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Trade Ease with Machine Learning and AWS

IEEE Access 2023年 11卷 25893-25905页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research. © 2013 IEEE.

关键词： Deep neural networks

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Physician Scheduling using Constraint Satisfaction programming 11

Physician Scheduling using Constraint Satisfaction Programmi...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Bakr, Hend A. Salama, Ahmed M. Fares, Ahmed Zaky, Ahmed B. Cairo University Biomedical Engineering Program Faculty of Engineering Giza Egypt Benha University Computer Systems Engineering Program Faculty of Engineering at Shoubra Banha Egypt Computer science and information technology Programs Alexandria Egypt Benha University On leave from Computer Systems Engineering Program Faculty of Engineering at Shoubra Egypt

ISBN: (纸本)9798350369328

Physician scheduling is a critical task that impacts the quality of patient care, staff satisfaction, and operational efficiency in healthcare institutions. The traditional approach to physician scheduling is manual and time-consuming, which can result in errors, staff burnout, and suboptimal schedules. To address these challenges, researchers have turned to optimization techniques like CSP, which has shown promise in solving physician scheduling problems. This paper reviews the existing literature on CSP for physician scheduling and highlights the benefits and limitations of this approach. CSP's benefits include generating schedules quickly and efficiently, incorporating complex constraints and preferences, and handling changes and disruptions in real time. However, CSP also has some limitations, such as the need for a formalized model and the fact that it may not always generate the most intuitive schedules. Overall, the findings suggest that CSP is a promising approach to physician scheduling that can produce high-quality schedules while minimizing staff burnout and improving operational efficiency. © 2023 IEEE.

关键词： Constraint satisfaction problems

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computer Vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

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2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Analyzing Patterns of Violence Against Women in Pernambuco Using Self-Organizing Maps and Apriori Algorithm

Analyzing Patterns of Violence Against Women in Pernambuco U...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Da Silva, Brenda Barros Alves Pereira, Rodolfo Moreira De Oliveira Rodrigues, Cleyton M. De Araujo Fagundes, Roberta Andrade Polytechnic School of Pernambuco POLI/UPE Graduate Program in Computer Engineering Recife Brazil

ISBN: (纸本)9798350374575

This study investigates significant patterns of violence against women in Pernambuco using Self-Organizing Maps (SOM) and the Apriori algorithm. The methodology includes trend analysis, clustering, and association rule mining, utilizing data from the Ministério da Mulher covering 2015 to 2021. The exploratory data analysis identified demographic, temporal, and spatial trends in violence. SOM was employed for dimensionality reduction and clustering, revealing three clusters representing 5.24%, 19.68%, and 75.08% of the dataset, respectively. The Apriori algorithm was applied to yearly subsets of each cluster to uncover relevant association patterns. Our findings highlight key characteristics and temporal dynamics of violence, supporting the development of targeted interventions and support systems. © 2024 IEEE.

关键词： Self organizing maps

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Sexism Identification in Tweets using BERT and XLM - Roberta 25

Sexism Identification in Tweets using BERT and XLM - Roberta

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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Usmani, Maha Siddiqui, Rania Rizwan, Samin Khan, Faryal Alvi, Faisal Samad, Abdul Computer Science Program Dhanani School of Science and Engineering Habib University Karachi Pakistan

The rapid growth of social media platforms has led to an increase in offensive content, often targeting specific demographic groups. This paper focuses on identifying and categorizing sexism in tweets collected from various social media platforms. We address three tasks from the EXIST 2024 lab, involving the classification of tweets in English and Spanish. These tasks include binary classification for sexism identification, source intention categorization of sexist tweets, and multi-label classification for different facets of sexism. Our approach employs BERT multilingual and XLM-RoBERTa models, along with an ensemble technique to enhance prediction accuracy. We evaluate the models using both hard labels, determined by majority vote, and soft labels, based on class probabilities. © 2022 Copyright for this paper by its authors.

关键词： Tweets

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Enhancing Language Learning with Real-Time Sign Language Recognition and Feedback

Enhancing Language Learning with Real-Time Sign Language Rec...

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2024 IEEE MIT Undergraduate Research Technology Conference, URTC 2024

作者： Daniel, Clapp A. Liam, Nasr M. Habchi, Yasmina Basnet, Saurav Wentworth Institute of Technology Program of Electrical and Computer Engineering BostonMA United States

ISBN: (纸本)9798331531003

Despite the significance of Sign Language education, access to resources with immediate feedback remains a challenge. This study aims to assess the effectiveness of an online learning tool offering real-time video feedback, accessible via basic laptops. Leveraging the capabilities of Google's Media Pipe software and the project's robust logic, the prototype aims to provide learners with immediate and accurate feedback, addressing the challenge of access to effective resources for American Sign Language (ASL) education. Focusing on the ASL alphabet, computer-vision based learning tools for static and dynamic signs will be analyzed to explore the tool's capabilities and limitations. © 2024 IEEE.

关键词： Contrastive Learning

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Impact Analysis of Time-of-Use pricing enabled Electric Vehicle charging to the uncoordinated charging on a Distribution Network

Impact Analysis of Time-of-Use pricing enabled Electric Vehi...

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2023 IEEE Power and Energy Society General Meeting, PESGM 2023

作者： Sohail, Muhammad Abeer Khan, Rashna Mukhtar, Syed Hammad Usman, Ahmad Program Habib University Electrical and Computer Engineering Karachi Pakistan

ISBN: (纸本)9781665464413

Increased adoption of Electric Vehicles (EVs) result in appearance of high energy demand clusters in a distribution network. This has adverse effects on the distribution network resulting in voltage drop, increased losses, overloading of distribution feeders, transformers, and critical components. This results in degradation of power quality and network stability. In this work, a modified IEEE 13 bus system has been used to model and simulate 11 kV distribution grid using the actual network parameters, network topology, and an identified cluster region, based on the information from a distribution company in Pakistan. A scheduling strategy for EV charging using the the time-of-use pricing (ToUP) mechanism is devised and compared to the uncoordinated EV charging approach. The performance evaluation of these strategies for various degrees of EV penetration has been conducted and new challenges are identified. © 2023 IEEE.

关键词： Electric vehicles

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An Ant Colony Algorithm Approach to the Vehicle Routing Problem and Variants

An Ant Colony Algorithm Approach to the Vehicle Routing Prob...

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2024 Systems and Information engineering Design Symposium, SIEDS 2024

作者： Tablada, Tulio Davis, Cleon Palumbo, Neil Johns Hopkins University Electrical and Computer Engineering Program Johns Hopkins University Applied and Computational Mathematics Program United States

ISBN: (纸本)9798350385144

In the basic vehicle routing problem (VRP), a vehicle must deliver goods from one centralized warehouse to multiple customers efficiently. Several VRP variants and constraints exist, including different product types, specific delivery times, multiple warehouses, vehicle fuel constraints, and pick-up from one location and delivery to another. This work proposes and demonstrates a flexible algorithm for solving the VRP via ant colony optimization (ACO) that can address many of the variants discussed above. ACO algorithms mimic the behavior of ants, learning optimal paths to a food source and back to the nest based on stigmergic behavior. This work compares a proposed, more flexible ACO algorithm to a traditional optimization algorithm that is implemented in the Google VRP solver. Readily available data were used to test and demonstrate results. Several VRP variants were implemented in both the (proposed) flexible ACO algorithm and the Google VRP solver. The flexible ACO algorithm performed better in terms of distance traveled versus the Google VRP solver for two variants and worse for three other cases. However, the Google VRP solver was not able to solve some of the VRP variant combinations considered here and failed when solving some backhaul datasets. Because the flexible ACO algorithm was able to better handle many case variations, it may be an attractive alternative optimization tool. © 2024 IEEE.

关键词： Ant colony optimization

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Rate Distortion Analysis of Wavefield Coding in Wireless Geophone Networks 8th

Rate Distortion Analysis of Wavefield Coding in Wireless G...

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8th EAI International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2024

作者： Khan, Hamood ur Rehman Khan, Farhan Sir Syed Center for Advanced Studies in Engineering Islamabad Pakistan Electrical and Computer Engineering Program Habib University Karachi Pakistan

ISBN: (纸本)9783031788055

Current and future trends in seismic acquisition point towards higher geophone densities (forecasted to be 1M nodes per survey). The geophones’ high operating precision and a sampling rate of a few milliseconds leads to a huge aggregate data rate in the geophone array. To handle this large data rate a hierarchy of multiplexed lines (including fiber optic cables) are used, resulting in substantial deployment costs. This work considers wireless geophone networks to mitigate these costs. Because of limited bandwidth of the wireless medium, compression of acquired data is needed. We assess lossy source coding (signal compression) performance using a rate-distortion tradeoff based on a physical model of the earth. The distortion criterion used is mean squared error. The earth’s physical model considered here consists of a randomly layered subsurface structure where the acoustic impedance of the earth varies as a homogeneous spatial random process. The rate distortion performance is assessed in terms of the parameters of this physical model e.g., the speed of sound underground and correlation length of acoustic impedance process. In comparison with previous work, this paper derives a closed form expression for the autocorrelation function for the reflection process for the 3D subsurface volume. We also show from the resulting rate-distortion curves that the compression performance improves both as the coding bock length increases and as the correlation length of the medium properties increases. The rate-distortion surface as a function of normalized MSE and sound of speed underground is also computed and validated through extensive simulations. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Signal distortion

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