Master of Science in Computer Sciencehttps://hdl.handle.net/20.500.12852/792024-03-29T11:29:34Z2024-03-29T11:29:34ZDocument management system using optical character recognition, clustering, watermarking and QR coding algorithmsCensoro, Keith C.https://hdl.handle.net/20.500.12852/15192022-03-09T08:24:10Z2021-01-01T00:00:00ZDocument management system using optical character recognition, clustering, watermarking and QR coding algorithms
Censoro, Keith C.
The Document Management System is a stand-alone desktop application that provides the employees of the Department of Budget and Management Regional Office VI a service that would secure the circulars and memorandum documents. The Document Management System will accept an official document sent by the Central office to be scanned into the system thru a scanning module that will use Optical Character Recognition (OCR). The captured image of the scanned document is converted to text and clustered into supervised keywords to facilitate searching using the Term Frequency-Inverse Document Frequency (TF-IDF) Algorithm. The scanned document will then undergo authentication by imprinting a watermark image and a QR Code using the watermarking algorithm using Text Brush Embedding and a QR Code Model 2 matrix code. The Evolutionary Prototyping model was used throughout the system development process. It has phases where system evaluation is made directly by the evaluators and the system is refined based on feedbacks which fastened the system process.
Employees of the Department of Budget and Management Regional Office VI evaluated the system and based on feedback, the scanned documents that underwent the authentication process was very secured as the watermark and QR code is imprinted on the document accurately.
The features of the system was able to generate a scanned document with watermark and QR Code imprint and was scanned via the verifier that accepted the document as an authenticated and secured copy generated by the system.
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2021-01-01T00:00:00ZTryk: A mobile transportation application using Bellman Ford algorithmFuentes, Anntoniete A.https://hdl.handle.net/20.500.12852/13442021-09-01T06:00:14Z2020-01-01T00:00:00ZTryk: A mobile transportation application using Bellman Ford algorithm
Fuentes, Anntoniete A.
Tryk is a mobile transportation application for a transport service provider that facilitates communication between the commuters and tricycle drivers regarding transportation services with the localities. Tryk is linked to the global positioning system (GPS), a navigations satellite system that provides location, velocity and time synchronization. The main features of the system conveniently allows to connect the commuters and drivers for transportation services, uses the Bellman Ford Algorithm to determine the shortest path from pick-up point to travel destination based on LTFRB transport fare and travel distance, provides the users with an interface for selecting point of origin, destination and ride type and administering particularly on ensuring the validity and reliability of transport services by the registered tricycle drivers. The Rapid Application Development model was used as modification of the modules throughout the process of development caters to the needs of the software without affecting the end product. It has the facility to frequently receive feedback from the users directly interfacing with the application during the development process.
Experts and users feedback showed that the application was able to conveniently connect commuters and drivers for transportation services in determining the shortest path.
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2020-01-01T00:00:00ZFrame-based expert decision support system for medical diagnosisPalomar, Cherry A.https://hdl.handle.net/20.500.12852/13402021-09-01T02:00:12Z2021-01-01T00:00:00ZFrame-based expert decision support system for medical diagnosis
Palomar, Cherry A.
The Frame-Based Expert Decision Support System for Medical Diagnosis is a web based application designed for the use of a physician in providing a diagnosis to patients who undergoes medical consultation. It is a Decision Support System using the frame based expert system algorithm that assesses the possible diseases that a patient may have basing on the symptoms and patient information provided into the system.
The system includes the recording of information, storing of health records, diagnosing of patients, issuance of electronic prescriptions and generating of statistical reports.
The methodology used in the system is the extreme programming as the development process is continuous as the phases allows the system to be defined and modified as errors are encountered during the testing phase. The system is then released upon completion of the developed study and all modules tested has passed.
Unit testing was used in testing the system developed as this allowed the each form of the modules to be tested thoroughly to accomplish the objective set.
As a result, the web based application was able to contribute in the diagnosis of the physician. With the knowledge base updated with the diseases and its relevant information, Physicians and patients provided a feedback that showed that the application was able to provide an accurate diagnosis based on the patient information that was provided to be able to assist the physician to arrive to a final diagnosis.
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2021-01-01T00:00:00ZUsing item-based collaborative filtering recommendation algorithm for Graduate School LibraryOjacastro, Rose Leah Joy A.https://hdl.handle.net/20.500.12852/12292021-07-26T03:00:14Z2017-01-01T00:00:00ZUsing item-based collaborative filtering recommendation algorithm for Graduate School Library
Ojacastro, Rose Leah Joy A.
The Henry Luce Library (HLL) is a library system located in the campus of the Central Philippine University (CPU) in Jaro, Iloilo City, Philippines. The library is vital to support and strengthen the educational quality. Over time, a library has been the source of information through books, journals, magazine and other relevant materials that supports any type of learning processes. Nowadays, technology can help the community sift through all the available information that can be valuable and useful.
The Using Item-Based Collaborative Filtering Recommendation Algorithm for Graduate School Library System is designed for CPU Graduate School Library to enhance the current library operations. The system used an Item-based Collaborative Filtering Recommendation Algorithm to improve library material usage by recommending title to other patron’s that has similar taste.
The algorithm used rating scale and recommendations for library patrons are computed through Pearson’s correlation. The system supports the following features: housekeeping operations such as cataloging, inventory, and circulation services.
After thorough investigation of the problem cited in chapter one solution where created and implemented through Evolutionary prototype methodology. It has been proven that the system answers the problem and improves the process of the Graduate School Library.
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2017-01-01T00:00:00Z