Humber College

Phishing remains a persistent cybersecurity threat, often bypassing traditional detection methods due to evolving attack techniques. This study presents a Reinforcement Learning (RL)-based phishing detection framework, leveraging a Deep Q-Network (DQN) to enhance detection accuracy, reduce false positives, and improve classification performance. The model was trained and evaluated using a real-world dataset comprising 5000 emails (2500 phishing and 2500 benign) and externally validated against a synthetic phishing dataset of 1000 samples simulating unseen attacks. It achieved a 95% accuracy, 96% precision, 94% recall, and a 2% false positive rate on the real-world dataset and a 93% accuracy, 94% precision, and a 4% false positive rate on the synthetic dataset. Area Under the Curve (AUC) analysis yielded a score of 0.92, confirming excellent classification separability and alignment with the model’s high accuracy and low false positive rate. This work contributes to scalable, real-world phishing defense by addressing the limitations of static detection systems and improving detection reliability.

The Predictive Strategic-Fit Model (PSFM) represents a transformative approach to forging successful industry-academia collaborations. It offers higher education institutions, like Humber Polytechnic, a systematic, data-driven framework to assess potential partnerships by aligning institutional goals with industry capabilities. The model operates through a dual-sided analysis: the Demand Side, which focuses on value creation, revenue diversification, and systems leadership, and the Supply Side, which evaluates a partner’s attributes, such as financial health, relevance, and existing relationships. By combining Subjective Evaluative Judgments (SEJs) and objective data, the PSFM ensures a balanced, evidence-based approach to decision-making. The model's integration into a web application enhances accessibility and scalability, providing users with actionable insights through an intuitive interface. This digital platform is designed to evolve, incorporating future advancements in machine learning and data analysis to further optimize partnership evaluations. While the PSFM offers new opportunities for strategic alignment, it also supports long-term, multi-faceted collaborations by addressing the untapped potential within the vast amount of underutilized data available to institutions. The PSFM complements traditional methods of relationship-building, providing a structured way to prioritize and assess partnerships.

Retrieving semantically relevant documents in niche domains poses significant challenges for traditional TF-IDF-based systems, often resulting in low similarity scores and suboptimal retrieval performance. This paper addresses these challenges by introducing an iterative and semi-automated query refinement methodology tailored to Humber College's career services webpages. Initially, generic queries related to interview preparation yield low top-document similarities (approximately 0.2--0.3). To enhance retrieval effectiveness, we implement a two-fold approach: first, domain-aware query refinement by incorporating specialized terms such as resources-online-learning, student-online-services, and career-advising; second, the integration of structured educational descriptors like "online resume and interview improvement tools." Additionally, we automate the extraction of domain-specific keywords from top-ranked documents to suggest relevant terms for query expansion. Through experiments conducted on five baseline queries, our semi-automated iterative refinement process elevates the average top similarity score from approximately 0.18 to 0.42, marking a substantial improvement in retrieval performance. The implementation details, including reproducible code and experimental setups, are made available in our GitHub repositories \url{https://github.com/Elipei88/HumberChatbotBackend} and \url{https://github.com/Nisarg851/HumberChatbot}. We also discuss the limitations of our approach and propose future directions, including the integration of advanced neural retrieval models.

As a group of 10 applied researchers, faculty, and essential support staff at Humber Polytechnic, we share our enlightening experiences, working together in a collaborative setting to acquire knowledge on applied research practices. Our work is a testament to the power of collaboration, as we have used a collaborative and engaging autoethnographic model to disseminate our experiences of seven weeks. Although our reflections are independently composed pieces of work, they are observations of the collective work we completed during our participation in the Applied Research Program designed and hosted by Humber Polytechnic in Toronto, Canada.

<p>Background: The coronavirus disease-2019 (COVID-19) pandemic has implications for students who are also nurses. Purpose and Methods: This qualitative descriptive study used a practice development approach to explore the intersection between academic and professional work experiences for undergraduate Post-Diploma Registered Practical Nurses bridging to Registered Nurse Bachelor of Science in Nursing students and Master of Nursing graduate nursing students during the first wave of the COVID-19 pandemic. The study incorporated critical aesthetic reflections that focused on the personal and aesthetic ways of knowing, as a data collection approach and knowledge dissemination strategy. Results: Analysis of the narrative component of participants’ reflections revealed the following themes: sensing a “call to duty,” experiencing a myriad of emotions, shifting societal and individual perceptions of nursing, and learning in an uncertain environment. Conclusions: The results of the study can inform educational strategies and academic policies to support this unique nursing population, who are frontline practitioners as well as student learners.</p> <p><br></p>

Academic integrity serves as a critical foundation for learning in post-secondary institutions. However, educational organizations continuously face challenges that threaten efforts to uphold and promote academic integrity. While global collaborations focused on policies, procedures, activities, and research dedicated to academic integrity are valuable, it is equally important to recognize the unique contexts of groups of educational organizations, which are influenced by things like organizational culture, missions, geography, priorities, and specialties, to name a few. Consortiums that meet the specific needs of groups of organizations play a crucial role in this endeavour. This article will highlight one such consortium that is working to establish a Canadian presence in academic integrity and is affiliated with the International Center for Academic Integrity.

In recent years, fluorescent imaging has emerged as an active area of interest in medical imaging. Fluorescent imaging plays a critical role in molecular imaging. Evidence suggests its use in providing a detailed structural outlook and genetic and cellular operatives of the body procedures on a molecular plane. Imaging agents are identified to be related to risks such as not biologically disintegration and great poisonousness. Researchers have shown a keen attentiveness to the growth of targeted multifunctional agents in oncology and near-infrared (NIR) fluorescence imaging. This study assessed fluorescent imaging and bio-cellular acceptance of the gold (NIR) conjugated cockle shell-derived calcium carbonate nanoparticles Au-CsCaCO3NPs. The synthesized Au-CsCaCO3NPs were characterized by Transmission electron microscopy (TEM) for size and morphology, Zeta potential, and UV-Vis spectrophotometer. Biocompatibility of Au-CsCaCO3NPs in cultured human breast carcinoma cells MCF-7 and mouse embryonic fibroblast cells NIH3T3 was evaluated using bioassays like Lactate Dehydrogenase LDH and Reactive Oxygen Species ROS for toxic examination. Cellular morphology and uptake were studied by fluorescence and confocal microscopy. The outcomes proved that MCF-7 treated Au-CsCaCO3NP cells observed more cell deaths than NIH3T3 treated Au-CsCaCO3NP cells. Additionally, the cells were capable of assuming nanoparticles within their cellular compartments. In conclusion, gold-near infrared dye conjugated cockle shell calcium carbonate nanoparticles Au-CsCaCO3NPs were easily synthesized, biocompatible, and environmentally friendly. It is safe to state that the Au-CsCaCO3NPs could be used for imaging and could present opportunities for progressing cancer imaging.