively, the spotless signal is reconstructed by an application of inverse EMCD. The proposed method has achieved a higher performance than that of conventional methods. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Curve fitting

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Augmenting Security Systems with Sign Language Recognition Using Deep Learning

Augmenting Security Systems with Sign Language Recognition U...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Nancy Deborah, R. Vinora, A. Alwyn Rajiv, S. Loghitha, K.Y. Soundarya, M. Madhumitha, R. Velammal college of Engineering and Technology Department of Information Technology Tamilnadu Madurai India Kamaraj College of Engineering and Technology Department of Electronics and Communication Engineering Virudhunagar India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543617

Sign language is the ancient way of communication which was found before the vocal communication. It bridges the gap between people who are deaf and it overcome the barrier of language difference. Many people learn sign languages as they express themselves through hand movements and facial expressions in absent of spoken communication. The current security CCTV cameras with manual security is not efficient in critical situation, this novel approach overcome the limitation and immediately send assistance. If any distressing situation occurs in absent of vocal communication, how can a person seek help orescape the situation is still in dispute. To elucidate, this security assessment will help people in those critical cenarios. When a person shows help sign in the camera, the backend mechanism in the camera will detect and sends security alert to the registered emergency contacts. This can be implemented in public cameras for security purpose. Furthermore, it will be a great aid to women in any unexpected situation. This suggested mechanism emphasis the automated meta data such as the image captured by the camera. The Deep learning model implemented can be an effective mechanism in terms of risk assessment and security exclusive for deaf and dumb people. This study can further improve in future by detection of emotion along with the handgesture can increase the novelty of the gesture that is the real emergency and reduce people tampering the system for amusement. © 2024 IEEE.

关键词： Risk assessment

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An Intelligent Recommendation of Organ Transplantation System Machine Learning for Donor Recipient Matching 5

An Intelligent Recommendation of Organ Transplantation Syste...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Nancy Deborah, R. Alwyn Rajiv, S. Vinora, A. Naveen Kumar, S. Sri Kathir, R. Gomathi Harish, J. Velammal College of Engineering and Technology Department of Information Technology Tamilnadu Madurai India Kamaraj College of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu Virudhunagar India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

Organ transplantation refers to the transference of organs from donors to recipients for patients suffering from conditions such as kidney failure, liver disease, or heart failure. Despite the importance of organ transplantation, finding suitable donors for the recipients, organ availability, and geographic issues still continue to face extensive challenges. Moreover, a need for transparency heightens these problems. This project aims to propose a new approach of improvement in donor-recipient matching by using machine learning in providing predictive algorithms concerning more accurate compatibility assessments and reduced search times. In this scoring model on compatibility, utilizes a core Random Forest algorithm. The Random Forest algorithm allows us to bring into account blood and tissue matching features along with urgency levels to produce an approximation of the transplantation probability of having a good outcome. With the summing of the results for multiple decision trees, the Random Forest provides a highly robust and accurate matching score to enhance general compatibility assessments. © 2024 IEEE.

关键词： Predictive analytics

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Waste Segregation using IoT and Machine Learning 4

Waste Segregation using IoT and Machine Learning

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4th International Conference on Advancement in electronics and Communication engineering, AECE 2024

作者： Nancy Deborah, R. Vidya Janani, V. Soundarya, M. Poorvaja, J.V. Alwyn Rajiv, S. Madhumitha, R. Velammal College of Engineering and Technology Department of Information Technology Tamilnadu Madurai India Kamaraj College of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu Viruthunagar India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364729

India is one of the most populated countries in the world, and its population is escalating rapidly, being very close to surpassing China in the near future. As the population increases, the waste generated is also rising rapidly. The per-capita waste generation in India is approximately 0.5 to 0.7 kg per day, which can lead to significant environmental setbacks. To tackle this issue, the Indian government has initiated several waste management programs that have demonstrated significant advancements. Nevertheless, certain segments still lack the intended impact on the populace and exhibit inconsistencies. To bolster these efforts, an automated waste segregation system has been introduced. This paper focuses on developing an automated waste segregation model to make the waste management system more efficient and automated. By achieving this, we aim to help clean our environment and invest our time in working towards a circular economy as a society. We employed YOLOv5 technology in conjunction with the Roboflow dataset to classify waste into four fundamental categories: Dry waste, Wet waste, E-waste, and Plastic waste. The model has been trained on 31,690 images and has achieved a high classification rate. The Roboflow dataset was used to develop a more accurate, flexible, and scalable waste segregation model, paving the way for effective waste segregation. The proposed model has achieved a mean CV of about 97%, demonstrating its potential to effectively segregate real-world waste into various categories. The efficacy of this waste segregation model lies in automating the waste segregation system, which not only reduces human labor in disease-prone situations but also improves overall efficiency. © 2024 IEEE.

关键词： Circular economy

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