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Selecting the optimal movement subset with different pattern recognition based EMG control algorithms
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Publication Date
Sun Aug 25 2019
Journal Name
Civil Engineering Journal
Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
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Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Sat Feb 07 2026
Journal Name
Algorithms
An In-Depth Review of Speech Enhancement Algorithms: Classifications, Underlying Principles, Challenges, and Emerging Trends
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Speech enhancement aims to improve speech quality and intelligibility in noisy environments and is important in applications such as hearing aids, mobile communications and automatic speech recognition (ASR). This paper shows a structured review of speech enhancement techniques, classified depending on the channel configuration and signal processing framework. Both traditional and modern approaches are discussed, including classical signal processing methods, machine learning techniques, and recent deep learning-based models. Furthermore, common noise types, widely used speech datasets, and standard evaluation metrics for evaluating speech quality and intelligibility are reviewed. Key challenges such as non-stationary noise, data li

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Fri Jun 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Occurrence and pattern of antibiotic resistance among dental plaque bacteria from gingivitis patients and their clinical correlation
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Background: A diverse group of bacteria live in biofilms in the oral cavity. On dental surfaces biofilms form plaque that is potentially involved in caries and periodontal diseases. Periodic studying of plaque microflora and their antimicrobial sensitivity patterns strongly affects the clinical practice in plaque-induced oral diseases. Materials and methods: Dental plaque samples were collected from 22 patients having ages ranged between 33 and 49 years with gingivitis that met the study criteria. Plaque, gingival and gingival bleeding indices (PI, GI, GBI) were measured for each patient. Laboratory procedures included microbiological examination of plaque samples followed by antibiotic sensitivity testing using disc diffusion method were

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Gingival Pigmentation Pattern in Correlation to Skin Color in a Group of Kurdish People in Sulaimani City
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Background: Melanin pigmentation of the gingiva appears in all ethnicities. Excessive pigmentation is an esthetic concern that has increased awareness about depigmentation procedures. This epidemiological study aims to find the correlation between skin color and gingival pigmentation in Sulaimani Governorate, Kurdistan/Iraq.

Subjects and Methods: A total of 820 apparently healthy and non-smokers, including 338 males and 482 females with healthy gingiva, aged between (18-40 years old) were enrolled in this study. Clinical examination on the participants’ gingivae was performed to assess color, and the distribution of pigmentations. Afterward the of participants skin color were

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