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 Nanning, People's Republic of China, by NewsRx correspondents, research stated, "Escape is one of the most ess ential behaviors for an animal's survival because it could be a matter of life a nd death. Much of our current understanding of the neural mechanisms underlying escape is derived from the looming paradigm, which mimics a diving aerial predat or." Our news journalists obtained a quote from the research from Guangxi University, "Yet, the idea of the looming paradigm does not account for all types of threat s like lions hunting antelopes or cats stalking mice. Escape responses to such t errestrial threats may require different strategies and neural mechanisms. Here, we developed a real-time interactive platform to study escape behavior to terre strial threats in mice. A closed-loop controlled robot was magnetically pulled t o mimic a terrestrial threat that chases a mouse. By using strong magnets and hi gh-precision servo motors, the robot is capable of moving precisely with a high spatial-temporal resolution. Different algorithms can be used to achieve single approach or persistent approach. Animal experiments showed that mice exhibited c onsistent escape behavior when exposed to an approaching robotic predator. When presented with a persistently approaching predator, the mice were able to rapidl y adapt their behavior, as evidenced by a decrease in startle responses and chan ges in movement patterns. In comparison to existing methods for studying escape behavior, such as the looming paradigm, this approach is more suitable for inves tigating animal behavior in response to sustained threats."
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 Rajasthan, India, by NewsRx correspondents, research stated, "This study's foremost objectives were to scrutinize how unexpected weather affects agricultural output and to assess h ow well AIbased machine learning and deep leaning algorithms work for spotting apple leaf diseases. The researchers carried out a bibliometric study to obtain understanding of the current research trends, citation patterns, ownership and p artnership arrangements, publishing patterns, and other parameters related to ea rly identification of apple illnesses." Our news journalists obtained a quote from the research from Amity University, " Comprehensive interdisciplinary scientific maps are limited because syndrome rec ognition is not restricted to any solitary arena of research, despite the fact t hat there have been many studies on the identification of apple diseases. By emp loying a scientometric technique and 109 publications from the Scopus database p ublished between 2011 and 2022, this study attempted to assess the condition of the research area and combine knowledge frameworks. To find important journals, authors, nations, articles, and topics, the study used the automated processes o f VOSviewer and Biblioshiny software."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Shenyang, Peop le's Republic of China, by NewsRx journalists, research stated, "Large-scale und erground hydrogen storage (UHS) plays a vital role in energy transition. H-brine interfacial tension (IFT) is a crucial parameter in structural trapping in unde rground geological locations and gaswater two-phase flow in subsurface porous m edia." The news reporters obtained a quote from the research from Northeastern Universi ty, "On the other hand, cushion gas, such as CO, is often co-injected with H to retain reservoir pressure. Therefore, it is imperative to accurately predict the (H + CO)-water/brine IFT under UHS conditions. While there have been a number o f experimental measurements on H-water/brine and (H + CO)-water/brine IFT, an ac curate and efficient (H + CO)-water/brine IFT model under UHS conditions is stil l lacking. In this work, we use molecular dynamics (MD) simulations to generate an extensive (H + CO)-water/brine IFT databank (840 data points) over a wide ran ge of temperature (from 298 to 373 K), pressure (from 50 to 400 bar), gas compos ition, and brine salinity (up to 3.15 mol/kg) for typical UHS conditions, which is used to develop an accurate and efficient machine learning (ML)-based IFT equ ation. Our MLbased IFT equation is validated by comparing to available experime ntal data and other IFT equations for various systems (H-brine/water, CO-brine/w ater, and (H + CO)-brine/water), rendering generally good performance (with = 0. 902 against 601 experimental data points)."
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 State Universi ty of New York (SUNY) Buffalo by NewsRx correspondents, research stated, "Custom er attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connec tion with the bank." The news editors obtained a quote from the research from State University of New York (SUNY) Buffalo: "Therefore, customer retention is essential in today's ext remely competitive banking market. Additionally, having a solid customer base he lps attract new consumers by fostering confidence and a referral from a current clientele. These factors make reducing client attrition a crucial step that bank s must pursue. In our research, we aim to examine bank data and forecast which u sers will most likely discontinue using the bank's services and become paying cu stomers. We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics. In addition, we developed a Data Visualization RShiny app for data science and management regarding custo mer churn analysis."
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 Beijing, People's Repu blic of China, by NewsRx correspondents, research stated, "We propose a novel ta sk-oriented and semantic-aware heterogeneous networks (TOSA-HetNets) framework f or multitype Artificial Intelligence of Things (AIoT) devices with various requi rements, where the dense edge servers with different transmission capabilities, computing resources, and power consumption are divided into different layers to provide on-demand collaboration for AIoT devices located in accessible areas. Mo reover, we propose a device-edge collaboration intelligent tasks inference schem e between edge servers and AIoT devices in TOSA-HetNets, it includes AIoT device s performing semantic features extraction and uploading the corresponding semant ic features to the associated edge servers, multiple layers of edge servers coll aborating with AIoT devices to execute the intelligent tasks and transmit the in telligent task results back to AIoT devices." Financial support for this research came from National Key R&D Prog ram of China.
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 Singapore, Singapore , by NewsRx correspondents, research stated, "To identify blood metabolite marke rs associated with intraocular pressure (IOP) in a population-based cross-sectio nal study. This study was conducted in a multiethnic Asian population (Chinese, n=2805; Indians, n=3045; Malays, n=3041 aged 40-80 years) in Singapore." Financial supporters for this research include National Medical Research Council , Singapore, National Medical Research Council, Singapore.
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 from Xi'an, People's Republi c of China, by NewsRx journalists, research stated, "This article presents a hyb rid recommender framework for smart medical systems by introducing two methods t o improve service level evaluations and doctor recommendations for patients." Our news correspondents obtained a quote from the research from First Affiliated Hospital: "The first method uses big data techniques and deep learning algorith ms to develop a registration review system in medical institutions. This system outperforms conventional evaluation methods, thus achieving higher accuracy. The second method implements the term frequency and inverse document frequency (TF- IDF) algorithm to construct a model based on the patient's symptom vector space, incorporating score weighting, modified cosine similarity, and K-means clusteri ng."
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 from the Muroran Institute of Technology by NewsRx correspondents, research stated, "Infrastructu re facilities have been deteriorating and require a vast number of inspections c onducted by skilled engineers." The news journalists obtained a quote from the research from Muroran Institute o f Technology: "Inspection robots are now necessary because of a shortage of skil led engineers. To improve the inspection efficiency of outdoor infrastructure fa cilities, we investigated an omni-directional mobile robot that can move freely in all directions. However, it is necessary to design a vibration-isolation mech anism because the positional-inspection accuracy of underground objects is adver sely affected by vibration in an outdoor environment. We constructed an experime ntal setup to evaluate the vibration properties of the robot's wheel and evaluat ed the acceleration characteristics due to the difference between the direction of movement and speed of the wheel. Experiments using the omni-wheel as the robo t's wheel were performed. We clarified that the input vibration is transmitted t o the robot body by the wheel."
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 originating from Cambridge, United Kingdom, by NewsRx correspondents, research stated, "Drones, also known as unma nned aerial vehicles, could potentially be a key part of future smart cities by aiding traffic management, infrastructure inspection and maybe even last mile de livery." Our news editors obtained a quote from the research from Anglia Ruskin Universit y: "This paper contributes to the research on managing a fleet of soaring aircra ft by gaining an understanding of the influence of the weather on soaring capabi lities. To do so, machine learning algorithms were trained on flight data, which was recorded in the UK over the past ten years at selected gliding clubs (i.e., sailplanes). A random forest regressor was trained to predict the flight durati on and a random forest (RF) classifier was used to predict whether at least one flight on a given day managed to soar in thermals. SHAP (SHapley Additive exPlan ations), a form of explainable artificial intelligence (AI), was used to underst and the predictions given by the models. The best RF have a mean absolute error of 5.7 min (flight duration) and an accuracy of 81.2% (probability of soaring in a thermal on a given day). The explanations derived from SHAP are in line with the common knowledge about the effect of weather systems to predic t soaring potential." According to the news editors, the research concluded: "However, the key conclus ion of this study is the importance of combining human knowledge with machine le arning to devise a holistic explanation of a machine learning model and to avoid misinterpretations."
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 Aalborg, Denmark, by NewsRx correspondents, research stated, "In the modern digital age, companies n eed to be able to quickly explore the process innovation affordances of digital technologies. This includes exploration of Machine Learning (ML), which when emb edded in processes can augment or automate decisions." Financial support for this research came from Manufacturing Academy of Denmark. Our news journalists obtained a quote from the research from Aalborg University, "BPM research suggests using lightweight IT (Bygstad, Journal of Information Te chnology, 32(2), 180-193 2017) for digital process innovation, but existing rese arch provides conflicting views on whether ML is lightweight or heavyweight. We therefore address the research question ‘How can Lightweight IT contribute to ex plorative BPM for embedded ML?' by analyzing four action cases from a large Dani sh manufacturer. We contribute to explorative BPM by showing that lightweight ML considerably speeds up opportunity assessment and technical implementation in t he exploration process thus reducing process innovation latency."
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