Over the years, injection vulnerabilities have been at top of Open Web Application Security Project Top 10 and are one most damaging widely exploited types against web applications. Structured Query Language (SQL) attack detection remains a challenging problem due to heterogeneity loads, diversity methods, variety patterns. It has demonstrated that no single model can guarantee adequate security protect applications, it is crucial develop an efficient accurate for SQL detection. In this...

Adaptively modeling the target birth intensity while maintaining filtering efficiency is a challenging issue in multi-target tracking (MTT). Generally, probability predefined as constant and only density considered existing adaptive models, resulting deteriorated accuracy, especially appearing cases. In addition, models also give rise to decline operation on account of extra calculations. To properly adapt real variation number newborn targets improve performance, novel fast sequential Monte...

Ship detection and tracking has been recognized as a challenging task in the maritime administration. The method of LSDT (Light Spot Detection Tracking) applied to achieve ship based on nighttime surveillance video. Firstly, light spots video images are detected through LOG invalid filtered by gray threshold. Multiple targets subsequently tracked Kalman filtering marked determine properties order add delete spots. A case study performed middle reach (Wuhan) Yangtze River. Nighttime obtained...

Compared with the single sensor tracking system, multi-sensor system has several advantages in target tracking, such as a larger field of view and higher accuracy. Different from filters based on random finite set (RFS) theory, product probability hypothesis density (PM-PHD) filter modified cardinality coefficient performs well estimating number targets. Since PM-PHD employs iterative fusion structure, its state estimation is sensitive to parameters. Furthermore, improve estimation, may...

Deep learning-based approaches play important roles and achieve impressive performances in remote sensing image change detection. Most of the networks are designed by researchers with rich experiences. It is difficult to design fixed universal good performance on various datasets. Regarding this issue, study presents a transformer architecture search for The architectures can be automatically two-stage search. first stage effective combinations attention mechanisms, while second identify...

The iterated‐corrector probability hypothesis density (IC‐PHD) filter propagates the posterior intensity of each sensor at one time step to improve tracking accuracy. However, targets cannot be estimated by IC‐PHD filter, if detection last update is low. To deal with this problem, study presents a new multi‐sensor multi‐target method. Analysing iterative process it can observed that measurements obtained sensors divided into several measurement subsets. Then, similarity among described two...

Due to the simplicity of implementation and high threat level, SQL injection attacks are one oldest, most prevalent, destructive types security on Web-based information systems. With continuous development maturity artificial intelligence technology, it has been a general trend use AI technology detect injection. The selection sample set is deciding factor whether algorithms can achieve good results, but dataset with tagged specific category labels difficult obtain. This paper focuses data...

For LCD low‐frequency display products, study the influence of factors such as Ioff, frequency, and capacitance on grayscale Flicker, to meet specification products quality.

With the qualitative analysis method, paper uses three types of generative AI such as ChatGPT, Claude2, and ERNIE Bot to translate chemical text, aiming conclude common errors committed by during E-C translation text provide some countermeasures. The findings show that include five aspects: terminological aspect, lexical syntactic discourse format aspect. Based on these errors, proposes following countermeasures: (1) Translators can obtain accurate terminology utilizing “Method Suspicion,...

Electrical switching of magnetization is central to spintronics. Despite the enormous efforts on spin torques and Dzyaloshinskii-Moriya interaction (DMI) effects, some fundamental physics for electrical still missing as indicated by a number remarkable long-standing puzzles. Here, we report discovery long-range intralayer DMI effect widely existing in magnetic heterostructure, which distinct from yet-known effects it describes chiral coupling two orthogonal domains within same layer via...

The Cardinality Balanced MeMBer (CBMeMBer) filter is a single sensor multi-target tracking method based on the random finite set. Compared with system, multi-sensor system can achieve more stable and better performance in targets. However, some problems exist CBMeMBer filter. Tracks are described by parameter sets which may be generated miss-detection, targets clutters. It difficult to associate correctly because of their complex forms various types. Moreover, reacts slowly disappeared...

Swarm intelligence is one of the most promising area for researchers in field numerical optimization. Monkey algorithm a new swarm intelligent optimization algorithm. The can effectively solve problems linear, nonlinear, nonconvex and complex high dimensional function. Currently, it has been widely studied concerned by many researchers. In order to further improve solution accuracy algorithm, this paper proposes kind improved monkey basic idea proposed that an inducing factor adopted...

Accurate and continuous monitoring of large scale machinery is important for modern industries. Existing solutions are often unsuitable large-scale complex scenarios where a huge number data flows that generated by hundreds heterogeneous sensors should be considered in combination processed simultaneously to finally judge the status machinery. In this paper, we propose multisensing collaborative diagnosis system accurate realtime Our proposed approach tries capture model underlying temporal...

The partly resolvable group tracking is significant for the anti multi-agent system, in which some individual targets of may generate only one measurement, and association relationships between measurements are unknown. To estimate state, target states, variables accurately, this paper proposes a novel algorithm considering resolvability group. Firstly, unified Bayesian framework formulated, including data state estimation. Secondly, variational approach derived using Kalman filter random...

Existing knowledge distillation methods generally use a teacher-student approach, where the student network solely learns from well-trained teacher. However, this approach overlooks inherent differences in learning abilities between teacher and networks, thus causing capacity-gap problem. To address limitation, we propose novel method called SLKD.