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5th IEEE International Conference on Advances in computing, Communication Control and Networking, ICAC3N 2023

作者： Singh, Abhishek Kumar Janarthanan, S. Upadhyay, Sushant Verma, Siddhant Galgotias University School Of Computing Science And Engineering India

ISBN: (纸本)9798350330861

Nowadays, everyone has become so busy in their life that they sometimes forget their meetings, events, and many day-to-day activities. We are dependent on others for information to get somewhere which we often forget. Many of the people face problem of depending on others to get anywhere on the planet for their crucial activities such as important meetings, sport activities, or kind of event that is to be happen in future. Some of them also don't remember all the activities and places to visit on. So, we have come up with the solution. The proposed solution to the existing problem is MAPIFY, a front-end web application developed by us which is an excellent example that one should include in their lifestyle. This application will keep the record of your various events in the local storage API of the web browser. This will make sure their location to be mapped on a map so that one can easily track it down, making life easier. It will keep record of all the activities that one should want to schedule along with location of that venue on the map. Also, there is no limit to these records, so one should not fear of storage run out, Since, we have used local storage Web API to solve the problem users face in case of weak internet connection which often leads to refresh of the web page which in turn leads to data losing. This mapify project will make sure to keep the record of the events with the location so that one can easily follow this to keep their day-to-day activities well-arranged and manage their time easily. © 2023 IEEE.

关键词： Location

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Virtual Assistant with Facial Expession Recognition 5

Virtual Assistant with Facial Expession Recognition

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5th IEEE International Conference on Advances in computing, Communication Control and Networking, ICAC3N 2023

作者： Saxena, Kanish Janarthanan, S. Goyal, Himanshi Galgotias University School Of Computing Science And Engineering India

ISBN: (纸本)9798350330861

In Today's world, Intelligent Virtual Assistants are used everywhere, and their base working principle is voice commands. And there are numerous technologies available for reading human facial expressions. So, in this paper, we will learn what happens if we combine both technologies. Does it better or create chaos? Artificial intelligence is gaining strength in the modern world. Every industry will soon use AI technology. AI has made great progress in recent years in identifying human emotions through voice, body language, facial expressions, etc. I's significance stems from the fact that traditional human capabilities can now be studied inexpensively and at scale in the software. Every sector can use me to provide new possibilities and efficiencies. It is significant because it successfully overcomes a well-defined set of technological challenges. The technology enables us to complete competitive tasks with basic controls quickly. Every new voice-interactive technology we adopt deepens our reliance on artificial intelligence (AI) and machine learning from our smartphones, computers, televisions, and refrigerators. The connection between machines and humans that we had been seeing and dreaming about a few decades ago has been real thanks to voice assistants like Amazon Echo, Siri, Google Home, and Amazon Lexa. But today, the fact is undeniable and real. Voice search technology is the upcoming digital trend on the market;in certain cases, touch screens have already been replaced. © 2023 IEEE.

关键词： Face recognition

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Deep Learning Approach for Identifying Red Lesions in Retinal Fundus Imagery 6th

Deep Learning Approach for Identifying Red Lesions in Retina...

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6th International conference on communication and computational technologies, ICCCT 2024

作者： Divyashrree, R. Dhawan, Samarth Saranya, P. Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai603203 India

ISBN: (纸本)9789819774258

One dangerous side effect of diabetes that affects the eyes is called diabetic retinopathy. It happens as a result of alterations in the retina’s blood vessels, which can cause harm and even blindness. The development of red lesions in the retina is one typical sign of diabetic retinopathy. These red lesions may be a sign of microaneurysms or hemorrhages, which are important characteristics to identify and track as diabetic retinopathy progresses. This process becomes even more demanding in the early stages of the disease where symptoms are less pronounced in the images. Leveraging machine-based learning for medical image analysis, especially deep learning algorithms, has demonstrated its capability to enhance the early diagnosis of diabetic retinopathy, providing a more efficient and effective alternative to traditional manual assessments. The proposed work aims to improve the efficiency of early detection of diabetic retinopathy by utilizing Deep Learning (16-layer CNN) to determine a person’s likelihood of having diabetic retinopathy using a 02-Class model that compiles a variety of datasets, specifically IDRiD dataset. The entire dataset contains 18,590 fundus photographs, in which 3662 are allocated for training, 1928 for validation, and 13,000 for testing. All datasets had a similar distribution of output classes, which is a fundamental property of this type of data. Using the IDRiD dataset, the suggested Red Lesion detection system’s specificity and sensitivity were found to be 98% and 89%, respectively, with an accuracy of 95.32%. Using the MESSIDOR dataset, the Diabetic Retinopathy Severity Classification System’s specificity, sensitivity, and accuracy were found to be 93.8, 92.3, and 94%, respectively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ophthalmology

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Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

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Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 Department of Information Engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 511400China Department of Electrical Engineering and Industrial Computing University Institute of TechnologyDoualaCameroon Department of Computer Engineering Jamia Millia IslamiaNew Delhi 110025India Department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical Engineering Department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

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The Distribution of Zeros of Quasi-Polynomials

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 301-304页

作者： Honghai Wang Qing-Long Han the College of Information Science and Engineering Northeastern UniversityShenyang 110004China IEEE the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, has posted a paper on arXiv [1] that hints at the possibility that he may have solved the Landau-Siegel zeros conjecture. He has claimed that he has disproved a weaker version of the Landau-Siegel zeroes conjecture, an important problem related to the *** conjecture is that there are solutions to the zeta function that do not assume the form prescribed by the Riemann hypothesis. Inspired by his work, in this Perspective, we would like to discuss about the distribution of zeros of quasi-polynomials for linear time-invariant(LTI) systems with time delays.

关键词： conjecture assume invariant

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Exploring the Impact of Deep Learning Models on Lane Detection Through Semantic Segmentation

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SN Computer science 2024年第1期5卷 139页

作者： Kumar, Sunil Pandey, Ankur Varshney, Sudeep School of Computing Science and Engineering Galgotias University Greater Noida India Department of Computer Science & Engineering Manipal University Jaipur Jaipur India Department of Computer Science & Engineering Sharda School of Engineering & Technology Greater Noida India

Due to advancements in the deep learning technology, object detection has become significantly important for lane detection and vehicle detection. In recent times, lane detection has become more popular as it plays a significant role in traffic surveillance compared to other object detection technology. However, these strategies have several intrinsic flaws which need to be addressed. Traditional-based techniques still suffer from the challenges of the effectiveness and accuracy, whereas a complex convolutional layer is a challenge for deep learning-based strategies. A parameter selection issue affects the majority of the available lane detection algorithms, which further contributes to their unsatisfactory detection performance. In this study, we provide an effective lane detection method based on semantic segmentation to identify lane lines in a high-dimensional dataset by adding vertical spatial properties and contextual driving information. This paper employs two created frames—feature merging block and information exchange block—to identify unclear and obstructed lane lines more effectively. The simulations have been carried out for the proposed model on TUSimple and CULane datasets which resulted with 94.42% accuracy, 93.47% precision, 92.85% recall, and 93.17% F1-score. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： CNN Deep learning Lane detection Occluded lane lines Semantic segmentation

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Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

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Computers, Materials & Continua 2024年第3期78卷 4243-4262页

作者： Youseef Alotaibi B.Rajasekar R.Jayalakshmi Surendran Rajendran Department of Software Engineering College of ComputingUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Electronics and Communication Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)*** networks give a safe and more effective driving experience by presenting time-sensitive and location-aware *** communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with ***,the scheme of an effectual routing protocol for reliable and stable communications is *** research demonstrates that clustering is an intelligent method for effectual routing in a mobile ***,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in *** FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the *** accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust *** the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR *** experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

关键词： Vehicular networks communication protocol clustering falcon optimization algorithm routing

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Blockchain Based Verification of Educational and Professional Certificates 2

Blockchain Based Verification of Educational and Professiona...

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2nd International Conference on Computational Systems and Communication, ICCSC 2023

作者： Singh, Anjali Chauhan, S.P.S. Goel, Amit Kumar Master of Technology in Computer Science and Engineering School of Computing Science and Engineering Galgotias University Greater Noida India School of Computing Science and Engineering Galgotias University Greater Noida India

ISBN: (纸本)9781665493932

Educational Documents and Certificates are a proof of professional achievements for anyone. Without these documents, it is not possible to start your career and hence play a very important role in everyone's professional life. Till date, Colleges, Universities and various educational institutes issue paper based degrees and certificates which are prone to get damaged or may be lost. The other drawback is that this process of issuing of degrees and manual process of verification of those documents by third parties is a time taking and cumbersome process. The employers take a lot of time for verifying these paper based degrees and certificates before they give the job offer. Forgery of paper based documents is also easier and has led to many educational scams. This paper aims to give the solution to the problems mentioned above through Blockchain Implementation. Block chain technology is not only limited to crypto currencies but is also of great applications in various fields like health, supply chain management, finance, etc. It has disrupted the traditional education system. This paper highlights as to how the educational certificates can be verified using the Ethereum platform and smart contracts. The traditional paper certificates would be converted to digital certificates on student's request, their hash value would be calculated using cryptographic hash functions and stored on Blockchain. A unique certificate ID and transaction hash value would be generated which would then be used to verify the certificates through a common platform. © 2023 IEEE.

关键词： Smart contract

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Polymorphic signal responses of phase-change quantum dot string upon stochastic resonance

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Nano Research 2025年第2期18卷 717-724页

作者： Qin Wan Fei Zeng Ziao Lu Junwei Yu Feng Pan Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Center for Brain Inspired Computing Research(CBICR) Tsinghua UniversityBeijing 100084China

We successfully constructed phase-change quantum dots string(PCQDS)systems and studied their signal *** PCQDs actually is a cascaded structure consisted of several stochastic resonance(SR)two-state systems,in which inherent non-linearity,i.e.,phase-change of quantum dots(QDs),plays elementary and important roles to modulate signal *** established an SR model to simulate signal responses depending on stimulation *** know that some QDs will oscillate with input forcing frequency,while certain QDs will oscillate in their own frequency triggered by phase *** two effectscooperate togeneratepolymorphic response patterns,including action potential patterns exhibited by envelope of spike peak *** interesting and important simulation is that we replicate the memory effect in Nb-doped AINO,i.e.,a QDs dispersed *** result indicates that memory can occur in a system only constructed by volatile elementary units,implying memory existing in ***-term plasticity and spike-rate dependent plasticity can also be realized by using frequency and phase *** study provides a new scope to study signal handling and memory effect in quantum system.

关键词： quantum-dot string phase-change inherent nonlinearity signal modulation niobium oxide stochastic resonance

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Bias analysis of AI models for undergraduate student admissions

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Neural computing and Applications 2025年第12期37卷 7785-7795页

作者： Van Busum, Kelly Fang, Shiaofen Department of Computer Science and Software Engineering Butler University IndianapolisIN United States Computing and Engineering Indiana University Luddy School of Informatics Indiana University Indianapolis IndianapolisIN United States

Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors Van Busum and Fang (Proceedings of the 38th ACM/SIGAPP Symposium on Applied computing, 2023) to provide a rigorous and more complete analysis of the bias found in AI predictive models. Admissions data spanning six years was used to create an AI model to determine whether a given student would be directly admitted into the school of science under various scenarios at a large urban research university. During this time, submission of standardized test scores as part of a student’s application became optional which led to interesting questions about the impact of standardized test scores on admission decisions. We developed and analyzed AI models to understand which variables are important in admissions decisions, and how the decision to exclude test scores affects the demographics of the students who are admitted. We then evaluated the predictive models to detect and analyze biases these models may carry with respect to three variables chosen to represent sensitive populations: gender, race, and whether a student was the first in his/her family to attend college. We also extended our analysis to show that the biases detected were persistent. Finally, we included several fairness metrics in our analysis and discussed the uses and limitations of these metrics. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Students

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