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    Studies from Xi'an Polytechnic University in the Area of Machine Learning Report ed (Reed-inspired Three-dimensional Printed Microcolumn Array Reinforced Hierarc hically Structured Composites for Efficient Noise Reduction)

    47-48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 Machine Learning are pre sented in a new report. According to news reporting out of Xi'an, People's Repub lic of China, by NewsRx editors, research stated, "Against the background that n oise pollution has become a global problem, it is a challenge to prepare acousti c functional materials that combine strong low-frequency sound absorption at low thicknesses with excellent mechanical and thermal insulation properties. Inspir ed by natural reed, a unique microcolumn array was three-dimensional printed by stereolithography (SLA) and combined with sodium alginate aerogel (SA) and polyu rethane (PU) foam to design a highly efficient acoustic composite (PC-FMPPL comp osite), featuring both ‘cavity-like' and ‘filled microperforated plate-like' str uctures." Funders for this research include National Natural Science Foundation of China ( NSFC), Innovation Capability Support Program of Shaanxi, Key Research and Develo pment Program of Shaanxi, Outstanding Young Talents Support Plan of Shaanxi Univ ersities, Young Talent Fund of Association for Science and Technology in Shaanxi , China, Natural Science Basic Research Program of Shaanxi, Shaanxi Provincial E ducation Department, Young Talent Fund of Xi'an Association for Science and Tech nology, Youth Innovation Team of Shaanxi Universities.
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    Reports from Universita Politecnica delle Marche Describe Recent Advances in Rob otics (Design and Prototyping of a Collaborative Station for Machine Parts Assem bly)

    48-49页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on robotics have bee n published. According to news originating from Ancona, Italy, by NewsRx corresp ondents, research stated, "Collaboration between humans and machines is the core of the Industry 5.0 paradigm, and collaborative robotics is one the most impact ful enabling technologies for small and medium Enterprises (SMEs)." Our news reporters obtained a quote from the research from Universita Politecnic a delle Marche: "In fact, small batch production and high levels of product cust omization make parts assembly one of the most challenging operations to be autom ated, and it often still depends on the versatility of human labor. Collaborativ e robots, for their part, can be easily integrated in this productive paradigm, as they have been specifically developed for coexistence with human beings. This work investigates the performance of collaborative robots in machine parts asse mbly. Design and research activities were carried out as a case study of industr ial relevance at the i-Labs industry laboratory, a pole of innovation that is br iefly introduced at the beginning of the paper."
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    Duy Tan University Researcher Reports Recent Findings in Machine Learning (Lever aging a Hybrid Machine Learning Approach for Compressive Strength Estimation of Roller-Compacted Concrete with Recycled Aggregates)

    49-49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 reporting from Da Nang, Vietnam, by New sRx journalists, research stated, "In recent years, the use of recycled aggregat e (RA) in roller-compacted concrete (RCC) for pavement construction has been inc reasingly attractive due to various environmental and economic benefits. Early d etermination of the compressive strength (CS) is crucial for the construction an d maintenance of pavement." The news editors obtained a quote from the research from Duy Tan University: "Th is paper presents the idea of combining metaheuristics and an advanced gradient boosting regressor for estimating the compressive strength of roller-compacted c oncrete containing RA. A dataset, including 270 samples, has been collected from previous experimental works. Recycled aggregates of construction demolition was te, reclaimed asphalt pavement, and industrial slag waste are considered in this dataset. The extreme gradient boosting machine (XGBoost) is employed to general ize a functional mapping between the CS and its influencing factors. A recently proposed gradient-based optimizer (GBO) is used to fine-tune the training phase of XGBoost in a data-driven manner. Experimental results show that the hybrid GB O-XGBoost model achieves outstanding prediction accuracy with a root mean square error of 2.64 and a mean absolute percentage error less than 8%. T he proposed method is capable of explaining up to 94% of the variation in the CS."
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    Report Summarizes Machine Learning Study Findings from Wichita State University (Flood susceptibility mapping: Integrating machine learning and GIS for enhanced risk assessment)

    50-50页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on artificial intelligence is now ava ilable. According to news reporting from Wichita State University by NewsRx jour nalists, research stated, "Flooding presents a formidable challenge in the Unite d States, endangering lives and causing substantial economic damage, averaging a round $5 billion annually. Addressing this issue and improving comm unity resilience is imperative." Financial supporters for this research include Wichita State University. Our news editors obtained a quote from the research from Wichita State Universit y: "This project employed machine learning techniques and publicly available dat ato explore the factors influencing flooding and to develop flood susceptibilit y maps at various spatial resolutions. Six machine learning algorithms, includin g Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), K- nearest neighbor (KNN), Adaptive Boosting (Ada Boost), and Extreme Gradient Boos ting (XGB) were used. Geospatial datasets comprising thirteen predictor variable s and 1528 flood inventory data collected since 1996 were analyzed. The predicto r variables are rainfall, elevation, slope, aspect, flow direction, flow accumul ation, Topographic Wetness Index (TWI), distance from the nearest stream, evapot ranspiration, land cover, impervious surface, land surface temperature, and hydr ologic soil group. Five hundred twentyeight non-flood data points were randomly created using a stream buffer for two scenarios. atotal of 2964 data points we re classified into flooded (1) and non-flooded (0) categories and used as atarg et. Overall, testing results showed that the XGB and RF models performed relativ ely well in both cases over multiple resolutions compared to other models, with an accuracy ranging from 0.82 to 0.97. Variable importance analysis depicted that predictor variables such as distance from the streams, hydrologic soil type, r ainfall, elevation, and impervious surfaces significantly affected flood predict ion, suggesting a strong association with the underlying driving process."
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    New Artificial Intelligence Data Have Been Reported by Researchers at Jinan Univ ersity (Climate policy and corporate artificial intelligence: Evidence from low- carbon city pilots in China)

    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 reporting originating from Guangzhou, People's Republic of China, by NewsRx correspondents, research stated, "The Low-C arbon City Pilot (LCCP) program in China is a climate policy implemented at the city level, and its impact on the development of corporate artificial intelligen ce (AI) remains to be studied." Our news journalists obtained a quote from the research from Jinan University: " The LCCP program aims to promote low-carbon transformation in multiple Chinese c ities and serves as a quasi-natural experiment to determine whether similar city -level climate policies can foster the development of corporate AI. This study e mploys a multi-period differences-in-differences (DID) approach to evaluate the impact of China's LCCP program on the development of corporate AI. By redirectin g attention from national-level policies to city-level initiatives, this study p rovides unique insights into the localized effects of climate policies on techno logical innovation within firms. The research findings indicate that the LCCP pr ogram has a significant promoting effect on the development of corporate AI. The se results underscore the potential of city-level climate policies, such as the LCCP program, to drive advancements in corporate AI technologies. By demonstrati ng a positive correlation between the implementation of the LCCP program and inc reased levels of AI development within companies, the study provides valuable in sights into the intersection of environmental policies and technological innovat ion."
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    Reports Outline Robotics Study Findings from Beijing Jiaotong University (Qualit y Control of Robotic Floor-tiling By the Modifications On Technology Parameters and Adhesive Properties)

    51-52页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics are disc ussed in a new report. According to news reporting originating in Beijing, Peopl e's Republic of China, by NewsRx journalists, research stated, "Floor-tiling rob otics are increasingly employed in on-site building constructions owing to their remarkable benefits on rising working efficiency and reducing labor costs. In t his study, a fluid-structure interaction (FSI) model of robotic tiling was estab lished for the first time, construction parameters and adhesive properties were modified, and their influences on the quality of robotic floor-tiling were syste matically investigated by tracking the mechanical behaviors of tiles and adhesiv e during tiling and the interfacial defects after tiling."
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    Second Affiliated Hospital of Harbin Medical University Reports Findings in Diab etic Nephropathy (Identification of key immunerelated genes and potential thera peutic drugs in diabetic nephropathy based on machine learning algorithms)

    52-53页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Kidney Diseases and Conditions-Diabetic Nephropathy is the subject of a report. According to news originating f rom Harbin, People's Republic of China, by NewsRx correspondents, research state d, "Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN."
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    Research from Harbin Institute of Technology Yields New Findings on Machine Lear ning (3D printed piezoelectric composite filament width and height prediction us ing individual and stacking ensemble of machine learning algorithms)

    53-54页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New study results on artificial intelligence have been published. According to news originating from the Harbin Institute of Tech nology by NewsRx editors, the research stated, "The dimensions of extrusion prin ted filament determine its processing resolution and efficiency."
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    Research in the Area of Artificial Intelligence Reported from Kristianstad Unive rsity (VoiceBack: Design of Artificial Intelligence-Driven Voice-Based Feedback System for Customer-Agency Communication in Online Travel Services)

    54-55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 artificial intelligence. According to news originating from Kristianstad, Sweden , by NewsRx editors, the research stated, "Online travel booking has become incr easingly popular; however, most travel websites do not yet offer voice interacti on." Our news editors obtained a quote from the research from Kristianstad University : "This study introduces VoiceBack, an artificial intelligence (AI)-driven voice -based feedback system conceptualized to support both customers and online trave l agencies during the booking process. It proposes atheoretically and empirical ly underpinned design concept that involves a voice user interface (VUI) for cus tomer feedback. This feedback, collected by an AI agent, is analyzed and convert ed into actionable statistics, which are then presented to online travel agencie s through a visual interface. The interface is designed to highlight problem are as and usability issues during the booking process. This study contributes to th e field of human-centered AI, by offering insight into the complex process of de signing and integrating voice, emotion, and feedback within user interfaces."
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    New Findings from School of Mechanical Engineering and Automation Describe Advan ces in Robotics and Automation (Bionic Bird Claw Design for Grabbing and Perchin g Inspired By Tendon-locking Mechanism)

    55-56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 Robotics-Ro botics and Automation have been published. According to news reporting out of Be ijing, People's Republic of China, by NewsRx editors, research stated, "This let ter proposes a novel bionic bird claw with a digit-locking mechanism inspired by atendon-locking mechanism (TLM). First, the biological mechanisms of both the bird digit-locked TLM (tendon locking) and the leg automatic digit flexion mecha nism (ADFM) (quick digit flexion) of birds are introduced." Funders for this research include National Key R&D Program of China , National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from the School of Mecha nical Engineering and Automation, "Then, a digit-locking mechanism that locks th e flexion tendon on the digit based on the TLM is proposed, requiring only aten sioned cable to unlock the digit. A parallelogram fold leg mechanism is designed based on the ADFM to drive the digit's flexion and locking motions. The digit l ocking and unlocking statics, the claw's gripping range, and the gripping force were analyzed. Finally, a prototype is developed, and several experiments are co nducted to measure digit locking and unlocking force, digit loading, claw grippi ng range, claw loading capability, and multi-angle dive grabbing of the claw. Th e load-to-weight ratio of the claw is 45.0-87.6. Moreover, the success rate of c law-grasping branches is found to reach 95${\ %}$."
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