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Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforward neural network (FNN) model. Data acquisition involved 60 subjects diagnosed with the studied cases. The implementation of FNN achieved an accuracy of 96.6% using 50% of the dataset as training data and 92.8% using only 30% training data. The comparison with related work shows good impact of using the differential values of pressure points as input for neural networks compared with raw data.

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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
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 May 01 2019
Journal Name
Sensors And Actuators B: Chemical
Fabrication and Characterizations of a Novel Etched-tapered Single Mode Optical Fiber Ammonia Sensors Integrating PANI/GNF Nanocomposite
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Publication Date
Thu Mar 30 2023
Journal Name
College Of Islamic Sciences
The effect of readings on the multiplicity of explanatory significance of a single Qur’anic word, a study through the interpretation of Ibn Attia al-Andalusi
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The study aimed to clarify the meanings learned and inferred from reading books، letters and messages in Surat Al-Qur’an. The inductive method، the analytical method، and the deductive method، One of the most prominent results of the research: that the multiplicity of Qur’anic readings produces a variety and expansion in the meaning that has a clear impact on the interpretation by clarifying the meaning of the verse.

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Publication Date
Fri Jun 12 2020
Journal Name
Test Engineering & Management
Studying the Optical Properties of CdSe Quantum Dots Prepared by Colloidal Method with Different pH Values
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The analytical potentiality of three different liquid stationary phases in analysing rathylchlorosilanes by gas - liquid ehromatography
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Organohalosilanes conslitute an important subject ١٦؛ the chemistry oforganosilicon compound؛. Being starting materials and intermediates in the synthesis of a large number of various compounds so it is very important to get such materials in its highest purity ,but the separation of rathylchlorosilanes was still a big^oblem, duet^the great similarity in their physical and chemical properties, making its analysing verydifficult, ^or this reason tteir must be a good method o^e^r^iondealing^ththe^compounds, gas- liquid chromatography proved that it was the best, specially when (m- nitrotoluene) was used as a stationary liquid phase, it gave a complete separation and a good statistical results

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
The optical properties of Poly methyl methacrylate (PMMA) polymers doped by Potassium Iodide with different thickness
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Films of pure Poly (methyl methacrylate) (PMMA) doped by potassium iodide (KI) salt with percentages (1%) at different thickness prepared by casting method at room temperature. In order to study the effect of increasing thickness on optical properties, transmission and absorption spectra have been record for five different thicknesses(80,140,210,250,320)µm. The study has been extended to include the changes in the band gap energies, refractive index, extinction coefficient and absorption coefficient with thickness.

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Publication Date
Wed Mar 25 2020
Journal Name
Journal Of Physical Education
تأثير تمرينات خاصة (FOOT WORK) في تطوير بعض القدرات الحركية والمهارات الاساسية بكرة القدم بأعمار (16-18)
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هدف البحث الى اعداد تمرينات خاصة (Foot Work) بكرة القدم بأعمار (16-18) سنة، والتعرف على تأثير هذه التمرينات الخاصة  في التوافق والرشاقة وبعض المهارات الاساسية بكرة القدم (المناولة، والدحرجة، والاخماد) بأعمار (16-18) سنة، وقام الباحثان باستخدام المنهج التجريبي ذو المجموعتين التجريبية والضابطة ذات الاختبار القبلي والبعدي، على عينة من لاعبي نادي الشرطة بأعمار (16-18) سنة، وعددهم (16)، وتم تقسيمهم الى مجموعتين كل مجموعة م

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Lightweight route adjustment strategy for mobile sink wireless sensor networks
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<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

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