E-learning has become one of the most extensively used electronic systems in the field of education. Despite its benefits, there are some capabilities and concerns that may have a negative impact on students’ performance. As a result, personalized e-learning systems are being developed, which adapt e-learning systems to the users’ personality, knowledge, behavior, interests, or preferences. This will improve the overall learning experience and performance of the students. This study created and tested an e-learning system, called “Cybele” to help students learn cybersecurity in an online mode of learning. “Cybele” is a personality-based virtual instructor for cybersecurity online learning that includes a chatbot built using Rasa Open Source. The paper used Myers-Briggs Type Indicator (MBTI) personality model for initial learner assessment to address various student learning styles for a better online learning experience. Testing was done for the system functionality and the traditional learning approach was compared to the personalized e-learning system. Results show that students who participated in the developed adaptive e-learning environment performed better than those who pursue the traditional learning method.

This study is about sign language translation into text; this technology is for those experiencing difficulty in communicating, i.e., those who have speech disorders, hearing impairment, and are deaf. Sign language translation into text is done through a process when one uses sign language that could be translated into text. Deep learning is a machine learning and artificial intelligence (AI) technique that mimics how humans acquire knowledge; the complexity and abstraction of deep learning algorithms are stacked in a hierarchy. The researchers utilized Convolutional Neural Networks (CNN), Connectionist Temporal Classification (CTC), and Deep Belief Network (DBN) to collect and gather the results of their system through different methods of translating sign language into text. Through the systematic literature review of various published papers related to sign language translation using deep learning techniques, this paper discusses and systematically analyzed various studies and come up with a proposed model in translating sign language into text.

Smartphones are being used on a daily basis by most people. It assists every persons' needs and wants in terms of communication, entertainment, news, and many more. As times passes by, it provided more ways to help people on their everyday life. The project aims to provide a way for sea vessel's watch-standing officers to monitor the marine traffic, and to provide information to avoid collision within Philippine maritime area of responsibility. The developed systems was also conceptualized to consider monitoring unidentified ship intruders within local territory that can possibly serve as a threat to national security. This research is to create an Automatic Identification System (AIS) localized monitoring application using mobile phone. An AIS monitoring system is used to simulate actual maritime data to check the location and movement of vessels or ships within the surrounding maritime area. After actual data simulation is done in the system, results show that accurate sea vessels information are being tracked using the AIS mobile app.

Integrating real-time systems in healthcare technology has revolutionized patient care and operational efficiency, yet it poses a significant challenge: safeguarding patient data from data breaches. This paper comprehensively reviews data breach prevention strategies within real-time systems integration in healthcare. Data breaches in healthcare have profound impacts, compromising patient confidentiality, damaging reputations, and incurring financial costs. Effective prevention strategies include robust cybersecurity measures like Intrusion Detection Systems (IDS), advanced identity and access management (IAM) protocols, and Security Information and Event Management (SIEM) platforms. Additionally, innovations such as blockchain, artificial intelligence (AI), and encryption play crucial roles in fortifying data security. However, success depends on technological measures, organizational readiness, and awareness. Cultivating a culture of cybersecurity among healthcare professionals through training and strict policies is essential. While progress has been made, the evolving nature of cyber threats requires continuous adaptation and vigilance. Ongoing refinement of prevention strategies is necessary to combat data breaches in healthcare effectively.