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2nd International Conference on Innovations in Data Analytics, ICIDA 2023

作者： Tiwari, Amit Kumar Pandey, Raghvendra Kumar Singh, Saharsh Tiwari, Gaurav Kumar, Ambuj Mishra, Prateek Department of Computer Science and Engineering United Institute of Technology Uttar Pradesh Prayagraj211008 India Department of Information Technology United Institute of Technology Uttar Pradesh Prayagraj211008 India

ISBN: (纸本)9789819749270

The fundamental aim of this research paper is to make Machine Learning-Based Smart Traffic Control System. The traffic light timer timing changes on detecting the traffic density count at each crossroad. Traffic congestion is most common problem in the major highly populated cities across the world, and it has made traveling very tough from one place to other. Traditional traffic lights run on the fixed timer concept assigned to each side of the road which can’t be changed as per changing vehicles density. In some situation lane with higher density demands longer green time as compared to the basic fixed time. The object or vehicles in the traffic signal are detected using cameras then processed into a simulator then its threshold is assumed on the basis of vehicle count in respect to each lane and compute the total number of vehicles present in the given area. After computing the total number of vehicles the system will acknowledge that which side the density of vehicles is high and based on the density the signals will be allotted for a particular side. Traffic mishaps or accidents are very common at overcast, rainy day, night when no street lights are available, foggy day and many others when there is minimum visibility. Traffic light control is one of the severe technical hazards of the Major cities in almost every country across the world. This is due to exponential rate of growth in the number of vehicles. In respect to minimize the time, a system has to be come up with the technology of artificial intelligence which makes a machine to think themselves. This modern developed technology will help the traffic light to switch the traffic signals from green to red based upon traffic density. This paper is related with the enhancement of traffic control system using machine learning which will be base on the different density on each lane. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Traffic congestion

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Blockchain-Based Two-Stage Federated Learning With Non-IID Data in IoMT System

Blockchain-Based Two-Stage Federated Learning With Non-IID D...

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作者： Lian, Zhuotao Zeng, Qingkui Wang, Weizheng Gadekallu, Thippa Reddy Su, Chunhua The University of Aizu Department of Computer Science and Engineering Aizuwakamatsu965-8580 Japan Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210093 China City University of Hong Kong Department of Computer Science SAR Hong Kong Hong Kong Vellore Institute of Technology School of Information Technology and Engineering Vellore632014 India Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon

The Internet of Medical Things (IoMT) has a bright future with the development of smart mobile devices. information technology is also leading changes in the healthcare industry. IoMT devices can detect patient signs and provide treatment guidance and even instant diagnoses through technologies, such as artificial intelligence (AI) and wireless communication. However, conventional centralized machine learning approaches are often difficult to apply within IoMT devices because of the difficulty of large-scale collection of patient data and the potential risk of privacy breaches. Therefore, we propose a blockchain-based two-stage federated learning approach that allows IoMT devices to train a global model collaboratively without gathering the data to a central server. Specifically, to address the problem of poor training performance on non-independent identically distributed (non-IID) data, we design a blockchain-based data-sharing scheme that can significantly improve the model's accuracy without threatening user privacy. We also design a client selection mechanism to further improve the system's efficiency. Finally, we validate the feasibility and effectiveness of our system through simulation experiments on three popular datasets (i.e., MNIST, Fashion-MNIST, and CIFAR-10). © 2014 IEEE.

关键词： Data privacy

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A Comparison of Different Optimization Techniques in AlexNet for Plant Disease Classification: SGD, Adadelta, ASGD and Adagrad 5

A Comparison of Different Optimization Techniques in AlexNet...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Ponnila, P. Bazila Banu, A. Bannari Amman Institute of Technology Department of Information Technology Erode Tamilnadu Sathyamangalam India Kpr Institute of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9798331504403

Plant diseases are a biggest challenge for the farmers. Agriculture relies heavily on its production, and diagnosis of plant disease in an accurate manner will help in identification of the appropriate disease. If correct identification was not performed, there might be a significant financial loss that could have an impact on both farmers and the national economy. For resolving this issue, the AlexNet was employed, a convolutional neural network method. In this research, AlexNet is used to classify the diseases occurring in chilli, cauliflower and sunflower. This AlexNet model, with Stochastic Gradient Descent(SGD) algorithm optimization techniques had achieved 82% accuracy for the overall classification of the test images of chilli plant, 98% accuracy for the overall classification of the test images of cauliflower plant and 91% accuracy for the overall classification of the test images of sunflower plant;with Adadelta optimization 86%, 99% and 93% accuracy was achieved for the overall classification of the test pictures of chilli plant, cauliflower plant and sunflower plant respectively. After using the Asynchronous Stochastic Gradient(ASGD) optimization with AlexNet model, the accuracy obtained are 88% for the test images of chilli plant, 98% for the test images of cauliflower plant and 91% for the test images of sunflower plant;and finally, AdaGrad optimization with AlexNet achieved accuracy of 80% for the test images of chilli plant, 9 8% for the test images of cauliflower plant and 93% for the test images of sunflower plant. © 2024 IEEE.

关键词： Convolutional neural networks

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Enabling Adaptable Mixed-Signal Circuits Using Advanced Packaging Techniques

Enabling Adaptable Mixed-Signal Circuits Using Advanced Pack...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Upadhyay, Ramakant Upadhyay, Ajay Kumar Mandal, Sanjeev Kumar Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India College of Engineering Teerthanker Mahaveer University Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

this paper affords a way to enable adaptable mixed-sign circuits through superior packaging techniques. Existing strategies need to competently address a number of the demanding situations related to the combination of notably complicated circuit designs right into a single bundle. To this cease, the authors present a sophisticated packaging method wherein a preliminary, over molded package deal is used in combination with a rework able polyimide film. Through this mixture, a circuit dressmaker can dynamically reconfigure mixed-signal circuits without bodily gaining access to the tool. It keeps the design loose from any bodily constraints and improves its adaptability and scalability. The primary gain of this approach lies in its potential to reduce the time-to-market of a product, as the hit-and-pass over transform technique to modifying silicone may be eliminated. Moreover, the use of the rework able film allows for the device to be reworked in multiple instances, further decreasing the full value of possession. The paper plays an intensive assessment of the proposed method using successful test beds, demonstrating the ability of the supplied answer. © 2024 IEEE.

关键词： Adaptable Complicated Demonstrating Intensive Possession Transform

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LSTDA: Link Stability and Transmission Delay Aware Routing Mechanism for Flying Ad-Hoc Network (FANET)

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computers, Materials & Continua 2023年第10期77卷 963-981页

作者： Farman Ali Khalid Zaman Babar Shah Tariq Hussain Habib Ullah Altaf Hussain Daehan Kwak Department of Computer Science and Engineering Sungkyunkwan UniversitySeoul03063South Korea Information Engineering School Chang’an UniversityXi’an710061China College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhou310018China Institute of Computer Science and IT The University of Agriculture PeshawarPeshawer25120Pakistan Department of Computer Science and Technology Kean UniversityUnionNew Jersey07083USA

The paper presents a new protocol called Link Stability and Transmission Delay Aware(LSTDA)for Flying Adhoc Network(FANET)with a focus on network corridors(NC).FANET consists of Unmanned Aerial Vehicles(UAVs)that face challenges in avoiding transmission loss and delay while ensuring stable *** proposed protocol introduces a novel link stability with network corridors priority node selection to check and ensure fair communication in the entire *** protocol uses a Red-Black(R-B)tree to achieve maximum channel utilization and an advanced relay *** paper evaluates LSTDA in terms of End-to-End Delay(E2ED),Packet Delivery Ratio(PDR),Network Lifetime(NLT),and Transmission Loss(TL),and compares it with existing methods such as Link Stability Estimation-based Routing(LEPR),Distributed Priority Tree-based Routing(DPTR),and Delay and Link Stability Aware(DLSA)using MATLAB *** results show that LSTDA outperforms the other protocols,with lower average delay,higher average PDR,longer average NLT,and comparable average TL.

关键词： LSTDA routing protocol Flying Ad-hoc Network link stability unmanned aerial vehicles maxim priority channel

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On the Performance of Multidimensional Constellation Shaping for Linear and Nonlinear Optical Fiber Channel 49

On the Performance of Multidimensional Constellation Shaping...

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49th European Conference on Optical Communications, ECOC 2023

作者： Chen, Bin Liang, Zhiwei Li, Shen Lei, Yi Liga, Gabriele Alvarado, Alex School of Computer Science and Information Engineering Hefei University of Technology China Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Department of Electrical Engineering Eindhoven University of Technology Netherlands

ISBN: (纸本)9781839539954

Multidimensional constellation shaping of up to 32 dimensions with different spectral efficiencies are compared through AWGN and fiber-optic s imulations. The results show that no constellation is universal and the balance of required and effective SNRs should be jointly considered for the specific optical transmission scenario. © The Institution of engineering & technology 2023.

关键词： Optical fibers

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Web Application Based Text Encryption 2022

Web Application Based Text Encryption

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14th International Conference on Contemporary Computing, IC3 2022

作者： Kushwah, Rashmi Rajpurohit, Rishabh Jonathan, Paul Kumar, Gaurav Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Uttar Pradesh Noida India

ISBN: (纸本)9781450396752

In today's world we are using cryptography everywhere. Cryptography ensures that the information is secured and can only be accessed by the sender and the receiver of the message. We use it to securely send passwords over vast networks for online purchases. During recent time, we have seen a rise in the number of cyberattacks. Our data is becoming less and less secure. Also, the encryption and decryption process has become really cumbersome which has made it really difficult for it to be used in daily life. The aim of our paper is to protect the privacy of users. We have proposed a novel RKJ algorithm which is based on keyless encryption. In this algorithm the message is converted to binary and divided into groups of 32 bits. Every group is used as its own key after round shifting the bits by a random amount. This is done for a number of times (rounds). Apart from the proposed algorithms, we have also provided the users to create an id and use our proposed web application to store important data in the form of notes. We have used the blowfish algorithm to store these passwords in our database. The proposed RKJ algorithm has been used to encrypt these notes. To read the notes we would have to use login and password. Finally, we have hosted proposed web application on Heroku. © 2022 ACM.

关键词： Cryptography

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Synergistic Fusion of CNN and BiLSTM Models for Enhanced Video Captioning

Synergistic Fusion of CNN and BiLSTM Models for Enhanced Vid...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Sharma, Pankaj Sharma, Sanjiv Madhav Institute of Technology and Science Computer Science and Engineering M.P. Gwalior India Madhav Institute of Technology and Science Information Technology M.P. Gwalior India

ISBN: (纸本)9798350379525

In the realm of video captioning systems, the significance of leveraging CNN models for feature extraction cannot be overstated. These deep features, extracted from video frames, are seamlessly integrated with textual data features through a probabilistic matching approach, establishing crucial connections with the target text data. This study delves into the effectiveness of utilizing pretrained standard convolutional neural networks for feature extraction from video frames, with a keen focus on identifying the most suitable model to bolster video captioning systems. Through an exhaustive analysis, we explore various combinations of recurrent neural networks (RNN) with LSTM and GRU layers, coupled with the integration of Bidirectional layers, aiming to pinpoint nuanced model requirements for optimizing BLEU scores. Evaluation on the MSR- VTT dataset showcases notable enhancements, particularly when employing the MobileNet-V3 model for video frame feature extraction in conjunction with a BiLSTM-based model for subsequent text data processing. These findings culminate in substantial improvements in captioning outcomes, underscoring the potential of this integrated approach. © 2024 IEEE.

关键词： Convolutional neural networks

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Deep Learning-Based Diagnosis System for Liver Cancer Through Multimodal Determination for Early Treatment 4

Deep Learning-Based Diagnosis System for Liver Cancer Throug...

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

作者： Dandotiya, Monika Singh, Anupam Agarwal, Nishi Jaheda, Shaik Gulati, Samridhi Poornima University Department of Computer Science & Engineering Jaipur India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Dev Bhoomi Uttrakhand University Department of Computer Science and Engineering Dehradun India Cvr College of Engineering Department of Information Technology Hyderabad India Raj Kumar Goel Institute of Technology Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350364729

Liver cancer is still one of the top causes of worldwide mortality from cancer, which highlights the demand for earlier diagnostic tools aimed at improved treatment outcomes. Although these traditional diagnostic practices are helpful, they may take time and also be subject to human error. The present study aims to fill the gap in existing diagnostic tools for liver cancer by evaluating prostate deep learning models (VGG 16, VGG 19 and ResNet 50) on CT scan images. This problem statement is related to improving the accuracy and reliability of liver cancer detection using powerful computational techniques. We processed a dataset of 1020 CT scan images by resizing, then normalizing the data, and performing an augmentation and some noise reduction. The performance of each model was evaluated in terms of precision, recall and F1 score using Dice Similarity Coefficient to identify the liver tumours. VGG 19 was the top performer in terms of accuracy and another score, followed by VGG 16 and ResNet 50. The use of such models in clinical settings can significantly improve diagnostic accuracy and, ultimately, diagnosis time, which will lead to better patient outcomes. The study ultimately underscores the promise of deep learning models (specifically VGG 19) as an essential resource in medical imaging by developing new and prospective methods for computerized liver cancer diagnosis that will help improve healthcare. © 2024 IEEE.

关键词： Diseases

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Robot operating system for live work in substation based on machine vision 4

Robot operating system for live work in substation based on ...

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4th International Conference on computer Vision and Data Mining, ICCVDM 2023

作者： Shen, Jianfang Shen, Miaofang School of Computer Science and Technology Guangdong University of Technology Guangdong Guangzhou510006 China The college of Information Engineering Guangzhou Vocational University of Science and Technology Guangdong Guangzhou510550 China

ISBN: (纸本)9781510674448

Substation is an essential part of the whole power system, which is burdened with the important functions of voltage and current conversion, electric energy receiving and distribution. At present, the operation and maintenance of substation in our country is mainly through regular inspection and maintenance of duty personnel, and there are many problems in related work efficiency and personnel safety. Therefore, with the development of robot technology, the power grid began to gradually replace some manual work with substation robots to solve the above problems. According to the basic requirements of the substation, develop the functional framework of the robot, develop the relevant hardware framework, understand the technology involved in the relevant hardware, and carry out the hardware selection. In this paper, the hardware framework is divided into three layers: main station layer, communication layer and implementation layer. Combining the advantages of traditional electric mobile robot and multi-degree of freedom robotic arm, an intelligent operating robot system with more comprehensive functions is designed. The positioning error of the moving robot is compensated step by step by image features, so that the operation unit at the end of the manipulator arm is in an ideal relative position to the operating object, and the operation unit is inserted into the operation hole by moving the manipulator along a fixed path to perform the corresponding operation. This method greatly reduces the calculation amount through step compensation and tentative movement. And the control accuracy also well meets the task requirements. © 2024 SPIE.

关键词： Manipulators

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