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Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breathing difficulty) used to diagnose the person being infected by COVID-19 virus or not. Secondly, this approach divides the infected peoples into four classes, based on their immune system risk level (very high degree, high degree, mild degree, and normal), and using two indices of age and current health status like diabetes, heart disorders, or hypertension. Where, these people are graded and expected to comply with their class regulations. There are six important COVID-19 virus infections of different classes that should receive immediate health care to save their lives. When the test is positive, the patient age is considered to choose one of the six classifications depending on the patient symptoms to provide him the suitable care as one of the four types of suggested treatment protocol of COVID-19 virus infection in COVID-19 DSS application. Finally, a report of all information about any classification case of COVID-19 infection is printed where this report includes the status of patient (infection level) and the prevention protocol. Later, the program sends the report to the control centre (medical expert) containing the information. In this paper, it was suggested the use of C4.5 Algorithm for decision tree.

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Publication Date
Fri Dec 01 2023
Journal Name
Ieee Antennas And Wireless Propagation Letters
Stabilized and Fast Method for Compressive-Sensing-Based Method of Moments
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Design and Implementation of a Multiplier free FPGA based OFDM Transmitter
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Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multi-carrier technique.The core operation in the OFDM systems is the FFT/IFFT unit that requires a large amount of hardware resources and processing delay. The developments in implementation techniques likes Field Programmable Gate Array (FPGA) technologies have made OFDM a feasible option. The goal of this paper is to design and implement an OFDM transmitter based on Altera FPGA using Quartus software. The proposed transmitter is carried out to simplify the Fourier transform calculation by using decoder instead of multipliers. After programming ALTERA DE2 FPGA kit with implemented project, several practical tests have been done starting from monitoring all the results of

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Publication Date
Thu Feb 01 2024
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Wireless channel-based ciphering key generation: effect of aging and treatment
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Key generation for data cryptography is vital in wireless communications security. This key must be generated in a random way so that can not be regenerated by a third party other than the intended receiver. The random nature of the wireless channel is utilized to generate the encryption key. However, the randomness of wireless channels deteriorated over time due to channel aging which casing security threats, particularly for spatially correlated channels. In this paper, the effect of channel aging on the ciphering key generations is addressed. A proposed method to randomize the encryption key each coherence time is developed which decreases the correlation between keys generated at consecutive coherence times. When compared to the

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Publication Date
Mon May 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparison hybrid techniques-based mixed transform using compression and quality metrics
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Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

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Publication Date
Tue May 01 2018
Journal Name
2018 2nd Ieee Advanced Information Management,communicates,electronic And Automation Control Conference (imcec)
Hybrid Regressor and Approximation-Based Adaptive Control of Piezoelectric Flexible Beams
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Publication Date
Sun Jul 01 2018
Journal Name
2018 2nd International Conference On Imaging, Signal Processing And Communication (icispc)
Analogy-based Common-Sense Knowledge for Opinion-Target Identification and Aggregation
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The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.

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Publication Date
Sun Aug 06 2023
Journal Name
Journal Of Economics And Administrative Sciences
Probit and Improved Probit Transform-Based Kernel Estimator for Copula Density
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Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis, Characterization and Antibacterial Activity Evaluation of New Indole-Based Derivatives
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A new series of N-acyl hydrazones (4a-g) derived from indole-3-propionic acid (IPA) were synthesized. These N-acyl hydrazones were prepared by the reaction of 3-(1H-indol-3-yl) propane hydrazide and aldehyde in the existence of glacial acetic acid as a catalyst. 1HNMR and FT-IR analyses were used to identify the synthesized compounds and they were in vitro evaluated as antibacterial agents against six different types of microorganisms by using well diffusion method. All the tested N-acyl hydrazones (4a-g) displayed moderate activity against the Gram-negative E.coli, comparable to that of Amoxicillin. Some of the tested N-acyl hydrazones also exhibited intermediate activity ag

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Publication Date
Sun Mar 30 2025
Journal Name
Mustansiriyah Journal Of Pure And Applied Sciences
Secure E-voting authentication system employing biometric technology, Crypto-Watermarking Approach and blockchain technology: A Review
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Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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