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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering 被引量:13
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作者 Fei-Yue Wang Qinghai Miao +6 位作者 Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan Yonglin Tian Qing-Long Han 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第4期809-815,共7页
DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in... DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning. 展开更多
关键词 SOMETHING intelligence replace
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A review of artificial intelligence applications in high-speed railway systems 被引量:2
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作者 Xuehan Li Minghao Zhu +3 位作者 Boyang Zhang Xiaoxuan Wang Zha Liu Liang Han 《High-Speed Railway》 2024年第1期11-16,共6页
In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,e... In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions. 展开更多
关键词 High-speed railway Artificial intelligence intelligent distribution intelligent control intelligent scheduling
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Toward a Learnable Climate Model in the Artificial Intelligence Era 被引量:2
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作者 Gang HUANG Ya WANG +3 位作者 Yoo-Geun HAM Bin MU Weichen TAO Chaoyang XIE 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第7期1281-1288,共8页
Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of ... Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal. 展开更多
关键词 artificial intelligence deep learning learnable climate model
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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence 被引量:1
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作者 Tianyu Shen Jinlin Sun +4 位作者 Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第6期1313-1316,共4页
THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to pos... THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real environments.In this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5]. 展开更多
关键词 intelligence DAO TAO
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Automation 5.0: The Key to Systems Intelligence and Industry 5.0 被引量:1
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作者 Ljubo Vlacic Hailong Huang +10 位作者 Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第8期1723-1727,共5页
AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with machinery.The rise of steam engines and water wheels represented the f... AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with machinery.The rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:L.Vlacic,H.Huang,M.Dotoli,Y.Wang,P.Ioanno,L.Fan,X.Wang,R.Carli,C.Lv,L.Li,X.Na,Q.-L.Han,and F.-Y.Wang,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA J.Autom.Sinica,vol.11,no.8,pp.1723-1727,Aug.2024. 展开更多
关键词 AUTOMATION MACHINERY intelligence
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Artificial Intelligence and Computer Vision during Surgery: Discussing Laparoscopic Images with ChatGPT4—Preliminary Results 被引量:1
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作者 Savvas Hirides Petros Hirides +1 位作者 Kouloufakou Kalliopi Constantinos Hirides 《Surgical Science》 2024年第3期169-181,共13页
Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce... Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce. Aim: To test a novel AI commercially available tool for image analysis on a series of laparoscopic scenes. Methods: The research tools included OPENAI CHATGPT 4.0 with its corresponding image recognition plugin which was fed with a list of 100 laparoscopic selected snapshots from common surgical procedures. In order to score reliability of received responses from image-recognition bot, two corresponding scales were developed ranging from 0 - 5. The set of images was divided into two groups: unlabeled (Group A) and labeled (Group B), and according to the type of surgical procedure or image resolution. Results: AI was able to recognize correctly the context of surgical-related images in 97% of its reports. For the labeled surgical pictures, the image-processing bot scored 3.95/5 (79%), whilst for the unlabeled, it scored 2.905/5 (58.1%). Phases of the procedure were commented in detail, after all successful interpretations. With rates 4 - 5/5, the chatbot was able to talk in detail about the indications, contraindications, stages, instrumentation, complications and outcome rates of the operation discussed. Conclusion: Interaction between surgeon and chatbot appears to be an interesting frontend for further research by clinicians in parallel with evolution of its complex underlying infrastructure. In this early phase of using artificial intelligence for image recognition in surgery, no safe conclusions can be drawn by small cohorts with commercially available software. Further development of medically-oriented AI software and clinical world awareness are expected to bring fruitful information on the topic in the years to come. 展开更多
关键词 Artificial intelligence SURGERY Image Recognition Autonomous Surgery
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Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease 被引量:1
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作者 Yan Pan Fu-Yong Jiao 《World Journal of Clinical Cases》 SCIE 2024年第23期5304-5307,共4页
This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Cl... This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture. 展开更多
关键词 Artificial intelligence Kawasaki disease DIAGNOSIS PREDICTION IMAGE
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Integrating artificial intelligence and high-throughput phenotyping for crop improvement 被引量:1
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作者 Mansoor Sheikh Farooq Iqra +3 位作者 Hamadani Ambreen Kumar A Pravin Manzoor Ikra Yong Suk Chung 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第6期1787-1802,共16页
Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have rev... Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI. 展开更多
关键词 artificial intelligence crop improvement data analysis high-throughput phenotyping machine learning precision agriculture trait selection
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Artificial intelligence-driven radiomics study in cancer:the role of feature engineering and modeling 被引量:1
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作者 Yuan-Peng Zhang Xin-Yun Zhang +11 位作者 Yu-Ting Cheng Bing Li Xin-Zhi Teng Jiang Zhang Saikit Lam Ta Zhou Zong-Rui Ma Jia-Bao Sheng Victor CWTam Shara WYLee Hong Ge Jing Cai 《Military Medical Research》 SCIE CAS CSCD 2024年第1期115-147,共33页
Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of... Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’anatomy.However,the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.Moreover,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical practice.In contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical endpoints.Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research. 展开更多
关键词 Artificial intelligence Radiomics Feature extraction Feature selection Modeling INTERPRETABILITY Multimodalities Head and neck cancer
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A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT 被引量:1
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作者 Yifan Liu Shancang Li +1 位作者 Xinheng Wang Li Xu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第8期1233-1261,共29页
The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated... The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats. 展开更多
关键词 Cyber security Industrial Internet of Things artificial intelligence machine learning algorithms hybrid cyber threats
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Exploration of Graduate Student Cultivation Mode of Landscape Architecture under the Background of“Artificial Intelligence+X” 被引量:1
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作者 CAO Yangyang ZENG Junfeng 《Journal of Landscape Research》 2024年第1期67-69,76,共4页
Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper anal... Under the background of“artificial intelligence+X”,the development of landscape architecture industry ushers in new opportunities,and professional talents need to be updated to meet the social demand.This paper analyzes the cultivation demand of landscape architecture graduate students in the context of the new era,and identifies the problems by comparing the original professional graduate training mode.The new cultivation mode of graduate students in landscape architecture is proposed,including updating the target orientation of the discipline,optimizing the teaching system,building a“dualteacher”tutor team,and improving the“industry-university-research-utilization”integrated cultivation,so as to cultivate high-quality compound talents with disciplinary characteristics. 展开更多
关键词 Artificial intelligence+ Landscape architecture Graduate training model Professional talent
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Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges 被引量:2
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作者 Yang Guo Liying Sun +3 位作者 Wenyao Zhong Nan Zhang Zongxuan Zhao Wen Tian 《Neural Regeneration Research》 SCIE CAS CSCD 2024年第3期663-670,共8页
Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on p... Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies. 展开更多
关键词 artificial intelligence artificial prosthesis medical-industrial integration brain-machine interface deep learning machine learning networked hand prosthesis neural interface neural network neural regeneration peripheral nerve
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Multi-level intelligence empowering lithium-ion batteries
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作者 Guangxu Zhang Jiangong Zhu +1 位作者 Haifeng Dai Xuezhe Wei 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第10期535-552,I0011,共19页
With the significant and widespread application of lithium-ion batteries,there is a growing demand for improved performances of lithium-ion batteries.The intricate degradation throughout the whole lifecycle profoundly... With the significant and widespread application of lithium-ion batteries,there is a growing demand for improved performances of lithium-ion batteries.The intricate degradation throughout the whole lifecycle profoundly impacts the safety,durability,and reliability of lithium-ion batteries.To ensure the long-term,safe,and efficient operation of lithium-ion batteries in various fields,there is a pressing need for enhanced battery intelligence that can withstand extreme events.This work reviews the current status of intelligent battery technology from three perspectives:intelligent response,intelligent sensing,and intelligent management.The intelligent response of battery materials forms the foundation for battery stability,the intelligent sensing of multi-dimensional signals is essential for battery management,and the intelligent management ensures the long-term stable operation of lithium-ion batteries.The critical challenges encountered in the development of intelligent battery technology from each perspective are thoroughly analyzed,and potential solutions are proposed,aiming to facilitate the rapid development of intelligent battery technologies. 展开更多
关键词 Battery intelligence intelligent response intelligent sensing intelligent management
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Explainable Artificial Intelligence(XAI)Model for Cancer Image Classification
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作者 Amit Singhal Krishna Kant Agrawal +3 位作者 Angeles Quezada Adrian Rodriguez Aguiñaga Samantha Jiménez Satya Prakash Yadav 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第10期401-441,共41页
The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare environments.It is to make sure that decisions are based on trustworthy algorithms and ... The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare environments.It is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these algorithms.These models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial intelligence.Nevertheless,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer images.This research presents an advanced investigation of XAI models to classify cancer images.It describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare applications.In addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging techniques.The proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive explanation.The proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%DOR.It will discuss the potential applications of the proposed XAI models in the smart healthcare environment.It will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment. 展开更多
关键词 Explainable artificial intelligence artificial intelligence XAI healthcare CANCER image classification
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Artificial intelligence in individualized retinal disease management
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作者 Zi-Ran Zhang Jia-Jun Li Ke-Ran Li 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2024年第8期1519-1530,共12页
Owing to the rapid development of modern computer technologies,artificial intelligence(AI)has emerged as an essential instrument for intelligent analysis across a range of fields.AI has been proven to be highly effect... Owing to the rapid development of modern computer technologies,artificial intelligence(AI)has emerged as an essential instrument for intelligent analysis across a range of fields.AI has been proven to be highly effective in ophthalmology,where it is frequently used for identifying,diagnosing,and typing retinal diseases.An increasing number of researchers have begun to comprehensively map patients’retinal diseases using AI,which has made individualized clinical prediction and treatment possible.These include prognostic improvement,risk prediction,progression assessment,and interventional therapies for retinal diseases.Researchers have used a range of input data methods to increase the accuracy and dependability of the results,including the use of tabular,textual,or image-based input data.They also combined the analyses of multiple types of input data.To give ophthalmologists access to precise,individualized,and high-quality treatment strategies that will further optimize treatment outcomes,this review summarizes the latest findings in AI research related to the prediction and guidance of clinical diagnosis and treatment of retinal diseases. 展开更多
关键词 artificial intelligence artificial intelligence in ophthalmology retinal disease
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Advancements in Barrett's esophagus detection:The role of artificial intelligence and its implications
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作者 Sara Massironi 《World Journal of Gastroenterology》 SCIE CAS 2024年第11期1494-1496,共3页
Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utili... Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings. 展开更多
关键词 Barrett's esophagus Artificial intelligence Endoscopic images Artificial intelligence model Early cancer detection ENDOSCOPY
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Intelligent Transformation: General Intelligence Theory
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作者 Alexander Ngu Amaya Odilon Kosso 《International Journal of Intelligence Science》 2024年第3期59-70,共12页
This paper aims to formalize a general definition of intelligence beyond human intelligence. We accomplish this by re-imagining the concept of equality as a fundamental abstraction for relation. We discover that the c... This paper aims to formalize a general definition of intelligence beyond human intelligence. We accomplish this by re-imagining the concept of equality as a fundamental abstraction for relation. We discover that the concept of equality = limits the sensitivity of our mathematics to abstract relationships. We propose a new relation principle that does not rely on the concept of equality but is consistent with existing mathematical abstractions. In essence, this paper proposes a conceptual framework for general interaction and argues that this framework is also an abstraction that satisfies the definition of Intelligence. Hence, we define intelligence as a formalization of generality, represented by the abstraction ∆∞Ο, where each symbol represents the concepts infinitesimal, infinite, and finite respectively. In essence, this paper proposes a General Language Model (GLM), where the abstraction ∆∞Ο represents the foundational relationship of the model. This relation is colloquially termed “The theory of everything”. 展开更多
关键词 intelligence GENERALIZATION ABSTRACTION TRANSFORMATION General Language Model General intelligence Theory Theory of Everything
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Artificial Intelligence-Based Sentiment Analysis of Dynamic Message Signs that Report Fatality Numbers Using Connected Vehicle Data
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作者 Dorcas O. Okaidjah Jonathan Wood Christopher M. Day 《Journal of Transportation Technologies》 2024年第4期590-606,共17页
This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influe... This study presents results from sentiment analysis of Dynamic message sign (DMS) message content, focusing on messages that include numbers of road fatalities. As a traffic management tool, DMS plays a role in influencing driver behavior and assisting transportation agencies in achieving safe and efficient traffic movement. However, the psychological and behavioral effects of displaying fatality numbers on DMS remain poorly understood;hence, it is important to know the potential impacts of displaying such messages. The Iowa Department of Transportation displays the number of fatalities on a first screen, followed by a supplemental message hoping to promote safe driving;an example is “19 TRAFFIC DEATHS THIS YEAR IF YOU HAVE A SUPER BOWL DON’T DRIVE HIGH.” We employ natural language processing to decode the sentiment and undertone of the supplementary message and investigate how they influence driving speeds. According to the results of a mixed effect model, drivers reduced speeds marginally upon encountering DMS fatality text with a positive sentiment with a neutral undertone. This category had the largest associated amount of speed reduction, while messages with negative sentiment with a negative undertone had the second largest amount of speed reduction, greater than other combinations, including positive sentiment with a positive undertone. 展开更多
关键词 intelligent Transportation System Sentiment Analysis Dynamic Message Signs Large Language Models Traffic Safety Artificial intelligence
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Overcoming the Potential Drawbacks of Artificial Intelligence in Psychotherapy: Literature Updates
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作者 Ogochukwu Agazie Evaristus Chino Ezema +15 位作者 Amir Meftah Bashir Aribisala Tania Sultana Uchenna Esther Ezenagu Satwant Singh Thant Zin Htet Jude Beauchamp Ndukaku Ogbonna Nnenna Bessie Emejuru Emmanuel Chiebuka Sanmi Michael Obe Chinenye Loveth Aleke Obioma Onah Ezema Chinwe Okeke-Moffatt Omotola Emmanuel Stephen Okorom 《Open Journal of Psychiatry》 2024年第S1期451-456,共6页
Artificial Intelligence (AI) has progressively impacted healthcare around the world. The increasing need for readily available mental health services, coupled with the swift advancement of novel technologies, prompts ... Artificial Intelligence (AI) has progressively impacted healthcare around the world. The increasing need for readily available mental health services, coupled with the swift advancement of novel technologies, prompts conversations over the viability of psychotherapy approaches using engagements with AI. Despite the positive impacts, there are recognizable drawbacks associated with the application of AI in psychotherapy. Establishing a therapeutic alliance is difficult for non-human entities. Psychotherapy is a task too complex for limited artificial intelligence. AI appears capable of handling jobs that are clearly defined and relatively straightforward. Besides, AI malfunctions, data confidentiality, informed consent, and risk of bias are potential concerns. We present a literature update of possible solutions to overcome these concerns. 展开更多
关键词 Artificial Drawbacks intelligence Overcoming PSYCHOTHERAPY
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Systematic bibliometric and visualized analysis of research hotspots and trends on the application of artificial intelligence in glaucoma from 2013 to 2022
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作者 Chun Liu Lu-Yao Wang +2 位作者 Ke-Yu Zhu Chun-Meng Liu Jun-Guo Duan 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2024年第9期1731-1742,共12页
AIM:To conduct a bibliometric analysis of research on artificial intelligence(AI)in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions fo... AIM:To conduct a bibliometric analysis of research on artificial intelligence(AI)in the field of glaucoma to gain a comprehensive understanding of the current state of research and identify potential new directions for future studies.METHODS:Relevant articles on the application of AI in the field of glaucoma from the Web of Science Core Collection were retrieved,covering the period from January 1,2013,to December 31,2022.In order to assess the contributions and co-occurrence relationships among different countries/regions,institutions,authors,and journals,CiteSpace and VOSviewer software were employed and the research hotspots and future trends within the field were identified.RESULTS:A total of 750 English articles published between 2013 and 2022 were collected,and the number of publications exhibited an overall increasing trend.The majority of the articles were from China,followed by the United States and India.National University of Singapore,Chinese Academy of Sciences,and Sun Yat-sen University made significant contributions to the published works.Weinreb RN and Fu HZ ranked first among authors and cited authors.American Journal of Ophthalmology is the most impactful academic journal in the field of AI application in glaucoma.The disciplinary scope of this field includes ophthalmology,computer science,mathematics,molecular biology,genetics,and other related disciplines.The clustering and identification of keyword nodes in the co-occurrence network reveal the evolving landscape of AI application in the field of glaucoma.Initially,the hot topics in this field were primarily“segmentation”,“classification”and“diagnosis”.However,in recent years,the focus has shifted to“deep learning”,“convolutional neural network”and“artificial intelligence”.CONCLUSION:With the rapid development of AI technology,scholars have shown increasing interest in its application in the field of glaucoma.Moreover,the application of AI in assisting treatment and predicting prognosis in glaucoma may become a future research hotspot.However,the reliability and interpretability of AI data remain pressing issues that require resolution. 展开更多
关键词 GLAUCOMA ar tificial intelligence BIBLIOMETRICS
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