Artificial intelligence-based human–computer interaction technology applied in consumer behavior analysis and experiential education

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce (E-commerce) has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial intelligence (AI) image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction (HCI) in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network (DNN) is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce

Data Valuation and Detections in Federated Learning

Federated Learning (FL) enables collaborative model training while preserving the privacy of raw data. A challenge in this framework is the fair and efficient valuation of data, which is crucial for incentivizing clients to contribute high-quality data in the FL task. In scenarios involving numerous data clients within FL, it is often the case that only a subset of clients and datasets are pertinent to a specific learning task, while others might have either a negative or negligible impact on the model training process. This paper introduces a novel privacy-preserving method for evaluating client contributions and selecting relevant datasets without a pre-specified training algorithm in an FL task. Our proposed approach FedBary, utilizes Wasserstein distance within the federated context, offering a new solution for data valuation in the FL framework. This method ensures transparent data valuation and efficient computation of the Wasserstein barycenter and reduces the dependence on validation datasets. Through extensive empirical experiments and theoretical analyses, we demonstrate the potential of this data valuation method as a promising avenue for FL research.Comment: Fixed some experimental errors and typo

Cost vs. accuracy: second-order vs. high-order methods for eddy-resolving simulations of turbulent separated flows

We report a comparative study of three numerical solvers for the direct numerical simulation of the flow over a sphere at Re = 3700. A high-order spectral-element code (Nek5000), a general purpose, unstructured finite-volume solver (OpenFOAM) and an in-house Cartesian solver using the immersed-boundary method (IBM) are employed for the analysis; results are compared against previous numerical and experimental data. Numerical results show that Nek5000 and the IBM code operate within a similar computational performance range, in terms of cost-vs-accuracy analysis; on the other hand, OpenFOAM needed a significantly higher number of degrees of freedom (and,overall, a higher cost) to match some of the basic features of the flow. Overall, our results suggest that high-order methods and second-order, energy-conserving approaches based on the IBM may be both viable options for high-fidelity scale-resolving simulations of turbulent flows with separation.Postprint (published version

Asymmetric Flow Control in a Slab Mold through a New Type of Electromagnetic Field Arrangement

This research aims to investigate the control effect of asymmetric flow in a slab mold using a novel magnetic field arrangement: freestanding adjustable combination electromagnetic brake (FAC-EMBr). Three scenarios (submerged entry nozzle moves to the narrow face, wide face of the slab mold, and rotates 10°) were studied using three-dimensional numerical simulation. The results show that the magnetic field generated by the FAC-EMBr system can effectively cover three key zones in mold and that the magnetic flux density in the zone cover by a vertical magnetic pole can be adjusted according to the actual flow condition. The FAC-EMBr can effectively improve the asymmetric flow in a mold and near the narrow surface caused by the asymmetric arrangement of the nozzle and can effectively inhibit the occurrence of the flow deviation phenomenon and stabilize the steel/slag interface fluctuation. At the same time, FAC-EMBr has obvious inhibition effects on the surface velocity and can optimize the asymmetric distribution of the surface velocity and the upper reflux velocity caused by the asymmetric arrangement of the nozzle. This study can provide theoretical evidence for the development and utilization of a new electromagnetic brake technology

Studies on the active SISFCL and its impact on the distance protection of the EHV transmission line

Abstract The active saturated iron-core superconductive fault current limiter (SISFCL) is a good choice to decrease fault current. This paper introduced the principles and impedance characteristic of the active SISFCL. Then, it shows the current-limiting effects of the SISFCL. Besides, the impact of the active SISFCL on the distance protection of the EHV transmission line is evaluated. Based on that, the coordination scheme of the distance protections is proposed. A 500 kV double-circuit transmission system with SISFCLs is simulated by Electro-Magnetic Transients Program including DC (EMTDC). Simulation tests demonstrate the correctness and validity of theoretical analyses

Parallel Implementation of OpenVX Feature Extraction Functions in Programmable Processing Architecture

Aiming at the mass computing and slow speed of serial structure calculation of digital image processing, parallel implementation of underlying feature extraction kernel functions in the latest open source OpenVX specification 1.3 is completed, and the verification is carried out with the self-designed OpenVX programmable parallel processor. In the underlying feature extraction of the image, the basic pixel processing function Color Convert, the local image processing functions Gaussian Filter and Median Filter of OpenVX specification 1.3 are selected for filtering and smoothing. Harris Corners and Canny Edge Detector are selected for feature extraction. By dividing the complex nodes with large amount of computation into several simple nodes, different graph execution models are constructed and mapped on the OpenVX parallel processor to realize image edge detection and feature point extraction respectively. Verilog is used to design the hardware circuit, and the FPGA chip xcvu440-flga-2892-2-e of Xilinx has comprehensively verified that, compared with the serial mapping structure, the parallel acceleration ratio of the selected kernel function on the OpenVX programmable parallel processor can be up to 14.269. Experimental results show that the kernel functions in OpenVX specification 1.3, especially the complex kernel functions, can achieve expected acceleration effect in this parallel processing structure, and the speedup ratio of parallel and serial structures increases linearly

Single Photon Emission from Single Perovskite Nanocrystals of Cesium Lead Bromide

The power conversion efficiency of photovoltaic devices based on semiconductor perovskites has reached ~20% after just several years of research efforts. With concomitant discoveries of other promising applications in lasers, light-emitting diodes and photodetectors, it is natural to anticipate what further excitements these exotic perovskites could bring about. Here we report on the observation of single photon emission from single CsPbBr3 perovskite nanocrystals (NCs) synthesized from a facile colloidal approach. Compared with traditional metal-chalcogenide NCs, these CsPbBr3 NCs exhibit nearly two orders of magnitude increase in their absorption cross sections at similar emission colors. Moreover, the radiative lifetime of CsPbBr3 NCs is greatly shortened at both room and cryogenic temperatures to favor an extremely fast output of single photons. The above findings have not only added a novel member to the perovskite family for the integration into current optoelectronic architectures, but also paved the way towards quantum-light applications of single perovskite NCs in various quantum information processing schemes

Virtual Reality-Integrated Immersion-Based Teaching to English Language Learning Outcome.

Globalization and informatization are reshaping human life and social behaviors. The purpose is to explore the worldwide strategies to cultivate international talents with a global vision. As a global language with the largest population, English, and especially its learning effect, have always been the major concerns of scholars and educators. This work innovatively studies the combination of immersion-based English teaching with virtual reality (VR) technology. Then, based on the experimental design mode, 106 students from a Chinese school were selected for a quasi-experimental study for 16 weeks (3 h a week, and 48 h in total). The collected data were analyzed by computer statistical software, and hypotheses are verified. The results showed that there is a significantly positive correlation between VR and immersion-based language teaching (0.851, p < 0.01). There is a significantly positive correlation between immersion-based language teaching and academic achievement (0.824, p < 0.01), and VR is positively correlated with learning outcome (LO) (0.836, p < 0.01). Compared with other state-of-art research methods, this work modifies the students' oral test through the analysis and comparison with the system database, and the students' learning effect is greatly improved. Finally, some suggestions are put forward according to the research results to provide an experimental reference for English teachers and future linguistics teaching

Parallel Architecture Design for OpenVX Kernel Image Processing Functions

Although the traditional programmable processors are highly flexible, their processing speed and perfor-mance are inferior to the application specific integrated circuit (ASIC). Image processing is often a diverse, intensive and repetitive operation, so the processor must balance speed, performance and flexibility. OpenVX is an open source standard for preprocessing or auxiliary processing of image processing, graph computing and deep learning applications. Aiming at the kernel visual function library of OpenVX 1.3 standard, this paper designs and implements a programmable and extensible OpenVX parallel processor. The architecture adopts an application specific instruction processor (ASIP). After analyzing and comparing the topological characteristics of various interconnection networks, the backbone of the ASIP chooses the hierarchically cross-connected Mesh+ (HCCM+) with outstanding performance, and processing element (PE) is set at network nodes. PE array is constructed to support dynamic configuration, and a parallel processor is designed to realize programmable image processing based on efficient routing and com-munication. The proposed architecture is suitable for data parallel computing and emerging graph computing. The two computing modes can be configured separately or mixed. The kernel visual function and graph computing model are mapped to the parallel processor respectively to verify the two modes and compare the image processing speed under different PE numbers. The results show that OpenVX parallel processor can complete the mapping and linear speedup of kernel functions and high complexity graph calculation model. The average speedup of scheduling 16 PEs to various functions is approximately 15.0375. When implemented on an FPGA board with a 20 nm XCVU440 device, the prototype can run at a frequency of 125 MHz

Підвищення ефективності сепарації пилу у вихрових апаратах із зустрічними закрученими потоками із циліндричною сепараційною камерою (ВАЗЗПЦ) для підприємств хімічних та будівельних матеріалів

Актуальною проблемою, яка постає сьогодні перед вітчизняною промисловістю, є вдосконалення техніки і технології охорони навколишнього середовища в цілому, і, зокрема, зменшення рівня запиленості атмосферного повітря.Вирішення проблеми міститься у процесі сепарації пилу у ВАЗЗПЦ і безперервним вивантаженням уловлюваного пилу стосовно хімічних та будівельних матеріалів