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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
Thu May 18 2023
Journal Name
Journal Of Engineering
Estimation of Some Mechanical Soil Properties from Static and Dynamic Plate Load Tests
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When the depth of stressed soil is rather small, Plate Load Test (PLT) becomes the most efficient test to estimate the soil properties for design purposes. Among these properties, modulus of subgrade reaction is the most important one that usually employed in roads and concrete pavement design. Two methods are available to perform PLT: static and dynamic methods. Static PLT is usually adopted due to its simplicity and time saving to be performs in comparison with cyclic (dynamic) method. The two methods are described in ASTM standard.

In this paper the effect of the test method used in PLT in estimation of some mechanical soil properties was distinguished via a series of both test methods applied in a same site. The comparison of

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Publication Date
Wed Mar 05 2014
Journal Name
Journal Of Engineering
Estimation of Some Mechanical Soil Properties from Static and Dynamic Plate Load Tests ‫
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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Static and Dynamic Behavior of Circularized Reinforced Concrete Columns Strengthened with Hybrid CFRP
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In this study, three strengthening techniques, near-surface mounted NSM-CRFP, NSM-CFRP with externally bonding EB-CFRP, and hybrid CFRP with circularization were studied to increase the seismic performance of existing RC slender columns under lateral loads. Experimentally, 1:3 scale RC models were studied and subjected to both lateral static load and seismic excitation. In the dynamic test, a model was subjected to El Centro 1940 NS earthquake excitation by using a shaking table. According to the test results, the strengthening techniques showed a significant increase in load carrying capacity, of about 86.6%, and 46.6%, for circularization and NSM-CFRP respectively, of the reference unstrengthened columns. On the other hand, column

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Spectrophotometric and Spectrofluorimetric Determination of Terazosin in Tablets by Eosin Y
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Simple, sensitive and accurate two methods were described for the determination of terazosin. The spectrophotometric method (A) is based on measuring the spectral absorption of the ion-pair complex formed between terazosin with eosin Y in the acetate buffer medium pH 3 at 545 nm. Method (B) is based on the quantitative quenching effect of terazosin on the native fluorescence of Eosin Y at the pH 3. The quenching of the fluorescence of Eosin Y was measured at 556 nm after excitation at 345 nm. The two methods obeyed Beer’s law over the concentration ranges of 0.1-8 and 0.05-7 µg/mL for method A and B respectively. Both methods succeeded in the determination of terazosin in its tablets

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Publication Date
Fri Mar 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancement of Biogas production and organic reduction of sludge by different pre-treatment processes
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Anaerobic digestion (AD) is the most common process for dealing with primary and secondary wastewater sludge. In the present work, four pre-treatment methods (ultrasonic, chemical, thermal, and thermo-chemical) are investigated in Al-Rustumya Wastewater Treatment plant in order to find their effect on biogas production and volatile solid removal efficiency during anaerobic digestion.
Two frequencies of ultrasonic wave were used 30 KHz and 50 KHz during the pre-treatment. Sodium hydroxide was added in different amounts to give three pH values of 9, 10 and 11 in chemical pre-treating processes. The sludge was heated at 60oC and 80oC through thermal pre-treatment experiment. Also, the sludge was treated thermo-chemically at 80 oC and pH

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Publication Date
Wed Oct 15 2014
Journal Name
International Journal Of Advanced Research
A survey/ Development of Passive Optical Access Networks Technologies
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The bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad

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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Evaluation and Improvement of Manufacturing System Using Computer Software Arena
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The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowi

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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of the foundations of preparing the general budget of the StateThrough the 2008 federal budget analysis
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تعد الموازنة الأداة الأساسية لتنفيذ أولويات أية دولة، ويتوجب النظر إليها في ضوء المناخ الاجتماعي والسياسي والاقتصادي، لأنها تساعد في توجيه الاقتصاد لتحقيق النمو ورفع مستوى الرفاهية. اعتمدت وزارة المالية في أعداد الموازنة السنوية بعد 9/4/ 2003 أسلوباً مغايراً لما كان معتمداً في العقود الماضية، إذ كانت هناك موازنتين الأولى الموازنة الجارية، والثانية الموازنة الاستثمارية رغم وجود قانون يحتم إصدار موازنة

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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