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Analysis and Design of a Two stage Telescopic OTA using SCL 180nm CMOS Technology 1

Analysis and Design of a Two stage Telescopic OTA using SCL ...

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1st IEEE International Conference on Networking and Communications, ICNWC 2023

作者： Soman, Vanitha Gandhi, Kamala Kannan Baskaran, M. Terna Engineering College Dept. of Electronics and Communication Navi Mumbai India Ministry of Electronics and IT Dept. of National Informatics Centre Mumbai India Sri Sairam Engineering College Dept. of Electronics and Communication Chennai India

ISBN: (纸本)9798350336009

This paper presents the design of two stages Operational Transconductance Amplifier with a telescopic cascode configuration. A telescopic cascode configuration is used to achieve high gain, low power, and large swing. This work is achieved by incorporating well known Rz tracking technique. Achieved simulation results show 10 percent improvements in power consumption as a compared result with the same gain and technology. Further in this process variation analysis is also performed. The designed circuit shows only a 6 percent variation among FF to SS process corners. © 2023 IEEE.

关键词： Operational amplifiers

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A Novel Disturbance Particle Filtering Algorithm for Reduced Degeneracy and Improved Tracking Accuracy 8

A Novel Disturbance Particle Filtering Algorithm for Reduced...

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8th IEEE International Conference on Information and Communication Technology, CICT 2024

作者： Kattula, Deepthi Choppala, Praveen B. Pullagura, Rajesh K. Teal, Paul D. Andhra University Dept. of Electronics & Communication Engineering India School of Engineering & Computer Science Victoria University of Wellington New Zealand

ISBN: (纸本)9798331531539

Particle filtering is a Bayesian technique used for tracking moving targets in nonlinear dynamic systems. However, the resampling step in this filter is computationally intensive, limiting its application in real-time tracking. This paper introduces a methodology that eliminates the need for resampling while effectively parallelizing the particle filter. The approach involves iteratively sampling multiple heading disturbances for each particle until unbiasedness is achieved. This method is highly suitable for parallel processing since all particles are handled in batches, rather than sequentially as in the resampling process. The benefits of the proposed technique are demonstrated through a simulated study. © 2024 IEEE.

关键词： Importance sampling

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Optimized SVM-Based Network Anomaly Detection with Genetic Algorithm and Recursive Feature Elimination 2

Optimized SVM-Based Network Anomaly Detection with Genetic A...

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Ibrahim, Yusuf Muhammad, Abubakar Ibrahim Rabiu, Abdullahi Muhammad Ahmadu Bello University Dept. of Computer Engineering Zaria Nigeria Kaduna Polytechnic Dept. of Electrical and Electronics Engineering Nigeria

ISBN: (纸本)9798350358834

Network anomaly detection is a critical task in cybersecurity which aims to identify unusual patterns and potential threats in network traffic. Existing solutions often rely on machine learning (ML) algorithms, including support vector machines (SVMs). However, traditional SVMs with fixed kernels may struggle to capture complex, non-linear relationships in network data, leading to suboptimal detection performance. Additionally, selecting the right hyperparameters is often a non-Trivial task. In this paper, we investigate the application of SVMs with varying kernels (linear, sigmoid, polynomial, and radial basis function (RBF)) for network anomaly detection. We extend our exploration to RBF kernel optimization using genetic algorithm (GA) to fine-Tune critical hyperparameters (C and Gamma). Concurrently, we integrate recursive feature elimination (RFE) for optimal feature selection, enhancing the model's discriminatory prowess. To evaluate our proposed method, our study encompasses a standard dataset of over 40,000 training instances and 40+ features, subjected to meticulous preprocessing. Rigorous evaluation using 10-fold cross-validation was performed culminating in a final validation on a distinct test dataset. Our empirical results show the supremacy of the GA-RBF-SVM model, driven by GA-optimized hyperparameters, in conjunction with RFE compared to the other SVM variants. This configuration achieves exceptional performance with 99.39% accuracy on validation data and 99.46% on the test dataset. Additionally, our study extends to advanced (ensemble) ML techniques all demonstrating exceptional performance benchmarks. This study demonstrates that with systematic parameter optimization and appropriate feature selection, RBF-kernel based SVMs can perform competitively in network anomaly detection compared to advanced machine learning schemes. © 2023 IEEE.

关键词： Support vector machines

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Enhanced Convolutional Neural Networks for Early Detection and Classification of Ophthalmic Diseases 2

Enhanced Convolutional Neural Networks for Early Detection a...

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2nd International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2023

作者： Shojol, Md. Shojeb Hossain Siddique, Md Abu Ismail Haque, Fariha Rajshahi University of Engineering & Technology Dept. of Electronics & Telecommunication Engineering Rajshahi Bangladesh Rajshahi University of Engineering & Technology Dept. of Electrical & Computer Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350358667

Eye diseases are an important public health concern that affects millions of people around the world. The detection and diagnosis of these disorders at an early stage is crucial for timely intervention and treatment. This study focuses on building a Custom convolutional neural network (CNN) model alongside well-known architectures such as SqueezeNet, VGG16, and ResNet50 with Long Short-Term Memory (LSTM) to identify common eye illnesses. Photos of four common eye illnesses, including squint, cataract, chalazion, keratitis, and normal eyes, were collected and preprocessed to boost the dataset's diversity and quality. To select the best effective model, the evaluation compared the models using several metrics such as the confusion matrix, classification report, accuracy, precision, recall, and F1-score. After thorough analysis, we determined the ideal configuration for each of these CNN models and got the highest test accuracy of 98.16% for SqueezeNet architecture. © 2023 IEEE.

关键词： Convolutional neural networks

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Selection of Outsource Security Guard using Multi-Objective Optimization Ratio Analysis Method 7

Selection of Outsource Security Guard using Multi-Objective ...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Aditya Firmansyah, Mochamad Rafly Ismail, Iklima Ermis Hidayati, Anita Politeknik Negeri Jakarta Dept. of Computer and Informatics Engineering Jawa Barat Depok Indonesia

ISBN: (纸本)9798350342154

The security guard profession is no longer a profession that only relies on the physical but also other aspects, such as attitude, leadership, language, and others. There are several problems faced by companies providing security guards, namely the demand for security personnel is quite high, the number of applicants is also large, but the selection process has to go through an administrative and interview process. With a limited number of interviewers, it takes a longer time to get the selection results. Interview results also tend to be more subjective, making it difficult to determine which candidates are under the company's criteria and specifications. This study aims to develop a decision support system for selecting the acceptance of new outsourced security guards using the MOORA method for a security guard service provider company, namely PT. Purba Alter Service. There are 19 criteria used in the selection of security guards. This research developed the system on a web-based using the MOORA method for calculating the selection of alternative security guards. By comparing the results of the selection system processing using the MOORA method with the results of the previous three years without a system, of the 14 alternative names tested, 12 names appeared in both results, and obtained 85.7% accuracy. The result shows that the MOORA method is successfully implemented in selecting security personnel. © 2023 IEEE.

关键词： Decision support systems

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Mechanical Design and Forward Kinematics Analysis of T-FLoW 3.0 Prosthetic Robot Hand: Lever-based Finger Movement Mechanism 24

Mechanical Design and Forward Kinematics Analysis of T-FLoW ...

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24th International electronics Symposium, IES 2022

作者： Apriandy, Kevin Ilham Dewantara, Bima Sena Bayu Dewanto, Raden Sanggar Pramadihanto, Dadet Dept. of Informatics and Computer Engineering Indonesia Dept. of Energy Mechanics Engineering Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

In this research, a prosthetic robot hand that features a lever-based finger movement mechanism is proposed as the new approach to the T-FLoW 3.0 humanoid robot's hand development. The proposed approach performs both grasping and releasing movements by pushing or pulling the finger-attached lever. The lever is pushed or pulled by micro-servo, which uses a stiff bar to transfer the force from the servo-horn to the finger's lever. Our prosthetic robot hand is equipped with six joints, six SG92R micro-servos as actuators, and six force-sensitive resistors (FSR) as grasping feedback. 3D printing manufacturing technology is utilized to give the hand a realistic appearance, and PLA filament material is used in the manufacturing process to provide low-cost, lightweight, and easy maintenance. Static structural analysis simulation result lead to the conclusion that our prosthetic robot hand could sustain a load of around 30N. With the lever-based finger movement mechanism, the proposed approach is expected to overcome the mechanical slip issues from finger movements, which are often experienced in the old approach of the T-FLoW 3.0 humanoid robot's hand development. © 2022 IEEE.

关键词： 3D printers

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Classification of brain ischemia and hemorrhagic stroke using a hybrid method 4

Classification of brain ischemia and hemorrhagic stroke usin...

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4th International Conference on Data Analytics for Business and Industry, ICDABI 2023

作者： Cinar, Necip Kaya, Buket Kaya, Mehmet Dicle University Dept. of Computer Engineering Diyabakir Turkey Firat University Dept. of Electronics and Automation Elaziǧ Turkey Firat University Dept. of Computer Engineering Elaziǧ Turkey

ISBN: (纸本)9798350369786

The availability of artificial intelligence applications has expanded with the development of extremely powerful computers. This speeds up the diagnosis of many ailments and allows for the application of effective treatments. This facilitates the work of numerous experts in the field of health, and more trustworthy outcomes are attained. Many researchers have started working in this topic as a result of how swiftly artificial intelligence has entered human life and the promising outcomes that have been obtained. The detection of brain strokes from CT images, which are the most prevalent in the world and a major threat to human life, is a field that is currently seeing a flurry of deep learning and machine learning-based approaches. This study attempted to distinguish between ischemic and hemorrhagic brain stroke types using CT images. Utilizing a hybrid methodology, multi-classification was carried out utilizing EfficientNetB0 and SVM model from ischemic, hemorrhagic, and normal brain CT images in our dataset. The purpose of this study is to demonstrate a higher classification performance by combining the feature extraction skills of deep learning networks with the classification capability of machine learning models. The ischemic, hemorrhagic, and normal CT images in our dataset were used to train the EfficientNet-B0 + SVM, EfficientNet-B0 + KNN, ResNet50 + SVM, ResNet50 + KNN, ResNet50, VGG19 + SVM, VGG19 + KNN, and VGG19 models. There was a triple classification. According to the study, the hybrid EfficientNet-B0 + SVM architecture had the highest load success rate. The model had 95.13%, 94.93, 95.06, and 94.94% accuracy, recall, precision, and F1 values, respectively. These findings demonstrated that the EfficientNet-B0 + SVM architecture is a highly effective method for classifying different types of brain strokes from CT images. © 2023 IEEE.

关键词： computerized tomography

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Characteristic Mode Analysis of Polarization Reconfigurable Compact Metasurface Antenna for sub-6GHz 5G Application 3

Characteristic Mode Analysis of Polarization Reconfigurable ...

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3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Vinaya Kumar, S.R. Venkatesh, T. Tharehalli Rajanna, Puneeth Kumar Ghousia College of Engineering Dept. of Electrical and Electronics Engineering Karnataka Ramanagara India Ghousia College of Engineering Dept. of Computer Science Engineering Karnataka Ramanagara India Siddaganga Institute of Technology Dept. of Electronics and Telecommunication Engineering Karnataka Tumkur India

ISBN: (纸本)9798350317022

This paper presents the characteristic mode based polarization reconfigurable compact metasurface(MTS) antenna for sub 6GHz 5G applications. The MTS consists 2x2 array of rectangular unit cells arranged on the circular substrate. By rotating the antenna, three states of polarization can be achieved such as linear polarization(LP), left hand circular polarization(LHCP) and right hand circular polarization(RHCP). The MTS is excited by the slot aperture with the help of electromagnetic coupling scheme. The designed and fabricated antenna is compact (0.29λ02), which provides an impedance band-width of 19.23%(3.45GHz-4.19GHz) and axial ratio bandwidth of 5.05%(3.55GHz-3.72GHz). The peak gain of 5.2dBiC at 3.72GHz is obtained within CP bandwidth with 75% of radiation efficiency. The radiation pattern has better cross polarization values of more than -30dB with respect to co-polarization value in all the three states of polarization. This compact antenna is better suitable in sub-6GHz 5G application where switching of polarization is required without any hardware circuitry is essential. © 2023 IEEE.

关键词： Axial ratio Characteristic Mode Analysis(CMA) Circular Polarization Metasurface(MTS) Polarization reconfigurability

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Alpha-x Framework for Assessing Network Robustness in Nakagami-m Fading and Co-Channel Interference Environments 3

Alpha-x Framework for Assessing Network Robustness in Nakaga...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Upadhyay, Deepak Siwach, Karan Dhondiyal, Shiv Ashish Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India G.L. Bajaj Institute of Technology and Management Dept. of Computer Science and Engineering Greater Noida India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India

ISBN: (纸本)9798331518592

This article explores how the Alpha-x framework can improve network robustness under Nakagami-m fading and co-channel interference (CI), The study evaluates network performance using key metrics such as outage probability, spectral efficiency, and capacity degradation. The simulations show a 50% reduction in outage probability, a 20% boost in spectral efficiency, and a 33.3% lower capacity degradation compared to traditional models. These results demonstrate how the Alpha-x framework enhances network performance by adapting to various fading conditions and interference levels in wireless communication systems. The framework not only improves reliability and efficiency but also shows practical relevance in network planning and management. This can potentially lead to better user experiences and increased operational resilience. Future research could focus on optimizing the underlying algorithms and testing their performance on a larger scale in real-world environments. As telecommunications systems evolve, frameworks like Alpha-x could play a crucial role in ensuring reliable and efficient wireless networks. © 2024 IEEE.

关键词： Cochannel interference

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PV Systems Efficiency Evaluation Using Machine Learning Techniques 8

PV Systems Efficiency Evaluation Using Machine Learning Tech...

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8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Wadi, Mohammed Jouda, Mohammed Salemdeeb, Mohammed Husain, Nour Istanbul Sabahattin Zaim University Electrical & Electronics Engineering Dept. Istanbul Turkey Istanbul Sabahattin Zaim University Electrical Engineering Dept. Istanbul Turkey Istanbul Sabahattin Zaim University Computer Engineering Dept. Istanbul Turkey

ISBN: (纸本)9798331531492

Many factors, such as solar irradiance, temperature, angle of incidence, shading, panel degradation, temperature coefficient, and other parameters, can substantially affect the efficiency of photovoltaic (PV) systems. This work presents a concise overview of cooling strategies, temperature coefficient analysis, geographical influence, and advanced materials to explain the effects of solar irradiance and ambient temperature on the efficiency of PV systems. Furthermore, the study examines the two factors of solar irradiance and ambient temperature using two distinct approaches: deterministic techniques and machine learning methods. The results demonstrate that solar irradiance and temperature significantly impact the efficiency of PV models. These results lead to enhancing the performance and reliability of solar energy systems. © 2024 IEEE.

关键词： Solar irradiance

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