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    Uppsala University Reports Findings in Artificial Intelligence (Machine Learning Based Prediction of Imminent ICP Insults During Neurocritical Care of Traumatic Brain Injury)

    39-40页
    查看更多>>摘要:New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Uppsala, Sweden, by NewsRx journalists, research stated, "In neurointensive care, increased intra cranial pressure (ICP) is a feared secondary brain insult in traumatic brain inj ury (TBI). A system that predicts ICP insults before they emerge may facilitate early optimization of the physiology, which may in turn lead to stopping the pre dicted ICP insult from occurring." Financial supporters for this research include Vetenskapsradet, Kjell och Marta Beijers Stiftelse, Uppsala University.

    Prince Mohammad Bin Fahd University Researcher Has Provided New Data on Machine Learning (Employing combined spatial and frequency domain image features for mac hine learning-based malware detection)

    40-41页
    查看更多>>摘要:Investigators publish new report on ar tificial intelligence. According to news reporting out of Prince Mohammad Bin Fa hd University by NewsRx editors, research stated, "The ubiquitous adoption of An droid devices has unfortunately brought a surge in malware threats, compromising user data, privacy concerns, and financial and device integrity, to name a few. To combat this, numerous efforts have explored automated botnet detection mecha nisms, with anomaly-based approaches leveraging machine learning (ML) gaining at traction due to their signature-agnostic nature." Our news editors obtained a quote from the research from Prince Mohammad Bin Fah d University: "However, the problem lies in devising accurate ML models which ca pture the ever evolving landscape of malwares by effectively leveraging all the possible features from Android application packages (APKs).This paper delved int o this domain by proposing, implementing, and evaluating an image-based Android malware detection (AMD) framework that harnessed the power of feature hybridizat ion. The core idea of this framework was the conversion of text-based data extra cted from Android APKs into grayscale images. The novelty aspect of this work li ed in the unique image feature extraction strategies and their subsequent hybrid ization to achieve accurate malware classification using ML models. More specifi cally, four distinct feature extraction methodologies, namely, Texture and histo gram of oriented gradients (HOG) from spatial domain, and discrete wavelet trans form (DWT) and Gabor from the frequency domain were employed to hybridize the fe atures for improved malware identification. To this end, three image-based datas ets, namely, Dex, Manifest, and Composite, derived from the information security centre of excellence (ISCX) Android Malware dataset, were leveraged to evaluate the optimal data source for botnet classification. Popular ML classifiers, incl uding naive Bayes (NB), multilayer perceptron (MLP), support vector machine (SVM ), and random forest (RF), were employed for the classification task."

    Studies from Federal University Paraiba Yield New Data on Artificial Intelligenc e (The Over-concentration of Innovation and Firmspecific Knowledge In the Artif icial Intelligence Industry)

    41-41页
    查看更多>>摘要:Current study results on Artificial In telligence have been published. According to news originating from Joao Pessoa, Brazil, by NewsRx correspondents, research stated, "The development of the artif icial intelligence (AI) landscape has been impressive in virtually all economic sectors in recent years. Our study discusses the over-concentration of AI knowle dge (OCAIK) as the origin of dominance over the global AI industry by a small nu mber of companies and universities that deploy the needed resources to develop a nd use cutting edge, inimitable AI knowledge." Our news journalists obtained a quote from the research from Federal University Paraiba, "Business agents appropriate AI-related scholarly research and absorb r esearch findings that grant them increasingly inimitable competitive advantages over new entrants. Our study verifies the occurrence of OCAIK by processing thou sands of papers presented in AI conferences from 2013 to 2022. To analyze our hy potheses, we used classification techniques and inferential statistics. We found a significant difference between clusters of companies that we called ordinary investors and outlier investors. We also observed the influence of universities in the correlation between OCAIK and investments made in both research and devel opment (R&D) and capital goods. Our findings indicate a strong coll aboration between AI leading companies and universities in generating firm-speci fic AI knowledge."

    Investigators from Trinity College Dublin Have Reported New Data on Computationa l Intelligence (Multi-medium Image Enhancement With Attentive Deformable Transfo rmers)

    42-43页
    查看更多>>摘要:New research on Machine Learning-Com putational Intelligence is the subject of a report. According to news reporting originating in Dublin, Ireland, by NewsRx journalists, research stated, "Visibil ity challenges such as atmospheric haze, water turbidity, etc. are imposed while capturing images in various mediums like aerial, outdoor, underwater, etc. Such reduction in visibility affects the functioning of high-level computer vision a pplications like object detection, semantic segmentation, military surveillance, earthquake assessment, etc."

    Researchers from Dalian Neusoft University of Information Provide Details of New Studies and Findings in the Area of Artificial Intelligence (Prediction of Drou ght Hydrological and Water Scarcity Based On Optimal Artificial Intelligence By ...)

    42-42页
    查看更多>>摘要:2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on Artificial Intelligence is now ava ilable. According to news reporting from Liaoning, People's Republic of China, b y NewsRx journalists, research stated, "This study presents a novel approach to predicting water stress in Yichang City, China, through an optimized Capsule Neu ral Network (CapsNN) model enhanced by the Improved Aquila Optimization (IAO) al gorithm. The model, applied to monthly water stress data from 2000 to 2022, is g auged using the Streamflow Drought Index (SDI)." The news correspondents obtained a quote from the research from the Dalian Neuso ft University of Information, "When compared to traditional metaheuristic models , our CapsNN/IAO framework demonstrates superior accuracy in drought forecasting across various time scales with significant reductions in The Mean Absolute Err or is 0.1021, the Root Mean Square Error is 0.1824, and good the Nash-Sutcliffe Efficiency is 0.75, the coefficient of determination R2 is 0.89, and the Willmot t's Index is 0.93. Notably, the model predicts short-term water shortages with g reater frequency at the SDI3 scale, while identifying the most severe drought co nditions at the SDI6 scale."

    Data from University of Electronic Science and Technology of China Advance Knowl edge in Machine Learning (A High Stability Clustering Scheme for the Internet of Vehicles)

    43-44页
    查看更多>>摘要:Current study results on Machine Learn ing have been published. According to news reporting originating in Shenzhen, Pe ople's Republic of China, by NewsRx journalists, research stated, "In existing r esearch on cluster head selection schemes in the Internet of Vehicles (IoV), des igning a stable cluster structure poses a significant challenge. Choosing a cent rally-located cluster head that can respond rapidly is crucial for meeting vario us requirements." Funders for this research include National Key Research & Developm ent Program of China, National Natural Science Foundation of China (NSFC), Shenz hen Science and Technology Program, Key research and development plan of Shaanxi province, National Natural Science Foundation of Guangdong Province, Key Projec t on Artificial Intelligence of Xi'an Science and Technology Plan, Xi'an Science and Technology Plan, Proof-of-concept fund from Hangzhou Research Institute of Xidian University.

    Corteva Agriscience Reports Findings in Machine Learning (High-Throughput Image- Based Assay for Identifying In Vitro Hepatocyte Microtubule Disruption)

    44-45页
    查看更多>>摘要:New research on Machine Learning is th e subject of a report. According to news reporting from Indianapolis, Indiana, b y NewsRx journalists, research stated, "Disruption of microtubule stability in m ammalian cells may lead to genotoxicity and carcinogenesis. The ability to scree n for microtubule destabilization or stabilization is therefore a useful and eff icient approach to aid in the design of molecules that are safe for human health ." The news correspondents obtained a quote from the research from Corteva Agriscie nce, "In this study, we developed a high-throughput 384-well assay combining imm unocytochemistry with high-content imaging to assess microtubule disruption in t he metabolically competent human liver cell line: HepaRG. To enhance analysis th roughput, we implemented a supervised machine learning approach using a curated training library of 180 compounds. A majority voting ensemble of eight machine l earning classifiers was employed for predicting microtubule disruptions. Our pre diction model achieved over 99.0% accuracy and a 98.4% F1 score, which reflects the balance between precision and recall for in-sample validation and 93.5 % accuracy and a 94.3% F1 score f or out-of-sample validation."

    New Robotics Study Results Reported from Texas A&M University (A Hy brid Task-constrained Motion Planning for Collaborative Robots In Intelligent Re manufacturing)

    45-46页
    查看更多>>摘要:2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on Robotics is now available. Accordi ng to news reporting originating from College Station, Texas, by NewsRx correspo ndents, research stated, "Industrial manipulators have extensively collaborated with human operators to execute tasks, e.g., disassembly of end-of-use products, in intelligent remanufacturing. A safety task execution requires real-time path planning for the manipulator's end-effector to autonomously avoid human operato rs." Financial support for this research came from National Science Foundation (NSF).

    ASST Santi Paolo e Carlo Reports Findings in Radical Cystectomy (Robotic-Assiste d Radical Cystectomy: Single-Center Analysis of Factors Impacting Clavien II Com plications)

    46-47页
    查看更多>>摘要:New research on Surgery-Radical Cyst ectomy is the subject of a report. According to news originating from Milan, Ita ly, by NewsRx correspondents, research stated, "Despite the advent of robotics a nd the decreasing rate of complications after radical cystectomy, several factor s are renowned to impair the early outcomes of this procedure. The aim of this p aper is to provide a multivariate analysis (MVA) of patient and surgical procedu re-related variables likely to affect postoperative course and 30-day complicati on rate." Our news journalists obtained a quote from the research from ASST Santi Paolo e Carlo, "Fifty-five robotic-assisted radical cystectomies (RARCs) performed at a single center from July 2021 to March 2023 were enrolled. Baseline demographics, comorbidities, and intraoperative and postoperative data were collected. Uni- a nd multivariate analyses were performed to evaluate the relationship with Clavie n II complications arising within 30 days of surgery. A postoperative Clavien II complication was evident in 15 patients (28%), whereas Clavien III occurred only in 5 (9%). At MVA, the only independent predictor of Clavien II complications was a prior neoadjuvant chemotherapy (OR 5.6; 95% CI 1.22-25.3, = 0.026)."

    Findings from University of New South Wales Sydney Has Provided New Data on Robo tics (Soft Upper-limb Wearable Robotic Devices: Technology and Applications)

    47-48页
    查看更多>>摘要:Current study results on Robotics have been published. According to news originating from Sydney, Australia, by NewsRx correspondents, research stated, "One of the practical applications in the fiel d of soft robotics involves the development of soft robotic wearable devices. Th ese devices make use of their intrinsically compliant structures to interact saf ely and harmoniously with the human body." Financial support for this research came from National Heart Foundation of Austr alia. Our news journalists obtained a quote from the research from the University of N ew South Wales Sydney, "While soft wearable robots demonstrate their utility in lower-limb applications for locomotion, the upper-limb domain offers significant prospects in a wide range of applications that soft robotic technology can addr ess. In this review, the current state of technology in the field of soft wearab le upper limbs is systematically analyzed and categorized. Categorizations are m ade based on their applications in rehabilitation, activities of daily living su pport, and human augmentation. Furthermore, in this study, also contemporary tec hnological aspects, encompassing sensing technology and control systems, are exp lored. Despite exciting potential in this domain, several limitations from exist ing devices inherently impede widespread adoption and thus hinder further progre ss in the field. In this study, also an overview of the different facets of the domain is provided and key considerations for the advancement of soft wearable r obotic devices intended for upper-limb applications are prescribed. In this arti cle, current state of art of soft robotic devices for the upper body is reviewed , exploring how they help in rehabilitation, daily activities, and enhancing hum an abilities."