Recent Patents on Engineering - Online First

Deep-brain stimulation (DBS) is a demonstrated rehabilitation for Alzheimer's Disease (AD), regularly resulting in an upgrade of engine work. In any case, some unfortunate incidental upshots can occur past DBS, which can deteriorate the patient's satisfaction. In this way, the medical group must painstakingly choose patients over whom to perform DBS. In the past, there have been a few endeavors to associate pre-usable information and DBS experimental results, generally centered on engine symptomatology.

A machine learning (ML)-based strategy called a multimodel pipeline alluded to as FlowModel is designed and implemented to anticipate an enormous number of DBS medical results for AD. It is composed of a patented Artificial Neural Network (ANN) for processing medical data, using a conventional image handling technique to extract morphological biomarkers from T1 imaging, and employing a Support Vector Machine (SVM) to perform regressions. We authenticated it in 256 AD patients who underwent DBS.

The FlowModel demonstrated high predictive precision, achieving a correlation coefficient of as high as 0.82 and successfully predicting 63 out of 84 clinical outcome scores. Importantly, FlowModel outperformed traditional linear models, demonstrating the capability to learn effectively from preoperative data alone.

The uniqueness of this study lies in its ability to predict multiple clinical outcomes across different modalities, independent of stimulation parameters. The introduction of this ML pipeline contributes to the precision medicine landscape by providing a robust, data-driven tool to select patients for DBS, potentially improving clinical decision-making and patient outcomes.

Firstly, the mapping relationship between the make-up torque and the axial preload of directional Measurement While Drilling (MWD) instruments was obtained. Next, the influence of thread joint stand-off deviation on their conversion relationship was studied. Finally, the make-up work of the instrument was guided effectively.

This patent research aims to investigate the make-up process of the MWD instruments and the impact of stand-off.

The experiment was designed to map the relationship between the make-up torque and axial pre-tightening force of the directional MWD instrument with a barrel. The influence of the thread joint stand-off deviation on the said relationship was studied.

Test results have shown that the relationship between the make-up torque and the axial preloading force is nonlinear. Further, in the American Petroleum Institute (API) standard, the relationship between the two is defined as linear, increasing the effect of preloading within the high torque range.

For identical make-up torques, the threaded joint with positive stand-off produced a smaller axial preloading force compared to its counterpart with negative stand-off. However, a large enough make-up torque reduced the influence of the threaded joint stand-off deviation on the make-up torque-axial preloading force.

With the arrival of the first airplane, the technology of anti-G suits for fighter pilots emerged. Anti-G suit technology has advanced rapidly over time, and anti-G suits are now widely used in modern fighter jets around the world. Furthermore, as fighter aircraft performance improves, the pilots' driving environment becomes more severe, and traditional anti-G suits no longer meet the requirements. As a result, all relevant countries are currently researching new types of anti-G suits for pilots to meet the load-resistant requirements in high-performance fighter aircraft.

Through a detailed analysis of the development history, research status and related technologies of fighter pilots' anti-G suit, and with reference to the papers and latest patents related to anti-G suit, we are looking for ways to improve the anti-overload resistance of fighter pilots' anti-G suit, and to optimize the man-machine efficacy of the anti-G suit.

The methodology of this study is as follows: By classifying the anti-G suit for fighter pilots, briefly explainining the development direction and research direction of key technologies, summarizing the advantages and disadvantages of each type of key technology respectively, and looking forward to the future development trend of anti-G suits.

Through the research and analysis of each key technology of anti-G suit for fighter pilots, it can be seen that the anti-G suit mainly maintains the pilot's ability to operate the aircraft by pressurizing the abdomen and lower limbs of the human body when positive overload is applied, in order to reduce the deformation and displacement of the internal organs and to stop the transfer of the blood to the lower half of the body, so as to ensure the circulating blood volume of the head; the differences in the clothing material, structure and filling medium influence the anti-G suit's anti-overload performance. The speed of media filling reaction and the filling process also have an important effect on the overload resistance performance.

The use of new anti-G suit clothing materials, filler structures, and media, and the use of intelligent technology to improve the reaction speed of media filling and optimize the media filling process can significantly improve the anti-load performance of fighter pilots and meet the higher anti-load requirements of today's high-performance fighter pilots.

Path planning technology has a wide range of applications in many fields. Applications in the field of high technology include: autonomous and touchless action of robots; obstacle avoidance and defense flight of drones; cruise missiles to avoid radar search, anti-bouncing attacks, and to complete the task of sudden defense and demolition. Applications in daily life include: GPS navigation; road planning based on GIS system; urban road network planning and navigation. Applications in the field of decision-making management include: vehicle problem (VRP) in logistics management and similar resource allocation problems in resource management. Routing problems in the field of communication technology. Any planning problem that can be topologized as a point and line network can basically be solved by the method of path planning. Different intelligent algorithms have different characteristics, and their application scope and fields are also different, so it is of great significance for the development of path planning technology to study the path planning intelligent algorithms from the characteristics of the algorithms themselves and their applications.

Analyze the advantages and disadvantages of various types of planning algorithms, look forward to the future development trend of mobile robot path planning, and provide certain ideas for the research of mobile robot path planning.

Search journals, patents, conferences, and papers related to mobile robot path planning, and summarize and analyze the advantages and disadvantages of various planning algorithms.

Based on the research results of many scholars, this study summarizes different mobile robot path planning methods. It is divided into four categories: traditional planning, intelligent search, artificial intelligence and local obstacle avoidance. This paper introduces and analyzes the latest research results of these types, including their design ideas, advantages and disadvantages, and improvement measures. The research methods adopted are analyzed in order to maximize the advantages of each algorithm and expand the application field of robot path planning to provide ideas and references.

This paper provides guidance for the design and optimization of robot path planning. Finally, this paper summarizes the future development trend of robot path planning, and looks forward to the future development trend and key areas of robot path planning.

With rapid economic development and urbanization, urban and rural areas face environmental challenges. Traditional optimization methods struggle with complexity and often fail to find global optima.

This study integrates a Bidirectional Long Short-Term Memory Network (BiLSTM) with Genetic Algorithm (GA)-Ant Colony Optimization (ACO) to improve environmental planning. BiLSTM captures long-term data correlations and predicts future trends, achieving an average Mean Squared Error (MSE) of 0.0217. GA-ACO, using GA-generated solutions as initial input for ACO, identifies optimal planning solutions.

This approach enhances air quality indicators and provides robust predictions and optimizations for sustainable urban and rural development.

To sum up, future development needs comprehensive technical progress, policy support and public participation to form a multi-level and multi-field collaborative mechanism to achieve the real sustainable development goal.

Indian agriculture is the backbone of the country's economy. As the population increases, the need for water arises accordingly. The main challenge in the extraction and transportation of water for agriculture and drinking purposes is high energy consumption. Among the various alternatives, the best one is to use solar energy, which is abundant and nearly cost-free, to power any industry, especially for irrigation. Photovoltaic (PV) solutions are the most suitable for remote agricultural needs.

The present research aimed to study the challenge of the use of solar energy, energy conversion initiatives, and the application of photovoltaic pumping systems in India and other developing countries.

Solar cells make up the smallest portion of a PV panel. Two or more distinct layers of material known as semiconductors that have been specially prepared are present in every solar cell and when exposed to light, these layers generate direct current (DC) electrical power. The electrical wiring in the circuit board accumulates the DC. After conversion, it is then given to either a DC pump or an AC pump, which pumps water while the sun shines.

Water pumps powered by solar energy are less expensive, have a silent operation, and require less maintenance. Moreover, in addition to pumping water, PV panels can be used to generate electricity for domestic use.

Solar energy finds potential applications for agricultural uses, such as, irrigation, purification, threshing aeration, and electrical fencing. Photovoltaic arrays of solar-powered water pumping systems can be used to generate electricity, reducing the dependency on conventional energy sources.

Titanium alloy, as a high-strength alloy material, has been widely used in aerospace and other fields due to its high specific strength, good corrosion resistance, super fracture toughness, and fatigue resistance. However, its small elastic modulus, low thermal conductivity, and strong chemical affinity result in high cutting forces and cutting temperatures during the cutting process. Different thermo-mechanical coupling effects can change the surface structure, composition, and mechanical properties of the workpiece and show different surface integrity. This paper summarizes the recent progress in the experimental research on surface integrity in the cutting of titanium alloy from four aspects, including surface roughness, microhardness, white layer, and residual stress. It focuses on analyzing the experimental results about the influence of process parameters, tool wear, and lubrication methods on surface integrity. The problems existing in current research and the future development direction are pointed out in this article. It is helpful to provide theoretical guidance for the machining of titanium alloy that meets the requirement of service performance.

Surface integrity encompasses both geometric features and physical and mechanical properties. Geometric features include surface roughness, surface morphology, and blade direction. Extensive research has been conducted on surface roughness, microhardness, the white layer, and residual stress. This article reviews recent advancements in experimental research on surface integrity during titanium alloy cutting, focusing on the impact of cutting parameters, tool wear, and lubrication methods. It also addresses current research challenges and suggests directions for future development.

Scholars have conducted extensive research on surface roughness, microhardness, the white layer, and residual stress using both experimental methods and finite element simulations. Experiments are the primary method due to existing issues with finite element simulations, which often suffer from low accuracy and poor reliability in studying surface integrity during titanium alloy machining.

At present, a large amount of experiments have been conducted. However, due to the numerous influencing factors and insufficient consideration of materials microstructure, the conclusions of current research are not consistent. Therefore, it is necessary to conduct more in-depth and systematic experimental research to clarify the influencing factors and the influence of cutting parameters on surface integrity.

There is a need for a deeper understanding of the physical and mechanical fundamentals of surface integrity. Integrating experimental research with finite element simulations can enhance the investigation of these mechanisms and improve predictions related to phase transformation, microhardness, white layer, and residual stress. It is helpful to provide theoretical guidance for the machining of titanium alloy that meets the requirement of service performance.

Rolling bearings are widely used as core components in mechanical equipment. Most bearings are equipped with a cage. However, when bearings work under conditions of large load and high speed, the cage will produce violent friction and collision between the rolling body and the rings of the bearing, which will reduce the stability of the bearing operation and even fracture the cage. Bearing cage significantly impacts the rotational accuracy and life of the bearing. Therefore, in recent years, many scholars have begun researching cageless rolling bearings. The cageless rolling bearing eliminates the various adverse effects brought about by the cage and reduces the weight of the bearing. However, the bearing structure must be reasonably designed to eliminate the reverse friction between adjacent rolling elements in cageless cases. Therefore, it is essential to design the structure of cageless rolling bearings and study their performance.

By analyzing and summarizing the research on cageless rolling bearings in recent years, the current problems and the future development of cageless rolling bearings are analyzed to provide a reference for researchers in the related fields.

This paper reviews representative patents related to cageless rolling bearings, discusses the structure and performance of various cageless rolling bearings, and analyzes their advantages and disadvantages, mainly including full complement cageless bearings, isolation element bearings, and special cageless bearings. Each type of bearing is analyzed through ball bearings and roller bearings.

Through the analysis of the related patents on cageless rolling bearings, it is found that the main problems affecting the development of cageless rolling bearings are the irregular collision of rolling elements with each other, the friction between rolling elements and the adjacent elements, and the difficulty in machining the particular shape isolation and raceway. Future research focuses on how to improve the service performance of cageless rolling bearings comprehensively so that they can work under high speed and heavy load.

Cageless rolling bearings simplify the bearing structure to increase the number of rolling elements. Therefore, the capacity of the rolling bearing is improved. The internal bearing friction can be reduced through structural innovation design. Cageless rolling bearings have broad development prospects

In most of the deep-cavity shell plastic products injection moulds, such as test tubes, syringes, and other medical devices, the slender core structure is essential. The uneven pressure of the polymer melt acting on the core during the filling process easily causes core deformation, resulting in core shift, the wall thickness inequality of the parts, and a series of problems, which then affect the final shape and mechanical properties of the plastic parts. The type of deep cavity component is prone to core shift defects during injection molding, resulting in uneven wall thickness of the syringe sleeve and inability to achieve perfect fit with the syringe core rod. Reducing the core shift of the component is the key issue of this article.

This study aims to combine injection moulding CAE with neural networks and optimization algorithms to reduce core shift, improve molding quality and dimensional accuracy, extend mold life, establish a regression model for predicting core shift, shorten product development time, and improve production efficiency.

Propose an injection moulding process parameter optimization method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) and Rireworks Algorithm (FWA). Taking a certain medical syringe as the research object, the Taguchi experiment was designed with mold temperature, melt temperature, injection time, injection pressure, packing pressure, and packing time as optimization variables. A simulation was conducted using Moldflow software, and the signal-to-noise ratio was used to analyze the significance and trend of the influence of process parameters on the plastic core shift. A predictive regression model is constructed based on ANFIS to express the nonlinear function relationship between process parameters and core shift. FWA is used to conduct global optimization based on the ANFIS model to determine the optimal combination of injection molding process parameters.

Through simulation verification, the errors between the FIS prediction model and the ANFIS prediction model were compared with the actual simulation values. The ANFIS prediction model had the highest accuracy, and the core shift of plastic parts based on the ANFIS-FWA combination optimization method decreased by 27.6% compared to before optimization. It was effective in improving the molding quality of plastic parts.

The core shift prediction model established based on ANFIS can accurately predict the core shift of the product, greatly reducing the lengthy simulation time of the computer and shortening the product development cycle. The ANFIS-FWA coupling method can find the best combination of process parameters among multiple injection molding process parameters, achieve the improvement of core shift defects, and provide new ideas for optimizing the core shift of the same type of product.