Computer Artificial Intelligence Research Articles

Application Types of Computer Artificial Intelligence Recognition Technology

Application Types of Computer Artificial Intelligence Recognition Technology

The Future of Electric Vehicles: Navigating the Intersection of AI, Cloud Technology, and Cybersecurity

The emergence of electric vehicles (EVs) represents a paradigm shift in transportation, offering not only the promise of reduced carbon emissions but also the potential for enhanced sustainability and innovation. However, the full realization of EVs' transformative capabilities extends beyond mere electrification; it encompasses the integration of state-of-the-art technologies such as Artificial Intelligence (AI) and Cloud Computing. This meticulously crafted research article delves into the profound impact of AI and cloud technologies on the EV landscape within the United States. It meticulously examines how these technological advancements are reshaping EV ecosystems, catalyzing advancements in autonomous driving, optimizing battery management systems, and enriching user experiences. Furthermore, it elucidates the imperative need for robust cybersecurity measures to fortify these sophisticated systems against cyber threats, thereby ensuring the integrity, privacy, and stability of the transportation network. With a diverse audience in mind, including automotive industry professionals, policymakers, cybersecurity experts, environmental advocates, technology enthusiasts, and the broader public, this article serves as a beacon illuminating the future of transportation, sustainability, and digital security within the realm of EVs. Through a blend of rigorous analysis, insightful commentary, and visionary foresight, it aims to provide profound insights into the trajectory of EV technology in the United States and beyond.

Artificial Intelligence Computer Weapon Based True Research on Corona Virus [Covid-19]

Electronic torture, Electromagnetic radiation torture, or Psychotronic torture are terms used by individuals who are targeted by this wireless Synthetic telepathic technology or Direct Energy Weapon [Electromagnetic Radiation weapon]. Wireless Synthetic telepathy technology or Super artificial intelligence computers Criminal operators, often actors or often government employees, agents or crime syndicates, use transmitted electromagnetic radiation (Such as microwave listening effects), satellite technology and surveillance techniques. Wireless Remote Neural Monitoring:  Bridging the gap between brain and technology In the field of neuroscience and technological advancement, the concept of deep tech satellite wireless neural monitoring technology has emerged as an unprecedented innovation weapon. Which has been developed to read and understand the human brain and to interact with the human brain and understand the human body, it is also a wireless direct energy weapon. These deep tech satellite surveillance criminal operators are using this Neurotechnology and wireless Direct Energy Weapons on a large scale against civilians. This true research has been done to protect citizens from illegal deep tech satellite surveillance weapon technology and cyber terrorism. The researcher has presented his research to the whole world in very simple words and in an easy manner. So that the world can easily understand this research and the governments of the countries of the world can protect their citizens from future man-made diseases and viruses.

AUTOMATED HATE SPEECH DETECTION USING RECURRENT NEURAL NETWORK

The rising use of online amusement and information sharing has given critical promotion advantages to humankind. Regardless, this has in like manner prompted various troubles including the spreading likewise, sharing of scorn talk messages. Thus, to tackle this emerging issue in virtual diversion objections, continuous assessments utilized a combination of incorporated planning techniques and artificial intelligence estimations to distinguish the contempt talk messages on different datasets. Nevertheless, suppose, there is no audit to investigate the variety of component planning strategies and Artificial intelligence computations to evaluate which incorporate planning strategy and simulated intelligence estimation beat on a standard transparently open dataset. In the published paper we are going to distinguish discourse utilizing repetitive brain organization. In this system, we get the 87.38% accuracy for 300 epochs. Keywords— Convolutional Neural Network, Deep Learning, Recurrent Neural Network

Integrated cybersecurity for metaverse systems operating with artificial intelligence, blockchains, and cloud computing

In the ever-evolving realm of cybersecurity, the increasing integration of Metaverse systems with cutting-edge technologies such as Artificial Intelligence (AI), Blockchain, and Cloud Computing presents a host of new opportunities alongside significant challenges. This article employs a methodological approach that combines an extensive literature review with focused case study analyses to examine the changing cybersecurity landscape within these intersecting domains. The emphasis is particularly on the Metaverse, exploring its current state of cybersecurity, potential future developments, and the influential roles of AI, blockchain, and cloud technologies. Our thorough investigation assesses a range of cybersecurity standards and frameworks to determine their effectiveness in managing the risks associated with these emerging technologies. Special focus is directed towards the rapidly evolving digital economy of the Metaverse, investigating how AI and blockchain can enhance its cybersecurity infrastructure whilst acknowledging the complexities introduced by cloud computing. The results highlight significant gaps in existing standards and a clear necessity for regulatory advancements, particularly concerning blockchain’s capability for self-governance and the early-stage development of the Metaverse. The article underscores the need for proactive regulatory involvement, stressing the importance of cybersecurity experts and policymakers adapting and preparing for the swift advancement of these technologies. Ultimately, this study offers a comprehensive overview of the current scenario, foresees future challenges, and suggests strategic directions for integrated cybersecurity within Metaverse systems utilising AI, blockchain, and cloud computing.

The coupling and coordination of digital economy and manufacturing transformation and upgrading for industry 5.0 in Hebei Province

In the context of the widespread application of digital technologies such as the Internet, big data, artificial intelligence, and cloud computing, digital transformation in the manufacturing sector has become an important engine to promote high-quality economic development in Hebei Province. This paper aims to objectively analyze the current situation of industrial integration between the Beijing-Tianjin-Hebei digital economy and the manufacturing industry, and conduct level measurement, so as to promote the in-depth integration and development of the digital economy and manufacturing industry in Hebei Province, so that the manufacturing enterprises in Hebei Province can rebuild their competitive advantages in the future development, finally realize digital transformation, and promote the high-quality development of the manufacturing industry in Hebei Province. Therefore, it is very important to carry out empirical research on the integrated development of digital economy and manufacturing industry in Hebei Province. First of all, this paper constructs the index evaluation system of digital economy and manufacturing industry respectively, takes the relevant data of Beijing-Tianjin-Hebei region in recent five years as data samples, uses entropy weight-TOPSIS method to measure the level of digital economy development and manufacturing industry transformation, and uses the coupling coordination degree model to measure the level of industrial integration of the two. The final results show that: (1) The development level of digital economy in Hebei Province fluctuates greatly, and there is still a certain gap with Beijing and Tianjin, but the future development potential of digital economy is huge. (2) The transformation level of manufacturing industry in Hebei Province shows a trend of fluctuation and rise on the whole, and the development trend is good, and the gap between Hebei Province and developed regions is gradually narrowing. (3) The integration of digital economy and manufacturing industry in Hebei Province has a good development trend, but there is still a certain gap with Beijing and Tianjin, and there are problems of inadequate, unstable and unbalanced industrial integration. Finally, based on the research conclusions, suggestions are put forward to promote the coordinated development of Beijing-Tianjin-Hebei region, improve the level of digital economy and manufacturing integration of industrial convergence development, raise the level of digital infrastructure construction, and raise the level of science and technology innovation. This paper reveals the mechanism of digital economy affecting the high-quality development of manufacturing industry, studies the whole process of digitalization, information technology and intelligence integration into the development of manufacturing industry, and fully releases the positive effect of digital economy driving the high-quality development of manufacturing industry, which has important theoretical and practical significance for promoting the high-quality development of manufacturing industry and formulating relevant industrial policies.

Risks and Benefits in Using RPA in Financial Reporting

In the general picture of financial-accounting processes digitization, RPA (Robotic Process Automation) tools are distinguished by a series of characteristics given, mainly, by the ability to replicate human activities. Thus, unlike Artificial Intelligence, Machine Learning or Cognitive Computing, RPA acts primarily in the user interface area based on clearly defined protocols and procedures without compromising or modifying the basis of the IT infrastructure. That's why these solutions are considered non-intrusive, easy to use and cheaper compared to other financial reporting automation technologies. However, beyond more or less quantifiable benefits, these programs carry certain risks whose awareness is essential to achieve the desired goal of automation. This paper, in addition to presenting the opportunities created by aligning RPA to facilitate financial monitoring and reporting efforts, pinpoints a series of challenges or weaknesses of these solutions that, if not properly managed or combated by alternative solutions, can at least lead to the failure of such a project. The practice of the last years together with the diversification of automation solutions already allow the generation of some conclusions as well as the adoption of a cautious approach regarding the attractiveness of RPA in designing and building financial reports.

An Exploratory view of Application of Digital Twin Technology in Education

Digital twins have gained significant attention and become a buzzword in recent years. The advancement of technologies such as the Internet of Things (IoT), artificial intelligence (AI), data analytics, and cloud computing has made it easier and more cost-effective to collect, analyze, and process vast amounts of data. This has enabled the creation and implementation of digital twins on a larger scale. Digital twins provide valuable insights and data- driven information to support decision-making. They enable organizations to simulate scenarios, test different strategies, and assess the impact of changes or interventions before implementing them in the physical world and thus help minimize risks and uncertainties associated with decision- making processes. Applications of Digital twins are not limited to specific industries or sectors. They have versatile applications across domains such as manufacturing, healthcare, transportation, smart cities, energy management etc. This broad applicability has contributed to the widespread interest and buzz around digital twins. The academic world has also not remained untouched with the advancement in this technology and efforts are on in the direction of designing Digital Twins for various aspects of education including supporting teaching, research, and administrative processes. As the technology continues to evolve, new and innovative applications are likely to emerge, transforming various aspects of teaching, learning, research, and administration in the academic sphere. In this study an effort is made to bring together the work carried out in the field of application of digital twins technology for teaching. Existing studies have been deliberated upon to analyze the progress and discover the prospects of bringing the digital teachers closer to human teachers. It can be inferred that as the technology continues to evolve, new and innovative applications are likely to emerge, transforming various aspects of teaching and learning in the academic sphere. It is also important to note that while digital twins of teachers hold potential benefits, their implementation and adoption in real-world educational settings are still developing. Ethical considerations such as data privacy, algorithmic bias, and the need for human involvement in teaching roles needs to be carefully addressed to ensure their effective and equitable use in education

EDITORIAL NOTES: APPLICATION OF COMPUTATIONAL/ARTIFICIAL INTELLIGENCE IN CONCRETE STRUCTURES AND MATERIALS

In recent years, the application of computational/artificial intelligence (CI/AI) in concrete structures and materials has gained popularity as evident in the search in the SCOPUS database using these keywords. The integration of CI/AI in concrete structures marks a significant advancement in civil engineering, offering innovative solutions across various stages of infrastructure development. From analysis and design to construction, monitoring, and maintenance, CI/AI technologies revolutionize traditional practices, enabling engineers to optimize concrete structures for enhanced performance, durability, and sustainability. Material design and optimization in concrete have also been propelled forward by CI/AI technologies. Traditional methods rely on trial-and-error, but CI/AI models analyze vast datasets to identify optimal mixtures with superior properties and resistance to environmental factors. Utilization of supplementary cementitious materials and industrial wastes introduces complexities, addressed by CI/AI's predictive capabilities for short- and long-term concrete properties. By minimizing waste and energy consumption, CI/AI-driven design fosters environmentally friendly formulations while ensuring structural integrity. Overall, CI/AI enhances prediction, optimization, and monitoring, ushering in a new era of resilient and sustainable concrete materials. These advancements also contribute to sustainable development by optimizing material usage, reducing waste, and improving energy efficiency, underscoring CI/AI's transformative potential in shaping the future of concrete structures and materials.

Research on Computer Artificial Intelligence Algorithm to Optimize Physical Training Intensity and Recovery Cycle Model

Research on Computer Artificial Intelligence Algorithm to Optimize Physical Training Intensity and Recovery Cycle Model

Enabling lightweight immersive user interaction in smart buildings through learning-based mobile panorama streaming

Smart buildings integrate users’ digitized wearables with their physical surroundings, creating a seamless and interactive user experience. This is achieved through the utilization of multiple sensors, video streaming, artificial intelligence, and edge computing. These technologies gather extensive data and provide users with a wide range of applications, such as 3D audio/video in AR/VR, localization, virtual tours, and vigilant monitoring. Nevertheless, the current AR/VR devices face limitations due to the bulkiness and discomfort of the hardware used for on-body sensing, such as headsets and specialized glasses. These components often become uncomfortable during prolonged usage, posing a challenge for creating an immersive system that combines lightweight interaction with high-quality presentation.This paper presents a comprehensive system designed to enable immersive interaction in smart buildings with a focus on lightweight solutions. The system consists of the following components: (1). A lightweight panoramic imaging framework to address the challenges related to hardware size and functionality. (2). A learning-based video transcoding cost prediction framework for efficient load balancing. (3). A layered networking architecture designed to facilitate high-quality mobile panorama live streaming. Collectively, these components offer lightweight interaction paired with enhanced presentation quality. Our experimental results demonstrate the effectiveness of the system design, showcasing its seamless operation across different times, geographical locations, and heterogeneous wireless networks.

The Application Strategy of Intelligent Computer Multimedia Technology in Film and Television Post Production

<p>The development of short videos and big movies requires high-quality visual design. In the context of digital technology development, computer multimedia technology has begun to emerge in the field of video processing, promoting innovative development in China’s industry. The post production of film and television works requires the use of computer multimedia technology to expand the creative space and improve the artistic expression effect of film and television works. This article elaborates on the unique role of computer multimedia technology in the field of film and television post production, and then analyzes the various stages of film and television post production. The focus is on using computer artificial intelligence techniques to improve the quality and efficiency of video editing in the video editing stage. Then, in the color rendering stage of some black and white video resources, computer technology is automatically processed, Therefore, computer multimedia technology can play an advantageous role in film and television post production and should be promoted and applied.</p> <p> </p>

Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery

BackgroundIntraoperative hypotension during cesarean section has become a serious complication for maternal and fetal healthy. It is commonly encountered by subarachnoid anesthesia. However, currently used control methods have varying degrees of side effects, such as drugs. The Root Cause Analysis (RCA) - Plan, Do, Check, Act (PDCA) is a new model of care that identifies the root causes of problems. The study aimed to demonstrate the usefulness of RCA-PDCA nursing methods in preventing intraoperative hypotension during cesarean section and to predict the occurrence of intraoperative hypotension through a machine learning model. MethodsPatients who underwent cesarean section at Traditional Chinese Medicine of Southwest Medical University from January 2023 to December 2023 were retrospectively screened, and the data of their gestational times, age, height, weight, history of allergies, intraoperative vital signs, fetal condition, operative time, fluid out and in, adverse effects, use of vasopressor drugs, anxiety-depression-pain scores, and satisfaction were collected and analyzed. The statistically different features were screened and five machine learning models were used as predictive models to assess the usefulness of the RCA-PDCA model of care. Results(1) Compared with the general nursing model, the RCA-PDCA nursing model significantly reduces the incidence of intraoperative hypotension and postoperative complications in cesarean delivery, and the patient experience is comfortable and satisfactory. (2) Among the five machine learning models, the RF model has the best predictive performance, and the accuracy of the random forest model in preventing intraoperative hypotension is as high as 90%. ConclusionThrough computer machine learning model analysis, we prove the importance of the RCA-PDCA nursing method in the prevention of intraoperative hypotension during cesarean section, especially the Random Forest model which performed well and promoted the application of artificial intelligence computer learning methods in the field of medical analysis.

Knowledge digitization and high-tech firm performance: A moderated mediation model incorporating business model innovation and entrepreneurial orientation

In today's rapidly evolving digital landscape, knowledge digitization, facilitated by advanced tools such as artificial intelligence, big data, blockchain, and cloud computing, has captured significant scholarly attention. To comprehensively explore the implications and outcomes of this knowledge digitization trend, our study delves into its impact on the performance of high-tech firms. Based on the knowledge-based view, we develop a moderated mediation model to examine the mediating role of business model innovation and the moderating effect of entrepreneurial orientation in the relationship between knowledge digitization and firm performance. To test our hypotheses, we employ the PLS-SEM method, analyzing data from a sample of 291 Chinese high-tech firms. Our findings indicate that knowledge digitization has a positive effect on firm performance, and both types of business model innovation—novel and efficient—partially mediate the positive relationship. Additionally, entrepreneurial orientation is found to strengthen the relationship between knowledge digitization and business model innovation. However, it does not significantly moderate the connection between knowledge digitization and firm performance. Our research offers actionable insights for strategic development in the digital era and makes a substantial contribution to the existing body of knowledge in this field.

국내외 인공지능 반도체에 대한 연구 동향

Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

Frontiers of Computing - Evolutionary Trends and Cutting-Edge Technologies in Computer Science and Next Generation Application

The cutting edge of computing is always changing because people are always looking for new ways to do things and combining cutting-edge tools. There are a number of natural trends that will affect the next generation of apps. Quantum computing is one of the most important trends. It is a new way of doing things that uses the rules of quantum physics to do calculations at speeds that are impossible with regular computers. Quantum computing could help solve hard issues in security, optimization, and modeling, which would lead to new science discoveries and technological progress.Neuromorphic computing, which is based on the structure of the human brain, is another new realm. The goal of this revolutionary way of computing is to create artificial neural networks that can learn, change, and process information in ways that are similar to how biological systems do it. There is a lot of promise for neuromorphic computing to improve machine learning and make AI apps more efficient and complex.The world of computing is also changing because artificial intelligence (AI) and edge computing are coming together. Edge computing brings computing power closer to the data source, which lowers delay and improves real-time processing. This is why it is so important for the growth of technologies like self-driving cars, smart cities, and the Internet of Things (IoT).Adding blockchain technology is another step forward that will make sure deals in open systems are safe and clear. Blockchain is used for more than just cryptocurrency. It has an impact on supply chain management, healthcare, and banking, among other areas. The quantum computing, neuromorphic computing, the combination of AI and edge computing, and the use of blockchain technology are all on the cutting edge of computing. Together, these trends bring computer science into a new era and lay the groundwork for groundbreaking uses that will shape the future of technology.

Analysis of computational power as a potential breakthrough in advancing AI technology

The term Artificial Intelligence(AI) has become more common in view recently. The performance and fame of ChatGPT brought a new AI fever to present industries with multiple big companies announcing their upcoming AI plans. People are arguing about whether AI will help them or steal their jobs. It seems that AI will be, if not have been, walking into peoples daily lives. As a result, this article analyzes the current challenges and potential future breakthroughs of Artificial intelligence by focusing on one of the most fundamental factors that support the development and operation of AIcomputational power. This article analyzes the relationship between AI performance and computer performance from different eras particularly. It summarizes and analyzes several sources published in related fields. The primary purpose of this article is to provide people with a better overview of present AI technology by taking a close look at the history, present difficulties, and potential solutions of AI and computational power and concludes with possibilities of each solution and expected futures of the AI industry. This paper concludes that the development of AI relies on the computer performance acquired by the industry. Finding a way to obtain better computer performance at a lower cost might be the next breakthrough in the AI industry.

Research on Ferrographic Image Fault Diagnosis Based on Channel Overlapping Technique and Information Fusion Mechanism

Abstract Utilizing computer technology to realize the application of ferrographic intelligent fault diagnosis technology is a foundational investigation to oversee the operations of mechanical equipment. To continuously improve the accuracy of artificial intelligence recognition, the complexity and computation of the model will be increased. The proposal of the transformer model (the core technology of chatgpt) has fundamentally changed the intelligence level of artificial intelligence, but it has also greatly increased the demand for computer computing power. What's more, it is difficult to equip industrial quality inspection sites with high computing power computers. The channel overlapping technique developed in this paper is a technology to segment the three channels of image information and reserve overlapping areas for an information communication mechanism. With this mechanism, the model location channel overlapping convolutional neural network can obtain high recognition accuracy by using only one-half of the original training computing power. When channel overlapping combines with no position information, information fusion is formed. The model channel overlapping technique fusion convolutional neural network established by the information fusion mechanism will get a higher prediction accuracy through joint training with the original image. However, the computation consumption is nearly one-third of the pure traditional convolutional neural network algorithm.

Edge AI for Internet of Medical Things: A literature review

The Internet of Things (IoT) consists of heterogeneous devices such as wearables and monitoring devices that collect data to provide autonomous decision-making and smart applications. IoT technologies, such as the Internet of Medical Things (IoMT), have become gradually popular for medical purposes, combining IoT and medical devices to achieve good health and well-being. However, IoMT devices are often tight and have resource constraints, which leads to limited local data processing in the device. Edge computing provides access to additional computation and storage resources for IoMT devices, bringing intelligent processing closer to the data sources. This technology opens up great possibilities for IoMT applications, especially when combined with Artificial Intelligence (AI). Edge AI runs AI computations close to the IoT devices and users instead of centralized services such as cloud servers. This paper investigates the potential of Edge AI and IoMT. In this sense, this survey is the first work to further detail Edge AI and Machine Learning Operations in IoMT domains and wearable technology, thus contributing to the literature by comprehensively exploring the potential of ML strategies and operations at the network’s edge and intelligence distribution. This study also presents a case study on heart anomaly detection.

Aligning restaurants and artificial intelligence computing of food delivery service with product development

Purpose This study aims to analyze how restaurants' collaboration with mobile food delivery applications (MFDAs) affects product development efficiency and argues that technological capabilities moderate relational ties impact the joint decision-making and development efficiency of restaurant products. Design/methodology/approach A product development efficiency model was formulated using a resource-based view and real options theory. In all, 472 samples were collected from restaurants collaborating with MFDAs, and partial least squares structural equation modeling was applied to the proposed model. Findings The findings of this study indicate three factors are critical to the product development efficiency between restaurants and MFDAs; restaurants must develop a strong connection with the latter to ensure meals are consistently served promptly. Developers of MFDAs should use artificial intelligence analysis, such as order records of different genders and ages or various consumption attributes, to collaborate with restaurants. Originality/value To the best of the authors’ knowledge, this study is one of the few that considers the role of MFDAs as a product strategy for restaurant operations, and the factors the authors found can enhance restaurants’ product development efficiency. Second, as strategic artificial intelligence adaptation changes, collaborating firms and restaurants use such applications for product development to help consumers identify products.