Alexander T . Lopez | Austin Peay State University (original) (raw)

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Conference Presentations by Alexander T . Lopez

Computer Science & Information Technology (CS & IT), 2024

Over the past few years, wildfires have become a worldwide environmental emergency, resulting in ... more Over the past few years, wildfires have become a worldwide environmental emergency, resulting in substantial harm to natural habitats and playing a part in the acceleration of climate change. Wildfire management methods involve prevention, response, and recovery efforts. Despite improvements in detection techniques, the rising occurrence of wildfires demands creative solutions for prompt identification and effective control. This research investigates proactive methods for detecting and handling wildfires in the United States, utilizing Artificial Intelligence (AI), Machine Learning (ML), and 5G technology. The specific objective of this research covers proactive detection and prevention of wildfires using advanced technology; Active monitoring and mapping with remote sensing and signaling leveraging on 5G technology; and Advanced response mechanisms to wildfire using drones and IOT devices. This study was based on secondary data collected from government databases and analyzed using descriptive statistics. In addition, past publications were reviewed through content analysis, and narrative synthesis was used to present the observations from various studies. The results showed that developing new technology presents an opportunity to detect and manage wildfires proactively. Utilizing advanced technology could save lives and prevent significant economic losses caused by wildfires. Various methods, such as AI-enabled remote sensing and 5G-based active monitoring, can enhance proactive wildfire detection and management. In addition, super intelligent drones and IOT devices can be used for safer responses to wildfires. This forms the core of the recommendation to the fire Management Agencies and the government.

Papers by Alexander T . Lopez

Computer Science & Information Technology (CS & IT), 2024

This paper provides a comprehensive examination of the evolution of credit cards in the United St... more This paper provides a comprehensive examination of the evolution of credit cards in the United States, tracing their historical development, causes, consequences, and impact on both individuals and the economy. It delves into the transformation of credit cards from specialized merchant cards to ubiquitous financial tools, driven by legal changes like the Marquette decision. Credit card debt has emerged as a significant financial challenge for many Americans due to economic factors, consumerism, high healthcare costs, and financial illiteracy. The consequences of this debt on individuals are extensive, affecting their financial well-being, credit scores, savings, and even their physical and mental health. On a larger scale, credit cards stimulate consumer spending, drive e-commerce growth, and generate revenue for financial institutions, but they can also contribute to economic instability if not managed responsibly. The paper emphasizes various strategies to prevent and manage credit card debt, including financial education, budgeting, responsible credit card uses, and professional counselling. Empirical studies support the relationship between credit card debt and factors such as financial literacy and consumer behavior. Regression analysis reveals that personal consumption and GDP positively impacts credit card debt indicating that responsible management is essential. The paper offers comprehensive recommendations for addressing credit card debt challenges and maximizing the benefits of credit card usage, encompassing financial education, policy reforms, and public awareness campaigns. These recommendations aim to transform credit cards into tools that empower individuals financially and contribute to economic stability, rather than sources of financial stress.

Computer Science & Information Technology (CS & IT), 2024

This research explores the consequences of AI integration in the labor market. As AI shapes vario... more This research explores the consequences of AI integration in the labor market. As AI shapes various industries, it brings a dual impact: displacing some jobs while creating others. The automation driven by AI could be a threat to routine tasks, potentially leading to the displacement of specific roles within the routine tasks. However, AI also creates new job opportunities, particularly in AI development and related fields. This study aims to analyze the multifaceted impact of AI on US jobs, considering displacement, creation, and skills. The research considered the following aspects: Evaluation of job displacement and creation, skill shifts, the quality of AI's impact on performance, and exploring the relationship between AI models and human tasks. We were able to show AI's influence on the tasks performed by humans. The negative relationship between AI influence and tasks performed by humans shows that AI indeed has a notable and statistically significant adverse impact on human-performed tasks. We discovered that as AI technology advances and becomes more prevalent, certain tasks and roles traditionally carried out by humans are being automated or replaced by machines. Also, we were able to show the relationship between the AI model and human-performed tasks. It was found that AI models exhibit a substantial and statistically significant positive relationship with tasks performed by humans. Our findings suggest a more optimistic outlook for the labor market, where rather than displacing jobs and workers, AI technologies have the potential to enhance their capabilities and create new opportunities.

Computer Science & Information Technology (CS & IT), 2024