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检索条件"机构=Dept. of Information Engineering and Computer Science and Mathematics"

共 8635 条记录，以下是241-250 订阅

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Design and Implementation of the Crib Monitoring System

Design and Implementation of the Crib Monitoring System

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Hu, ZhiJie Chang, Chih-Yung Shen, RuiBing Wu, Shih-Jung Hou, Di Xi'an Eurasia University School of Information Engineering Xi'an China Tamkang University Dept. of Computer Science and Information Engineering Taiwan Xi'an ShiYou University Dept. of Electronic Engineering China

ISBN: (纸本)9798350324174

This paper designs a crib monitoring system based on the STM32 microcontroller. The system uses temperature and humidity sensors to collect the ambient temperature and humidity. The microcontroller processes and analyzes the collected data, and displays it through the display module. When the temperature is higher or lower than the preset threshold, the fan module or heating module is started to adjust the temperature. The temperature threshold is set by the key module. The system will give an alarm when the baby touches the fence to prevent the baby from falling. The system can adjust the motor speed through the key module, aiming to control the crib swing speed. Lullabies are played through the voice broadcasting module to help the baby relax and fall asleep;In addition, the temperature and humidity information is uploaded to the mobile terminal for real-time display through the Bluetooth communication module, and the mobile terminal can also control the motor speed, playing, and music switching. The test result shows that the crib monitoring system has the characteristics of fast response speed, high identification accuracy, and good stability. It can provide a theoretical basis for the actual crib production, and has a certain reference value. © 2023 IEEE.

关键词： Microcontrollers

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Real Time Flight Timing Estimation at Airports Using Kalman Filter 1

Real Time Flight Timing Estimation at Airports Using Kalman ...

引用

1st IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent information Systems, ICAECIS 2023

作者： Sri Siddhartha, Mutyala Sai Saha, Samirit Murali, K. Amrita Vishwa Vidyapeetham Dept. Computer Science Engineering Bengaluru India Amrita Vishwa Vidyapeetham Dept. Mathematics Bengaluru India

ISBN: (纸本)9798350348057

The proposed model aims to utilize Kalman filter-based time forecasting to predict the delay in flights at various airports. Specifically, the model considers five major airports in India, namely Bengaluru, Hyderabad, Mumbai, Kolkata, and Delhi, and assesses various parameters such as temperature, humidity, wind speed, etc. to accurately forecast the actual time of take-off for upcoming flights. The model's performance is evaluated by comparing the predicted, estimated, and actual time of departure of flights at the airport. © 2023 IEEE.

关键词： Kalman filters

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Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge Computing based on Deep Learning Approach 3

Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge ...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Samuel, Amalorpava Mary Rajee Yamuna Devi, M.M. Madhusudhanan, S. Dept. of Electrical and Information Engineering University of Witwatersrand Johannesburg South Africa Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundatio Vijayawada India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9798331532420

Unmanned aerial vehicles (UAVs) are used as supportive edge computing for sparsely located user equipment on a large scale. In this work, we propose and address a collaborative edge computing system involving multiple UAVs as agents in deep reinforcement learning (DRL) approach due to the restricted computation and energy capabilities of UAVs. The challenge of task offloading is being tackled to reduce the total delays in execution and energy usage by simultaneously planning the paths, assigning computation tasks, and managing communication resources of UAVs. Additionally, Lyapunov optimization is incorporated for the system stability of mobile edge computing assisted by multiple UAVs. Exploring a multi-agent deep reinforcement learning framework to achieve a combined strategy to manage task allocation, and power management. The sum rate results of the evaluation show that our method for task offloading using multi-UAV and multi-EC achieves superior performance with 25 % increase when compared to other optimization methods and ability to reduce cost and delay. © 2024 IEEE.

关键词： Energy utilization

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Secrecy Capacity Optimization in RF/FSO Systems: Impact of Mixed Rayleigh and Log-Normal Fading with Atmospheric Turbulence

Secrecy Capacity Optimization in RF/FSO Systems: Impact of M...

引用

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

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

This paper investigates the secrecy capacity optimization in RF/FSO systems with mixed Rayleigh and log-normal fading, while masking eavesdroppers channel state information () as well as suffering from atmospheric turbulence. We explore the impact of several parameters including beamforming angles, modulation schemes and hybrid RF/FSO link configurations through a combination of simulations as well as analytical models. Secrecy capacity is enhanced for an improved SNR and vice versa under higher turbulence conditions and cooler influents eavesdropped scenarios. Performance of the hybrid RF/FSO systems dominates considerably over single-link solutions, especially at longer distances. All these mechanisms appreciably increase the secrecy capacity, while beamforming and advanced modulation techniques offer most of the improvement. The study also demonstrates the interdependencies of system parameters, providing guidelines for designing secure communication systems under different environmental and operational conditions. © 2024 IEEE.

关键词： Beamforming

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Digital Image Encryption Based On Elliptic Curve Cryptography 4

Digital Image Encryption Based On Elliptic Curve Cryptograph...

引用

4th IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2024

作者： Hasan, Mahmoud H. S. Ahmed, Medht H. S. H. Alasmarya Islamic University College of Information Technology Dept. Computer Science Zliten Libya Higher Institute of Engineering Technology Dept. Communication Engineer Zliten Libya

ISBN: (纸本)9798350372632

information security is currently a major problem for data communication. Cryptography has emerged as a treatment and is essential to information security systems. Techniques for encryption can effectively prevent attacks on images. Elliptic curve cryptography (ECC) is an approach of public-key encryption, depends on the algebraic grouping of elliptic curves over finite fields. The present study introduces an intriguing elliptic curve cryptography-based image encryption approach and applied it to various images. The proposed technique was tested. We computed the number of pixels change rate (NPCR), unified average changing intensity (UACI), and peak signal to noise ratio (PSNR) to assess the effectiveness of the suggested technique. © 2024 IEEE.

关键词： Geometry

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Smart bracelet based on the Internet of Things

Smart bracelet based on the Internet of Things

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

ISBN: (纸本)9798350324174

With the development of the economy and the improvement of people's living standards, more and more people start to pay attention to health and exercise, and the smart bracelet is born. The designed smart bracelet in this paper can collect data such as heart rate, exercise, temperature, humidity, altitude, atmospheric pressure, and light intensity in the current environment. The collected data are processed by the STM32F103C8T6 controller. Then the processed data is displayed in the OLED display module. In addition, the corresponding data can be uploaded to the mobile phone for real-time display through the Bluetooth communication module. The test results show that the system is stable and reliable. © 2023 IEEE.

关键词： Bluetooth

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Constructing Disease Comorbidity Networks Using Statistical Methods from Electronic Health Records

Constructing Disease Comorbidity Networks Using Statistical ...

引用

2023 IEEE International Conference on Network, Multimedia and information Technology, NMITCON 2023

作者： Bramesh, S.M. Anil Kumar, K.M. P. E. S. College of Engineering Dept. of Information Science & Engineering Mandya India Jss Science and Technology University Dept. of Computer Science & Engineering Mysuru India

ISBN: (纸本)9798350300826

Disease comorbidity is a prevalent and significant concern in modern medical practice. Patients in such circumstances will need specialized medical interventions. This study proposes a network-based computation model to extract the disease comorbidity patterns by utilizing the electronic health records of a 'Diabetes 130-US hospitals for years 1999-2008' dataset. The estimate of disease-disease relationships using statistical methods is a crucial step in this paradigm. A Disease Comorbidity Network (DCN) was constructed based on these relationships. This model can then be used to extract the corresponding illness comorbidity patterns for various races and genders, using the endocrine disease (diabetes) as an example to determine the associations between various diseases and their comorbidities. The outcomes of this research demonstrated that the strength of some interesting and or clinically relevant disease associations (Example: musculoskeletal disorder and endocrine disorder, nervous disorder and endocrine disorder) is stronger in male patients than in female patients. Also, observed that the endocrine-specific comorbidity patterns will vary based on the race and gender of a patient. Finally, extracted comorbidities patterns are validated with medical literature as well as with the state of art method. Notably, this study exploits the network-level relationships between diseases, which will improve our perception about disease associations at the level of the patient population. © 2023 IEEE.

关键词： Statistical methods

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Deep Learning for Channel Prediction in Non-Stationary Wireless Fading Environments

Deep Learning for Channel Prediction in Non-Stationary Wirel...

引用

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

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Data Science and Quantum Computing ABV Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9798350379525

In non-stationary wireless fading channels deep learning models are effective in predicting channel states as indicated by this study. This work compared the LSTM and GRU models with autoregressive methods or Kalman filter, implying that deep learning is indeed able to capture temporal dependence between variables and was likely more adapted than linear method when dealing with many changes in dynamics. From the perspective of pre-processing data, keys like attention mechanism and transfer learning were decisive elements in helping them to improve prediction scores and make models more robust. These results showed that these enhanced procedures allow the models to generalise over a wide range of non-stationary situations, generating consistent performance in various diverse environments. This study indicates the promise of deep learning for enhancing wireless network operation, which could lead to greater self-awareness and utilization features in emerging future-generation wireless systems. © 2024 IEEE.

关键词： Prediction models

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Formal Algebraic Model of a Generic BCube Data Center Network Architecture 5

Formal Algebraic Model of a Generic BCube Data Center Networ...

引用

5th International Conference on Electrical, Communication and computer engineering, ICECCE 2024

作者： Roig, Pedro Juan Alcaraz, Salvador Gilly, Katja Bernad, Cristina Juiz, Carlos Miguel Hernández University Dept. of Computing Engineering Alicante Elche Spain University of the Balearic Islands Dept. of Mathematics and Computer Science Palma de Mallorca Spain

ISBN: (纸本)9798331529437

The optimization of data center performance need to consider different points of view, such as higher bandwidth, lower latency, lower costs, lower energy efficiency, or higher resource capacity. However, the selection of an appropriate data center network architecture is one of the key features as it can make a difference in some of those points. In this paper, a formal algebraic model of a generic BCube is presented ir order to remark the main characteristics of this server-centric approach. © 2024 IEEE.

关键词： Network architecture

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Improving Liver Disease Diagnosis Through Generative Adversarial Network Driven Synthetic Tabular Data

Improving Liver Disease Diagnosis Through Generative Adversa...

引用

2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Mahendran, S. Venkatasekhar, D. Shanmugasundaram, G. Annamalai University Department of Information Technology Chidambaram India Chennai Institute of Technology Dept. of Computer Science & Engineering Chennai India

ISBN: (数字)9798331540821

ISBN: (纸本)9798331540821

Liver ailments pose a significant worldwide health concern, with their extensive effects and severe repercussions highlighting the pressing necessity for precise diagnosis. Diagnosing hepatic disorders is frequently intricate and expensive. This work presents a Generative Adversarial Network (GAN) based methodology for producing synthetic tabular data to enhance early prediction of liver ailments, employing a dataset of Indian liver patients. The contribution of the work is the introduction of innovative architecture that integrates Stacked Ensemble Model with advanced preprocessing techniques and the use of Generative Adversarial Networks for data augmentation not extensively explored in current data-driven machine learning approaches for liver ailments prediction. The Stacked Ensemble Model has two tiers: the base-level and the meta-level. The base-level learning component trains various base learners, including Gradient Boosting, Ride classifier, Multi-layer Perceptron, and LightGBM on the input dataset. A strong prediction model is then constructed by combining and feeding the outputs of these several classifiers into a Random Forest classifier, which is the meta-learner. The results show that the model performs much better when synthetic data generated by GANs is included, obtaining an overall accuracy of 95%. This approach aims to greatly improve the prediction of liver ailments, hence enabling quick intervention and more effective treatment. © 2024 IEEE.

关键词： Generative adversarial networks

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