Background: Agile Methods have been around for nearly 25 years, yet there is still ongoing debate about their effectiveness in improving software development. Project management remains one of the most critical aspect...
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Industries encounter challenges in managing wastewater treatment systems, particularly in controlling aeration, which is vital for maintaining optimal oxygen levels for effective treatment. Frequent malfunctions in ae...
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ISBN:
(数字)9798331533816
ISBN:
(纸本)9798331533823
Industries encounter challenges in managing wastewater treatment systems, particularly in controlling aeration, which is vital for maintaining optimal oxygen levels for effective treatment. Frequent malfunctions in aerator control can lead to system damage and operational inefficiencies, impacting environmental compliance and increasing costs. To address these issues, this study examines the potential of an IoT-based monitoring system for aerators. The paper discusses specific IoT applications for aerator monitoring and explores enhancements in monitoring efficiency. The primary objective is to develop a system that maintains optimal oxygen levels by monitoring and controlling aerator operations. The system includes automatic notifications for oxygen level adjustments via the LINE application and manages data through Microsoft SQL Server for centralized storage. The methodology utilizes digital innovation and transformation techniques, integrating IoT technology through sensors, control boards, and Supervisory Control and Data Acquisition (SCADA) software, significantly enhancing monitoring and control efficiency. Automatic notifications facilitate timely issue resolution for operators, reducing their workload in wastewater management. Results indicate substantial improvements in system efficiency and operator workload reduction, highlighting the practical implications of this IoT solution for optimizing wastewater treatment processes in industrial settings.
Cybersecurity challenges are inherently complex, characterized by both advanced technical elements and complex aspects of human cognition. Although extensive research has explored how victims' human factors affect...
ISBN:
(纸本)9798331534202
Cybersecurity challenges are inherently complex, characterized by both advanced technical elements and complex aspects of human cognition. Although extensive research has explored how victims' human factors affect their susceptibility to cyberattacks, the influence of cybercriminals' personalities on the pattern of cyberattack campaigns and the resulting damage to organizations has not received equivalent attention. To bridge this research gap through computer simulation, we introduce a cyberattack campaign designer that enables modelers to construct cyberattack campaigns. This tool allows modelers to define how the process or pattern of the cyberattack campaign can change based on the cybercriminal's personality and simulates how these personality differences influence the magnitude of cyberattack damage on the target organization. In this paper, through computer simulation, we demonstrate how cautious and reckless personalities result in variations in the cyberattack pattern and, consequently, affect the magnitude of cyberattack damage, despite identical cyberattack objectives and techniques used at each step.
A promising solution for operations in the moderate voltage and high-power ranges, the Alternate Arm Multilevel Converter (AAMC) distinguishes itself with a distinctive topology as an AC-DC Voltage Source Converter (V...
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ISBN:
(数字)9798331533946
ISBN:
(纸本)9798331533953
A promising solution for operations in the moderate voltage and high-power ranges, the Alternate Arm Multilevel Converter (AAMC) distinguishes itself with a distinctive topology as an AC-DC Voltage Source Converter (VSC). However, traditional implementations require numerous sensors to maintain capacitor voltage balancing across series Full-Bridge Sub-Modules (FB-SBs). Introducing an innovative approach to enhance AAMC efficiency, this study proposes two sensor reduction methods for calculating capacitor voltages with estimation algorithms, demonstrating the current paths within each method. These streamlined approaches simplify the control structure and eliminate the requirement for individual current sensors in each phase and voltage sensors per FB-SBs. By continuously adjusting capacitor voltages based on estimated values used by data from executed last steps and switching signals, the provided methods achieve precise voltage balance with minimal estimation error. The methods’ effectiveness is validated through extensive simulations achieved by MATLAB Simulink software across various operational conditions. The results demonstrate notable reductions in measurement component requirements while maintaining robust performance in AAMC applications. This research highlights the potential of optimizing sensor utilization to improve the performance of voltage source converter technologies in the future.
Artificial intelligence (AI) relies on tasks like pattern recognition and object detection, but software-based implementations often struggle to meet real-time requirements. Field-Programmable Gate Arrays (FPGAs) have...
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ISBN:
(数字)9798350357509
ISBN:
(纸本)9798350357516
Artificial intelligence (AI) relies on tasks like pattern recognition and object detection, but software-based implementations often struggle to meet real-time requirements. Field-Programmable Gate Arrays (FPGAs) have become a promising solution for hardware acceleration, offering parallelism, energy efficiency, and adaptability, making them ideal for accelerating Artificial Neural Networks (ANNs) in edge and low-power environments. This paper implements a scalable and efficient FPGA-based ANN inference model, incorporating a fully connected layer with sigmoid activation for non-linear processing. The design is evaluated for FPGA resource utilization and benchmarked against CPU and GPU implementations for computational time. Results show that the FPGA implementation achieves a 34,000x speedup over CPU-based inference and a 2,000x improvement over GPUs on computational time while consuming significantly fewer resources on FPGA (except IO).
Multiple Sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. Nerves are covered by a layer called myelin, which is responsible for protecting and maintaining their functionality. In...
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Parameter estimation performance bounds serve as valuable tools in statistical signal processing, yet deriving them traditionally requires full knowledge of the data distribution. Recently, a framework has been propos...
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ISBN:
(数字)9798331513269
ISBN:
(纸本)9798331513276
Parameter estimation performance bounds serve as valuable tools in statistical signal processing, yet deriving them traditionally requires full knowledge of the data distribution. Recently, a framework has been proposed that combines a generative model with estimation performance bounds, thus eliminating the need for full knowledge of the data distribution by learning it from data. We refer to this approach as learning-to-bound (L2B). In this paper, we offer a comprehensive review of recent developments and emphasize their advantages. We then dive into open challenges and future directions within the L2B framework. Lastly, we explore a different perspective – the application of estimation performance bounds to deep learning.
Feedback control system analysis and design is a vital part of any engineering education. The most commonly applied software solutions related to it are Matlab together with Simulink. In recent years, especially due t...
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ISBN:
(数字)9798331542726
ISBN:
(纸本)9798331542733
Feedback control system analysis and design is a vital part of any engineering education. The most commonly applied software solutions related to it are Matlab together with Simulink. In recent years, especially due to an ever-increasing importance of artificial intelligence in all aspects of our life, Python seems to be the programming language of choice in many universities. For this reason there seems to be pressure on Control engineering society to also adopt Python in both educational and industrial environment. Consequently, a decision was made to present current state of the art in Python libraries that try to offer Matlab/Simulik capabilities for Python users. In this paper, a critical assessment will be made together with some examples being presented.
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