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 Ma chine Learning. According to news reporting from Delft, Netherlands, by NewsRx j ournalists, research stated, "Earthquakes have devastating effects on densely ur banised regions, requiring rapid and extensive damage assessment to guide resour ce allocation and recovery efforts. Traditional damage assessment is time-consum ing, resource-intensive, and faces challenges in covering vast affected areas, o ften limiting timely decision-making." Financial support for this research came from Netherlands Organization for Scien tific Research (NWO). The news correspondents obtained a quote from the research from the Delft Univer sity of Technology, "Space-borne synthetic aperture radars (SAR) have gained att ention for their all-weather and day-night imaging capabilities. These advantage s, coupled with wide coverage, short revisits and very high resolution (VHR), ha ve created opportunities for using SAR data in disaster response. However, most SAR studies for post-earthquake damage assessment rely on change detection metho ds using pre-event SAR images,which are often unavailable in operational scenar ios. Limited studies using solely post-event SAR data primarily concentrate on c ity-block-level damage assessment, thus not fully exploiting the VHR SAR potenti al. This paper presents a novel method integrating solely post-event VHR SAR ima gery and machine learning (ML) for regional-scale post-earthquake damage assessm ent at the individual buildinglevel. We first used supervised learning on case- specific datasets, and then introduced a combined learning approach, incorporati ng inventories from multiple case studies to assess generalisation. Finally, the ML model was tested on unseen study areas, to evaluate its flexibility in unfam iliar contexts. The method was implemented using datasets collected during the E arthquake Engineering Field Investigation Team (EEFIT) reconnaissance missions f ollowing the 2021 Nippes earthquake and the 2023 Kahramanmaras earthquake sequen ce. The results demonstrate the method's ability to classify standing and collap sed buildings, achieving up to 72% overall accuracy on unseen regi ons."
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 new report. According to news reporting from Purdue Univer sity by NewsRx journalists, research stated, "Due to their importance in weather and climate assessments, there is significant interest to represent cities in n umerical prediction models."
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 out of Zurich, Switzerland, by NewsRx editor s, research stated, "Robots were introduced in the field of upper limb neuroreha bilitation to relieve the therapist from physical labor, and to provide high-int ensity therapy to the patient. A variety of control methods were developed that incorporate patients' physiological and biomechanical states to adapt the provid ed assistance automatically." Financial support for this research came from Innosuisse - Schweizerische Agentu r fr Innovationsfrderung. Our news journalists obtained a quote from the research from the Swiss Federal I nstitute of Technology, "Higher level states, such as selected type of assistanc e, chosen task characteristics, defined session goals, and given patient impairm ents, are often neglected or modeled into tight requirements, low-dimensional st udy designs, and narrow inclusion criteria so that presented solutions cannot be transferred to other tasks, robotic devices or target groups. In this work, we present the design of a modular high-level control framework based on invariant states covering all decision layers in therapy. We verified the functionality of our framework on the assistance and task layer by outlaying the invariant state s based on the characteristics of 20 examined state-of-the-art controllers. Then , we integrated four controllers on each layer and designed two algorithms that automatically selected suitable controllers. The framework was deployed on an ar m rehabilitation robot and tested on one participant acting as a patient. We obs erved plausible system reactions to external changes by a second operator repres enting a therapist."
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 the Swiss Fed eral Institute of Technology Zurich (ETH) by NewsRx editors, the research stated , "Concerns about data privacy are omnipresent, given the increasing usage of di gital applications and their underlying business model that includes selling use r data." Funders for this research include Swiss Federal Institute of Technology Zurich. Our news editors obtained a quote from the research from Swiss Federal Institute of Technology Zurich (ETH): "Location data is particularly sensitive since they allow us to infer activity patterns and interests of users, e.g., by categorizi ng visited locations based on nearby points of interest (POI). On top of that, m achine learning methods provide new powerful tools to interpret big data. In lig ht of these considerations, we raise the following question: What is the actual risk that realistic, machine learning based privacy attacks can obtain meaningfu l semantic information from raw location data, subject to inaccuracies in the da ta? In response, we present a systematic analysis of two attack scenarios, namel y location categorization and user profiling. Experiments on the Foursquare data set and tracking data demonstrate the potential for abuse of high-quality spatia l information, leading to a significant privacy loss even with location inaccura cy of up to 200 m. With location obfuscation of more than 1 km, spatial informat ion hardly adds any value, but a high privacy risk solely from temporal informat ion remains. The availability of public context data such as POIs plays a key ro le in inference based on spatial information."
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 in Marseille, France, by NewsRx journalists, research stated, "The LIBERTY®Robotic System is a miniature , single-use device designed to facilitate remote-controlled navigation to intra vascular targets. We aim to evaluate the robot's performance to manipulate a ran ge of microguidewires and microcatheters during percutaneous endovascular proced ures." The news reporters obtained a quote from the research from University Hospital, "Six interventional radiologists performed selective robotic-assisted catheteriz ation of eight pre-determined vascular targets in a pig model. The navigation ti me from the guiding catheter tip to the target vessel was recorded. Each physici an with a clinical experience of 20 years completed a questionnaire to evaluate the ease of use, accuracy, and safety of the robotic operation. Most of the phys icians reached the vascular targets in less than one minute. There was no angiog raphic evidence of vascular injury such as artery laceration or contusion. All p hysicians reported consensus about the high performance of the robot. The miniat ure disposable robot is effective at reaching a range of vessels in a porcine mo del."
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 artificial intell igence have been published. According to news reporting originating from Hong Ko ng, People's Republic of China, by NewsRx correspondents, research stated, "Opti mal power flow (OPF) is a crucial tool in the operation and planning of modern p ower systems." Funders for this research include The Hong Kong Polytechnic University. Our news reporters obtained a quote from the research from Hong Kong Polytechnic University: "However, as power system optimization shifts towards larger-scale frameworks, and with the growing integration of distributed generations, the com putational time and memory requirements of solving the alternating current (AC) OPF problems can increase exponentially with system size, posing computational c hallenges. In recent years, machine learning (ML) has demonstrated notable advan tages in efficient computation and has been extensively applied to tackle OPF ch allenges."
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 originating in Oslo, Norway , by NewsRx journalists, research stated, "While momentum-based accelerated vari ants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that there exists a convex l oss function for which the stability gap for multiple epochs of SGD with standar d heavy-ball momentum (SGDM) becomes unbounded." Funders for this research include Research Council of Norway, Research Council o f Norway, Hasler Foundation Program: Hasler Responsible AI, Swiss National Scien ce Foundation (SNSF), CGIAR.
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 Ma chine Learning. According to news reporting from Shenyang, People's Republic of China, by NewsRx journalists, research stated, "The mutual constraint between se nsitivity and measurement range has always been a problem that restricts the dev elopment and application of optical fiber interference sensors. We propose a new high-sensitivity tapered dual-parameter optical fiber sensor packaged with poly dimethylsiloxane (PDMS) in this article." Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), State Key Laborat ory of Synthetical Automation for Process Industries, Natural Science Foundation of Hebei Province.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Surgical Procedures - Ureteroscopy is the subject of a report. According to news originating from Ista nbul, Turkey, by NewsRx correspondents, research stated, "The management of kidn ey stones, particularly those in the renal pelvis, is a critical aspect of urolo gy. The European Association of Urology guidelines recommend Extracorporeal Shoc k Wave Lithotripsy or Endourology methods, encompassing Percutaneous Nephrolitho tomy and Ureterorenoscopy (URS), for stones ranging from 10-20 mm." Our news journalists obtained a quote from the research from Istanbul University , "Robotic-assisted urological procedures have gained prominence in recent years , promising enhanced precision, and safety. This article aims to provide a detai led account of the technical aspects and outcomes of a robotic URS (robo-URS) pr ocedure in a 63-year-old male patient with a 15 mm renal pelvis stone, serving a s a reference for urologists considering this approach. The patient presented wi th right flank pain, and an unenhanced computed tomography scan confirmed the pr esence of a 15x12x13 mm stone in the right renal pelvis. After assessment and pr eparation, robo-URS was performed using the Roboflex Avicenna robotic platform ( ELMED, Ankara, Turkey) in conjunction with conventional urological instruments a nd laser technology. The procedure was completed successfully in 50 minutes with out any detectable blood loss or intraoperative complications. Robotic-assisted Ureterorenoscopy (robo-URS) is a promising approach for managing renal pelvis st ones."
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 robotic s. According to news reporting from Nanyang Technological University by NewsRx j ournalists, research stated, "The uncanny valley (UV) effect captures the observ ation that artificial entities with near-human appearances tend to create feelin gs of eeriness. Researchers have proposed many hypotheses to explain the UV effe ct, but the visual processing mechanisms of the UV have yet to be fully understo od." Funders for this research include Nanyang Technological University. The news correspondents obtained a quote from the research from Nanyang Technolo gical University: "In the present study, we examined if the UV effect is as acce ssible in brief stimulus exposures compared to long stimulus exposures (Experime nt 1). Forty-one participants, aged 21-31, rated each human-robot face presented for either a brief (50 ms) or long duration (3 s) in terms of attractiveness, e eriness, and humanness (UV indices) in a 7-point Likert scale. We found that bri ef and long exposures to stimuli generated a similar UV effect. This suggests th at the UV effect is accessible at early visual processing. We then examined the effect of exposure duration on the categorisation of visual stimuli in Experimen t 2. Thirty-three participants, aged 21-31, categorised faces as either human or robot in a two-alternative forced choice task. Their response accuracy and vari ance were recorded. We found that brief stimulus exposures generated significant ly higher response variation and errors than the long exposure condition. This i ndicated that participants were more uncertain in categorising faces in the brie f exposure condition due to insufficient time. Further comparisons between Exper iment 1 and 2 revealed that the eeriest faces were not the hardest to categorise ."
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