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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 supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.

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Publication Date
Sat Apr 09 2016
Journal Name
Photonic Sensors
Parametric Analysis of NO2 Gas Sensor Based on Carbon Nanotubes
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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Improving Reverse Engineering Processes by using Articulated Arm Coordinate Measuring Machine
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The invention relates to a coordinate measuring machine (CMM) for determining a measuring position of a probe. The AACMM isdepends on the robotkinematics (forward and reverse) in their measurementprinciple, i.e., using the AACMM links and joint angles todetermine the exact workspace or part coordinates. Hence, themeasurements are obtained using an AACMM will be extremely accurate and precise since that ismerely dependent on rigid structural parameters and the only source of measurement error is due to human operators. In this paper, a new AACMM design was proposed. The new AACMM design addresses common issues such as solving the complex kinematics, overcoming the workspace limitation, avoiding singularity, and eliminating the effects of

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Publication Date
Wed Aug 31 2022
Journal Name
Ieee Access
SHE Networks: Security, Health, and Emergency Networks Traffic Priority Management Based on ML and SDN
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Recently, the increasing demand to transfer data through the Internet has pushed the Internet infrastructure to the nal edge of the ability of these networks. This high demand causes a deciency of rapid response to emergencies and disasters to control or reduce the devastating effects of these disasters. As one of the main cornerstones to address the data trafc forwarding issue, the Internet networks need to impose the highest priority on the special networks: Security, Health, and Emergency (SHE) data trafc. These networks work in closed and private domains to serve a group of users for specic tasks. Our novel proposed network ow priority management based on ML and SDN fullls high control to give the required ow priority to SHE dat

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Publication Date
Thu Dec 18 2025
Journal Name
Journal Of Optical Communications
Enhancing of underwater wireless optical communication system based on single photon detector
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Abstract<p>This work investigates a simulation model of an underwater optical wireless communication (UOWC) system. Several water scenarios are considered: Harbor I (HA-I), Harbor II (HA-II), Coastal Ocean (CO), Clear Ocean (CL), and Pure Sea (PU). A laser diode (LD) with modulation schemes (NRZ-OOK) transmits data at various speeds of 2.5 Gbps, 5 Gbps, and 10 Gbps. To identify the optical signal, a single-photon detection (SPD), APD and PIN photodiodes are utilized. The analytical evaluation of the performance is executed using Q-factor, received power and bit error rate (BER). According to the results, the PU achieved an underwater distance of 35.5 m, 35 m, 34.5 m, for data tran</p> ... Show More
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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Fri Jan 15 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Comparison of the Effect Using Color Sensor and Pixy2 Camer on the Classification of Pepper Crop
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Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving Thermal Performance in the University Classrooms
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Universities are among spaces where it's important to ensure thermal comfort in indoor spaces, improving the occupants' well-being and productivity. The problem of the research was to study appropriate glazing systems for the spaces of the University of Baghdad because glazing systems are one of the most important elements of the indoor environments, and it has a major impact on the thermal performance of buildings. Glass is one of the most seasoned materials that are most utilized in the design. Since it is a diaphanous material, it allows sunlight to enter the building, increasing the space's temperature, cooling loads, and energy consumption in summer. The research followed the experimental method by studying and

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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
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Mon Jun 30 2025
Journal Name
Ingénierie Des Systèmes D Information
Comparative Analysis of Four Programming Languages for Machine Learning
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