Hot deformation behavior at low-rate strain of 316LN stainless steel

The study on hot deformation behavior of 316LN stainless steel at low-rate strain is very seldom at present. By sam-pling from industrial 316LN stainless steel and carrying out a compression heat deformation test by means of a Gleeble-3800 thermal simulation testing machine at a strain rate of 3×10^-3s^-1 and a deformation temperature of 600 - 1 100℃, true stress- strain curves are obtained. By analyzing the true stress-strain curves and microscopic structure of the samples, it can be conclu-ded that 1 000℃ and slightly higher temperature are suitable for low-rate strain processing of 316LN stainless steel.

云计算环境下Low-Rate DDoS攻击检测模型构建

作为一种新型的分布式拒绝服务Low-Rate(低速率)DDoS,是另一种破坏云服务的分布式拒绝服务攻击方式。DDoS攻击通常具有较高的攻击队列,而LDoS采用较低的攻击率,此外这种攻击是周期性的,具有攻击速率低、隐蔽性强的特点。LDoS攻击流量的行为与正常流量的行为非常类似,很容易避开DDoS攻击检测系统,很难被检测出来。因此,LDDoS攻击可以持续很长时间,从而危及受害者。LDoS攻击在很长一段时间内欺骗性地消耗云资源,导致云计算提供商成本大幅增加。现提出一种基于机器学习的检测方法,它能够有效地检测出云计算环境下的LDDoS攻击流。

Low-Rate DoS Attack Flows Filtering Based on Frequency Spectral Analysis

In frequency domain,the power spectrum of Low-rate denial of service(LDoS) attacks is totally spread into the spectrum of normal traffic.It is a challenging task to detect and filter LDoS attack flows from the normal traffic.Based on the analysis of LDoS attack flows and legitimate TCP traffic in time and frequency domains,the periodicity of the TCP traffic and LDoS attack flows is explored to facilitate the research of network traffic processing.Hence,an approach of LDoS attack flow filtering based on frequency spectrum analysis is proposed.In this approach,the TCP traffic and LDoS attack flows are transformed from the time domain into the frequency domain.Then the round-trip time(RTT) is estimated by using frequency domain search method.Analysis of amplitude spectrum shows that TCP traffic energy is mainly concentrated on the points of n/RTT.Therefore,a comb filter using infinite impulse response(IIR) filter is designed to filter out the LDoS attack flows in frequency domain,while most legitimate TCP traffic energy at the points of n/RTT are pass through.Experimental results show that the maximum pass rate for legitimate TCP traffic reaches 92.55%,while the maximum filtration rate of LDoS attack flows reaches 81.36%.The proposed approach can effectively filter the LDoS attack flows while less impact on the legitimate TCP traffic.

The detection method of low-rate DoS attack based on multi-feature fusion

As a new type of Denial of Service(DoS)attacks,the Low-rate Denial of Service(LDoS)attacks make the traditional method of detecting Distributed Denial of Service Attack(DDoS)attacks useless due to the characteristics of a low average rate and concealment.With features extracted from the network traffic,a new detection approach based on multi-feature fusion is proposed to solve the problem in this paper.An attack feature set containing the Acknowledge character(ACK)sequence number,the packet size,and the queue length is used to classify normal and LDoS attack traffics.Each feature is digitalized and preprocessed to fit the input of the K-Nearest Neighbor(KNN)classifier separately,and to obtain the decision contour matrix.Then a posteriori probability in the matrix is fused,and the fusion decision index D is used as the basis of detecting the LDoS attacks.Experiments proved that the detection rate of the multi-feature fusion algorithm is higher than those of the single-based detection method and other algorithms.

High Robust Broadcasting over DTMB-A with Low-rate LDPC Codes

As the 2nd generation digital terrestrial television broadcasting(DTTB)standard,digital terrestrial/television multimedia broadcasting-advanced(DTMB-A)can provide higher spectrum efficiency and transmission reliability by adopting flexible frame structure and advanced forward error correction coding compared with the 1 st generation DTTB systems.In order to increase the flexibility and robustness of the DTTB network,the frequency reuse scheme of factor one(reuse-1)is proposed,where the same RF channel is used by different stations covering the adjacent service areas.However,it demands a very low carrier-tonoise ratio(C/N)threshold below 0 dB at the DTTB physical layer.In this paper,a robust broadcasting technique is proposed based on DTMB-A with newly designed low-rate low density parity check(LDPC)codes.By adopting quasi-cyclic(QC)Raptor-like structure and progressive lifting method,the high performance low-rate LDPC codes are designed supporting multiple code lengths.Both density-evolution analyses and laboratory measurements demonstrate that DTMB-A with low-rate coding can complete the demodulation reliably with the C/N threshold below0 d B,which is one important necessary condition to support frequency reuse-1 scheme.

具有时滞效应的air2stream河流水温模型及应用研究

高精度河流水温模型对于深入了解水温的时空变化特征和河流生态修复具有重要意义。基于数据驱动的air2stream模型在保证预测精度的同时,避免了计算的复杂性,已成为河流水温模拟常用的模型。由于水的热惯性及水文条件等的影响,河流水温变化往往显著滞后于气温变化,而air2stream原模型并未考虑滞后效应,导致该模型在流量未知情况下实际精度偏低。为解决该问题,采用气温-水温皮尔逊相关系数计算时滞天数,构建具有时滞的air2stream新模型,进一步根据长江中下游地区两个监测站的多年实测数据验证新模型的有效性和稳定性。结果表明:新模型在不引进额外观测数据的条件下具有更高精度且性能更稳定。相比原模型,在两个监测站新模型的均方根误差分别降低约4.29%和5.85%。新模型具有精度高、水文要素需求少的特点,可为长江中下游的水环境影响评价和生态保护提供依据。

Physical Layer Encryption of OFDM-PON Based on Quantum Noise Stream Cipher with Polar Code

Orthogonal frequency division multiplexing passive optical network(OFDM-PON) has superior anti-dispersion property to operate in the C-band of fiber for increased optical power budget. However,the downlink broadcast exposes the physical layer vulnerable to the threat of illegal eavesdropping. Quantum noise stream cipher(QNSC) is a classic physical layer encryption method and well compatible with the OFDM-PON. Meanwhile, it is indispensable to exploit forward error correction(FEC) to control errors in data transmission. However, when QNSC and FEC are jointly coded, the redundant information becomes heavier and thus the code rate of the transmitted signal will be largely reduced. In this work, we propose a physical layer encryption scheme based on polar-code-assisted QNSC. In order to improve the code rate and security of the transmitted signal, we exploit chaotic sequences to yield the redundant bits and utilize the redundant information of the polar code to generate the higher-order encrypted signal in the QNSC scheme with the operation of the interleaver.We experimentally demonstrate the encrypted 16/64-QAM, 16/256-QAM, 16/1024-QAM, 16/4096-QAM QNSC signals transmitted over 30-km standard single mode fiber. For the transmitted 16/4096-QAM QNSC signal, compared with the conventional QNSC method, the proposed method increases the code rate from 0.1 to 0.32 with enhanced security.

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

最新一代Eagle Stream平台服务器的主板工艺技术研究

随着Intel最新一代Eagle Stream平台的推出,该平台服务器将会占据未来的服务器主流市场。本文关于Eagle Stream平台服务器,围绕0.94 mm pitch背钻出双线、正、反面树脂塞孔+POFV和插入损耗需达到Ultra Low Loss要求这三个产品特点,分析了工艺上存在的挑战和难点,并列举介绍了关键工序和管控措施,以及相应的过程数据。

Dynamics of iron and aluminum storages in a subtropical forest headwater stream

The forest headwater streams are important hubs for connecting terrestrial and aquatic ecosystems,with plant litter and sediments as the major carriers for material migrations;however,until now we knew little about the dynamics of trace elements such as iron(Fe)and aluminum(Al)in forest headwater streams.Here,we quantitatively identified the spatiotemporal dynamics of Fe and Al storages in plant litter and sediments and their influencing factors in a subtropical forest headwater stream,and assessed the potential pollution risk.The results showed that:(1)the mean concentrations of Fe and Al in plant litter(sediments)were 5.48 and 8.46(7.39 and 47.47)g·kg^(-1),and the mean storages of Fe and Al in plant litter(sediments)were 0.26 and 0.43(749.04 and 5030.90)g·m^(-2),respectively;(2)the storages of Fe and Al in plant litter and sediments significantly fluctuated from January to December,and showed a decreasing pattern from the source to mouth;and(3)storages of Fe and Al had no significant correlation with riparian forest type and the present of tributary and the Fe and Al storages in plant litter were mainly affected by water temperature and water alkalinity,and their storages in sediments were mainly affected by water temperature and frequency of rainfall;and(4)there were no anthropogenic pollution in Fe and Al in the forest headwater stream.Our study revealed the primary factors of concentrations and storages of Fe and Al in plant litter and sediments in a forest headwater stream,which will improve our understanding of the role of headwater streams in forest nutrient storage and cycling along with hydrological processes.

An Improved Framework of Massive Superpoly Recovery in Cube Attacks Against NFSR-Based Stream Ciphers

A critical problem in the cube attack is how to recover superpolies efficiently.As the targeting number of rounds of an iterative stream cipher increases,the scale of its superpolies becomes larger and larger.Recently,to recover massive superpolies,the nested monomial prediction technique,the algorithm based on the divide-and-conquer strategy,and stretching cube attacks were proposed,which have been used to recover a superpoly with over ten million monomials for the NFSR-based stream ciphers such as Trivium and Grain-128AEAD.Nevertheless,when these methods are used to recover superpolies,many invalid calculations are performed,which makes recovering superpolies more difficult.This study finds an interesting observation that can be used to improve the above methods.Based on the observation,a new method is proposed to avoid a part of invalid calculations during the process of recovering superpolies.Then,the new method is applied to the nested monomial prediction technique and an improved superpoly recovery framework is presented.To verify the effectiveness of the proposed scheme,the improved framework is applied to 844-and 846-round Trivium and the exact ANFs of the superpolies is obtained with over one hundred million monomials,showing the improved superpoly recovery technique is powerful.Besides,extensive experiments on other scaled-down variants of NFSR-based stream ciphers show that the proposed scheme indeed could be more efficient on the superpoly recovery against NFSR-based stream ciphers.

Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach

Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.

The viscous strip approach to simplify the calculation of the surface acoustic wave generated streaming

In recent decades,the importance of surface acoustic waves,as a biocompatible tool to integrate with microfluidics,has been proven in various medical and biological applications.The numerical modeling of acoustic streaming caused by surface acoustic waves in microchannels requires the effect of viscosity to be considered in the equations which complicates the solution.In this paper,it is shown that the major contribution of viscosity and the horizontal component of actuation is concentrated in a narrow region alongside the actuation boundary.Since the inviscid equations are considerably easier to solve,a division into the viscous and inviscid domains would alleviate the computational load significantly.The particles'traces calculated by this approximation are excellently alongside their counterparts from the completely viscous model.It is also shown that the optimum thickness for the viscous strip is about 9-fold the acoustic boundary layer thickness for various flow patterns and amplitudes of actuation.

Macroinvertebrate Community in Streams on the Canary Islands: Gradient Analysis and Stressors

This study describes the gradient analysis of the freshwater macroinvertebrate assemblages in eight streams of Tenerife and La Gomera (Canary Islands) over a 16-year period. During this period, a total of 75 taxa belonging to 34 taxonomic families were found. Endemism has an important presence in the streams on both islands, especially regarding Trichoptera and Coleoptera. The overall status of freshwater macroinvertebrates is rather uncertain as recent data on these communities are scarce and focused on a limited number of sites. Overexploitation of aquifers and the diversion of natural water flows for irrigation have resulted in the drying up of numerous natural streams, inevitably endangering the fauna that inhabits them. A reduction in number and abundance of endemic and sensitive species was observed in the majority of the sampled streams resulting in a lower ecological rating. Therefore, it is proposed that the protection of streams of high conservation value is essential to conserve freshwater macroinvertebrate fauna native to the Canary Islands.

An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in Streaming Data

Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDC)model.The aim of the OSODLSDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed OS-ODLSDC model initially undergoes preprocessing step.Since streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling process.Besides,the OS-ODLSDC model employs bidirectional long short-term memory(Bi LSTM)for AD and classification.Finally,the root means square propagation(RMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM model.For ensuring the promising performance of the OS-ODLSDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.

Features of sampling stream sediments of large river valleys under cryolithogenesis conditions in the Balygychan-Sugoy trough,North-East of Russia

Comprehensive research has been implemented to raise the efficiency of the geochemical survey of stream sediments(SSs)that formed under the cryolithogenesis conditions.The authors analysed the composition,structure and specific features of the formation of exogenous anomalous geochemical fields(AGFs)identified through SSs of large river valleys of IV order.In our case,these were the valleys of Maly Ken,Ken and Tap Rivers.These rivers are located in the central and southern parts of the Balygychan-Sugoy trough enclosed in the Magadan region,North-East of Russia.The authors proposed a new technique to sample loose alluvium of SSs in the large river valleys along the profiles.The profiles were located across the valleys.The AGFs of Au,Ag,Pb,Zn,Sn,Bi,Mo and W were studied.Correlations between elements have been established.These elements are the main indicator elements of Au-Ag,Ag-Pb,Sn-Ag,Mo-W and Sn-W mineralization occurring on the sites under study.The results obtained were compared with the results of geochemical surveys of SSs.It is concluded that the AGFs recognized along the profiles reflect the composition and structure of eroded and drained ore zones,uncover completely and precisely the pattern of element distribution in loose sediments of large water flows.The alluvium fraction<0.25 mm seems to be most significant in a practical sense,as it concentrated numerous ore elements.Sampling of this fraction in the river valleys of IV order does not cause any difficulty,for this kind of material is plentiful.The developed technique of alluvium sampling within large river valleys is efficient in searching for diverse mineralization at all stages of prognostic prospecting.It is applicable for geochemical survey of SSs performed at different scales both in the North-East of Russia,as well as other regions with similar climatic conditions,where the SSs are formed under the cryolithogenesis conditions.

Rosgen stream classification and fluvial processes of the Shiyang River,China

The Shiyang River is an important ecological pillar in northwest China,sustaining Minqin oasis and its surrounding society.However,the basin has long been plagued by water scarcity and ecological fragility.Although the river classification is critical for understanding the complexity,diversity,and ecological functions of rivers,and the foundation of river management and watershed ecological restoration,it has not received adequate attention in this region.To obtain a deeper and comprehensive understanding of the Shiyang River,this study utilizes the Rosgen stream classification system to assess the river morphology,geomorphic features,and hydrologic processes.The results showed that seven first-level and fourteen second-level river types can be identified along 53 river sections of the Shiyang River.Further comparison analysis on the hydrologic parameters for each river type demonstrated a strong positive correlation between discharge and all river parameters.As discharge increased,channels with moderate to high width/depth ratios experienced significant lateral adjustments.A consistent channel gradient,coupled with higher discharge,facilitated the transition from single to multiple channels.Braiding tendencies were more pronounced in rivers where riverbeds were wider and shallower with higher stream power.Additionally,water-flow shear stress decreased with the increase in the width/depth ratio.This study offered critical insights into the Shiyang River’s forms and processes and for the river management and ecological restoration practices.

基于STREAM教育理念的初中物理实验拓展的内涵和价值研究

基于初中物理实验教学现状,结合初中物理实验教学对STREAM教育进行本土化解读,探索基于STREAM教育理念的初中物理实验拓展的内涵和价值。

Research on Current Situation and Legal Regulation of Cosmetics Live Streaming E-commerce in China

Analyze the compatibility between cosmetics and live streaming e-commerce from its own nature,marketing means and supply chain characteristics.According to the prominent problems,sort out the relationship between all parties in the cosmetics live e-commerce industry chain.Combined with the latest regulatory policies of live streaming e-commerce and cosmetics,the responsibilities of different subjects in cosmetics live streaming e-commerce are summarized,and relevant suggestions and countermeasures are put forward for the standardization and development of live streaming e-commerce.Cosmetics brand owners are the first responsible persons for product quality.Anchors,as a mixed identity between intermediary,advertising spokesperson and operator,should bear stricter joint and several liability when recommending products related to consumers’health.If anchors fail to clearly identify themselves in the recommendation process,thus causing consumers to mistake them for the operator of the cosmetics,they should assume the obligations of the operator.

Significance of Live Streaming in Shaping Business: A Critical Review and Analytical Study

With the rise of live streaming on social media, platforms like Facebook, Instagram, and YouTube have become powerful business tools. They enable users to share live videos, fostering direct connections between businesses and their customers. This critical literature review paper explores the impact of live streaming on businesses, focusing on its role in attracting and satisfying consumers by promoting products tailored to their needs and wants. It emphasizes live streaming’s crucial role in engaging customers, a key to business growth. The study also provides viable strategies for businesses to leverage live streaming for growth and customer engagement, underscoring its importance in the business landscape.