Artificial Intelligence Environment Research Articles

Research on the Design and Application of Henan Museum Jade Carving Cultural and Creative Products Based on Big Data Analysis in the Artificial Intelligence Environment

In the enduring tapestry of China’s rich and ancient civilization, the jade culture has unfolded hand in hand with the progression of Chinese society, with the art of jade carving representing its very essence. Through millennia of refinement, jade carving has reached a pinnacle of artistic expression. In today’s era characterized by the rapid advancement of artificial intelligence, the strategic utilization of AI technology and comprehensive data analysis has become pivotal in creating jade sculptures that resonate more deeply with contemporary tastes. In the present age, excessively traditional jade carving designs no longer fully meet the aesthetic demands of contemporary individuals, thus hampering the advancement of the jade carving industry. In order to effectively disseminate Chinese jade culture on a broader scale and foster the growth of the jade industry, it necessitates designers harnessing artificial intelligence technology and utilizing methodologies of big data analysis to create products infused with innovative cultural symbols and contemporary imprints. ade carving products embody distinctive traditional cultural attributes of China, where the key to modern jade carving creative design lies in seamlessly blending traditional cultural artistry with contemporary aesthetic values. Artificial intelligence technology offers excellent facilitative conditions for the innovation and advancement of jade carving. Only by striving for breakthroughs to meet the psychological consumption demands of the new era can we more effectively foster development. His paper, within the realm of artificial intelligence and based on the perspective of big data analysis, conducts a thorough examination and analysis of the existing cultural and creative products developed by the Henan Museum, utilizing elements from its collection of cultural relics. It summarizes the current status and challenges present in the design of cultural and creative jade carving products at the Henan Museum. Finally, it puts forth relevant opinions and recommendations addressing these issues. Furthermore, it aims to provide insights for the development and innovation of cultural and creative products in other museums, offering valuable experiences in this regard.

The Human Digi-real Duality

Current technologies allow acquiring whatever amount of data (even big data), from whatever system (object, component, mechanism, network, implant, machinery, structure, asset, etc.), during whatever time lapse (secs, hours, weeks, years). Therefore, potentially it is possible to fully characterize any system for any time we need, with the possible consequence of creating a virtual copy, namely the digital twin (DT) of the system. When technology of DT meets an augmented reality scenario, the augmented digital twin (ADT) arises, when DT meets an artificial intelligence environment, the intelligent digital twin (IDT) arises. DTs, ADTs and IDTs are successfully adopted in electronics, mechanics, chemistry, manufacturing, science, sport, and more, but when adopted for the human body it comes out the human digital twin (HDT) or alternatively named virtual human simulator (VHS). When the VHS incorporates information from surroundings (other VHSs and environment), taking a cue from the particle-wave duality (the mix of matter and energy), we can name this super-VHS as the human digi-real duality (HDRD). This work is focused on defining the aforementioned acronyms, on evidencing their differences, advantages and successful case adoptions, but highlighting technology limits too, and on foreseeing new and intriguing possibilities.

Linguistic analysis for occupational risk assessment communication using the Lpac in an AI environment

Risk assessment methodologies results in construction sector are usually reported within a very limited linguistic context of preventive action, which may involve interpretation difficulties. This research identifies the problem of risk assessment methodologies to linguistically convey the results of risk assessment to construction workers. The methodology adapted to construction sites called Level of Preventive Action (Lpac) determines levels of preventive action control related to a spectrum of quantitative results, with data collection based on physical conditions of the environment with sensors in the construction and safety systems; and behavioural conditions and worker emotional state with body sensors, locators and integrating with the BIM approach. The communication of the results must be adapted to the multiple variables that occur in a communicative interaction. The Lpac method proposes a broad spectrum of preventive action control conditions on the physical and human environment that are transmitted to the worker, which allows for different communicative possibilities. In this sense, safety is assessed concerning the different risks involved in work performance, applying control banding concepts. Optimising the physical and human environment in real time is essential through devices that generate a complex human-machine interaction within an artificial intelligence environment in the construction sector.

Investigation of the Evaluation System of General Education in Higher Vocational Colleges under the Artificial Intelligence Environment

Investigation of the Evaluation System of General Education in Higher Vocational Colleges under the Artificial Intelligence Environment

Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment

Abstract Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES.

Retracted: Vehicle Safety-Assisted Driving Technology Based on Computer Artificial Intelligence Environment.

[This retracts the article DOI: 10.1155/2022/4390394.].

Human intelligence for authors, reviewers and editors using artificial intelligence

We call artificial intelligence any machine that processes information with some purpose, complying with the logical rules of Turing's computation described more than 70 years ago. These machines work with instructions called algorithms, a finite and well-defined sequence of information processing implemented by automata (computers) or any digital technology to optimize a process. (2) This means that the purpose of artificial intelligence is optimization. Optimization is the ability to do or solve something in the most efficient way possible and, in the best case, using the least amount of resources. The intended optimization is programmed and preset by humans; therefore, these technologies are tools humans create for human purposes. The optimization capability of artificial intelligence is staggering. It is estimated that using artificial intelligence will facilitate the achievement of 134 of the 169 goals agreed in the 2030 Agenda for Sustainable Development. However, in this evaluation, it was projected that it could negatively affect the progress of 59 goals of the same agreement, being social, economic, educational, legal and gender inequality, the phenomenon most affected by artificial intelligence. This projection shows us that it is necessary to counterbalance the development and implementation of processes mediated by artificial intelligence, to maintain reflection and question the influence of these technological tools, and, above all, to be based on human intelligence. A definition of human intelligence in the data science and artificial intelligence environment would be a collection of contextual tacit knowledge about human values, responsibility, empathy, intuition, or care for another living being that algorithms cannot describe or execute.

MINDFUL UX DESIGN IN INDUSTRY 4.0: MITIGATING ADDICTION AND ENHANCING USER WELL-BEING INSOCIAL MEDIA AND AI ENVIRONMENTS

The rapid advancements in technology under Industry 4.0 bring forth both opportunities and challenges, particularly in User Experience (UX) design in social media and Artificial Intelligence (AI) environments. This research paper explores these dichotomies, focusing primarily on the role of UX design in mitigating addiction and enhancing user well-being. In this paper, authors begin by exploring the historical evolution of UX design and its increasing importance in the context of technological progression. We then discuss the psychological impacts of UX design on users, drawing a parallel between addictive characteristics of social media platforms and AI-based systems, and the deterioration of user well-being. Recognizing the gravity of the situation, we delve into the concept of 'Responsible UX Design,' a design philosophy that focuses on developing interfaces and systems that foster positive user behaviour while minimizing the risk of digital addiction. Authors present a comprehensive analysis of current strategies, practices, and policies related to responsible UX design in Industry 4.0 and discuss how these could be evolved for future. Drawing on a wide range of case studies, user interviews, and psychological research, the paper provides actionable recommendations for businesses, policymakers, and UX designers. These recommendations promote responsible design practices, discourage addictive design patterns, and encourage user-centric design approaches that improve digital well-being. Additionally, this paper provides a critical review of the challenges and potential ethical considerations in implementing responsible UX design. It introduces the concept of 'Digital Ethics,' which requires organizations and designers to uphold user well-being as a primary consideration during the design process. In conclusion, this research emphasizes the need for a paradigm shift towards responsible UX design, both as a moral obligation and as a competitive advantage in Industries 4.0. It advocates for an approach that balances user engagement with user well-being, and ensures that technological innovations enhance, rather than compromise, human lives. Unprecedented technical developments, including the fusion of social media platforms and artificial intelligence (AI), have been made possible by industry 4.0. User experience (UX) design now faces ethical and societal repercussions as a result of these developments. This paper provides a thorough examination of responsible UX design in Industry 4.0, with a particular emphasis on the growing usage of social media and AI tools. The research emphasizes the significance of ethical issues while examining recent information, trends, and best practices in UX design. Unprecedented technical developments, including the fusion of social media platforms and artificial intelligence (AI), have been made possible by industry 4.0. User experience (UX) design now faces ethical and societal repercussions as a result of these developments. This article provides a thorough examination of responsible UX design in Industry 4.0, with a particular emphasis on the growing usage of social media and AI tools. The research emphasizes the significance of ethical issues while examining recent information, trends, and best practices in UX design.

초등학생의 미디어 활용 및 학교 교육 실태연구

This study examined the perceptions and attitudes of elementary school students in Korea facing a generative artificial intelligence environment in the digital media environment. At the level of the national curriculum in Korea, this study looked at the current status of software education encountered by elementary school students, and analyzed surveys on smartphone use, YouTube and online/mobile games for 4th, 5th, and 6th graders. As a result of the study, there was more time spending to watch YouTube related to non-learning than learning, and the trust in the information encountered on YouTube was high. As a result of a survey on media education experience, the proportion of students who received “education on how to distinguish whether information provided online is true or not” was lower than that of other media education. Therefore, the ability to understand and evaluate the media does not arise by itself as time increases, and it requires a critical perspective and conscious effort to acquire and use information. Finally, it is important to raise awareness of the education students received.

Retracted: College English Teaching Mode Based on Output-Oriented Method in Artificial Intelligence Environment

Retracted: College English Teaching Mode Based on Output-Oriented Method in Artificial Intelligence Environment

Retracted: Cognitive Computing Model Based on Machine Learning Algorithm in Artificial Intelligence Environment

Retracted: Cognitive Computing Model Based on Machine Learning Algorithm in Artificial Intelligence Environment

Towards the ultimate brain: Exploring scientific discovery with ChatGPT AI

AbstractThis paper presents a novel approach to scientific discovery using an artificial intelligence (AI) environment known as ChatGPT, developed by OpenAI. This is the first paper entirely generated with outputs from ChatGPT. We demonstrate how ChatGPT can be instructed through a gamification environment to define and benchmark hypothetical physical theories. Through this environment, ChatGPT successfully simulates the creation of a new improved model, called GPT4, which combines the concepts of GPT in AI (generative pretrained transformer) and GPT in physics (generalized probabilistic theory). We show that GPT4 can use its built‐in mathematical and statistical capabilities to simulate and analyze physical laws and phenomena. As a demonstration of its language capabilities, GPT4 also generates a limerick about itself. Overall, our results demonstrate the promising potential for human‐AI collaboration in scientific discovery, as well as the importance of designing systems that effectively integrate AI's capabilities with human intelligence.

Retracted: Human Resource Data Integration System Based on Artificial Intelligence Environment.

[This retracts the article DOI: 10.1155/2022/1650583.].

Retracted: Design of Integrated Management System of IPE Instructional Resources Information Based on Artificial Intelligence Environment.

[This retracts the article DOI: 10.1155/2022/4594090.].

Capital Accumulation Dynamics

The article discusses the scheme of K. Marxian expanded reproduction through the prism of the capital accumulation analysis by R. Luxembourg taking into account of the infrastructure impact on the development of capitalism. The author gives examples of the 21st century infrastructure, in par ticular he examines multilateral platforms — payment systems for cross-border payments, associated with broadband satellite Internet access and an ar tificial intelligence environment.

Design of artificial intelligence image encryption algorithm based on hyperchaos

The artificial intelligence is an inevitable breakthrough direction, and the privacy protection of images in the artificial intelligence environment has become a hotspot. An image encryption algorithm that can be applied in the AI-based work combining compression sensing with Rabinovich hyperchaos is proposed. Firstly, the plaintext image will be transformed into a sparse form by DWT transform. With the improved hyperchaotic sequence, the double reset mechanism of the bit plane and the encryption engine function are designed to perform circular diffusion operation. Finally, the combined random Gaussian measurement matrix will perform compressed sensing sampling on the encrypted image. Simulation experiments show that the encryption algorithm can pass the plaintext sensitivity test (with the NPCR of 0.9978 and the UACI of 0.3337), the correlation test (with the best result of −0.0021), and the information entropy test (with the result of 7.9987), which shows high security to resist several types of attacks.

Self-Powered Electronic Skin for Remote Human–Machine Synchronization

Human–machine interaction (HMI) allows the transfer of human intent to the robot and the collection of feedback from the robot. Human perception of the outside world is a direct response to human brain training, but low-level perception movements of robots are more complex than advanced reason. In the study, we designed a self-powered electronic skin (SPES) based on a piezoelectric nanogenerator (PENG). SPES shows a good piezoelectric effect and certain mechanical flexibility and can realize gesture recognition and tracking by sensing external pressure stimulation in HMI. Through the feedback control of the closed-loop system, the equivalent behavior trigger of the real intelligent robotic capacitive touch sensors (CATS) and SPES can be realized. SPES and Robot Hall Rotary Position Sensor (HRPS) have small perceptual errors, and remote signal feedback and behavior control of intelligent robots are realized by wireless transmission equipment, which is a greater advantage in a flexible environment. The proposed SPES tracking application in the HMI has great potential in the future artificial intelligence environment, the auxiliary equipment for people with disabilities, and the human–machine cooperation in a flexible environment.

ВАРИАНТЫ РЕАЛИЗАЦИИ МАШИННОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ В ПРОГРАММЕ АNУLОGIС

Artificial intelligence methods are widely applied in the detection of type problems. There are many variations of machine learning, among which reinforcement learning occupies a special place. At present, there is no answer to the teacher's question, but there is a response from the environment. Such environments can be real (for example, on random roads, in confined airspace, or on a training assembly line) or natural. Simulation software tools allow you to create realistic artificial intelligence environments, safely train and test learning agents. Including such approaches to solving various business problems. This article is devoted to the analysis of implementation options for a coupling simulation model with machine learning with reinforcement, used in the proposed software product, to identify their features, shortcomings and shortcomings.

Comparison of Named Data Networking Mobility Methodology in a Merged Cloud Internet of Things and Artificial Intelligence Environment.

In-network caching has evolved into a new paradigm, paving the way for the creation of Named Data Networking (NDN). Rather than simply being typical Internet technology, NDN serves a range of functions, with a focus on consumer-driven network architecture. The NDN design has been proposed as a method for replacing Internet Protocol (IP) addresses with identified content. This study adds to current research on NDN, artificial intelligence (AI), cloud computing, and the Internet of Things (IoT). The core contribution of this paper is the merging of cloud IoT (C-IoT) and NDN-AI-IoT. To be precise, this study provides possible methodological and parameter explanations of the technologies via three methods: KITE, a producer mobility support scheme (PMSS), and hybrid network mobility (hybrid NeMO). KITE uses the indirection method to transmit content using simple NDN communication; the PMSS improves producer operation by reducing handover latency; and hybrid NeMO provides a binding information table to replace the base function of forwarding information. This study also describes mathematical equations for signaling cost and handover latency. Using the network simulator ndnSIM NS-3, this study highlights producer mobility operation. Mathematical equations for each methodology are developed based on the mobility scenario to measure handover latency and signaling cost. The results show that the efficiency of signaling cost for hybrid NeMO is approximately 4% better than that of KITE and the PMSS, while the handover latency for hybrid NeMO is 46% lower than that of KITE and approximately 60% lower than that of the PMSS.

Design of Integrated Management System of IPE Instructional Resources Information Based on Artificial Intelligence Environment.

With the development of modern networks and their fast and convenient characteristics, the construction of instructional resources has become the focus of information construction in universities. Based on AI (Artificial intelligence) technology, this paper discusses the software development technology used in the comprehensive management system of IPE instructional resources. According to the application environment and application objects of the system, a comprehensive information management system of IPE instructional resources based on AI technology is constructed. In this paper, a concept similarity algorithm based on semantic similarity and semantic correlation is proposed to calculate the distance between words and establish concept mapping pairs. The semantic analysis of the information input by students is realized, and the proposed concept similarity algorithm is used in the domain ontology knowledge base to search for similar courses and recommend them to students for their choice. The test results show that the stability of this system can reach about 96%, which is about 10% higher than other systems. The comprehensive management system of instructional resources information proposed in this paper will promote educators and learners to find high-quality IPE instructional resources.