The power system is confronted with a variety of cybersecurity threats, such as False Data Injection Attacks(FDIA), Denial Service (DoS) attacks, and botnet which pose serious risks to the stable operation grid. Traditional model-based attack detection methods face limitations related parameter selection, computational efficiency, overall model performance, resulting in challenges enhancing effectiveness generalization ability these models. In this paper, we propose an based on Extremely...

The Internet of Things (IoT) has gained significant attention from industry as well academia during the past decade.The main reason behind this interest is capabilities IoT for seamlessly integrating classical networks and networked objects, hence allowing people to create an intelligent environment based on powerful integration. However, how extract useful information data produced by facilitate standard knowledge sharing among different systems are still open issues be addressed. In paper,...

In this paper, we propose a Neural Knowledge DNA (NK-DNA)-based framework that is capable of learning from the car’s daily operations and reusing such learned knowledge in future tasks. The NK-DNA novel representation reasoning approach designed to support discovering, storing, reusing, improving, sharing among machines computing devices. We examine our for drivers’ classification based on their driving behaviors. experimental data are collected via smartphone sensors. initial results...

This article researches on node importance ranking of multiplex network. Existing methods are amost monoplex network using only single relationship. However, in real life a person often has various relationships, so how to rank nodes is more realistic and meaningful. In this article, we propose method based weighted aggregation. Firstly, weight each layer by Analytic Hierarchy Process for existing aggregation either lack weighting process or rely artificial calculation rather than precise...

The hemodynamic balloon model describes the change in coupling from underlying neural activity to observed blood oxygen level dependent (BOLD) response. It plays an increasing important role brain research using magnetic resonance imaging (MRI) techniques. However, changes BOLD signal are sensitive resting volume fraction (i.e., $$V_0$$ ) associated with regional vasculature. In previous studies value was arbitrarily set a physiologically plausible circumvent ill-posedness of inverse...

Malicious web domains represent a serious threat to online users’ privacy and security, causing monetary loss, theft of private information, malware attacks, among others. In recent years, machine learning methods have been widely used as prediction models identify malicious domains. this study, we propose Fuzzy-Weighted Least Squares Support Vector Machine (FW-LS-SVM) model for domain identification. our proposed model, fuzzy-weighted operation is applied each data sample considering the...

The Internet of Things (IoT) has gained significant attention from industry as well academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible building new smart In this paper, we propose novel approach: Neural Knowledge DNA based Smart that enables to extract knowledge experiences, store, evolve, share, reuse such aiming functions. By...

Video summarization can help people retrieve videos quickly. Existing unsupervised video models make insufficient use of frame uniqueness in the self-attention mechanism and have redundancy computation uniqueness. In this paper, we rethink relationship between attentive diversity frames, improve calculation method by masking adjacent information model framework based on a mechanism, simplify concentrated attention with it. addition, propose new loss function called Deviation loss, which uses...

The prediction of emergency event occupies an important position in the network public opinion. In this paper, improved algorithm for based on statistics word frequency is presented, which takes BBS, blog, news sites with commentary function as investigated subjects. experiment shows it can provide useful ideas and exploration analysis opinion early warning mass group incidents.

In Chinese text clustering, short is very different from traditional long text, principally in the low frequency of word. As a result, feature extraction and method for weight calculating not directly suitable clustering. To solve problem clustering drift segments, this paper proposes an through improving based on words co-occurrence. Experiments show can get better performance short-text compared with TF-IDF.

Online learning is the main implementation of distance education and adult education. A pertinence timely online teaching intervention could determine persistence quality learning. However, existing mechanism mainly determined by teachers focus on offline which cannot be compatible with system well. In this paper we propose a model based behavior features. After interveners selection, adaptive measures generated in strategy library executed automated. We emphasis construction combines...

Abstract Intelligent vehicle is a complex system includes at least three parts of information, the vehicles themselves, driving surroundings and drivers which has different formats, properties, collection methods. These differences bring difficulties to communication knowledge sharing among drivers, also create barriers safety research. To address these problems, we propose novel intelligent framework contain all related information with clear hierarchical architecture unified SOEKS...

With the development of deep learning, object detection has achieved rapid in recent years, and is widely used real-life scenarios such as face automatic driving. In field ship navigation safety, it necessary to identify whether some specific items appear wheelhouse help determine there a threat drive safety. These are usually small size require higher efficiency. To address this problem, paper proposes ship-specific item method that improves YOLOv5s algorithm. By introducing convolution...