Empirical modeling for intelligent, real-time manufacture control

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper

An Urban Traffic Flow Fusion Network Based on a Causal Spatiotemporal Graph Convolution Network

Traffic flow prediction is an important part of intelligent transportation systems. In recent years, most methods have considered only the feature relationships of spatial dimensions of traffic flow data, and ignored the feature fusion of spatial and temporal aspects. Traffic flow has the features of periodicity, nonlinearity and complexity. There are many relatively isolated points in the nodes of traffic flow, resulting in the features usually being accompanied by high-frequency noise. The previous methods directly used the graph convolution network for feature extraction. A polynomial approximation graph convolution network is essentially a convolution operation to enhance the weight of high-frequency signals, which lead to excessive high-frequency noise and reduce prediction accuracy to a certain extent. In this paper, a deep learning framework is proposed for a causal gated low-pass graph convolution neural network (CGLGCN) for traffic flow prediction. The full convolution structure adopted by the causal convolution gated linear unit (C-GLU) extracts the time features of traffic flow to avoid the problem of long running time associated with recursive networks. The reduction of running parameters and running time greatly improved the efficiency of the model. The new graph convolution neural network with self-designed low-pass filter was able to extract spatial features, enhance the weight of low-frequency signal features, suppress the influence of high-frequency noise, extract the spatial features of each node more comprehensively, and improve the prediction accuracy of the framework. Several experiments were carried out on two real-world real data sets. Compared with the existing models, our model achieved better results for short-term and long-term prediction.© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

‘New Engineering Education’ in Chinese Higher Education: Prospects and challenges

Since becoming a formal signatory of the Washington Accord in 2016, China has outlined an initiative ‘New Engineering Education’ (NEE) to reform its engineering education at university level. This paper elaborates upon the NEE initiative by presenting analysis of its domestic and international context, the goals of the initiative, how the initiative draws upon international standards, major actions under the initiative, and the challenges remaining for NEE to achieve its goals. The paper argues that China views international practices and standards of engineering education in developed nations as highlands to imitate and surpass, and the NEE goals embody an ambitious systematic rather than partial reform of the sector. China has pushed forward the NEE reform with measures such as formulating National Standards for dozens of categories of engineering programs, commissioning 600+ research projects on NEE development, establishing new engineering programs and interdisciplinary courses, strengthening university-partnership, updating accreditation for engineering programs, and improving both external and internal quality assurance mechanism. The sector, however, still faces challenges in achieving systematic quality upgrade due to hindering factors like enlarged uneven resource allocation, downplayed teaching activities and the difficulties in reforming the curricula system. Expected changes are also discussed.Received: 06 March 2018Accepted: 07 November 2018Published online: 29 November 2018</p

3D Object Detection Algorithm Based on the Reconstruction of Sparse Point Clouds in the Viewing Frustum

In response to the problem that the detection precision of the current 3D object detection algorithm is low when the object is severely occluded, this study proposes an object detection algorithm based on the reconstruction of sparse point clouds in the viewing frustum. The algorithm obtains more local feature information of the sparse point clouds in the viewing frustum through dimensional expansion, performs the fusion of local and global feature information of the point cloud data to obtain point cloud data with more complete semantic information, and then applies the obtained data to the 3D object detection task. The experimental results show that the precision of object detection in both 3D view and BEV (Bird’s Eye View) can be improved effectively through the algorithm, especially object detection of moderate and hard levels when the object is severely occluded. In the 3D view, the average precision of the 3D detection of cars, pedestrians, and cyclists at a moderate level can be increased by 7.1p.p., 16.39p.p., and 5.42p.p., respectively; in BEV, the average precision of the 3D detection of car, pedestrians, and cyclists at hard level can be increased by 6.51p.p., 16.57p.p., and 7.18p.p., respectively, thus indicating the effectiveness of the algorithm.© 2022 Xing Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Research on financing ecology and financing efficiency of strategic emerging industries in China

After integrating external ecological and endogenous factors of the development of the industry, the paper builds a financing ecology index system, and analyses the financing ecology of strategic emerging industries in recent years. Then the paper further analyses the influence of external and internal financing ecology on financing efficiency. The results show that the financing ecology of the strategic emerging industries, external financing ecology in particular, is in the continuous improvement. The financing efficiency is significantly positively correlated with the macro-economy level and the internal financing ecology, and significantly negatively correlated with the role of government. There is a positive but non-significant correlation between financial development and financing efficiency, meanwhile a negative and non-significant correlation between credit environment and financing efficiency. The internal and external financing ecology can be replaced to some extent. Therefore, the strategic emerging industries should give full consideration to the synergistic optimization of the endogenous factors and external financing ecology so as to improve the financing efficiency

Desarrollo y validación de una escala PLEs desde la perspectiva del alumno y el aprendizaje en la educación terciaria

The study's goal is to create and validate a Personal Learning Environment Scale (PLEs) from the learner and learning perspective (named PLEsS-LL) to ensure effective learning in Chinese tertiary education. 657 undergraduates participated in the study after completing scale development steps. Six factors were extracted from the PLEsS-LL using Exploratory Factor Analysis (EFA). Confirmatory Factor Analysis (CFA) supported the six-factor scale with 22 items. Furthermore, the PLEsS-LL was redesigned as a questionnaire to assess learners' readiness for PLE learning. The findings indicated that participants were comfortable learning in PLEs in general. They were mostly positive in terms of learning motivation and problem-solving abilities. They did, however, report less confidence in self-directed learning. Meanwhile, male participants outperformed female participants in all categories except learning motivation. The reasons were explained, and suggestions for future PLE design were made. The PLEsS-LL could be used as a resource or guide for learner preparation in the PLE context in higher education around the world.El objetivo del estudio es crear y validar una Escala de Entornos Personales de Aprendizaje (PLEsS) desde la perspectiva del alumno y el aprendizaje (llamada PLEsS-LL) para garantizar un aprendizaje efectivo en la educación terciaria china. 657 estudiantes universitarios participaron en el estudio después de completar los pasos de desarrollo de escala. Se extrajeron seis factores del PLEsS-LL mediante Análisis Factorial Exploratorio (EFA). El Análisis Factorial Confirmatorio (AFC) apoyó la escala de seis factores con 22 ítems.  Además, el PLEsS-LL fue rediseñado como un cuestionario para evaluar la preparación de los alumnos para el aprendizaje PLE. Los hallazgos indicaron que los participantes se sentían cómodos al aprender en PLE en general. En su mayoría fueron positivos en términos de motivación de aprendizaje y habilidades para resolver problemas. Sin embargo, informaron menos confianza en el aprendizaje autodirigido. Mientras tanto, los participantes masculinos superaron a las participantes femeninas en todas las categorías, excepto en la motivación de aprendizaje. Se explicaron las razones y se hicieron sugerencias para el diseño futuro de PLE. El PLEsS-LL podría utilizarse como un recurso o guía para la preparación del alumno en el contexto de los PLEs en la educación superior de todo el mundo

Theoretical and Experimental Analysis of Auctions with Negative Externalities

We investigate a private value auction in which a single "entrant" on winning imposes a negative externality on two "regular" bidders. In an English auction, when all bidders are active "regulars" free ride, exiting before price reaches their value. In a first-price sealed-bid auction incentives for free riding and aggressive bidding coexist, limiting free riding. We find substantial, though incomplete, free riding in the clock auction. In first-price auctions, regular bidders bid more aggressively than the "entrant" and both bid higher than in auctions with no externality. Predictions regarding revenue, efficiency, and successful entry between the two auctions are satisfied

Theoretical and Experimental Analysis of Auctions with Negative Externalities

We investigate a private value auction in which a single "entrant" on winning imposes a negative externality on two "regular" bidders. In an English auction, when all bidders are active "regulars" free ride, exiting before price reaches their value. In a first-price sealed-bid auction incentives for free riding and aggressive bidding coexist, limiting free riding. We find substantial, though incomplete, free riding in the clock auction. In first-price auctions, regular bidders bid more aggressively than the "entrant" and both bid higher than in auctions with no externality. Predictions regarding revenue, efficiency, and successful entry between the two auctions are satisfied

Study on Wear Resistance of Nickel Cladding Layer with Imitation Shell Convex Strip Structure on the Surface of 7075 Aluminum Alloy Drill Pipe

In this study, a nickel cladding layer with a bionic convex strip structure was applied to the surface of an aluminum alloy drill pipe, and laser cladding technology was used to improve the wear resistance of the aluminum alloy drill pipe. Firstly, by observing the morphological characteristics of the shell surface, the ratio of the width of the convex strips to the spacing between the convex strips was obtained as 0.39–0.53, and thus a model of the bionic structure was constructed. Numerical simulations were performed, and the results showed that the wear of the bionic structure was reduced by 77.6% compared with that of the smooth structure. Subsequently, the cladding layers of both structures were coated on the drill pipe using nickel powder as the material, and wear tests were performed. The microstructure, composition, and hardness behavior of the cladding layers were analyzed using scanning electron microscopy, an X-ray diffractometer, and a microhardness tester. It was found that the cladding layer mainly consists of Al3Ni2, and there is a transition layer between the cladding layer and the aluminum alloy matrix, whose hardness is lower than that of Al3Ni2. In addition, the groove space can be formed between the convex strips, which effectively reduces the frequency of the debris flow. The results of the wear tests show that the wear of the cladding layer with the bionic structure is reduced by 74.0%. Similar results in numerical simulations and experiments verified that the designed cladding layer with a bionic convex strip structure can significantly improve the wear resistance of aluminum alloy drill pipes.© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Anti-CRISPR-mediated control of gene editing and synthetic circuits in eukaryotic cells.

Repurposed CRISPR-Cas molecules provide a useful tool set for broad applications of genomic editing and regulation of gene expression in prokaryotes and eukaryotes. Recent discovery of phage-derived proteins, anti-CRISPRs, which serve to abrogate natural CRISPR anti-phage activity, potentially expands the ability to build synthetic CRISPR-mediated circuits. Here, we characterize a panel of anti-CRISPR molecules for expanded applications to counteract CRISPR-mediated gene activation and repression of reporter and endogenous genes in various cell types. We demonstrate that cells pre-engineered with anti-CRISPR molecules become resistant to gene editing, thus providing a means to generate "write-protected" cells that prevent future gene editing. We further show that anti-CRISPRs can be used to control CRISPR-based gene regulation circuits, including implementation of a pulse generator circuit in mammalian cells. Our work suggests that anti-CRISPR proteins should serve as widely applicable tools for synthetic systems regulating the behavior of eukaryotic cells