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The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

Previous studies focused on the influence of outsourcing (labor division) on productivity, especially in the industrial economy. However, few studies have focused on how labor division in agriculture affects agricultural productivity. To bridge this gap, this study uses survey data from 4864 farmer households in China to explore the impacts of outsourcing on agricultural productivity.

This study employs an endogenous switching regression to account for selection bias and a counterfactual framework to measure the degree of influence. Thus, this study analyzes determinants of outsourcing and the impacts of outsourcing on agricultural productivity under the same framework.

The results revealed the following. (1) Farmer households with the below average productivity tended to outsource; conversely, farmer households with the above average productivity tended to cultivate the land by themselves. (2) Productivity increased by 25.61% for farmer households who choose to outsource. Moreover, if nonoutsourcing farmer households would choose to outsource, their productivity would increase by 10.86%.

This study furthers one’s understanding of how outsourcing affects agricultural productivity among farmer households.

The purpose of this paper is to develop a potential nanoparticles lubricant additive for solving the problem of the insolubility and stable dispersity; the complex nanoparticles with core-shell structures are less studied in the field. Therefore, this paper determines novel complex nanoparticles and their tribological properties.

According to the conventional preparation method, the complex nanoparticle styrene/calcium borate (PS/O-CaB) was synthesized. The microstructures of the as-obtained samples were characterized by X-ray diffraction infrared spectroscopy and thermogravimetric analysis. Tribological properties of PS/O-CaB used as lubricating oil additive were evaluated on four-ball tribometer. The worn surface of the steel ball was investigated by a three-dimensional non-contact surface profilometer and X-ray photoelectron spectroscopy (XPS).

The results of the structure characteristic indicate two different crystalline forms, namely, Ca₂B₆O₁₁ and Ca₂B₂O₅, and the average size of calcium borate nanoparticles in PS/O-CaB is about 20-40 nm. Moreover, the good tribological properties are due to a wear resistance film containing both depositions and the tribochemical reaction products which comprise B2O3, FeB and Fe2O3.

Novel complex nanoparticles with core-shell structure (PS/O-CaB) were successfully prepared. Moreover, the PS/O-CaB shows excellent tribological capacity such as load-carrying, friction-reducing and antiwear property.

This study aims to analyze the impact mechanism of typical environments in China's western mountainous areas on the durability of railway concrete and propose measures to improve durability.

With the continuous promotion of infrastructure construction, the focus of China's railway construction has gradually shifted to the western region. The four typical environments of large temperature differences, strong winds and dryness, high cold and low air pressure unique to the western mountainous areas of China have adverse effects on the durability of typical railway structure concrete (bridges, ballastless tracks and tunnels). This study identified the characteristics of four typical environments in the western mountainous areas of China through on-site research. The impact mechanism of the four typical environments on the durability of concrete in different structural parts of railways has been explored through theoretical analysis and experimental research; Finally, a strategy for improving the durability of railway concrete suitable for the western mountainous areas of China was proposed.

The daily temperature difference in the western mountainous areas of China is more than twice that of the plain region, which will lead to significant temperature deformation and stress in the multi-layered structure of railway ballastless tracks. It will result in cracking. The wind speed in the western plateau region is about 2.5 to 3 times that of the plain region, and the average annual rainfall is only 1/5 of that in the plain region. The drying effect on the surface of casting concrete will significantly accelerate its cracking process, leading to serious durability problems. The environmental temperature in the western mountainous areas of China is generally low, and there are more freeze-thaw cycles, which will increase the risk of freeze-thaw damage to railway concrete. The environmental air pressure in the western plateau region is only 60% of that in the plain region. The moisture inside the concrete is more likely to diffuse into the surrounding environment under the pressure difference, resulting in greater water loss and shrinkage deformation of the concrete in the plateau region. The above four issues will collectively lead to the rapid deterioration of concrete durability in the western plateau region. The corresponding durability improvement suggestions from theoretical research, new technology development and standard system was proposed in this paper.

The research can provide the mechanism of durability degradation of railway concrete in the western mountainous areas of China and corresponding improvement strategies.

This paper aims to study the lubrication and sealing performance on the textured piston pair under the cross action of the shape and structure parameters. This paper further carries out the optimization design of low energy consumption hydraulic impact piston pair.

Based on the characteristics of the ring gap seal piston pair, the flow field analysis model of the whole film gap is established for its periodic treatment. The friction power loss of the piston pair is defined as the evaluation index of the lubrication performance and the leakage power loss as the evaluation index of the sealing performance. The orthogonal test design and CFD software were used to analyze the lubrication and sealing performance of the textured piston pair.

The cross action of shape and structure factors has a great influence of the lubrication and sealing performance on the textured piston pair. Clearance and shape parameters have great influence on it, while seal length and depth diameter ratio have little influence. The sealing performance of conical textured piston pair is good, while the lubrication performance of square textured piston pair is good. The primary and secondary order of influence of shape and structure on energy consumption on piston pair is B (seal clearance) > C (texture shape) > D (area ratio) > A (seal length) > E (depth diameter ratio).

Breaking the defect of local optimization design on traditional piston pair structure, then find the matching relationship of structural parameters on textured piston pair. Further improve the lubrication and sealing performance of the piston pair, and provide reference for the global optimization design of the low energy consumption hydraulic impact piston pair.

This paper aims to reveal the influence of the grooved texture parameters on the lubrication performance of circular pocket-roller pairs in cylindrical roller bearings.

In this paper, the thermal elastohydrodynamic lubrication mathematical model of the grooved texture circular pocket-roller pair was established, the finite difference method and successive over-relaxation method were used to solve the model, the influence of texture quantity, texture depth and texture area ratio on circumferential bearing capacity, friction coefficient, maximum temperature rise, stiffness and damping of the circular pocket-roller pairs were analyzed.

The results show that texture quantity, texture depth and texture area ratio significantly influence the static and dynamic characteristics of circular pocket-roller pairs. The suitable surface groove texture parameters can dramatically improve the circumferential bearing capacity, reduce the friction coefficient, inhibit the maximum temperature rise and increase the stiffness and damping of the circular pocket-roller pairs.

The research in this paper can provide a theoretical basis for the optimization design of pockets in cylindrical roller bearings to reduce friction and vibration.

Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.

This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.

Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.

The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.

The purpose of this study was to map the quantity (frequency), quality (impact) and structural indicators (correlations) of research produced on cloud computing in 48 countries and 3 territories in the Asia continent.

To achieve the objectives of the study and scientifically map the indicators, data were extracted from the Scopus database. The extracted bibliographic data was first cleaned properly using Endnote and then analyzed using Biblioshiny and VosViewer application software. In the software, calculations include citations count; h, g and m indexes; Bradford's and Lotka's laws; and other scientific mappings.

Results of the study indicate that China remained the most productive, impactful and collaborative country in Asia. All the top 20 impactful authors were also from China. The other most researched areas associated with cloud computing were revealed to be mobile cloud computing and data security in clouds. The most prominent journal currently publishing research studies on cloud computing was “Advances in Intelligent Systems and Computing.”

The study is the first of its kind which identified the quantity (frequencies), quality (impact) and structural indicators (correlations) of Asian (48 countries and 3 territories) research productivity on cloud computing. The results are of great importance for researchers and countries interested in further exploring, publishing and increasing cross country collaborations related to the phenomenon of cloud computing.

The purpose of this paper is to present a methodology based on an optimizer linked with electric finite element method (FEM) for automating the optimized design of power transformer insulation system structures.

The proposed methodology combines two stages to obtain the optimized design of transformer insulation system structures. First, an analytical calculation is carried out with the optimizer to search a candidate solution. Then, the candidate solution is numerically checked in detail to validate its consistency. Otherwise, these two steps are iteratively repeated until the optimizer finds a candidate solution according to the objective function.

The solutions found applying the proposed methodology reduce the inter-electrode distances compared to those insulation designs referenced in the literature for the same value of safety margin.

The proposed methodology explores a wide range of insulation system structures in an automated way which is not possible to do with the classical trial-and-error approach based on personal expertise.

Recent decade has witnessed exponential growth in e-commerce segment, leading to emergence of various online selling platforms catering to diverse product requirements of customers. Such a development has provided impetus to both existing businesses and newly established ventures to make available their offerings through online selling platforms with a view to improve the reach of their products. This study is an attempt to identify the experience of registered vendors with the online marketplaces. It aims to develop and validate a scale to measure vendor's experience with e-commerce platforms.

As a part of the scale development process, relevant literature sources were scanned to spot the precise knowledge gap and to put in place a sound theoretical background for the study. Thereafter, a scientific approach was adopted for scale creation. First, the scale items were identified through interviews of vendors registered with major online selling platforms and other academic experts pertaining to the marketing domain. Subsequently, major dimensions of seller experience were identified through exploratory factor analysis (EFA) applied on data collected from active vendors by the means of a structured survey instrument. The final data set was subjected to confirmatory factor analysis (CFA) in a bid to validate the scale.

The study’s outcomes reveal that seller experience in an online marketplace can be best captured by a multidimensional scale characterized by six major dimensions. These are “Registration,”; “Product Listing”; “Pricing Autonomy”; “Ease of Pick-up and Delivery”; “Credit of Receivables” and “Vendor Assistance.” A proper emphasis to continually improve upon these dimensions by the e-commerce platforms is expected to enhance the utility and overall experience of vendors from such platforms. Existence of a mutually beneficial relationship between vendors and online marketplaces will help marketplaces to mitigate concerns like nonfulfillment of orders and dispatch of substandard products.

Sustainable long-term relations between vendors and online marketplaces hold the key for such marketplaces to render error-free and delightful service on each individual order received. Seller experience of registering and operating on such e-marketplaces inspite of playing a defining role in vendor–marketplace relations has received scant attention of researchers, both in academia and industry till date. The present research is a seminal attempt to address this gap in marketing literature and offer additional know-how.