Intelligent Era Research Articles

B-TBM: A Novel Deep Learning Model with Enhanced Loss Function for HAZOP Risk Classification Using Natural Language Statistical Laws

HAZOP is a paradigm of industrial safety, and the introduction of deep learning-based HAZOP text categorization marks the arrival of an intelligent era of safety analysis. However, existing risk analysis methods have limitations in processing complex texts and extracting deep risk features. To solve this problem, this paper proposes a novel HAZOP risk event classification model based on BERT, BiLSTM, and TextCNN. The complexity of HAZOP text is revealed by introducing statistical laws of natural language, such as Zipf’s law and Heaps’ law, and the outputs of different levels of BERT are further combined linearly to collaborate with BiLSTM and TextCNN to capture long-term dependency and local contextual information for a more accurate classification task. Meanwhile, an improved loss function is proposed to effectively solve the deficiencies of the traditional cross-entropy loss function in the mislabeling process and improve the generalization ability of the model. It is experimentally demonstrated that the accuracy of the model is improved by 3% to 4% compared to the traditional BERT model in the task of severity and possibility classification of HAZOP reports. This study not only improves the accuracy and efficiency of HAZOP risk analysis, but also provides new ideas and methods for the application of natural language processing in industrial safety.

Study On the Value Connotation, Dilemma and Path of the Integration of Industry and Education in the Open University in the Intelligent Era

The intelligent age puts forward new requirements to the education industry. As an important part of the lifelong education system, the Open University faces challenges in the adaptability and effectiveness of its production-education integration model in the intelligent age. This paper analyzes the value connotation of the integration of industry and education in the Open University under the background of the intelligent era and deeply discusses the core dilemma encountered in the integration of industry and education, including poor policy response, incomplete feedback mechanism, unclear school-running positioning, lack of characteristics of the integration of industry and education, increasing demand for cooperation between enterprises, lack of cooperation ability of schools, lack of learning motivation, and lack of effective external incentives. On this basis, this paper puts forward targeted path optimization strategies, aiming to realize the effective promotion of the integration of industry and education in the Open University through integrated and coordinated development, improving feedback mechanism, clarifying school-running positioning, co-building cooperation platforms, clarifying enterprise needs, increasing on-campus investment, taking students as the center, strengthening external incentives and other solutions. The research in this paper not only guides for the Open University to carry out the integration of industry and education in the intelligent era but also provides decision-making reference for relevant policymakers.

An Exploration of the Innovation Path of Adult College Education Management Based on the Concept of Intelligent Management

With the continuous development of Internet technology in our country, many fields are beginning to introduce information technology into the work, and the country has gradually entered an intelligent era. Adult education is an important part of education in our country, and its value is self-evident. As an important part of adult college education, the introduction of intelligent management concept is of great significance to improve the management effect. In view of this, this paper will analyze the innovation of adult college education management based on the concept of smart management, and put forward some strategies for your colleagues’ reference.

Erosion and Remodeling: New Alienation of User Subjects Led by Intelligent Algorithms

As the core technological means of today's artificial intelligence products, intelligent algorithms have become an indispensable tool for human development. They have led the progress of the intelligent era, fully demonstrating the powerful charm and infinite possibilities of technology, and depicting a hopeful intelligent future. However, while bringing convenience and imagination to users, it also makes them objects dominated by intelligent technology, gradually losing their independence and creativity as humans, losing their ability to criticize and think deeply, and causing a series of inevitable alienation problems that cannot be ignored. This article uses qualitative research methods to conduct in-depth interviews with respondents, extract their attitudes and opinions towards one of the artificial intelligence technologies - algorithms, and organize and analyze them. The phenomenon of "new alienation" brought about by reshaping algorithms is based on users' real thinking and more accurate needs, breaking the constraints of intelligence and adding benefits to the development of algorithms.

Opportunities and Challenges for the Professional Development of College Teachers in the Intelligent Era

This paper explores the significance, opportunities, and challenges presented by the intelligent era for the professional development of college teachers. We categorize teachers' professional development into four key dimensions: professional concepts, knowledge, skills, and emotional intelligence. The intelligent era offers various opportunities, including the innovation of teaching methodologies, the transformation of educational paradigms, and the evolution of learning styles. However, it also poses significant challenges, such as the redefinition of teachers' identities, the transition from fragmented to systematic knowledge, and the increasing demands for digital literacy and higher-order cognitive skills. In response to these dynamics, it is imperative for college educators to actively engage with these changes and continuously enhance their professionalism to effectively guide the evolution of education.

Light‐controlled smart materials: Supramolecular regulation and applications

AbstractSmart materials serve as the fundamental cornerstone supporting humanity's transition into the intelligent era. Smart materials possess the capability to perceive external stimuli and respond accordingly. Light‐controlled smart materials (LCSMs) are a significant category that can sense and respond to light stimuli. Light, being a non‐invasive, precisely regulated, and remotely controllable source of physical stimulation, makes LCSMs indispensable in certain application scenarios. Recently, the construction of LCSMs using supramolecular strategies has emerged as a significant research focus. Supramolecular assembly, based on non‐covalent bonding, offers dynamic, reversible, and biomimetic properties. By integrating supramolecular systems with photoresponsive molecular building blocks, these materials can achieve synergistic and rich intelligent stimulus responses. This review delves into the latest research advancements in LCSMs based on supramolecular strategies. There are four sections in this review. The first section defines LCSMs and outlines their advantages. The second section discusses the design approaches of supramolecular LCSMs. The third section highlights the latest advancements on supramolecular LCSMs over the past 3 years. The fourth section summarizes the current research and provides insights into the future development of this field.

Incident Angle Sensing and Adaptive Control of Scattering by Intelligent Metasurface.

The passive sensing and active control of electromagnetic (EM) waves have always been attractive in electronic and information areas, especially during the intelligent era. Here a new method is presented to achieve the angle sensing of incident wave and adaptive control of backward scattering using the intelligent metasurface. The proposed unit cells have the ability to dynamically manipulate the receiving and reflection of the EM energy respectively. The angle sensing of incident waves can be actualized using the method of compressive sensing based on multiple receiving patterns, which are generated by randomly switching the receiving and reflection states of the unit cells. Afterward, the customized performances of backward scattering waves according to the cognitive incident angle can be realized by controlling the programmable reflective phases of unit cells correspondingly. One prototype composed of the metasurface and the module for sensing and adaptive feedback control is fabricated. The whole intelligent metasurface with customizing the function of retro-reflection or low scattering is measured without human intervention and the good results acquired can verify the validity of the proposed concept and design.

Comparative Study of AI Textbooks for Primary and Secondary Schools

With the development of information technology, artificial intelligence (AI) has become a new focal point of international competition. AI education in primary and secondary schools is gradually becoming an important component of education in the intelligent era in China. Textbooks are a crucial medium for courses, and AI textbooks for primary and secondary schools are the core teaching materials for AI courses. This study examines 18 AI textbooks for primary and secondary schools, based on relevant curriculum standards such as the AI Curriculum Development Standards for Primary and Secondary Schools in China (Trial). Using content analysis and quantitative curriculum difficulty models, the study compares and analyzes the textbooks from five dimensions: teaching arrangement logic, textbook content, textbook usage conditions, textbook evaluation, and textbook difficulty. The study concludes that the textbooks have systematic teaching arrangement logic, though some lack learning objectives; the content is contemporary, but the knowledge system is not comprehensive; the usage conditions are diverse, but some schools lack the necessary implementation environment; and the difficulty is moderate, though there is a gap compared to the curriculum standards.

Research on the impact and improvement path of artificial intelligence on government regulation efficiency

With the deep integration of intelligent technology and government management scenarios, the management functions of modern government have also undergone changes, and artificial intelligence has gradually penetrated into the modernization process of government management. Artificial intelligence not only accelerates the transformation and innovation of government management models, but also impacts government regulation, triggers information security risks, and brings legal and ethical issues to the government. The article will analyze from four aspects: achieving intelligent control, strengthening joint governance, conducting credit supervision, and accelerating regulatory mechanism reform, providing a basis for the government to choose a path to improve regulatory efficiency in the intelligent era.

Triboelectric Nanogenerators with Machine Learning for Internet of Things

AbstractThe development of the Internet of Things (IoT) indicates that humankind has entered a new intelligent era of the “Internet of Everything”. Thanks to the characteristics of low‐cost, diverse structure, and high energy conversion efficiency, the self‐powered sensing systems, which are based on the Triboelectric Nanogenerator (TENG), demonstrate great potential in the field of IoT. In order to solve the challenges of TENG in sensing signal processing, such as signal noise and nonlinear relations, Machine Learning (ML), which is an efficient and mature data processing tool, is widely applied for efficiently processing the large and complex output signal data generated by TENG intelligent sensing system. This review summarizes and analyzes the adaptation of different algorithms in TENG and their advantages and disadvantages at the beginning, which provides a reference for the selection of algorithms for TENG. More importantly, the application of TENG is introduced in multiple scenarios, including health monitoring, fault detection, and human‐computer interaction. Finally, the limitations and development trend of the integration of TENG and ML are proposed by classification to promote the future development of the intelligent IoT era.

A Multielectrode Layout for High Reliability of Flexible Piezoresistive Sensor: One Stimulus Signal to Three Sensing Signals.

Flexible sensors have developed rapidly due to their great application potential in the intelligent era. However, the frequent bending work requirements pose a serious challenge to the mechanical reliability of flexible sensors. Herein, a strategy of using a new multielectrode layout to achieve multiple sensing signals based on one external signal is proposed for the first time to improve the reliability of flexible piezoresistive sensors. The multielectrode layout consists of a pair of interdigital electrodes and a bottom electrode. The interdigitated electrodes are used to sense the change in the surface resistance of the sensor, and the interdigital electrodes and the bottom electrode are used to sense the change in the bulk resistance of the sensor. As a result, without increasing the sensing unit area, the electrode layout allows the sensor to generate three response electrical signals when sensing an external pressure, thus improving the reliability of the sensor. Based on the electrode layout, a highly reliable flexible piezoresistive sensor with a multilevel porous structure is obtained by a microwave foaming method with a template. In the working state of sensing surface resistance, the sensor has a 22.12 kPa-1 sensitivity. Meanwhile, in the working state of sensing bulk resistance, the sensor shows a 55.17 kPa-1 sensitivity. Furthermore, the sensor is applied to monitor human pulse and speech signals, demonstrating its multisignal output characteristics and potential applications in flexible electronics. In conclusion, the new strategy of using the proposed electrode layout to improve the reliability of flexible sensors is expected to greatly promote the practical application of flexible electronics.

Research on the promotion of intelligent entertainment voice robots in personalized English learning based on data mining and gamified teaching experience

With the development of educational technology and the arrival of the intelligent era, intelligent entertainment voice robots have gradually become a research hotspot in the field of education. This study aims to explore the application of intelligent entertainment voice robots based on data mining in the promotion of personalized English learning, and combine with gamified virtual teaching to improve learners’ learning interest and learning effect. The study uses data mining technology to analyze learners’ learning data, interest preferences and learning performance, and provides learners with targeted learning resources and gamified virtual teaching environment based on personalized recommendation. The study creates a virtual teaching environment presented in the form of games, which contains various interesting tasks, challenges and reward mechanisms. Learners can participate in the virtual teaching environment at the same time, experience the fun and stimulation of games, so as to stimulate the interest and motivation of learning. Learners can engage in interactive speech learning through conversations with intelligent entertainment speech robots. The robot can provide real-time answers to learners’ questions, provide personalized learning suggestions, and provide encouragement and feedback. By interacting with robots, learners can get more flexible and personalized learning support, improving learning effectiveness and satisfaction. Through experiments and data analysis, it is found that intelligent entertainment voice robot based on data mining and gamification teaching experience can effectively improve learners’ learning interest and learning effect. Learners show higher engagement and motivation in personalized recommended learning resources and gamified virtual teaching environments.

Design and Implementation of an Adaptive Evaluation System for Teachers’ Information-Based Teaching Ability in the Intelligent ERA

The rapid development of teacher informatization has become a major highlight in current teaching. The information system under adaptive conditions has become the key to the reform of the intelligent era. The goal of this study is to design and implement an adaptive evaluation system for teachers’ information-based teaching ability, aiming at improving ability to meet the needs of modern education. This system analyzes the level of acceptance under key learning technologies. It combines elements by learning and analyzing their impact on general forms. It aims to analyze the rule algorithm dataset in a single machine environment. By analyzing multiple sets of different datasets, it calculates the number of key technologies that appear together in the same report based on the key technology word matrix. A co-occurrence matrix is constructed. The system adopts an advanced adaptive algorithm, which can conduct personalized assessments according to the actual ability and needs of teachers, so as to provide more accurate and effective feedback, help teachers understand their own advantages and disadvantages, and formulate more targeted promotion strategies. In the process of system design, the detailed requirement analysis is carried out first, and the function and performance requirements of the system are clarified. Then, we design the architecture of the system and determine the main modules and functions of the system. The function module is designed and the system is implemented. Through the practical application and effect evaluation of the system, we find that the system has high effectiveness and practicability. It can not only help teachers understand their own level of information-based teaching ability and provide personalized suggestions for improvement, but also provide decision support for education administrators and promote the development of education based on information. We expect that this system can play a greater role in the future education practice and promote the further development of education informatization.

Review of Two-timescale Stochastic Approximation Algorithms

Artificial Intelligence has gradually become an important force to drive human beings into the intelligent era, and machine learning has made great contributions to the rise and development of Artificial Intelligence. Stochastic approximation (SA) is a com-monly used optimization algorithm in machine learning, and with the complexity of practical problem scenarios, two-timescale SA have received extensive attention and research. In this paper, the basic idea and development process of SA are introduced firstly, followed by the description of several algorithmic frameworks for linear and nonlinear SA, and the specific applications of two-timescale SA in the fields of opti-mization and reinforcement learning are also introduced. Finally, the two-timescale SA is summarized and outlooked.

Modulating oxygen vacancies in MXene/MoO3-x smart fiber by defect engineering for ultrahigh volumetric energy density supercapacitors and wearable SERS sensors

MXene fibers are expected to accelerate the sustainable development of intelligent era as multi-functional smart fibers. However, MXene fibers have serious obstacles when used for multi-functional applications. Here, we fabricated a multi-functional MXene fiber by incorporating MoO3-x nanobelts with abundant oxygen vacancies via wet spinning and defect engineering methods. Benefiting from the presence of abundant oxygen vacancies, the produced MXene/MoO3-x fibers not only provide more active sites to interact with electrolyte ions, but also substantially augment the rate capacities of fibers due to the enlarged distances between MXene flakes. Thus, the assembled fiber-based supercapacitor (SCs) realized high capacitance of 869.1F cm−3 at 0.5 A cm−3, good volumetric energy density of 77.3 mWh cm−3 at a power density of 204.8 mW cm−3 and long-term cycling stability along with 86.4 % capacity retention after 5000 cycles. Moreover, due to the narrowed bandgap of MoO3-x produced by defect engineering enhanced the charge transfer between the fiber and molecules, MXene/MoO3-x fiber also demonstrated a low limit of detection and reliable biomarkers detection in artificial sweat. These findings provide the potential application of MXene-based fibers in multi-functional devices.

The Development and Challenges of Digital Government in the Intelligent Era

With the advent of the intelligent era, there is a need to leverage the empowering effects of data and construct a digital government governance system. Currently, driven by a reform mindset, innovative concepts, robust resource integration and implementation capabilities, as well as complementary technological advancements and innovative practices, the digital government exhibits governance characteristics of infrastructure cloudification, full-touchpoint digitization, online business processes, and data-driven operations. Its transformation logic reflects the interactive philosophy of flat communication, collaborative sharing of government data, optimization of precise service delivery, and the effective output of scientific decision-making. Despite its powerful governance effectiveness, digital government governance still faces challenges such as slow response to departmental needs, data silos, poor service collaboration, and weak business consistency. A comprehensive deepening of government digital transformation in the future requires innovative concepts, transitioning from information dissemination to intelligent applications, data innovation transitioning from data silos to data circulation and sharing, service innovation transitioning from function-driven to demand-driven by society, and decision-making innovation transitioning from unilateral decisions to collaborative, participatory, and shared decision-making. This will ultimately enhance the governance effectiveness of digital government.

Machine Learning Assisted Self-Powered Identity Recognition Based on Thermogalvanic Hydrogel for Intelligent Security.

Identity recognition as the first barrier of intelligent security plays a vital role, which is facing new challenges that are unable to meet the need of intelligent era due to low accuracy, complex configuration and dependence on power supply. Here, a finger temperature-driven intelligent identity recognition strategy is presented based on a thermogalvanic hydrogel (TGH) by actively discerning biometric characteristics of fingers. The TGH is a dual network PVA/Agar hydrogel in an H2O/glycerol binary solvent with [Fe(CN)6]3-/4- as a redox couple. Using a concave-arranged TGH array, the characteristics of users can be distinguished adequately even under an open environment by extracting self-existent intrinsic temperature features from five typical sites of fingers. Combined with machine learning, the TGH array can recognize different users with a high average accuracy of 97.6%. This self-powered identity recognition strategy is further applied to a smart lock, attaining a more reliable security protection from biometric characteristics than bare passwords. This work provides a promising solution for achieving better identity recognition, which has great advantages in intelligent security and human-machine interaction toward future Internet of everything.

Research on the application of BIM technology in intelligent building technology

With the continuous progress of society and science, building technology is also developing in the direction of intelligence, and the introduction of BIM technology has greatly promoted the development of intelligent buildings in China. The application of BIM technology in the field of intelligent construction is of great significance. It optimises project quality management, accelerates the building delivery process, and improves the operation and maintenance management efficiency of buildings. It is foreseeable that with the arrival of the intelligent era, BIM technology will continue to play an important role and bring more opportunities and challenges to the construction industry. Relevant practitioners should also actively learn and apply this technology to promote the development of the construction industry. This paper is based on a number of typical engineering cases, analyses a large number of existing literature, and reads various working reports and policies issued by the government. It introduces the role of BIM technology in project quality management, intelligent construction delivery and operation and maintenance management, with a view to providing reference for relevant practitioners.

Transformation of Financial Accounting to Management Accounting in the Era of Artificial Intelligence

With the rapid development of the Internet, the era of artificial intelligence has become a trend in today's society, ushering in an intelligent revolution in various industries. The advent of the era of artificial intelligence has laid a solid information foundation and environmental support for the development and progress of the information age, which will greatly impact the traditional working methods and approaches of financial accountants. Basic and repetitive tasks such as issuing invoices and expense reimbursement approvals can be replaced by intelligent machines, allowing financial professionals to focus more on management accounting. The application of artificial intelligence technology can not only improve the efficiency of financial accountants, but also promote the transition from financial accounting to management accounting. Therefore, how to utilize artificial intelligence to assist financial professionals in management accounting work is an inevitable requirement for the development of the intelligent era, which presents more demands for management accounting. Based on this background, the development process of enterprises needs to transform the financial management model, enabling the technical aspects of data collection and organization to move towards more advanced and efficient directions. This article analyzes and studies the strategies for using artificial intelligence to help financial accountants acquire management accounting capabilities, achieve the transformation of financial professionals into management accountants, and provide support for the development of enterprises in the era of artificial intelligence.

Human Rights Dilemma and International Rule of Law in the Age of Digital Intelligence

The digital intelligence era is an intelligent era represented by digital technology. In this era, human attributes, lifestyles, and the embodiment of rights have shown new characteristics. The impact of the digital intelligence era on human rights is a double-edged sword: on the one hand, digital technology, artificial intelligence, and so on greatly liberate human labor productivity, effectively protecting people's rights to subsistence, health, and development; on the other hand, it also brings great threats and challenges to human rights. Anthropocentrism is threatened, the boundaries of human beings are broken, and people's freedom, equality, privacy, labor, intellectual property, environmental and ecological rights are threatened. In the face of the digital intelligence era, development is the only way to break through. In the United Nations Declaration on the Right to Development, the right to development is defined as an inalienable right of human beings. Only in development can all human rights be fully realized