London Journal of Engineering Research London Journal of Engineering Research is focused on publishing groundbreaking ideas on theoretical and experimental research in all the domains relating to engineering. It provides practical, theoretical, and managerial implications useful for further research development. As a flagship scholarly journal, It is a peer-reviewed, international, indexed journal. The Journal publishes high-quality research papers that are double-blind refereed. Authors and readers include academic researchers and educators, as well as engineering professionals. SUBMIT MANUSCRIPT
Implementation of Generative Artificial Intelligence in a Virtual Reality Exhibition
Background:?Exhibitions are an activity that is often attended by many companies around the world because of its benefits as a promotional event. Companies can build the image of their company and products and interact directly with buyers through an exhibition. With recent advances in technology, virtual exhibitions have begun being created as an alternative to conventional face-to-face exhibitions. This presents an opportunity to implement other technologies within these new type of exhibition, namely generative artificial intelligence. Methods:?This research involved the use of the Unity game engine to create a virtual environment resembling an exhibition space. Within this environment users can navigate their surroundings and view the products displayed at the exhibition. Generative artificial intelligence was then implemented to generate content based on the products available in the exhibition. A head mounted display and virtual reality controllers were used to view and control the application. Participants were instructed to test the application. Once done, they then filled out a user acceptance test in order to evaluate their experience of using the application and how the use of generative artificial intelligence impacted that experience. Results:?Five participants tested and evaluated the application. The implementation of generative artificial intelligence had a positive impact on the quality of the information provided by the application. In addition, it did not impact the immersion of the experience. Conclusions:?Generative artificial intelligence can be used in a virtual exhibition setting to dynamically generate content regarding available products.
Digital radiography; Multiscale analysis; Pixel-level fusion; Image detail enhancement; Nondestructive testing
Copyright (c) 2025 Authors and Global Journals Private Limited http://creativecommons.org/licenses/by/4.0/
Polyphenol-Rich Collas-Coe a Study on Antioxidant Activity and Cellular Safety
Polyphenols, known for their strong antioxidant properties, combat oxidative stress, enhance cell viability, and protect against free radical damage. These bioactive compounds hold immense potential for functional food and cosmetic innovations, supporting overall health and promoting skin resilience, offering exciting opportunities in nutraceutical and cosmetic product development. This study evaluates the bioactive properties and potential applications of Collas-Co�, a high-polyphenol ingredient with promising antioxidant activity. The total phenolic content (TPC) of Collas-Co� was determined to be 58.05 � 0.33 mg GAE/g. Its antioxidant capacity, assessed via ORAC assay, revealed a remarkably high scavenging activity of 15,221 � 409 �mol TE/100g. Furthermore, the DPPH assay demonstrated superior radical scavenging activity, with Collas-Co� achieving 85.67% inhibition at 2.5 mg/mL, outperforming gallic acid by approximately 15%. Cytotoxicity studies using primary human dermal fibroblasts indicated that Collas-Co� exhibited dose-dependent effects. At lower concentrations (0.39 mg/mL), it enhanced cell viability to 112.94%, suggesting potential protective or stimulatory properties. Moderate concentrations (0.78�6.25 mg/mL) showed tolerability, while higher concentrations (>12.50 mg/mL) resulted in cytotoxicity, with an IC50 of 50.50 � 2.07 mg/mL. These findings highlight Collas-Co� as a potent antioxidant with moderate cytotoxicity, suitable for functional foods and cosmetic applications.
CFD Investigation of Turbulence Behaviour in Grooved Divergent Rocket Nozzles using 2 the k-? Model
�The adiabatic gas expansion in the divergent rocket area generally results in the generation of thrust 19 required for propulsion by providing an environment where the gas molecules speed rapidly out the nozzle 20 exit after traversing the nozzle area. This study investigates the impact of wall grooving in the divergent 21 section of rocket nozzles on turbulence characteristics and flow performance using Computational Fluid 22 Dynamics (CFD). Employing the Finite Volume Method (FVM) and the k� ? turbulence model in 23 ANSYS Fluent, the study compares a conventional nozzle and a grooved counterpart under identical 24 boundary conditions. Key parameters analyzed include Turbulent Kinetic Energy (TKE), Turbulent 25 Eddy Dissipation (TED), and velocity profiles. Results reveal that while the grooved nozzle slightly 26 reduces axial velocity, it significantly enhances turbulence dissipation and flow stability by suppressing 27 lateral velocity fluctuations. Enhanced TED and uniform TKE distribution suggest improved mixing 28 and thermal energy control, making grooved nozzles a promising modification for advanced propulsion 29 systems.�
Evolution of Performance Metrics for Accurate Evaluation of Speech-to-Speech Translation Models: A Literature Review
The translation of speech from a source to speech in a target language with generative artificial intelligence is an area of research that is presently being actively explored. This is aimed at solving global language barriers thereby ensuring seamless communication between the individuals involved. It has been well developed for high-resourced languages like English, Spanish, French and Chinese. Currently, objective evaluation metrics such as Bilingual Evaluation Understudy Scores (BLEUS), and subjective metrics such as Mean Opinion Score Naturalness (MOSN) and Mean Opinion Score Similarity (MOSS) are being used to evaluate the performance of the output of speech-to-speech models. However, low resourced languages are still undeveloped in the area of speech processing applications, especially the African indigenous languages. The output speech in the target language needs to be evaluated to determine the closeness to the ground truth, as well as how natural and intelligible it is to the intended listeners. This paper presents a review of trends from the current metrics to emerging ones such as Recall Oriented Understudy for Gisting Evaluation-L (ROUGE-L) and BLASER. The applications of speech models� metrics on various leaderboards and modern AI platforms were also discussed. The outcome shows that while BLEU score and MOSN metrics are prevalent for speech models, there is a need to explore metrics such as ROUGE-L, and BERTScore which are machine translation metric due to their benefits.
visualization of the axiom control CNC system
Bilingual Evaluation Understudy Scores (BLEUS)
Recall Oriented Understudy for Gisting Evaluation Longest Common Subsequence (ROUGE-L)
Refurbishment and Conversion to Pumped/Storage Systems of Hydroelectric Power Plants in C????ba (Argentina)
This research presents a comprehensive methodology for the technical and environmental assessment of the refurbishment and modernization of existing hydroelectric plants in the province of C�rdoba (Argentina) to use pumped storage hydropower (PSH) systems. The study is based on leveraging existing civil infrastructure, with the goal of minimizing environmental impacts, optimizing economic resources, and improving provincial energy management. The proposed methodology combines technical, hydrological, environmental, and water resource management criteria to prioritize sites with high conversion feasibility. Of the total number of plants analyzed, four were identified as having favorable conditions: Fitz Simon, Cassaffousth, Los Molinos I, and La Vi�a. Field campaigns and specific analyses were subsequently conducted to assess the technical and operational feasibility of their refurbishment and modernization. The results show that the selected plants have high potential to operate with pumped storage energy storage schemes, contributing to the integration of intermittent renewable energy and strengthening the provincial electricity grid. The case of the La Vi�a Power Plant is presented in detail, given its current modernization process, highlighting the technical and economic opportunity of incorporating the reversible pumping function simultaneously with the equipment upgrade.
Development of Nanotechnology for Manned and unmanned Aircraft: Perspectives on Jet Engines, Fuels, spacecraft, AI, and Sustainability
These days, nanotechnology has provided an enormous benefit to the aviation and aerospace industries for improved manufacturing, spacecraft, fuels, health, and more. The objective of this paper is to review and propose a higher level of nanotechnology development in the aviation industry. While space exploration and tourism have brought about an appreciation for Earth's environmental changes from space, numerous criticisms have indicated the large negative impact space travel has made on the environment. Here,� nanotechnology is offered as a field that can both improve space tourism and decrease its impact on the Earth�s environment. Specifically, this paper starts with a review of what material properties are needed for space exploration and then suggests the use of nanotechnology in the development of improved composite materials for jet engines, propulsion, and durability, considering aeronautical standards and aerospace developments, introducing the implementation of artificial intelligence (AI). This research includes aerospace and aeronautical industry�� manufacturers, their new nanotechnological strategies and breakthroughs, as well as failed attempts during manufacturing or� operations. Addressing the failures, this research indicates possible future steps for developing nanotechnology in unmanned and� manned aircraft to reduce harm to the environment while still� achieving space exploration.��
Development of a Structural Model for Constructing a Cutting Tool Trajectory Analysis Module in the Axiom Control CNC System
Justification. Currently, metalworking machines are used in various industries. The operation of these machines, designed for numerical control (CNC), is impossible without the use of appropriate systems that allow for the operational configuration of the system to solve various technological problems by controlling the machine's drives.� The purpose of this work is to comprehensively analyze the functionality of the Axiom Control CNC visualization module in order to identify its strengths and weaknesses compared to similar systems on the market. In the course of the research, a detailed review of existing technologies and visualization methods used in numerical control systems will be conducted, which will allow for a deeper understanding of current trends and needs in this area. Materials and methods. To achieve this goal, the following task has been set, aimed at expanding the functionality of the cutting tool rendering module in the Axiom Control CNC system, namely, the analysis of existing visualization tools for the trajectory of cutting tools in CNC systems.
CNT’s based Nanomaterials: An Interesting Cluster of Biosensors
This article outlines the function of carbon nanotubes (CNTs) in the fabrication of biosensors for various applications. We explain why CNTs are employed more frequently in biosensor fabrications for different applications and why CNTs have significant potential in these areas of application by examining the differences between other members of the nano-carbon family. Furthermore, we investigated the role of these nano-carbons in the detection of different analytes in bio-sensing. This chapter focuses on recent breakthroughs in the construction of sensors and biosensors using carbon nanotubes (CNTs). Biosensors are employed in a wide range of applications, from prosthetic devices to checking food quality. Because of the unique physical features of CNTs nanomaterials for biosensing applications, including optical, structural, mechanical, and thermal capabilities, the scientific community has put in a lot of effort.
Decisions with Uncertainty using Deterministic Analysis
The purpose of this article is to present a simple algorithm for the analysis of decisions with multiple objectives whose measures of effectiveness are random variables. This paper discusses the possibility of using the probability functions: uniform, normal, exponential, Cauchy, Chi-square, Erlang, Gamma, and Laplace. The algorithm, based on the concepts and methodology of Decision Theory, guides the analyst so that he can interact with the decision- maker. First, the analyst asks the decision-maker to define his objectives in the problem he is going to analyze, as well as the measures of effectiveness to evaluate its achievement. Then, he asks questions to the decision-maker to determine his type of behavior: aversion, proneness or neutrality to risk, for each measure of effectiveness. Next, for each of them, calculate its utility function. At that point, he asks the decision-maker to specify the alternatives to be analyzed with their probability function, their range, their mean, and standard deviation.
online hospital services; technology acceptance model; perceived usefulness; perceived ease of use; trust
Copyright (c) 2024 Authors and Global Journals Private Limited http://creativecommons.org/licenses/by/4.0/
Structural Equation Model Approach to Understand Intentions to use Online Hospital Services (OHS) in Context of Rural China
This study aims to explore the factors influencing the adoption of Online Hospital Services (OHS) among rural residents in China, utilizing the Technology Acceptance Model (TAM) framework. A Structural Equation Model (SEM) was employed to analyze data collected from 422 participants with Internet hospital experience, selected through random sampling. Data collection involved online questionnaires distributed over 45 days, resulting in effective samples. The survey was divided into six sections, focusing on various aspects of user perceptions and intentions regarding OHS. The results indicate that perceived usefulness (PU) and perceived ease of use (PEOU) positively affect attitudes towards OHS, with trust acting as a crucial mediator between these variables and usage intentions. The studys theoretical contributions include extending TAM by highlighting the central role of trust in digital health adoption, particularly in rural contexts. Practically, the findings suggest that policymakers and technology developers should focus on enhancing trust and user-friendliness to promote OHS adoption, thereby bridging the urban-rural healthcare divide and improving healthcare accessibility.
Optimization of Solar Energy using Artificial Neural Network VS Recurrent Neural Network Controller with Ultra Lift Luo Converter
In today's society, the demand for clean energy is essential. Traditionally, renewable sources such as hydropower, wind, and solar have provided sustainable solutions. Photovoltaic (PV) systems generate electricity from sunlight using semiconductor PV cells, which have been effective for over 30 years. The efficiency of PV cells depends on irradiance (solar photon intensity) and temperature. Higher irradiance boosts efficiency, while higher temperatures reduce it. Despite their low voltage outputs, PV systems can be optimized with DC-DC Ultra Lift Luo converters to meet load requirements, improving system efficiency. The Ultra Lift Luo converter, a type of DC-DC converter, offers a higher voltage conversion gain than conventional boost converters. This converter belongs to the Luo converter family, which uses advanced techniques to achieve high voltage gain and efficiency. Solar irradiance fluctuates throughout the day, impacting PV cell output. Maximum Power Point Trackers (MPPTs) adjust the system's operating point to sustain peak efficiency. This study aims to design AI controllers for MPPT management. In addition, we evaluate the performance of Artificial Neural Networks (ANN) and Recurrent Neural Networks (RNN) with three datasets to determine the most efficient AI controller for optimizing solar energy systems.
Study of the Eigenmodes of Anoptical Waveguide with a Refractive Index that Varies in the Radial Direction from the Central Axis
Using finite element analysis, the eigenmodes of the optical waveguide whose refractive index vary in the radial direction was obtained. To perform efficient calculations, the cross section of the waveguide was divided into a mesh structure of triangular element. The eigenmatrix equations that describe the characteristics of eigenmode were composed of the edges and nodes of triangular elements. The eigenmodes were established with transverse electric field, and electric potential. These were represented schematically as 2-Dim electric field, 3-Dim electric potential and 2-Dim electric equipotential contour. These representations were arranged sequentially from the lower order eigenmodes. And the unusual ones were randomly organized regardless of ordering index to reveal their characteristics more clearly. From these results, it was found that the refractive index distribution adopted in this study sufficiently performed the function of focusing electromagnetic waves in the central region.
Electrode Process with DC High Voltage and Electrochemical Plasma for Synthesis of Nanoparticle Solution and Wastewater Treatment
Conventional electrochemical processes with voltages of a few Volts only occur in an electrolyte solution, but with high DC voltage� electrode reactions can still occur in non-aqueous electrolyte, even distilled water. Electricity not only converts to heat, which increases the temperature of the water environment, but also performs anodic electrochemical reactions such as dissolving metals or generating oxygen (Me�Men++ne; 2H2O�O2+4H+) and generating hydrogen gas on the cathode (2H2O�H2+2OH). The gaseous environment formed from the electrochemical reactions on the electrodes with high electric, magnetic and suitable temperature conditions will appear plasma on the electrodes � the ionized state of materials. The reactions in the plasma state will generate many strong reactive agents such as electrons, atoms of H, O, O3 as well as free radicals H�, O�, OH�...Simultaneous dispersion into solution of agents formed by eletrochemical processes with DC high-voltage� and plasma reactions creates a variety of application possibilities.
Survey on Fibre Optic Deployment for Telecommunications Operators in Ghana: Coverage Gap, Recommendations and Research Directions
This paper presents a comprehensive survey on the deployment of fibre optic networks for telecommunications operators in Ghana. It addresses the challenges encountered by operators using microwave transmission systems for backhauling traffic and emphasises the advantages of deploying fibre optic networks. The study delves into the coverage gap, provides recommendations, and outlines research directions to enhance the telecommunications infrastructure in Ghana. Additionally, it evaluates next-generation optical access technologies and architectures tailored to operators' needs. The paper also investigates current technological solutions and regulatory, technical, and economic dimensions related to sharing mobile telecommunication networks in emerging countries. Overall, this paper offers valuable insights into fibre optic network deployment for telecommunications operators in Ghana and suggests strategies to meet the increasing demand for data and mobile applications.
Real-Time Object Detection in Disaster Zones and UAV Thermal-RGB Imagery
This research presents an innovative real-time disaster detection framework that leverages YOLOv11, a deep learning model, to enhance situational awareness and decision-making in emergency response operations. Unlike traditional UAV-based systems that often suffer reduced accuracy in low-visibility or complex environments, the proposed approach fuses RGB and thermal imagery from quadcopter drones with the advanced feature extraction and high-speed inference capabilities of YOLOv11. Integrated into an edge computing platform, the system supports low-latency, real-time object detection, making it highly effective for time-critical disaster scenarios. To further support operational decision-making, a multi-criteria decision-making (MCDM) module based on the Analytic Hierarchy Process (AHP) is embedded within the pipeline, enabling automated prioritization of detected threats. The model was trained and validated on a 10,000-image multimodal dataset comprising annotated UAV data from wildfire, flood, and earthquake zones. YOLOv11 consistently outperformed baseline models such as YOLOv5, achieving 88% detection accuracy, with precision, recall, and F1-scores all exceeding 0.85, and reduced response time by 40% compared to manual inspection workflows. The integration of YOLOv11 with thermal-RGB fusion significantly improved detection robustness under smoke, haze, and debris-obscured conditions. This study validates YOLOv11 on multimodal UAV disaster imagery with an integrated decision-support layer to improve emergency response effectiveness. The proposed framework sets a new benchmark in intelligent aerial surveillance, combining high detection accuracy with real-time processing capabilities. Designed for cost-efficiency and modular deployment, the framework supports scalability across local governments, first responders, and humanitarian organizations.
Conversational Intelligence for All: Speech Recognition Systems for Inclusive Digital Access
Digital service accessibility confronts enduring challenges in multilingual societies, where technological and linguistic barriers limit participation for numerous population segments. Voice-based interfaces operating through telephone systems present valuable pathways to narrow these divides, facilitating interaction without literacy prerequisites or technical proficiency. Telephone-based speech recognition faces distinctive technical obstacles, including limited bandwidth, ambient noise interference, and natural conversational patterns substantially different from laboratory speech inputs. Modern algorithmic techniques, especially those employing probabilistic modeling frameworks, show remarkable capacity to function within these demanding audio environments while handling regional accents and language variations. Practical implementations across transit networks, administrative service systems, and learning platforms demonstrate how these technologies establish vital access points for traditionally underserved communities. Such systems support transportation schedule inquiries, social program registration, and educational material engagement via conventional telephone infrastructure instead of demanding broadband connections or advanced mobile devices. Widespread implementation requires thoughtful attention to information security protocols, recognition fairness across accent variations, and strategic language selection to prevent perpetuating societal imbalances. This contribution outlines system architectures, deployment methodologies, and performance assessment frameworks for developing genuinely inclusive conversational technologies that broaden digital participation across communication and technological boundaries.
Deep Learning-based Severity Classification of Concrete Cracks using YOLOv8 for Structural Health Analysis
Crack detection and severity classification are essential tasks in structural health monitoring, especially for critical civil infrastructure such as roads and bridges. Traditional methods rely heavily on manual inspection, which is time-consuming, costly, and prone to human error. This study introduces a computer vision approach using the YOLOv8n model to automatically classify concrete surface conditions into seven categories, ranging from &quot;No Crack&quot; to & quot;Very Large Crack & quot;. After augmenting and preprocessing the dataset, the model was trained over 10 epochs and achieved an accuracy of 97.1% and accuracy of 99.9% on the validation set, demonstrating strong classification performance on 53 samples. With a dataset containing over 11,501 images across six categories, the model displayed strong generalization and fast inference speeds reached 0.4ms per image. These results validate the YOLOv8 classifier�s capability for rapid and accurate infrastructure assessment and pave the way for scalable deployment on drones and mobile devices in real-time field scenarios.
Search of Floating Mines by Unmanned Aerial Vehicles using Kinematic Projection Methods
The question of demining sea raids and ports, which is relevant for Europe in the period of active deployment of military confrontations on its territory, is considered. It is proposed to combine the search capabilities of unmanned aerial vehicles (UAV) with the ability of trawler boats to clear floating mines. The optimal trajectory of search movements of UAV along the Archimedean spiral is proposed. An appropriate number of UAV that can effectively search for floating mines simultaneously is determined. Mine detonation with warheads dropped from an aerial liquidator drone is proposed as one of the most effective ways of the disposal of mines.� The proposed method can be used to manage the search movements of UAV, to process the data provided by them about the detected floating mine, and to clarify the coordinates of the floating mine. A corresponding block diagram for computer software is proposed. It has been established that using the proposed search method and at the speed of UAV 5-5.5 m/s, it is possible to survey up to 6 square kilometers of sea every hour. At the same time, it is possible to save up to 20 liters of fuel for the trawler boat.
Effectiveness of Silica Fume as a Partial Cement Replacement in Recycled Aggregate Concrete
Recycled concrete aggregate (RAC) can be used in structural concrete to lessen the environmental impact of waste concrete and the use of natural resources. The current study summarized the mechanical performances of concrete and assessed the synergistic impacts of recycled aggregate, likely at 100% content, with silica fume (SF) partially substituting cement. The study's primary variables included the dosage of silica fume used as a partial replacement of ordinary Portland cement (OPC) at five different percentages: 0%, 4%, 8%, 12%, and 16% by weight. Five distinct mixtures, designated RACSF-0, RACSF-4, RACSF-8, RACSF-12, and RACSF-16, were made using differing concentrations of silica fume for M30 concrete. The workability of concrete mixes was examined using the slump test.� After increasing the proportion of SF, a declining trend was observed in the test results.� The mechanical characteristics of RACSF were examined at 7 and 28 days using compressive and splitting tensile tests.� The results demonstrated that adding SF enhanced RACSF's performance at both early and later curing ages, with the highest results occurring at 12% SF addition.� As a result, it is advised to partially substitute 12% SF for cement in RAC.
A Hybrid Multi-Attribute Framework for Optimizing Turnaround Inspection Scope in Oil and Gas Facilities
Purpose�� The purpose of this paper is to support operating facilities in identifying the appropriate and adequate initial turnaround (TA) inspection scope strategies and prioritizing operation, maintenance & engineering efforts to help deliver production operational targets by limiting the TA on to the equipment that internal inspection is necessary and avoid unnecessary replacement of internal parts (e.g., catalysts, desiccant, etc.) due to exposing the equipment to internal inspection. Furthermore, identify the inspections that can be performed non-intrusively and online, which can shorten the TA duration, minimize business interruption, and maximize plant availability. Design/methodology/approach�� The case study was conducted using one of the most widely deployed risk models in the oil and gas industry, where a full assessment was performed on an offshore gas-producing platform.
Analysis of Dynamic Characteristics of Straight Cylindricalgears based on Gyroscopic Effect
Purpose: The main objective of the study is to investigate the shaft plane inclination caused by bendingmoments and torsional vibrations during rotation without considering tooth friction. Methods: The law of vortex effects on gear vibrations was also considered. A four-degree-of-freedomstraight-tooth cylindrical gear dynamics model was developed based on the gyroscopic effect. ANSYSWorkbench was used to perform the model's finite element analysis, and Simulink was used for the simulationand analysis of the model.� Results: The gyroscopic effect is being investigated to determine the variation law of the intrinsic characteristicsofstraight cylindrical gears. The dynamic characteristics of straight cylindrical gears with and without gyroscopiceffects were compared, and the impact of gyroscopic effects on straight cylindrical gear systems was discussed. Conclusions: Forward and backward vortex phenomena can be observed under the influence of the gyroscopiceffect, as the intrinsic frequency increases with rotational speed. The results show that the gyroscopic effect significantly affects the translational and torsional vibrations of the master/follower wheel. It has a moresignificant impact on the torsional vibration displacement of the master wheel and the translational vibrationdisplacement of the follower wheel.�
The Solution of the 3 Dimensional Navier-Stokes Momentum Equations (A 3 Dimensional Integral Equation Approach)
This paper provides the solution of the classical navier stokes mo-mentum equations within the common three dimensional euclidean space. The function variable of the equations, h := (p, v) takes values in R4, consisting of a skalar field �pressure� p and a vector field �velocity� v where both, p and v depend on the same four variables (x, y, z, t). The solution space L ? {h ? C(R4 , R4 ), the continuous differentiable functions from R4 to R4 |v(x, y, z, t) = h(�, w(x, y, z, t)) ? C 2 (R4 , R3 ), the twice continuous differentiable functions from R4to R3� , for all functions w}. The equation system �navier-stokes�, as we will show, is underspecified as infinite many solutions exist. We will show smoothness and existence of the general solution of the navier stokes equations. We will deal with fluid dynamics and their boundary conditions for the com- pressible case as a general case of the incompressible one.
Claude-Luis Navier and George Gabriel Stokes
Understanding the World Through Systems: History, Classification and Future Directions
In recent years, the concept of "system" has been increasingly used. As a result, the concept of a system is found in almost all fields of knowledge, which has given rise to many definitions. It is almost impossible to give an accurate comprehensive definition of the system. Any of them will be relative. Therefore, it is better to consider the historical process of the formation of the concept of "system".
Design, Construction and Performance Comparison of Fuzzy Logic Controller and PID Controller for two-Wheel Balance Robot
In this article, the design, construction and control of a two-wheeled balancing robot was carried out with two PID controllers and fuzzy logic. This type of robot has advantages such as lower energy consumption and the ability to be used in small spaces with the ability to navigate in the entire workspace and rotate in place compared to other wheeled robots. Therefore, the need for research on the knowledge of building a two-wheeled balancing robot and controlling its balance optimally is felt to enter fields such as medical robots (assistant and military and robotics of humanoid robots), etc. For the design and modeling of the robot, SolidWorks software was used, and for programming, Arduino software was used along with the Arduino microcontroller board. In this research, the robot system is nonlinear and is considered as a black box, and two linear PID and nonlinear fuzzy controllers have been used. After conducting investigations and obtaining numerous results for both controllers in the results section, the performance of the fuzzy controller was observed to be much more optimal than the PID controller. The PID coefficients have been obtained experimentally, and the membership functions of the fuzzy controller have also been adjusted experimentally, and the Mamdani method and trapezoidal functions have been used. All the results have been obtained from the Arduino software and with a serial port connection between the computer and the Arduino microcontroller, all of which are presented in the results section.
Design, Simulation, and Real-Time Implementation of a DC Microgrid Powered by Renewable Hybrid Energy Sources
When large amounts of renewable energy sources are integrated, DC microgrids face difficulties with voltage regulation, energy management, inertia control, and uncertainty management. Numerous approaches have been offered to address these difficulties, such as droop control, centralized control, distributed control, virtual inertia control, and uncertainty management algorithms. Despite these efforts, a comprehensive overview that offers a panoramic understanding of the existing techniques and forthcoming trends in controlling renewable energy-integrated DC microgrids has been lacking. This paper involves designing, simulating, and implementing a DC Microgrid based on hybrid renewable energy sources to achieve high efficiency and sustainability in energy systems. �The research focuses on integrating solar and wind energy sources with the design of an advanced energy management system that ensures network stability and reduces electrical losses. A comprehensive mathematical model was developed to study network dynamics and analyze its response to operating conditions, such as climate and load changes. High-precision numerical simulation techniques were adopted to analyze the performance and improve the compatibility between the network components to achieve maximum operational efficiency. The research includes designing and implementing a controller to manage the real-time dynamic balance between energy generation and consumption. Practical tests of the proposed system were conducted in realistic operating environments to study the network's performance in multiple cases, such as peak loads and sudden outages.
Computation of the Minimum One-sided Hausdorff Distance Between Plane Curves under a Similarity Transformation and Relevant Applications in Roundness Error Evaluation
A two-stage (rough and accurate) computation strategy was developed in this study in order to accurately calculate the minimum one-sided Hausdorff distance between continuous plane curves under a similarity transformation. In the rough computation, a mathematical programming model based on the discretisation method was constructed to ascertain the minimum one-sided Hausdorff distance. In addition, the linearisation method in this model was elucidated. Based on that, the solutions were attained through a stable and efficient simplex method and 5 characteristic points were obtained. In the accurate computation, a local iterative accurate algorithm for computing the minimum one-sided Hausdorff distance was established after 4 similarity transformation parameters were separated from 10 curve parameters corresponding to 5 characteristic points. Similar results, which verify the feasibility of this algorithm, were obtained based on rough and accurate computations in a numerical example. Moreover, a roundness error evaluation programming model based on the minimum one-sided Hausdorff distance and relevant linear solution methods was also developed. Furthermore, the numerical examples based on this model were compared with those based on a conventional roundness error computation model. The results revealed that similar computation circle centre coordinates, roundness error, and characteristic points can be obtained based on both models. The computational efficiency can be significantly improved via the method proposed in this study.
Stamp Tests of Loess Soil Samples in a Tray
For construction conditions, when it is necessary to determine the expected amount of subsidence of small-width structures on high-capacity loess bases having a soaking area larger than the area of the base of their foundation due to prolonged moistening by filtration flow, the compression compression model for determining relative subsidence becomes unacceptable.�In addition, when determining the relative subsidence based on the results of compression tests, it is assumed that the soil of the loess base is deformed only in the vertical direction during moistening, while lateral deformations of the soil from the action of horizontal compacting stresses are not taken into account. However, as the results of comparing the calculations of many researchers of the expected subsidence with field data show, compression tests underestimate the additional deformations of structures that occur when their loess bases are moistened.
Towards an Epistemology of Structural Theory
This article summarizes, partly as a glossary and partly as a compilation, the main concepts involved in the theory of architectural structures. It contains a holistic arrangement of the theoretical foundations of the main components of materials mechanics and, above all, their interaction with architecture, in the exercise of the so-called structural calculation. In thematic literature, it is not easy to find all this information gathered in simple, plain language. Hence the importance of reviewing, in a relatively simple and quick reading, the principles that lead to the epistemology of structural theory.�
Loess Plateau; Ancient landslide; Unloading creep; Differential deformation; Stress path
On the Mechanical Interaction between two Small Antennas
The emergence of a time-constant interaction force between a pair of antennas of sound and electromagnetic waves is shown analytically. This force is identically analytically expressed through the phases of excitation of the antennas and the distance between them both for acoustic and electromagnetic cases. Frequencies, excitation phases, and distances between the antennas were found at which the antennas maximize either the mutual repulsive (attractive) forces in a pair of antennas, or the wave thrust forces that tend to move a pair of antennas in one direction. It is shown that the force of the wave thrust of a pair of antennas is opposite to the radiation flux, which plays a role similar to gases flowing from a rocket nozzle. For a catamaran (two floats-antennas of surface gravity waves on water with a phase shift of their vertical oscillations by ) the forward motion speed and the force of wave thrust, as well as the surface jet current near the float, similar to the flow created by a propeller, were measured. In this case, the inversion of the difference in the excitation phases of the half floats simultaneously led to an inversion of the thrust force, translational motion and jet flow. The dependence of the wave thrust on the excitation frequency (with a structurally fixed phase difference ) in the experiment turned out to be similar to the analytically obtained dependences for sound and electromagnetic waves.
Tracking Control using Sensor Technology Solar Cell: In Real Time Domain Analysis
Solar Tracking (ST) is employed to maximize output power due to the nonlinear characteristics of renewable energy sources. Sunlight is considered the most reliable traditional source of energy when energy emergencies arise. First, we present some basic characteristics of the motor in the form of Tables and Figures. Solar panel tracking is, therefore, necessary to enhance their efficiency. In this article, we present the sensor based viz. STM32 microcontroller has been implemented in real-time using the PV arrays. In addition, we did an analysis of stateof-the-art reviews of solar photo-voltaic systems for this research article. Researchers have developed sensor-based techniques to improve renewable energy systems. This technique performs better than other traditional methods.