Sniffing Threat and Practices in IPv6 Networks

The IPv4 protocol suite is vulnerable to a variety of attacks. IPv6 security is in many ways the same as IPv4 security, the basic mechanisms for transporting packets across the network stay mostly unchanged, and the upper-layer protocols that transport the actual application data are mostly unaffected. This paper illustrates sniffing threat against IPv4 and then compares how the threat might influence an IPv6 networks. This is prefaced by a brief overview of current practices around the design of an IPv4 Internet edge network and then followed by a review of how that IPv4 edge network needs to evolve in order to secure the addition of IPv6. As IPv6 security is a large and complex subject, and also, IPv6 network is still at the very beginning stage and has not been fully examined in fact, this paper focus on the security requirements of medium edge networks.

The Nexus between Social Networks and Sexual Practices among Female University Students

The study was conducted among college students in Addis Ababa University, Ethiopia. The objective of the study was to understand whether social networks influence students to make decisions on sexual practices. A total of 130 female students between 18-24 years participated in the study. Among them, 122 participated in the survey and eight in the case studies. The study revealed female students joined various types of social networks, which influence the decision making processes and outcomes of their sexual practices. The study has implications for women empowerment activities.

A Practical Quantum Network Coding Protocol Based on Non-Maximally Entangled State

In many earlier works,perfect quantum state transmission over the butterfly network can be achieved via quantum network coding protocols with the assist of maximally entangled states.However,in actual quantum networks,a maximally entangled state as auxiliary resource is hard to be obtained or easily turned into a non-maximally entangled state subject to all kinds of environmental noises.Therefore,we propose a more practical quantum network coding scheme with the assist of non-maximally entangled states.In this paper,a practical quantum network coding protocol over grail network is proposed,in which the non-maximally entangled resource is assisted and even the desired quantum state can be perfectly transmitted.The achievable rate region,security and practicability of the proposed protocol are discussed and analyzed.This practical quantum network coding protocol proposed over the grail network can be regarded as a useful attempt to help move the theory of quantum network coding towards practicability.

Evolution Handoff Strategy for Real-Time Video Transmission over Practical Cognitive Radio Networks

The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.

Research on the credit classification of practicing qualification personnel in construction market based on self-organizing neural network

Combining with the characters of the practicing qualification personnel in construction market,evaluation method based on the self-organizing neural network is brought out to analyze the credit classification of the practicing qualification personnel. And the impact factors on the credit classification of the practicing qualification personnel,such as the number of neurons,the training steps,the dimension of neurons and the field of winning neurons are studied. Then a self-organizing competitive neural network is built. At last,a case study is conducted by taking practicing qualification personnel as an example. The research result reveals that the method can efficiently evaluate the credit of the practicing qualification personnel;thus,it could provide scientific advice to the construction enterprise to prevent relevant discreditable behaviors of some practicing qualification personnel.

Statewide GNSS-RTN Systems: Current Practices

The applications of geospatial technologies and positioning data embrace every sphere of modern-day science and industry. With technological advancement, the demands for highly accurate positioning services in real-time led to the development of the Global Navigation Satellite System—Real-Time Network (GNSS-RTN). While there is numerous published information on the technical aspects of the GNSS-RTN technology, information on the best practices or guidelines in building, operating, and managing the GNSS-RTN networks is lacking in practice. To better understand the current practice in establishing and operating the GNSS-RTN systems, an online questionnaire survey was sent to the GNSS-RTN system owners/operators across the U.S. Additionally, a thorough review of available literature on business models and interviews with representatives of two major manufacturers/vendors of GNSS-RTN products and services were conducted. Study results revealed a great deal of inconsistency in current practices among states in the way the GNSS-RTN systems are built, operated, and managed. Aspects of the diversity in state practices involved the business models for the GNSS-RTN systems besides the technical attributes of the network and system products. The information gathered in this study is important in helping state agencies make informed decisions as they build, expand or manage their own GNSS-RTN systems.

Research on the Influences of the Invisible Environment of Language Laboratories on the Practical Teaching Based on the Network

There is a close relationship between the environmental factors and the human learning.The language laboratory is an important place for the foreign language learning.Building a good learning and practice environment of language laboratories plays an important role in the foreign language teaching.Learning can never take place in a vacuum.It always takes place in a variety of environments.Some of these environments may be more conducive to the development of the cognitive,emotional and social skills than others.

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char:A statistical neural network approach

The goals of this study are to assess the viability of waste tire-derived char(WTDC)as a sustainable,low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network(SCNN)model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC.The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures(WTDC-MAM).The input variables comprised waste tire char content and asphalt binder content.The output variables comprised mixture unit weight,total voids,voids filled with asphalt,Marshall stability,and flow.Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures.For predictive modeling,the SCNN model is employed,incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability.The optimal network architecture,using the collected dataset,was a 2:6:5 structure,and the neural network was trained with 60%of the data,whereas the other 20%was used for cross-validation and testing respectively.The network employed a hyperbolic tangent(tanh)activation function and a feed-forward backpropagation.According to the results,the network model could accurately predict the volumetric and Marshall properties.The predicted accuracy of SCNN was found to be as high value>98%and low prediction errors for both volumetric and Marshall properties.This study demonstrates WTDC's potential as a low-cost,sustainable aggregate replacement.The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

Research on Risk Prevention and Resolution Strategies of College Network Ideology in the Context of the Internet

With the rapid development of the Internet,the network ideology of colleges and universities is facing severe challenges.This paper deeply analyzes the root of the risk of network ideology and makes a specific investigation of the status quo of network public opinion in colleges and universities.On this basis,the study explores and puts forward a series of targeted risk prevention and resolution strategies,aiming at providing a systematic solution for the network ideology security of colleges and universities.In this paper,with the combination of theory and practice as the path,we verify the effectiveness and applicability of the proposed strategy through the analysis of the implementation effect of the strategy.This study also provides theoretical support and practical guidance for the prevention and control of ideological risks and public opinion guidance in universities under the network environment,which has important practical significance.With the continuous progress of network technology,the threats to the network ideology of colleges and universities are increasing.For example,the spread of false information has become a serious problem affecting the security of college network ideology.

思政教育融入诊断学线上实践教学的探索

诊断学是打开临床医学的一把钥匙,学习该课程是医学生培养医者仁心的重要环节,其线上实践教学存在挑战性。使诊断学教学与课程思政同向同行,形成协同效应,亦是其教学的重点与难点。文章从诊断学实践教学的特点出发,从思政与课程融合教学特色、思政教育融入诊断学实践教学的具体实施等方面进行阐述,期许为思政教育融入诊断学实践教学提供思路。

Back propagation artificial neural network for community Alzheimer's disease screening in China

AIzheimer＇s disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measured in blood samples using an atomic absorption method, and neurotransmitters were measured using a radioimmunoassay method. SPSS 13.0 was used to establish a database, and a back propagation artificial neural network for Alzheimer＇s disease prediction was simulated using Clementine 12.0 software. With scores of activities of daily living, creatinine, 5-hydroxytryptamine, age, dopamine and aluminum as input variables, the results revealed that the area under the curve in our back propagation artificial neural network was 0.929 （95% confidence interval： 0.868-0.968）, sensitivity was 90.00%, specificity was 95.00%, and accuracy was 92.50%. The findings indicated that the results of back propagation artificial neural network established based on the above six variables were satisfactory for screening and diagnosis of Alzheimer＇s disease in patients selected from the community.

Intelligent Reflecting Surfaces Enabled Cognitive Internet of Things Based on Practical Pathloss Model

In this paper,we aim to unlock the potential of intelligent reflecting surfaces(IRSs)in cognitive internet of things(loT).Considering that the secondary IoT devices send messages to the secondary access point(SAP)by sharing the spectrum with the primary network,the interference is introduced by the IoT devices to the primary access point(PAP)which profits from the IoT devices by pricing the interference power charged by them.A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers,but each reflected signal can be aligned with its own desired direction.Moreover,two transmission policies of the secondary network are investigated without/with a successive interference cancellation(SIC)technique.The signal-to-interference plus noise ratio(SINR)balancing is considered to overcome the nearfar effect of the IoT devices so as to allocate the resource fairly among them.We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks.For the proposed game,the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing.Numerical results are demonstrated to validate the performance of the theoretical derivations.

Experimental Point-to-Multipoint Plug-and-Play Measurement-Device-Independent Quantum Key Distribution Network

Measurement-device-independent quantum key distribution(MDI-QKD) offers a practical way to realize a startype quantum network. Previous experiments on MDI-QKD networks can only support the point-to-point communication. We experimentally demonstrate a plug-and-play MDI-QKD network which can support the pointto-multipoint communication among three users. Benefiting from the plug-and-play MDI-QKD architecture,the whole network is automatically stabilized in spectrum, polarization, arrival time, and phase reference. The users only need the encoding devices, which means that the hardware requirements are greatly reduced. Our experiment shows that it is feasible to establish a point-to-multipoint MDI-QKD network.

On the model-based networked control for singularly perturbed systems

In this paper, the control of a two-time-scale plant, where the sensor is connected to a linear controller/ actuator via a network is addressed. The slow and fast systems of singularly perturbed systems are used to produce an estimate of the plant state behavior between transmission times, by which one can reduce the usage of the network. The approximate solutions of the whole systems are derived and it is shown that the whole systems via the network control are generally asymptotically stable as long as their slow and fast systems are both stable. These results are also extended to the case of network delay.

Calculation of the Behavior Utility of a Network System： Conception and Principle

The service and application of a network is a behavioral process that is oriented toward its operations and tasks, whose metrics and evaluation are still somewhat of a rough comparison, This paper describes sce- nes of network behavior as differential manifolds, Using the homeomorphic transformation of smooth differential manifolds, we provide a mathematical definition of network behavior and propose a mathe- matical description of the network behavior path and behavior utility, Based on the principle of differen- tial geometry, this paper puts forward the function of network behavior and a calculation method to determine behavior utility, and establishes the calculation principle of network behavior utility, We also provide a calculation framework for assessment of the network＇s attack-defense confrontation on the strength of behavior utility, Therefore, this paper establishes a mathematical foundation for the objective measurement and precise evaluation of network behavior,

AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice

This comparative review explores the dynamic and evolving landscape of artificial intelligence(AI)-powered innovations within high-tech research and development(R&D).It delves into both theoreticalmodels and practical applications across a broad range of industries,including biotechnology,automotive,aerospace,and telecom-munications.By examining critical advancements in AI algorithms,machine learning,deep learning models,simulations,and predictive analytics,the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies.The review integrates both qualitative and quantitative data derived from academic studies,industry reports,and real-world case studies to showcase the tangible impacts of AI on product innovation,process optimization,and strategic decision-making.Notably,it discusses the challenges of integrating AI within complex industrial systems,such as ethical concerns,technical limitations,and the need for regulatory oversight.The findings reveal a mixed landscape where AI has significantly accelerated R&D processes,reduced costs,and enabled more precise simulations and predictions,but also highlighted gaps in knowledge transfer,skills adaptation,and cross-industry standardization.By bridging the gap between AI theory and practice,the review offers insights into the effectiveness,successes,and obstacles faced by organizations as they implement AI-driven solutions.Concluding with a forward-looking perspective,the review identifies emerging trends,future challenges,and promising opportunities inAI-poweredR&D,such as the rise of autonomous systems,AI-driven drug discovery,and sustainable energy solutions.It offers a holistic understanding of how AI is shaping the future of technological innovation and provides actionable insights for researchers,engineers,and policymakers involved in high-tech Research and Development(R&D).

Reflection on the construction of the information sharing platform and the network open experiment

The construction of the computer network experimental platform can effectively solve the existing problems in the computer network teaching, and has the vital significance for promoting the quality education, and improving the students＇ practical skills. This article mainly discusses the construction of the open experimental platform of the computer network laboratory of the Shandong University, mainly introduces the software and hardware resources of the open experimental platform, and the teaching contents and teaching methods of the open experiment, and sums up the teaching effect of the open experimental platform.

Effectiveness Analysis of Flipped Classroom on Business English Teaching under Multimedia Network Environment

In the era of rapid technological development, business English teaching methods are in the development and changes and multimedia network technology gradually appeared. It has brought great convenience to business English teaching.This paper starts from the feasibility and necessity of multimedia network teaching in Business English to discuss the advantages of multimedia network Teaching Business English. Finally, it is to put forward multimedia network teaching mode, to provide practical recommendations for the majority of business English teacher during the multimedia network teaching.

Capacity Analysis for Dynamic Space Networks

To evaluate transmission rate of highly dynamic space networks,a new method for studying space network capacity is proposed in this paper. Using graph theory,network capacity is defined as the maximum amount of flows ground stations can receive per unit time. Combined with a hybrid constellation model,network capacity is calculated and further analyzed for practical cases. Simulation results show that network capacity will increase to different extents as link capacity,minimum ground elevation constraint and satellite onboard processing capability change. Considering the efficiency and reliability of communication networks,how to scientifically design satellite networks is also discussed.