Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

An intelligent active probing and trace-back scheme for IoT anomaly detection

Due to their simple hardware,sensor nodes in IoT are vulnerable to attack,leading to data routing blockages or malicious tampering,which significantly disrupts secure data collection.An Intelligent Active Probing and Trace-back Scheme for IoT Anomaly Detection(APTAD)is proposed to collect integrated IoT data by recruiting Mobile Edge Users(MEUs).(a)An intelligent unsupervised learning approach is used to identify anomalous data from the collected data by MEUs and help to identify anomalous nodes.(b)Recruit MEUs to trace back and propose a series of trust calculation methods to determine the trust of nodes.(c)The last,the number of active detection packets and detection paths are designed,so as to accurately identify the trust of nodes in IoT at the minimum cost of the network.A large number of experimental results show that the recruiting cost and average anomaly detection time are reduced by 6.5 times and 34.33%respectively,while the accuracy of trust identification is improved by 20%.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Ethical framework for artificial intelligence in healthcare research:A path to integrity

The integration of Artificial Intelligence(AI)into healthcare research promises unprecedented advancements in medical diagnostics,treatment personalization,and patient care management.However,these innovations also bring forth significant ethical challenges that must be addressed to maintain public trust,ensure patient safety,and uphold data integrity.This article sets out to introduce a detailed framework designed to steer governance and offer a systematic method for assuring that AI applications in healthcare research are developed and executed with integrity and adherence to medical research ethics.

Double-Edge Intelligent Integrated Satellite Terrestrial Networks

The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of coexistence.This has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIGENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular networks.In this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and standardization.Then we present the overall design of the proposed DILIGENT architecture,where the advantages are discussed and summarized.Strategies of task offloading,content caching and distribution are presented.Numerical results show that the proposed network architecture outperforms the existing integrated networks.

Intelligent Integrated Model for Improving Performance in Power Plants

Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants.Poor performance problem in maintaining power plants is the result of both human errors,human factors and the poor implementation of automation in energy management.This problem can potentially be solved using artificial intelligence(AI)and an integrated management system(IMS).This article investigates the current challenges to improving personnel and energy management performance in power plants,identifies the critical success factors(CSFs)for an integrated intelligent framework,and develops an intelligent framework that enables power plants to improve performance.The theoretical basis is founded on a systematic literature review to locate 110 out of 3108 papers studied carefully to examine the performance architecture that best enables effective maintenance.The findings from this literature review are combined with expert judgment and the big data advantages of AI applications to develop an intelligent model.Data are collected from a power plant in Iraq.To ensure the reliability of the proposed model,various hypotheses are tested using structural equation modeling.The results confirm that the measurement model is acceptable,and that the hypotheses are supported and significant.A case study demonstrates the strong relationship and significance between big data of performance and the CSFs.It is hoped that this model will be adopted to enable performance improvement in power plants.

Integrated and Intelligent Manufacturing： Perspectives and Enablers

随着市场竞争的日益激烈和技术的进步,越来越多的国家把先进制造技术摆在促进经济增长的首要位置。德国于2013年公布"工业4.0"战略。美国政府于2011年推出"先进制造业伙伴关系"(AMP)计划,又于2014年推出"国家制造业创新网络"(NNMI)计划。最近,美国正式推出"美国制造业"计划,该计划通过加强工业界、学术界和政府伙伴间的密切合作,进一步有效"利用现有资源……培育制造业创新能力并加速商业化进程"。2015年,中国政府正式发布《中国制造2025》这一面向制造业的十年规划和路线图。在所有的国家计划中,核心技术的发展都集中应用于先进制造系统领域。一种新的制造模式正在兴起,其具备两个独特的特征:集成化制造和智能制造。这一趋势符合工业革命的发展进程,而在此进程中人们不断追求更高效率的生产系统。为此,人们为新的制造模式划定了10项主要技术。本文介绍了集成化智能制造(i^2M)系统的基本原理和需求,同时也介绍了来自不同领域的相关技术。值得一提的是,本文还讨论了物联网和服务(Io TS)、信息物理系统(CPS)和云计算等关键的技术推动力量。通用电气(GE)的Predix和美国参数技术公司(PTC)的Thing Worx等商用平台的应用所面临的挑战也得到了有效应对。

Intelligent Control and Maintenance Man-agement Integrated System Based on Multi-Agents for Coal-Preparation Plant

This paper discusses the progress of computer integrated processing (CIPS) of coal-preparation and then presents an intelligence controlled production-process, device-maintenance and production-management system of coal-preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing distributed intelligence con- trol system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal-preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Manage- ment integrated system, is studied and the implemention methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal-preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of pro- duction adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal-preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption.

Internet of Lamps for Future Ubiquitous Communications:Integrated Sensing,Hybrid Interconnection,and Intelligent Illumination

The ubiquitous deployment and restricted consumption are the requirements restricting the development of Internet of Things.Thus,a promising technology named Internet of Lamps(Io L)is discussed in this paper to address these challenges.Compared with other communication networks,the remarkable advantage of Io L is that it can make full use of the existing lighting networks with sufficient power supply.The lamps can be connected to the Internet through wired power line communication and/or wireless communication,while the integration of integrated sensing,hybrid interconnection,and intelligent illumination is realized.In this paper,the Io L is discussed from three aspects including sensing layer,network layer,and application layer,realizing the comprehensive upgrade based on the conventional communication and illumination systems.Meanwhile,several novel technologies of Io L are discussed based on the requirements of sensing,communication,and control,which have put forward practical solutions to the issues faced by Io L.Moreover,the challenges and opportunities for Io L are highlighted from various parts of the system structure,so as to provide future insights and potential trends for researchers in this field.

The New Integrated Management of Efficient Buildings: An Intelligent Method Approach and AI

Building process innovation highlights building systems and products that denounce both an incremental and radical development,indicating the technological sector as the driver for energy efficiency.The prototypes of this innovation stand out both in the tertiary and residential sector and are aimed at sustainable development with the use of renewable resources,intelligent technologies,with a view to contextualizing and environmental energy requalification.The objectives are those of a new integrated building management,intended as an increase in energy efficiency and an efficient digitalized connection with users and smart grids,through control platforms,IoT(internet of things),security throughout the building’s life cycle and use of AI(artificial intelligence)devices and materials.The approach is a new methodology,with the application of BMS(building management system)and BEMS(building energy management system)systems integrated with other systems,with an interface of protocols open to different manufacturers and multiple functions that invest both the technological and environmental system of the building,with advantages in electrical energy management and thermoelectric like intelligent HVAC systems,with intelligent monitoring and user comfort.Both the new Artificial Intelligence and Machine Learning platforms contribute to a predictive use of energy efficiency with plant optimization.Therefore efficiency and energy saving strategies with intelligent integrated management and medium-long term maintenance programs.The challenge is a new intelligent method approach with the use of artificial intelligence and the development of new technologies in sustainable buildings.

The Intelligent Terminal Design for Integrated Substation Auxiliary System

The integrated substation auxiliary system is a project composed by software and hardware to help operators of a substation carry daily maintain works. The intelligent terminal is the key part of the system and it provides important UI and communication functions for the user. Smart phones can achieve higher bandwidth data communication, and at the same time can carry Bluetooth communication, video call, multimedia display and other functions. Smart phone is a potential common platform, suitable for the deployment of substation integrated auxiliary system terminal. Based on the Android Smart phone platform, this paper develops intelligent client-side software for the integrated substation auxiliary system and it can realize the operation ticket control, the video call, the substation map display and other functions. This client-side software has been applied in practice, and has gained good effects.

Intelligent Integrated Control of Underactuated Mechanical Systems with Second-order Nonholonomic Constraints

This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.

APPLICATION OF INTEGRATED INTELLIGENT METHODOLOGY TO PREDICT STABILITY AND SUPPORTING DECISION IN UNDERGROUND DRIFT

The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal rock mechanical problem is proposed.By the terms of the non linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft rock drifts.

Multiple Intelligence Theory in Integrated English Teaching

Integrated English is a core course for English major students in our college,and this article mainly discusses the application of Multiple Intelligence theory in Integrated English classroom.

Key issues and progress of industrial big data-based intelligent blast furnace ironmaking technology

Blast furnace (BF) ironmaking is the most typical “black box” process, and its complexity and uncertainty bring forth great challenges for furnace condition judgment and BF operation. Rich data resources for BF ironmaking are available, and the rapid development of data science and intelligent technology will provide an effective means to solve the uncertainty problem in the BF ironmaking process. This work focused on the application of artificial intelligence technology in BF ironmaking. The current intelligent BF ironmaking technology was summarized and analyzed from five aspects. These aspects include BF data management, the analyses of time delay and correlation, the prediction of BF key variables, the evaluation of BF status, and the multi-objective intelligent optimization of BF operations. Solutions and suggestions were offered for the problems in the current progress, and some outlooks for future prospects and technological breakthroughs were added. To effectively improve the BF data quality, we comprehensively considered the data problems and the characteristics of algorithms and selected the data processing method scientifically. For analyzing important BF characteristics, the effect of the delay was eliminated to ensure an accurate logical relationship between the BF parameters and economic indicators. As for BF parameter prediction and BF status evaluation,a BF intelligence model that integrates data information and process mechanism was built to effectively achieve the accurate prediction of BF key indexes and the scientific evaluation of BF status. During the optimization of BF parameters, low risk, low cost, and high return were used as the optimization criteria, and while pursuing the optimization effect, the feasibility and site operation cost were considered comprehensively.This work will help increase the process operator’s overall awareness and understanding of intelligent BF technology. Additionally, combining big data technology with the process will improve the practicality of data models in actual production and promote the application of intelligent technology in BF ironmaking.

In-plane micro-sized energy storage devices:From device fabrication to integration and intelligent designs

The rapid development of micro-electronics raises the demand of their power sources to be simplified,miniaturized and highly integratable with other electronics on a chip.In-plane Micro-sized energy storage devices(MESDs),which are composed of interdigitated electrodes on a single chip,have aroused particular attentions since they could be easily integrated with other miniaturized electronics,reducing the complexity of overall chip design via removing complex interconnections with bulky power sources.This review highlights the achievements in the device fabrication of in-plane MESDs,as well as their integration and intelligent designs.We also discussed the current challenges and future perspectives for the development of in-plane MESDs.

Intelligent Deep Learning Enabled Wild Forest Fire Detection System

The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfire detec-tion and alarming system using deep learning(IWFFDA-DL)model.The pro-posed IWFFDA-DL technique aims to identify forestfires at earlier stages through integrated sensors.The proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast thefire.Then,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of danger.For hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection performance.Finally,when thefire is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required actions.An extensive set of simulations were performed and the results are investigated interms of several aspects.The obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.

The Client/server-based Distributed Architecture of a CIM Intelligent Integrating Platform

Information integrating platform is a basic supporting environment based on informationtechnology for a CIM(Computer Integrated Manufacturing)system.There are some prob-lems to solve in the research and development of the platform,such as the type of informa-tion processed in the platform and the distribution strategy of the platform system.This pa-per introduces a plan of an intelligent information integrating platform for CIM system basedon the client/server architecture,named I3P.The architecture,organization and detailed de-sign of services in I3P are also described.