Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions.In the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication protocols.Smart grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for IEDs.Hence,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for IEDs.Initially,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security assessment.Subsequently,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal behaviors.This index system contains 18 indicators in 3 categories.Additionally,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and 5.The higher the level,the greater the security risk.Finally,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by IEDs.The results show that calculated security risk level based on the proposed assessment method are consistent with actual simulation.Thus,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

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.

Research on urban intelligent fashion advertising service model based on wearable devices

We are developing a novel wearable devices called the urban intelligent fashion advertising.Such system is mobile information devices capable of supporting remote communication and intelligent interaction between terminals.In this paper,we explore the possible functions of such a wearable devices and will present the service-based architecture combing the hardware and the software.This architecture involves two major parts.The first part is hardware design,which includes microcontroller,display part,communication module,and positioning system module.The second part is software design,which is a real-time interactive system that includes signal reception,position detection,and user workload assessment.Then,we use the interactive concept and interactive technology to construct the urban fashion advertising service model,and elaborate on its business model.Finally,we present sustainability development recommendations for the proposed service model.

基于DeviceNet总线的智能照明控制器设计

Devicenet总线在智能照明控制方面有着明显优势。本文设计了一个基于Device Net现场总线的智能照明控制器。以协议规范为蓝本,介绍了智能照明控制器的Device Net接口硬件实现方案,系统软件在分析了对象模型的基础上由Keil u Vision4编写,最终实现调节灯光照度的效果。

Design of the Control System of Adaptive Balancing Device Based on PLC

Due to the well condition and the un-expected imbalance movement of the pumping unit in use, the energy consumes a lot. The existing balancing equipment cannot adjust and monitor the pumping units in real time. Therefore this paper introduces the new adaptive balancing equipment—fan-shaped adaptive balancing intelligent device, projects a design of such control system based on PLC, and determines the principle of the control system, the execution software and the design flow. Site commissioning effect on Daqing Oilfield shows this fan-shaped adaptive balancing intelligent device can effectively adjust and monitor the pumping unit in real time, the balance even adjusts from 0.787 to 0.901, and integrated energy saving rate is 14.2%. It is approved that this control device is professionally designed, with strong compatibility, and high reliability.

Research on intelligent ultrasonic thickness measurement system applied to large area of hull

For a ship in service,seawater corrosion is unavoidable. In order to ensure navigation safety and master the steel plate thickness in service ship,thickness of the ship steel plate must be tested periodically by a scientific method. After consideration of an actual situation of thickness measurement,the bearing mechanism of ultrasonic thickness meter probe has been designed on the basis of wall-climbing robot,and preliminary experiments have been carried out. The device is mainly used for thickness measurement of a large area of ship hull plate when the docking ship has been sandblasted. Efficiency and safety can be improved to finish thickness measurement by using the device.

Application of Mobile Intelligent Inspection System in Substation Equipment Management

Intelligent inspection is more and more widely applied in all walks of life. This paper introduces the application of the intelligent inspection system in substation equipment management based on mobile phone terminal. It can make the power supply enterprise have more effective means to ensure the safe operation of equipment, improve equipment management level, and improve the economic benefits of power supply.

The Research of Intelligent Substation Time Synchronization System and the Influence of Its Fault to Relay Protection

The intelligent substation realizes the digitization of information in the whole substation and thus time synchronization system becomes more and more important. This paper introduces time synchronization technology of intelligent substation and puts forward the principles for designing intelligent substation time synchronization system. According to some relay protection malfunction examples caused by time synchronization system fault, analyze the influence of time synchronization system fault to relay protection and correspondingly put forward some improving measures.

Edge Device Fault Probability Based Intelligent Calculations for Fault Probability of Smart Systems

In a smart system, the faults of edge devices directly impact the system’s overall fault. Further, complexity arises when different edge devices provide varying fault data. To study the Smart System Fault Evolution Process (SSFEP) under different fault data conditions, an intelligent method for determining the Smart System Fault Probability (SSFP) is proposed. The data types provided by edge devices include the following: (1) only known edge device fault probability;(2) known Edge Device Fault Probability Distribution (EDFPD);(3) known edge device fault number and EDFPD;(4) known factor state of the edge device fault and EDFPD. Moreover, decision methods are proposed for each data case. Transfer Probability (TP) is divided into Continuity Transfer Probability (CTP) and Filterability Transfer Probability (FTP). CTP asserts that a Cause Event (CE) must lead to a Result Event (RE), while FTP requires CF probability to exceed a threshold before RF occurs. These probabilities are used to calculate SSFP. This paper introduces a decision method using the information diffusion principle for low-data SSFP determination, along with an improved method. The method is based on space fault network theory, abstracting SSFEP into a System Fault Evolution Process (SFEP) for research purposes.

The accuracy of arrhythmia detection and its clinical significance of intelligent wearable electrocardiogram monitoring devices in asymptomatic myocardial ischemia patients during daily activities.

This study focuses on the accuracy of arrhythmia detection by intelligent wearable electrocardiogram(ECG)monitoring devices in asymptomatic myocardial ischemia patients during daily activities.It elaborates on the technical principles,features,and working modes of such devices and makes a comparison with traditional ECG monitoring methods.Through a well-designed experimental approach involving data collection and analysis using specific evaluation metrics and standards,the accuracy of arrhythmia detection is evaluated.The relationship between arrhythmia and myocardial ischemia is explored,along with its impact on diagnosis,prognosis,and treatment strategy development.The application of these devices in daily activities,including feasibility,compliance,and analysis during different activity states and long-term trends,is also examined.Despite the potential benefits,technical limitations and barriers to clinical acceptance are identified,and future research directions are proposed.The findings contribute to a better understanding of the role and value of intelligent wearable ECG monitoring devices in the management of asymptomatic myocardial ischemia patients.

Impact of Artificial Intelligence on Corporate Leadership

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

基于《国际功能、残疾和健康分类》评价中国智能化辅盲设备的补偿功能

背景:辅盲设备及技术的应用是当今视力障碍人群常用的干预手段,可提高日常生活活动的参与及工作学习能力,帮助其回归家庭、回归社会。数字信息和智能化时代下辅盲设备的形式、技术和功能各有不同,其分类目前暂未能得到有效统一的讨论和评价。目的:基于《国际功能、残疾和健康分类》评价国内视力障碍人群智能化辅盲设备的补偿功能。方法:通过计算机检索中国知网、维普和万方数据库2013-01-01/2023-12-31收录的相关文献。基于《国际功能、残疾和健康分类》理论模式和框架结构,应用术语结构和编码程序归纳相关视力障碍评估类目,整理与分析国内视力障碍的智能化辅盲设备补偿功能研究与分类。结果与结论:①共纳入197篇文献:其中身体功能1篇,包含b2(b210);身体结构1篇,包含s2(s220);活动与参与共119篇,包含d1(10篇,d110、d115、d120、d140、d166),d3(4篇,d315、d325、d345、d360),d4(102篇,d465、d470),d8(3篇,d820、d825);环境因素共76篇,包含e1(72篇,e115、e120、e125、e130、e140、e150、e155、e160),e2(4篇,e210、e240);②基于《国际功能、残疾和健康分类》的视力障碍智能化辅盲设备补偿功能研究分类包含4个部分、8个分类、25个类目,领域涉及身体补偿类、生活用品类、教育学习类、出行导盲类、布局规划类。

Intelligent algorithms: new avenues for designing nanophotonic devices [Invited]

The research on nanophotonic devices has made great progress during the past decades. It is the unremitting pursuit of researchers that realize various device functions to meet practical applications. However, most of the traditional methods rely on human experience and physical inspiration for structural design and parameter optimization, which usually require a lot of resources, and the performance of the designed device is limited. Intelligent algorithms, which are composed of rich optimized algorithms, show a vigorous development trend in the field of nanophotonic devices in recent years. The design of nanophotonic devices by intelligent algorithms can break the restrictions of traditional methods and predict novel configurations, which is universal and efficient for different materials, different structures, different modes, different wavelengths, etc. In this review, intelligent algorithms for designing nanophotonic devices are introduced from their concepts to their applications, including deep learning methods, the gradient-based inverse design method, swarm intelligence algorithms, individual inspired algorithms, and some other algorithms. The design principle based on intelligent algorithms and the design of typical new nanophotonic devices are reviewed. Intelligent algorithms can play an important role in designing complex functions and improving the performances of nanophotonic devices, which provide new avenues for the realization of photonic chips.

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare

Chronic diseases are a growing concern worldwide,with nearly 25% of adults suffering from one or more chronic health conditions,thus placing a heavy burden on individuals,families,and healthcare systems.With the advent of the“Smart Healthcare”era,a series of cutting-edge technologies has brought new experiences to the management of chronic diseases.Among them,smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.However,how to organize and analyze the data to achieve the ultimate goal of improving chronic disease management,in terms of quality of life,patient outcomes,and privacy protection,is an urgent issue that needs to be addressed.Artificial intelligence(AI)can provide intelligent suggestions by analyzing a patient’s physiological data from wearable devices for the diagnosis and treatment of diseases.In addition,blockchain can improve healthcare services by authorizing decentralized data sharing,protecting the privacy of users,providing data empowerment,and ensuring the reliability of data management.Integrating AI,blockchain,and wearable technology could optimize the existing chronic disease management models,with a shift from a hospital-centered model to a patient-centered one.In this paper,we conceptually demonstrate a patient-centric technical framework based on AI,blockchain,and wearable technology and further explore the application of these integrated technologies in chronic disease management.Finally,the shortcomings of this new paradigm and future research directions are also discussed.

Flexible and breathable 3D porous SSE/MXene foam towards impact/electromagnetic interference/bacteria multiple protection performance for intelligent wearable devices

As intelligent wearable devices,they will inevitably be subjected to various damages and disturbances from the external environment during daily use.Therefore,it is urgent to develop safeguarding materials with multiple protective properties.Herein,this work developed a flexible and breathable three-dimensional(3D)porous shear stiffening elastomer(SSE)/MXene(M-SSE)foam with impact/electromagnetic interference(EMI)/bacteria multiple protection performance for intelligent wearable devices.The continuous conductive MXene network in the 3D SSE porous structure made M-SSE foam exhibit excellent electromagnetic interference shielding property with a high shielding effectiveness of 34 dB.Attributed to the shear stiffening effect of porous SSE matrix,M-SSE foam possessed unique anti-impact and protection properties.The energy dissipation rate reached up to more than 85%,illustrating M-SSE foam could effectively attenuate the external impact force and absorb the impact energy.Inherited from the excellent photothermal performance of MXene,M-SSE foam achieved a considerable saturated temperature of 98℃ under 0.57 W/cm^(2) laser power.Therefore,M-SSE foam showed extraordinary antimicrobial property for Staphylococcus aureus according to the principle of photothermal sterilization.Finally,for the development of intelligent wearable devices,conductive MSSE foam could be used as an intelligent sensor to monitor various human movements owing to the highly sensitive property.This work greatly expanded the application prospect of multifunctional protective materials in various complex environments and promoted the development of multifunctional smart wearable devices in protection field.

Improve the Accuracy of Fall Detection Based on Artificial Intelligence Algorithm

This work presents a fall detection system based on artificial intelligence.The system incorporates miniature wearable devices for fall detection.Fall detection is achieved by integrating a three-axis gyroscope and a threeaxis accelerometer.The system gathers the differential data collected by the gyroscope and accelerometer,applies artificial intelligence algorithms for model training and constructs an effective model for fall detection.To provide easywearing and effective position detection,it is designed as a small device attached to the user’swaist.Experiment results have shown that the accuracy of the proposed fall detection model is up to 98%,demonstrating the effectiveness of the model in real-life fall detection.

2D materials for intelligent devices

Neuromorphic intelligent hardware technologies have undergone rapid advancement during the past decade,with the goal of building intelligent devices and systems capable of overcoming challenges associated with conventional hardware.Realization of neuromorphic intelligent hardware depends on major advances in materials science,condensed matter physics,device physics and engineering.As a revolutionary discovery,two-dimensional(2D)materials with atomically-thin thickness and exceptionally high tunability introduce a new physical paradigm and show great promise in the development of intelligent devices.Here,we give prominence to three categories of tunable properties(i.e.,charge carrier,band structure,lattice structure)that are inherent for 2D materials and review their superiorities in constructing intelligent devices particularly in electronics and optoelectronics.Furthermore,we provide insight into how the unique physical mechanisms emerging in 2D materials offer a fertile ground for the design of diverse intelligence devices.

Artificial Intelligence Providing a More Optimized Assessment Tool for Comprehensive Geriatric Assessment

With the continuous development of science and technology,artificial intelligence(AI)is coming into our lives and changing our lives.Since China entered the aging society in 2000,the degree of population aging has deepened.Comprehensive geriatric assessment(CGA)is now the accepted gold standard for the care of older people in hospitals.However,some problems limit the clinical application,such as complexity and time consuming.Therefore,by analyzing previous studies,we summarize some existing AI tools in order to find a more optimized assessment tool to complete the entire CGA process.

Information Technology in Domain of Electronic Intelligence and Cyberterrorism Combat

Terms of intelligence in 20th and 21th century mean the methods of automatic extraction, analysis, interpretation and use of information. Thus, the intelligence services in the future created an electronic database in which to their being classified intelligence products, users could choose between the latter themselves relevant information. The EU （European Union） that activities are carried out from at least in year 1996, terrorist attacks in year 200l is only accelerating. Proposals to increase surveillance and international cooperation in this field have been drawn up before September 11 2011. On the Web you can fmd a list of networks （Cryptome, 2011）, which could be connected, or are under the control of the security service--NSA （National Security Agency）. United States of America in year 1994 enacted a law for telephone communication--Digital Telephony Act, which would require manufacturers of telecommunications equipment, leaving some security holes for control. In addition, we monitor the Internet and large corporations. The example of the United States of America in this action reveals the organization for electronic freedoms against a telecom company that the NSA illegally gains access to data on information technology users and Internet telephony.

Application of Machine Learning in Electronic Device Fault Diagnosis

As electronic devices become increasingly complex, traditional fault diagnosis methods face significant challenges. Machine learning technologies offer new opportunities and solutions for electronic device fault diagnosis. This paper explores the application of machine learning in electronic device fault diagnosis, focusing on common machine learning algorithms, data preprocessing techniques, and diagnostic model construction methods. Case study analysis elucidates the advantages of machine learning in improving diagnostic accuracy, reducing diagnosis time, and implementing predictive maintenance. Research indicates that machine learning techniques can effectively enhance the efficiency and precision of electronic device fault diagnosis, providing robust support for device reliability and maintenance strategy optimization. In the future, as artificial intelligence technology further develops, machine learning will play an increasingly important role in the field of electronic device fault diagnosis.