Published Journal Articles
2024
Assessment of the effects of the number of projections and use of selected filters on a reconstructed artificial phantom
2024-03
journal of education and science (Issue : 4) (Volume : 3)
Appropriate selection of features may lead to the specificity of classification methods
and identify the most critical features from all sparse or dense impact data using a filter
based on the recognition selection method characterized. Filtration is used to reduce
sample complexity, improve the clarity of viscous samples, and reduce background
signals, resulting in increased signal-to-noise ratios in analytical tests. Depending on the
filtration method applied, particles are separated based on properties such as size. This
study assessed the impact of filter selection and the variation in the number of projections
on the final reconstructed artificial phantom images. Utilizing image reconstruction
techniques, it delves into the application of mathematical transforms, including Radon and
Fourier, to improve image quality and resolution, particularly in medical imaging
modalities such as CT and MRI. The research predominantly focuses on the application of
the Filtered Back Projection (FBP) algorithm to reconstruct images from changing
numbers of projections. The results underscore the main role of filter choice in removing
noise, with the Ramp filter presenting the most promising results. The investigation
concludes that reducing the number of projections results in a decline in image contrast
and an increase in image noise.
Leukemia detection using Artificial Neural Networks in Images of Human Blood Sample
2024-02
Al-Salam Journal for Medical Science (Issue : 4) (Volume : 3)
ABSTRACT: This article presents a preliminary report that uses minuscule images of blood tests to develop a
diagnosis of leukemia. Examining through images is crucial since illnesses can be recognized and examined at an
earlier stage using the images. The framework will be centered on leukemia and white blood cell illness. In fact,
even the hematologist has trouble organizing the leukemic cells, and manually arranging the platelets takes a long
time and is quite loose. In this way, early detection of leukemia recurrence allows the patient to receive the
appropriate treatment. In order to address this problem, the framework will make use of the capabilities in small
images and examine surface, geometry, shading, and quantifiable investigation modifications. These features'
variations will be utilized as the classifier input. has transformed the use of images K proposes that (NN) and
agglomeration. Examining a wide range of failure measures and increasing the intricacy of every system, the
findings are examined. Utilizing feedforward (NN), image division is accomplished with less noise and a very
sluggish conjunction rate. K-means agglomeration and (ANN) are intentionally used in this analysis to create a
collection of processes that will work together to produce a much better presentation in (IS). An analysis has been
conducted to determine the best rule for (IS).
Collaborative Learning in Computer Labs for Science Education: A Systematic Review
2024-01
ASCARYA (Issue : 1) (Volume : 4)
This study analyzes the use of Computer-Supported Collaborative
Learning (CSCL) in computer laboratory settings for secondary school
science education. The literature review evaluates the impact of
collaborative methods using computer simulations, virtual experiments,
and other digital technologies. The search yielded 33 relevant studies,
indicating that collaborative conditions outperformed individual
laboratory work in computer environments across various measures.
Collaborative work in pairs or small teams has been shown to lead to
better learning outcomes and expert-like reasoning patterns.
Additionally, students have reported finding collaborative computer
laboratory work more enjoyable, engaging, and preferable to
independent work. The integration of computer-supported
collaborative learning (CSCL) into science education presents
opportunities to enhance students' learning experiences through
interactive and collaborative approaches. This study highlights the
importance of student-centered learning design, effective group
dynamics, and reliable technology infrastructure for successful CSCL
implementation. Additional research is required to identify the best
group composition and task design, as well as the implications for
effectively implementing computer-supported collaborative learning in
science laboratories
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