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    Study Findings on Artificial Intelligence Detailed by Researchers at Physikalisc h-Technische Bundesanstalt (Benchmarking the influence of pre-training on explan ation performance in MR image classification)

    76-77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 Berlin, Germany, by Ne wsRx correspondents, research stated, "Convolutional Neural Networks (CNNs) are frequently and successfully used in medical prediction tasks." Funders for this research include European Research Council; Bundesministerium F ur Wirtschaft Und Klimaschutz. Our news editors obtained a quote from the research from Physikalisch-Technische Bundesanstalt: "They are often used in combination with transfer learning, lead ing to improved performance when training data for the task are scarce. The resu lting models are highly complex and typically do not provide any insight into th eir predictive mechanisms, motivating the field of ‘explainable' artificial inte lligence (XAI). However, previous studies have rarely quantitatively evaluated t he ‘explanation performance' of XAI methods against ground-truth data, and trans fer learning and its influence on objective measures of explanation performance has not been investigated. Here, we propose a benchmark dataset that allows for quantifying explanation performance in a realistic magnetic resonance imaging (M RI) classification task. We employ this benchmark to understand the influence of transfer learning on the quality of explanations. Experimental results show tha t popular XAI methods applied to the same underlying model differ vastly in perf ormance, even when considering only correctly classified examples."
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    Department of Behavioral Science Reports Findings in Artificial Intelligence (Th e Promises and Possibilities of Artificial Intelligence in the Delivery of Behav ior Analytic Services)

    77-77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 Artificial Intelligenc e is the subject of a report. According to news reporting from Amherst, New York, by NewsRx journalists, research stated, "Artificial intelligence (AI) has begu n to affect nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this journal likely work in one or more areas of be havioral health." The news correspondents obtained a quote from the research from the Department o f Behavioral Science, "For readers who work in behavioral health and who are int erested in AI, the purpose of this article is to highlight the pervasiveness of AI research being conducted around many facets of behavioral health service deli very. To do this, we first provide a brief overview of some of the areas within AI and the types of problems each area of AI attempts to solve. We then outline the prototypical client journey in behavioral healthcare beginning with diagnosi s/assessment and ending with intervention withdrawal or ongoing monitoring. Next, for each stage in the client journey, we highlight several areas that parallel existing behavior analytic practice where researchers have begun to use AI, oft en to improve the efficiency of service delivery or to learn new things that imp rove the effectiveness of behavioral health services. Finally, for those whose a ppetite has been whet for getting involved with AI, we close by describing three roles they might consider trying out and that parallel the three main domains o f behavior analysis."
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    Reports on Machine Learning Findings from Guangzhou University Provide New Insig hts (Exploring the relationship between air temperature and urban morphology fac tors using machine learning under local climate zones)

    77-78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 out of Guangzhou, People's Re public of China, by NewsRx editors, research stated, "Urban microclimate faces s erious challenges due to increased urbanization and frequent heatwave events. Ma ny studies focused on investigating the holistic quantitative relationships betw een urban morphology factors and heat island intensity at the city scale, but le ss effort has been devoted to exploring the relationships on a block scale. Addi tionally, there is a lack of fast prediction methods for urban microclimate for local climate zones (LCZ) planning and design." Financial supporters for this research include National Natural Science Foundati on of China. The news correspondents obtained a quote from the research from Guangzhou Univer sity: "To address these challenges, this study proposes a Long Short-Term Memory Networks (LSTM) model to predict the effects of urban morphology factors on the air temperature under local climate zones. The effects of the spatial morpholog y features on the air temperature were characterized and quantified employing a postinterpretation method. The Pearl River New Town (PRNT), the downtown area o f Guangzhou, China, was considered as the research area for the model implementa tion. The results showed that air temperature prediction accuracy is the best wh en using the historical three-time step data, with R2 of 0.975. LCZ A has the hi ghest prediction accuracy, with an R2 of 0.990. LCZ 5 has the lowest accuracy, w ith an R2 of 0.881. Moreover, the effect of urban morphology factors on air temp erature was found to be greater than the effect of land cover type. In this rega rd, the sky view factor (SVF) has the highest impact, followed by the aspect rat io (AR) and the pervious surface fraction (PSF). Nevertheless, the warming effec t in built type was stronger than that in land cover. During the heatwave period, the maximum and minimum temperature changes were recorded in LCZ 4 and LCZ A, respectively, with values of 9.7 °C and 8.6 °C. It was shown that low-rise areas are more resilient than high-rise areas during heatwave periods. This is becaus e low-rise areas generally exhibit a smaller increase in air temperature."
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    Bialystok University of Technology Researcher Reports Research in Robotics (Fast 50 Hz Updated Static Infrared Positioning System Based on Triangulation Method)

    78-79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 reporting originating from Bialystok, Poland, by NewsRx correspondents, research stated, "One of the important issues being explo red in Industry 4.0 is collaborative mobile robots." Financial supporters for this research include Bialystok University of Technolog y. Our news journalists obtained a quote from the research from Bialystok Universit y of Technology: "This collaboration requires precise navigation systems, especi ally indoor navigation systems where GNSS (Global Navigation Satellite System) c annot be used. To enable the precise localization of robots, different variation s of navigation systems are being developed, mainly based on trilateration and t riangulation methods. Triangulation systems are distinguished by the fact that t hey allow for the precise determination of an object's orientation, which is imp ortant for mobile robots. An important feature of positioning systems is the fre quency of position updates based on measurements. For most systems, it is 10-20 Hz. In our work, we propose a high-speed 50 Hz positioning system based on the t riangulation method with infrared transmitters and receivers."
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    Study Findings from University Canada West Update Knowledge in Machine Learning (Navigating the ethical and privacy concerns of big data and machine learning in decision making)

    79-80页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in artificial intelligence. According to news reporting originating from Vancouver, Canada, by NewsRx correspondents, research stated, "In recent years, the fields of big dat a and machine learning have gained significant attention for their potential to revolutionize decision-making processes." The news correspondents obtained a quote from the research from University Canad a West: "The vast amounts of data generated by various sources can provide valua ble insights to inform decisions across a range of domains, from business and fi nance to healthcare and social policy. Machine learning algorithms
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    Lanzhou University Researchers Yield New Study Findings on Artificial Intelligen ce (How artificial intelligence affects the labour force employment structure fr om the perspective of industrial structure optimisation)

    80-81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 artificial in telligence have been published. According to news originating from Lanzhou, Peop le's Republic of China, by NewsRx correspondents, research stated, "To investiga te how artificial intelligence (AI) affects the structure of labour force employ ment, we integrate robotics adoption and employment into this study's model." Funders for this research include Lanzhou University. The news journalists obtained a quote from the research from Lanzhou University: "Based on Chinese provincial panel data from 2010 to 2019, fixed, mediating and threshold effects models and a spatial heterogeneity model were used to empiric ally test the impact of AI on the employment structure from the perspective of i ndustrial structure optimisation and its mechanisms of action. The findings demo nstrate that the impact of AI on the labour force employment structure reflects unique characteristics for China and promotes the advancement of the nation's em ployment structure. The influence of AI on the labour force employment structure follows a non-linear pattern, fostering labour force employment structure optim isation and upgrading from the perspective of industrial structure optimisation. Further investigation reveals the influence of spatial spillover effects from A I on employment structure optimisation."
      原文链接:
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    University of Peradeniya Reports Findings in Robotics (Quality of life of patien ts treated with robotic surgery in the oral and maxillofacial region: a scoping review of empirical evidence)

    81-82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 Robotics is the subjec t of a report. According to news originating from Peradeniya, Sri Lanka, by News Rx correspondents, research stated, "There is a blooming trend in the applicatio n of robotic surgery in oral and maxillofacial care, and different studies had e valuated the quality of life (QoL) outcomes among patients who underwent robotic surgery in the oral and maxillofacial region. However, empirical evidence on th e QoL outcomes from these procedures is yet to be mapped." Our news journalists obtained a quote from the research from the University of P eradeniya, "Thus, this study was conducted to evaluate the available scientific evidence and gaps concerning the QoL outcomes of patients treated with robotic s urgery in the oral and maxillofacial region. This study adopted a scoping review design, and it was conducted and reported based on the Arksey and O'Malley, PRI SMA-ScR, and AMSTAR-2 guidelines. SCOPUS, PubMed, CINAHL Complete, and APA PsycI NFO were searched to retrieve relevant literature. Using Rayyan software, the re trieved literature were deduplicated, and screened based on the review's eligibi lity criteria. Only the eligible articles were included in the review. From the included articles, relevant data were charted, collated, and summarized. A total of 123 literature were retrieved from the literature search. After deduplicatio n and screening, only 18 heterogeneous original articles were included in the re view. A total of 771 transoral robotic surgeries (TORSs) were reported in these articles, and the TORSs were conducted on patients with oropharyngeal carcinomas (OPC), recurrent tonsillitis, and obstructive sleep apnoea (OSA). In total, 20 different QoL instruments were used in these articles to assess patients' QoL ou tcomes, and the most used instrument was the MD Anderson Dysphagia Inventory Que stionnaire (MDADI). Physical functions related to swallowing, speech and salivar y functions were the most assessed QoL aspects. TORS was reported to result in i mproved QOL in patients with OPC, OSA, and recurrent tonsillitis, most significa ntly within the first postoperative year. Notably, the site of the lesion, invol vement of neck dissections and the characteristics of the adjuvant therapy seeme d to affect the QOL outcome in patients with OPC. Compared to the conventional t reatment modalities, TORS has demonstrated better QoL, mostly in the domains rel ated to oral functions such as swallowing and speech, among patients treated wit h such."
      原文链接:
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    Study Findings from Sun Yat-sen University Provide New Insights into Androids (A ip-net: an Anchor-free Instance-level Human Part Detection Network)

    82-83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-Androids. According to news reporting out of Shenzhen, People's Republi c of China, by NewsRx editors, research stated, "Human part detection has signif icant research and application in computer vision fields such as human- robot in teraction, motion capture, facial recognition, and human key point detection. Ho wever, the current human body part detection method encounters challenges when d etecting multi -scale objects and capturing the correlation relationship between human instances and human parts." Funders for this research include Shenzhen Science and Technology Program, Guang dong Basic and Applied Basic Research Foundation, National Natural Science Found ation of China (NSFC), Science, Technology, and the Innovation Commission of She nzhen Municipality. Our news journalists obtained a quote from the research from Sun Yat-sen Univers ity, "To address these problems, a new anchor -free instance -level human part d etection network (AIP-Net) is proposed. AIP-Net is a ‘two-level'structure that c onsists of two lightweight anchor -free detectors: a body detector and a parts d etector. AIP-Net gradually focuses the human body on the human part from top to down, effectively avoiding the interference of extraneous background and enhanci ng the correlation relationship between human instances and body parts. Addition ally, we design a body -part multidimensional context (BPMC) model in the parts detector branch to enhance the capability of the network. We trained the AIP-Ne end -to -end and achieved a state-of-the-art (SOTA) performance of 36.2 mean ave rage precision (mAP) on COCO Human Parts Dataset."
      原文链接:
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    New Findings from Ecole de Technologie Superieure in the Area of Robotics and Au tomation Described (Stereotac: a Novel Visuotactile Sensor That Combines Tactile Sensing With 3d Vision)

    83-84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-Roboti cs and Automation are discussed in a new report. According to news originating f rom Montreal, Canada, by NewsRx correspondents, research stated, "Combining 3D v ision with tactile sensing could unlock a greater level of dexterity for robots and improve several manipulation tasks. However, obtaining a close-up 3D view of the location where manipulation contacts occur can be challenging, particularly in confined spaces, cluttered environments, or without installing more sensors on the end effector." Financial supporters for this research include Natural Sciences and Engineering Research Council of Canada (NSERC), Fonds de recherche du Quebec-Nature et tec hnologies (FRQNT). Our news journalists obtained a quote from the research from Ecole de Technologi e Superieure, "In this context, this letter presents StereoTac, a novel vision-b ased sensor that combines tactile sensing with 3D vision. The proposed sensor re lies on stereoscopic vision to capture a 3D representation of the environmentbef ore contact and uses photometric stereo to reconstruct the tactile imprint gener ated by an object during contact. To this end, two cameras were integrated in a single sensor, whose interface is made of a transparent elastomer coated with a thin layer of paint with a level of transparency that can be adjusted by varying the sensor's internal lighting conditions. We describe the sensor's fabrication and evaluate its performance for both tactile perception and 3D vision."
      原文链接:
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    Reports from University of Perugia Advance Knowledge in Machine Learning (A Doma in Adaptation Approach To Damage Classification With an Application To Bridge Mo nitoring)

    84-85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 originating from Perugia, Italy, by Ne wsRx correspondents, research stated, "Data -driven machine-learning algorithms generally suffer from a lack of labelled health -state data, mainly those referr ing to damage conditions. To address such an issue, population -based structural health monitoring seeks to enrich the original dataset by transferring knowledg e from a population of monitored structures." Funders for this research include Ministry of Education, Universities and Resear ch (MIUR), FABRE Consortium, Engineering & Physical Sciences Resea rch Council (EPSRC), University of Perugia, Italy via the funded projects "Math4 Bridges"and "AIDMIX"in the internal research program fund. Our news journalists obtained a quote from the research from the University of P erugia, "Within this context, this paper presents a transfer learning approach, based on domain adaptation, to leverage information from completelylabelled brid ge structure data to accurately predict new instances of an unknown target domai n. Since intrinsic structural differences may cause distribution shifts, domain adaptation attempts to minimise the distance between the domains and to learn a mapping within a shared feature space. Specifically, the methodology involves th e long-term acquisition of natural frequencies from several structural scenarios . Such damage-sensitive features are then aligned via domain adaptation so that a machine-learning algorithm can effectively utilise the labelled source domain data and generalise well to the unlabelled target-domain data. The described pro cedure is applied to two case studies, including the Z24 and the S101 benchmark bridges and their finite element models, respectively."
      原文链接:
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