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Systematic Review: Face Recognition Algorithms for Photos and Real-Time Applications 5

Systematic Review: Face Recognition Algorithms for Photos an...

引用

5th International Conference on Mobile Computing and Sustainable informatics, ICMCSI 2024

作者： Ranmale, Sumant Jagdale, Balaso Dr. Vishwanath Karad MIT World Peace University Dept. of Computer Engineering and Technology Maharashtra Pune India

ISBN: (纸本)9798350395235

Face recognition technology has many uses in the distribution of photographs, from detecting persons in pictures to automatically grouping pictures based on people's faces. Several methods have been proposed for face detection, including deep learning methods like Convolutional Neural Networks and Histogram of Oriented Gradients. This study analyzes the suitability of CNN and HOG algorithms for recognizing faces with higher accuracy and speed. The accuracy of the algorithms implemented and the standard of quality of the images determine how well face recognition technology performs in the distribution of photographs. Further, this study also contributes to present effectiveness and impact on storing and retrieving images as well as its advantages and disadvantages in the context of image distribution applications. © 2024 IEEE.

关键词： Face recognition

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A Data-Driven Approach to Time-Domain Electromagnetic Modeling Based on Dynamic Mode Decomposition

A Data-Driven Approach to Time-Domain Electromagnetic Modeli...

引用

2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Zhang, Yanming Gao, Steven Jiang, Lijun Chinese University of Hong Kong Dept. of Electronic Engineering Shatin Hong Kong Missouri University of Science and Technology Dept. of Electrical and Computer Engineering RollaMO United States

ISBN: (纸本)9798350355581

This paper presents a data-driven methodology that utilizes Dynamic Mode Decomposition (DMD) for the time-domain (TD) electromagnetic (EM) modeling of microwave devices. As an unsupervised machine learning technique, DMD leverages a limited set of unlabeled spatio-temporal electromagnetic (EM) data to determine DMD eigenvalues and eigenmodes. Then, the obtained DMD model reconstructs the dynamics as a series of exponential terms based on linear assumptions. The effectiveness of this approach is demonstrated through the TD EM modeling of photonic crystal waveguides. Comparative analysis with the finite-difference time-domain (FDTD) method shows that the DMD model not only achieves precise modeling but also facilitates robust short-term forecasting. © 2024 IEEE.

关键词： Dynamic mode decomposition

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BanijyaPrayukti: E-Commerce Recommendation Engine for Sustainable Products 7

BanijyaPrayukti: E-Commerce Recommendation Engine for Sustai...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Pradhan, Aditya Ghosh, Amartya Mondal, Rintu Saxena, Kumar Abhi Dutta, P.K. Mitra, Anirban Dept. of Computer Science and Engineering Amity School of Engineering and Technology Kolkata Kolkata India Dept. of Electronics and Communication Engineering Amity School of Engineering and Technology Kolkata Kolkata India

ISBN: (纸本)9781839539831

The rapid growth of e-commerce has revolutionized the way businesses operate and interact with customers. E- commerce has revolutionized the way businesses operate, making it easier than ever to reach customers and sell products. However, with this convenience comes a challenge: how can we promote sustainable products and encourage consumers to make eco- friendly choices? The primary objective of this project is to pro- mote sustainability by utilizing artificial intelligence techniques in recommending eco-friendly alternatives. Our goal is to provide users with recommendations on sustainable products based on their shopping history, behavior patterns, and demographic information. The system continuously learns from user interactions, enabling it to provide increasingly accurate and personalized recommendations over time. © The Institution of engineering & technology 2023.

关键词： Electronic commerce

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Enhancing Early Detection of Pancreatic Cancer: A Machine Learning Approach with Explainable AI Insights

Enhancing Early Detection of Pancreatic Cancer: A Machine Le...

引用

2024 IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2024

作者： Pattanashetti, Neeraj V Mayur, R. Prakash, Adarsh Adiga, Tryambaka B Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Information Science & Engineering Karnataka Bangalore India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798350376876

Among the most deadly and complex illnesses in the world, pancreatic cancer is typified by its early asymptomatic stage and subsequent discovery of the disease when it has progressed to an advanced stage. Getting the patients in a correct treatment path at the earliest point is important for suitable intervention and patient outcomes in the long run. We utilized advanced algorithms and model prediction techniques includes, feature extraction, hyperparameter tuning and explainability methods which aims to enhance both the comprehension and predictive accuracy of models employed. The goal is to assess patient health status and diagnose pancreatic diseases (cancer vs. non-cancer) by developing a learning algorithm. We obtained a dataset containing demographic information and urine biomarkers to start the investigation. First stage of our analysis employs a single classifier and later we apply bagging and boosting algorithms to achieve ensemble models. Hyperparameter fine-tuning has got a positive outcome, which has Gradient Boosting and Cat Boosting as its top performing models. The ensemble model produced excellent results (92.02 %), demonstrating the usefulness of the suggested approach. LIME and SHAP techniques play the key role in model outcome interpretability providing an insight of algorithmic decision-making process. Such a wide range of combinations of biomarkers have a potential of pancreatic cancer detection in early stages and thus will help shape diagnostics strategies in near future. © 2024 IEEE.

关键词： Diseases

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A multi-point capacitive sensing smart clothing applied to posture detection

A multi-point capacitive sensing smart clothing applied to p...

引用

2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Liao, Kuo-Cheng Wu, Ze-We Chen, Shih-Hung Chen, Chi-Chun Ming Young Biomedical Corp. Miaoli Taiwan National Chin-Yi University of Technology Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

This study introduced a system of multi-point capacitive sensing smart garment designed for posture detection. This smart garment utilized multiple capacitive sensors placed at different positions to monitor changes in body posture movements. These sensors were capable of detecting subtle variations between the garment and the wearer's body and translating this data into understandable information. By analyzing the collected data, this smart garment can provide real-Time monitoring of the user's posture, such as standing, sitting, or lying down. © 2024 IEEE.

关键词： garment multi-point capacitive sensing posture respiration

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A PID Control Algorithm for Path Tracking of a Nonholonomic Car-Like Robot 1

A PID Control Algorithm for Path Tracking of a Nonholonomic ...

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1st IEEE International Symposium on Consumer technology, ISCT 2024

作者： Siradjuddin, Indrazno Prayoga, Dimas Adi Wibowo, Sapto Syaifudin, Yan Watequlis Wicaksono, Rendi Pambudi Achmadiah, Mas Nurul State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Madiun Dept. of Computer Control Engineering Madiun Indonesia

ISBN: (纸本)9798350365191

A car-like robot with an Ackermann steering system is a type of nonholonomic which is characterised by a set of first-order differential constraints on its configuration variables, which are not integrable. This distinctive characteristic gives rise to complex issues in the construction of feedback controllers. This research proposes reactive control using a feedback controller using PID algorithm for a car-like robot navigation. The proposed method controls the steering angle of the car-like robot to follow the prescribed path with a constant longitudinal robot velocity. The open-loop car-like dynamical system has been formulated in the form of state-space model. Two PID controllers in parallel computed the lateral position error and the yaw angle error. The summation of the two outputs from the PID controllers was inputted into the state-space model. The PID controller parameters were selected based on trial and error. The simulation results confirm the effectiveness of the proposed control algorithm. © 2024 IEEE.

关键词： Three term control systems

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Design and Develop an Efficient Load Balancing Approach with AOMDV Routing in 7G-FANET 4

Design and Develop an Efficient Load Balancing Approach with...

引用

4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Soni, Gaurav Chandravanshi, Kamlesh Deoskar, Devashri Parashar, Sadhana Thakur, Ruchi Vit Bhopal University School of Computing Science and Engineering Kothrikalan Bhopal-Indore Highway Madhya Pradesh Sehore India Lakshmi Narain College of Technology Dept. of Computer Science and Engineering Raisen Road Madhya Pradesh Bhopal India Bansal Institute of Research and Technology Dept. of Computer Science and Engineering Kokta Bypass Rd Anandnagar Madhya Pradesh Bhopal India Sati Dept. of Computer Science and Engineering Madhya Pradesh Vidisha India

ISBN: (纸本)9798331518981

The congestion in the Flying Ad hoc Network (FANET) is due to insufficient bandwidth or a heavy load on the network. The multipath routing protocol AOMDV (Ad -hoc On-demand Distance Vector) is used for balance the load in network. The multiple routes serve as backup routes for data transmission in the connection breakdown. The speed of the Seventh Generation (7G) is much higher than other generations of wireless networks. 7G has a speed of 100 Gigabits, which reduces communication latency. To optimize the bandwidth capacity, we must shift the load to other or alternative routes for handle congestion and proper load balancing. In this paper, propose a delay estimation rate-based control scheme to improve UAV-to-UAV communication in 7G-FANET. The Efficient Load Balancing AOMDV (ELAOMDV) scheme furnishes data on the number of packets that failed to reach their destination. The variation in the rate of transmission is based on the delay of successful acknowledgement. The proposed approach is to avoid the risk of congestion and balance the load on a specific link. 7G has the advantage of rapid communication. The ELAOMDV congestion management strategy is to minimize the latency and buffer overflow caused by network congestion. The delay difference confirms the existence of congestion and indicates the availability of multipath to balance the load. The performance of ELAOMDV is better than the multipath ad hoc on demand protocol (MAODV). All of the performance metrics showing improved results, indicating that the ELAOMDV approach has improved routing performance in 7G-FANET. © 2024 IEEE.

关键词： Bandwidth

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Explainable AI for Enhanced Intrusion Detection Systems 3

Explainable AI for Enhanced Intrusion Detection Systems

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Ananya, G. Siri, N. Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Electronic and Communication Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bengaluru India

ISBN: (纸本)9798350354171

As everything is turning digital there is a hike in the invasion of digital space, because of which advanced tools are needed. One such tool is the Intrusion Detection System (IDS). In this work, we have tried to detect and classify suspicious connections accurately. This is done by incorporating advanced computing into Intrusion Detection Systems. To achieve this, we have used the Coburg Intrusion Detection Dataset. To achieve this, we used the Coburg intrusion detection dataset. We investigate the effectiveness of Single Classifiers and Bagging and Boosting in this context. We proposed a four-stage Ensemble model to classify the connections using its attributes. The proposed model uses four Single Classification models: Logistic Regression, KNN, Decision Tree, and SVM. Before applying the algorithms, the data was Preprocessed. Later, the models were hyper-tuned to increase the accuracy. The results showed that Random Forest outperforms other single classifiers and machine learning algorithms, with a mean accuracy of 99.99%, a precision of 99.99%, and an F1-score of 99.99%. Furthermore, as models are usually hard to understand by using Explainable AI we can increase the transparency of the model. Explainable AI techniques are used to make the advanced computing models reliable and more understandable. This study aims to develop advanced and dependable intrusion detection systems. © 2024 IEEE.

关键词： Network intrusion

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A smart clothing sensing system for long-term ECG Monitoring

A smart clothing sensing system for long-term ECG Monitoring

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Chen, Shih-Hung Liao, Kuo-Cheng Wu, Ze-We Chen, Chi-Chun Ming Young Biomedical Corp. Miaoli Taiwan National Chin-Yi University of Technology Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

This study integrated smart garment, data acquisition device (DAD), iPad and remote server to develop an ECG measurement system for long-term healthcare monitoring in daily life. This system allowed the subjects to measure in a comfortable state, and their movements are not restricted. The experimental results showed that good ECG signals can be acquired from sleeping, sitting, standing and walking. Therefore, the system can not only be applied to daily long-term monitoring, but also has the opportunity for clinical application. © 2024 IEEE.

关键词： data acquisition device ECG iPad long-term remote server smart garment

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IoT based Truck Wheel Temperature Monitoring System

IoT based Truck Wheel Temperature Monitoring System

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Zaid, Mohd Ahmad, Nadeem Aljamal, Mohammed Patel, Sarosh Khan, Asif Dept. of Computer Science and Engineering Integral University Lucknow India Dept. of Electronics and Communication Engg. Goel Institute of Technology and Managment Lucknow India School of Engineering University of Bridgeport United States Integral Robotics Lab Dept. of Computer Application Integral University Lucknow India

ISBN: (纸本)9798350374933

The main objective of this paper is to design an IoT based truck wheel temperature monitoring system using Arduino board with the aim to overcome endanger and raise the safety measures for truck and goods. By designing and implementing a temperature-detecting system, we can detect the temperature of the wheels trucks. By the use of such detecting device we can prevent the major problem associated with wheel’s temperature and may avoid the major accidents. This monitoring system senses the temperature data of the wheel and transmits through the Wi-Fi module. In addition, it upgrades Thingspeak channel that can collect the data and it can easily be accessed by the transport agency and the truck driver. This can further be analysed using any computer system or mobile with internet connectivity anywhere across the globe to take real-time decision. The core function of the proposed detecting system is to monitor the real- time value of truck wheel temperature and to inform the concerned people. © 2024 IEEE.

关键词： Wi-Fi

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