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Research Article
Data Analysis of Cancer Incidence and Mortality Disparities Among African Americans in Louisiana
Prasanthi Sreekumari*
,
Abhishek Amgain
Issue:
Volume 8, Issue 2, June 2025
Pages:
40-51
Received:
5 March 2025
Accepted:
21 March 2025
Published:
27 April 2025
DOI:
10.11648/j.ajcst.20250802.11
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Views:
Abstract: Cancer is a major cause of death in the United States. Different racial and ethnic groups have different cancer rates and survival chances. In Louisiana, African Americans have some of the highest cancer rates in the state, according to a recent report. Louisiana also ranks fifth in the country for cancer deaths, making the issue even more serious. Several factors contribute to these differences. Many African Americans in Louisiana have limited access to healthcare, struggle financially, and live in areas with environmental risks. Because of these challenges, they often cannot get cancer screenings and treatment early, leading to late diagnoses and worse health outcomes. Low income and unemployment make it even harder to get proper medical care. Some areas also have high pollution, which can increase cancer risk. Cancer rates vary between cities and rural areas in Louisiana. Rural areas have fewer hospitals and doctors, causing delays in diagnosis. Cities may have more hospitals, but more pollution, which can raise cancer risks. Gender also affects cancer rates. African American men are more likely to get prostate and thyroid cancer, while African American women are more likely to develop severe types of liver and breast cancer. These differences show the need for better prevention and treatment plans. In this research, we study the five most common cancers among African Americans in Louisiana over the past five years, focusing on gender and location. Using Python and tools like Pandas, Seaborn, Matplotlib and SAS, the research analyzes cancer patterns and causes. The goal is to find useful information to improve public health and make healthcare more accessible for African Americans in Louisiana.
Abstract: Cancer is a major cause of death in the United States. Different racial and ethnic groups have different cancer rates and survival chances. In Louisiana, African Americans have some of the highest cancer rates in the state, according to a recent report. Louisiana also ranks fifth in the country for cancer deaths, making the issue even more serious....
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Research Article
Multi-model Database Design and Query Processing in NewSQL DBMSs
Joachim Tankoano*
Issue:
Volume 8, Issue 2, June 2025
Pages:
52-71
Received:
4 April 2025
Accepted:
17 April 2025
Published:
9 May 2025
DOI:
10.11648/j.ajcst.20250802.12
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Views:
Abstract: NewSQL DBMSs are hybrid systems that combine the advantages of both SQL DBMSs and NoSQL DBMSs. This paper proposes a method for designing a database to be implemented on a NewSQL DBMS. The objectives of this method are identifying and defining heterogeneous collections of values that adhere to different data models, which are essential for an enterprise's operations, with the goal of storing and managing them within only one database. This method is based on a Relational Data Store and the Nested Relational Model. It allows the designer to use the Data Store as a guarantor of integrity and to optimize it for hybrid workloads (transactional and analytical), performance, scalability, and continuous data availability. As for the nested relational model, it is used by the designer to: (1) clarify their choices regarding storage models that can enable fast access to data about complex real-world entities; (2) specify access paths that can meet user needs. The main interest and the originality of this methodological approach are that this enables us to use the Nested Relational Model as a Pivot Model to: (1) automatically generate the global external schemas of the NoSQL virtual databases, allowing users to view and manipulate the Data Store as if it were a NoSQL database (object-relational, XML, JSON, or graph-oriented), and (2) unify the processing of cross-model SQL queries through an innovative and efficient approach. This method consistently integrates, through five levels of abstraction, the design process of the relational Data Store and that of the virtual databases. The research method used consisted of: (1) defining the objectives of this approach, (2) identifying the required levels of abstraction in light of the targeted objectives, (3) determining, for each level of abstraction, its specific objectives as well as the role to be played by the designer, a design support tool, and the DBMS, and (4) applying this approach to a typical example reflecting the most common needs, in order to facilitate the understanding of its contributions and relevance with respect to the intended objectives.
Abstract: NewSQL DBMSs are hybrid systems that combine the advantages of both SQL DBMSs and NoSQL DBMSs. This paper proposes a method for designing a database to be implemented on a NewSQL DBMS. The objectives of this method are identifying and defining heterogeneous collections of values that adhere to different data models, which are essential for an enter...
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Research Article
A Next-Generation Metaheuristic Inspired by Nomadic Behavior: The Raute Algorithm
Yam Krishna Poudel*,
Rajiv Kumar
Issue:
Volume 8, Issue 2, June 2025
Pages:
72-84
Received:
11 April 2025
Accepted:
21 April 2025
Published:
22 May 2025
DOI:
10.11648/j.ajcst.20250802.13
Downloads:
Views:
Abstract: The Raute community of Nepal is the one of the last remaining nomadic indigenous groups. Which exhibits a unique lifestyle centered on adaptation, mobility, and resource management. Their dynamic movement patterns, decision-making hierarchy, and sustainable utilization of resources provide inspiration for a novel computational approach. Which is called the Raute Metaheuristic Algorithm. This algorithm applies key aspects of the Raute people's survival strategies to address complex optimization problems. The Rautes continuously migrate to locate optimal resources while avoiding depletion and the Raute Algorithm dynamically balances exploration and exploitation. This is inspired by the Raute leadership structure which has its hierarchical decision-making model allows solutions to adapt based on the best-performing agents. Therefore, it preventing early convergence and ensuring an efficient search for global optima in high-dimensional spaces. Also, the algorithm integrates a resource-based movement probability function and which ensuring strategic migration away from low-quality solutions. To validate the effectiveness of the Raute Algorithm it is apply to the Rastrigin function. Which is a well-known multimodal benchmark problem in optimization. Comparative analysis with Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) shows that the Raute Algorithm achieves competitive accuracy. It improves the convergence speed, and superior robustness in avoiding local optima. A comprehensive attribute comparison highlights its scalability, adaptability, and computational efficiency which making it particularly well-suited for dynamic and real-time optimization challenges. The Raute Algorithm presents substantial opportunities in real-world domains beyond theoretical applications which including engineering optimization, artificial intelligence, supply chain management and data science. This research not only enhances computational innovation but also highlights the importance of cultural heritage in shaping innovative problem-solving methodologies while integrating indigenous wisdom into computational intelligence. The Raute Algorithm is the findings which is nature-inspired and human-centric approaches: contribute to the next generation of efficient and adaptive metaheuristic techniques.
Abstract: The Raute community of Nepal is the one of the last remaining nomadic indigenous groups. Which exhibits a unique lifestyle centered on adaptation, mobility, and resource management. Their dynamic movement patterns, decision-making hierarchy, and sustainable utilization of resources provide inspiration for a novel computational approach. Which is ca...
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