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bsj-3559
An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language
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The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey system based on structured query language and R programming language is designed to optimize methods to manage survey systems by applying large features offered via combining multi data science languages. The experiments verified enhancements of flexibility, technical tools, and data visualization features employed to process the collected data from different aspects; therefore, the proposed approach demonstrates a simple case study to enhance the evaluation requirements of the proposed technique. Finally, the estimated results of this research can be used to improve the methods of information management on different aspects such as survey systems and other data models that hold the relational and non-relational models using SABR. This method demonstrated improved accuracy of data collected, reduced data processing time and arranged data to the willing model.

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Numerical Solutions of Two-Dimensional Vorticity Transport Equation Using Crank-Nicolson Method
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This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

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Publication Date
Fri Mar 01 2024
Journal Name
The International And Political Journal
Constitutional Amendments in Oman and Their Impact on Internal and Foreign Policy
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The Sultanate of Oman is located in the far southwest of the Arabian Peninsula and enjoys a distinctive geographical location as it overlooks the Arabian Gulf and the Gulf of Oman. The Sultanate has good relations with various countries of the world and enjoys an important regional position. At the beginning of 2020, Sultan Qaboos bin Said died, and Haitham bin Tariq assumed power after him, according to the will of his cousin, the late Sultan. The new Sultan had held some important positions before 2020, including: Minister of Heritage and Culture since February 2002, Chairman of the Supreme Committee for the Future Vision (Oman 2040), Secretary-General of the Ministry of Foreign Affairs, Undersecretary of the Ministry of Foreign Affairs f

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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Publication Date
Mon Oct 31 2022
Journal Name
Biodiversitas Journal Of Biological Diversity
Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data
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Abstract. Hassan FM, Mahdi WM, Al-Haideri HH, Kamil DW. 2022. Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data. Biodiversitas 23: 5239-5246. The biodiversity and water quality of the Diyala River require screening water in terms of biological contamination, because it is the only water source in Diyala City and is used for many purposes. This study aimed to identify a new species record of Cynaophyceae and emphasize the importance of using molecular methods beside classic morphological approaches, particularly in the water-shrinkage-aqua system. Five different sites along Diyala River were selected for Cyanophyceae identification. Morphological examination and 16S rRNA sequen

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Publication Date
Thu Sep 29 2022
Journal Name
World Journal Of Clinical Infectious Diseases
Five-year retrospective hospital-based study on epidemiological data regarding human leishmaniasis in West Kordofan state, Sudan
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Fri May 30 2025
Journal Name
Iraqi Journal Of Science
A Novel Approach for Synthesizing the Pan-chromatic Band to (10 m) of Landsat 9 Based on Sentinel-2 Data to Improve Classification Performance
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This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
A Discourse Taxonomy of Language Cliched Units in English and Russian: Дискурсивная таксономия языковых клишированных единиц в английском и русском языках
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 The paper exposes a discourse taxonomy of language clichéd units in English and Russian, and presents some definitions of what is a cliché as being a semioticform of perceiving language and discourse. Also, it deals with language clichés as being units of structure reflecting a scheme of stereotypical situations of dialogue, whether among individuals of one culture, or in relation to cross-cultural communication. The paper proposes a taxonomy of units in language clichés in English and Russian by tackling clichés of daily use, such as professional, cultural, artistic, and scientific clichés.

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