The need for a personalized user experience brought recommendation systems to the forefront of digital innovation. However, traditional approaches tend to often forget human emotions, which represent a critical driver...
详细信息
In the contemporary world, humanoid robots are likely to play a key role in various fields, including health care, domestic service, hospitality, business, and military and security activities. The robots are employed...
详细信息
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar...
详细信息
Solar flares are one of the strongest outbursts of solar activity,posing a serious threat to Earth’s critical infrastructure,such as communications,navigation,power,and ***,it is essential to accurately predict solar flares in order to ensure the safety of human ***,the research focuses on two directions:first,identifying predictors with more physical information and higher prediction accuracy,and second,building flare prediction models that can effectively handle complex observational *** terms of flare observability and predictability,this paper analyses multiple dimensions of solar flare observability and evaluates the potential of observational parameters in *** flare prediction models,the paper focuses on data-driven models and physical models,with an emphasis on the advantages of deep learning techniques in dealing with complex and high-dimensional *** reviewing existing traditional machine learning,deep learning,and fusion methods,the key roles of these techniques in improving prediction accuracy and efficiency are *** prevailing challenges,this study discusses the main challenges currently faced in solar flare prediction,such as the complexity of flare samples,the multimodality of observational data,and the interpretability of *** conclusion summarizes these findings and proposes future research directions and potential technology advancement.
ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential sec...
详细信息
ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.
Dear Editor,This letter presents a latent-factorization-of-tensors (LFT)-incorporated battery cycle life prediction framework. Data-driven prognosis and health management (PHM) for battery pack (BP) can boost the safe...
详细信息
Dear Editor,This letter presents a latent-factorization-of-tensors (LFT)-incorporated battery cycle life prediction framework. Data-driven prognosis and health management (PHM) for battery pack (BP) can boost the safety and sustainability of a battery management system (BMS),which relies heavily on the quality of the measured BP data like the voltage (V), current (I), and temperature (T).
In this paper, we present a class of codes, referred to as random staircase generator matrix codes (SGMCs), which have staircase-like generator matrices. In the infinite-length region, we prove that the random SGMC is...
详细信息
Breast Cancer Detection introduces a prominent confrontation for researchers and clinical experts as it is one of the major public health issues and is weighed as a leading root for cancer correlated deaths among wome...
详细信息
In recent years,the phenomenon of multistability has attracted wide *** this paper,a memristive chaotic system with extreme multistability is constructed by using a *** dynamic behavior of the system is analyzed by Po...
详细信息
In recent years,the phenomenon of multistability has attracted wide *** this paper,a memristive chaotic system with extreme multistability is constructed by using a *** dynamic behavior of the system is analyzed by Poincar´e mapping,a time series diagram,and a bifurcation *** results show that the new system has several significant ***,the new system has a constant Lyapunov exponent,transient chaos and one complete Feigenbaum ***,the system has the phenomenon of bifurcation map shifts that depend on the initial *** addition,we find periodic bursting oscillations,chaotic bursting oscillations,and the transition of chaotic bursting oscillations to periodic bursting *** particular,when the system parameters take different discrete values,the system generates a bubble phenomenon that varies with the initial conditions,and this bubble can be shifted with the initial values,which has rarely been seen in the previous *** implementation by field-programmable gate array(FPGA)and analog circuit simulation show close alignment with the MATLAB numerical simulation results,validating the system’s ***,the image encryption algorithm integrating DNA-based encoding and chaotic systems further demonstrates its practical applicability.
In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scal...
详细信息
In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scale object detection algorithm based on an improved YOLOv8 has been proposed. Firstly, a lightweight attention mechanism, Triplet Attention, is introduced to enhance the algorithm’s ability to extract multi-dimensional and multi-scale features, thereby improving the receptive capability of the feature maps. Secondly, the Diverse Branch Block (DBB) is integrated into the CSP Bottleneck with two Convolutions (C2F) module to strengthen the fusion of semantic information across different layers. Thirdly, a new decoupled detection head is proposed by redesigning the original network head based on the Diverse Branch Block module to improve detection accuracy and reduce missed and false detections. Finally, the Minimum Point Distance based Intersection-over-Union (MPDIoU) is used to replace the original YOLOv8 Complete Intersection-over-Union (CIoU) to accelerate the network’s training convergence. Comparative experiments and dehazing pre-processing tests were conducted on the RTTS and VOC-Fog datasets. Compared to the baseline YOLOv8 model, the improved algorithm achieved mean Average Precision (mAP) improvements of 4.6% and 3.8%, respectively. After defogging pre-processing, the mAP increased by 5.3% and 4.4%, respectively. The experimental results demonstrate that the improved algorithm exhibits high practicality and effectiveness in foggy traffic scenarios.
As more users seek generative AI models to enhance work efficiency, generative AI and Model-as-a-Service will drive transformative changes and upgrades across all industries. However, when users utilize generative AI ...
详细信息
暂无评论