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    Data from University of Maine at Presque Isle Broaden Understanding of Machine L earning (Exploring Childhood Disabilities in Fragile Families: Machine Learning Insights for Informed Policy Interventions)

    28-29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 from Presque Isle, Maine, by NewsRx journalists, research stated, “This study delves into the multifaceted c hallenges confronting children from vulnerable or fragile families, with a speci fic focus on learning disabilities, resilience (measured by grit), and material hardship-a factor intricately linked with children’s disabilities.” Our news editors obtained a quote from the research from University of Maine at Presque Isle: “Leveraging the predictive capabilities of machine learning (ML), our research aims to discern the determinants of these outcomes, thereby facilit ating evidence-based policy formulation and targeted interventions for at-risk p opulations. The dataset underwent meticulous preprocessing, including the elimin ation of records with extensive missing values, the removal of features with min imal variance, and the imputation of medians for categorical data and means for numerical data. Advanced feature selection techniques, incorporating mutual info rmation, the least absolute shrinkage and selection operator (LASSO), and tree-b ased methods, were employed to refine the dataset and mitigate overfitting. Addi tionally, we addressed the challenge of class imbalance through the implementati on of the Synthetic Minority Over-sampling Technique (SMOTE) to enhance model ge neralization. Various ML models, encompassing Random Forest, Neural Networks [multilayer perceptron (MLP)], Gradient-Boosted Trees (XGBoost ), and a Stacking Ensemble Model, were evaluated on the Future of Families and C hild Wellbeing Study (FFCWS) dataset, with fine-tuning facilitated by Bayesian o ptimization techniques.”

    Researcher from National University of Singapore Publishes Findings in Machine L earning (Efficient machine learning-assisted failure analysis method for circuit -level defect prediction)

    29-30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 out of National Unive rsity of Singapore by NewsRx editors, research stated, “Integral to the success of transistor advancements is the accurate use of failure analysis (FA) which be nefits in fine-tuning and optimization of the fabrication processes. However, th e chip makers face several FA challenges as device sizes, structure, and materia l complexities scale dramatically.” The news journalists obtained a quote from the research from National University of Singapore: “To sustain manufacturability, one can accelerate defect identifi cation at all steps of the chip processing and design. On the other hand, as tec hnologies scale below the nanometer nodes, devices are more sensitive to unavoid able process-induced variability. Therefore, metallic defects and process-induce d variability need to be treated concurrently in the context of chip scaling, wh ile failure diagnostic methods to decouple the effects should be developed. Inde ed, the locating a defective component from thousands of circuits in a microchip in the presence of variability is a tedious task. This work shows how the SPICE circuit simulations coupled with machine learning based-physical modeling shoul d be effectively used to tackle such a problem for a 6T-SRAM bit cell. An automa tic bridge defect recognition system for such a circuit is devised by training a predictive model on simulation data. For feature descriptors of the model, the symmetry of the circuit and a fundamental material property are leveraged: metal s (semiconductors) have a positive (negative) temperature coefficient of resista nce up to a certain voltage range.”

    Data on Machine Learning Reported by Researchers at School of Resources & Safety Engineering (Uniaxial Compressive Strength Prediction for Rock Material I n Deep Mine Using Boosting-based Machine Learning Methods and Optimization Algor ithms)

    30-31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 Machine Lea rning. According to news originating from Changsha, People’s Republic of China, by NewsRx correspondents, research stated, “Traditional laboratory tests for mea suring rock uniaxial compressive strength (UCS) are tedious and timeconsuming. T here is a pressing need for more effective methods to determine rock UCS, especi ally in deep mining environments under high in-situ stress.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).

    Researchers from University of Florida Report on Findings in Machine Learning (V alidation Workflow for Machine Learning Interatomic Potentials for Complex Ceram ics)

    31-32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 Gainesville, F lorida, by NewsRx journalists, research stated, “The number of published Machine Learning Interatomic Potentials (MLIPs) has increased significantly in recent y ears. These new data-driven potential energy approximations often lack the physi cs-based foundations that inform many traditionally-developed interatomic potent ials and hence require robust validation methods for their accuracy, computation al efficiency, and applicability to the intended applications.” The news reporters obtained a quote from the research from the University of Flo rida, “This work presents a sequential, three-stage workflow for MLIP validation : (i) preliminary validation, (ii) static property prediction, and (iii) dynamic property prediction. This material-agnostic procedure is demonstrated in a tuto rial approach for the development of a robust MLIP for boron carbide (B4C), a wi dely employed, structurally complex ceramic that undergoes a deleterious deforma tion mechanism called ‘amorphization’ under high-pressure loading.”

    Researchers at University of Picardie Jules Verne Have Reported New Data on Robo tics and Automation (Focusing On Object Extremities for Tree Instance Segmentati on In Forest Environments)

    32-33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 originating from Amiens, France, by NewsRx correspondents, research stated, “As part of the devel opment of many robotic systems for the forestry sector, forest scene understandi ng requires the use of computer vision algorithms. However, this dense and unstr uctured environment is complex and puts conventional detection approaches to the test.” Financial support for this research came from Agence Nationale de la Recherche ( ANR). Our news editors obtained a quote from the research from the University of Picar die Jules Verne, “In the case of tree instance segmentation, the presence of clo sely spaced or even intertwined trees, their highly variable shapes, and complex masks due to their branches and leaves are just some of the challenges to be ov ercome. For this, specific learning of tree boundaries is required to better dis tinguish one from another. In this letter, we propose ConvexMask, a convolutiona l neural network for real-time instance segmentation. ConvexMask opts for a labe l representation approach with a convex exterior polygon, defined by tree extrem ities, and a binary mask to handle the detail and occlusions that the label may contain.”

    Studies Conducted at Kwame Nkrumah University of Science and Technology on Artif icial Intelligence Recently Published [ChatGPT effects on cog nitive skills of undergraduate students: Receiving instant responses from AI-bas ed conversational large ...]

    33-33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 originating from Kwame Nkrumah University o f Science and Technology by NewsRx correspondents, research stated, “This study investigated the impact of using ChatGPT, a state-of-the-art generative AI-based model, on the critical, creative, and reflective thinking skills of university students in Ghana.” Our news editors obtained a quote from the research from Kwame Nkrumah Universit y of Science and Technology: “The study utilized a mixed-methods research approa ch, incorporating quantitative and qualitative data collection instruments, and an experimental procedure with a pretest-posttest control group. The study ultim ately enlisted a sample of 125 students randomly allocated to either the experim ent group (60 students) or the control group (65 students). The research was con ducted in the context of a Research Methodology course, which had adopted the fl ipped classroom approach. The students in the experiment group engaged with Chat GPT for in-class tasks, while those in the control group used traditional databa ses and search engines for similar tasks. Data were collected using the Critical Thinking Scale, Creative Thinking Scale, Reflective Thinking Scale, and a stude nt interview guide (semi-structured). The study’s findings illustrated that inco rporating ChatGPT influenced the students’ critical, reflective, and creative th inking skills and their dimensions discernibly.”

    Recent Studies from Xidian University Add New Data to Robotics and Automation (E pl-vins: Efficient Point-line Fusion Visual-inertial Slam With Lk-rg Line Tracki ng Method and 2-dof Line Optimization)

    34-34页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Robotics - Robotics and Auto mation are discussed in a new report. According to news originating from Guangzh ou, People’s Republic of China, by NewsRx correspondents, research stated, “The performance of a visual SLAM system based on point features significantly dimini shes in low-textured environments due to the challenges in extracting sufficient and reliable points. The fusion of line and point features improves SLAM system performance by providing additional visual constraints.” Financial support for this research came from Guangzhou Key Research and Develop ment Program. Our news journalists obtained a quote from the research from Xidian University, “To improve the efficiency and accuracy of the point-line-based SLAM system, thi s letter introduces EPL-VINS, an efficient point-line fusion visual-inertial SLA M system. We present the LK-RG line segment tracking method, which combines the Lucas-Kanade (LK) algorithm with the Region Growing (RG) algorithm from the Line Segment Detector (LSD). Moreover, we introduce a novel representation for spati al lines, based on which we construct line reprojection residuals and conduct a 2-degrees-of-freedom (2-DoF) optimization of spatial lines in the back-end. The proposed system is built upon VINS-Fusion, and supports the original three senso r suites: a monocular with an IMU, stereo cameras, and stereo cameras with an IM U. The experimental results show that the LK-RG method exhibits rapid processing and a high success rate in line segments matching.”

    Seventh Affiliated Hospital of Sun Yat-sen University Reports Findings in Cutane ous Melanoma (Machine learning-derived immunosenescence index for predicting out come and drug sensitivity in patients with skin cutaneous melanoma)

    35-35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 Oncology - Cutaneous M elanoma is the subject of a report. According to news reporting from Guangdong, People’s Republic of China, by NewsRx journalists, research stated, “The functio ns of immunosenescence are closely related to skin cutaneous melanoma (SKCM). Th e aim of this study is to uncover the characteristics of immunosenescence index (ISI) to identify novel biomarkers and potential targets for treatment.” The news correspondents obtained a quote from the research from the Seventh Affi liated Hospital of Sun Yat-sen University, “Firstly, integrated bioinformatics a nalysis was carried out to identify risk prognostic genes, and their expression and prognostic value were evaluated. Then, we used the computational algorithm t o estimate ISI. Finally, the distribution characteristics and clinical significa nce of ISI in SKCM by using multi-omics analysis. Patients with a lower ISI had a favorable survival rate, lower chromosomal instability, lower somatic copy-num ber alterations, lower somatic mutations, higher immune infiltration, and sensit ive to immunotherapy. The ISI exhibited robust, which was validated in multiple datasets. Besides, the ISI is more effective than other published signatures in predicting survival outcomes for patients with SKCM. Single-cell analysis reveal ed higher ISI was specifically expressed in monocytes, and correlates with the d ifferentiation fate of monocytes in SKCM. Besides, individuals exhibiting elevat ed ISI levels could potentially receive advantages from chemotherapy, and promis ing compounds with the potential to target high ISI were recognized.”

    National Oceanic and Atmospheric Administration (NOAA) Researchers Detail Findin gs in Robotics [Sequential Treatment Application Robot (STAR) for high-replication marine experimentation]

    36-36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 originating from Miami, Florida, by NewsRx corre spondents, research stated, “Marine organisms are often subject to numerous anth ropogenic stressors, resulting in widespread ecosystem degradation.” Our news reporters obtained a quote from the research from National Oceanic and Atmospheric Administration (NOAA): “Physiological responses to these stressors, however, are complicated by high biological variability, species-specific sensit ivities, nonlinear relationships, and countless permutations of stressor combina tions. Nevertheless, quantification of these relationships is paramount for para meterizing predictive tools and ultimately for effective management of marine re sources. Multi-level, multi-stressor experimentation is therefore key, yet the h igh replication required has remained a logistical challenge and a financial bar rier. To overcome these issues, we created an automated system for experimentati on on marine organisms, the Sequential Treatment Application Robot (STAR). The s ystem consists of a trackmounted robotic arm that sequentially applies precisio n treatments to independent aquaria via syringe and peristaltic pumps. The accur acy and precision were validated with dye and spectrophotometry, and stability w as demonstrated by maintaining corals under treatment conditions for more than a month.”

    Research from Kyoto University Provides New Data on Robotics (Impact of politene ss and performance quality of android robots on future interaction decisions: a conversational design perspective)

    37-38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 out of Kyoto, Japan, by NewsRx editors, rese arch stated, “Despite robots being applied in various situations of modern socie ty, some people avoid them or do not feel comfortable interacting with them.” The news reporters obtained a quote from the research from Kyoto University: “De signs that allow robots to interact appropriately with people will make a positi ve impression on them resulting in a better evaluation of robots, which will sol ve this problem. To establish such a design, this study conducted two scenario-b ased experiments focusing on the politeness of the robot’s conversation and beha vior, and examined the impressions caused when the robot succeeds or slightly fa ils at a task. These two experiments revealed that regardless of whether the par tner is a robot or a human, politeness not only affected the impression of inter action but also the expectations for better task results on the next occasion. A lthough the effect of politeness on preference toward robot agents was smaller t han those toward human agents when agents failed a task, people were more likely to interact with polite robots and human agents again because they thought that they would not fail the next time.”