Analysis of the Incidence of the Tax on Profits in a Credit and Service Cooperative

The examination of tax compliance expenses is becoming more relevant, revealing a complex challenge that involves both national and international fiscal policies. This matter is closely linked to tax evasion and avoidance, and its consequences could distort taxpayers' economic choices. Against this background, the study focuses on the impact of profit tax on the operational outcomes of the 'Fortalecida Abel Santamaría Cuadrado' Credit and Services Cooperative, which operates within the sugarcane sector in Camagüey, Cuba. The research uses both qualitative and quantitative methodologies to investigate this issue. The study aims to provide a detailed understanding of how tax compliance costs affect the cooperative in question by implementing a tripartite procedure that uses mathematical techniques and relative frequency analysis. A key finding from this investigation is the negative impact resulting from the exclusion of advance salary payments as deductible expenses in tax calculations. This finding highlights a critical area for fiscal policy reform as the policy oversight is identified as a source of financial strain for the cooperative. The implications of this discovery are far-reaching, indicating that similar cooperatives and businesses within Cuba (and possibly in comparable economic contexts) may also be experiencing analogous fiscal burdens. Based on these insights, the study recommends the creation of customized methodologies to accurately measure tax compliance costs in the Cuban context. These methodologies should consider the distinctive socio-economic and regulatory features that define the Cuban economy, allowing for more precise evaluations of tax-related burdens on businesses. Furthermore, this research invites broader contemplation on the intersection of tax policy and business sustainability, particularly within sectors that are crucial to national economies but may be vulnerable to strict tax regimes. It emphasizes the need for a balanced approach to tax legislation that protects revenue interests without impeding economic vitality.  

Motion Planning for Non-Holonomic Mobile Robots in Cluttered Environment

Motion planning for mobile robots has several important applications in industry, planetary operations, defence, and medical automation. Planning an optimal path for nonholonomic (such as car-like) mobile robots is a vital aspect of this domain. Rapidlyexploring Random Tree Star (RRT*) has gained immense popularity due to its feasibility for path planning of non-holonomic mobile robots. Moreover, it does not require explicit information of environment obstacles and also supports complex high dimensional problems very well. Though RRT* is widely used method for path planning of mobile robots; slow convergence rate, large memory requirements and sub-optimal jagged paths are its proven problems. Such jagged paths consume more fuel and time during path following process and exert robot’s controller module also. Incorporating smoothness in jagged paths by satisfying differential constraints during planning phase increases the complexity of problem. Another solution is to use post processing smoothness techniques. However, after applying smoothness, resultant smooth path deviates the robot from planned path and introduces collision again. Since, most of the robots are battery operated; therefore planned path is required to be time and energy efficient, i.e., smooth and short. This thesis presents a comprehensive overview of state of the art path planning and path smoothing approaches. Secondly, a planning algorithm RRT*-Adjustable Bounds (RRT*-AB) is proposed to resolve the aforementioned issues in RRT*. The proposed planner has introduced novel strategies for space exploration and path optimization. Robustness and efficiency of proposed algorithm is tested using different environment maps of standard robotic datasets. These environment maps are cluttered with structured and unstructured obstacles, including narrow and complex maze cases. A thorough performance comparison along with numerical and theoretical complexity analysis of the proposed approach with state of the art techniques, i.e., RRT* and RRT*-Smart is also presented. Performance analysis shows that proposed approach has significantly improved path length, execution time and memory requirements even in narrow and dense environment. It has improved convergence rate up to 93 percent. Further, a path smoothing approach is applied to make the planner generated path feasible for non-holonomic mobile robots. The proposed smoothing approach uses clamped B-spline with automatic and economical control point adjustment while maintaining collision-free route. It also improves smooth path by eliminating post smoothness collisions, if any with desired smoothness. Proposed smoothing approach generates collision-free smooth path with reduced path length and execution time. In the end, thesis concludes with future research directions.