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1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Gnanakumar, D. Anusooya, V. Muthupradeepa, R. Gobalakrishnan, S. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil India Srm Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur India Thandalam India

ISBN: (纸本)9798350352931

Machine learning-based optical modulation format recognition is essential for dynamic optical networks. Convolutional Neural Networks (CNNs) can analyze signal space diagrams directly from raw data. Specifically, CNNs excel in image classification due to their ability to extract features and learn autonomously. In this study, signal space diagrams for various modulation formats (BPSK, QPSK, 8-QAM, 16-QAM, 32-QAM, and 64-QAM) are generated using an electrical constellation visualizer in Optisystem software, with the Optical Signal-to-Noise Ratio (OSNR) varying from 10 to 40 dB and the noise figure ranging from 5 to 25 dB. The proposed VGG-16 CNN architecture achieves 100% accuracy in modulation format recognition (MFR) for all six formats, utilizing minimal training data and fewer epochs. This approach can significantly enhance next-generation dynamic optical communication networks by enabling automatic detection and recognition of modulation formats. © 2024 IEEE.

关键词： Convolutional neural networks

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High Refractive Index Localized Surface Plasmon Resonance Sensor Based on Hollow Core Fiber Filled with Gold Nanowires 22

High Refractive Index Localized Surface Plasmon Resonance Se...

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22nd International Conference on Optical communications and Networks, ICOCN 2024

作者： Zhan, Ailing Wang, Zhiyang Sui, Pengxia Chang, Pengxiang College of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin Key Laboratory of Thin Film Electronics and Communication Devices Engineering Research Center of Optoelectronic Devices and Communication Technology Ministry of Education Tianjin300384 China

A localized surface plasmon resonance sensor based on hollow-core fibers for high RI detection is proposed, which has good sensing performance and obtains a high sensitivity of 47623.83 nm/RIU in the RI range of 1.430... 详细信息

ISBN: (纸本)9798350367652

关键词： Surface plasmon resonance

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Fabrication and characterization of silicon solar cells towards improvement of power efficiency

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Materials Today: Proceedings 2022年 62卷 2050-2055页

作者： Joseph, J.D. Jasmin, M. R.S., Sidharth Raj Department of Electronics and Communication Engineering Bharath Institute of Science & Technology Affiliated to Bharath Institute of Higher Education and Research Tamilnadu Chennai India

In recent years, natural energy has been increasingly popular as a source of electricity. Silicon-based solar cell devices are employed to harvest the natural energy, which uses the photovoltaic effect to convert sunlight into an electromotive force. Texturing was usually done on the solar cell surface using a variety of ways to improve solar cell efficiency. In this work, an inductively coupled plasma reactive ion etching (ICP-RIE) texturing approach has been adopted. This research also examines the fabrication of crystalline silicon solar cells with and without texturing and characterizes them to quantify the efficiency improvement. All the characterization is performed inside a clean room to support efficient results. © 2022

关键词： Photovoltaic effects

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Contagion Classification using Deep Learning Approach 2

Contagion Classification using Deep Learning Approach

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2nd IEEE International Conference on Networking and communications, ICNWC 2024

作者： Kacham, Sai Prajwal Angayarkanni, S.A. Rohithshan, S. Mishra, Arpan Vignesh, K. SRM Institute of Science and Technology College of Engineering and Technology Department of Networking and Communication Tamilnadu Kattankulathur603203 India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil626126 India

ISBN: (纸本)9798350365269

Potatoes are a major crop globally, but diseases can seriously harm their growth and quality. Recently, there's been a lot of interest in using machine learning to identify potato diseases from pictures. In this study, we've developed a way to automatically classify potato diseases using deep learning methods. By training a model with CNN and SVM algorithms on a dataset of potato disease images, we achieved an accuracy rate of 93.95%. This shows that deep learning is effective in identifying potato diseases. Our method could be a big help to farmers and researchers, making it faster and easier to spot and deal with potato diseases, which could lead to better crop yield and quality. © 2024 IEEE.

关键词： Support vector machines

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Designing of Robust, Energy Efficient Hybrid Approach for Implementing a 1-Bit Adder 2

Designing of Robust, Energy Efficient Hybrid Approach for Im...

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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Aiswarya, Bynaboyina Kumar, Yangalasetty Sai Jyothi, Bhavana Naga Sahoo, Satyajeet Samantaray, Aswini K. Vignan's Foundation for Science Technology and Research Department of Electronics and Communication Engineering Guntur522213 India Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru Department of Electronics and Communication Engineering Karnataka Manipal576104 India

ISBN: (纸本)9798350367461

Hybrid logic is a popular approach for designing full adders (FAs), balancing factors like speed, power, and driving capability. This work proposes a novel 4-transistor (4T) XOR-XNOR circuit for hybrid FAs. It delivers both full swing outputs, crucial for signal integrity, and improved delay performance for faster operation. Circuit performance is evaluated through Cadence Virtuoso simulations using 90nm CMOS technology with a 1.2V supply voltage. Metrics include power consumption and propagation delay, combined to calculate the (PDP). The key innovation of optimized 4T XORXNOR design, which significantly reduces PDP compared to conventional circuits. This translates to a more efficient FA, enabling faster computations with lower power consumption. This research not only presents a high-performance XORXNOR circuit but also highlights optimization strategies for hybrid FAs, paving the way for advancements in digital arithmetic circuits. © 2024 IEEE.

关键词： Adders

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Evaluating and Contrasting the Performance of Web Development Technologies 9

Evaluating and Contrasting the Performance of Web Developmen...

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9th International Conference on communication and Electronics Systems, ICCES 2024

作者： Swedheetha, C. Shruthika, C. Preethi, Rubi Vedha Varshini, T.B.J. Maryam, Sabreen Manikandan, P. Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Virudhunagar India

ISBN: (纸本)9798350377972

The next generation of webpages is heavily influenced by large scale, high concurrency, and massive amounts of data. Building data-intensive web apps has made *** popular and effective. We employed scenario testing and benchmark testing to examine and contrast the performance of ***, Python-Web, and PHP. Per the testing results, PHP and Python-Web handle a lot less requests in a given amount of time than ***, which is evident from some useful performance metrics. Our findings, taken together, show that *** is the most lightweight and efficient of the three, making it a good choice for I/O-intensive websites;PHP, on the other hand, is best suited for small- to medium-sized applications, while Python-Web is developer-friendly and excels at large web architectures. This research study includes the performance evaluation of web development technologies. © 2024 IEEE.

关键词： Python

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Intelligent Monitoring System for Automatic Air Conditioning System 5

Intelligent Monitoring System for Automatic Air Conditioning...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Manikandan, P. Swedheetha, C. Ram Mohan, R.L. Kumar, Sandala Likith Reddy, Peram Damodar Sri Sai, Pachabotla Adithya Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Krishnankoil India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798331518097

In order to improve indoor air quality, optimize energy consumption and avoid the accidents due to gas leakage, this paper proposes an intelligent air conditioning system that integrates several sensors such as DHT11, PIR sensors, MG6 Gas sensor and PMS7003 sensor and control mechanisms. An Arduino Mega, the system's central component, synchronizes data from several sensors to efficiently control the air conditioner and other linked equipment. This system keeps track of how many people enter and leave the space, enabling the air conditioning system to modify its settings in real time according to occupancy. When the room is empty, this feature saves energy. If gas leakage is present, system notifies users through a buzzer and turn off the AC. Many users often forget to clean their AC filters regularly, which can lead to reduced efficiency, higher energy consumption, and poorer air quality. Our innovative AC system addresses this common issue. Once the dust level crosses a predefined threshold, the system triggers a clean filter alert, reminding to act before it affects performance. Also, the air conditioner kicks on to cool the room if the outside temperature is high and the inside temperature is higher than an acceptable level. In contrast, the air conditioner is shut off to avoid needless cooling if the inside temperature is low. A display unit shows temperature, humidity, occupancy, gas levels, and dust concentration. This integrated technique automatically modifies the system's operation based on conditions, ensuring not only a more hygienic and comfortable environment but also improved energy efficiency © 2024 IEEE.

关键词： Air quality

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The Future of Online Shopping: Blockchain- Powered E-Commerce Platforms

The Future of Online Shopping: Blockchain- Powered E-Commerc...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Kiran, Ajmeera Sri, Nemani Divya Ayyasamy, Ramesh Kumar Chinnasamy, P. Vellanki, Sreelakshmi Vujwala, Maddula MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India Faculty of Information and Communication Technology Kampar Malaysia School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India

ISBN: (纸本)9798331540685

A cutting-edge online marketplace that uses blockchain technology to transform how we purchase and sell goods and services is known as a blockchain- powered e-commerce platform. This platform uses a decentralized network of computers, also known as nodes, to maintain a transparent and impenetrable record of all transactions instead of depending on a central authority like a bank or a company. A blockchain-based e-commerce platform is a secure, transparent, and trusted online marketplace. It does away with the need for intermediaries, improves security, and provides a world market where users can confidently conduct peer-to-peer transactions. This novel strategy could change how online commerce and shopping are performed. © 2024 IEEE.

关键词： Marketplaces

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CLIMAX: An Exploration of Classifier-Based Contrastive Explanations 5

CLIMAX: An Exploration of Classifier-Based Contrastive Expla...

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5th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2023

作者： Nanavati, Praharsh Prasad, Ranjitha Indian Institute of Science Education and Research Data Science and Engineering Bhopal India Indraprastha Institute of Information Technology Electronics and Communication Engineering Delhi India

ISBN: (纸本)9798350323832

Explainable AI is an evolving area that deals with understanding the decision making of machine learning models so that these models are more transparent, accountable, and understandable for humans. In particular, post-hoc model-agnostic interpretable AI techniques explain the decisions of a black-box ML model for a single instance locally, without the knowledge of the intrinsic nature of the ML model. Despite their simplicity and capability in providing valuable insights, existing approaches fail to deliver consistent and reliable explanations. Moreover, in the context of black-box classifiers, existing approaches justify the predicted class, but these methods do not ensure that the explanation scores strongly differ as compared to those of another class. In this work we propose a novel post-hoc model agnostic XAI technique that provides contrastive explanations justifying the classification of a black box classifier along with a reasoning as to why another class was not predicted. Our method, which we refer to as CLIMAX which is short for Contrastive Label-aware Influence-based Model Agnostic XAI, is based on local classifiers. In order to ensure model fidelity of the explainer, we require the perturbations to be such that it leads to a class-balanced surrogate dataset. Towards this, we employ a label-aware surrogate data generation method based on random oversampling and Gaussian Mixture Model sampling. Further, we propose influence subsampling in order to retaining effective samples and hence ensure sample complexity. We show that we achieve better consistency as compared to baselines such as LIME, BayLIME, and SLIME. We also depict results on textual and image based datasets, where we generate contrastive explanations for any black-box classification model where one is able to only query the class probabilities for an instance of interest. © 2023 IEEE.

关键词： Decision making

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Design of a Low-Power Sigma-Delta ADC Digital Filter 5

Design of a Low-Power Sigma-Delta ADC Digital Filter

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5th International Conference on Electronic communication and Artificial Intelligence, ICECAI 2024

作者： Li, Manyi Qin, Kun Bofan Tang, Jiacheng Huiminliu Engineering Research Center of Optoelectronic Devices and Communication Technology Tianjin University of Technology Ministry of Education School of Integrated Circuit Science and Engineering Tianjin University of Technology China Meraki Integrated Corpline Shenzhen China

ISBN: (纸本)9798350386943

With the development of science and technology, Sigma-Delta (∑-A) ADCs are widely used in various fields of electronics with their flexible advantages. As an essential component of a Sigma-Delta ADC, digital filters directly and significantly impact the ADC's accuracy, delay, and power consumption. This paper presents a multistage digital filter for 18-bit ∑-A ADCs;the filter uses a cascade of multiple filters, including cosine-like (CL), cascaded integral comb (CIC), interpolated second-order polynomial (ISOP), and half-band (HB) filters, to enhance the ADC's accuracy. The filter's order and downsampling multiplier are designed using canonical signed digit (CSD) and common subexpression (CSE) to reduce hardware resource consumption and improve computational performance. The ADC is synthesized using 0.18 μm CMOS technology, achieving an output SNDR of 96.26 dB, ENOB of 15.73 bits, total power of 518.35 uW, and a Digital filter power of 82.93 uW, which effectively reduces the power consumption while improving the accuracy. © 2024 IEEE.

关键词： Digital filters

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