AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

Age-Driven Joint Sampling and Non-Slot Based Scheduling for Industrial Internet of Things

Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of tech-nology.The aviation industry is a sector that is open to more automation and digi-tal transformation,mainly because of the intense competition and the analysis of a large variety of data.The long duration of operations in current airline processes and some processflows cause customer dissatisfaction and cost increase.In this study,the boarding process,which is one of the operational processes of airline transportation and is open to improvement,was discussed.The classical boarding process has been redesigned using Internet of Things technology a model called Boarding 4.0 was created.With Boarding 4.0,it is aimed to design a process where passengers can take their time before boarding more efficiently.In the study,the sub-processes of the Boarding 4.0 model,other processes that the sub-processes interact with,their activities,and data exchange passenger move-ments during the activities are explained in detail.Compared to the classical boarding process and Boarding 4.0 with the fuzzy ahp technique,it has been shown that boarding 4.0 is more advantageous and passenger movement times can be reduced during boarding.As a result of the evaluation made with the fuzzy ahp,it was determined that boarding 4.0 is more advantageous than the classical boarding process.In addition,when the total time of the sub-activities in the board-ing process is calculated,boarding activities for a passenger take 50 min with the classic boarding process and 20 min with Boarding 4.0.Thus,when Boarding 4.0 is used,the passenger gains 30 min.Furthermore,when the calculation is made concerning the airport’s current capacity,two passengers are hosted with the clas-sical boarding process,whilefive passengers are hosted with Boarding 4.0.This acquisition is significant for airports in terms of efficient use of resources.

Process Tolerant and Power Efficient SRAM Cell for Internet of Things Applications

The use of Internet of Things(IoT)applications become dominant in many systems.Its on-chip data processing and computations are also increasing consistently.The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications.The cache memory designed on Static Random-Access Memory(SRAM)cell with features such as low power,high speed,and process tolerance are highly important for the IoT memory system.Therefore,a process tolerant SRAM cell with low power,improved delay and better stability is presented in this research paper.The proposed cell comprises 11 transistors designed with symmetric approach for write operations and single ended circuit for read operations that exhibits an average dynamic power saving of 43.55%and 47.75%for write and 35.59%and 36.56%for read operations compared to 6 T and 8 T SRAM cells.The cell shows an improved write delay of 26.46%and 37.16%over 6 T and 8T and read delay is lowered by 50.64%and 72.90%against 6 T and 10 T cells.The symmetric design used in core latch to improve the write noise margin(WNM)by 17.78%and 6.67%whereas the single ended separate read circuit improves the Read Static Noise Margin(RSNM)by 1.88x and 0.33x compared to 6 T and 8T cells.The read power delay product and write power delay product are lower by 1.94x,1.39x and 0.17x,2.02x than 6 T and 8 T cells respectively.The lower variability from 5000 samples validates the robustness of the proposed cell.The simulations are carried out in Cadence virtuoso simulator tool with Generic Process Design Kit(GPDK)45 nm technology file in this work.

Technical Regulations on Cleaning Processing of Feeding Millet Seeds in Hebei Province

According to many years of experimental summary, the technical demands, process control, seed test, seed quality and work record （ledger management） of cleaning processing of feeding millet seeds in Hebei Province were studied, and specific measures and technical indicators of the technical regulations were analyzed to provide normalized, standardized, industrial and marketization technical support for the cleaning processing of feeding millet seeds.

Financial innovation and its governance:Cases of two major innovations in the financial sector

The power of financial innovations to affect societies on global and intergenerational levels compels us to ask how we can ensure their responsible emergence in society.This requires an understanding of how innovation occurs and how it is governed in practice.Despite this,there is little research on the process and governance of financial innovation.The few studies conducted in this area have focused on the‘backend’of the innovation process.Therefore,using data from secondary sources,this study investigates how two major financial innovations occurred and were governed,and it discusses the findings in relation to those in the literature.This approach revealed that innovation processes fall within a continuum ranging from structured to unstructured.Moreover,lead times are potentially longer for innovations that are significantly disruptive,new to the market,and technological in nature.Finally,innovation processes can involve multiple stakeholders who use both statutory regulation and self-regulation for innovation governance.This paper concludes that innovation processes and their governance can vary significantly according to different areas of the financial landscape and associated innovation contexts.Thus,there is a need for more empirical work to understand such variability and practices in the sector as a whole.

Design and Simulation of IoT Systems Using the Cisco Packet Tracer

Design and implementation of Internet of Things (IoT) systems require platforms with smart things and components. Two dominant architectural approaches for developing IoT systems are mashup-based and model-based approaches. Mashup approaches use existing services and are mainly suitable for less critical, personalized applications. Web development tools are widely used in mashup approaches. Model-based techniques describe a system on a higher level of abstraction, resulting in very expressive modelling of systems. The article uses Cisco packet tracer 7.2 version, which consists of four subcategories of smart things—home, smart city, industrial and power grid, to design an IoT based control system for a fertilizer manufacturing plant. The packet tracer also consists of boards—microcontrollers (MCU-PT), and single boarded computers (SBC-PT), as well as actuators and sensors. The model facilitates flexible communication opportunities among things—machines, databases, and Human Machine Interfaces (HMIs). Implementation of the IoT system brings finer process control as the operating conditions are monitored online and are broadcasted to all stakeholders in real-time for quicker action on deviations. The model developed focuses on three process plants;steam raising, nitric acid, and ammonium nitrate plants. Key process parameters are saturated steam temperature, fuel flowrates, CO and SOx emissions, converter head temperature, NOx emissions, neutralisation temperature, solution temperature, and evaporator steam pressure. The parameters need to be monitored in order to ensure quality, safety, and efficiency. Through the Cisco packet tracer platform, a use case, physical layout, network layout, IoT layout, configuration, and simulation interface were developed.

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning（CAPP） is an important content of computer integrated manufacturing, and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize, and the same technical aim always can be achieved by different process schemes, so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing （CIM）. For the purpose of intelligent aided process decision making and reuse of process resource, this paper proposed a decision making method based on rough sets（RS） and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment, the concept of process knowledge granule is represented, and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification, the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions, and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise＇s manufacturing resources, so as to realize process resources＇ conflict resolution and quick excavate and reuse of enterprises＇ existing process knowledge, to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

Assembling structurally customizable synthetic carriers of si RNA through thermodynamically self-regulated process

This study demonstrates that our previously reported polywraplex, a synthetic siRNA carrier consisting of a uni-molecular polyplex core of customizable size and a self-assembled triblock copolymer envelop, may be constructed using dendrimers as the crosslinking junctions. Replacing the branched low molecular weight PEI with polyamidoamine(PAMAM) dendrimer in the zeta potential regulated polymerization resulted in the similar network structured cationic polymer with electron microscopically visible crosslinking junctions. This visibility may offer a convenient way to characterize the molecular structure of the rationally designed networked siRNA-packing cationic polymer without altering its chemical properties and biologic functions. A series of physical-chemical characterizations and biological assays, comprising size, zeta potential, pre-phagocytic siRNA leaking and degradation, and silencing of functional genes, confirmed that the advanced properties of polywraplexes remained with the dendrimer junctions. Although sixth generation PAMAM dendrimer was used as the crosslinking junctions in the size-customizable polymerization for electron microscopic observation, lower generation dendrimer should also work in case more practical and structurally defined cationic polymer is needed.

Exploration of Integrated Course Project Mode of the Internet of Things Engineering Based on the Relevance Theory

Based on analysis of the present situation and problems of course project of the Internet of Things engineering,we propose a relational integrated course project pattern around three levels of perception layer,network layer,application layer of the Internet of Things system.The realization of a complete Internet of Things system is divided into three course projects to complete three key points,which may eventually make a complete system of things.Through the link among the three integrated course projects,knowledge of four years will be connected together and form an organic whole.We use a team performance and examination methods of the process-oriented examination,project paper and oral examination for the integrated course project in order to improve students’cooperation ability,expression ability,communication ability and other integrated quality.

The New Plating Process on Plastics

This process does not use general electroless plating solution containing formaldehyde(carcinogen) and phosphate(the object of waste water regulation). Furthermore, we succeeded in developing a new electroless copper plating solution which is usable semi-permanently by using the special reducing agent. The electroless deposition forms a very thin conductive film on substrate. Therefore, it can prevent some appearance defects (e.g. pits, pin-holes, laminations and inclusions) that occur in the conventional ones. In addition, it is possible to eliminate electroplating of copper from the process by applying the exclusive nickel solution in electroplating. Therefore, the obtained metal parts can be recycled as high quality stainless steel. Given this copper electroplating-free process, 25 u m-thick nickel deposition at the stage of electroplating, at least, enables the metal layers to show properties as versatile as those of the conventional(its total thickness is 25 n m in the comparative conventional process).

物联网发展、科技创新与农业碳排放强度

农业生产导致的温室气体排放以及引发的环境问题,已成为人们关注的热点,研究物联网发展对农业碳排放强度的作用机理,有助于农业农村能源转型和促进农业绿色可持续发展。基于2010—2021年我国除港、澳、台外的31个省级地区的面板数据,分析物联网发展对农业碳排放强度的影响,以及科技创新在此过程中的作用。研究发现:物联网发展显著抑制了农业碳排放强度,并且存在显著异质性,在中国东部和中部地区,科技创新水平有效提升了物联网发展对农业碳排放强度的抑制作用。把农业科技创新水平作为门槛变量,发现物联网发展和农业碳排放强度之间存在非线性关系,当农业科技创新水平跨越门槛值后,物联网发展对农业碳排放强度的抑制作用显著增强。研究结论在推动数字化农业、促进科技与农业融合方面具有理论和实践价值。

Anxiety in the Process of Writing M.A. Theses in English Majors

In terms of second language acquisition or learning, research on anxiety has primarily focused on foreign language classroom anxiety or test anxiety, with little attention paid to anxiety in the process of writing academic theses. This study aims to explore to what extent anxiety affects the whole process of three English majors writing their M.A. theses, as well as testing the relationships between anxiety and self-regulation in the whole process. The findings indicate that anxiety appears with high degree atthe preparation stage, slumps at the writing stage and reaches another high level at the revision stage. Anxiety also exists when negotiating with supervisors. What’s more, self-regulation has been proved to alleviate anxiety in the process of writing. This studycontributes new knowledge to the field by relating anxiety to self-regulation in the process of writing M.A. theses, yielding a deepened understanding of self-regulation that reduces anxiety in terms of the progress gradually achieved in the writing process. It alsohas implications for supervisors to pay attention to the way of negotiating with students that may cause anxiety during the academictheses writing process.

个人信息的内生安全机制及其实现

个人信息处理的技术性、隐蔽性,使自上而下的“命令式”监管范式失效。数字时代,个人信息治理的重点是防止个人信息处理者滥用数据权力威胁国家安全、盘剥和操控个体。为有效控制数据权力这一风险源,国家应当督促个人信息处理者建立健全涵盖制度保障、组织程序保障的个人信息内生安全机制。通过监管激活个人信息处理者内部的自我规制机制,增强其内部的组织控制和行为规范化程度,消减个人信息处理的负外部性,实现个人信息处理的正和博弈。通过监管督促个人信息处理者强化内部治理机制,严格落实个人信息保护影响评估制度,遵从“三同步”要求将个人信息保护法规定的各项义务嵌入产品“代码”中,防控个人信息处理过程中妨害个人自主性、减损人格尊严的风险。

基于物联网的造纸过程监控与控制系统设计与实践

造纸业是一种技术密集型产业,造纸工业发展情况与一个国家的经济发展水平、文化发展有密切的关系。为达成提升造纸生产效率、控制品质、节能环保等要求,造纸企业应对造纸过程进行监控和分析。这有利于企业合理调整造纸生产环节各项参数或保护造纸生产线昂贵的设施,对优化整个造纸过程、推进造纸企业大规模发展具有重要的意义。基于此,以造纸业为对象,在深入分析造纸生产实现流程基础上,基于物联网技术设计造纸过程监控与控制系统,详细介绍系统制浆调节、数据采集、纸病诊断等模块设计情况,并对其安全性等指标展开测试。本次测试结果表明,所设计的监控与控制系统能满足造纸生产过程监控和控制要求,支持全方位监控造纸生产现场,以期推进造纸业可持续发展。

品质导向的粮油食品精准加工分子基础与调控

粮油是国家最重要的战略物资,粮油食品产业在国民经济中起着基础作用,深度关系着国计民生和国民健康。粮食和油料中营养组分丰富及其多尺度结构复杂,且加工方式多变,进而影响粮油食品的感官、安全特性和消化吸收、营养健康效应。本文通过系统梳理粮油食品发展现状及产业战略意义,品质导向的粮油食品加工与制造发展现状及面临的挑战,提出从粮油食品的加工过程控制,营养组分多尺度结构变化与结构重构,多维度品质特性调控3个角度,系统解析基于品质导向的粮油食品精准加工的结构基础与调控机制,重点探讨粮油食品中主要营养组分的加工适应性、互作机制,粮油食品加工对感官品质、健康品质和安全品质等品质特性的影响,多维品质与加工过程构效关系与关联调控机制等制约粮油食品未来发展的研究方向,以期建立品质导向的粮油食品精准加工的理论基础、技术方法和新型绿色加工策略,为创制感官、安全和健康品质协同提升的营养健康粮油食品提供理论支撑,推动我国粮油食品加工产业的高质量发展。

水库拦沙对黄河下游河床演变的影响

为充分认识水库拦沙对其下游河道河床演变及防洪的影响,基于三门峡水库和小浪底水库拦沙期水沙及断面观测资料,研究了黄河下游河槽冲淤、洪水冲刷效率、河槽几何特征、排洪能力等规律。结果表明:水库拦沙期,黄河下游沿程河槽均发生了不均衡冲刷;河床粗化明显,粗化后床沙中值粒径最大值为冲刷前的2.1~2.5倍;高村以上河段同水位过洪能力增加明显,冲刷后较大的河槽容积可为小浪底水库排沙提供暂时的滞沙;河床粗化后细泥沙和中泥沙补给能力不足,河槽冲刷效率随冲刷历时的增加衰减明显。由于水库多年调节水沙过程及下游相对完善的河道整治工程约束,小浪底水库拦沙期黄河下游河槽冲刷重心下移,河床粗化程度增加,冲刷效率明显降低。研究成果可为水库水沙调控技术指标的选取提供科学依据。

侵犯个人信息行为的刑法全流程规制模式研究

在个人信息行为规制方面,我国前置法与刑法之间存在明显差异,前置法通过处理规则的设计实现了全流程规制,而刑法只能对部分不法处理行为进行惩治。此种规范格局导致法律难以衔接并形成刑法保护的盲区,不利于全面保护个人信息权益。对此,应提倡个人信息的刑法全流程规制模式,通过间接罪名适用法和法益量刑评价法对不同类型处理行为进行合理规制。通过理论维度和规范维度的证成,可以验证全流程规制模式具有可操作性。应当适用刑法合理规制非法收集行为和非法存储行为,保障前期阶段信息处理安全;适用刑法精准规制非法加工行为、非法使用行为和非法流转行为,保障中期阶段信息处理安全;运用刑法适度规制非法披露行为和非法删除行为,保障后期阶段信息处理安全。

智能教育中可计算感知技术:系统性综述

随着教育技术的进步和发展,以深度学习、机器学习、虚拟现实、物联网为代表的可计算感知技术在以人为本的教育中的应用愈发广泛,同时也是赋能教育发展变革的关键力量之一。然而,目前对于可计算感知技术在智能教育中的应用还知之甚少。以面部表情、语音、文本、眼动、触觉、生理信号等可感知的物理及虚拟空间中可感知数据为基础,对当前公开发表的期刊文献和会议论文进行筛选和统计,系统分析了智能教育中可计算感知技术的进展与应用,并提出了其对教育实践的潜在影响和挑战。最后,基于结论对智能教育中可计算感知技术的未来发展方向展开了前瞻讨论。