An anomaly intrusion detection method based on HMM is presented. The system call trace of a UNIX privileged process passed to obtain state transition sequences. Preliminary experiments prove the sequences can express different mode between normal action and behaviour in more stable simple manner.

For agricultural disease image identification, obtained images are typically unclear, which can lead to poor identification results in real production environments. The quality of an has a significant impact on the accuracy pre-trained classifiers. To address this problem, we propose generative adversarial network with dual-attention and topology-fusion mechanisms called DATFGAN. This effectively transform unclear into clear high-resolution images. Additionally, weight sharing scheme our...

Bloom filters have been extensively applied in many network functions. Their performance is judged by three criteria: query overhead, space requirement, and false positive ratio. Due to wide applicability, any improvement the of can potentially a broad impact areas networking research. In this paper, we study Bloom-1, data structure that performs membership check one memory access, which compares favorably with k accesses standard filter. We also generalize Bloom-1 Bloom-g Bloom-Q, allowing...

Due to network operation and maintenance relying heavily on traffic monitoring, matrix analysis has been one of the most crucial issues for management related tasks. However, it is challenging reliably obtain precise measurement in computer networks because high cost, unavoidable transmission loss. Although some methods proposed recent years allowed estimating from partial flow-level or link-level measurements, they often perform poorly estimation nowadays. Despite strong assumptions like...

The increasing demand for efficient last-mile delivery in smart logistics underscores the role of autonomous robots enhancing operational efficiency and reducing costs. Traditional navigation methods, which depend on high-precision maps, are resource-intensive, while learning-based approaches often struggle with generalization real-world scenarios. To address these challenges, this work proposes Openstreetmap-enhanced oPen-air sEmantic Navigation (OPEN) system that combines foundation models...

Abstract Coal and gas outburst is a dynamic phenomenon in underground mining engineering that often accompanied by the throwing breakage of large amounts coal. To study crushing effect its evolution during outbursts, coal samples with different initial particle sizes were evaluated using testing device. Three basic sizes, 5–10 mesh, 10–40 40–80 as well some mixed size used tests. The particles pre-compacted at pressure 4 MPa before vertical ground stress (4 MPa) horizontal (2.4 initially...

The growth of the most significant field crops such as rice, wheat, maize, and soybean are influenced because various pests. And crop production is decreased due to categories insects. Deep learning technologies significantly increased efficiency identifying controlling agricultural pests attack. However, images obtained often obscure unclear sparse density cameras deployed in real farmland. This always makes difficult recognize monitor. Additionally, existing classification segmentation...

This paper addresses the problem of anomaly detection for high-dimensional sensing data. The one-class support vector machine (OCSVM) is one most popular unsupervised methods detection. When data are high dimensional and large scale, however, efficiency OCSVM-based in suffers. Although dimensionality-reduction tools, such as deep belief networks, can be applied to compress alleviate problem, accuracy timely still hard improve due inherent features OCSVM. In this paper, we propose a new form...

Active probing is an effective tool for monitoring networks. By measuring responses, we can perform fault diagnosis actively and efficiently without instrumentation on managed entities. In order to reduce the traffic generated by messages measurement infrastructure costs, optimal set of probes desirable. However, computational complexity obtaining such very high. Existing works assume single-fault scenarios, apply only small size networks, or use simplistic methods that are vulnerable...

Understanding the pattern of end-to-end traffic flows in datacenter networks (DCNs) is essential to many DCN designs and operations (e.g., engineering load balancing). However, little research work has been done obtain information efficiently yet accurately. Researchers often assume availability tracing tools OpenFlow) when their proposals require as input, but these may have high monitoring overhead consume significant switch resources even if they are available a DCN. Although estimating...

Elastic waves have different attenuation laws when propagating in various materials, which is one of the important challenges application non-destructive testing methods, such as acoustic emission (AE) technology geotechnical engineering. The study presented this paper investigated influence mechanism concrete composition materials and parameters on propagation law elastic using specimens produced six particle sizes sand or gravel. burst AE signal was generated through lead-breaking...

The rapid expansion of high-speed railways (HSRs) and the growing demand for diverse data services during long journeys require efficient computing services. Mobile Edge Computing (MEC) emerged as a promising platform to fulfill this demand. We envision scenario wherein passengers interact with each other on same or different trains in real-time by offloading computationally intensive delay-sensitive tasks track-side MEC networks HSRs computation results are multicast receivers. To improve...

Unsupervised anomaly detection for multivariate time series (MTS) is a challenging task due to the difficulties of precisely learning complex data patterns MTS. The recent progress in sample generation achieved by diffusion models (DMs) motivates us leverage powerful ability DMs make breakthrough unsupervised In this paper, we first attempt design novel diffusion-based model (named TimeADDM) MTS using effective mechanism DMs. To enhance effect on data, propose apply steps representations...

Parenting style plays an important role in children’s development. This study examines the influence mechanism of authoritative parenting on individuals’ proactive behavior. We propose a chain mediation model for linkage between and behavior through self-esteem growth mindset. Based survey 388 undergraduate students coastal areas China, we find significant positive impact college students’ In addition, our provides evidence effect relation among style, self-esteem, mindset, Our results...

An origin-destination (OD) flow between two routers is the set of packets that pass both in a network. Measuring sizes OD flows important to many network management applications such as capacity planning, traffic engineering, anomaly detection, and reliability analysis. Measurement efficiency accuracy are main technical challenges. In terms efficiency, we want minimize per-packet processing overhead accommodate future have extremely high packet rates. accuracy, generate precise measurement...