MAMBAs (Multivariate Analysis Methods in Biomechanistic Activity Studies) is an integrated workstation-based graphics program designed for the investigation of quantitative structure activity relationships (QSAR). It combines many of the commonly used statistical techniques with an extensive database of substituent constants, a variety of molecular and substituent property calculations and detailed graphics-based table and graph editors. Graphical representations of standard substituent generation and optimization techniques are also included. These are all utilized within a state-of-the-art real-time graphics environment.
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http://dx.doi.org/10.1016/0263-7855(93)80067-2 | DOI Listing |
J Med Internet Res
January 2025
Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Background: The aging global population and the rising prevalence of chronic disease and multimorbidity have strained health care systems, driving the need for expanded health care resources. Transitioning to home-based care (HBC) may offer a sustainable solution, supported by technological innovations such as Internet of Medical Things (IoMT) platforms. However, the full potential of IoMT platforms to streamline health care delivery is often limited by interoperability challenges that hinder communication and pose risks to patient safety.
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January 2025
Wollega University, Nekemte, Ethiopia.
This research paper presents an advanced AI-driven hybrid power quality management system for electrical railways that addresses critical challenges in 25 kV AC traction networks through a novel integration of single-phase PV-UPQC with ANN-Lyapunov control architecture. The system effectively manages voltage unbalance exceeding 2%, high THD, voltage variations of ± 10%, and poor power factor through a dual-approach methodology combining ANN-based reference signal generation with Lyapunov optimization, enabling dynamic parameter tuning and real-time load adaptation. MATLAB/Simulink simulations validate the system's superior performance, demonstrating significant improvements, including voltage unbalance reduction from 1.
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January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
In this paper, a comprehensive energy management framework for microgrids that incorporates price-based demand response programs (DRPs) and leverages an advanced optimization method-Greedy Rat Swarm Optimizer (GRSO) is proposed. The primary objective is to minimize the generation cost and environmental impact of microgrid systems by effectively scheduling distributed energy resources (DERs), including renewable energy sources (RES) such as solar and wind, alongside fossil-fuel-based generators. Four distinct demand response models-exponential, hyperbolic, logarithmic, and critical peak pricing (CPP)-are developed, each reflecting a different price elasticity of demand.
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January 2025
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.
Power quality (PQ) disturbances, such as voltage sags, are significant issues that can lead to damage in electrical equipment and system downtime. Detecting and classifying these disturbances accurately is essential for maintaining reliable power systems. This paper introduces a novel approach to voltage sag analysis by employing wavelet packet analysis combined with energy-based feature extraction to enhance PQ monitoring.
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January 2025
Changchun Automobile Economic & Technological Development Zone Employment Service Bureau, Jilin City, China.
The permanent magnet synchronous motor control system is characterized by its nonlinear and strongly coupled complexity, presenting significant challenges for control performance optimization. To address these challenges, a Fuzzy adaptive fractional order [Formula: see text] control strategy based on torque observation compensation is proposed. The parameters of the fractional order [Formula: see text] controller are optimized real time using fuzzy logic reasoning, in order to enhance the speed of parameters tuning, a graphical design method of the fractional order [Formula: see text] controller parameters based on frequency domain performance indicators is proposed to obtain the initial values of the fuzzy adaptive fractional order [Formula: see text] controller parameters graphically and intuitively.
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