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A Neuro-Fuzzy Technique for the Modeling of β-Glucosidase Activity from Agaricus bisporus
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This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANFIS technique were embedded in a new fuzzy inference system to simultaneously encompass the impact of temperature and pH level on the activity of β-glucosidase. The required base rules for the developed fuzzy inference system were created to describe the antecedent (pH and temperature) implication to the consequent (enzyme activity), using the singleton Sugeno fuzzy inference technique. The simulation results from the developed models achieved high accuracy. The neuro-fuzzy approach performed very well in predicting β-glucosidase activity through comparative analysis. The proposed approach may be used to predict enzyme kinetics for several nonlinear biosynthetic processes.

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Publication Date
Mon Oct 01 2018
Journal Name
Conference: First International Conference On Water Resources
Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network October 2018
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The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Improvement of the technique for the solution method of Gauss Seidel
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In this paper, a new approach was suggested to the method of Gauss Seidel through the controlling of equations installation before the beginning of the method in the traditional way. New structure of equations occur after the diagnosis of the variable that causes the fluctuation and the slow extract of the results, then eradicating this variable. This procedure leads to a higher accuracy and less number of steps than the old method. By using the this proposed method, there will be a possibility of solving many of divergent values equations which cannot be solved by the old style.

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Publication Date
Mon Jun 30 2025
Journal Name
Acta Logistica
A business continuity-based framework for risk management in smart supply chains: a fuzzy multi-criteria decision-making approach
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The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

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Publication Date
Wed Dec 13 2023
Journal Name
Iraqi Journal Of Architecture And Planning
Geospatial Techniques for Preparing the Requirements of 3D Modeling for Smart City Planning- Review paper
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Developing smart city planning requires integrating various techniques, including geospatial techniques, building information models (BIM), information and communication technology (ICT), and artificial intelligence, for instance, three-dimensional (3D) building models, in enabling smart city applications. This study aims to comprehensively analyze the role and significance of geospatial techniques in smart city planning and implementation. The literature review encompasses (74) studies from diverse databases, examining relevant solutions and prototypes related to smart city planning. The focus highlights the requirements and preparation of geospatial techniques to support the transition to a smart city. The paper explores various aspects,

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Publication Date
Thu Jun 01 2017
Journal Name
The Journal Of Immunology
Definition of the Nature and Hapten Threshold of the β-Lactam Antigen Required for T Cell Activation In Vitro and in Patients
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Abstract<p>Covalent modification of protein by drugs may disrupt self-tolerance, leading to lymphocyte activation. Until now, determination of the threshold required for this process has not been possible. Therefore, we performed quantitative mass spectrometric analyses to define the epitopes formed in tolerant and hypersensitive patients taking the β-lactam antibiotic piperacillin and the threshold required for T cell activation. A hydrolyzed piperacillin hapten was detected on four lysine residues of human serum albumin (HSA) isolated from tolerant patients. The level of modified Lys541 ranged from 2.6 to 4.8%. Analysis of plasma from hypersensitive patients revealed the same pattern and leve</p> ... Show More
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
A Fuzzy Logic Controller Based Vector Control of IPMSM Drives
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This paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Classification of Fetus Gender Based on Fuzzy C-Mean Using a Hybrid Filter
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Abstract<p>This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap</p> ... Show More
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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Visual Modeling Language for Agent Treasury Pharmaceutical
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The researches to discover useful ways to represent the agents and agent-based
systems are continuous. Unified Modeling Language (UML) is a visual modeling language
used for software and non software modeling systems. The aim of this paper is: using UML
class diagram to design treasury pharmaceuticals agent and explain its internal action. The
diagram explains the movement of the agent among other nodes to achieve user's requests
(external) after it takes them. The paper shows that it is easy to model the practical systems by
using agent UML when they are used in a complex environment.

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Modeling and Filtering for Tracking Maneuvering Targets
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     A new mathematical model describing the motion of manned maneuvering targets is presented. This model is simple to be implemented and closely represents the motion of maneuvering targets. The target maneuver or acceleration is correlated in time. Optimal Kalman filter is used as a tracking filter which results in effective tracker that prevents the loss of track or filter divergency that often occurs with conventional tracking filter when the target performs a moderate or heavy maneuver. Computer simulation studies show that the proposed tracker provides sufficient accuracy.

 

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