Health information technology is a subcategory of health technology that covers medical and healthcare information technology. It allows for the secure exchange of health information among consumers, providers, payers...
详细信息
In this paper the author investigates the following predator-prey model with prey-taxis and rotational?ux terms■in a bounded domain with smooth *** presents the global existence of generalized solutions to the model...
详细信息
In this paper the author investigates the following predator-prey model with prey-taxis and rotational?ux terms■in a bounded domain with smooth *** presents the global existence of generalized solutions to the model■in any dimension.
Edge learning (EL) is an end-to-edge collaborative learning paradigm enabling devices to participate in model training and data analysis, opening countless opportunities for edge intelligence. As a promising EL framew...
详细信息
Generative adversarial networks(GANs) have drawn enormous attention due to their simple yet efective training mechanism and superior image generation quality. With the ability to generate photorealistic high-resolutio...
详细信息
Generative adversarial networks(GANs) have drawn enormous attention due to their simple yet efective training mechanism and superior image generation quality. With the ability to generate photorealistic high-resolution(e.g., 1024 × 1024) images, recent GAN models have greatly narrowed the gaps between the generated images and the real ones. Therefore, many recent studies show emerging interest to take advantage of pre-trained GAN models by exploiting the well-disentangled latent space and the learned GAN priors. In this study, we briefly review recent progress on leveraging pre-trained large-scale GAN models from three aspects, i.e.,(1) the training of large-scale generative adversarial networks,(2) exploring and understanding the pre-trained GAN models, and(3) leveraging these models for subsequent tasks like image restoration and editing.
The diagnosis and recognition of skin conditions, including both benign and malignant forms, have become a significant area of interest in medical imaging. Convolutional Neural Networks (CNNs), a deep learning archite...
详细信息
Nowadays,with the widespread application of the Internet of Things(IoT),mobile devices are renovating our *** data generated by mobile devices has reached a massive *** traditional centralized processing is not suitab...
详细信息
Nowadays,with the widespread application of the Internet of Things(IoT),mobile devices are renovating our *** data generated by mobile devices has reached a massive *** traditional centralized processing is not suitable for processing the data due to limited computing power and transmission *** Edge computing(MEC)has been proposed to solve these *** of limited computation ability and battery capacity,tasks can be executed in the MEC ***,how to schedule those tasks becomes a challenge,and is the main topic of this *** this paper,we design an efficient intelligent algorithm to jointly optimize energy cost and computing resource allocation in *** view of the advantages of deep learning,we propose a Deep Learning-Based Traffic Scheduling Approach(DLTSA).We translate the scheduling problem into a classification *** demonstrates that our DLTSA approach can reduce energy cost and have better performance compared to traditional scheduling algorithms.
Software security poses substantial risks to our society because software has become part of our life. Numerous techniques have been proposed to resolve or mitigate the impact of software security issues. Among them, ...
详细信息
Software security poses substantial risks to our society because software has become part of our life. Numerous techniques have been proposed to resolve or mitigate the impact of software security issues. Among them, software testing and analysis are two of the critical methods, which significantly benefit from the advancements in deep learning technologies. Due to the successful use of deep learning in software security, recently,researchers have explored the potential of using large language models(LLMs) in this area. In this paper, we systematically review the results focusing on LLMs in software security. We analyze the topics of fuzzing, unit test, program repair, bug reproduction, data-driven bug detection, and bug triage. We deconstruct these techniques into several stages and analyze how LLMs can be used in the stages. We also discuss the future directions of using LLMs in software security, including the future directions for the existing use of LLMs and extensions from conventional deep learning research.
Let 1≤q≤∞,b be a slowly varying function and letΦ:[0,∞)■[0,∞)be an increasing convex function withΦ(0)=0 and■Φ(r)=∞.In this paper,we present a new class of Doob’s maximal inequality on Orlicz-Lorentz-Karam...
详细信息
Let 1≤q≤∞,b be a slowly varying function and letΦ:[0,∞)■[0,∞)be an increasing convex function withΦ(0)=0 and■Φ(r)=∞.In this paper,we present a new class of Doob’s maximal inequality on Orlicz-Lorentz-Karamata spaces LΦ,q,*** results are new,even for the Lorentz-Karamata spaces withΦ(t)=tp,the Orlicz-Lorentz spaces with b≡1,and weak Orlicz-Karamata spaces with q=∞in the framework of LΦ,q,b-Moreover,we obtain some even stronger qualitative results that can remove the△2-condition of Liu,Hou and Wang(Sci China Math,2010,53(4):905-916).
Entity linking refers to linking a string in a text to corresponding entities in a knowledge base through candidate entity generation and candidate entity *** is of great significance to some NLP(natural language proc...
详细信息
Entity linking refers to linking a string in a text to corresponding entities in a knowledge base through candidate entity generation and candidate entity *** is of great significance to some NLP(natural language processing)tasks,such as question *** English entity linking,Chinese entity linking requires more consideration due to the lack of spacing and capitalization in text sequences and the ambiguity of characters and words,which is more evident in certain *** Chinese domains,such as industry,the generated candidate entities are usually composed of long strings and are heavily *** addition,the meanings of the words that make up industrial entities are sometimes *** semantic space is a subspace of the general word embedding space,and thus each entity word needs to get its exact ***,we propose two schemes to achieve better Chinese entity ***,we implement an ngram based candidate entity generation method to increase the recall rate and reduce the nesting ***,we enhance the corresponding candidate entity ranking mechanism by introducing sense *** the contradiction between the ambiguity of word vectors and the single sense of the industrial domain,we design a sense embedding model based on graph clustering,which adopts an unsupervised approach for word sense induction and learns sense representation in conjunction with *** test the embedding quality of our approach on classical datasets and demonstrate its disambiguation ability in general *** confirm that our method can better learn candidate entities’fundamental laws in the industrial domain and achieve better performance on entity linking through experiments.
Paddy is a major nutritional requirement for the human population. However, diseases such as bacterial leaf blight, brown spot, and leaf smut are significantly impacting the leaves of the paddy at various stages, resu...
详细信息
暂无评论