Search Results (11,593)

The paper investigates various methods of microfinishing and arrives at the best technique to produce a very smooth surface. Various setups, with and without oscillation, were developed, together with a microfinishing attachment used on conventional lathes and milling machines. The workpiece material used was an amorphous nickel–phosphorus Ni–P alloy. The surface roughness parameters, such as Sa, Sv, and Sp, were measured with the TalySurf CCI6000 instrument. For the measurement of the surface protrusions, an “analysis of islands” technique was used at various levels of cut-off. The 2BA method—machining below the workpiece axis with oscillation—turned out to be the most effective method applied because it had the highest density of protrusions while having the smallest value of surface roughness. Non-oscillation with the machining zone below the axis also becomes effective, indicating that repositioning can compensate for a lack of oscillation. Already, the very compact surface structure achieved with minimized depths in the valleys by the 2BA method supported the improvement in tribological performance and increase in load-carrying capacity, together with lubricant retention enhancement. These results show that the microfinishing process can be optimized by parameter tuning, and also, non-oscillating methods could come to be a practical alternative, probably reducing the complexity of equipment and cutting costs. Further studies need to be aimed at the scalability of these methods and their application to other materials and fields. Full article

Accurate peach detection is essential for automated agronomic management, such as mechanical peach harvesting. However, ubiquitous occlusion makes identifying peaches from complex backgrounds extremely challenging. In addition, it is difficult to capture fine-grained peach features from a single RGB image, which can suffer from light and noise in scenarios with dense small target clusters and extreme light. To solve these problems, this study proposes a multimodal detector, called CRLNet, based on RGB and depth images. First, YOLOv9 was extended to design a backbone network that can extract RGB and depth features in parallel from an image. Second, to address the problem of information fusion bias, the Rough–Fine Hybrid Attention Fusion Module (RFAM) was designed to combine the advantageous information of different modes while suppressing the hollow noise at the edge of the peach. Finally, a Transformer-based Local–Global Joint Enhancement Module (LGEM) was developed to jointly enhance the local and global features of peaches using information from different modalities in order to enhance the percentage of information about the target peaches and remove the interference of redundant background information. CRLNet was trained on the Peach dataset and evaluated against other state-of-the-art methods; the model achieved an $mA{P}_{50}$ of 97.1%. In addition, CRLNet also achieved an $mA{P}_{50}$ of 92.4% in generalized experiments, validating its strong generalization capability. These results provide valuable insights for peach and other outdoor fruit multimodal detection. Full article

The aim of this study is to investigate how two different polishing techniques affect the color stability, surface roughness, and changes in surface morphology of aged and coffee-stained bulk-fill resin composites. A total of 112 disc-shaped samples were prepared using Omnichroma Flow Bulk (OB), Charisma Bulk Flow One (CB), Estelite Bulk Fill Flow (EB), and Estelite Sigma Quick (control). Samples were divided into two subgroups (n = 16) and aged using thermocycling. A profilometer was used to measure the surface roughness (R_a) and a spectrophotometer was used for color stability (ΔE₀₀). The EB group had the highest Ra values both before aging (disc: 0.23 ± 0.05, twist: 0.42 ± 0.05) and after aging (discs: 0.28 ± 0.04, twist: 0.46 ± 0.05). The OB group had the highest ΔE₀₀ values before and after aging (discs: 3.06 ± 0.54, twist 3.05 ± 0.41) and the highest after coffee-staining (discs: 3.75 ± 0.70, twist: 3.91 ± 0.57). Re-polishing reduced the ΔE₀₀ values in all materials but did not restore all to clinically acceptable levels. According to the results of this study, it can be concluded that the surface roughness and color stability of resin composites are notably influenced by the polishing technique, aging process, and coffee staining. Specimens that were polished using the multi-stage Super-Snap discs consistently exhibited smoother surfaces across all bulk-fill resin composites compared to those polished with the two-stage Diacomp plus Twist. Full article

Micro-pyramid copper molds are critical components in the preparation of high-precision optical elements, such as light-trapping films and reflective films. Their surfaces are composed of micro-pyramid arrays (MPAs). The surface roughness and edge burrs of MPAs seriously affect the optical properties of optical elements. To reduce the surface roughness, as well as the sizes of the edge burrs, the longitudinal ultrasonic vibration-assisted planing (LUVP) method for processing MPAs was developed during this study. In addition, an experiment was conducted to compare the precision planing and LUVP methods of MPA generation. The results show that the tool nose amplitude of the LUVP experimental platform constructed during this study was 3.3 μm, and that the operating frequency was 19.85 kHz. An MPA processed by LUVP had a smaller surface roughness than that of an MPA produced by precision planing; it also had fewer and smaller edge burrs, and there was slightly less diamond tool wear. The MPA cut using the LUVP method had no corrugation on its surface. This research lays a foundation for developing higher-precision micro-pyramid plastic films. Full article

In the manufacturing sector, there is a constant effort to improve procedures to produce high-quality goods at a lower cost. Academics are improving aspects of the metal machining process to increase efficiency. New techniques have been developed to achieve this, utilizing better production procedures and more advanced technological tools. It is essential to optimize production processes and minimize their negative impact on the environment and human health. Therefore, environmentally friendly machining operations, such as minimal quantity lubrication (MQL) machining, are being implemented. MQL is used in metal removal processes like milling, drilling, and turning to reduce the use of cutting fluids. The effectiveness of MQL can be improved by misting the flank face and the area near the chip tool contact. A turning center suitable for MQL configuration has been developed as part of the current research project. During the turning of Inconel 718 under dry, conventional fluid, and conventional fluid under MQL process conditions, forces and surface roughness data were examined. Full article

Most visual simultaneous localization and mapping (SLAM) systems are based on the assumption of a static environment in autonomous vehicles. However, when dynamic objects, particularly vehicles, occupy a large portion of the image, the localization accuracy of the system decreases significantly. To mitigate this challenge, this paper unveils DOT-SLAM, a novel stereo visual SLAM system that integrates dynamic object tracking through graph optimization. By integrating dynamic object pose estimation into the SLAM system, the system can effectively utilize both foreground and background points for ego vehicle localization and obtain a static feature points map. To rectify the inaccuracies in depth estimation from stereo disparity directly on the foreground points of dynamic objects due to their self-similarity characteristics, a coarse-to-fine depth estimation method based on camera–road plane geometry is presented. This method uses rough depth to guide fine stereo matching, thereby obtaining the 3 dimensions (3D)spatial positions of feature points on dynamic objects. Subsequently, by establishing constraints on the dynamic object’s pose using the road plane and non-holonomic constraints (NHCs) of the vehicle, reducing the initial pose uncertainty of dynamic objects leads to more accurate dynamic object initialization. Finally, by considering foreground points, background points, the local road plane, the ego vehicle pose, and dynamic object poses as optimization nodes, through the establishment and joint optimization of a nonlinear model based on graph optimization, accurate six degrees of freedom (DoFs) pose estimations are obtained for both the ego vehicle and dynamic objects. Experimental validation on the KITTI-360 dataset demonstrates that DOT-SLAM effectively utilizes features from the background and dynamic objects in the environment, resulting in more accurate vehicle trajectory estimation and a static environment map. Results obtained from a real-world dataset test reinforce the effectiveness. Full article

α-Ga₂O₃ films were grown on a c-plane sapphire substrate by HCl-supported mist chemical vapor deposition with multiple solution chambers, and the effect of HCl support on α-Ga₂O₃ film quality was investigated. The growth rate monotonically increased with increasing Ga supply rate. However, as the Ga supply rate was higher than 0.1 mmol/min, the growth rate further increased with increasing HCl supply rate. The surface roughness was improved by HCl support when the Ga supply rate was smaller than 0.07 mmol/min. The crystallinity of the α-Ga₂O₃ films exhibited an improvement with an increase in the film thickness, regardless of the solution preparation conditions, Ga supply rate, and HCl supply rate. These results indicate that there is a low correlation between the improvement of surface roughness and crystallinity in the α-Ga₂O₃ films grown under the conditions described in this paper. Full article

In this work, multilayer gradient coatings obtained by detonation spraying were studied. To obtain a multilayer gradient coating by detonation spraying, two modes with different numbers of shots of NiCrAlY and YSZ were developed. The presented results demonstrate the effectiveness of creating a gradient structure in coatings, ensuring a smooth transition from metal to ceramic materials. Morphological analysis of the coatings confirmed a layered gradient structure, consisting of a lower metallic (NiCrAlY) layer and an upper ceramic (YSZ) layer. The variation in the contents of elements along the thickness of the coatings indicates the formation of a gradient structure. X-ray analysis shows that all peaks in the X-ray diffraction patterns correspond to a single ZrO₂ phase, indicating the formation of a non-transformable tetragonal primary (t′) phase characteristic of the thermal protective coatings. This phase is known for its stability and resistance to phase transformation under changing operating temperature conditions. As the thickness of the coatings increased, an improvement in their mechanical characteristics was found, such as a decrease in the coefficient of friction, an increase in hardness, and an increase in surface roughness. These properties make such coatings more resistant to mechanical wear, especially under sliding conditions, which confirms their prospects for use in a variety of engineering applications, including aerospace and power generation. Full article

As a public service, municipal waste management at the local and regional levels should be carried out in an environmentally friendly and economically justified manner. Information on the quantity and composition of generated municipal waste is essential for planning activities related to the implementation and optimization of the process. There is a need for reliable forecasts regarding the amount of waste generated in each area. Due to the variability in the waste accumulation rate, this task is difficult to accomplish, especially at the local level. The literature contains many reports on this issue, but there is a lack of studies indicating the preferred method depending on the independent variables, the complexity of the algorithm, the time of implementation, and the quality of the forecast. The results concerning the quality of forecasting methods are difficult to compare due to the use of different sets of independent variables, forecast horizons, and quality assessment indicators. This paper compares the effectiveness of selected forecasting models in predicting the amount of municipal waste collection generated in Polish municipalities. The authors compared nine methods, including artificial neural networks (ANNs), support regression trees (SRTs), rough set theory (RST), multivariate adaptive regression splines (MARS), and random regression forests (RRFs). The analysis was based on 31 socioeconomic indicators for 2451 municipalities in Poland. The Boruta algorithm was used to select significant variables and eliminate those with little impact on forecasting. The quality of the forecasts was evaluated using eight indicators, such as the absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R²). A comprehensive evaluation of the forecasting models was carried out using the APEKS method. An analysis of the results showed that the best forecasting methods depended on the set of independent variables and the evaluation criteria adopted. Waste management expenditures, the levels of sanitation and housing infrastructure, and the cost-effectiveness of waste management services were key factors influencing the amount of municipal waste. Additionally, this research indicated that adding more variables does not always improve the quality of forecasts, highlighting the importance of proper selection. The use of a variable selection algorithm, combined with the consideration of the impact of various socioeconomic factors on municipal waste generation, can significantly improve the quality of forecasts. The SRT, CHAID, and MARS methods can become valuable tools for predicting municipal waste volumes, which, in turn, will help to improve waste management system. Full article

In recent years, additive manufacturing (AM) has made considerable progress and has spread in many industries. Despite the advantages of this technology including freedom of design, lead time reduction, material waste reduction, special tools manufacturing elimination, and sustainability, there are still a lot of challenges regarding finding the beneficial application. In this study, the feasibility of replacing traditional manufacturing methods with additive manufacturing in the energy sector is investigated, with a specific focus on gas-insulated high-voltage switchgear (GIS). All aluminum parts in one specific GIS product are analyzed and a decision flowchart is proposed. Using this flowchart, printability and the best AM technique are suggested with respect to part size, required surface roughness, requirements of electrical and mechanical properties, and additional post processes. Simple to medium complexity level of geometry, large size, high requirements for electrical and mechanical properties, threading and sealing, and lack of a standard for printed parts in the high voltage industry make AM a challenging manufacturing technology for this specific product. In total, implementing AM as a short series production method for GIS aluminum parts may not be sufficient because of the higher cost and more complex supply chain management, but it can be beneficial in R&D cases or prototyping scenarios where a limited number of parts are needed in a brief time limit. Full article

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most cellular systems, such as Bluetooth indoor positioning systems, due to multipath and non-line-of-sight (NLOS) propagation, indoor positioning accuracy is severely affected. In this paper, a comprehensive algorithm that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates is investigated, which is obtained using particle filtering. This algorithm allows us to explore new optimized methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by approximately 25.7% on average. Full article

Area selective deposition (ASD) is a promising IC fabrication technique to address misalignment issues arising in a top–down litho-etch patterning approach. ASD can enable resist tone inversion and bottom–up metallization, such as via prefill. It is achieved by promoting selective growth in the growth area (GA) while passivating the non-growth area (NGA). Nevertheless, preventing undesired particles and defect growth on the NGA is still a hurdle. This work shows the selectivity of Ru films by passivating the Si oxide NGA with self-assembled monolayers (SAMs) and small molecule inhibitors (SMIs). Ru films are deposited on the TiN GA using a metal-organic precursor tricarbonyl (trimethylenemethane) ruthenium (Ru TMM(CO)₃) and O₂ as a co-reactant by atomic layer deposition (ALD). This produces smooth Ru films (<0.1 nm RMS roughness) with a growth per cycle (GPC) of 1.6 Å/cycle. Minimizing the oxygen co-reactant dose is necessary to improve the ASD process selectivity due to the limited stability of the organic molecule and high reactivity of the ALD precursor, still allowing a Ru GPC of 0.95 Å/cycle. This work sheds light on Ru defect generation mechanisms on passivated areas from the detailed analysis of particle growth, coverage, and density as a function of ALD cycles. Finally, an optimized ASD of Ru is demonstrated on TiN/SiO₂ 3D patterned structures using dimethyl amino trimethyl silane (DMA-TMS) as SMI. Full article

Supercapacitor electrode materials play a decisive role in charge storage and significantly affect the cost and capacitive performance of the final device. Engineering of the heterostructure of metal–organic framework (MOF)-derived transition metal nitrides (TMNs) can be conducive to excellent electrochemical performance owing to the synergistic effect, optimized charge transport/mass transfer properties, and high electrical conductivity. In this study, a Co₄N/CoN heterostructure was incorporated into a nitrogen-doped support by radio-frequency (RF) plasma after simple pyrolysis of Co-based formate frameworks (Co-MFFs), with the framework structure well retained. Plasma engineering can effectively increase the ratio of Co₄N in the Co₄N/CoN heterostructure, accelerating the electron transfer rate and resulting in a rough surface due to the reduction effect of high-energy electrons and the etching effect of ions. Benefiting from the plasma modification, the obtained electrode material Co₄N/CoN@C-P exhibits a high specific capacitance of 346.2 F·g⁻¹ at a current density of 1 A·g⁻¹, approximately 1.7 times that of CoN/Co₄N@C prepared by pyrolysis. The specific capacitance of Co₄N/CoN@C-P reaches 335.6 F·g⁻¹ at 10 A·g⁻¹, approximately 96.9% of that at 1 A·g⁻¹, indicating remarkable rate capability. Additionally, the capacitance retention remains at 100% even after 1000 cycles, suggesting excellent cycling stability. The rational design and plasma engineering of the TMN heterostructures at the nanoscale are responsible for the excellent electrochemical performance of this novel composite material. Full article

Implants and other medical devices are prone to bacterial infections on their surface due to bacterial attachment and biofilm formation. In this study, silver nanoparticles were generated in situ onto regulated synthesized polydopamine particles, and the optimal amount of silver nitrate was determined. Composite micro–nano particles were then deposited on a titanium alloy surface. X-ray photoelectron spectroscopy and energy-dispersive X-ray spectroscopy were used to confirm that the titanium alloy surface was successfully coated with PDA-Ag. Scanning electron microscopy, transmission electron microscopy, and three-dimensional optical profilometry were utilized to analysis the morphology of the micro–nano particles and the surface morphology after deposition. The diameters of the polydopamine particles and silver nanoparticles were 150 nm and 25 nm, respectively. The surface roughness values decreased from 0.357 μm to 25.253 μm because of the coated PDA-Ag. Morphology and chemical composition analyses of the modified surface indicated that the PDA-Ag particles were uniformly bonded to the substrate surface. Antimicrobial assays illustrated that the PDA-Ag-modified surface possessed resistance against Escherichia coli and Staphylococcus aureus attachment, with an effectiveness of 96.14 and 85.78%, respectively. This work provides a new strategy and theoretical basis for tackling medical-related surface infections caused by bacterial adhesion. Full article

With the advancement of urbanization and the continuous deepening of reforms in urban–rural systems, China’s urbanization process has entered a new era of integrated urban–rural integration. Currently, as a global “new green revolution” gains momentum, numerous countries are deeply integrating the concept of sustainable development into new urban planning. Against this backdrop, urban planners worldwide are committed to building green, livable, and smart cities that can meet the needs of the present generation without compromising the ability of future generations to meet their needs, thus achieving the vision of harmonious coexistence between humanity and nature. Characteristic towns, leveraging their resource advantages, play a significant role in achieving sustainable regional economic development. They serve as valuable references for China’s urban transformation and upgrading, as well as for promoting rural urbanization, and are crucial avenues for advancing China’s urban–rural integration development strategy. The evaluation of the development level of characteristic towns is a necessary step in their progress and a strong guarantee for promoting their construction and development. Therefore, effectively evaluating the social benefits of characteristic towns is paramount. This study constructs an evaluation model based on the grey rough set theory and Technique for Order Preference by Similarity to Ideal Solution of TOPSIS. Firstly, an evaluation index system for the development level of characteristic towns is established. Then, the grey relational analysis method and rough set theory are used to reduce the index attributes, while the conditional information entropy theory is introduced to determine the weights of the reduced indicators. Finally, the TOPSIS model is applied to evaluate the development level of characteristic towns. Through empirical research, eight characteristic towns in Zhejiang Province, China, were assessed and ranked, verifying the effectiveness and feasibility of the proposed model. Full article