PROJECTS

Building on Ontology of Historical Newspapers based on Methontology and Natural Language Processing Techniques

In the past years, there has been increasing concern on ontology for its ability to explain data semantics in the usual manner independent of the data source characteristics, providing a schema that allows interchanging data between heterogeneous information systems and users. The ontology development in some areas is not expected due to the large amount of information, particularly in history, leading its semantic impossible. Several works have been designed to enhance the technological aspects of ontology, such as the discovery and representation of concepts for historical newspaper.
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Trust Crawler: An Automated Verification Tool

There are difficulties in determining the trustworthiness of information, especially on social media. This study focuses on developing an approach that assists social media users to make judgments on the information they obtained from social media. For this reason, an approach has been developed to verify the trustworthiness of information in social media by using an automated tool named TrustCrawler. In this study, the automated approach has also been evaluated for its usability and functionality. TrustCrawler is a tool which capable to generate the degree of trustworthiness of the information.
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Skin Burn Depth Classification System

A correct first evaluation of burn injury is very critical, as the first treatment given to the patient based on the evaluation can lead to a better healing process In this project, an automated skin burn depth evaluation application is proposed to augment the diagnosis of the medical practitioners in helping them with their visual based examination accuracy.
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Monotone Fuzzy Systems

This project focus on constructing monotone fuzzy systems, from data and/or fuzzy if-then rules from human experts. This include to derive parametric conditions for a Fuzzy Inference System to be monotone, as well as, devising various approach to deal with data and/or fuzzy if-then rules which is inconsistent with the derived parametric conditions. The use of monotone fuzzy systems in various real-world applications, including, n-Ary aggregation, FMEA, risk analytic, and education assessment are illustrated. We have also proposed a number of new theorems, hypothesis and approaches pertaining to monotone fuzzy systems. This includes a new hypothesis stating that monotone data does not always produce monotone fuzzy rules. We also proposed MIFIS, monotone fuzzy rule relabeling, monotone fuzzy rule interpolations and etc.
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Data analytics dashboard of IoT-based water quality monitoring for sustainable smart farming

The widespread adoption of IoT-based water management sensors for smart farming sensors is not new. However, the use of data analytics dashboards for IoT-based plant water quality monitoring for smart agriculture is currently limited. The objective of this study is two-fold: (i) to formulate a new method to monitor water quality data from IoT sensors from smart farming; and (ii) to explore a new data analytics dashboard of IoT-based water quality monitoring for sustainable smart farming. The methodology for this research will involve two phases: (i) Exploring the Elements for a New Framework; and (ii) developing the data Analytics Prototype. Our project is expected to have an implication on Dasar Agromakanan Negara 2021 - 2030 (DAN 2.0). It also has the connection with SDG2: Zero Hunger and SDG6: Clean Water. Our proposal will contribute towards Strategic Thrust 1 (Restructuring Business and Industry Ecosystem), Wawasan Kemakmuran Bersama 2030.

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