A Review of Artificial Intelligence Applications in Contemporary Computer Network Technologies

Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.

美国国家教育技术计划的政策主题、目标与工具变迁--基于NETP 1996-2024年的文本研究

教育数字化转型是推动未来教育发展与变革的关键。美国通过制定并调整教育技术政策以培养具有技术素养的创新人才提升国家竞争力。文章基于政策文本分析视角,构建了包括政策主题、政策目标与政策内容三个维度的分析框架,运用政策文献量化分析法对美国联邦教育部教育技术规划办公室于1996-2024年发布的7份关于教育技术与教育数字化发展的战略规划性文件进行整体分析,研究结论如下:在政策主题维度,政策主题的针对性与可操作性逐渐增强;政策目标维度,政策目标的内涵与协同性不断丰富与提升;政策工具维度,供给型、环境型和需求型政策工具使用较为均衡,在不同教育技术内容要素中的政策工具使用各有偏好与侧重。美国教育技术政策的变迁动向与行动逻辑为我国数字教育政策发展提供借鉴参考。

Dual carbon goal and agriculture in China:Exploring key factors influencing farmers’behavior in adopting low carbon technologies

Identifying the factors influencing farmers’adoption of low-carbon technologies(FA)and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequestration in China.This study employs a meta-analysis of 122 empirical studies,delves into 23 driving factors affecting FA and addresses the inconsistencies present in the existing literature.We systematically examine the effect size,source of heterogeneity,and time-accumulation effect of the driving factors on FA.We find that significant heterogeneity in the factors influencing FA,except for farming experience,sources of heterogeneity from the survey zone,methodology model,technological attributes,report source,financial support,and the sampling year.Additionally,age,farming experience,and adoption cost negatively correlate with FA.In contrast,educational level,health status,technical training,economic and welfare cognition,land contract,soil quality,terrain,information accessibility,demonstration,government promotion,government regulation,government support,agricultural cooperatives member,peer effect,and agricultural income ratio demonstrate a positive correlation.Especially,demonstration and age show a particularly strong correlation.Finally,the effect of demonstration,age,economic and welfare cognition,farming experience,land contract,soil quality,information accessibility,government promotion,and support,as well as agricultural cooperative membership and peer effects on FA,are generally stable but exhibit varying degrees of attenuation over time.The effect of village cadre,family income,farm scale,gender,health status,technical training,and off-farm work on FA show notable temporal shifts and maintain a weak correlation with FA.This study contributes to shaping China’s current low-carbon agriculture policies across various regions.It encourages policymakers to comprehensively consider the stability of key factors,other potential factors,technological attributes,rural socio-economic context,and their interrelations.

Pelleting and particle size reduction of corn increase net energy and digestibility of fiber,protein,and fat in corn-soybean meal diets fed to group-housed pigs

Background Reduction of the particle size of corn increases energy digestibility and concentrations of digestible and metabolizable energy.Pelleting may also reduce particle size of grain,but it is not known if there are interactions between particle size reduction and pelleting.The objective of this experiment was to test the hypothesis that particle size reduction and pelleting,separately or in combination,increase N balance,apparent total tract digestibility(ATTD)of fiber and fat,and net energy(NE)in corn-soybean meal diets fed to group-housed pigs.Methods Six corn-soybean meal-based diets were used in a 3×2 factorial design with 3 particle sizes of corn(i.e.,700,500,or 300μm)and 2 diet forms(i.e.,meal or pelleted).Pigs were allowed ad libitum access to feed and water.Twenty-four castrated male pigs(initial weight:29.52 kg;standard diviation:1.40)were allotted to the 6 diets using a 6×6 Latin square design with 6 calorimeter chambers(i.e.,4 pigs/chamber)and 6 periods.Oxygen consumption and CO_(2)and CH_(4)productions were measured during fed and fasting states and fecal and urine samples were collected.Results Regardless of particle size of corn,the ATTD of gross energy(GE),N,and acid-hydrolyzed ether extract(AEE),and the concentration of NE were greater(P<0.05)in pelleted diets than in meal diets.Regardless of diet form,the ATTD of GE,N,and AEE,and the concentration of NE were increased(linear;P<0.05)by reducing the particle size of corn,but the increase was greater in meal diets than in pelleted diets(interaction;P<0.05).Conclusions Both pelleting and reduction of corn particle size increased nutrient digestibility and NE,but increases were greater in meal diets than in pelleted diets.

Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

Coupling effect on the thermal hazard assessment of hazardous chemical materials via calorimetric technologies and simulation approaches

The coupling effect of heat absorption and release exists in the thermal decomposition of a few chemical materials.However,the impact of the above coupling on thermal hazard assessment is not considered in the literature studies.In this work,nitroguanidine(NQ)and 1,3,5-trinitro-1,3,5-triazine(RDX)are selected as representative materials to explore the influence of the coupling effect on the thermal hazard assessment of chemical materials.The linear heating experiments of NQ and RDX are carried out by a microcalorimeter and synchronous thermal analyser.The thermal decomposition curves are decoupled by advanced thermokinetics software.The thermal decomposition and kinetic parameters before and after decoupling are calculated.The results of TG experiment show that both NQ and RDX began to lose mass during the endothermic stage.The endothermic melting and exothermic decomposition of NQ and RDX are coupled within this stage.The coupling effect has different degrees of influence on its initial decomposition temperature and safety parameters.Compared with the parameters in the coupling state,the initial decomposition temperature and adiabatic induction period after decoupling decrease.The self-accelerating decomposition temperature increases,and internal thermal runaway time decreases.In the thermal hazard assessment of chemical materials with coupling effects,the calculated parameters after decoupling should be taken as an important safety index。

Attention-Enhanced Voice Portrait Model Using Generative Adversarial Network

Voice portrait technology has explored and established the relationship between speakers’ voices and their facialfeatures, aiming to generate corresponding facial characteristics by providing the voice of an unknown speaker.Due to its powerful advantages in image generation, Generative Adversarial Networks (GANs) have now beenwidely applied across various fields. The existing Voice2Face methods for voice portraits are primarily based onGANs trained on voice-face paired datasets. However, voice portrait models solely constructed on GANs facelimitations in image generation quality and struggle to maintain facial similarity. Additionally, the training processis relatively unstable, thereby affecting the overall generative performance of the model. To overcome the abovechallenges,wepropose a novel deepGenerativeAdversarialNetworkmodel for audio-visual synthesis, namedAVPGAN(Attention-enhanced Voice Portrait Model using Generative Adversarial Network). This model is based ona convolutional attention mechanism and is capable of generating corresponding facial images from the voice ofan unknown speaker. Firstly, to address the issue of training instability, we integrate convolutional neural networkswith deep GANs. In the network architecture, we apply spectral normalization to constrain the variation of thediscriminator, preventing issues such as mode collapse. Secondly, to enhance the model’s ability to extract relevantfeatures between the two modalities, we propose a voice portrait model based on convolutional attention. Thismodel learns the mapping relationship between voice and facial features in a common space from both channeland spatial dimensions independently. Thirdly, to enhance the quality of generated faces, we have incorporated adegradation removal module and utilized pretrained facial GANs as facial priors to repair and enhance the clarityof the generated facial images. Experimental results demonstrate that our AVP-GAN achieved a cosine similarity of0.511, outperforming the performance of our comparison model, and effectively achieved the generation of highqualityfacial images corresponding to a speaker’s voice.

Measuring Pedestrian Stress Response (MPSR) Using Wearable Technologies

Walkability is an essential aspect of urban transportation systems. Properly designed walking paths can enhance transportation safety, encourage pedestrian activity, and improve community quality of life. This, in turn, can help achieve sustainable development goals in urban areas. This pilot study uses wearable technology data to present a new method for measuring pedestrian stress in urban environments and the results were presented as an interactive geographic information system map to support risk-informed decision-making. The approach involves analyzing data from wearable devices using heart rate variability (RMSSD and slope analysis) to identify high-stress locations. This data-driven approach can help urban planners and safety experts identify and address pedestrian stressors, ultimately creating safer, more walkable cities. The study addresses a significant challenge in pedestrian safety by providing insights into factors and locations that trigger stress in pedestrians. During the pilot study, high-stress pedestrian experiences were identified due to issues like pedestrian-scooter interaction on pedestrian paths, pedestrian behavior around high foot traffic areas, and poor visibility at pedestrian crossings due to inadequate lighting.

Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry

Firms are embedded in complex networks,where diverse ideas combine and generate new ideas.Shareholders of firms are of-ten seen as critical external resources that have significant influence on firm innovation.The current literature tends to focus on the rela-tionship between firms and their shareholders,while paying less attention to the connections between firms with the same shareholders.This article identifies two types of network spillover effects,intra-city network effect and inter-city network effect,by visualizing the co-ownership networks in China’s electric vehicle(EV)industry.We find that firms with the same shareholders,which are defined as co-owned EV firms,are more innovative than non-co-owned ones.Furthermore,there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders.While corporate shareholders help exploiting local tacit knowledge,financial institutions are more active in bridging inter-city connections.The conclusion is confirmed at both firm and city levels.This paper theor-izes the firm co-ownership network as a new form of institutional proximity and tested the result empirically.For policy consideration,we have emphasized the importance of building formal or informal inter-firm network,and the government should further enhance the knowledge flow channel by institutional construction.

Exploring Nutritional Compositions,Volatile Compounds,Health Benefits,Emerging Processing Technologies,and Potential Food Products of Glutinous Rice:A Review

Glutinous rice(Oryza sativa var.glutinosa)stands out as one of the most popular rice varieties globally,amidst thousands of rice cultivars.Its increasing popularity is attributed to its rich nutritional compositions and health benefits.This review aims to summarize the nutritional compositions,volatile compounds,and health benefits of glutinous rice.Further,in-depth studies are necessary to explore the utilization of glutinous rice in enhancing processing technologies and developing new food products.Glutinous rice has been shown to possess numerous health benefits,including antioxidant activity,bioactive compounds,anti-cancer properties,anti-inflammatory effects,anti-diabetic potential,and cholesterol-lowering effects.Besides its nutritional compositions,the major volatile compounds identified in glutinous rice could serve as a functional food for human consumption.Emerging processing technologies related to glutinous rice are elaborated to improve the latest developments for incorporating them into various food products.

Combined Insights from Leachate Structure and Microstructure Characteristics for Eating Quality of Convenience Rice Processed by Super-Heated and Pressurized Steam Technologies

Convenience rice has become widely popular due to its easy availability for cooking. This study investigated the starch structure and composition of leachate and the microstructure of reheated convenience rice using novel processing technologies: super-heated steaming(SHS), auto-electric cooking(AEC), and pressurized-steam cooking(PSC). Additionally, the effect of two different target water contents(58% and 63%) was also evaluated. The PSC_63% sample had the highest total solids and amylopectin amount in the leachate. The amylopectin amount in the leachate differed significantly based on the targeted water content. Morphological characterization revealed that the swelling of starch and the coated layer on the surface of rice grains were most pronounced in the PSC_63% sample due to the pressure processing. The textural hardness of the AEC_58% sample was much higher than that of the other samples. The PSC_63% sample had the highest textural adhesiveness value, which can be attributed to the highest amylopectin amount in the leachate. Sensory characterization showed that the PSC_63% sample had the highest glossiness, whiteness, moistness, and overall acceptability. The principal component analysis score plots presented substantial differences in the leachate and textural and sensory characteristics of reheated convenience rice among the different processing technologies.

Metal–Organic Gel Leading to Customized Magnetic‑Coupling Engineering in Carbon Aerogels for Excellent Radar Stealth and Thermal Insulation Performances

Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.

Ad Blockers & Online Privacy: A Comparative Analysis of Privacy Enhancing Technologies (PET)

Online tracking mechanisms employed by internet companies for user profiling and targeted advertising raise major privacy concerns. Despite efforts to defend against these mechanisms, they continue to evolve, rendering many existing defences ineffective. This study performs a large-scale measurement of online tracking mechanisms across a large pool of websites using the OpenWPM (Open Web Privacy Measurement) platform. It systematically evaluates the effectiveness of several ad blockers and underlying Privacy Enhancing Technologies (PET) that are primarily used to mitigate different tracking techniques. By quantifying the strengths and limitations of these tools against modern tracking methods, the findings highlight gaps in existing privacy protections. Actionable recommendations are provided to enhance user privacy defences, guide tool developers and inform policymakers on addressing invasive online tracking practices.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

An Examination of Computer Science and Internet Technologies in Addressing Educational Inequities and Societal Psychological Concerns:A Literature Review from the Perspectives of 5G,Artificial Intelligence,and Augmented/Virtual Reality

This study comprehensively reviews the literature to deeply explore the role of computer science and internet technologies in addressing educational inequality and socio-psychological issues,with a particular focus on applications of 5G,artificial intelligence(AI),and augmented/virtual reality(AR/VR).By analyzing how these technologies are reshaping learning and their potential to ameliorate educational disparities,the study reveals challenges present in ensuring educational equity.The research methodology includes exhaustive reviews of applications of AI and machine learning,the Internet of Things and wearable technologies integration,big data analytics and data mining,and the effects of online platforms and social media on socio-psychological issues.Besides,the study discusses applications of these technologies in educational inequality and socio-psychological problem-solving through the lens of 5G,AI,and AR/VR,while also delineating challenges faced by these emerging technologies and future outlooks.The study finds that while computer science and internet technologies hold promise to bridge academic divides and address socio-psychological problems,the complexity of technology access and infrastructure,lack of digital literacy and skills,and critical ethical and privacy issues can impact widespread adoption and efficacy.Overall,the study provides a novel perspective to understand the potential of computer science and internet technologies in ameliorating educational inequality and socio-psychological issues,while pointing to new directions for future research.It also emphasizes the importance of cooperation among educational institutions,technology vendors,policymakers and researchers,and establishing comprehensive ethical guidelines and regulations to ensure the responsible use of these technologies.

Ensuring Security and Privacy in the Internet of Things: Challenges and Solutions

The Internet of Things (IoT) represents a revolutionary paradigm, enabling a vast array of devices to be ubiquitously interconnected via the Internet, thereby facilitating remote control and management of these devices. This pervasive integration into daily life brings significant convenience but also raises substantial concerns regarding the security of personal data collected and stored online. As the number of connected devices grows, the urgency to address privacy and security issues becomes paramount. IoT systems are particularly susceptible to threats that could compromise consumer privacy and security, affecting their practical deployment. Recent research efforts have focused on enhancing the security of IoT devices, including the exploration of blockchain technologies to mitigate these concerns. This paper aims to elucidate the security and privacy challenges inherent in IoT systems by examining vulnerabilities at each layer of the IoT protocol stack. It identifies key security requirements and reviews existing solutions designed to protect IoT systems from a layered perspective, thereby providing a comprehensive overview of the current landscape of IoT security and highlighting the critical need for robust security measures as the adoption of IoT continues to expand.

Ecological Restoration Technologies of Urban Artificial Landscape Lakes

Aiming at the problems of water pollution and ecological environment degradation in urban artificial landscape lakes,the ecological restoration technologies of artificial landscape lakes at home and abroad were studied to provide some reference for the ecological restoration of urban artificial landscape lakes in China.

Developing Healthcare Infrastructure in Saudi Arabia Using Smart Technologies: Challenges and Opportunities

This study aims to explore the challenges and opportunities associated with developing healthcare infrastructure in Saudi Arabia through the implementation of smart technologies. The healthcare sector in Saudi Arabia is undergoing significant transformation, and the integration of smart technologies has the potential to revolutionize healthcare delivery, improve patient outcomes, and enhance the overall healthcare experience. However, several challenges need to be addressed in order to fully leverage the benefits of smart technologies in healthcare infrastructure development. This research identifies and analyzes these challenges while also highlighting the opportunities that arise from the adoption of smart technologies in the Saudi Arabian healthcare system. The findings contribute to the understanding of the current state of healthcare infrastructure in Saudi Arabia and provide insights into the strategies and policies required to overcome challenges and maximize the benefits of smart technologies in healthcare.

Monitoring Technologies for Marine Carbon Sequestration in Zhanjiang

Marine carbon sequestration is an important component of carbon dioxide capture, utilization and storage(CCUS) technology. It is crucial for achieving carbon peaking and carbon neutralization in China. However, CO_(2) leakage may lead to seabed geological disasters and threaten the safety of marine engineering. Therefore, it is of great significance to study the safety monitoring technology of marine carbon sequestration.Zhanjiang is industrially developed and rich in carbon sources. Owing to the good physical properties and reservoirs and trap characteristics,Zhanjiang has huge storage potential. This paper explores the disaster mechanism associated with CO_(2) leakage in marine carbon sequestration areas. Based on the analysis of the development of Zhanjiang industry and relevant domestic monitoring technologies, several suggestions for safety monitoring of marine carbon sequestration are proposed: application of offshore aquaculture platforms, expansion and application of ocean observation networks, carbon sequestration safety monitoring and sensing system. Intended to build a comprehensive and multi-level safety monitoring system for marine carbon sequestration, the outcome of this study provides assistance for the development of marine carbon sequestration in China's offshore areas.