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    New Artificial Intelligence Study Results from Edith Cowan UniversityDescribed (Malware Detection With Artificial Intelligence: aSystematic Literature Review)

    84-84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 originating in Joondalup, Aus tralia, by NewsRx journalists, research stated, “In this survey, we review the k ey developments in the field of malware detection using AI and analyze core chal lenges. We systematically survey state-of-the-art methods across five critical a spects of building an accurate and robust AI-powered malware-detection model: ma lware sophistication, analysis techniques, malware repositories, feature selecti on, and machine learning vs. deep learning.” The news reporters obtained a quote from the research from Edith Cowan Universit y, “The effectiveness of an AI model is dependent on the quality of the features it is trained with. In turn, the quality and authenticity of these features is dependent on the quality of the dataset and the suitability of the analysis tool . Static analysis is fast but is limited by the widespread use of obfuscation. D ynamic analysis is not impacted by obfuscation but is defeated by ubiquitous ant i-analysis techniques and requires more computational power.”

    University of Granada Researcher Publishes New Studies and Findings in the Area of Robotics (Neuromorphic Perception and Navigation for Mobile Robots: A Review)

    85-85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 robotics have been pr esented. According to news originating from Granada, Spain, by NewsRx correspond ents, research stated, “With the fast and unstoppable evolution of robotics and artificial intelligence, effective autonomous navigation in real-world scenarios has become one of the most pressing challenges in the literature.” Financial supporters for this research include Spanish National; Erdf/eu. The news reporters obtained a quote from the research from University of Granada : “However, demanding requirements, such as real-time operation, energy and comp utational efficiency, robustness, and reliability, make most current solutions u nsuitable for real-world challenges. Thus, researchers are fostered to seek inno vative approaches, such as bio-inspired solutions. Indeed, animals have the intr insic ability to efficiently perceive, understand, and navigate their unstructur ed surroundings. To do so, they exploit self-motion cues, proprioception, and vi sual flow in a cognitive process to map their environment and locate themselves within it. Computational neuroscientists aim to answer “how” and “why” such cogn itive processes occur in the brain, to design novel neuromorphic sensors and met hods that imitate biological processing.”

    Affiliated Hospital of Nantong University Reports Findings in Inflammatory Bowel Disease (The shared circulating diagnostic biomarkers and molecular mechanisms of systemic lupus erythematosus and inflammatory bowel disease)

    86-87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 Digestive System Disea ses and Conditions - Inflammatory Bowel Disease is the subject of a report. Acco rding to news reporting originating from Nantong, People’s Republic of China, by NewsRx correspondents, research stated, “Systemic lupus erythematosus (SLE) is a multi-organ chronic autoimmune disease. Inflammatory bowel disease (IBD) is a common chronic inflammatory disease of the gastrointestinal tract.” Our news editors obtained a quote from the research from the Affiliated Hospital of Nantong University, “Previous studies have shown that SLE and IBD share comm on pathogenic pathways and genetic susceptibility, but the specific pathogenic m echanisms remain unclear. The datasets of SLE and IBD were downloaded from the G ene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identif ied using the Limma package. Weighted gene coexpression network analysis (WGCNA) was used to determine co-expression modules related to SLE and IBD. Pathway enr ichment was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes a nd Genomes (KEGG) analysis for co-driver genes. Using the Least AbsoluteShrinkag e and Selection Operator (Lasso) regressionand Support Vector Machine-Recursive Feature Elimination (SVM-RFE), common diagnostic markers for both diseases were further evaluated. Then, we utilizedthe CIBERSORT method to assess the abundance of immune cell infiltration. Finally,we used the single-cell analysis to obtain the location of common diagnostic markers. 71 common driver genes were identifi ed in the SLE and IBD cohorts based on the DEGs and module genes. KEGG and GO en richment results showed that these genes were closely associated with positive r egulation of programmed cell death and inflammatory responses. By using LASSO re gression and SVM, five hub genes (KLRF1, GZMK, KLRB1, CD40LG, and IL-7R) were ul timately determined as common diagnostic markers for SLE and IBD. ROC curve anal ysis also showed good diagnostic performance. The outcomes of immune cell infilt ration demonstrated that SLE and IBD shared almost identical immune infiltration patterns. Furthermore, the majority of the hub genes were commonly expressed in NK cells by single-cell analysis. This study demonstrates that SLE and IBD shar e common diagnostic markers and pathogenic pathways.”

    Findings from King’s College London in Robotics and Automation Reported (Univers al Actuation Module and Kinematic Model for Heart Valve Interventional Catheter Robotization)

    87-88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 Robotics - Robotics a nd Automation have been presented. According to news reporting out of London, Un ited Kingdom, by NewsRx editors, research stated, “Catheters have been widely us ed to deal with heart valve diseases. However, the diversity in handle structure s and bending curvatures imposes significant complexities in safe delivery and p ositioning.” Financial support for this research came from China Scholarship Council. Our news journalists obtained a quote from the research from King’s College Lond on, “In this letter, we designed a module for single knob actuation assembled co axially on the catheter handle, composed of a chuck for universal clamping of di ameters from 15 to 45 mm and a position-adjustable shaft to accommodate various spacing between knobs. In addition, we proposed a two-curvature with pseudo join ts (TC-PJ) model for bending control of bendable sections (BSs) in catheters. Th e verification was decoupled into two steps based on the other three deformation patterns. Firstly, comparing the two-curvature (TC) model with pseudo-rigid-bod y (PRB), constant curvature (CC), and Euler spiral (ES) models to simulate plana r bending and elongation, the results showed a more accurate shape representatio n. Then, five distinct catheters were employed to test the clamping universality of the module and tip positioning precision of the TC-PJ model which took torsi on and shear strain into consideration. The rootmean- square error (RMSE) and th e standard deviation (SD) of tip position and direction were analysed. Results i ndicated the module’s suitability for clamping these catheters, with the large g uide sheath exhibiting minimal position RMSE (SD) of around 0.10 (0.051) mm and 0.049 (2.15) degrees, while the puncture catheter demonstrated the highest posit ion and direction RMSE (SD) extending to about 1.16 (0.53) mm and 0.70 (31.33) d egrees, primarily attributed to the coupling of two sequential bendable componen ts.”

    Ulm University Reports Findings in Delirium [Introducing a ma chine learning algorithm for delirium prediction-the Supporting SURgery with GEr iatric Co-Management and AI project (SURGE-Ahead)]

    88-89页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Nervous System Diseases and Condi tions - Delirium is the subject of a report. According to news reporting origina ting from Ulm, Germany, by NewsRx correspondents, research stated, “Post-operati ve delirium (POD) is a common complication in older patients, with an incidence of 14-56 %. To implement preventative procedures, it is necessary to identify patients at risk for POD.” Financial support for this research came from German Federal Ministry of Educati on and Research. Our news editors obtained a quote from the research from Ulm University, “In the present study, we aimed to develop a machine learning (ML) model for POD predic tion in older patients, in close cooperation with the PAWEL (patient safety, cos t-effectiveness and quality of life in elective surgery) project. The model was trained on the PAWEL study’s dataset of 878 patients (no intervention, age 70, 2 09 with POD). Presence of POD was determined by the Confusion Assessment Method and a chart review. We selected 15 features based on domain knowledge, ethical c onsiderations and a recursive feature elimination. A logistic regression and a l inear support vector machine (SVM) were trained, and evaluated using receiver op erator characteristics (ROC). The selected features were American Society of Ane sthesiologists score, multimorbidity, cut-to-suture time, estimated glomerular f iltration rate, polypharmacy, use of cardio-pulmonary bypass, the Montreal cogni tive assessment subscores ‘memory’, ‘orientation’ and ‘verbal fluency’, pre-exis ting dementia, clinical frailty scale, age, recent falls, post-operative isolati on and pre-operative benzodiazepines. The linear SVM performed best, with an ROC area under the curve of 0.82 [95% CI 0.78-0.85 ] in the training set, 0.81 [95% CI 0.71-0.88] in the test set and 0.76 [95 % CI 0.71-0.79] in a cross-centre validation. W e present a clinically useful and explainable ML model for POD prediction.” According to the news editors, the research concluded: “The model will be deploy ed in the Supporting SURgery with GEriatric Co-Management and AI project.”

    Findings in the Area of Artificial Intelligence Reported from University of Shef field (Ai-based Optimisation of Total Machining Performance: a Review)

    89-90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 reporting originating in Sheffi eld, United Kingdom, by NewsRx journalists, research stated, “Advanced modelling and optimisation techniques have been widely used in recent years to enable int elligent manufacturing and digitalisation of manufacturing processes. In this co ntext, the integration of artificial intelligence in machining provides a great opportunity to enhance the efficiency of operations and the quality of produced components.” The news reporters obtained a quote from the research from the University of She ffield, “Machine learning methods have already been applied to optimise various individual objectives concerning process characteristics, tool wear, or product quality in machining. However, the overall improvement of the machining process requires multi-objective optimisation approaches, which are rarely considered an d implemented. The state-of-the-art in application of various optimisation and a rtificial intelligence methods for process optimisation in machining operations, including milling, turning, drilling, and grinding, is presented in this paper. The Milling process and deep learning are found to be the most widely researche d operation and implemented machine learning technique, respectively. The surfac e roughness turns out to be the most critical quality measure considered. The di fferent optimisation targets in artificial intelligence applications are elabora ted and analysed to highlight the need for a holistic approach that covers all c ritical aspects of the machining operations. As a result, the key factors for a successful total machining performance improvement are identified and discussed in this paper.”

    Study Results from University of Virginia Provide New Insights into Robotics (St ereoscopic artificial compound eyes for spatiotemporal perception in three-dimen sional space)

    90-91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 robotic s. According to news reporting originating from Charlottesville, Virginia, by Ne wsRx correspondents, research stated, “Arthropods’ eyes are effective biological vision systems for object tracking and wide field of view because of their stru ctural uniqueness; however, unlike mammalian eyes, they can hardly acquire the d epth information of a static object because of their monocular cues.” The news journalists obtained a quote from the research from University of Virgi nia: “Therefore, most arthropods rely on motion parallax to track the object in three-dimensional (3D) space. Uniquely, the praying mantis (Mantodea) uses both compound structured eyes and a form of stereopsis and is capable of achieving ob ject recognition in 3D space. Here, by mimicking the vision system of the prayin g mantis using stereoscopically coupled artificial compound eyes, we demonstrate d spatiotemporal object sensing and tracking in 3D space with a wide field of vi ew. Furthermore, to achieve a fast response with minimal latency, data storage/t ransportation, and power consumption, we processed the visual information at the edge of the system using a synaptic device and a federated split learning algor ithm. The designed and fabricated stereoscopic artificial compound eye provides energy-efficient and accurate spatiotemporal object sensing and optical flow tra cking. It exhibits a root mean square error of 0.3 centimeter, consuming only ap proximately 4 millijoules for sensing and tracking.”

    Data on Machine Learning Detailed by Researchers at Korea Institute of Medical M icrorobotics (Field-Free Region Scanning-Based Magnetic Microcarrier Targeting i n Multibifurcation Vessels)

    91-91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 new report. According to news reporting from the Korea Ins titute of Medical Microrobotics by NewsRx journalists, research stated, “Navigat ion of microcarriers in complex environments as a vascular network remains an op en challenge due to limited solutions for effective targeting strategy.” Financial supporters for this research include Korea Medical Device Development Fund; Ministry of Trade, Industry And Energy.

    Researchers at China Institute of Water Resources and Hydropower Research Report New Data on Machine Learning (Lai-enhanced Analytical Modeling and Machine Lear ning Predictions of Vegetative Flow Resistance With Application In Meander Evolu tion ...)

    92-92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 reporting originating from Beijing, Pe ople’s Republic of China, by NewsRx correspondents, research stated, “Riparian v egetation imposes complex flow resistance, influencing hydraulics and morphodyna mics of meandering rivers. Analytical characterizations remain limited regarding flexible foliage reconfiguration and leaf area index (LAI) impacts.” Funders for this research include Significant Science and Technology Project of the Ministry of Water Resources, China, Basic Scientific Research Project of the China Institute of Water Resources and Hydropower Research, National Natural Sc ience Foundation of China (NSFC), Open Research Fund of Key Laboratory of Sedime nt Science and Northern River Training, Ministry of Water Resources, China Insti tute of Water Resources and Hydropower Research.

    Ludwig-Maximilians-Universitat Munchen Reports Findings in Machine Learning (A r efined approach for evaluating small datasets via binary classification using ma chine learning)

    93-93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 Machine Learning is th e subject of a report. According to news reporting originating in Munich, German y, by NewsRx journalists, research stated, “Classical statistical analysis of da ta can be complemented or replaced with data analysis based on machine learning. However, in certain disciplines, such as education research, studies are freque ntly limited to small datasets, which raises several questions regarding biases and coincidentally positive results.” The news reporters obtained a quote from the research from Ludwig-Maximilians-Un iversitat Munchen, “In this study, we present a refined approach for evaluating the performance of a binary classification based on machine learning for small d atasets. The approach includes a non-parametric permutation test as a method to quantify the probability of the results generalising to new data. Furthermore, w e found that a repeated nested cross-validation is almost free of biases and yie lds reliable results that are only slightly dependent on chance. Considering the advantages of several evaluation metrics, we suggest a combination of more than one metric to train and evaluate machine learning classifiers. In the specific case that both classes are equally important, the Matthews correlation coefficie nt exhibits the lowest bias and chance for coincidentally good results.”