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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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ESG Investing: A Statistically Valid Approach to Data-Driven Decision Making and the Impact of ESG Factors on Stock Returns and Risk

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IEEE Access 2024年 12卷 69434-69444页

This study examines the impact of environmental, social, and governance (ESG) factors on economic investment from a statistical perspective, aiming to develop a tested investment strategy that capitalizes on the connection between ESG factors and financial performance. ESG investing: A statistically valid approach to data-driven decision-making (ESGI-SVADDM) investment strategy is based on a rigorous, statistically valid approach that utilizes data, math, statistics, and data science libraries to drive investment decisions, eliminating the need for personal opinions and subjectivity. The process includes establishing an investment thesis, formulating testable hypotheses (HPS), retrieving and refining relevant data, calculating relevant measures, and testing and validating all hypotheses. The study uses S&P 500 stock data and ESG data from Sustainalytics to test the hypotheses. The empirical tests conducted revealed a negative correlation between ESG risk and expected returns, as well as a positive trend in the relationship between ESG risk and the overall risk of stocks. Moreover, the study found that higher ESG risk scores are associated with lower returns for investors, and that adopting a strategy of investing in stocks with low ESG risk and shorting stocks with high ESG risk yields superior returns compared to the market portfolio. © 2013 IEEE.

关键词： Investments

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Teaching reliable, secure and survivable Distributed Control System design

Teaching reliable, secure and survivable Distributed Control...

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2005 ASEE Annual Conference and Exposition: The Changing Landscape of engineering and Technology Education in a Global World

作者： Lessard, R. Beneat, J. Electrical and Computer Engineering Department Norwich University United States Norwich University Electrical Engineering Program United States

Distributed Control Systems (DCS) are deployed in power utilities as well as communication, transportation, and financial infrastructures. As demonstrated by power distribution grid failures, most recently in August of 2003, designing for reliability is an important need. In addition to inherent design weaknesses, critical infrastructures are potential targets of cyber-terrorism and protecting critical infrastructures against terrorist attacks is a national priority. DCS security and survivability need increased attention. One of the Norwich University electrical and computer engineering courses that address these issues is EE411 Microcomputer Based Applications. EE411 is designed to give computer and electrical engineering students a capstone DCS design experience applying concepts covered in earlier courses. They are introduced to "SCAD A ville", a municipal water system emulator modeled after a typical municipal water distribution system. The concepts of safety instrumentation and networking are introduced using Allen Bradley programmable Logic Controllers (PLCs). Students come to understand the advantages and disadvantages of ladder logic code for digital controller reliability. In designing Distributed Control Systems that make any connection to the outside world, the system must withstand attack from disgruntled employees, hackers or cyber terrorists. The system must function well even when the attacker breaks through the security barrier. In the EE411 course, the concepts of redundancy, robustness, and resilience are developed and reinforced in the laboratories.

关键词： engineering education

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Parallel processing in a cluster of microcomputers with application in contingency analysis

Parallel processing in a cluster of microcomputers with appl...

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2004 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America

作者： Balduino, Liliane Alves, Antônio César Baleerio Electrical and Computer Engineering in the Postgraduate Program School of Electrical and Computer Engineering Federal University of Goiás Brazil School of Electrical and Computer Engineering Federal University of Goiás Brazil Catholic University of Goiás

ISBN: (纸本)0780387759

This work is about the use of a microcomputer network as a parallel processing environment. In order to allow the communication, the synchronization and the distribution of the tasks among processes, the PVM (Parallel Virtual Machine) and MPI (Message Passing Interface) systems, were used. These computational systems allowed for parallel processing in the area of electric power systems, namely the contingency analysis. This application, usually found in Energy Management Systems, requires the use of a large quantity of resources in a short time. The aim is to analyze thousands of disturbance scenarios, in a preventive mode in real time. Two parallel programming paradigms classified as Master/Slave, in the synchronous and asynchronous modes, were implemented. Case studies with sequential and parallel implementations were carried out to validate the algorithms used to analyze elaborated contingencies, including the use of data from the Interconnected Brazilian Electric Power System, allowing the analysis of single and multiple disturbances. ©2004 IEEE.

关键词： Microcomputers

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An operating system for a Reconfigurable Active SSD processing node

An operating system for a Reconfigurable Active SSD processi...

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2012 19th International Conference on Telecommunications, ICT 2012

作者： Ali, Ali Jomaa, Mohamad Romanous, Bashar Sharafeddine, Mageda Saghir, Mazen A.R. Akkary, Haitham Artail, Hassan Awad, Mariette Hajj, Hazem Department of Electrical and Computer Engineering American University of Beirut Beirut Lebanon Electrical and Computer Engineering Program Texas A and M University at Qatar Doha Qatar

ISBN: (纸本)9781467307475

We have recently proposed a Distributed Reconfigurable Active SSD computation platform (RASSD) for processing data-intensive applications at the storage node itself, without having to move data over slow networks. In this paper, we present the design of an operating system (OS) for the RASSD node. RASSD OS is a multitasking real-time operating system that runs on the 32-bit MicroBlaze® soft processor core available for Xilinx® FPGA's. We discuss in this paper our OS design features which include initializing the node and configuring the different components of the RASSD node, monitoring the node's activities, and processing middleware requests. RASSD OS provides a set of services to the middleware through which it hides the low-level details of the node's hardware architecture. We describe the functions essential for the data-intensive processing within the RASSD node using examples that capture the common states of the node and various possible requests. © 2012 IEEE.

关键词： Distributed computer systems

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electrically Reconfigurable Intelligent Optoelectronics in 2-D van der Waals Materials

arXiv

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arXiv 2025年

作者： Wang, Yu Zhang, Dehui Song, Yihao Lee, Jea Jung Tian, Meng Biswas, Souvik Xia, Fengnian Guo, Qiushi Photonics Initiative Advanced Science Research Center City University of New York 85 St Nicholas Terrace New YorkNY10031 United States Physics Program Graduate Center City University of New York 365 5th Ave New YorkNY10016 United States Department of Electrical Engineering and Computer Sciences University of California Berkeley 566 Cory Hall BerkeleyCA94720 United States Department of Electrical Engineering Yale University 15 Prospect St New HavenCT06511 United States E. L. Ginzton Laboratory Stanford University 348 Via Pueblo Mall StanfordCA94305 United States

In optoelectronics, achieving electrical reconfigurability is crucial as it enables the encoding, decoding, manipulating, and processing of information carried by light. In recent years, two-dimensional van der Waals (2-D vdW) materials have emerged as promising platforms for realizing reconfigurable optoelectronic devices. Compared to materials with bulk crystalline lattice, 2-D vdW materials offer superior electrical reconfigurability due to high surface-to-volume ratio, quantum confinement, reduced dielectric screening effect, and strong dipole resonances. Additionally, their unique band structures and associated topology and quantum geometry provide novel tuning capabilities. This review article seeks to establish a connection between the fundamental physics underlying reconfigurable optoelectronics in 2-D materials and their burgeoning applications in intelligent optoelectronics. We first survey various electrically reconfigurable properties of 2-D vdW materials and the underlying tuning mechanisms. Then we highlight the emerging applications of such devices, including dynamic intensity, phase and polarization control, and intelligent sensing. Finally, we discuss the opportunities for future advancements in this field. Copyright © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

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Time-Component Complexity of Two Approaches to Multioperand Binary Addition

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IEEE Transactions on computers 1979年第12期C-28卷 918-926页

作者： Atkins, Daniel E. Ong, Shau-Chi Program in Computer Information and Control Engineering the Systems Engineering Laboratory of the Department of Electrical and Computer Engineering University of Michigan Ann Arbor MI 48109 United States

Component and time complexity measures in terms of number of gates and gate delays, respectively, are derived for two multioperand adder structures: a tree of carry-save adders and a tree of carry-lookahead adders. The parameters of the complexity measures are operand length, number of operands, and maximum fanin to the gates. The analysis involves a constructive derivation of the complexity of carry-lookahead networks including optimization by removal of redundant paths. An alternate measure of component complexity, number of packages with a given number of pinouts, rather than number of gates, is also presented. The general conclusion of the paper is that, under the assumptions made, for a large set of design parameters, the carry-save adder structure requires both less time and fewer components than the functionally equivalent carry-lookahead adder structure. Copyright © 1979 by The Institute of electrical and Electronics Engineers, Inc.

关键词： binary addition carry-lookahead adder carry-save adder Index Terms-Adder tree multioperand addition time-component complexity

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A framework for multi-cloud cooperation with hardware reconfiguration support

A framework for multi-cloud cooperation with hardware reconf...

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2013 IEEE 9th World Congress on Services, SERVICES 2013

作者： Mershad, Khaleel Kaitoua, Abdul Rahman Artail, Hassan Saghir, Mazen A.R. Hajj, Hazem Electrical and Computer Engineering Department American University of Beirut Beirut Lebanon Electrical and Computer Engineering Program Texas A and M University at Qatar Doha Qatar

ISBN: (纸本)9780768550244

Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In [1], we addressed some of these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. In this paper, we illustrate several enhancements to our work in [1] which focus on integrating hardware acceleration with the cloud services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We derive a mathematical model for evaluating the performance of the most important entity in our system under various conditions. © 2013 IEEE.

关键词： Cloud computing

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General order antenna selection in dual-hop amplify forward system with multi-antenna relay

General order antenna selection in dual-hop amplify forward ...

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2010 International Conference on Advanced Technologies for Communications, ATC 2010

作者： Gurung, Arun K. Ai-Qahtani, Fawaz S. Hussain, Zahir M. Alnuweiri, Hussein School of Electrical and Computer Engineering RMIT University Melbourne VIC Australia Electrical and Computer Engineering Program Texas A and M University at Qatar Doha Qatar

ISBN: (纸本)9781424488766

In this paper, we apply General Order Statistics (GOS) theorem for the antenna selection in dual-hop amplify-forward fixed-gain relay transmission. The antenna selection is employed at multi-antenna relay terminal for both receiving and transmission. The closed-form expressions of SNR (Signal-to-Noise-Ratio) statistics such as CDF (Cumulative Distribution Function), PDF (Probability Density Function), MGF (Moment Generating Function) and Generalized Moments were derived. The statistics were then used for performance analysis in terms of outage probability and error rate. The expressions are new and specialize to earlier results. The analysis is confirmed with computer simulation. The results facilitate to quantify the performance loss when lower order antenna is selected for the relay links. ©2010 IEEE.

关键词： Probability density function

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Robust Graph Autoencoder-Based Detection of False Data Injection Attacks Against Data Poisoning in Smart Grids

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1287-1301页

作者： Takiddin, Abdulrahman Ismail, Muhammad Atat, Rachad Davis, Katherine R. Serpedin, Erchin Department of Electrical and Computer Engineering Texas A and M University College StationTX77843 United States Department of Computer Science Tennessee Tech University CookevilleTN38505 United States Department of Electrical and Computer Engineering Program Texas A and M University Qatar Doha23874 Qatar

Machine learning-based detection of false data injection attacks (FDIAs) in smart grids relies on labeled measurement data for training and testing. The majority of existing detectors are developed assuming that the adopted datasets for training have correct labeling information. However, such an assumption is not always valid as training data might include measurement samples that are incorrectly labeled as benign, namely, adversarial data poisoning samples, which have not been detected before. Neglecting such an aspect makes detectors susceptible to data poisoning. Our investigations revealed that detection rates (DRs) of existing detectors significantly deteriorate by up to 9-29% when subject to data poisoning in generalized and topology-specific settings. Thus, we propose a generalized graph neural network-based anomaly detector that is robust against FDIAs and data poisoning. It requires only benign datasets for training and employs an autoencoder with Chebyshev graph convolutional recurrent layers with attention mechanism to capture the spatial and temporal correlations within measurement data. The proposed convolutional recurrent graph autoencoder model is trained and tested on various topologies (from 14, 39, and 118-bus systems). Due to such factors, it yields stable generalized detection performance that is degraded by only 1.6-3.7% in DR against high levels of data poisoning and unseen FDIAs in unobserved topologies. Impact Statement-Artificial Intelligence (AI) systems are used in smart grids to detect cyberattacks. They can automatically detect malicious actions carried out bymalicious entities that falsifymeasurement data within power grids. Themajority of such systems are data-driven and rely on labeled data for model training and testing. However, datasets are not always correctly labeled since malicious entities might be carrying out cyberattacks without being detected, which leads to training on mislabeled datasets. Such actions might degrade the d

关键词： Cybersecurity

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