International Journal of Information Technology, Research and Applications

Impact of Mathematical Models in IT System Design and Optimization

Krishnaveni Veeranan, Vaidhyanathan Pandian , Thamaraiselvi, Antonyraj Martin — Fri, 02 Feb 2024 00:00:00 +0000

This research investigates the crucial role of mathematical models in designing and optimizing modern IT systems. The paper explores how mathematical tools simplify complex systems, enabling efficient design and improved understanding. The impact of mathematical models extends beyond initial design. The research emphasizes the importance of maintaining these models throughout a system's life cycle to ensure ongoing optimization.

Fuzzy Logic Controllers and Coverage Path Planning (CPP) algorithms are highlighted as key examples of how mathematical models are utilized in IT system design, particularly for robotic guided vehicles. The research focuses on real-world applications of CPP and the role mathematical models play in finding optimal solutions.

This study aims to benefit professionals in robotics research, logistics, and process automation. It explores how mathematical models can contribute to overcoming challenges in modern industries, such as increased production efficiency and reduced costs.

Unveiling the Best-fit Model: A Comparative Analysis of Classification Methods in Predicting Student Success

Anette Guimmayen Daligcon, Dr. Jemima Priyadarshini, Lilibeth Rivera Decena — Thu, 07 Mar 2024 00:00:00 +0000

To reduce failure and personalize instruction, educators work to predict student achievement. For this objective, this study compared several categorization techniques. The study investigated techniques employing datasets from Portuguese schools, even though various circumstances make it difficult to gather full data and achieve high accuracy. Upon evaluating the various algorithms, including Random Forest and Decision Trees, the study determined that Random Forest was the most successful model, attaining a 94.55% accuracy rate. This demonstrates how machine learning—more especially, Random Forest—could forecast student achievement. The study opens the door for applying these techniques to early interventions and personalized learning. But more work needs to be done, such as creating publicly accessible educational datasets and investigating different strategies like regression algorithms to manage the nuances of grading systems more effectively.

Analysis Of Inhibiting Factors Implementation Of Electronic Medical Records In East Pamulang Community Health Center

Tue, 05 Mar 2024 00:00:00 +0000

Patient medical records in Indonesia are starting to transform into electronic-based medical records. Electronic Medical Records (EMR) are medical records created using an electronic system. It is an electronic repository of information about a patient's health status and health services throughout patient life. The impact if health services have not implemented EMR is that it could hamper patient health services. This research aims to identify factors inhibiting the implementation of EMR at the East Pamulang Community Health Center (Puskesmas). The research method used is descriptive with a qualitative approach. The research subject population was medical records officer and chief administrative officer, while the object population was the medical records, registration, clinics, laboratory, and pharmacy room. The results of the research identified several factors inhibiting the implementation of EMR, such as inadequate infrastructure, no officers with a background in medical records, and still using paper-based manual medical records. The conclusion of this research is the discovery of several factors inhibiting the implementation of EMR, human resource factors where it doesn’t yet have an officer with an educational background in medical records, the number of computers is still limited which supporting EMR in each service unit, and the electronic-based medical record applications are still not used comprehensively in the service units of the Puskesmas. Suggestions from the results of this research are that Puskesmas immediately recruits officers who have an educational background in Medical Records, increases the number of computer devices that support the implementation of EMR, and immediately implements electronic-based medical records.

Mimicking Photon Source Measurement with Quantum Digital Twin: A Framework for High-Quality Randomness

Rounak Biswas, Utpal Roy — Wed, 20 Mar 2024 00:00:00 +0000

Digital twins are virtual duplicates of tangible objects or systems. Within computer science, they play a pivotal role in simulating the software development life cycle, allowing for dynamic real-time testing and optimisation. Expanding beyond the confines of computing, sectors like manufacturing harness digital twins for predictive maintenance, ensuring operational efficiency, while healthcare employs them to replicate patient conditions, contributing to personalised treatment strategies. Through our efforts, we are crafting a digital twin of a renowned quantum mechanical attribute. This endeavour not only grants us insights into the inherent randomness intrinsic to quantum systems but also allows us to formulate a theoretical framework for a randomness generator using the model of this quantum digital twin. The outcomes, substantiated by results and plotted figures, substantiate our assertions, making a noteworthy impact on the advancement of authentic quantum random number generator sources. We are not just creating a novel avenue for generating randomness but pioneering a paradigm shift. Rooted in the digital twin model, our comprehensive framework affirms its efficiency when compared with the precision of the photon-based model.

An applicative substantiation of the Radon Transform appertain to Image Segmentation for the Prognosis of Metastatic Oncogenesis vis-a-vis Lung Cancer: a Boon in the Novel Emergences of Artificial Intelligence Manoeuvred Amelioration

Tamaghna Dutta, Soumen Santra, Dipankar Majumdar, Surajit Mandal — Sat, 30 Mar 2024 00:00:00 +0000

The prime approach of image segmentation is elementally to segregate an image into clusters of specific homogenous regions with respect to one or more similar characteristics and attributes eventually enabling the processing of the pertinent substantial sections of the image, disjointly, in lieu of the entire image – thereafter, enhancing edge detection. The Radon transform of an image being the integration of the Radon transforms of each individual pixel, the algorithm first sectionalizes pixels into four subpixels and projects each distinctly, as has been shown in the resultant figure. The radon transform is finding its widespread application in multiple fields of study, especially in medical research – thus - computes the projection of an image matrix along fixed axes. A dataset of annotated images is used to train the network, and each image is classified and labeled with the proper segmentation.

This paper corroborates the imperative and substratal role of the radon transformation and gives and aims at rendering a simple illustration of the same in CAT. This communication computes projections of an image matrix along specified directions. A projection of a two-dimensional function f (x, y) is a set of line integrals. The radon function computes the line integrals from multiple sources along parallel paths, or beams, in a certain direction.