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    Recent Studies from Tsinghua University Add New Data to Robotics (Robotic Assembly Control Reconfiguration Based On Transfer Reinforcement Learning for Objects With Different Geometric Features)

    20-20页
    查看更多>>摘要：Fresh data on Robotics are presented in a new report. According to news reporting from Beijing, People’s Republic of China, by NewsRx journalists, research stated, “Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular, reinforcement learning (RL) agents are gradually incorporated into the compliance controller to adapt to complex force-pose mapping which is hard to model analytically.” The news correspondents obtained a quote from the research from Tsinghua University, “Since forcepose mapping is strongly dependent on geometric features, a compliance controller is only optimal for current geometric features. To reduce the learning cost of assembly objects with different geometric features, this paper is devoted to answering how to reconfigure existing controllers for new assembly objects with different geometric features. In this paper, model-based parameters are first reconfigured based on the proposed Equivalent Theory of Compliance Law (ETCL). Then the RL agent is transferred based on the proposed Weighted Dimensional Policy Distillation (WDPD) method.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Data on Machine Learning Reported by Chen Qu and Colleagues [Formic Acid-Ammonia Heterodimer: A New D-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer]

    21-21页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Toronto, Canada, by NewsRx journalists, research stated, “The formic acid-ammonia dimer is an important example of a hydrogen-bonded complex in which a double proton transfer can occur. Its microwave spectrum has recently been reported and rotational constants and quadrupole coupling constants were determined.” The news correspondents obtained a quote from the research, “Calculated estimates of the double-well barrier and the internal barriers to rotation were also reported. Here, we report a full-dimensional potential energy surface (PES) for this complex, using two closely related D-machine learning methods to bring it to the CCSD(T) level of accuracy. The PES dissociates smoothly and accurately. Using a 2d quantum model the ground vibrational-state tunneling splitting is estimated to be less than 10 cm.”
      原文链接:
    • NETL
    • NSTL

    Reports Outline Artificial Intelligence Study Results from University of Airlangga (Artificial Intelligence and Philosophy of Humanism in Auditor Perceptions)

    21-22页
    查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news originating from East Java, Indonesia, by NewsRx correspondents, research stated, “This study aims to interpret the humanistic thinking of Chinese philosopher Confu-cius on the activity of integrating Artificial Intelligence (AI) into the process of au-diting financial statements.” The news journalists obtained a quote from the research from University of Airlangga: “The qualitativeinterpretive method was used for re-search purposes through in-depth interview techniques which were addressed to informants from audit firms that had used AI. The validity of the information was tested using triangulation of data sources from different audit firm informants. The main findings show that as humans who have cognitive, moral and ethical abilities, auditors can collaborate with AI without worrying that the existence of this profes-sion will be completely replaced by AI. However, excessive integration and tend to rely on auditors should be aware of so that high-tech assisted audit objectives such as AI work in harmony without eliminating the auditor’s humanism such as skepticism and professional judgment that AI does not have. Social and ethical issues are chal-lenges in the use of AI and solutions will continue to be sought.”
      原文链接:
    • NETL
    • NSTL

    Research from Tokyo Denki University Yields New Data on Androids (Development of the Lifelike Head Unit for a Humanoid Cybernetic Avatar 'Yui' and its Operation Interface)

    22-23页
    查看更多>>摘要：Investigators discuss new findings in androids. According to news reporting from Tokyo Denki University by NewsRx journalists, research stated, “In avatar-mediated communication, the face-to-face interlocutor must sense the operator’s presence and emotions via an avatar.” Financial supporters for this research include Japan Science And Technology Agency (Jst) Moonshot Research And Development Program. The news editors obtained a quote from the research from Tokyo Denki University: “Although androids resembling humans have been developed to convey presence through appearance and movement, few studies have prioritized deepening the communication experience for operators and interlocutors using android robots as avatars. To address this gap, we introduced the ‘cybernetic avatar ‘Yui,” featuring a human-like head unit with 28 actuation points, capable of expressing gaze, facial emotions, and speech-related mouth 22 movements. Through an eye-tracking unit in a head-mounted display (HMD) and the degrees of freedom in both eyes of Yui, operators can naturally control the avatar’s gaze. Additionally, microphones embedded in Yui’s ears allowed operators to hear surrounding sounds in three dimensions, enabling them to discern the direction of calls based solely on auditory information. The HMD’s face-tracking unit synchronizes the facial movements of the avatar with those of the operator. This immersive interface, coupled with Yui’s human-like appearance, enabled real-time emotional transmission and communication, thus enhancing the sense of presence for both parties.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Shanghai Maritime University Reports Findings in Breast Cancer (Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning)

    23-24页
    查看更多>>摘要：New research on Oncology - Breast Cancer is the subject of a report. According to news reporting out of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered.” Our news journalists obtained a quote from the research from Shanghai Maritime University, “The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes.”
      原文链接:
    • NETL
    • NSTL

    Investigators from University of Salerno Zero in on Robotics (Identity, Gender, Age, and Emotion Recognition From Speaker Voice With Multi-task Deep Networks for Cognitive Robotics)

    24-25页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting originating from Salerno, Italy, by NewsRx correspondents, research stated, “This paper presents a study on the use of multi-task neural networks (MTNs) for voice-based soft biometrics recognition, e.g., gender, age, and emotion, in social robots. MTNs enable efficient analysis of audio signals for various tasks on low-power embedded devices, thus eliminating the need for cloud-based solutions that introduce network latency.” Financial support for this research came from Universit degli Studi di Salerno. Our news editors obtained a quote from the research from the University of Salerno, “However, the strict dataset requirements for training limit the potential of MTNs, which are commonly used to optimize a single reference problem. In this paper, we propose three MTN architectures with varying accuracy-complexity trade-offs for voice-based soft biometrics recognition. In addition, we adopt a learnable voice representation, that allows to adapt the specific cognitive robotics application to the environmental conditions. We evaluate the performance of these models on standard large-scale benchmarks, and our results show that the proposed architectures outperform baseline models for most individual tasks. Furthermore, one of our proposed models achieves state-of-the-art performance on three out of four of the considered benchmarks.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Study Data from Norwegian University of Science and Technology (NTNU) Update Knowledge of Machine Learning (Agi-p: a Gender Identification Framework for Authorship Analysis Using Customized Fine-tuning of Multilingual Language Model)

    25-26页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Alesund, Norway, by NewsRx journalists, research stated, “In this investigation, we propose a solution for the author’s gender identification task called AGI-P. This task has several real-world applications across different fields, such as marketing and advertising, forensic linguistics, sociology, recommendation systems, language processing, historical analysis, education, and language learning.” Financial support for this research came from Norwegian University of Science and Technology (NTNU), Norway. The news correspondents obtained a quote from the research from the Norwegian University of Science and Technology (NTNU), “We created a new dataset to evaluate our proposed method. The dataset is balanced in terms of gender using a random sampling method and consists of 1944 samples in total. We use accuracy as an evaluation measure and compare the performance of the proposed solution (AGI-P) against state-of-the-art machine learning classifiers and fine-tuned pre-trained multilingual language models such as DistilBERT, mBERT, XLM-RoBERTa, and Multilingual DEBERTa. In this regard, we also propose a customized fine-tuning strategy that improves the accuracy of the pre-trained language models for the author gender identification task. Our extensive experimental studies reveal that our solution (AGI-P) outperforms the well-known machine learning classifiers and fine-tuned pre-trained multilingual language models with an accuracy level of 92.03%. Moreover, the pre-trained multilingual language models, finetuned with the proposed customized strategy, outperform the fine-tuned pre-trained language models using an out-of-the-box fine-tuning strategy.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Sun Yat-sen University Reports Findings in Esophageal Cancer (A pathway-based computational framework for identification of a new modal of multi-omics biomarkers and its application in esophageal cancer)

    26-27页
    查看更多>>摘要：New research on Oncology - Esophageal Cancer is the subject of a report. According to news originating from Guangzhou, People’s Republic of China, by NewsRx correspondents, research stated, “The pathway-based strategy has been recently proposed for identifying biomarkers with the advantages of higher biological interpretability and cross-data robustness than the conventional gene-based strategy. However, its utility in clinical applications has been limited due to the high computational complexity and ill-defined performance.” Our news journalists obtained a quote from the research from Sun Yat-sen University, “The current study presents a machine learning-based computational framework using multi-omics data for identifying a new modal of biomarkers, called pathway-derived core biomarkers, which have the advantages of both gene-based and pathway-based biomarkers. Machine-learning methods and gene-pathway network were integrated to select the pathway-derived core biomarkers. Multiple machine-learning algorithms were used to construct and validate the diagnostic models of the biomarkers based on more than 1400 multi-omics clinical samples of esophageal squamous cell carcinoma (ESCC). The results showed that the classifier models based on the new modal biomarkers achieved superior performance in the training datasets with an average AUC/accuracy of 0.98/0.95 and 0.89/0.81 for mRNAs and miRNA, respectively, higher than the currently known classifier models based on the conventional gene-based strategy and pathway-based strategy. In the testing cohorts, the AUC/accuracy increased by 6.1 %/7.3 % than the models based on the native gene-based biomarkers. The improved performance was further confirmed in independent validation cohorts. Specifically, the sensitivity/specificity increased by 3 % and the variance significantly decreased by 69 % compared with that of the native gene-based biomarkers. Importantly, the pathway-derived core biomarkers also recovered 45 % more previously reported biomarkers than the gene-based biomarkers and are more functionally relevant to the ESCC etiology (involved in 14 versus 7 pathways related with ESCC or other cancer), highlighting the cross-data robustness of this new modal of biomarkers via enhanced functional relevance.”
      原文链接:
    • NETL
    • NSTL

    Reports Outline Robotics Findings from Shanghai Jiao Tong University (Modeling and Experimental Validation of Anchoring Resistance of the Radial Expanding Capsule Robot In the Intestine)

    27-28页
    查看更多>>摘要：Current study results on Robotics have been published. According to news reporting originating in Shanghai, People’s Republic of China, by NewsRx journalists, research stated, “The anchoring performance of the radial expanding capsule robot (RECR) in the intestine is crucial to the accuracy of the examination. However, there is a lack of relevant research at present.” Financial support for this research came from National Facility for Translational Medicine(Shanghai) Open Project Fund. The news reporters obtained a quote from the research from Shanghai Jiao Tong University, “In this article, the anchoring resistance model of the radial expanding capsule robot (RECR) in the intestine is established by the theoretical analysis and verified by the experiment. Based on the anchoring resistance model, the optimization method to improve the anchoring performance of the RECR is proposed. Firstly, the biomechanical properties of the intestine in the expanding state are studied, and the longitudinal contour equation of the intestine is obtained. The anchoring resistance model of the RECR in the intestine is established by analyzing the mechanical characteristics between the capsule robot and the intestine. Then, an experimental platform is built, and the anchoring resistance of the testing dummy imitating the RECR with different radii and lengths in the intestine is tested by the platform. The experimental results verify the correctness of the anchoring resistance model. Finally, the expanding force model of a developed inchworm-like RECR is established by the kinematics and mechanical analysis. And combined with the anchoring resistance model, the anchoring performance of the inchworm-like RECR in the intestine is analyzed.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Recent Research from Opole University of Technology Highlight Findings in Machine Learning (Tool Wear and Its Mechanism In Turning Aluminum Alloys With Image Processing and Machine Learning Methods)

    28-29页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting out of Opole, Poland, by NewsRx editors, research stated, “Tool wear is intimately related to intelligent operation and maintenance of automated production, workpiece surface quality, dimension accuracy, and tool life. Therefore, it is necessary to improve the production efficiency and quality by predicting tool wear values.” Financial support for this research came from Opole University of Technology. Our news journalists obtained a quote from the research from the Opole University of Technology, “The purpose of this research is to use machine learning and image processing methods in estimating the tool wear values when turning AA7075 aluminum alloy. In addition, the indepth analysis of cutting tools at different parameters were examined with SEM and EDS analysis. The results shown that there was a 44.40% increase in tool wear when the cutting speed was raised by 100% while feed rates were maintained at the same level. On the other hand, there was a 22.78% increase in tool wear seen when the cutting speed was maintained at the same level.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier