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Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
SIMULATION MODEL FOR THE ASSESSMENT OF DIRECT AND INDIRECT GEOREFERENCING TECHNIQUES IN ANALYTICAL PHOTOGRAMMETRY
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This paper compares between the direct and indirect georeferencing techniques in Photogrammetry bases on a simulation model. A flight plan is designed which consists of three strips with nine overlapped images for each strip by a (Canon 500D) digital camera with a resolution of 15 Mega Pixels.

 

The triangulation computations are carried out by using (ERDAS LPS) software, and the direct measurements are taken directly on the simulated model to substitute using GPS/INS in real case. Two computational tests have been implemented to evaluate the positional accuracy for the whole model and the Root Mean Square Error (RMSE) relating to (30) check points show that th

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance
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Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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Publication Date
Mon Jun 15 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The role of knowledge and practice in orthodontists' attitudes towards bonding materials and techniques
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Background: The materials and techniques of orthodontic bonding systems remain a pivotal concern in orthodontic research. This issue is further complicated by orthodontists' preferences. To assess the effect of knowledge and practice on the attitudes of orthodontists towards bonding materials and techniques. Methods: A cross-sectional, questionnaire-based study was conducted using Google Forms. The questionnaire comprised 17 multiple-choice questions that targeted orthodontists' awareness, knowledge, and attitude towards bonding materials. It was distributed via email or social networking platforms to specialist Iraqi orthodontists. Results: A total of 176 participants responded with nearly equal representation between the sexes. Th

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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
Tue Sep 23 2025
Journal Name
Sensing And Imaging
A Review of Detection, Monitoring, and Analysis Techniques in Terahertz Sensing for Sustainable Agriculture
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Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Central European Agriculture
Power requirements for corn silage harvesters and application of precision agricultural techniques: a review
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The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
Future Teachers' Attitudes Towards Cloud Computing in the Kingdom of Saudi Arabia: Assistant Professor of Education Techniques, Department of Curriculum and Teaching Techniques Faculty of Education and Literature, Northern Border University Saudi Arabia
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The research aims to identify the future teachers' attitudes toward cloud computing in the Kingdom of Saudi Arabia from their point of view. The research adopted the descriptive approach, and a questionnaire was applied to a random sample of (370) male and female teachers in governmental and private general education schools in the Al-Jouf region, Saudi Arabia. The results of the research concluded that the reality of future teachers' attitudes towards cloud computing in the Kingdom of Saudi Arabia from their point of view is very high and that most areas of using computing are in the field of assessment, then teaching, and activities. The challenges of future teachers' attitudes toward cloud computing are recorded at a high level, parti

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
The relationship between the multiple intelligence and the numerical sense of mathematic subject among 4th secondary stage students
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The study aimed to investigate the relationship between the multiple intelligence and the numerical sense. The chosen population of the study was the 4th secondary stage students. The sample consisted of 400 female and male student. The researcher utilized two test; multiple intelligence test which include three categories of intelligence (logical-mathematical, spatial, and linguistics) consisted of (36) item, and the numerical sense test that consisted of (44) item. The two tests were constructed by the researcher himself. The psychometric properties of the test were also verified. The results showed that there was a correlation between the multiple intelligence and the numerical sense as well as the students’ means scores

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Strategic Risk's Variation as a function of Competitive Intelligence Investment - An applied research on some Iraqi's manufacturing Companies –
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ABSTRUCT

          The main aim of this research has been associated with the study of relationship between competitive intelligence and strategic risk, and to deduct their specific trends, which are interpreted as predicted by research hypotheses according to a review of literature including prior studies. The basic theme  of these hypotheses is related to the probability that declining levels of strategic risk and competitive positions of industrial companies is dependent upon the growing capacity to stay ahead of competitors in the market.

    A purposive non-random

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