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    Data from Department of Civil Engineering Provide New Insights into Machine Lear ning (Enhancing co-seismic landslide susceptibility, building exposure, and risk analysis through machine learning)

    39-40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 out of the Department of Civil En gineering by NewsRx editors, research stated, "Landslides are devastating natura l disasters that generally occur on fragile slopes. Landslides are influenced by many factors, such as geology, topography, natural drainage, land cover, rainfa ll and earthquakes, although the underlying mechanism is too complex and very di fficult to explain in detail." Our news journalists obtained a quote from the research from Department of Civil Engineering: "In this study, the susceptibility mapping of co-seismic landslide s is carried out using a machine learning approach, considering six districts co vering an area of 12,887 km2 in Nepal. Landslide inventory map is prepared by ta king 23,164 post seismic landslide data points that occurred after the 7.8 MW 20 15 Gorkha earthquake. Twelve causative factors, including distance from the rupt ure plane, peak ground acceleration and distance from the fault, are considered input parameters. The overall accuracy of the model is 87.2%, the a rea under the ROC curve is 0.94, the Kappa coefficient is 0.744 and the RMSE val ue is 0.358, which indicates that the performance of the model is excellent with the causative factors considered. The susceptibility thus developed shows that Sindhupalchowk district has the largest percentage of area under high and very h igh susceptibility classes, and the most susceptible local unit in Sindhupalchow k is the Barhabise municipality, with 19.98% and 20.34% of its area under high and very high susceptibility classes, respectively. For t he analysis of building exposure to co-seismic landslide susceptibility, a build ing footprint map is developed and overlaid on the co-seismic landslide suscepti bility map. The results show that the Sindhupalchowk and Dhading districts have the largest and smallest number of houses exposed to co-seismic landslide suscep tibility."
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    Findings from Chongqing University in Support Vector Machines Reported (Lineariz ed Alternating Direction Method of Multipliers for Elastic-net Support Vector Ma chines)

    40-41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 Support Vec tor Machines. According to news reporting out of Chongqing, People's Republic of China, by NewsRx editors, research stated, "In many high-dimensional datasets, the phenomenon that features are relevant often occurs. Elastic-net regularizati on is widely used in support vector machines (SVMs) because it can automatically perform feature selection and encourage highly correlated features to be select ed or removed together." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Scientific and Technological Research Program of Chongqing M unicipal Education Commission. Our news journalists obtained a quote from the research from Chongqing Universit y, "Recently, some effective algorithms have been proposed to solve the elastic- net SVMs with different convex loss functions, such as hinge, squared hinge, hub erized hinge, pinball and huberized pinball. In this paper, we develop a lineari zed alternating direction method of multipliers (LADMM) algorithm to solve above elastic-net SVMs. In addition, our algorithm can be applied to solve some new e lastic-net SVMs such as elastic-net least squares SVM. Compared with some existi ng algorithms, our algorithm has comparable or better performances in terms of c omputational cost and accuracy. Under mild conditions, we prove the convergence and derive convergence rate of our algorithm."
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    Researchers from McMaster University Report Findings in Artificial Intelligence [Incorporating Artificial Intelligence In Medical Diagnosis: a Case for an Invisible and (Un)Disruptive Approach]

    41-42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 Artificial Intelligen ce have been presented. According to news reporting out of Hamilton, Canada, by NewsRx editors, research stated, "As big data becomes more publicly accessible, artificial intelligence (AI) is increasingly available and applicable to problem s around clinical decision-making. Yet the adoption of AI technology in healthca re lags well behind other industries." Our news journalists obtained a quote from the research from McMaster University , "The gap between what technology could do, and what technology is actually bei ng used for is rapidly widening. While many solutions are proposed to address th is gap, clinician resistance to the adoption of AI remains high. To aid with cha nge, we propose facilitating clinician decisions through technology by seamlessl y weaving what we call ‘invisible AI' into existing clinician workflows, rather than sequencing new steps into clinical processes. We explore evidence from the change management and human factors literature to conceptualize a new approach t o AI implementation in health organizations." According to the news editors, the research concluded: "We discuss challenges an d provide recommendations for organizations to employ this strategy."
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    Study Data from University of Shanghai for Science and Technology Update Underst anding of Robotics (Design and Optimization of a Novel Sagittal-plane Knee Exosk eleton With Remote-center-ofmotion Mechanism)

    42-42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 reporting originating from Shanghai, People's R epublic of China, by NewsRx correspondents, research stated, "Powered exoskeleto n is a wearable robot that can provide power-assisted motion for the human body. One of the challenges in the exoskeleton research is how to improve its kinemat ic synergy." Our news editors obtained a quote from the research from the University of Shang hai for Science and Technology, "In this paper, a novel knee exoskeleton robot i s designed to improve the kinematic synergy between the exoskeleton and the huma n body. The novel exoskeleton adopts the sagittal-plane layout to reduce the bia s moment, and uses a remote-center-of-rotation mechanism to ensure the coinciden ce of the rotation centers of the exoskeleton and the human body. To analyze the influence of the interaction error on the performance of the exoskeleton, this paper proposes a human-exoskeleton fusion model based on the virtual equivalent parallel mechanism method, and parameterize the interaction error through virtua l kinematic chains. Finally, the assisting performance of the novel exoskeleton is analyzed and verified through simulation experiments, motion experiments, bod y motion experiments and human simulation experiments."
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    Researcher from Universidad Tecnologica de Bolivar Publishes New Studies and Fin dings in the Area of Machine Learning (Assessing the impact of missing data on w ater quality index estimation: a machine learning approach)

    43-43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 the Universida d Tecnologica de Bolivar by NewsRx correspondents, research stated, "Despite the regulations and controls implemented worldwide by governments and institutions to ensure the availability and quality of water resources, many water sources re main susceptible to contamination. This contamination poses significant risks to human health and can lead to substantial economic losses." The news correspondents obtained a quote from the research from Universidad Tecn ologica de Bolivar: "One of the challenges in this context is the presence of mi ssing or incomplete data, which can arise from various factors such as the metho dology used or the expertise of personnel involved in sample collection and anal ysis. The existence of such data gaps hampers the accurate analysis that can be conducted. To address this issue and estimate a water quality index from the ava ilable samples, it is crucial to handle missing information appropriately to avo id biased calculations. This study focuses on the application of machine learnin g methods for imputing missing data in water samples. Furthermore, it quantifies the performance of different models based on the distribution of the obtained d ata. By applying 10 distinct methods to a sample of water quality data, the most effective approaches, namely Bayesian Ridge, Gradient Boosting, Ridge, Support Vector Machine, and Theil-Sen regressors, were identified. The selection of thes e models was based on the evaluation of two estimation error metrics: average pe rcent bias (PBIAS) and Kling-Gupta Efficiency statistic (KGEss)."
      原文链接:
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    Research Data from Guangdong Ocean University Update Understanding of Robotics ( Industrial Robot Applications' Effects On Consumption of Energy and Its Spatial Effects)

    44-44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 Zhanjiang, People's Republi c of China, by NewsRx correspondents, research stated, "Industrial robot applica tions' influence on energy consumption is a significant area of concern in both theoretical and practical sectors. This study used panel data from 2006 to 2019, covering multiple Chinese provinces." Financial support for this research came from Youth Fund Project. Our news editors obtained a quote from the research from Guangdong Ocean Univers ity, "It applied panel regression and various statistical methods to investigate the potential impact of industrial robot deployment on energy consumption. Addi tionally, the research incorporated spatial variables, including adjacency matri ces, inverse geographical distance matrices, inverse economic distance matrices, and inverse industrial scale matrices. These spatial components were used in sp atial Durbin models, spatial Durbin models with quadratic terms, and spatial Dur bin models with lag terms. The analyses aimed to examine the spatial spillover e ffects of industrial robots on energy consumption, explore nonlinear characteris tics in these effects, and distinguish between short-term and long-term impacts. The research findings are as follows. Firstly, energy consumption can be greatl y reduced by industrial robot applications, and there are heterogeneous effects based on geographical location and income levels. Secondly, industrial robot app lications have spatial spillover effects that reduce energy consumption in the n eighborhood, as well as the energy consumption of other regions that border each other, are physically close together, have less economic inequality, and have s imilar industrial scales. Thirdly, the geographic spillage impacts of industrial robots demonstrate nonlinear characteristics, displaying a distribution pattern that resembles an inverted U shape when analyzed through the anti-economic dist ance matrix. Lastly, industrial robot spatial impact spillovers primarily have s hort-term effects with negligible long-term implications."
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    California Institute of Technology Researcher Has Published New Study Findings o n Robotics (EELS: Autonomous snake-like robot with task and motion planning capa bilities for ice world exploration)

    45-46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 robotics is now availab le. According to news reporting out of Pasadena, California, by NewsRx editors, research stated, "Ice worlds are at the forefront of astrobiological interest be cause of the evidence of subsurface oceans." Our news journalists obtained a quote from the research from California Institut e of Technology: "Enceladus in particular is unique among the icy moons because there are known vent systems that are likely connected to a subsurface ocean, th rough which the ocean water is ejected to space. An existing study has shown tha t sending small robots into the vents and directly sampling the ocean water is l ikely possible. To enable such a mission, NASA's Jet Propulsion Laboratory is de veloping a snake-like robot called Exobiology Extant Life Surveyor (EELS) that c an navigate Enceladus' extreme surface and descend an erupting vent to capture u naltered liquid samples and potentially reach the ocean. However, navigating to and through Enceladus' environment is challenging: Because of the limitations of existing orbital reconnaissance, there is substantial uncertainty with respect to its geometry and the physical properties of the surface/vents; communication is limited, which requires highly autonomous robots to execute the mission with limited human supervision. Here, we provide an overview of the EELS project and its development effort to create a risk-aware autonomous robot to navigate these extreme ice terrains/environments. We describe the robot's architecture and the technical challenges to navigate and sense the icy environment safely and effec tively."
      原文链接:
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    Aalen University Researcher Adds New Study Findings to Research in Machine Learn ing (Swift Prediction of Battery Performance: Applying Machine Learning Models o n Microstructural Electrode Images for Lithium-Ion Batteries)

    46-47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 Aalen, Germany , by NewsRx correspondents, research stated, "In this study, we investigate the use of artificial neural networks as a potentially efficient method to determine the rate capability of electrodes for lithium-ion batteries with different poro sities." Financial supporters for this research include Carl Zeiss Foundation; Aalen Univ ersity of Applied Sciences And Deutsche Forschungsgemeinschaft. The news correspondents obtained a quote from the research from Aalen University : "The performance of a lithium-ion battery is, to a large extent, determined by the microstructure (i.e., layer thickness and porosity) of its electrodes. Tail oring the microstructure to a specific application is a crucial process in batte ry development. However, unravelling the complex correlations between microstruc ture and rate performance using either experiments or simulations is time-consum ing and costly. Our approach provides a swift method for predicting the rate cap ability of battery electrodes by using machine learning on microstructural image s of electrode cross-sections. We train multiple models in order to predict the specific capacity based on the batteries' microstructure and investigate the dec isive parts of the microstructure through the use of explainable artificial inte lligence (XAI) methods."
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    Researchers from University of Deusto Discuss Findings in Machine Learning (Huma n-in-the-loop Machine Learning: Reconceptualizing the Role of the User In Intera ctive Approaches)

    47-47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 originating from Bilbao, Spain, by Ne wsRx correspondents, research stated, "The rise of intelligent systems and smart spaces has opened up new opportunities for human- machine collaborations. Inter active Machine Learning (IML) contribute to fostering such collaborations." Funders for this research include Basque Governments Department of Education, Sp ain, Ministry of Economy, Industry and Competitiveness of Spain for IoP, Europea n Commission through the AURORAL project. Our news journalists obtained a quote from the research from the University of D eusto, "Nonetheless, IML solutions tend to overlook critical factors such as the timing, frequency and workload that drive this interaction and are vital to ada pting these systems to users' goals and engagement. To address this gap, this wo rk explores users' expectations towards IML solutions in the context of an inter active hydration monitoring system for the workplace, which represents a challen ging environment to implement intelligent solutions that can collaborate with in dividuals. The proposed system involves users in the learning process by providi ng feedback on the success of detecting their drinking gestures and enabling the m to contribute with additional examples of their data. A qualitative study was conducted to evaluate this use case, where participants completed specific tasks with varying levels of involvement."
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    Seoul National University of Science and Technology Researchers Yield New Study Findings on Androids (Haptic interface with multimodal tactile sensing and feedb ack for human-robot interaction)

    48-48页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in android s. According to news originating from Seoul National University of Science and T echnology by NewsRx editors, the research stated, "Novel sensing and actuation t echnologies have notably advanced haptic interfaces, paving the way for more imm ersive user experiences. We introduce a haptic system that transcends traditiona l pressure-based interfaces by delivering more comprehensive tactile sensations. " The news editors obtained a quote from the research from Seoul National Universi ty of Science and Technology: "This system provides an interactive combination o f a robotic hand and haptic glove to operate devices within the wireless communi cation range. Each component is equipped with independent sensors and actuators, enabling real-time mirroring of user's hand movements and the effective transmi ssion of tactile information. Remarkably, the proposed system has a multimodal f eedback mechanism based on both vibration motors and Peltier elements. This mech anism ensures a varied tactile experience encompassing pressure and temperature sensations. The accuracy of tactile feedback is meticulously calibrated accordin g to experimental data, thereby enhancing the reliability of the system and user experience. The Peltier element for temperature feedback allows users to safely experience temperatures similar to those detected by the robotic hand."
      原文链接:
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