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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

共 1546 条记录，以下是921-930 订阅

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Greenhouse Monitoring and Controlling using Cloud-Based Android Application

Greenhouse Monitoring and Controlling using Cloud-Based Andr...

引用

international conference for Convergence of Technology (I2CT)

作者： Tarun Kumar Samli Dilip Kumar Department of Electronics and Communication Engineering Sant Longowal Institute of Engineering and Technology Longowal India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida

Wireless sensor network (WSN) technology is the amalgamation of numerous sensors exploited for monitoring and controlling the physical climate conditions. the integration of WSN technology in greenhouse farming has offered a new direction towards the production of crops. Greenhouse presents a protected environment for the plants/crops and facilitates the farmers in boosting their production. the paper presents a real-time greenhouse monitoring and controlling system. Humidity-Temperature sensor (DHT11), Soil Moisture sensor and Light sensor (LDR) are explored to measure the climate parameters accurately. To collect the real-time monitoring data from these sensors and transmit the data to the Firebase Cloud, the Wi-Fi module ESP8266 is attached to Arduino UNO. Further, an android application is developed for monitoring and controlling climate parameters via smart devices. the proposed model is efficient in terms of services and cost. the proposed automatic greenhouse monitoring and control system can facilitate the farmers in monitoring and controlling the climate conditions automatically as well as manually if the need arises. the developed application is user-friendly and can be efficiently utilized by farmers.

关键词： Wireless sensor networks Cloud computing Atmospheric modeling Green products Prototypes Control systems Real-time systems

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Advanced Graduate Admission Prediction

Advanced Graduate Admission Prediction

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international conference for Convergence of Technology (I2CT)

作者： Srujan Nalam Mohd Aleemuddin Yuva Teja Kadari Nanda Kumar M Dept. of Electronics and Computer Engineering Sreenidhi Institute of Science and Technology Hyderabad India

the process of choosing and narrowing down universities for graduate program admission plays a crucial role in the overall application procedure. this project aims to examine the uses of machine learning models to predict the likelihood of a student being accepted into a master's program. Hence this will provide students with an early indication of their admission prospects. In the past, models were constructed using different algorithms such as random forest, multiple linear regression and k-nearest neighbor. Results have shown that logistic regression out performs these algorithms. the admission of students into educational institutions is a critical issue, and this study addresses the application of machine learning algorithms to predict the chance of admission of students into master's programs. these models include SVM, Gaussian Naive Bayes, and Logistic Regression, with experiments demonstrating that the Logistic Regression model surpasses the others. this will give students a better understanding of their admission prospects in advance.

关键词： Support vector machines Machine learning algorithms Linear regression Predictive models Prediction algorithms software Naive Bayes methods

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Efficient Device Management for Enhanced Energy Utilization and Operational Performance in Internet of things

Efficient Device Management for Enhanced Energy Utilization ...

引用

international conference for Convergence of Technology (I2CT)

作者： Basil Romi Jose S. Mini Department of Computer Science and Engineering National Institute of Technology Goa Goa India

the Internet of things is a rapidly growing field, and the management of IoT nodes is becoming increasingly important. Perpetual energy supply remains a major area of concern for IoT devices. IoT nodes with low energy levels may go into a sleep state, making them unavailable for use and they must be recharged to be reused. the challenge is to select the nodes that should be charged to minimize downtime and maximize uptime. this paper proposes the use of the Gur game algorithm to optimize the management of IoT nodes for maximum uptime and minimum downtime. the Gur game algorithm is used to proactively select the nodes to be charged, considering the current energy levels of the nodes and the utilization of IoT nodes in the network. A preliminary result is proposed in this paper. the proposed method is a unique approach in managing IoT nodes, providing an effective way to ensure optimal utilization of resources and efficient operation of IoT systems.

关键词： Wireless communication Performance evaluation Wireless sensor networks Heuristic algorithms Scalability Games Switches

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Advanced Adaptive PID Controller for BLDC Motor 8

Advanced Adaptive PID Controller for BLDC Motor

引用

8th international conference on computer and Communication engineering, ICCCE 2021

作者： Mahmud, Md Motakabber, S.M.A. Zahirul Islam, A.H.M. Nordin, Anis Nurashikin Fawwaz Wafa, S.A. International Islamic University Malaysia Department of Electrical and Computer Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9781728110646

Brushless DC (BLDC) motors are very popular for applications in automation and electric vehicle systems due to their unique features. Although these motors have many advantages over conventional DC motors, they also suffer some limitations in their functionality due to their direct dependability on the controller driver circuit. the proportional integral derivative (PID) controller is a common and widely used control system in the BLDC motors and various applications. However, this simple system is insufficient to manage the BLDC motors' precise control in variable load, speed, and driving voltage. An auto-tuner can be used with a PID controller to increase the system adaptation. the proposed adaptive PID controller would quickly control the BLDC motors with minimal adjustment time and oscillation. the proposed controller system has been designed using mathematical transfer function modelling and verified by simulation using MATLAB software. Preliminary results showed that the overall ripple is less than 1% and has a faster stabilization time, which is better than other controllers. © 2021 ieee.

关键词： Controllers

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Blockchain Based Adaptive Non-Cooperative Game Strategy For Smart Power Contracts

Blockchain Based Adaptive Non-Cooperative Game Strategy For ...

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international conference for Convergence of Technology (I2CT)

作者： Desh Deepak Sharma Jeremy Lin Atul Sarojwal Ayan Sharma Antas Sharma Department Of Electrical Engineering MJP Rohilkhand University Bareilly India USA Chester Springs National Grid PA USA Department of Electronics and Communication NIT Hamirpur Hamirpur HP India Department of Computer Engineering Bannett University Gr. Noida Gr. Noida India

the peer-to-peer energy trading on the decentralized platform among microgrids requires new approaches to be developed. the heterogeneous microgrids may be surplus or deficit power due to uncertainty in power generation and electric power demand. this paper proposes the blockchain-based adaptive non-cooperative game strategy among the owners of microgrids. the power token-based smart contracts have been created for energy trading among the networked microgrids. the smart contracts are made secure, reliable, and trustworthy with blockchain technology. the distributed identity-based microgrid (DIBM) scheme is designed to avoid the distributed denial of service (DDoS) attack. For the smart power contracts, the hash key has been obtained with python programming and other simulation work has been done in MATLAB.

关键词： Adaptation models Adaptive systems Uncertainty Smart contracts Microgrids Games Tokenization

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Deep Learning based Contactless Biometric Recognition using Bracelet Lines

Deep Learning based Contactless Biometric Recognition using ...

引用

international conference for Convergence of Technology (I2CT)

作者： Ritwik Duggal Aarya Pandya Nitin Gupta Department of Computer Science and Engineering National Institute of Technology Hamirpur Himachal Pradesh India

Biometrics has always been an essential component for the identification of a personnel in every sector, even devices such as smartphones, and smart devices use it these days. Numerous methods have been implemented for biometric identification over the years, such as biometrics using fingerprint recognition, facial recognition and even using the finger knuckles. Contactless Biometrics has been more prevalent over the recent years due to the Covid Pandemic but has paved the way for more efficient and effective biometric systems for using the Bracelet lines on the wrist to identify a person. this work considers applying the YOLO model for the detection of wrists along with Deep Learning Techniques for recognition. the system is created using an Arduino Uno paired with Esp32 CAM for clicking and sending the photo of the user to the server for identification. the simulation results show that the proposed work is efficient enough to provide real-time recognition of the user.

关键词： Wrist Deep learning Biometrics (access control) Simulation Fingerprint recognition Cameras Servers

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ML4Cure: Machine Learning for Healthcare

ML4Cure: Machine Learning for Healthcare

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international conference for Convergence of Technology (I2CT)

作者： Milind Rane Mohit Chawla Aniket. P. More Mokshit Oswal Mohit Burchunde Aniket. A. More Electronics and Telecommunication VIT Pune India Artificial Intelligence and Data Science VIT Pune India Computer Science VIT Pune India Mechanical Engineering VIT Pune India

Nowadays, humans are facing various diseases due to the current climate conditions and habitants. the identification and prediction of such diseases at their earlier stages are much important, so to prevent the extremity of it, we are introducing a machine learning model which will identify person with long term diseases by asking some important questions and reports In order to prepare the data set, symptoms, the person's lifestyle choices, and information on doctor consultations were all considered in the overall illness prediction. Our website provides all the possible outcome and the way to prevent the diseases. If there is a necessity to visit a doctor, we consult best doctor near your location who is best in curing those diseases.

关键词： Machine learning algorithms Hospitals Machine learning Predictive models Prediction algorithms Data models Real-time systems

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Vocals - An App for Vocally Impaired using NLP Conversational Model

Vocals - An App for Vocally Impaired using NLP Conversationa...

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international conference for Convergence of Technology (I2CT)

作者： Prashasthi K Kanchan Sahana S Shreya K Loni R S Raksha Tina Babu Department of Computer Science and Engineering School of Engineering Dayananda Sagar University Bengaluru India

Conversations between humans and machines have become an increasingly common occurrence in today’s digital age. As technology progresses, automated systems are becoming more adept at comprehending and reacting to human language through advancements in language analysis and computational linguistics. While this has brought many benefits, such as improved customer service and faster access to information, there are also some potential drawbacks to consider. though technology is advancing rapidly, they still lack in many aspects such as understanding human emotions, intentions, empathy, flexibility, privacy and security. the main challenge here is how the machine responds relevantly and quickly in a continuous conversation with humans. this research is all about developing an android application that helps vocally impaired people to book appointments easily using a bidirectional LSTM model, text-to-speech and speech-to-text to have a natural conversation with human.

关键词： Privacy Customer services Oral communication Information age Computational linguistics Security Faces

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Deep Learning-Enabled Efficient Storage and Retrieval of Video Streams in the Cloud

Deep Learning-Enabled Efficient Storage and Retrieval of Vid...

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ieee international conference on Smart Cloud (SmartCloud)

作者： Mahmoud Darwich Taghreed Alghamdi Magdy Bayoumi Department of Mathematics and Computer Science University of Mount Union Alliance OH University of Ontario Institute of Technology Oshawa ON Canada Department of Electrical and Computer Engineering University of Louisiana Lafayette LA

In recent years, the rapid growth of video data has presented challenges for efficient storage and retrieval in cloud-based systems. this research proposes a novel approach that utilizes machine learning techniques to address these challenges. the objective is to develop a robust framework that optimizes storage utilization, enhances retrieval efficiency, and maintains video quality with minimal latency. Machine learning algorithms are employed for tasks such as video compression, content analysis, and metadata extraction, enabling effective storage and retrieval mechanisms. the framework leverages advanced video analytics algorithms to extract relevant features, incorporating them into the storage and retrieval process for efficient indexing and organization of video content. the framework adapts to changing workloads and dynamically allocates resources for optimal performance in cloud environments. Extensive experiments and comparisons with existing methods validate the proposed framework, demonstrating significant improvements in storage utilization, retrieval performance, and scalability. Specifically, our framework achieves an average improvement of 25% in storage efficiency compared to another method. It also demonstrates faster retrieval speeds, with an improvement of approximately 10-20%, and achieves higher video quality ratings, with an improvement of approximately 10-20% compared to existing methods.

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Corpus-based Sequence to Sequence with Luong Attention Mechanism for Ilocano to English Translation

Corpus-based Sequence to Sequence with Luong Attention Mecha...

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Recent Advances and Innovations in engineering (ICRAIE)

作者： Christian Jay B. Andres John Kenneth M. Jayme Hewlett Francee G. Fontiveros Jansen Lloyd Gabilan Macabangun Jay M. Ventura Bryan Urita Computer Engineering Program University of Saint Louis Tuguegarao City Philippines

Effective communication is a vital means of conveying ideas, yet language barriers often pose significant challenges for individuals and groups conversing in different languages and dialects. these challenges can result in misunderstandings and misinterpretations due to a lack of clarity in expression. Current Ilocano-English translation systems provide some assistance. However, they struggle with translating Ilocano accurately, especially when the input includes sentences with a higher number of words. To address this issue, our study developed a translator using the Seq2Seq model with Luong Attention Mechanism and employs Neural Machine Translation techniques. the developed translator application achieved notable results with an accuracy of 43.95% for English to Ilocano translation and 81.25% accuracy for Ilocano to English translation, along with a BLEU score of 2.50 and 15.42 across all n-gram levels (1-4 words), respectively. these findings contribute to bridging language barriers and enhancing cross-linguistic communication.

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