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Adaptive Pareto-Based Multi-Agent Decision Model for Resource Management in Cloud Business Intelligence Systems 认领 引用
1
作者 Khamza Eshankulov Bahodir Muminov +4 位作者 Robiya Farmonova Dilnavoz Sodikova Bakhriddin Bozorov Zavqiddin Temirov Rashid Nasimov 《Computers, Materials & Continua》 SCIE EI 2026年第9期2146-2166,共21页
Cloud-based Business Intelligence(BI)systems operate under highly dynamic analytical workloads,including bursty OLAP queries,concurrent aggregations,and real-time microservice interactions,where static resource alloca... Cloud-based Business Intelligence(BI)systems operate under highly dynamic analytical workloads,including bursty OLAP queries,concurrent aggregations,and real-time microservice interactions,where static resource allocation leads to latency spikes and inefficient resource utilization.This paper proposes a decentralized adaptive Pareto-based multi-agent decision model for real-time resource coordination in cloud BI microservice environments.The agent placement problem is formulated as a multi-criteria decision process that minimizes service response latency,improves computational resource utilization,and preserves Quality-of-Service(QoS)stability.Instead of constructing a centralized global optimization policy,the proposed framework relies on decentralized locally Pareto-efficient decisions combined with adaptive priority regulation driven by QoS deviation.The approach is evaluated through large-scale controlled simulation and validated in a Kubernetes-based pilot cloud environment.Experimental results demonstrate up to 54%latency reduction compared to static allocation and 22%improvement over GA-based optimization,with enhanced CPU utilization balance under dynamic workloads.Statistical analysis confirms the significance of improvements(p<0.05).The proposed model ensures bounded monotonic decision transitions without centralized orchestration or predictive training,making it suitable for real-time cloud-native BI service ecosystems. 展开更多
关键词 Cloud resource allocation pareto decision making decentralized coordination business intelligence microservices adaptive multi-agent systems
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A Survey on Artificial Intelligence Systems Robustness:Adversarial Attacks and Defenses 认领 引用
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作者 Wei Zheng 《Journal of Electronic Research and Application》 2026年第1期182-191,共10页
Artificial intelligence systems have achieved widespread applications across many fields such as image classification,speech recognition,and game playing.However,as their decision-making logic is primarily learned fro... Artificial intelligence systems have achieved widespread applications across many fields such as image classification,speech recognition,and game playing.However,as their decision-making logic is primarily learned from data,their outputs are highly sensitive to data anomalies and are particularly vulnerable to adversarial perturbations.This paper conducts a comprehensive survey on the robustness of artificial intelligence systems,reviewing classical adversarial attack and defense methods,and summarizing future development trends.We hope this work can provide valuable insights for research on the robustness of artificial intelligence systems and support the development of trustworthy artificial intelligence. 展开更多
关键词 Artificial intelligence Adversarial attacks Adversarial defense
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Multimodal artificial intelligence system for detecting a small esophageal high-grade squamous intraepithelial neoplasia: A case report 认领 引用 被引量：1
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作者 Yang Zhou Rui-De Liu +3 位作者 Hui Gong Xiang-Lei Yuan Bing Hu Zhi-Yin Huang 《World Journal of Gastrointestinal Endoscopy》 2025年第1期61-65,共5页
BACKGROUND Recent advancements in artificial intelligence(AI)have significantly enhanced the capabilities of endoscopic-assisted diagnosis for gastrointestinal diseases.AI has shown great promise in clinical practice,... BACKGROUND Recent advancements in artificial intelligence(AI)have significantly enhanced the capabilities of endoscopic-assisted diagnosis for gastrointestinal diseases.AI has shown great promise in clinical practice,particularly for diagnostic support,offering real-time insights into complex conditions such as esophageal squamous cell carcinoma.CASE SUMMARY In this study,we introduce a multimodal AI system that successfully identified and delineated a small and flat carcinoma during esophagogastroduodenoscopy,highlighting its potential for early detection of malignancies.The lesion was confirmed as high-grade squamous intraepithelial neoplasia,with pathology results supporting the AI system’s accuracy.The multimodal AI system offers an integrated solution that provides real-time,accurate diagnostic information directly within the endoscopic device interface,allowing for single-monitor use without disrupting endoscopist’s workflow.CONCLUSION This work underscores the transformative potential of AI to enhance endoscopic diagnosis by enabling earlier,more accurate interventions. 展开更多
关键词 Artificial intelligence Multimodal artificial intelligence system Esophageal squamous cell carcinoma High-grade intraepithelial neoplasia Case report
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Validation studies of the ParaDNA■Intelligence System with artificial evidence items 认领 引用 被引量：1
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作者 Min Li Ruiyang Tao +7 位作者 Wei Zhou Yanan Li Meng Meng Yilun Zhang Linsheng Yu Liqin Chen Yingnan Bian Chengtao Li 《Forensic Sciences Research》 CSCD 2021年第1期84-91,共8页
Short tandem repeat(STR)profiling is one of the mostly used systems for forensic applications.In certain circumstances,STR profiling is time-consuming and costly,which potentially leads to delays in criminal investiga... Short tandem repeat(STR)profiling is one of the mostly used systems for forensic applications.In certain circumstances,STR profiling is time-consuming and costly,which potentially leads to delays in criminal investigations.LGC(Laboratory of the Government Chemist,UK)Forensics has developed a robust STR profiling platform called the ParaDNAVR Intelligence Test System which can provide early tactical intelligence and aid investigators in making informed decisions on sample prioritization for detection.Here,we validated the ParaDNA■intelligence test for its application in forensic cases using a range of mock evidence items following guidelines set by the Scientific Working Group on DNA Analysis Methods(SWGDAM).Specifically,we tested the sensitivity and accuracy of the ParaDNA intelligence test,as well as the success rates for detecting mock samples and for use in case scenarios.Our findings demonstrate that the ParaDNA intelligence test generates useful DNA profiles,especially for samples such as blood,saliva,and semen that contain ample DNA,indicating the benefits of including ParaDNA as a prior step in forensic STR profiling pipelines. 展开更多
关键词 Forensic sciences forensic genetics ParaDNA■Test Intelligence System rapid DNA melt curve analysis HyBeaconTMprobes
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Artificial intelligence system for the detection of Barrett’s esophagus 认领 引用 被引量：8
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作者 Ming-Chang Tsai Hsu-Heng Yen +7 位作者 Hui-Yu Tsai Yu-Kai Huang Yu-Sin Luo Edy Kornelius Wen-Wei Sung Chun-Che Lin Ming-Hseng Tseng Chi-Chih Wang 《World Journal of Gastroenterology》 SCIE CAS 2023年第48期6198-6207,共10页
BACKGROUND Barrett’s esophagus(BE),which has increased in prevalence worldwide,is a precursor for esophageal adenocarcinoma.Although there is a gap in the detection rates between endoscopic BE and histological BE in ... BACKGROUND Barrett’s esophagus(BE),which has increased in prevalence worldwide,is a precursor for esophageal adenocarcinoma.Although there is a gap in the detection rates between endoscopic BE and histological BE in current research,we trained our artificial intelligence(AI)system with images of endoscopic BE and tested the system with images of histological BE.AIM To assess whether an AI system can aid in the detection of BE in our setting.METHODS Endoscopic narrow-band imaging(NBI)was collected from Chung Shan Medical University Hospital and Changhua Christian Hospital,resulting in 724 cases,with 86 patients having pathological results.Three senior endoscopists,who were instructing physicians of the Digestive Endoscopy Society of Taiwan,independently annotated the images in the development set to determine whether each image was classified as an endoscopic BE.The test set consisted of 160 endoscopic images of 86 cases with histological results.RESULTS Six pre-trained models were compared,and EfficientNetV2B2(accuracy[ACC]:0.8)was selected as the backbone architecture for further evaluation due to better ACC results.In the final test,the AI system correctly identified 66 of 70 cases of BE and 85 of 90 cases without BE,resulting in an ACC of 94.37%.CONCLUSION Our AI system,which was trained by NBI of endoscopic BE,can adequately predict endoscopic images of histological BE.The ACC,sensitivity,and specificity are 94.37%,94.29%,and 94.44%,respectively. 展开更多
关键词 Barrett’s esophagus Artificial intelligence system Endoscopy Narrow-band imaging Gastroesophageal reflux disease
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Application of an artificial intelligence system for endoscopic diagnosis of superficial esophageal squamous cell carcinoma 认领 引用 被引量：16
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作者 Qian-Qian Meng Ye Gao +6 位作者 Han Lin Tian-Jiao Wang Yan-Rong Zhang Jian Feng Zhao-Shen Li Lei Xin Luo-Wei Wang 《World Journal of Gastroenterology》 SCIE CAS 2022年第37期5483-5493,共11页
BACKGROUND Upper gastrointestinal endoscopy is critical for esophageal squamous cell carcinoma(ESCC)detection;however,endoscopists require long-term training to avoid missing superficial lesions.AIM To develop a deep ... BACKGROUND Upper gastrointestinal endoscopy is critical for esophageal squamous cell carcinoma(ESCC)detection;however,endoscopists require long-term training to avoid missing superficial lesions.AIM To develop a deep learning computer-assisted diagnosis(CAD)system for endoscopic detection of superficial ESCC and investigate its application value.METHODS We configured the CAD system for white-light and narrow-band imaging modes based on the YOLO v5 algorithm.A total of 4447 images from 837 patients and 1695 images from 323 patients were included in the training and testing datasets,respectively.Two experts and two non-expert endoscopists reviewed the testing dataset independently and with computer assistance.The diagnostic performance was evaluated in terms of the area under the receiver operating characteristic curve,accuracy,sensitivity,and specificity.RESULTS The area under the receiver operating characteristics curve,accuracy,sensitivity,and specificity of the CAD system were 0.982[95%confidence interval(CI):0.969-0.994],92.9%(95%CI:89.5%-95.2%),91.9%(95%CI:87.4%-94.9%),and 94.7%(95%CI:89.0%-97.6%),respectively.The accuracy of CAD was significantly higher than that of non-expert endoscopists(78.3%,P<0.001 compared with CAD)and comparable to that of expert endoscopists(91.0%,P=0.129 compared with CAD).After referring to the CAD results,the accuracy of the non-expert endoscopists significantly improved(88.2%vs 78.3%,P<0.001).Lesions with Paris classification type 0-IIb were more likely to be inaccurately identified by the CAD system.CONCLUSION The diagnostic performance of the CAD system is promising and may assist in improving detectability,particularly for inexperienced endoscopists. 展开更多
关键词 Computer-aided diagnosis Artificial intelligence Deep learning Esophageal squamous cell carcinoma Early detection of cancer Upper gastrointestinal endoscopy
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Battlefield target intelligence system architecture modeling and system optimization 认领 引用 被引量：4
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作者 LI Wei WANG Yue +2 位作者 JIA Lijuan PENG Senran HE Ruixi 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第5期1190-1210,共21页
To address the current problems of poor generality,low real-time,and imperfect information transmission of the battlefield target intelligence system,this paper studies the battlefield target intelligence system from ... To address the current problems of poor generality,low real-time,and imperfect information transmission of the battlefield target intelligence system,this paper studies the battlefield target intelligence system from the top-level perspective of multi-service joint warfare.First,an overall planning and analysis method of architecture modeling is proposed with the idea of a bionic analogy for battlefield target intelligence system architecture modeling,which reduces the difficulty of the planning and design process.The method introduces the Department of Defense architecture framework(DoDAF)modeling method,the multi-living agent(MLA)theory modeling method,and other combinations for planning and modeling.A set of rapid planning methods that can be applied to model the architecture of various types of complex systems is formed.Further,the liveness analysis of the battlefield target intelligence system is carried out,and the problems of the existing system are presented from several aspects.And the technical prediction of the development and construction is given,which provides directional ideas for the subsequent research and development of the battlefield target intelligence system.In the end,the proposed architecture model of the battlefield target intelligence system is simulated and verified by applying the colored Petri nets(CPN)simulation software.The analysis demonstrates the reasonable integrity of its logic. 展开更多
关键词 battlefield target intelligence system architecture modeling bionic design system optimization simulation verification
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Using MWD: A Business Intelligence System for Tourism Destination Web 认领 引用 被引量：2
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作者 Aurkene Alzua-Sorzabal Jon Kepa Gerrikagoitia Fidel Rebón 《Management Studies》 2014年第1期62-72,共11页
The importance of Internet as mass media in the field of tourism is that it constitutes an important channel of marketing institutions and business network of the tourist destinations. But very few subsequent processe... The importance of Internet as mass media in the field of tourism is that it constitutes an important channel of marketing institutions and business network of the tourist destinations. But very few subsequent processes of management, maintenance, improvement, and exploitation of this appearance are deeply studied. The interactive nature of the website, as both transmitter of information and receiver, has attracted the attention of scholars since the interaction allows opening new approaches to the study of the network traffic （the pages user has visited, order them, the time that it has been in them, the actions carried out...） and cyber behavior. Information flows from the physical to the cyber world, and vice versa, adapting the converged world to human behavior and social dynamic. The business intelligence systems based on Internet enable organizations intelligent actions to address time-sensitive business processes and benefit from analytics. As result provides the opportunity to anticipate and estimate visitor habits in a changing environment. This paper presents the research and technological fields which have been incorporated to study of the destination web, a business intelligent tool based on Internet that it aims to increase the performance of the local manager or tour operator by providing an enhanced insight through the behavior of visitors on the website and future trends in research are expressed. 展开更多
关键词 tourism destination web monitor web mining web analytics business intelligence system
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Comparative evaluation of artificial intelligence systems'accuracy in providing medical drug dosages:A methodological study 认领 引用
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作者 Swaminathan Ramasubramanian Sangeetha Balaji +5 位作者 Tejashri Kannan Naveen Jeyaraman Shilpa Sharma Filippo Migliorini Suhasini Balasubramaniam Madhan Jeyaraman 《World Journal of Methodology》 2024年第4期121-130,共10页
BACKGROUND Medication errors,especially in dosage calculation,pose risks in healthcare.Artificial intelligence(AI)systems like ChatGPT and Google Bard may help reduce errors,but their accuracy in providing medication ... BACKGROUND Medication errors,especially in dosage calculation,pose risks in healthcare.Artificial intelligence(AI)systems like ChatGPT and Google Bard may help reduce errors,but their accuracy in providing medication information remains to be evaluated.AIM To evaluate the accuracy of AI systems(ChatGPT 3.5,ChatGPT 4,Google Bard)in providing drug dosage information per Harrison's Principles of Internal Medicine.METHODS A set of natural language queries mimicking real-world medical dosage inquiries was presented to the AI systems.Responses were analyzed using a 3-point Likert scale.The analysis,conducted with Python and its libraries,focused on basic statistics,overall system accuracy,and disease-specific and organ system accuracies.RESULTS ChatGPT 4 outperformed the other systems,showing the highest rate of correct responses(83.77%)and the best overall weighted accuracy(0.6775).Disease-specific accuracy varied notably across systems,with some diseases being accurately recognized,while others demonstrated significant discrepancies.Organ system accuracy also showed variable results,underscoring system-specific strengths and weaknesses.CONCLUSION ChatGPT 4 demonstrates superior reliability in medical dosage information,yet variations across diseases emphasize the need for ongoing improvements.These results highlight AI's potential in aiding healthcare professionals,urging continuous development for dependable accuracy in critical medical situations. 展开更多
关键词 Dosage calculation Artificial intelligence ChatGPT Drug dosage Healthcare Large language models
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Techniques to integrate artificial intelligence systems with medical information in gastroenterology 认领 引用
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作者 Hong-Yu Jin Man Zhang Bing Hu 《Artificial Intelligence in Gastrointestinal Endoscopy》 2020年第1期19-27,共9页
Gastrointestinal(GI)endoscopy is the central element in contemporary gastroenterology as it provides direct evidence to guide targeted therapy.To increase the accuracy of GI endoscopy and to reduce human-related error... Gastrointestinal(GI)endoscopy is the central element in contemporary gastroenterology as it provides direct evidence to guide targeted therapy.To increase the accuracy of GI endoscopy and to reduce human-related errors,artificial intelligence(AI)has been applied in GI endoscopy,which has been proved to be effective in diagnosing and treating numerous diseases.Therefore,we review current research on the efficacy of AI-assisted GI endoscopy in order to assess its functions,advantages and how the design can be improved. 展开更多
关键词 Gastrointestinal endoscopy Artificial intelligence Diagnosis Advantages
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World Industrial Revolutions and the Development of Artificial Intelligence System 认领 引用
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作者 Khatira Guliyeva 《Chinese Business Review》 2024年第1期47-51,共5页
The objective-scientific conclusions obtained from the researches conducted in various fields of science prove that era and worldview are in unity and are phenomena that determine one another,and era and worldview are... The objective-scientific conclusions obtained from the researches conducted in various fields of science prove that era and worldview are in unity and are phenomena that determine one another,and era and worldview are the most important phenomena in the understanding of geniuses,historical events,including personalities who have left a mark on the history of politics,and every individual as a whole.And it is appropriate to briefly consider the problem in the context of human and personality factors.It is known that man has tried to understand natural phenomena since the beginning of time.Contact with the material world naturally affects his consciousness and even his subconscious as he solves problems that are important or useful for human life.During this understanding,the worldview changes and is formed.Thus,depending on the material and moral development of all spheres of life,the content and essence of the progress events,as the civilizations replaced each other in different periods,the event of periodization took place and became a system.If we take Europe,the people of the Ice Age of 300,000 years ago,who engaged in hunting to solve their hunger needs,in other words,the age of dinosaurs,have spread to many parts of the world from Africa,where they lived in order to survive and meet more of their daily needs.The extensive integration of agricultural Ice Age People into the Earth included farming,fishing,animal husbandry,hunting,as well as handicrafts,etc.,and has led to the revolutionary development of the fields.As economic activities led these first inhabitants of the planet from caves to less comfortable shelters,then to good houses,then to palaces,labor activities in various occupations,including crafts,developed rapidly.Thus,the fads of the era who differed from the crowd(later this class will be called personalities,geniuses...-Kh.G.)began to appear.If we approach the issue from the point of view of history,we witness that the world view determines the development in different periods.This idea can be expressed in such a way that each period can be considered to have developed or experienced a crisis according to the level of worldview.In this direction of our thoughts,the question arises:So,what is the phenomenon of worldview of this era-XXI century?Based on the general content of the current events,characterized as the globalization stage of the modern world,we can say that the outlook of the historical stage we live in is based on the achievements of the last stage of the industrial revolution.In this article,by analyzing the history of the artificial intelligence system during the world industrial revolutions,we will study both the concept of progress of the industrial revolutions and the progressive and at the same time regressive development of the artificial intelligence system. 展开更多
关键词 world industrial revolutions artificial intelligence development
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Analysis of the Relationship between Image and Blood Examinations in an Artificial Intelligence System for the Molecular Diagnosis of Breast Cancer 认领 引用
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作者 Natsumi Wada Maoko Nakashima Yoshikazu Uchiyama 《Open Journal of Applied Sciences》 2021年第9期1016-1027,共12页
Molecular subtype classification based on tumor genotype has recently been used for differential diagnosis of breast cancer. The shift from conventional tissue classification to molecular genetics-based classification... Molecular subtype classification based on tumor genotype has recently been used for differential diagnosis of breast cancer. The shift from conventional tissue classification to molecular genetics-based classification is primarily because objective genetic information can ensure a biologically clear classification system and patient groups may be created for a given set of diagnoses and suitable treatments. Given the stressful nature of biopsy, radiomic studies are conducted to determine breast cancer subtypes using non-invasive imaging tests. Minimally invasive blood tests using microRNAs (miRNAs) contained in exosomes have been developed. We investigated the usefulness of radiomic features and miRNAs in distinguishing triple-negative breast cancer (TNBC) from other cancer types. Fat suppression T2-weighted magnetic resonance images and miRNAs of 60 cases (9 TNBC and 51 others) were retrieved from the Cancer Genome Atlas Breast Invasive Carcinoma. Six radiomic features and six miRNAs were selected by least absolute shrinkage and selection operator. Linear discriminant analysis was employed to distinguish between TNBC and others. With miRNAs, TNBC and others were completely separated, whereas with radiomic features, TNBC overlapped with other types of breast cancer. Receiver operating characteristic curve analysis results showed that the area under the curve of radiomic features and miRNAs was 0.85 and 1.0, respectively. miRNAs showed a higher discrimination performance than radiomic features. Although gene analysis is expensive and facilities for performing it are limited, miRNAs for blood tests may be useful in artificial intelligence systems for the molecular diagnosis of breast cancer. 展开更多
关键词 Radiomic Feature microRNA Breast Cancer Artificial Intelligence Characterization
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AI-driven design of powder-based nanomaterials for smart textiles: from data intelligence to system integration 认领 引用 被引量：3
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作者 Zihui Liang Yun Deng +12 位作者 Zhicheng Shi Xiaohong Liao Huiyi Zong Lizhi Ren Xiangzhe Li Xinyao Zeng Peiying Hu Wei Ke Bing Wu Kai Wang Jin Qian Weilin Xu Fengxiang Chen 《Advanced Powder Materials》 EI CAS CSCD 2026年第1期39-63,共25页
Artificial intelligence(AI)is emerging as a transformative enabler in the development of smart textile systems,particularly those integrating powder-based functional materials.This review highlights recent progress in... Artificial intelligence(AI)is emerging as a transformative enabler in the development of smart textile systems,particularly those integrating powder-based functional materials.This review highlights recent progress in AIguided design of carbon nanomaterials,metallic nanoparticles,and framework-based powders for applications in energy harvesting,intelligent sensing,and robotic actuation.Machine learning techniques,including supervised learning,transfer learning,and Bayesian optimization are discussed for accelerating materials discovery,enhancing integration strategies,and enabling real-time adaptive control.Emphasis is placed on how AI enables multifunctional,wearable platforms that sense,process,and respond to environmental and physiological cues with high accuracy and autonomy.Representative breakthroughs in soft robotics,haptic interfaces,and assistive devices are presented,demonstrating the synergy of AI and responsive textiles.Finally,the review outlines key challenges related to data scarcity,model generalizability,manufacturing scalability,and sustainability,while proposing future directions involving multimodal learning,autonomous experimentation,and ethics-aware design.This work offers a comprehensive outlook on next-generation AI-driven textile systems that seamlessly integrate intelligence,functionality,and wearability. 展开更多
关键词 Smart textiles Artificial intelligence Powder-based functional materials Machine learning AI-driven textile system
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Probabilistic Rationale of Actions for Artificial Intelligence Systems Operating in Uncertainty Conditions 认领 引用
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作者 Andrey I.Kostogryzov 《Artificial Intelligence Advances》 2019年第2期5-23,共19页
The approach for probabilistic rationale of artificial intelligence systems actions is proposed.It is based on an implementation of the proposed interconnected ideas 1-7 about system analysis and optimization focused ... The approach for probabilistic rationale of artificial intelligence systems actions is proposed.It is based on an implementation of the proposed interconnected ideas 1-7 about system analysis and optimization focused on prognostic modeling.The ideas may be applied also by using another probabilistic models which supported by software tools and can predict successfulness or risks on a level of probability distribution functions.The approach includes description of the proposed probabilistic models,optimization methods for rationale actions and incremental algorithms for solving the problems of supporting decision-making on the base of monitored data and rationale robot actions in uncertainty conditions.The approach means practically a proactive commitment to excellence in uncertainty conditions.A suitability of the proposed models and methods is demonstrated by examples which cover wide applications of artificial intelligence systems. 展开更多
关键词 Analysis Artificial intelligence systems Model Operation Prediction Probability Rationale Risk System System engineering
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Mechanism Design and Simulation about an Exoskeleton Jumping Assisting Intelligence System for Soldiers 认领 引用
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作者 CHEN Xiao ZHOU Hong LI Zhi-qiang 《International Journal of Plant Engineering and Management》 2011年第1期1-8,共8页
The Lower Limbs Exoskeleton jumping assisting Intelligence System （LLEIS） can be used to improve ma- neuverability of soldiers with key technologies of human motion characteristics recognition and design of an intel... The Lower Limbs Exoskeleton jumping assisting Intelligence System （LLEIS） can be used to improve ma- neuverability of soldiers with key technologies of human motion characteristics recognition and design of an intelli- gence power assisting device. Data on the movement of human lower limbs has been collected by using three kinds of instruments to research the parameters of characteristics recognition. The results indicated that the optimal angle be- tween knee and ankle is 157° for jumping assistance, and the peak force on the arch is 80 N in upward jumping and much lower in forward jumping. The LLEIS simplified model is accomplished under UG and exported into AD- AMS for the kinematics and dynamics simulation. The research findings indicate that the LLEIS can be used to enhance carrying and hopping ability of lower limbs effectively and as a reference for the design of a real system. 展开更多
关键词 soldier exoskeleton intelligence simulation
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The Testing Intelligence System Based on Factor Models and Self-Organizing Feature Maps 认领 引用
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作者 A.S. Panfilova L.S. Kuravsky 《Journal of Mathematics and System Science》 2013年第7期353-358,共6页
Presented is a new testing system based on using the factor models and self-organizing feature maps as well as the method of filtering undesirable environment influence. Testing process is described by the factor mode... Presented is a new testing system based on using the factor models and self-organizing feature maps as well as the method of filtering undesirable environment influence. Testing process is described by the factor model with simplex structure, which represents the influences of genetics and environmental factors on the observed parameters - the answers to the questions of the test subjects in one case and for the time, which is spent on responding to each test question to another. The Monte Carlo method is applied to get sufficient samples for training self-organizing feature maps, which are used to estimate model goodness-of-fit measures and, consequently, ability level. A prototype of the system is implemented using the Raven＇s Progressive Matrices （Advanced Progressive Matrices） - an intelligence test of abstract reasoning. Elimination of environment influence results is performed by comparing the observed and predicted answers to the test tasks using the Kalman filter, which is adapted to solve the problem. The testing procedure is optimized by reducing the number of tasks using the distribution of measures to belong to different ability levels after performing each test task provided the required level of conclusion reliability is obtained. 展开更多
关键词 Self-organizing feature maps intelligence testing Kalman filter
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Embodied-Intelligence Power Industrial Control Systems:Architecture Design,Key Scientific Problems,and Research Recommendations 认领 引用
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作者 Tingjun Zhang Dong Yue 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第2期239-242,共4页
THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-... THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4]. 展开更多
关键词 power system embodied intelligence power industrial control system power architecture design key scientific problems power industrial control systems sensing communication deviceshas renewable energy resourcescoupled
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Large Language Models for Cybersecurity Intelligence: A Systematic Review of Emerging Threats, Defensive Capabilities, and Security Evaluation Frameworks 认领 引用
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作者 Hamed Alqahtani Gulshan Kumar 《Computers, Materials & Continua》 SCIE EI 2026年第6期297-367,共71页
Large Language Models(LLMs)are becoming integral components of modern cybersecurity ecosystems,simultaneously strengthening defensive capabilities while giving rise to a new class of Artificial Intelligence-Generated ... Large Language Models(LLMs)are becoming integral components of modern cybersecurity ecosystems,simultaneously strengthening defensive capabilities while giving rise to a new class of Artificial Intelligence-Generated Content(AIGC)-driven threats.This PRISMA-guided systematic review synthesises 167 peer-reviewed studies published between 2022 and 2025 and proposes a unified threat-defence-evaluation taxonomy as a central analytical framework to consolidate a previously fragmented body of research.Guided by this taxonomy,the review first examines AIGC-enabled threats,including automated and highly personalised phishing,polymorphic malware and exploit generation,jailbreak and adversarial prompting,prompt-injection attack vectors,multimodal deception,persona-steering attacks,and large-scale disinformation campaigns.The surveyed evidence indicates a qualitative escalation in adversarial capabilities,with LLMs significantly enhancing scalability,adaptability,and realism while markedly reducing the technical barriers to conducting sophisticated attacks.Second,the review analyses LLM-enabled defensive applications spanning intrusion and anomaly detection,malware analysis and log-semantic modelling,multilingual threat intelligence extraction,vulnerability discovery and code repair,and Security Operations Center(SOC)automation through Retrieval-Augmented Generation(RAG)and multi-agent systems.Although these approaches demonstrate strong potential as semantic reasoning and decision-support components within hybrid security architectures,their real-world effectiveness remains constrained by hallucination risks,adversarial susceptibility,distributional shifts,and operational overhead.Third,the review synthesises current security evaluation and red-teaming practices,revealing a fragmented assessment landscape characterised by narrow benchmarks,inconsistent evaluation metrics,and limited longitudinal robustness analysis.Overall,the taxonomy-driven synthesis highlights a structurally imbalanced ecosystem in which offensive innovation outpaces defensive maturity and governance,and it informs a structured,research-question-aligned roadmap for developing trustworthy,resilient,and policy-aligned LLM-powered cybersecurity systems. 展开更多
关键词 Artificial intelligence-generated content threats cybersecurity intelligence large language model-based defensive systems large language models red-teaming and evaluation frameworks
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Artificial intelligence-enabled high-precision colony extraction and isolation system 认领 引用 被引量：1
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作者 ZHAO Xu-feng JIA Zhi-qiang +5 位作者 CHEN Wei-xue HU Peng-tao SU Xin-ran LI Jun-lin GE Ming-feng DONG Wen-fei 《中国光学（中英文）》 EI CAS CSCD 北大核心 2026年第1期190-204,共15页
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and... Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel. 展开更多
关键词 artificial intelligence colony extraction and isolation large-field imaging automation
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Advancing electric vehicle ecosystems:a survey of generative artificial intelligence and distributed machine learning applications 认领 引用
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作者 Seyed Mahmoud Sajjadi Mohammadabadi Aidin Karimi Moghaddam +4 位作者 Mahmoudreza Entezami Mirali Seyedrezaei Dorsa Charkhian Behzad Moghaddami Mohammad Sassani 《Global Energy Interconnection》 EI CSCD 2026年第2期315-336,共22页
The growing popularity of Electric Vehicles(EVs)necessitates advanced systems capable of managing the increasing complexity of EV-generated data.However,the exponential expansion of data streams poses significant chal... The growing popularity of Electric Vehicles(EVs)necessitates advanced systems capable of managing the increasing complexity of EV-generated data.However,the exponential expansion of data streams poses significant challenges to existing network infrastructure,potentially limiting EV performance and scalability.This survey investigates the synergistic potential of Generative Artificial Intelligence(GenAI)and Distributed Machine Learning(DML)to address key challenges and enhance EV efficiency across diverse domains.DML facilitates collaborative learning across decentralized devices,enabling optimized resource allocation,strengthened privacy,and improved EV operations without data centralization.Meanwhile,GenAI techniques,such as Generative Adversarial Networks(GANs)and Variational Autoencoders(VAEs),offer transformative capabilities,including synthetic data generation for energy forecasting,data compression for efficient transmission,and resource-efficient task offloading.This paper explores the applications of GenAI and DML in several key areas of the EV ecosystem.These include battery lifecycle management,energy optimization,fault detection,and workload balancing.Furthermore,it highlights the primary advantages and challenges of implementing these technologies,such as addressing computational demands,algorithmic complexity,and mitigating biases in generated content.By advancing the integration of GenAI and DML,this study lays a foundation for a more sustainable,intelligent,and efficient transportation future. 展开更多
关键词 Generative artificial intelligence Electric vehicles Distributed machine learning Resource optimization Energy forecasting Fault detection ChatGPT Optimization
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