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    Investigators from Shenzhen University Zero in on Support Vector Machines (Robust Twin Bounded Support Vector Classifier With Manifold Regularization)

    93-94页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning - Support Vector Machines.According to news reporting originatin g from Shenzhen, People’s Republic of China, by NewsRx correspondents,research stated, “Support vector machine (SVM), as a supervised learning method, has different kinds of varieties with significant performance. In recent years, more res earch focused on nonparallelSVM, where twin SVM (TWSVM) is the typical one.” Funders for this research include National Natural Science Foundation of China ( NSFC), ShenzhenMunicipal Science and Technology Innovation Council.Our news editors obtained a quote from the research from Shenzhen University, “I n order to reducethe influence of outliers, more robust distance measurements a re considered in these methods, but thediscriminability of the models is neglec ted. In this article, we propose robust manifold twin bounded SVM(RMTBSVM), whi ch considers both robustness and discriminability. Specifically, a novel norm, t hat is,capped L-1-norm, is used as the distance metric for robustness, and a ro bust manifold regularization isadded to further improve the robustness and clas sification performance. In addition, we also use the kernelmethod to extend the proposed RMTBSVM for nonlinear classification. We introduce the optimization problems of the proposed model. Subsequently, effective algorithms for both linear and nonlinear cases areproposed and proved to be convergent. Moreover, the exp eriments are conducted to verify the effectivenessof our model.”
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    Reports Summarize Robotics Findings from University of Texas Rio Grande Valley (Effects of Third-party Observer Empathy When Viewing Interactions Between Robots and Customers: the Moderating Role of Robot Eeriness)

    94-95页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Robotics have been published. According to news reportingoriginating from Edinburg, Texas, b y NewsRx correspondents, research stated, “As service robots becomeincreasingly common in the marketplace, more research is necessary to better understand cust omer perceptionsof and responses to those robots, especially in the context of service failures. This paper investigatesservice robots from the perspective of a customer as a third-party observer, specifically examining the effectof the customer’s empathy toward the robot on downstream customer responses and the mod erating roleof robot eeriness on that effect.”Our news editors obtained a quote from the research from the University of Texas Rio Grande Valley,“Namely, we find that for a low eeriness robot (e.g., a robo tic ‘arm’), customer responses generally become more desirable as empathy increa ses (i.e., complaint intentions and dissatisfaction are lower, andsatisfaction is higher). Meanwhile, for a high eeriness robot (e.g., a humanoid robot), those same customerresponses generally become less desirable as empathy increases.”According to the news editors, the research concluded: “The findings have implic ations for scholarshipon robotic automation in services marketing and for marke ters seeking to implement service robots incustomer-facing contexts.”
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    Shandong University Researcher Focuses on Artificial Intelligence (Government Su bsidies, Green Innovation, and Firm Total Factor Productivity of Listed Artificial Intelligence Firms in China)

    95-96页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news reportingout of Jinan, People’s Republ ic of China, by NewsRx editors, research stated, “The world is being reshapedun der global economic development driven by new advances in information technology .”Financial supporters for this research include Shandong Provincial Social Scienc e Planning ResearchProject; National Natural Science Foundation of China.Our news editors obtained a quote from the research from Shandong University: “A rtificial intelligence,an essential potential technology, will play a vital rol e in technological change and industrial upgrades.Exploring the relationship be tween government subsidies, green innovation, and total factor productivitywill help us analyze government decisions’ effects and better promote artificial int elligence’s technologicalinnovation process. Based on data from China’s listed artificial intelligence companies from 2011 to2020, this study uses the Levinso hn-Petrin method to measure the total factor productivity of companiesand analy zes the impact of government subsidies on the total factor productivity of AI co mpanies, themediating effect of green innovation, and the moderating effect of intellectual property protection intensity.The research results show that (1) g overnment subsidies can promote the total factor productivity of AIenterprises; (2) green innovation capabilities play a mediating role between government subs idies and enterprise total factor productivity, and government subsidies can ind irectly promote green innovation topromote the improvement of total factor prod uctivity effectively; (3) in the AI industry, the promotion effectof government subsidies on total factor productivity is more significant among state-owned en terprises,while the impact mechanism of government subsidies on private enterpr ises is not significant; and (4)the intensity of intellectual property protecti on has played a positive moderating role in the impact ofgovernment subsidies f or artificial intelligence enterprises on total factor productivity.”
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    University of Technology Sydney Reports Findings in Artificial Intelligence (Eva luation of an artificial intelligence-facilitated sperm detection tool in azoospermic samples for use in ICSI)

    96-97页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Artificial Intelligenc e is the subject of a report. According to newsreporting out of Sydney, Austral ia, by NewsRx editors, research stated, “Can artificial intelligence (AI)improv e the efficiency and efficacy of sperm searches in azoospermic samples? This two -phase proofof-concept study began with a training phase using eight azoospermi c patients (>10,000 sperm images)to provide a variety o f surgically collected samples for sperm morphology and debris variation to trai na convolutional neural network to identify spermatozoa. Second, side-by-side t esting was undertaken ontwo cohorts of non-obstructive azoospermia patient samp les: an embryologist versus the AI identifyingall the spermatozoa in the still images (cohort 1, n = 4), and a side-by-side test with a simulated clinicaldepl oyment of the AI model with an intracytoplasmic sperm injection microscope and t he embryologistperforming a search with and without the aid of the AI (cohort 2 , n = 4).”Our news journalists obtained a quote from the research from the University of T echnology Sydney,“In cohort 1, the AI model showed an improvement in the time t aken to identify all the spermatozoa perfield of view (0.02 ± 0.30 x 10s versus 36.10 ± 1.18s, P<0.0001) and improved recall (91.95 ± 0.8 1%versus 86.52 ± 1.34%, P<0.00 1) compared with an embryologist. From a total of 2660 spermatozoa tofind in al l the samples combined, 1937 were found by an embryologist and 1997 were found b y the AI inless than 1000th of the time. In cohort 2, the AI-aided embryologist took significantly less time per droplet(98.90 ± 3.19 s versus 168.7 ± 7.84 s, P<0.0001) and found 1396 spermatozoa, while 1274 were fou ndwithout AI, although no significant difference was observed.”
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    New Robotics Study Results Reported from Xi’an Jiaotong University (G2-monodepth : a General Framework of Generalized Depth Inference From Monocular Rgb+x Data)

    97-98页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ro botics. According to news reporting out ofXi’an, People’s Republic of China, by NewsRx editors, research stated, “Monocular depth inference is afundamental pr oblem for scene perception of robots.”Financial support for this research came from National Natural Science Foundatio n of China (NSFC).Our news journalists obtained a quote from the research from Xi’an Jiaotong Univ ersity, “Specificrobots may be equipped with a camera plus an optional depth se nsor of any type and located in variousscenes of different scales, whereas rece nt advances derived multiple individual sub-tasks. It leads toadditional burden s to fine-tune models for specific robots and thereby high-cost customization in largescaleindustrialization.”According to the news editors, the research concluded: “This article investigate s a unified task ofmonocular depth inference, which infers high-quality depth m aps from all kinds of input raw data fromvarious robots in unseen scenes.”
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    University Medical Center Reports Findings in Dilated Cardiomyopathy (Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy)

    98-99页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Heart Disorders and Di seases - Dilated Cardiomyopathy is the subjectof a report. According to news re porting out of Gottingen, Germany, by NewsRx editors, research stated,“Integrat ion of multiple data sources presents a challenge for accurate prediction of mol ecular pathophenotypicfeatures in automated analysis of data from human model systems. Here, we applied a machinelearning-based data integration to distingui sh patho-phenotypic features at the subcellular level for dilatedcardiomyopathy (DCM).”Funders for this research include DZHK German Center for Cardiovascular Research , UniversitatsmedizinGottingen, Carl Zeiss Foundation, Deutsche Forschungsgemei nschaft, Germany’s Excellence Strategy.Our news journalists obtained a quote from the research from University Medical Center, “We employeda human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) model of a DCM mutation inthe sarcomere protein troponin T (TnT), Tn T-R141W, compared to isogenic healthy (WT) control iPSCCMs.We established a mu ltimodal data fusion (MDF)-based analysis to integrate source datasets forCa tr ansients, force measurements, and contractility recordings. Data were acquired f or three additionallayer types, single cells, cell monolayers, and 3D spheroid iPSC-CM models. For data analysis, numericalconversion as well as fusion of dat a from Ca transients, force measurements, and contractility recordings,a non-ne gative blind deconvolution (NNBD)-based method was applied. Using an XGBoost alg orithm,we found a high prediction accuracy for fused single cell, monolayer, an d 3D spheroid iPSC-CM models (92 ? 0.08 %), as well as for fused C a transient, beating force, and contractility models (>9 6 ? 0.04 %).”
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    Hebei University of Technology Reports Findings in Robotics (The application pro spects of robot pose estimation technology: exploring new directions based on YO LOv8-ApexNet)

    99-100页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Robotics is the subjec t of a report. According to news reportingout of Tianjin, People’s Republic of China, by NewsRx editors, research stated, “Service robot technologyis increasi ngly gaining prominence in the field of artificial intelligence. However, persis tent limitationscontinue to impede its widespread implementation.”Our news journalists obtained a quote from the research from the Hebei Universit y of Technology,“In this regard, human motion pose estimation emerges as a cruc ial challenge necessary for enhancingthe perceptual and decision-making capacit ies of service robots. This paper introduces a groundbreakingmodel, YOLOv8-Apex Net, which integrates advanced technologies, including Bidirectional Routing Attention (BRA) and Generalized Feature Pyramid Network (GFPN). BRA facilitates the capture of interkeypointcorrelations within dynamic environments by introduci ng a bidirectional information propagationmechanism. Furthermore, GFPN adeptly extracts and integrates feature information across different scales,enabling th e model to make more precise predictions for targets of various sizes and shapes . Empiricalresearch findings reveal significant performance enhancements of the YOLOv8-ApexNet model across theCOCO and MPII datasets. Compared to existing me thodologies, the model demonstrates pronouncedadvantages in keypoint localizati on accuracy and robustness. The significance of this research lies inproviding an efficient and accurate solution tailored for the realm of service robotics, e ffectively mitigatingthe deficiencies inherent in current approaches.”
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    Data on Computational Intelligence Detailed by Researchers at Guangzhou University (Effective Single-step Adversarial Training With Energy-based Models)

    100-100页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning - Com putational Intelligence is the subject of areport. According to news reporting originating in Guangzhou, People’s Republic of China, by NewsRxjournalists, res earch stated, “Adversarial training (AT) is one of the most effective ways again st adversarialattacks. However, multi-step AT is time-consuming while single-st ep AT is ineffective.”Financial support for this research came from National Natural Science Foundatio n of China (NSFC).The news reporters obtained a quote from the research from Guangzhou University, “In this paper, wepropose an Energy-AT framework to make single-step AT as eff ective as multi-step ones, by exploiting thetwo properties of energy-based mode ls (EBM). First, we utilize the Helmholtz free energy in EBM to pushgenerated e xamples to be outside of the distribution boundaries of their categories, such t hat they are moreadversarial. Second, we apply an adaptive temperature scheme i n EBM to amplify the training gradientsof weak adversarial examples targetedly, such that those originally hard-to-learn examples contribute to therobustifica tion of models also.”
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    Researchers at University of Gloucestershire Release New Data on Machine Learning (Machine Learning Driven Developments In Behavioral Annotation: a Recent Historical Review)

    101-101页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on Machine Learning are pre sented in a new report. According to newsreporting originating in Cheltenham, U nited Kingdom, by NewsRx journalists, research stated, “Annotationtools serve a critical role in the generation of datasets that fuel machine learning applicat ions. Withthe advent of Foundation Models, particularly those based on Transfor mer architectures and expansivelanguage models, the capacity for training on co mprehensive, multimodal datasets has been substantiallyenhanced.”The news reporters obtained a quote from the research from the University of Glo ucestershire, “Thisnot only facilitates robust generalization across diverse da ta categories and knowledge domains but alsonecessitates a novel form of annota tion-prompt engineering-for qualitative model fine-tuning. This advancementcrea tes new avenues for machine intelligence to more precisely identify, forecast, a nd replicatehuman behavior, addressing historical limitations that contribute t o algorithmic inequities. Nevertheless,the voluminous and intricate nature of t he data essential for training multimodal models poses significantengineering c hallenges, particularly with regard to bias. No consensus has yet emerged on opt imal proceduresfor conducting this annotation work in a manner that is ethicall y responsible, secure, and efficient.This historical literature review traces a dvancements in these technologies from 2018 onward, underscoressignificant cont ributions, and identifies existing knowledge gaps and avenues for future researc h pertinentto the development of Transformer-based multimodal Foundation Models . An initial survey of over 724articles yielded 156 studies that met the criter ia for historical analysis; these were further narrowed downto 46 key papers sp anning the years 2018-2022. The review offers valuable perspectives on the evolu tionof best practices, pinpoints current knowledge deficiencies, and suggests p otential directions for futureresearch.”
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    Investigators from Zhongnan University of Economics & Law Have Reported New Data on Robotics (The Dehumanization of Service Robots Influences Hosp itality Consumption Emotion)

    102-102页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Robotics is now availab le. According to news reporting out ofWuhan, People’s Republic of China, by New sRx editors, research stated, “Understanding whether andhow encountering servic e robots influences hospitality consumption emotions helps identify the psychological effects and appropriate scenarios of robotic adoption. Anthropomorphic and humanlike features arewidely applied to strengthen the social impact of robots , but they are still considered non-human socialagents.”Financial support for this research came from National Social Science Founda- ti on, PRC.Our news journalists obtained a quote from the research from the Zhongnan Univer sity of Economics& Law, “We argue that customers have dehumanized cognition of service robots, which induces fewersocial constraints and greater perceived autonomy in hospitality service encounters. Five experimentalstudies were adopted to test the underlying mechanism through which service robots infl uence customers’consumption emotions by increasing their perceived autonomy und er various boundary conditions. Ourresults illustrate that, compared with human servants, customers experienced more positive consumptionemotions with service robots. This effect is eliminated when interpersonal pressure from peer customersis perceived.”
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