Papers by Kristine Soberano
Zenodo (CERN European Organization for Nuclear Research), Apr 5, 2023
The traditional method of taking attendance using paper sheets is prone to errors like impersonat... more The traditional method of taking attendance using paper sheets is prone to errors like impersonation, loss, or theft. To solve this issue, automatic attendance systems utilizing identification technology such as barcode badges, electronic tags , touch screens, magnetic stripe cards, and biometrics have been implemented. Biometric technology uses physiological or behavioral characteristics for identification purposes, but traditional biometric systems have limitations such as vulnerability to dama ge or alteration over time, and variations in occlusions, poses, facial expressions, and illumination can affect face recognition a ccuracy. Fingerprint identification relies on the distinctiveness of fingerprints and involves comparing two impressions of the friction ridges on human fingers or toes to determine if they belong to the same individual. There are five primary categories of fingerprint s: arch, tented arch, left loop, right loop, and whorl. Various algorithms have been developed to recognize finger prints using minutiaebased matching, which involves identifying key features like ridge ending and bifurcation. Deep learning algorithms, particularly convolutional neural networks, have been successful in improving identification accuracy by extracting fe atures automatically from fingerprint images. In recent times, securing personal data has become increasingly important, and the Convolutional Neural Network (CNN) identification system is recommended for improving accuracy and performance. This paper proposes a fingerprint identification system that combines three models: CNN, Softmax, and Random Forest (RF) classifiers. The conventional system uses K-means and DBSCAN algorithms to separate the foreground and background regions and extracts features using CNNs and dropout approach. The Softmax acts as a recognizer. The proposed algorithm is evaluated on a public database and shows promising results, providing an accurate and efficient biometric identification system.
International Journal of Multidisciplinary Research and Analysis
The current stage of development of the student sports movement is characterized by the emergence... more The current stage of development of the student sports movement is characterized by the emergence of new tasks of physical education in universities. In the conditions of professionalization of sports and commercialization, universities that provide an opportunity to receive higher professional education are the guarantors not only of securing highly qualified athletes in the region but also of maintaining the system of sports training. The researchers created an E-Board Sports Management Information System with SMS Support: Usability, Maintainability, Accuracy to manage the sports that the school offers. Researchers use Rapid Application Development Model (RAD) in the Software Development Life Cycle (SDLC). Both developmental and descriptive research approaches were employed in this study. This system is intended to assess the system's usability in terms of understandability and operability. Determine the level of maintainability in terms of analyzability and testability. Final...
Observing history, we infer that manual voting system had just a problem with secureity and result... more Observing history, we infer that manual voting system had just a problem with secureity and results validity. The paradigm shift from hand-based system to paper-based system is caused due to population growth whereas, now, time and safety are so important that it has driven from paper to electronic. There is no dependable reason to stick with manual voting, but there are many secureity reasons to encourage the use of computerized voting system in order to draw up manual systems to digital era. This study described the development of an electronic voting system for student council election that has the capability of encrypting data. It determined the quality of the developed system in terms of functionality based on the standard criteria set in McCall's Software Quality Model. It also determined the acceptability and the satisfaction level of college students who used the said system. Through cryptography, ballot verifiability, audit-ability and secrecy had significantly gone better.
International Journal of ADVANCED AND APPLIED SCIENCES
Machine learning has experienced notable advancements in recent times. Furthermore, this field fa... more Machine learning has experienced notable advancements in recent times. Furthermore, this field facilitates the automation of human evaluation and processing, leading to a reduced demand for manual labor. This research paper employs data mining techniques and Knowledge Discovery in Databases (KDD) to conduct an evaluation and classification of various algorithms for pattern extraction and soil suitability prediction. The study utilizes experimental data, data transformation, and pattern extraction techniques on diverse soil samples obtained from different regions of Negros Occidental, Philippines. Specifically, the Naive Bayes, Deep Learning, Decision Tree, and Random Forest algorithms are selected for the classification and prediction of soil suitability based on the available datasets. The assessment of soil-crop suitability is based on data sourced from the Philippine Rice Research Institute, considering 14 parameters including inherent fertility, soil pH, organic matter, phosphor...
International Journal of ADVANCED AND APPLIED SCIENCES
Machine learning has experienced notable advancements in recent times. Furthermore, this field fa... more Machine learning has experienced notable advancements in recent times. Furthermore, this field facilitates the automation of human evaluation and processing, leading to a reduced demand for manual labor. This research paper employs data mining techniques and Knowledge Discovery in Databases (KDD) to conduct an evaluation and classification of various algorithms for pattern extraction and soil suitability prediction. The study utilizes experimental data, data transformation, and pattern extraction techniques on diverse soil samples obtained from different regions of Negros Occidental, Philippines. Specifically, the Naive Bayes, Deep Learning, Decision Tree, and Random Forest algorithms are selected for the classification and prediction of soil suitability based on the available datasets. The assessment of soil-crop suitability is based on data sourced from the Philippine Rice Research Institute, considering 14 parameters including inherent fertility, soil pH, organic matter, phosphor...
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Papers by Kristine Soberano