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    Studies from Shandong Technology & Business University Have Provid ed New Information about Artificial Intelligence (Shock or Empowerment? Artifici al Intelligence Technology and Corporate Esg Performance)

    50-50页
    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 Yantai, People’s Republic of China, by NewsRx journalists, research stated, “Artificial intelligence (AI) pl ays a significant role in realizing sustainable economic development. This paper uses the textual content of annual reports of listed companies to count 73 word s frequencies related to AI and construct AI indicators through precise vocabula ry.” Financial supporters for this research include National Natural Science Foundati on of China Key Project “Research on the Construction of China’s Economic Transf ormation Model for Carbon Neutrality”, National Social Science Fund “Study on th e Two-way Governance Model and Dynamic Optimization Mechanism of State-owned Ent erprises’ Cross-border Mergers and Acquisitions under Mixed Ownership Reform.”
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    Research Data from University of Granada Update Understanding of Machine Learnin g (Monocular visual SLAM, visual odometry, and structure from motion methods app lied to 3D reconstruction: A comprehensive survey)

    51-51页
    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 ar tificial intelligence. According to news originating from Granada, Spain, by New sRx correspondents, research stated, “Monocular Simultaneous Localization and Ma pping (SLAM), Visual Odometry (VO), and Structure from Motion (SFM) are techniqu es that have emerged recently to address the problem of reconstructing objects o r environments using monocular cameras.” Our news correspondents obtained a quote from the research from University of Gr anada: “Monocular pure visual techniques have become attractive solutions for 3D reconstruction tasks due to their affordability, lightweight, easy deployment, good outdoor performance, and availability in most handheld devices without requ iring additional input devices. In this work, we comprehensively overview the SL AM, VO, and SFM solutions for the 3D reconstruction problem that uses a monocula r RGB camera as the only source of information to gather basic knowledge of this ill-posed problem and classify the existing techniques following a taxonomy. To achieve this goal, we extended the existing taxonomy to cover all the current c lassifications in the literature, comprising classic, machine learning, direct, indirect, dense, and sparse methods. We performed a detailed overview of 42 meth ods, considering 18 classic and 24 machine learning methods according to the ten categories defined in our extended taxonomy, comprehensively systematizing thei r algorithms and providing their basic formulations. Relevant information about each algorithm was summarized in nine criteria for classic methods and eleven cr iteria for machine learning methods to provide the reader with decision componen ts to implement, select or design a 3D reconstruction system.”
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    Studies from University of New Mexico Have Provided New Information about Machin e Learning (Regression Tree Applications To Studying Alcohol-related Problems Am ong College Students)

    52-52页
    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 Machine Learn ing have been published. According to news reporting out of Albuquerque, New Mex ico, by NewsRx editors, research stated, “Machine learning algorithms hold promi se for developing precision medicine approaches to addiction treatment yet have been used sparingly to identify predictors of alcohol-related problems. Recursiv e partitioning, a machine learning algorithm, can identify salient predictors an d clinical cut points that can guide treatment.” Funders for this research include NIH National Institute on Alcohol Abuse & Alcoholism (NIAAA), NIH National Institute on Drug Abuse (NIDA).
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    New Findings on Machine Learning Described by Investigators at Wadia Institute o f Himalayan Geology (Machine Learning Assisted State-of-the-art-of Petrographic Classification From Geophysical Logs)

    53-53页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting out of Dehradun, India, by NewsRx e ditors, research stated, “In the E&P industry, accurate lithology c lassification is an essential task for successful exploration and production. Ge ophysical logs provide high-resolution petrophysical properties, but core loggin g is expensive and traditional techniques may not accurately classify lithologie s.” Financial supporters for this research include Directorate General of Hydrocarbo ns (DGH), Noida, Delhi, India, Science Engineering Research Board (SERB), India, Science and Engineering Research Board (SERB), Government of India.
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    Zhejiang Industry Polytechnic College Researcher Publishes Findings in Robotics (Vision-Guided Grasping Policy Learning from Demonstrations for Robotic Manipula tors)

    54-54页
    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 ro botics. According to news reporting originating from Shaoxing, People’s Republic of China, by NewsRx correspondents, research stated, “The integration of roboti cs into domestic environments poses significant challenges due to the dynamic an d varied nature of these settings.” Funders for this research include Engineering Research Center of Integration And Application of Digital Learning Technology, Ministry of Education; Scientific R esearch Project of Zhejiang Provincial Education Department; Zhejiang Provincial Department of Education Visiting Engineer “school Enterprise Cooperation Projec t”.
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    New Machine Learning Data Have Been Reported by Investigators at University of N ovi Sad (Reaching a Desirable Metastructure for Passive Vibration Attenuation By Using a Machine Learning Approach)

    55-55页
    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 Novi Sad, Serbia, by NewsRx editors, research stated, “The focus of this research is on designing a longitu dinally excited lightweight metastructure that consists of external units distri buted periodically, each enhanced with internal oscillators to serve as vibratio n absorbers. The metastructure initially exhibits uniformity, with all absorbers being identical to each other, being comprised of a cantilever that is integrat ed into the external parts of the metastructure, with each cantilever containing a concentrated mass block at its tip.” Funders for this research include Ministry of Science, Technological Development and Innovation of the Republic of Serbia, National Key R&D Program of China.
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    Universitas Brawijaya Reports Findings in Hypertension (Assessing the precision of machine learning for diagnosing pulmonary arterial hypertension: a systematic review and meta-analysis of diagnostic accuracy studies)

    56-57页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Cardiovascular Disease s and Conditions - Hypertension is the subject of a report. According to news re porting from Malang, Indonesia, by NewsRx journalists, research stated, “Pulmona ry arterial hypertension (PAH) is a severe cardiovascular condition characterize d by pulmonary vascular remodeling, increased resistance to blood flow, and even tual right heart failure. Right heart catheterization (RHC) is the gold standard diagnostic technique, but due to its invasiveness, it poses risks such as vesse l and valve injury.” The news correspondents obtained a quote from the research from Universitas Braw ijaya, “In recent years, machine learning (ML) technologies have offered non-inv asive alternatives combined with ML for improving the diagnosis of PAH. The stud y aimed to evaluate the diagnostic performance of various methods, such as elect rocardiography (ECG), echocardiography, blood biomarkers, microRNA, chest xray, clinical codes, computed tomography (CT) scan, and magnetic resonance imaging ( MRI), combined with ML in diagnosing PAH. The outcomes of interest included sens itivity, specificity, area under the curve (AUC), positive likelihood ratio (PLR ), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). This study employed the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool for quality appraisal and STATA V.12.0 for the meta-analysis. A comprehensive s earch across six databases resulted in 26 articles for examination. Twelve artic les were categorized as low-risk, nine as moderate-risk, and five as high-risk. The overall diagnostic performance analysis demonstrated significant findings, w ith sensitivity at 81% (95% CI = 0.76-0.85, <0.001), specificity at 84% (95% CI = 0.77-0.88, <0.001), and an AUC of 89% (95% CI = 0.85-0.91). In the subgroup analysis, echocardiography displayed outstanding results, with a se nsitivity value of 83% (95% CI = 0.72-0.91), specifi city value of 93% (95% CI = 0.89-0.96), PLR value of 12.4 (95% CI = 6.8-22.9), and DOR value of 70 (95% CI = 23-231). ECG demonstrated excellent accuracy performance, with a sensitivit y of 82% (95% CI = 0.80-0.84) and a specificity of 8 2 % (95% CI = 0.78-0.84). Moreover, blood biomarkers exhibited the highest NLR value of 0.50 (95% CI = 0.42-0.59). The implementation of echocardiography and ECG with ML for diagnosing PAH presents a promising alternative to RHC.”
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    Reports on Machine Learning Findings from Polytechnic University Milan Provide N ew Insights (Just-in-Time Morning Ramp-Up Implementation in Warehouses Enabled b y Machine Learning-Based Predictive Modelling: Estimation of Achievable Energy . ..)

    57-58页
    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 originating from Milan, Italy, by NewsRx correspondents, research stated, “This study proposes a simulation-bas ed methodology for estimating the energy saving achievable through the implement ation of a just-in-time morning ramp-up procedure in a warehouse (equipped with a heat pump).” Funders for this research include European Union Nextgenerationeu. Our news editors obtained a quote from the research from Polytechnic University Milan: “In this methodology, the operation of the heating supply unit each day i s initiated at a different time, aiming at achieving the desired setpoint upon ( and not before) the expected arrival of the occupants. It requires the estimatio n of the ramp-up duration (the time it takes the heating system to bring the ind oor temperature to the desired setpoint), which can be provided by machine learn ing-based models. To justify the corresponding required deployment investment, a n accurate estimation of the resulting achievable energy saving is needed. Accor dingly, physics-based energy behavior simulations are first performed. Next, var ious ML algorithms are employed to estimate the ramp-up duration using the simul ated time-series data of indoor temperature, setpoints, and weather conditions.”
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    Research from Peter the Great St. Petersburg Polytechnic University in Machine L earning Provides New Insights (Machine learning model for the BIM classification in IFC format)

    58-58页
    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 ar tificial intelligence. According to news originating from Peter the Great St. Pe tersburg Polytechnic University by NewsRx editors, the research stated, “In the rapid development of information technology in the field of Building Information Modeling (BIM) there is a growing need for efficient classification of construc tion information.” The news editors obtained a quote from the research from Peter the Great St. Pet ersburg Polytechnic University: “One of the key steps to move towards digital co nstruction involves creating reliable systems for classifying BIM elements, prov iding the foundation for various use cases, from facilitating model navigation t o obtaining practical outcomes such as cost estimates and materials quantities. However, the BIM classification process in practice is labor-intensive and time- consuming and leads to an increase in the cost. This study explores the applicat ion of an innovative method, based on artificial intelligence algorithms. This m ethod automates the assignment of codes to information model components. The res earch investigates classification systems, machine learning models and selects t he most accurate one for the classification task. It is based on metrics such as accuracy and F1-score in order to achieve an optimal balance between the effici ency and accuracy according to predefined parameters.”
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    Study Findings from University of Sharjah Provide New Insights into Artificial I ntelligence (Procurement of Artificial Intelligence Systems in UAE Public Sector s: An Interpretive Structural Modeling of Critical Success Factors)

    59-59页
    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 the University o f Sharjah by NewsRx correspondents, research stated, “This study investigates th e critical success factors (CSFs) influencing the procurement of artificial inte lligence (AI) systems within the United Arab Emirates (UAE) public sector.” Our news reporters obtained a quote from the research from University of Sharjah : “While AI holds immense potential to enhance public service delivery, its succ essful integration hinges on critical factors. This research utilizes Interpreti ve Structural Modeling (ISM) to analyze the CSFs impacting AI procurement within the UAE public sector. Through ISM, a structural model is developed to highligh t the interrelationships between these CSFs and their influence on the procureme nt process, outlining the key elements for successful AI procurement within the UAE public sector. Based on the literature review and expert validation from the UAE public sector, ten CSFs were identified. This study found that clear needs assessment is the most influential CSF, while the long-term value of AI systems or services is the least influential.”
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