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Deep Learning-Driven Decision Fusion: Spatio-Spectrogram Features for Inner Speech Recognition From Electroencephalogram Signals
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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Wed Aug 03 2022
Journal Name
Egyptian Journal Of Chemistry
A Novel Bio-electrochemical Cell with Rotating Cylinder Cathode for Cadmium Removal from Simulated Wastewater
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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Optium Conditions for the Production of Neutral Protease from local strain Aspergillus niger var cabonarius
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The optimum conditions for the production of neutral protease from local strain Aspergillus niger var carbonarius by solid – state fermentation system (Wheat bran) moisted with 0.2 M phosphate buffer (PH7.0) . the hydration ratio was 1:5 (V:W) . the concentration of inoculum was 1×106 spores per 10 gram of solid materials , initial P H 6.5 and 96 hours of incubation period at 30? C .the enzyme activity was 1300 unit / ml and specific activity was 1550 unit / mg protein .

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of The College Of Education For Women
The Necessity of College of Education for Woman from the Point of view of Students
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The Necessity of College of Education for Woman from the Point of view of Students

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Numerical Simulation of Unsaturated Soil Water from a Trickle Irrigation System for Sandy Loam Soils
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Trickle irrigation is a system for supplying filtered water and fertilizer directly into the soil and water and it is allowed to dissipate under low pressure in an exact predetermined pattern. An equation to estimate the wetted area of unsaturated soil with water uptake by roots is simulated numerically using the HYDRUS-2D/3D software. In this paper, two soil types, which were different in saturated hydraulic conductivity were used with two types of crops tomato and corn, different values of emitter discharge and initial volumetric soil moisture content were assumed. It was assumed that the water uptake by roots was presented as a continuous sink function and it was introduced into Richard's equation in the unsaturated z

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference On Scientific Research &amp; Innovation (icsri 2022)
Investigating the capability of MCM-41 nanoparticle for COD removal from Iraqi petroleum refinery wastewater
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