查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting out of Karlsruhe, Germany, by News Rx editors, research stated, “How can we quantify uncertainty if our favorite co mputational tool—be it a numerical, statistical, or machine learning approach, or just any computer model-provides singlevalued output only? In this article, we introduce the Easy Uncertainty Quantification (EasyUQ) technique, which trans forms real-valued model output into calibrated statistical distributions, based solely on training data of model output–outcome pairs, without any need to acce ss model input. In its basic form, EasyUQ is a special case of the recently intr oduced isotonic distributional regression (IDR) technique that leverages the poo l-adjacent-violators algorithm for nonparametric isotonic regression.” Financial supporters for this research include German Research Foundation (DFG), Swiss National Science Foundation (SNSF), Klaus Tschira Foundation.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in Robotics. Accordin g to news reporting out of Marrakech, Morocco, by NewsRx editors, research state d, “In recent years, trajectory tracking of a mobile robot has been one of the m ost addressed problems in the specilized literature, as a mobile robot must have the ability to follow a trajectory, while also compensating various external an d internal disturbances. This paper proposes an IEHO-STSM controller based on th e super-twisting sliding mode for the path tracking of a mobile robot.”Our news journalists obtained a quote from the research from Cadi Ayyad Universi ty, “First, a new improved IEHO algorithm has been developed and introduced, bas ed on the EHO (Elephant Herding Optimization) metaheuristic algorithm. The devel oped algorithm consisted in improving the performance of the basic EHO such as c onvergence speed, exploration and exploitation capabilities. Then, based on a dy namic model of the mobile robot, a super-twisting sliding mode (STSM) controller was designed to guide the robot to the desired trajectory. Finally, the improve d IEHO algorithm was applied for adjusting the parameters of the super-twisting sliding mode (STSM) controller. The analysis of the proposed IEHO algorithm has been done by comparing it with EHO, PSO (Particle Swarm Optimization) and GWO (G rey Wolf Optimizer) algorithms, by employing it in tuning the STSM.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news originating from Belfast, United Kingdom, by NewsR x editors, the research stated, “Many cases of radicalism, especially violent ra dicalism, manifest within the context of inter -ethnic conflict and war. Researc h in this domain has significantly contributed to our overarching comprehension of the issue.” Our news journalists obtained a quote from the research from Queen’s University Belfast, “This form of radicalism is inherently linked to the dynamics of group affiliation. However, our focus here is directed towards the individual motivati on driving radical actions. While radical actions may encompass dynamics of grou p affiliation (e.g., the most radical pro -life activists being members of the A rmy of God), they also possess a substantial individual component. For instance, numerous attacks on abortion doctors or clinics are categorized as ‘lone -wolf terrorism’. In this study, we sought to examine whether state-of-the-art Machine Learning technology for text analysis could effectively discern the intent behi nd radical actions from user -generated content. We analyzed a diverse array of radical texts published online by various activists, including anarchists, Irani an guerrilla members, Indian revolutionaries, activists from the US civil rights movement, and The Army of God.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on robotics are presented i n a new report. According to news reporting out of Beijing, People’s Republic of China, by NewsRx editors, research stated, “Achieving smooth motion for multi-l egged robots on complex terrains is a significant focus of research. When encoun tering high obstacles, robots often need to alter their motion direction to avoi d them, increasing redundancy in their motion trajectories.” Financial supporters for this research include National Key Research And Develop ment Program of China; National Natural Science Foundation of China.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Fibroma is the subject of a report. According to news reporting from Beijing, People’s Republic of Chi na, by NewsRx journalists, research stated, “In this study, our aim was to devel op and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery . We enrolled 220 patients with confirmed FD or OF.” The news correspondents obtained a quote from the research, “We extracted radiom ic features from nonenhanced CT images. Following dimensionality reduction and f eature selection, we constructed radiomic models using logistic regression, supp ort vector machine, random forest, light gradient boosting machine, and eXtreme gradient boosting. We then identified the best radiomic model using receiver ope rating characteristic (ROC) curve analysis. After combining radiomics features w ith clinical features, we developed a comprehensive model. ROC curve and decisio n curve analysis (DCA) demonstrated the models’ robustness and clinical value. W e extracted 1834 radiomic features from CT images, reduced them to eight valuabl e features, and achieved high predictive efficiency, with area under curves (AUC ) exceeding 0.95 for all the models. Ultimately, our combined model, which integ rates radiomic and clinical data, displayed superior discriminatory ability (AUC : training cohort 0.970; test cohort 0.967). DCA highlighted its optimal clinica l efficacy.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news reporting originating from the University of Sfax by NewsRx correspondents, research stated, “The study aimed t o identify the reality of using artificial intelligence applications in the huma n resources department at Tikrit University and to determine the requirements th at the human resources department needs in order to use artificial intelligence applications, in addition to identifying the difficulties facing the university’ s human resources department when using them to suggest treatments.” Our news reporters obtained a quote from the research from University of Sfax: “ The descriptive approach was used. The questionnaire was distributed to the stud y sample, which consisted of (225) managers, male and female employees. (210) qu estionnaires were retrieved and after canceling (4) questionnaires that included missing values and (6) questionnaires that were not suitable for analysis as th ey included extreme values, there were (200) questionnaires. The final total, an d the study concluded that the reality of using artificial intelligence applicat ions in human resources management at the university came with an arithmetic ave rage of (3.87) and a large degree. Also, the study sample agreed on the necessit y of providing the requirements to develop human resources management at the uni versity with an arithmetic average of (3.82) and the evaluation of the degree of agreement was a degree A large number of members of the study sample, represent ed by administrative organization with an arithmetic average of (3.85) and a lar ge degree, followed by (work performance) with an arithmetic average of (3.816) and a large degree, and finally (infrastructure) with an arithmetic average of ( 3.792) and a large degree. The study also showed that the level of agreement amo ng the members of the study sample reported that there were difficulties facing human resources management in using artificial intelligence applications, and th e average was (3.943).”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news reporting originating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Nonreciprocal in teraction crowd systems, such as human-human, human-vehicle, and human- robot sy stems, often have serious impacts on pedestrian safety and social order. A more comprehensive understanding of these systems is needed to optimize system stabil ity and efficiency.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Austin, Texas, by NewsRx edit ors, research stated, “For over a decade, machine learning (ML) models have been making strides in computer vision and natural language processing (NLP), demons trating high proficiency in specialized tasks. The emergence of large-scale lang uage and generative image models, such as ChatGPT and Stable Diffusion, has sign ificantly broadened the accessibility and application scope of these technologie s.” Funders for this research include NIH National Institute of General Medical Scie nces (NIGMS), Agence Nationale de la Recherche (ANR).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting originating from Chennai, India, by NewsRx correspondents, research stated, “The package industry relies heavily on efficient supply chain management to meet customer demands and maintain profi tability.”Our news journalists obtained a quote from the research from Vels Institute of S cience Technology and Advanced Studies: “However, managing complex supply chains involving multiple suppliers, transportation networks, and distribution channel s poses significant challenges. This research proposes a machine learningbased approach to optimize supply chain operations in the package industry. By analysi ng historical data on supply chain activities, including procurement, inventory management, and distribution, our system aims to identify patterns and trends to improve decision-making processes.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting from Cape Breton University by Ne wsRx journalists, research stated, “University ranking is a technique of measuri ng the performance of Higher Education Institutions (HEIs) by evaluating them on various criteria like student satisfaction, expenditure, research and teaching quality, citation count, grants, and enrolment.” Funders for this research include Social Sciences And Humanities Research Counci l of Canada; Natural Sciences And Engineering Research Council of Canada. Our news journalists obtained a quote from the research from Cape Breton Univers ity: “Ranking has been determined as a vital factor that helps students decide w hich institution to attend. Hence, universities seek to increase their overall r ank and use these measures of success in their marketing communications and prom inently place their ranked status on their institution’s websites. Despite decad es of research on ranking methods, a limited number of studies have leveraged pr edictive analytics and machine learning to rank universities. In this article, w e collected 49 Canadian universities’ data for 2017-2021 and divided them based on Maclean’s categories into Primarily Undergraduate, Comprehensive, and Medical /Doctoral Universities. After identifying the input and output components, we le veraged various feature engineering and machine learning techniques to predict t he universities’ ranks. We used Pearson Correlation, Feature Importance, and Chi -Square as the feature engineering methods, and the results show that ‘student t o faculty ratio,’ ‘total number of citations’, and ‘total number of Grants’ are the most important factors in ranking Canadian universities.”
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