Innovation and Practice of Teaching Methods in Digital and Adaptive Learning:Taking Communication Engineering Major as an Example

This paper proposes teaching reforms in communication engineering majors,emphasizing the implementation of digital and adaptive teaching methodologies,integrating emerging technologies,breaking free from the constraints of traditional education,and fostering high-caliber talents.The reform measures encompass fundamental data collection,recognition of individual characteristics,recommendation of adaptive learning resources,process-oriented teaching management,adaptive student guidance and early warning systems,personalized evaluation,and the construction of an integrated service platform.These measures,when combined,form a comprehensive system that is expected to enhance teaching quality and efficiency,and facilitate student development.

Research on Innovation and Entrepreneurship Education Reform in Local Colleges and Universities under the Background of Industry-Education Integration

With the continuous development of China’s economy and the continuous upgrading of market demand,the demand for talent in enterprises and industries is increasingly diversified and complex,especially innovation ability has become one of the important standards to measure the quality of talent.At the same time,the difficult employment of college students is still serious,the state has issued a series of policies to encourage college students to actively start their own businesses.In this context,local universities,as an important part of higher education,are facing the critical task of innovation and entrepreneurship education reform.This paper aims to explore the current situation,problems,and reform paths of innovation and entrepreneurship education reform in local universities under the background of the integration of industry and education,in order to improve the training quality of innovative and entrepreneurial talents.

Task-Oriented Semantic Communication with Foundation Models

In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.

Exploring the Cation Regulation Mechanism for Interfacial Water Involved in the Hydrogen Evolution Reaction by In Situ Raman Spectroscopy

Interfacial water molecules are the most important participants in the hydrogen evolution reaction(HER).Hence,understanding the behavior and role that interfacial water plays will ultimately reveal the HER mechanism.Unfortunately,investigating interfacial water is extremely challenging owing to the interference caused by bulk water molecules and complexity of the interfacial environment.Here,the behaviors of interfacial water in different cationic electrolytes on Pd surfaces were investigated by the electrochemistry,in situ core-shell nanostructure enhanced Raman spectroscopy and theoretical simulation techniques.Direct spectral evidence reveals a red shift in the frequency and a decrease in the intensity of interfacial water as the potential is shifted in the positively direction.When comparing the different cation electrolyte systems at a given potential,the frequency of the interfacial water peak increases in the specified order:Li+<Na^(+)<K^(+)<Ca^(2+)<Sr^(2+).The structure of interfacial water was optimized by adjusting the radius,valence,and concentration of cation to form the two-H down structure.This unique interfacial water structure will improve the charge transfer efficiency between the water and electrode further enhancing the HER performance.Therefore,local cation tuning strategies can be used to improve the HER performance by optimizing the interfacial water structure.

Core-shell nanoparticle enhanced Raman spectroscopy in situ probing the composition and evolution of interfacial species on PtCo surfaces

The composition and evolution of interfacial species play a key role during electrocatalytic process.Unveiling the structural evolution and intermediate during catalytic process by in situ characterization can shed new light on the electrocatalytic reaction mechanism and develop highly efficient catalyst.However,directly probing the interfacial species is extremely difficult for most spectroscopic techniques due to complicated interfacial environment and ultra-low surface concentration.Herein,electrochemical core-shell nanoparticle enhanced Raman spectroscopy is utilized to probe the composition and evolution processes of interfacial species on Au@Pt,Au@Co,and Au@PtCo core-shell nanoparticle surfaces.The spectral evidences of interfacial intermediates including hydroxide radical(OH*),superoxide ion(O_(2)^(−)),as well as metal oxide species are directly captured by in situ Raman spectroscopy,which are further confirmed by the both isotopic experiment and density functional theory calculation.These results provide a mechanistic guideline for the rational design of highly efficient electrocatalysts.

Degradation-adaptive neural network for jointly single image dehazing and desnowing

1 Introduction In harsh winter scenes,the captured images often suffer from hazeand snowdegradationssimultaneously,which significantly affect the performance of high-level computer vision tasks.However,most existing dehazing methods[1-4]and desnowing methods[5-7]are specialized to address only one type of weather-related degradation,and they struggle to effectively handle multiple types of degradations.