This presentation looks at how effective Duolingo, a popular language-learning app, is in helping university students learn a new language. The research is based on a semester-long study during a Second Language Acquisition course at Georgia State University, focusing on both the strengths and weaknesses of using mobile apps for learning languages. Duolingo’s game-like approach makes language learning fun and easy to access. However, the study found some clear limits to how much it helps with real language skills. The app focuses mostly on learning through repetition without giving much attention to grammar rules, which many students find helpful. It also provides little connection to cultural ideas, turning language practice into simple translation drills. These issues show that while Duolingo is a good starting point for learning, but it cannot fully replace more interactive or hands-on learning methods. The study also looks at how apps like Duolingo can be combined with other activities, such as talking with native speakers, joining cultural events, and taking formal language classes. These activities give students practical experiences as well as a better understanding of the language and its culture. This research contributes to the discussion about how technology can help with learning, especially when it comes to learning new languages. Looking closely at what works and what does not, this presentation will share practical tips for students and teachers to benefit from language apps like Duolingo. It will also suggest ways to make learning more engaging, and effective.

Moria Energy (my startup company) stands poised at the forefront of the renewable energy revolution, embodying the spirit of innovation and entrepreneurship in the geothermal power sector. With a vision to harness the Earth's heat, Moria Energy will leverage cutting-edge technologies to develop sustainable and efficient energy solutions. This presentation will explore how Moria Energy will drive significant change in the energy industry through business acumen and innovative geothermal applications. Our business model will integrate proprietary predictive analytics and optimization software to enhance geothermal production efficiency and precision. This technology will forecast maintenance needs and adjust outputs in real-time, ensuring optimal performance with minimal environmental impact. Furthermore, Moria Energy will develop advanced geothermal site mapping and assessment tools utilizing machine learning and data analytics. These tools will enable the identification of the most effective drilling locations, thereby reducing costs and ecological disturbances. A pivotal component of our strategy will be the Geothermal-as-a-Service (GaaS) model, which will reduce the barrier to entry for adopting geothermal energy by offering flexible financial arrangements. This approach will allow clients to benefit from sustainable energy solutions without significant upfront investments, thereby promoting wider adoption and fostering a greener future. Additionally, Moria Energy's commitment to driving change will extend beyond technology. We will establish a network of exclusive partnerships for carbon offsets, enhancing our clients' operational sustainability. This presentation will detail how Moria Energy will contribute to the energy sector and set new standards for environmental responsibility and innovation in business practices.

The report explores the implementation of a Central Bank Digital Currency (CBDC) alongside the traditional payment system, presenting a dual-framework approach that enhances financial innovation while safeguarding the stability of established systems. By integrating cutting-edge digital currency solutions with existing financial infrastructure, this strategy ensures inclusivity, security, and efficiency while addressing critical challenges like hacking risks, privacy concerns, and financial stability. Key considerations include collaboration with technology providers, payment system integrators, and cybersecurity firms to build a secure, scalable, and user-friendly ecosystem. The implementation process involves leveraging cloud technology, blockchain infrastructure, and intermediated design to ensure seamless adoption. Potential partners such as Amazon Web Services (AWS) for cloud infrastructure, IBM and Ripple for blockchain solutions, and Fiserv or PayPal for payment system integration are identified to facilitate development and deployment.

The intricacies of accurate decision-making in cricket officiating, which require detailed rule interpretation and responsiveness to dynamic match events, pose a significant challenge for automation. This research introduces an innovative framework that equips a Pepper robot to serve as an intelligent cricket umpire, capable of automating scoring and decision-making in real-time. Through an ontology-driven, multi-modal methodology, our system leverages Graph-based Retrieval-Augmented Generation (Graph RAG) to produce rule-compliant, context-aware decisions that align with professional officiating standards. The framework is structured around two core functionalities: first, a text-based retrieval system that uses a structured ontology of cricket rules encoded in graph formats (e.g., JSON-LD, RDF) to provide precise rule retrieval, informed by pretrained language models fine-tuned on historical decision data. This functionality supports accurate, scenario-specific text-based decisions. The second functionality expands to video analysis, employing models such as I3D and TimeSformer to extract critical features like ball trajectory from visual inputs. Integrating Graph RAG, the system dynamically cross-references these visual insights with encoded rules, improving accuracy in complex cases, including LBW adjudications. A multi-modal transformer further unifies text commentary and video data, producing comprehensive interpretations that adhere to cricket regulations. Extensive evaluations reveal high levels of accuracy, precision, and F1-score, with ablation studies highlighting Graph RAG’s essential role in decision-making for ambiguous scenarios. This project highlights the potential for intelligent automation in sports officiating and will be tested in practice nets at parks across North Georgia.