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    Studies from China University of Petroleum (East China) Yield New Data on Robotics and Automation (Transcodnet: Underwater Transparently Camouflaged Object Detection Via Rgb and Event Frames Collaboration)

    104-104页
    查看更多>>摘要：Current study results on Robotics - Robotics and Automation have been published. According to news reporting originating from Shandong, People's Republic of China, by NewsRx correspondents, research stated, “Underwater transparently camouflaged organisms can be perfectly 'invisible' in the ocean to avoid the capture of predators. Due to the blurry contour boundaries of their bodies, obtaining their boundary features and determining their specific positions are challenging for detection tasks.” Financial support for this research came from National Key Ramp;D Program of China. Our news editors obtained a quote from the research from the China University of Petroleum (East China), “To address this issue, first, we propose a large-scale underwater transparently camouflaged object dataset, termed Aqua-Eye, which is obtained from event data and contains five types of underwater transparent organisms, with a total of 6497 annotated images. Second, to evaluate the effectiveness of this dataset, we propose a simple and effective detection network termed underwater Transparently Camouflaged Object Detection Network (TransCODNet), which can obtain local features and specific locations of targets, providing a better detection method for underwater transparently camouflaged organisms. In this letter, we performed ablation study and nine representative deep learning algorithms were evaluated based on the dataset.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Chongqing Medical University Reports Findings in Head and Neck Cancer (Mononuclear phagocyte system-related multi-omics features yield head and neck squamous cell carcinoma subtypes with distinct overall survival, drug, and immunotherapy ...)

    105-106页
    查看更多>>摘要：New research on Oncology - Head and Neck Cancer is the subject of a report. According to news reporting from Chongqing, People's Republic of China, by NewsRx journalists, research stated, “Recent research reported that mononuclear phagocyte system (MPS) can contribute to immune defense but the classification of head and neck squamous cell carcinoma (HNSCC) patients based on MPS-related multi-omics features using machine learning lacked. In this study, we obtain marker genes for MPS through differential analysis at the single-cell level and utilize 'similarity network fusion' and 'MoCluster' algorithms to cluster patients' multi-omics features.” Financial supporters for this research include National Youth Science Foundation Project, Postdoctoral Fund project of Chongqing. The news correspondents obtained a quote from the research from Chongqing Medical University, “Subsequently, based on the corresponding clinical information, we investigate the prognosis, drugs, immunotherapy, and biological differences between the subtypes. A total of 848 patients have been included in this study, and the results obtained from the training set can be verified by two independent validation sets using 'the nearest template prediction'. We identified two subtypes of HNSCC based on MPS-related multi-omics features, with CS2 exhibiting better predictive prognosis and drug response. CS2 represented better xenobiotic metabolism and higher levels of T and B cell infiltration, while the biological functions of CS1 were mainly enriched in coagulation function, extracellular matrix, and the JAK-STAT signaling pathway. Furthermore, we established a novel and stable classifier called 'getMPsub' to classify HNSCC patients, demonstrating good consistency in the same training set. External validation sets classified by 'getMPsub' also illustrated similar differences between the two subtypes. Our study identified two HNSCC subtypes by machine learning and explored their biological difference.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Study Data from Sanata Dharma University Provide New Insights into Support Vector Machines (Classification of delivery type of pregnant women using support vector machine)

    106-106页
    查看更多>>摘要：Investigators publish new report on . According to news originating from Sanata Dharma University by NewsRx correspondents, research stated, “One of the ways to reduce maternal mortality is by diagnosing childbirth to find out whether a mother will give birth normally or not so that appropriate treatment can be done.” The news journalists obtained a quote from the research from Sanata Dharma University: “This study aims to improve maternal safety and health by classifying delivery type of pregnant women, either Caesarean or normal types, using the Support Vector Machine method. The dataset used in this study was taken from a hospital in 2020. It consists of 25 attributes and 302 records that include information about the health conditions of pregnant women and babies. Several experiments were performed towards the dataset with and without balancing. Three types of SVM kernels, namely Linear, RBF, and Polynomial kernels, were then implemented to classify the dataset using several variations of parameters of C, gamma, and degree. The validation was performed using several k-fold cross validations.”
      原文链接:
    • NETL
    • NSTL

    Universidad Central de Venezuela Reports Findings in Hernias (Is YouTube a reliable tool for approaching robotic assisted transabdominal preperitoneal surgery? A critical review of the available resources)

    107-107页
    查看更多>>摘要：New research on Gastroenterology - Hernias is the subject of a report. According to news reporting from Caracas, Venezuela, by NewsRx journalists, research stated, “The robotic transabdominal preperitoneal approach (rTAPP) is a relatively recent technique for the treatment of inguinal hernia. To achieve optimal results, the 10 golden rules described must be followed.” The news correspondents obtained a quote from the research from Universidad Central de Venezuela, “Surgeons in training often review videos to familiarize themselves with new techniques, YouTube being one of the most used platforms. The objective of this study is to carry out an evaluation of the 10 most viewed videos on YouTube of inguinal hernia repair by transabdominal preperitoneal approach (rTAPP) to determine if the 10 golden rules are met. Identify and evaluate the 10 videos with the highest number of views related to rTAPP. Three experienced Surgeons evaluated compliance with the 10 golden rules using a Likert scale. Data were analyzed in Excel (Microsoft) and plotted with Tableau (Tableau Inc). The consistency between evaluators was determined using Cronbach's alpha, considering a value >0.7 acceptable. The average overall evaluation was 3.63 with a range of 2.6 to 4.9. The scores related to compliance with the rules 1, 2, 9, 10 were satisfactory; on the other hand, rules 3, 4, 5, 7 and 8 were weak, particularly rule number 7. Internal consistency was observed between raters with a Cronbach's alpha of 0.98.”
      原文链接:
    • NETL
    • NSTL

    New Machine Learning Study Findings Recently Were Reported by Researchers at Ningbo University (Machine Learning Guided Rapid Discovery of Narrow-bandgap Inorganic Halide Perovskite Materials)

    108-109页
    查看更多>>摘要：A new study on Machine Learning is now available. According to news originating from Ningbo, People's Republic of China, by NewsRx correspondents, research stated, “The bandgap of inorganic halide perovskites plays a crucial role in the efficiency of solar cells. Although density functional theory can be used to calculate the bandgap of materials, the method is time-consuming and requires deep knowledge of theoretical calculations, theoretical calculations are frequently constrained by complex electronic correlations and lattice dynamics, resulting in discrepancies between calculated and experimental results.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), National Natural Science Foundation of China (NSFC), K. C. Wong Magna Fund at Ningbo University. Our news journalists obtained a quote from the research from Ningbo University, “To address this issue, this study employs machine learning to predict the bandgap of inorganic halide perovskites. The XGBoost classifier classifies ABX3-type inorganic halide perovskites into narrow and wide bandgap materials. The study collected a dataset consisting of 447 perovskites and generated material descriptors using the Matminer Python package. The model predicts narrow-bandgap materials with 95% accuracy. Finally, the Shapley analysis revealed that the key factor affecting the bandgap of perovskites is the electronegativity range. As the range of electronegativity increases, so does the possibility of a perovskite with a narrow bandgap.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Swiss Federal Institute of Technology Zurich (ETH) Reports Findings in Machine Learning (DeePhys: A machine learning-assisted platform for electrophysiological phenotyping of human neuronal networks)

    108-108页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news originating from Basel, Switzerland, by NewsRx correspondents, research stated, “Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays.” Our news journalists obtained a quote from the research from the Swiss Federal Institute of Technology Zurich (ETH), “DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions.”
      原文链接:
    • NETL
    • NSTL

    Data from Universidad Tecnica Federico Santa Maria Update Knowledge in Machine Learning (Adopting New Machine Learning Approaches on Cox's Partial Likelihood Parameter Estimation for Predictive Maintenance Decisions)

    109-110页
    查看更多>>摘要：Data detailed on artificial intelligence have been presented. According to news reporting from Santiago, Chile, by NewsRx journalists, research stated, “The Proportional Hazards Model (PHM) under a Condition-Based Maintenance (CBM) policy is used by asset-intensive industries to predict failure rate, reliability function, and maintenance decisions based on vital covariates data.” Funders for this research include Anid. Our news editors obtained a quote from the research from Universidad Tecnica Federico Santa Maria: “Cox's partial likelihood optimization is a method to assess the weight of time and conditions into the hazard rate; however, parameter estimation with diverse covariates problem could have multiple and feasible solutions. Therefore, the boundary assessment and the initial value strategy are critical matters to consider. This paper analyzes innovative non/semi-parametric approaches to address this problem. Specifically, we incorporate IPCRidge for defining boundaries and use Gradient Boosting and Random Forest for estimating seed values for covariates weighting. When applied to a real case study, the integration of data scaling streamlines the handling of condition data with diverse orders of magnitude and units. This enhancement simplifies the modeling process and ensures a more comprehensive and accurate underlying data analysis.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Data on Machine Learning Described by Researchers at Los Alamos National Laboratory (Uncovering Acoustic Signatures of Pore Formation In Laser Powder Bed Fusion)

    110-111页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating in Los Alamos, New Mexico, by NewsRx journalists, research stated, “We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a lowdimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography.” Financial support for this research came from Los Alamos National Laboratory. The news reporters obtained a quote from the research from Los Alamos National Laboratory, “Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom k-means clustering (NMFk) to learn the underlying spectral patterns associated with pore formation. NMFk returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMFk decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    University of Sydney Researcher Publishes Findings in Machine Learning (Panoramic imaging errors in machine learning model development: a systematic review)

    111-112页
    查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of Sydney by NewsRx correspondents, research stated, “To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models. This systematic literature followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and used three databases.” Our news editors obtained a quote from the research from University of Sydney: “Keywords were selected from relevant literature. Eligibility criteria: PAN studies that used ML models and mentioned image quality concerns. Out of 400 articles, 41 papers satisfied the inclusion criteria. All the studies used ML models, with 35 papers using deep learning (DL) models. PAN quality assessment was approached in 3 ways: acknowledgement and acceptance of imaging errors in the ML model, removal of low-quality radiographs from the dataset before building the model, and application of image enhancement methods prior to model development. The criteria for determining PAN image quality varied widely across studies and were prone to bias.”
      原文链接:
    • NETL
    • NSTL
    • British Inst Radiology

    Patent Issued for Image encoding method and image encoding device (USPTO 11882269)

    112-114页
    查看更多>>摘要：From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Kitagawa, Masao (Yokohama, JP), Shigenobu, Yuya (Yokohama, JP), filed on April 15, 2021, was published online on January 23, 2024. The patent's assignee for patent number 11882269 is Socionext Inc. (Kanagawa, Japan). News editors obtained the following quote from the background information supplied by the inventors: “Encoding of moving images is roughly divided into preceding “implementer-dependent” processing and succeeding “standardized” processing. The former corresponds to determining various modes such as determination of the size of encoded blocks, intra prediction, and motion detection. On the other hand, the latter corresponds to standardized processing performed in accordance with the mode determined in the former processing, such as orthogonal transformation, quantization, entropy coding, and motion compensation. “The former mode determination is processing performed in accordance with a theoretical algorithm and corresponds to obtaining an optimum or quasi optimum combination from among an enormous number of combinations. Thus, it becomes possible to design a mode determination engine that performs such mode determination. Note that the engine is a device that executes data processing and is, for example, hardware such as an electronic circuit, or an integrated system of software and hardware, the integrated system including programs and a CPU executing programs.
      原文链接:
    • NETL
    • NSTL