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

共 55698 条记录，以下是571-580 订阅

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Churn Buster: Uncovering Patterns and Predicting Churn in OTT Platforms 6

Churn Buster: Uncovering Patterns and Predicting Churn in OT...

引用

6th Parul International Conference on engineering and Technology, PICET 2024

作者： Anand, Akshat Sarika, D. Malviya, Harshit Vatsa, Dipti Yadwad, Sunita Adarsh Dholariya, Shreya M. Dept. Computer Science Engineering Parul Institute of Engineering and Technology Vadodara India

ISBN: (纸本)9798350369748

Churn, a common concern among business leaders, poses a significant challenge in today's fast-paced world where consumer attention spans are short. This research focuses on churn analysis within the OTT streaming platform sector, essential for retaining subscribers and ensuring business longevity. Utilising data preprocessing methods and machine learning algorithms, this study aims to identify factors influencing churn and provide insights for targeted retention strategies. The dataset includes 16 variables, with churn serving as the binary-dependent variable. Data preprocessing involved addressing missing values and converting categorical data into numerical format. Four machine learning models-Random Forest, XGBoost, K-Nearest Neighbors, and Support Vector Machine-were applied, with Random Forest achieving the highest accuracy of 89%. Evaluation metrics like confusion matrices, ROC curves, and Precision-Recall curves were used to evaluate model performance, revealing Random Forest's effectiveness in churn prediction. Principal Component Analysis (PCA) was employed to handle the complexity of user data, aiding in the identification of influential churn factors. This study emphasises the importance of understanding customer behaviour and utilising machine learning to forecast subscription choices. The insights gained provide valuable guidance to OTT companies for enhancing customer satisfaction and retention strategies, ensuring competitiveness in a dynamic industry landscape. © 2024 IEEE.

关键词： Sales

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Detection of Cardiovascular Disease from ECG Image Using Optimized Weighted Average Ensemble Machine Learning Technique 26

Detection of Cardiovascular Disease from ECG Image Using Opt...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Hasan, Md. Nahid Hossain, Md. Ali Akash, Ahsan Sadek Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Bangladesh Pabna University of Science & Technology Dept. of Computer Science & Engineering Bangladesh

ISBN: (纸本)9798350359015

cardiovascular diseases (CVD) stand as a prominent global cause of death in worldwide. Timely identification and intervention are paramount in dealing with heart disease, as its failure to detect and treated promptly can lead to life-threatening outcomes. The Electrocardiogram (ECG) Signals are mainly used as diagnostic tools that routinely assess the electrical and muscular function of the heart. Until recently, ECG records were predominantly maintained in paper form;thus, manually examining and re-examining the ECG paper records are often proved time-consuming and laborious tasks. Therefore, this research work utilizes, the power of machine learning and deep learning in predicting four different cardiac abnormalities named Abnormal Heartbeats (AHB), History of Myocardial Infarction (HMI), Myocardial Infarction (MI), and Normal Heartbeats (NHB) from paper-based ECG images. Different image pre-processing methods have been employed to improve the quality of individual ECG images and a novel lightweight deep neural model is proposed for extracting prominent features from each ECG images. Finally, we used an optimized weighted average ensemble technique for the final prediction. The grid search technique is used to find the optimal parameters and weights of each machine-learning model. Our proposed model shows state-of-the-art results in accuracy, precision, recall, and f1-score of 99.29%, outperforming the existing work. The model has attained an Area Under Curve (AUC) score of 99.96%. © 2023 IEEE.

关键词： Cardiovascular disease convolution neural network (CNN) deep learning ECG image feature extraction image classification machine learning weighted average ensemble

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Post Quantum Code-Based Cryptosystems with Dual Inverse Matrix 13

Post Quantum Code-Based Cryptosystems with Dual Inverse Matr...

引用

13th International Conference on Information Technology in Asia, CITA 2023

作者： Makoui, Farshid Haidary Gulliver, T. Aaron Dakhilalian, Mohammad University of Victoria Dept. of Electrical & Computer Engineering VictoriaBC Canada Isfahan University of Technology Dept. of Electrical & Computer Engineering Isfahan Iran

ISBN: (纸本)9798350326208

The Shor algorithm demonstrates the significant risk that quantum attacks pose to the security of widely used cryptographic primitives. However, code-based cryptography has been shown to be resistant to these attacks. To date, no polynomial-time attack exists that can break code-based cryptosystems such as the McEliece cryptosystem. Despite this, these cryptosystems are not employed in practical applications in domains such as online banking, blockchains, and e-commerce platforms. The primary reason is the large sizes of the public and private keys associated with code-based cryptosystems. In this paper, a new code-based cryptosystem is introduced which employs a dual matrix based on the transpose and inverse of the parity check matrix to reduce the key size compared to the McEliece cryptosystem. © 2023 IEEE.

关键词： Public key cryptography

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Effective Pest Detection by YOLOv5 with BottleneckCSP 2

Effective Pest Detection by YOLOv5 with BottleneckCSP

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2nd International Conference on Power, electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Tani, Ishrat Zahan Jannat, Tasmia Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh

ISBN: (纸本)9798331517984

Pest damage poses a significant risk to crop quality and productivity, underscoring the necessity for accurate and efficient detection methods for farmers. Artificial intelligence (AI) facilitates targeted pest management with reduced reliance on broad-spectrum insecticides and enables early detection of insect infestations. Object detection, a computer vision approach, is revolutionizing pest identification in agriculture by locating pests in digital crop photographs. However, the detection of tiny objects within these datasets presents challenges due to sparse spatial information. In response to this challenge, we have replaced the C3 block of YOLOv5 with the BottleneckCSP module, which is more effective for feature mapping of tiny objects. Our enhanced model demonstrates superior performance on the IP102 dataset, which is characterized by the presence of tiny objects. Comparative analysis reveals that our BottleneckCSP-integrated model significantly improves feature mapping, resulting in a notable increase in mean average precision (mAP). Specifically, our modified model achieves an mAP of 63.9%, outperforming many state-of-the-art methods on this dataset. This advancement in the YOLOv5 architecture sets a new benchmark for AI-powered precision agriculture, providing farmers with a highly efficient tool for crop protection and pest management. The significant performance gains highlight the potential of our approach to transform current agricultural practices, paving the way for more sustainable and effective pest control strategies. © 2024 IEEE.

关键词： Damage detection

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Survey on Graph Neural Networks for Imitation Learning: Algorithms and Applications 15

Survey on Graph Neural Networks for Imitation Learning: Algo...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Hwang, Injun Jung, Soyi Ajou University Dept. of Electrical and Computer Engineering Suwon16499 Korea Republic of

ISBN: (纸本)9798350364637

This survey examines the integration of graph neural networks (GNNs) and imitation learning (IL), focusing on the algorithms that merge these technologies and their practical applications. It explores how GNNs are used to effectively embed task-relevant information and how IL enables agents to replicate complex tasks. The review covers several key algorithms and examines their use in robotics, transportation, and engineering, highlighting the potential of GNNs and IL to enhance decision-making and performance in intricate environments. © 2024 IEEE.

关键词： Adversarial machine learning

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Intelligent Traffic Management System: An Advanced Solution 7

Intelligent Traffic Management System: An Advanced Solution

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Rushi, Tankala Zamaan, Shaik Mohammad Pravin, A. Sathyabama Institute of Science And Technology Dept. of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350359299

The Intelligent Traffic Management System (ITMS) is a cutting-edge solution designed to address multiple aspects of traffic management and safety. This advanced system incorporates various technologies to tackle issues such ashelmet compliance, traffic signal violations, number plate identification, cell phone usage tracking, and proximity-based police station alerts. By leveraging the power of artificial intelligence and machine learning algorithms, the ITMS can accurately detect and enforce helmet compliance among motorcyclists, ultimately reducing the risk of head injuries in road accidents. Furthermore, the system utilizes advanced video analytics to detect violations of traffic signals, ensuring that motorists adhere to traffic rules and regulations. Additionally, the ITMS employs automatic number plate recognition (ANPR) technology to quickly and efficiently identify vehicles with illegal or expired license plates, enabling law enforcement agencies to take appropriate action. Moreover, the system includes a cell phone usage tracking feature which uses computer vision techniques to identify drivers who are using their phones while driving, contributing toa decrease in distracted driving incidents. Lastly, by introducing proximity-based police station alerts, the system offers a comprehensive approach to address challenges and improve efficiency, the ITMS enables prompt response from law enforcement agencies by automatically notifying the nearest police station in the event of a traffic violation or accident. In summary, the Intelligent Traffic Management System provides a comprehensive and holistic approach to management and safety through itsfeatures of helmet compliance, traffic signal violation detection, number plate identification, cell phone usage tracking, and proximity-based police station alerts. © 2024 IEEE.

关键词： Traffic signals

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User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-Contact Fingerprint Captures 58

User Authentication and Vital Signs Extraction from Low-Fram...

引用

58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Olugbenle, Olaoluwayimika Drake, Logan Venkataswamy, Naveenkumar G. Rahman, Arfina Afolayanka, Yemi Imtiaz, Masudul Banavar, Mahesh K. Clarkson University Dept. of Electrical and Computer Engineering PotsdamNY United States

ISBN: (纸本)9798350354058

We present our work on leveraging low-frame-rate monochrome (blue light) videos of fingertips, captured with an off-the-shelf fingerprint capture device, to extract vital signs and identify users. These videos utilize photoplethysmography (PPG), commonly used to measure vital signs like heart rate. While prior research predominantly utilizes high-frame-rate, multi-wavelength PPG sensors (e.g., infrared, red, or RGB), our preliminary findings demonstrate that both user identification and vital sign extraction are achievable with the low-frame-rate data we collected. Preliminary results are promising, with low error rates for both heart rate estimation and user authentication. These results indicate promise for effective biometric systems. We anticipate further optimization will enhance accuracy and advance healthcare and security. © 2024 IEEE.

关键词： Photoplethysmography

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Physical-Design Aware Scan Cell Reordering for Low Power Testing

Physical-Design Aware Scan Cell Reordering for Low Power Tes...

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2024 IEEE East-West Design and Test Symposium, EWDTS 2024

作者： Badjatya, Rohit Vinay Kumar, Rahul Tudu, Jaynarayan T Fujita, Masahiro Singh, Virendra Indian Institute of Technology Bombay Dept. of Electrical Engineering Mumbai India Indian Institute of Technology Tirupati India Dept. of Computer Science Engineering Tirupati India University of Tokyo Dept. of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798331515768

Scan chain architecture is widely employed in modern VLSI design for test applications. However, it often leads to high power consumption during testing. The architecture experiences elevated simultaneous switching activity due to non-functional input patterns applied during test time, resulting in significant peak power in the circuits. This increased power consumption can cause IR drop issues, negatively impacting the chip's yield. This paper proposes an innovative approach to reduce both peak power and routing length by effectively reordering the scan chains. Experimental results show that the proposed approach is effective for the ISCAS'89 and ITC'99 benchmark circuits and this method achieves lower peak power and routing length compared to the state of the art. © 2024 IEEE.

关键词： low power testing peak power routing constraint scan chain reordering voltage drop

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Gallium Nitride-based 48V-to-1V Point-of-Load (PoL) Converter for Aerospace Telecommunications and Computing Applications 39

Gallium Nitride-based 48V-to-1V Point-of-Load (PoL) Converte...

引用

39th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2024

作者： Ellis, Nathan M. Zhu, Yicheng Pilawa-Podgurski, Robert C.N. University of California Dept. of Electrical Engineering and Computer Sciences Berkeley United States

ISBN: (纸本)9798350316643

This paper presents a regulating Hybrid Switched Capacitor Converter (HSCC) topology suitable for high conversion ratio Point-of-Load (PoL) applications, specifically targeting 48 V to 1 V power delivery in space-based high-performance computing systems, where size and weight are important considerations, along with device de-rating for radiation tolerance. The proposed topology merges an initial 2:1 switched capacitor conversion stage with a recently developed symmetric dual inductor hybrid (SDIH) conversion stage, reaping benefits of both. The SDIH stage offers reduced component count and an excellent switch stress figure of merit, while the initial 2:1 voltage reduction stage significantly reduces the volume of flying capacitors, enabling compact size and low weight. A high density gate drive solution is also presented, using a minimal number of driver ICs without compromising on driving capability. A preliminary hardware prototype demonstrates this topology's feasibility while employing de-rated gallium nitride (GaN) switches to safeguard against radiation total ionizing dose (TID) and single event effects (SEE). This prototype achieves a very high measured power density of 2,020 W/inch3 (123.3 kW/liter) while performing 48 V to 1 V conversion and switching at 1 MHz. © 2024 IEEE.

关键词： Gallium nitride

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A Formal Quality Control System for Millimetre-Wave Channel Sounder Verification 100

A Formal Quality Control System for Millimetre-Wave Channel ...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Chen, Xin Michelson, David G. The University of British Columbia Dept. of Electrical & Computer Engineering VancouverBC Canada

ISBN: (纸本)9798331517786

Various hardware and software defects may distort or impair the channel-measurement data produced by millimetre-wave channel sounders. The IEEE Standard Association's P2982 standards development effort was begun with the understanding that the ad hoc and incomplete verification methods in common use today are inadequate for the task and a consensus-based approach is the best method to achieve methods that are complete, effective, and economical and which will be widely accepted and adopted. Past efforts have focused on identifying discrepancies between actual and expected channel responses, but have not incorporated these processes into a formal quality control system. Here, we show how formal quality control can be incorporated into the P2982 vison for millimetre-wave channel sounder verification and thereby: 1) allow more effective identification and correction of shortcomings in channel sounder performance and/or post-processing techniques, 2) give greater confidence that a given set of channel measurement data is suitable for inclusion in a pooled database, and 3) align more closely with metrology practices in other disciplines. © 2024 IEEE.

关键词： Sounding apparatus

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