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Solar Investment Decision Application System Based on Big Data Technology

Solar Investment Decision Application System Based on Big Da...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), international conference on IEEE international conference on

作者： Xianwu Liang Dongqing Hou College of Computer Science and Technology Jishou University Jishou China

With the rapid development of photovoltaic new energy industry, more and more investors have started to invest in photovoltaic projects. In order to help investors make wise investment decisions, a photovoltaic investment decision-making application system based on big data technology has been designed. This system uses temperature sensors, humidity sensors, light sensors, and power sensors in the equipment layer to obtain environmental data around photovoltaic solar panels, and uses NBIOT wireless network in the communication layer to transmit the data to the service layer. The service layer connects to the Web server cluster to access components and transfers the environmental data to modules such as big data encryption, parsing, and offline storage control. The system utilizes big data technology to encrypt, parse, and store the data offline, and then transfers the data to the application layer. The application layer provides data management and query functions for investors, making it easier for them to manage and query photovoltaic investment decision-making terminal data. The system has also undergone experimental testing, and the results show that the system can collect, network, and remotely transmit operating data of distributed photovoltaic solar panels. It can also provide remote access and control of data through a computer or mobile client. This system can help investors consider the impact of different geographical environments and seasonal climates on equipment, thereby making better investment decisions.

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Fuzzy Logic in computer Technology: Applications and Advancements

Fuzzy Logic in Computer Technology: Applications and Advance...

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Pervasive Computing and Social Networking (ICPCSN), international conference on

作者： Shashank Pareek Hemant Gupta Jaspreet Kaur Raman Kumar Jasgurpreet Singh Chohan Department of Computer Science and Engineering Chandigarh University Mohali India Department of Electrical Engineering GLA University Mathura India Computer Science and Engineering Department Gulzar Group of Institutes Khanna India Department of Mechanical Engineering Chandigarh University Mohali India University Centre for Research and Development Chandigarh University Mohali India

The development of Fuzzy Logic has had a profound impact on the field of computing. A crucial part of any decision-making process is the use of this mathematical method for dealing with uncertainty and imprecision. In this article, it will go over what Fuzzy Logic is, how it may be used in computing, and what recent developments have been achieved in the field. The strengths and weaknesses of using Fuzzy Logic in IT are also discussed. The introduction of Fuzzy Logic into the realm of computer science was a game-changer, since it provided a robust mathematical strategy for addressing uncertainty and imprecision in decision-making. This article introduces readers to Fuzzy Logic by discussing its background, basic ideas, and potential uses in the field of information technology. Artificial intelligence, control systems, decision-making, data analysis, and image processing are just some of the many areas where Fuzzy Logic has been put to use. In addition, this article discusses contemporary developments in Fuzzy Logic, such as those in machine learning, control systems, and robotics. Although this study extols Fuzzy Logic's numerous benefits, it also addresses the method's drawbacks. Workers in the IT industry would do well to familiarize themselves with the merits and drawbacks of Fuzzy Logic, as this knowledge may inform the development of superior products. This study's overarching goal is to introduce readers to Fuzzy Logic in the context of computer technology, including its advantages and disadvantages. Fuzzy logic has been more useful in many areas of computer science and technology. Used in areas such as control systems, image processing, robotics, and decision making, fuzzy logic allows for the processing of imprecise or uncertain input. This study gives a thorough introduction to fuzzy logic in computer technology, including its history, current developments, and potential future uses. The first section of the study provides a foundational understanding of fu

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6D Pose Estimation from Point Cloud Using an Improved Point Pair Features Method 7

6D Pose Estimation from Point Cloud Using an Improved Point ...

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7th international conference on control, Automation and Robotics (ICCAR)

作者： Wang, Haoyu Wang, Hesheng Zhuang, Chungang Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

ISBN: (纸本)9781665449861

The Point Pair Features (PPF) method has been shown to be effective for pose estimation under clutter and occlusion. Our improved method mainly includes: (1) an approach for solving normal orientations of closed geometries based on Odd-even Rule;(2) an efficient downsampling approach by dividing a voxel grid into equivalent angle cells;(3) a verification step based on fitting points. The method is evaluated on real datasets of clutter and shows better performance as well as efficiency for 6D pose estimation compared to original PPF method.

关键词： pose estimation point pair features point cloud normal estimation 3D computer vision

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Efficiency and Precision: control Systems Empowered by Smart Image Processing

Efficiency and Precision: Control Systems Empowered by Smart...

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Smart Generation Computing, Communication and Networking (SMART GENCON), international conference on

作者： Gunji Sreenivasulu T Padmavathi Anagandula Nirisha Dudi Bhanu Prakash Mohammed Yousif Oudah K Saikumar Department of Computer Science & Engineering Madanapalle Institute of Technology & Science Madanapalle Department of ECE CVR College of engineering Department of Computer Science and Information Technology MLR Institute of Technology Hyderabad Telangana India Department of ECE CVR College of Engineering Hyderabad Scientific Research Center Al-Ayen University Thi-Qar Iraq Computer Science School of Engineering Malla Reddy University Hyderabad Telangana

The rapid increase in the population has resulted in traffic jams on the roads. There was a corresponding increase in the number of calls for emergency services, such as ambulances, police cars, and fire trucks. Maintaining rapid response times for emergency vehicles is critical right now. In this study, we present a smart traffic control system that integrates Internet of Things (IoT) chips into traffic signals and modifies their timing parameters. These chips will function in response to a road's estimated automobile count and the subsequent need for emergency vehicles along that route. The number of people in each automobile is going to be calculated using digital image analysis of the live camera feed. To make sure emergency vehicles get the help they require, GPS systems are going to be utilized to track the vehicles and update the chips with their current locations. It is envisioned that traffic lights on a road network will function by dynamically assigning weights for a particular node or the time among two consecutive lights. In order to maintain track of each node in the network, the weights assigned to each one must be updated in real-time.

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An Optimized Novel Hybrid CNN-vision Transformer (ViT) Architecture for Brain Tumor Classification

An Optimized Novel Hybrid CNN-Vision Transformer (ViT) Archi...

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Emerging Trends in Electrical, control, and Telecommunication Engineering (ETECTE), international conference on

作者： Shams Ur Rehman Saba Anwer Junaid Aftab Ameer Hamza Ammad Ahmed National University of Technology Islamabad Riphah College of Science & Technology Riphah international University Islamabad Lahore Campus Hitech University Taxila

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

Brain tumor is the uncontrolled division of mutated cells. If not detected and treated timely, it may ultimately cause death. According to data collected from different sources it is evident that, in past few decades brain tumor has badly affected a significant population worldwide and due to its expensive diagnostic and treatment strategies it has various associated socio-economic consequences. AI has played an important role in the medical imaging industry for the detection of various diseases. In this study a novel hybrid CNN-ViT architecture has been proposed for classification of Giloma, Pituitary and Meningioma tumors in a publicly available dataset ‘SARTAJ’. As compared to the conventional designed CNN architectures our proposed hybrid architecture achieved 98.1% accuracy. The proposed model has the potential to achieve the significant milestones in the medical imaging industry specially for detection of the brain tumors.

关键词： Industries Magnetic resonance imaging Brain tumors Transformers Market research Brain modeling Communications technology Socioeconomics Biomedical imaging Diseases

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Sequential Convolutional Neural Network based Face Mask Detection 3

Sequential Convolutional Neural Network based Face Mask Dete...

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Sree Duggireddy, Greeshma Sai Dammalapati, Komali Sravya, Y Afroz, S.K. Triinayanaa, K Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering India Koneru Lakshmaiah Education Foundation Vaddeswaram Department of Computer Science and Engineering AP Guntur India

ISBN: (纸本)9781665438117

Due to the COVID-19 pandemic, we have encountered signs such as "No entry without face mask"in public spaces such as theatres, restaurants, shopping malls, other places. The Face mask is one among the necessary preventive measures taken against COVID-19. Many doctors and scientists have suggested the continued use of face masks even after the vaccination drive. This new change in the way of life necessitates the use of a face mask in public places. Open public spaces cannot be monitored but enclosed public spaces can be monitored. The passageway of these public spaces should monitor if an individual has put on a face mask. Without manual supervision, the CNN algorithm could potentially be used to check the face mask of the persons entering the enclosed public spaces. In this paper, a Convolutional Neural Network prototype is constructed using TensorFlow, OpenCV and, Keras to detect, if an individual has put on a face mask to protect themselves. At the entrance of these public spaces, a monitor scans the faces of the people entering and detects if they are wearing a facemask using the CNN deep learning model. We collect data of images and pre-process them to develop a CNN prototype. The above deep learning algorithm could be coordinated with the doorways of public places to ensure, no person without a face mask enters the space. © 2021 IEEE.

关键词： COVID-19

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Optimal Robust control For Tremor Suppression in Parkinson's Disease

Optimal Robust Control For Tremor Suppression in Parkinson's...

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2022 IEEE international conference on Systems, Man, and Cybernetics, SMC 2022

作者： Saeedi, Mobin Zarei, Jafar Balouchi, Hoda Razavi-Far, Roozbeh Saif, Mehrdad Shiraz University of Technology Department of Electrical Engineering Shiraz Iran Jundishapur University of Medical Sciences Department of Medical Sciences Ahvaz Ahvaz Iran Windsor University Department of Electrical and Computer Engineering WindsorONN9B3P4 Canada

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Deep brain stimulation (DBS) is an effective and promising therapy to control Parkinson's tremor movement in patients with advanced Parkinson's disease (PD). This paper proposes a new alternative medication that has several advantages, including compatibility with individual needs and low side effects. There has been a rapid improvement in the literature on the development of the dynamic computational model of neuroscience, alongside the development of DBS. A combination of DBS and model-based control strategies opens up a new vision for Parkinson's disease treatment. Despite the numerous studies on basal ganglia (BG) modeling, researchers are required to employ adaptive and robust strategies to eliminate Parkinson's patients' tremors. This paper proposes a new adaptive optimal fast terminal sliding mode control (AOFTSMC) method to mitigate tremors by tuning GABA thorough DBS. This approach represents finite-time convergence law, a new method to stimulate the inner nuclei of BG in a robust and optimum manner that leads to removing tremors of PD fluctuation signal in the presence of uncertainties. Finally, simulation results of the basal ganglia model under the addressed approach are adopted to demonstrate the effectiveness of the proposed method. © 2022 IEEE.

关键词： Disease control

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IoT-based Door Automation and Smart Health Monitoring System

IoT-based Door Automation and Smart Health Monitoring System

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Ruchi Chaurasiya Shakshi Yadav Swagata Malik Meena Belwal Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

This project presents the design of an automated access control system that aims to enhance security through the use of an ultrasonic motion sensor and a live heartbeat check. This system makes use of an ultrasonic sensor which detects any motion within a certain radius directing a signal to the controller based on Arduino. The controller is able to communicate with a script written in Python that queries API for the pulse of the user in question. Using these parameters, the system compares the real-time heartbeat of the pulse taken against the thresholds set beforehand. When the parameters exceed the range, the control unit within the Arduino will trigger the servo to unlock the door. Another scenario the parameters are within range, the door will remain closed. Such a system is able to increase the control measures in biological information system as it enables people to open the door while maintaining their hands free. The outcome demonstrates that by combining simple hardware components with data processing techniques, a reliable and secure automated access system can be created with minimal manual intervention, improving security while ensuring ease of use.

关键词： Access control Heart beat Manuals Acoustics Real-time systems Motion detection Hardware Reliability Monitoring Python

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Smart Eye of Traffic Management control System 3

Smart Eye of Traffic Management Control System

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Maduri, Praveen Kumar Dhiman, Preeti Rathour, Shalini Dutt, Eeshaan Gupta, Aman Department of Electronics and Instrumentation Engineering Greater Noida India

ISBN: (纸本)9781665438117

In the era of fast-growing technology, automation in public transportation is gaining popularity worldwide. License plate recognition is a technology that is being utilized efficiently these days. On comparing with the past scenario, we realize there weren't many roles of technology in transport surveillance. In its initial phase, this technology was majorly used by police and the army for recognition and filtering the stolen or blacklisted vehicles out of traffic. Day by day this technology came under implementation and got advanced with rapid developments. In the present scenario, this technology in public transportation plays a vital role by recognizing whether the vehicle is registered or licensed in e-challans by monitoring the vehicle which came under over speed and traffic rules violations. This technology can be implemented either on the still images of the vehicle or real-time detection. The proposed model focuses on the real-time execution of the license plate as well as speed detection. Methodology of the model invokes the usage of the concept of transfer learning and the model being used is MobileNetv2-SSD for recognition of license plate, further followed by implementation of package namely easyOCR, to recognize the alpha-numeric contents of license plate. For speed detection, the ensemble learning technique is being utilized, which invokes the usage of computer visualization, and its working is very much similar to machine learning. © 2021 IEEE.

关键词： License plates (automobile)

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Integrating IoT with Vedic Technology to Purify Atmosphere 3

Integrating IoT with Vedic Technology to Purify Atmosphere

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3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Bhatia, Shailee Sachdeva, Shelly Goswami, Puneet SRM University Computer Sc. and Engg. India NIT Computer Sc. and Engg. Delhi India

ISBN: (纸本)9781665438117

Agnihotra/Homa therapy is a gift to humanity from the ancient Vedic technology of bioenergy, climate science, medicine, and agriculture. It is an urgent need to purify the atmosphere and strengthen the immune system through Vedic Science techniques. Covid-19 has become a major threat globally. Agnihotra can be a useful tool to combat coronavirus. Agnihotra process purifies the atmosphere through fire prepared in a copper pyramid tuned to the biorhythm of sunrise and sunset. Technology is now part of our lives and the Internet of Things takes a significant share in making it possible. So IoT and Agnihotra fire technology is applicable for the improvement of all aspects of the environment and thereby having a very positive impact on the thrive of living organisms. IoT-based sensors will become the weapon in measuring the presence of bacteria, microbes, viruses in the surrounding area. They can be used for both indoor and outdoor environments and offers monitoring at a lower cost than conventional methods, in theory making the process of monitoring possible in many more locations. We also proposed an IoT based model where data will be gathered from various sensors before and after Yajna. It is then transmitted and stored on a cloud sub-system, where it is maintained, managed, and backed up. Further automation of analytical model building is done through the process of machine learning and data visualizations, thus enabling users to enhance their immune system by using technology and Vedic knowledge of Agnihotra. © 2021 IEEE.

关键词： Bacteria

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