Projection Method Research Articles

Autofocusing of laser lithography through the crosshair projection method

In laser direct writing lithography, there is not any image information from the sample surface, which makes it difficult to find the position of the focal plane. To overcome the problem, an autofocusing through the crosshair projection method is proposed in this work. The crosshair on the reticle is inserted into the lighting path and imaged onto the sample surface. The addition of the crosshair projection increases the image information from the sample surface, meeting the requirement for the image information in focusing and improving the focusing environment. Furthermore, this work presents what we believe to be a new division of the focusing curve based on the range of the perpendicular feature extracted from the crosshair projection during the focusing process. The perpendicular feature can be extracted from the crosshair projection in the focusing zone but not in the flat zone. Compared with the traditional division, this new division enables the use of the perpendicular feature to directly determine the zone of the current sample position and to find the focusing zone during the focusing process. This can completely filter out the interference of local fluctuations in the flat zone, greatly facilitating the sample focusing. The autofocusing process was designed based on this division, and experiments were carried out accordingly. The focusing accuracy is about 0.15 µm, which is in the range of the depth of focus of the optical system. The results show that the proposed method provides a good solution to achieve accurate focusing based on the crosshair projection image from the sample surface in laser lithography.

Material Planning Analysis with Material Requirement Planning Method in High-rise Building Projects

Planning material supplies well is very important in implementing construction projects to ensure smoothness and efficiency. Smoothness includes thorough planning, including ensuring materials are met as planned, while efficiency aims to reduce time and cost. In this study, material planning will be carried out using the Material Requirement planning (MRP) method, using three different lot measurement techniques, namely Lot for Lot (LFL), Economic Order Quantity (EOQ), and Period Order Quantity (POQ). The MRP method is carried out to accurately calculate the amount of material needed to avoid excessive material inventory levels. After the MRP method, the most optimal number of orders and the total cost required for each lot measurement technique are obtained. The results of this study show that the LFL technique produces the optimum number of orders for gelam wood, plywood, reinforcement, bendrat wire, and ready mix concrete. Meanwhile, for materials such as lubricating oil, meranti wood, randu wood, and nails, it is optimal to order using the POQ technique.

A computational scheme and its comparison with optical soliton solutions for the stochastic Chen–Lee–Liu equation with sensitivity analysis

In this study, the stochastic Chen–Lee–Liu equation is considered numerically and analytically which is forced by the multiplicative noise in the Itô sense. The Chen–Lee–Liu equation is a special type of Schrödinger’s equation which has applications in optical fibers and photonic crystal fibers. The stochastic Crank–Nicolson scheme is formed to obtain the computational results. The numerical scheme is analyzed under the mean square sense and Von-Neumann criteria to show consistence and stability, respectively. Meanwhile, stochastic optical soliton solutions are attained by using two techniques, namely, the modified auxiliary equation method and the generalized projective Riccati equation method. These methods provide us with the different types of optical soliton solutions such as hyperbolic, trigonometric, mixed trigonometric, and rational forms. Mainly, the comparison of computational results with newly constructed optical soliton solution is shown graphically. To compare these results, initial conditions and boundary conditions are constructed by selecting some soliton solutions. The 3D and line graphs are drawn by choosing different values of parameters. Additionally, the sensitivity analysis is observed for the different initial values.

Gradient projection-based trajectory tracking control for automatic guided vehicle

In order to solve the problems of long operation time for solving the trajectory tracking controller and low real-time tracking. This paper proposes an improved model predictive control algorithm. By introducing the gradient projection method (GPM), the projection direction is used as the fastest descent direction of the objective function, which is used to reduce the number of iterations of the operation. Meanwhile, this paper adds constraints and relaxation factors to improve the trajectory tracking accuracy and prevent the controller operations from falling into local optimal solutions. Simulation by Simulink, the improved model predictive control algorithm reduces the average operation time by 24.74% and the single maximum operation time by 36.04%, effectively improving the real-time trajectory tracking performance. Finally, the verification experiment of trajectory tracking control is carried out by actual vehicle, proving the method’s effectiveness.

3D-AMM: a 3D artificial moment method for path planning of manipulator in multiple obstacles scenario

Purpose In response to the issue of traditional algorithms often falling into local minima or failing to find feasible solutions in manipulator path planning. The purpose of this paper is to propose a 3D artificial moment method (3D-AMM) for obstacle avoidance for the robotic arm's end-effector. Design/methodology/approach A new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second, distance weight factorization and spatial projection methods are introduced to improve the solution of repulsive moments in multiobstacle scenarios. Third, a novel motion vector-solving mechanism is proposed to provide nonzero velocity for the end-effector to solve the problem of limiting the solution of the motion vector to a fixed coordinate plane due to dimensionality constraints. Findings A comparative analysis was conducted between the proposed algorithm and the existing methods, the improved artificial potential field method and the rapidly-random tree method under identical simulation conditions. The results indicate that the 3D-AMM method successfully plans paths with smoother trajectories and reduces the path length by 20.03% to 36.9%. Additionally, the experimental comparison outcomes affirm the feasibility and effectiveness of this method for obstacle avoidance in industrial scenarios. Originality/value This paper proposes a 3D-AMM algorithm for manipulator path planning in Cartesian space with multiple obstacles. This method effectively solves the problem of the artificial potential field method easily falling into local minimum points and the low path planning success rate of the rapidly-exploring random tree method.

Measurement Of Spatial-Temporal Waves In The Laboratory Using Computer Vision Technolog

Given the complexity of ocean wave phenomena, physical modeling continues to be essential in various engineering and research applications. Wave height, a characteristic measured in nearly all projects, is commonly assessed using resistance/capacitance wave gauges. However, a significant limitation of these traditional wave gauges is their point-based nature, which restricts their ability to describe detailed spatial wave characteristics, especially during wave nonlinearity or when waveforms change. Furthermore, to reconstruct the 3D wave field, an array of wave gauges is often employed alongside an appropriate interpolation algorithm. Additionally, wave gauges may alter flow/wave conditions in specific scenarios. To address these limitations, various non-intrusive measurement techniques have been proposed. Gomit et al. (2022) classified these into stereoscopic, projection, and light-based methods, including LiDAR (Blenkinsopp et al., 2012), RGB-D cameras (Martínez-Aranda et al., 2018), and binocular stereo vision (Li et al., 2022). However, their applicability is constrained by factors such as optical setup complexity and device cost. With the rapid advancement of computer vision technology, it is possible to improve these issues and better describe temporal and spatial wave field variations using such techniques. This conference contribution details the reconstruction of the temporal and spatial 3D free water surface using photogrammetry techniques applied to images from consumer webcams. It also compares these results with measurements obtained from a wave gauge.

Tseng-type splitting projection algorithms for equilibrium problems in Hilbert spaces

In this work, based on the subgradient-type projection method considered by Santos and Scheimberg (Optimization, 2017), we propose some Tseng-type splitting algorithms for solving equilibrium problems whose bifunction is decomposed into the sum of two bifunctions in Hilbert spaces. We establish the weak and strong convergence of the proposed algorithm under standard assumptions. Numerical results in Nash–Cournot oligopolistic electricity market equilibrium model and comparisons with other related methods demonstrate the effectiveness of the proposed algorithm.

Correlation between climatic environment and characteristic components of 14 kinds of huajiao by thermal analysis techniques, GC‐MS and HS‐IMS

AbstractHuajiao (Zanthoxylum bungeanum Maxim.) is extensively cultivated in various countries, including China, Korea, and India, owing to its adaptability to diverse environments. This study comprehensively analyzed the volatile substance composition of 14 varieties of red huajiao with distinct geographical origins. Thermal analysis methods, gas chromatography‐mass spectrometry (GC‐MS), and headspace‐ion mobility chromatography (HS‐IMS) were employed to evaluate the total volatile substance composition and content. The study revealed minor variations in water content, volatile matter content, and fractions among the geographically sourced huajiao samples. Utilizing correlation analysis based on GC‐MS and orthogonal partial least squares discriminant analysis (OPLS‐DA) with HS‐IMS, a robust classification method for the 14 types of huajiao was developed. Applying the variable importance in the projection (VIP) method, seven distinctive components were identified as potential markers for distinguishing the geographical origins of red huajiao. By integrating climatic and topographical factors of the 14 huajiao varieties, the correlation analysis of GC‐MS, and OPLS‐DA classification outcomes from HS‐IMS elucidated the influence of geo‐environmental factors on huajiao components and contents. This research provides insights into the impact of diverse geographic environments on the constituents and characteristics of huajiao. It offers valuable guidance for selecting optimal cultivation locations to enhance huajiao quality, aiding consumers in making informed choices.

Efficient second-order accurate scheme for fluid–surfactant systems on curved surfaces with unconditional energy stability

Accurately simulating the interplay between fluids and surfactants is a challenge, especially when ensuring both mass conservation and guaranteed energy stability. This study proposes a highly accurate numerical scheme for the water–oil–surfactant system coupled with the Navier–Stokes equation. We use the second-order accurate discrete operators on triangular grids representing these surfaces. We use the Crank–Nicolson method to achieve the second-order temporal accuracy. To handle high-order nonlinearities, we employ the consistency-enhanced Scalar Auxiliary Variable method. Additionally, the projection method tackles the Navier–Stokes equations. These techniques guarantee the unconditional stability. Consequently, larger time steps are permissible. Our method achieves the high accuracy with lower computational cost. This efficiency stems from solely utilizing surface information, eliminating the need for calculations across the entire 3D space. The proposed scheme’s accuracy, stability, and robustness can be confirmed through various numerical experiments.

Exploring intricate connectivity patterns for cognitive functioning and neurological disorders: incorporating frequency-domain NC method into fMRI analysis.

This study extends the application of the frequency-domain new causality method to functional magnetic resonance imaging analysis. Strong causality, weak causality, balanced causality, cyclic causality, and transitivity causality were constructed to simulate varying degrees of causal associations among multivariate functional-magnetic-resonance-imaging blood-oxygen-level-dependent signals. Data from 1,252 groups of individuals with different degrees of cognitive impairment were collected. The frequency-domain new causality method was employed to construct directed efficient connectivity networks of the brain, analyze the statistical characteristics of topological variations in brain regions related to cognitive impairment, and utilize these characteristics as features for training a deep learning model. The results demonstrated that the frequency-domain new causality method accurately detected causal associations among simulated signals of different degrees. The deep learning tests also confirmed the superior performance of new causality, surpassing the other three methods in terms of accuracy, precision, and recall rates. Furthermore, consistent significant differences were observed in the brain efficiency networks, where several subregions defined by the multimodal parcellation method of Human Connectome Project simultaneously appeared in the topological statistical results of different patient groups. This suggests a significant association between these fine-grained cortical subregions, driven by multimodal data segmentation, and human cognitive function, making them potential biomarkers for further analysis of Alzheimer's disease.

Analysis of Soil Improvement Through PVD and Vacuum Preloading with Several Equivalent Permeability Methods

Vacuum preloading combined with prefabricated vertical drain (PVD) is one of the common soft soil improvement methods. Soft soils often pose significant problems in construction projects due to their low shear strength and high compressibility, leading to settlement issues and potential structural instability. The PVD combined with vacuum preloading method addresses these problems by accelerating the consolidation process and minimizing settlement during service period. The acceleration occurs due to the presence of PVD, allowing dissipation of excess pore water in horizontal direction towards the PVD. Thereafter, the water in the PVD is drained to the surface. When modelled in 2D, PVD behaves as a continuous drain in the plane strain direction, causing the flow conditions to deviate from the actual conditions. To address this issue, equivalent soil permeability values is required, allowing the 2D model to produce results closely resembling the actual conditions. This research explores the improvement of PVD vacuum preloading through three equivalent permeability approaches. Utilizing field monitoring data, which includes settlement measurements from settlement plates, changes in pore water pressure recorded by piezometers, and lateral deformation data captured by inclinometers, the study evaluates the effectiveness of these approaches. Comparative analyses with field monitoring data reveal that Indraratna equivalent permeability method has the best fit. The integration of PVD and vacuum preloading, coupled with the refinement of equivalent permeability methodologies, offers a promising solution for addressing soft soil problems in geotechnical engineering. This research contributes to the practical application of these methods in construction projects, emphasizing their potential to enhance soil stabilization and reduce settlement-related risks.

Implementasi Metode Agile Scrum Dalam Perancangan UI/UX Design Command Control Map Service Di PT. Len Industri (Persero)

Implementasi Metode Agile Scrum Dalam Perancangan UI/UX Design Command Control Map Service Di PT. Len Industri (Persero)

Finding and implementing the numerical solution of an optimal control problem for oscillations in a coupled objects system

In the modern world, where efficiency, stability, and precision play a crucial role, the development and application of optimal control strategies in oscillatory systems hold significant importance. The issues related to the numerical solution of control problems associated with damping oscillatory systems consisting of two objects are considered. To numerically solve the discussed problem, the gradient projection method, based on the formula for the first variation of the functional, and the method of successive approximations, associated with the linearity of boundary problems describing oscillatory processes, are applied. The oscillations of one object are described by a wave equation with first-order boundary conditions, while a second-order ordinary differential equation models the oscillations of the other object. Furthermore, the original and the adjoint boundary value problems are solved using direct methods at each iteration step. An algorithm for the numerical solution of the problem is proposed, and based on this algorithm, a software code for implementation is developed. The numerical results obtained in the study demonstrate that there is convergence in terms of functionality, and the approximately optimal controls found in this process are minimizing sequences in the control space. The mechanism of controlling and regulating the operation of the system according to its input constraints is provided by observed feedback, allowing systems with limited excitation to maintain stability and optimal functioning in conditions of changing external or internal circumstances. The obtained results can also be used to forecast the system's behavior in the future, resource planning, prevention of emergencies, or optimization of production processes

A novel model-based welding trajectory planning method for identical structural workpieces

Welding robots have been widely used with the development of manufacturing industry. At present, welding trajectory planning and programming of welding robots are performed separately for similar (structural) workpieces with different dimensions or deformations. Besides, the welding torch pose planning using conventional robot programming methods is time-consuming for workpieces with complex welding trajectories. To realize automatic planning of the welding torch pose for similar workpieces and improve the programming efficiency of welding robots, we propose a novel model-based welding trajectory planning method for welding robots. We create a basic model (point set) containing information on welding seam trajectory planning for similar workpieces. The welding seam trajectory extraction of similar workpieces is achieved by the non-rigid point set registration of the feature point cloud of similar workpieces with the basic model. Then, the welding torch pose planning is implemented by the geometric projection method of the local point cloud of the welding seam trajectory. Finally, the results of offline experiments and online experiments demonstrate the effectiveness of the proposed method.

An Omnidirectional Image Super-Resolution Method Based on Enhanced SwinIR

For the significant distortion problem caused by the special projection method of equi-rectangular projection (ERP) images, this paper proposes an omnidirectional image super-resolution algorithm model based on position information transformation, taking SwinIR as the base. By introducing a space position transformation module that supports deformable convolution, the image preprocessing process is optimized to reduce the distortion effects in the polar regions of the ERP image. Meanwhile, by introducing deformable convolution in the deep feature extraction process, the model’s adaptability to local deformations of images is enhanced. Experimental results on publicly available datasets have shown that our method outperforms SwinIR, with an average improvement of over 0.2 dB in WS-PSNR and over 0.030 in WS-SSIM for ×4 pixel upscaling.

Pembelajaran Pendidikan Agama Islam Berbasis Proyek

The project method is a way of teaching that provides students with the opportunity to use daily life units as learning material and aims to make students interested in learning. The project learning method is a teaching and learning activity whose process is based on inquiry. In this learning, the focus is on complex questions and problems. Then answer questions or solve problems through an investigative process carried out collaboratively over time. Most projects are carried out by investigating authentic issues and topics found outside of school. During the inquiry process, students learn the content, information and facts needed to draw conclusions from each question. During the process students also learn valuable skills and thinking habits. The project-based learning method is a learning method that uses problems as the first step in collecting and integrating new knowledge based on experience in real activities. Then the problem is solved in groups. In this learning, students are able to find their own solutions to the products/tasks given. Project-based learning methods can increase students' learning motivation in Islamic religious education, project-based learning methods can facilitate more active learning experiences.

Rock Breaking Law Under the Condition of Multi-row Drilling of Static Crushing Agent and Its Application in Roadway Expansion

Static crushing agent (SCA) has the advantages of good safety, no harmful gas and no vibration. It is widely used in rock crushing engineering of mine or underground engineering. Aiming at the performance of static crushing agent with different water-cement ratios, based on the engineering and environmental conditions of roadway side protection in a mine of Shanxi coking coal, the stress-time curve of SCA and the fracturing law of SCA on roadway side rock under the condition of multi-row drilling were studied by means of laboratory test and numerical simulation. The results show that: the smaller the hole spacing, the better the fracturing effect of SCA, the smaller the required fracture initiation stress and penetration stress, and the existence of the free surface contributes to the development of the fracture, and the fracture around the hole extends along the direction of the incoming pressure under the peripheral pressure conditions; the porous SCA fracturing can be used for the high efficiency of underground rock fracturing projects such as rocky roadway spreading and other underground rock fracturing projects. The research results of the project provide a new method for non-blasting roadway expansion, roof picking and other rock-breaking projects in underground coal mines.

A non-hydrostatic numerical model for simulating regular wave breaking and surf-swash zone motions

In the present study, a non-hydrostatic two-dimensional vertical model has been developed to simulate the breaking of regular waves and surf-swash zone motions on a sloping beach. The objective of the present study was to estimate parameters at depth. The governing equations, based on the pressure-correction projection method, were solved in two main phases. In the initial phase, intermediate velocities were acquired through the resolution of advection–diffusion and explicit dynamic pressure gradient terms within the momentum equations, employing a time-splitting technique. To ensure local momentum conservation and solution monotonicity, modifications were made to the governing equations and the solution approach. In the second phase, through the substitution of intermediate velocities and the corrected pressure gradient term from the momentum equations into the continuity equation, with the elimination of velocities, a Poisson pressure-correction equation was derived. In the discretization stage, an innovation was proposed to compute horizontal velocities at the locations where vertical velocities are present, significantly reducing computational costs. The equation was then converted into a system of linear equations, which was solved implicitly. Comparisons between numerical results and experiments concerning plunging and spilling breakers reveal that the developed model satisfactorily simulates the outcomes.

Relaxed Inertial Projective Forward-backward Splitting Algorithms for Regularized Least Square Problems

This study presents flexible conditions of the inertial extrapolation parameter for easy implementation that is added to the algorithm in faster convergence. Modified inertial forward-backward splitting algorithms for solving variational inclusion problems are introduced to apply to solve the LASSO problem for image restoration and signal recovery, and the elastic net model for classification problem. Projection methods are used in the final step for narrowing down the search field, resulting in a better solution.

Conjugate Gradient Derived Kernel Affine Projection Method for Post-distortion in Visible Light Communication Systems

Conjugate Gradient Derived Kernel Affine Projection Method for Post-distortion in Visible Light Communication Systems