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 reporting out of the National Institute of Technology by NewsRx editors, research stated, "The vast volume of redundant and irrelevant network traffic data poses significant hurdles for intrusion detecti on. Effective feature selection is crucial for eliminating irrelevant informatio n." Our news reporters obtained a quote from the research from National Institute of Technology: "Presently, most filtering and embedded methods rely on fixed thres holds or ratios, necessitating prior knowledge. Conversely, wrapper methods are computationally intensive, and individual feature selection methods may introduc e biases in evaluation. To address these challenges, this study introduces Adapt ive Neighborhood based Feature Selection (AN-SFS), a dynamic feature selection a pproach that adapts to local statistical properties of the data. Unlike traditio nal methods, AN-SFS adjusts its threshold based on the characteristics of the cu rrent feature subset and incorporates statistical measures of neighboring featur es, capturing subtle relationships and dependencies. This adaptability enables A N-SFS to achieve robust and effective feature selection outcomes. Using NSL-KDD and UNSW-NB15 datasets, our model demonstrates superiority over conventional ML classifiers in detection rate, precision, and recall, achieving outstanding accu racy rates of 99.3% on NSL-KDD and 97.5% on UNSW-NB1 5, significantly outperforming contemporary methods."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on are presented in a new report. Acco rding to news reporting out of Hefei, People's Republic of China, by NewsRx edit ors, research stated, "The driving style of the driver has a significant impact on the safety of vehicle operation." Financial supporters for this research include Anhui New Energy Vehicle Industry Innovation Development Project; The Fundamental Research Funds For The Central Universities of China; Science And Technology Program of Wuhu. Our news editors obtained a quote from the research from Hefei University of Tec hnology: "This paper proposes a driving style recognition model that takes into account speeding behavior, aiming to improve the accuracy of driving style recog nition. Initially, vehicle operation data is collected through onroad experimen ts with drivers. Subsequently, feature parameters related to driving conditions are extracted from the vehicle operation data, and dimensionality reduction is a pplied to these parameters. The principal components extracted are then utilized as inputs for the particle swarm optimization support vector machine algorithm to determine driving conditions. This information is used to establish the speed ing threshold, which is then used to calculate the number of speeding occurrence s and the longest speeding time as evaluation indicators. These indicators are i ntegrated into a comprehensive evaluation system comprising 18 evaluation criter ia to improve the accuracy of driving style recognition."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting originating fr om West Lafayette, Indiana, by NewsRx correspondents, research stated, "Examinin g the effectiveness of machine learning techniques in analyzing engineering stud ents' decisionmaking processes through topic modeling during simulation-based d esign tasks is crucial for advancing educational methods and tools." Funders for this research include National Science Foundation. The news journalists obtained a quote from the research from Purdue University: "Thus, this study presents a comparative analysis of different supervised and un supervised machine learning techniques for topic modeling, along with human vali dation. Hence, this manuscript contributes by evaluating the effectiveness of th ese techniques in identifying nuanced topics within the argumentation framework and improving computational methods for assessing students' abilities and perfor mance levels based on their informed decisions. This study examined the decision -making processes of engineering students as they participated in a simulation-b ased design challenge. During this task, students were prompted to use an argume ntation framework to articulate their claims, evidence, and reasoning, by record ing their informed design decisions in a design journal. This study combined qua litative and computational methods to analyze the students' design journals and ensured the accuracy of the findings through the researchers' review and interpr etations of the results. Different machine learning models, including random for est, SVM, and K-nearest neighbors (KNNs), were tested for multilabel regression, using preprocessing techniques such as TF-IDF, GloVe, and BERT embeddings."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Boltzmann Mac hines have been published. According to news reporting from Beijing, People's Re public of China, by NewsRx journalists, research stated, "Although lithofacies r outinely is featured by distinct logging responses from each other, many types o f lithofacies in practical cases show similar measuring characteristics on logs, and then to achieve a desirable solution from logging-based lithofacies predict ion actually is challengeable. Since the mathematical essence of lithofacies pre diction can be explained as an issue of pattern recognition, a light gradient bo osting machine, a stateof- the-art ensemble learning, specifically developed to address supervised classification, could be a potential solver."
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 Chuzhou, Peopl e's Republic of China, by NewsRx editors, research stated, "Plant nitrogen conce ntration (PNC) is a key indicator reflecting the growth and development status o f plants. The timely and accurate monitoring of plant PNC is of great significan ce for the refined management of crop nutrition in the field." Financial supporters for this research include Scientific Research Projects in H igher Education Institutions of Anhui Province; Anhui Engineering Research Cente r of Smart Crop Planting And Processing Technology Open Research Project; Natura l Science Foundation of Hebei Province; Scientific Research Projects in Higher E ducation Institutions of Hebei Province; Anhui Province Agricultural Science And Technology Modernization Pilot County Project.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Biotechnology - Bioinf ormatics is the subject of a report. According to news originating from Yunnan, People's Republic of China, by NewsRx correspondents, research stated, "Percutan eous coronary intervention (PCI) combined with stent implantation is currently o ne of the most effective treatments for coronary artery disease (CAD). However, in-stent restenosis (ISR) significantly compromises its long-term efficacy." Our news journalists obtained a quote from the research from the Affiliated Hosp ital of Kunming University of Science and Technology, "Mitophagy plays a crucial role in vascular homeostasis, yet its role in ISR remains unclear. This study a ims to identify mitophagy-related biomarkers for ISR and explore their underlyin g molecular mechanisms. Through differential gene expression analysis between IS R and Control samples in the combined dataset, 169 differentially expressed gene s (DEGs) were identified. Twenty-three differentially expressed mitophagy-relate d genes (DEMRGs) were identified by intersecting with mitophagyrelated genes (M RGs) from the GeneCards, and functional enrichment analysis indicated their sign ificant involvement in mitophagy-related biological processes. Using Weighted Ge ne Co-expression Network Analysis (WGCNA) and three machine learning algorithms (Logistic-LASSO, RF, and SVM-RFE), LRRK2, and ANKRD13A were identified as mitoph agy-related biomarkers for ISR. The nomogram based on these two genes also exhib ited promising diagnostic performance for ISR. Gene Set Enrichment Analysis (GSE A) as well as immune infiltration analyses showed that these two genes were clos ely associated with immune and inflammatory responses in ISR. Furthermore, poten tial small molecule compounds with therapeutic implications for ISR were predict ed using the connectivity Map (cMAP) database."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting originating in Guangzhou, People's Repub lic of China, by NewsRx journalists, research stated, "Molecular design of small -molecule inhibitors targeting programmed cell death-1 (PD-1)/programmed cell de ath ligand-1 (PD-L1) pathway has been recognized as an active research area by t he clinical success of cancer immunotherapy. In recent years, using machine lear ning (ML) methods to accelerate drug design have been confirmed." The news reporters obtained a quote from the research from South China Agricultu ral University, "However, the black box character of ML methods makes model inte rpretation and ligands optimization obscured. Herein, five explainable ML models were constructed by integrating five ML models with the SHAP method, where thes e ML models were pretrained with >4000 molecules and the ir R ranged from 0.835 to 0.86 on test set. Subsequently, the explainable ML mod els were employed to identify the relationship between fragments and bio-activit y of a small molecule inhibitor BMS-1166, leading to the modification of BMS-116 6 into 60 novel compounds. After consensus docking and ADMET test, 3 small molec ules (C27, C52 and C54) with better docking scores and lower toxicity than BMS-1 166 were screened out further. Finally, the improved binding affinity of C27, C5 2 to the PD-L1 dimer was validated by the MD simulation."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics - Androids are presented in a new report. According to news reporting originating from Hangzhou , People's Republic of China, by NewsRx correspondents, research stated, "Signif icant advancements have been made in the field of humanoid robot, particularly i n walking control strategies. However, achieving straight-legged walking remains a challenge." Funders for this research include Natural Science Foundation of Zhejiang Provinc e, Natural Science Foundation of Zhejiang Province, National Natural Science Fou ndation of China (NSFC). Our news editors obtained a quote from the research from Zhejiang University, "B oth the traditional model-based and the learning-based control methods confront with difficulties in achieving natural humanoid gait feature. To address this is sue, a general motion retargeting method is developed and also evaluated for hum anoid robots with different structure, size and degrees of freedom. Moreover, a conditional adversarial motion priors method is proposed based on reinforcement learning and validated on the humanoid robot GTX-III. Through various motion seg ments from the motion capture database, it is shown that this method can success fully enable the humanoid robot to perform straight-legged walking with flexible and natural transitions between different gaits within a single discriminator n etwork. A novel motion retargeting method enables humanoid robots of varying str uctures and sizes to perform straight-legged walking with natural transitions be tween gaits."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news originating from Pekan, Malaysi a, by NewsRx correspondents, research stated, "Hybrid Electric Vehicles (HEVs) h ave emerged as a viable option for reducing pollution and attaining fuel savings in addition to reducing emissions. The effectiveness of HEVs heavily relies on the energy management strategies (EMSs) employed, as it directly impacts vehicle fuel consumption." Financial supporters for this research include Malaysian Ministry of Higher Educ ation, University Malaysia Pahang. Our news journalists obtained a quote from the research from the University of M alaysia Pahang, "Developing suitable EMSs for HEVs poses a challenge, as the goa l is to maximize fuel economy yet optimize vehicle performance. EMSs algorithms are critical in determining power distribution between the engine and motor in H EVs. Traditionally, EMSs for HEVs have been developed based on optimal control t heory. However, in recent years, a rising number of people have been interested in utilizing machinelearning techniques to enhance EMSs performance. This artic le presents a current analysis of various EMSs proposed in the literature. It hi ghlights the shift towards integrating machine learning and artificial intellige nce (AI) breakthroughs in EMSs development. The study examines numerous case stu dies, and research works employing machine learning techniques across different categories to develop energy management strategies for HEVs. By leveraging advan cements in machine learning and AI, researchers have explored innovative approac hes to optimize HEVs' performance and fuel economy. Key conclusions from our inv estigation show that machine learning has made a substantial contribution to sol ving the complex problems associated with HEV energy management."
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 originating from Hangzhou, People's Rep ublic of China, by NewsRx correspondents, research stated, "Mildew infestation i s a significant cause of loss during grain storage. The growth and metabolism of mildew leads to changes in gas composition and temperature within granaries." Financial supporters for this research include Ningbo Science And Technology Pla n Project; Key R&D Projects in Zhejiang Province; Research Developm ent Foundation of Zhejiang A&funiversity. Our news reporters obtained a quote from the research from Zhejiang A& F University: "Recent advances in sensor technology and machine learning enable the prediction of grain mildew during storage. Current research primarily focuse s on predicting mildew occurrence or grading using simple machine learning metho ds, without in-depth exploration of the time series characteristics of mildew pr ocess data. A monitoring device was designed and developed to capture high-quali ty microenvironment parameters and image data during a simulated mildew process experiment. Using the "Yongyou 15" rice varieties from Zhejiang Province, five s imulation experiments were conducted under varying temperature and humidity cond itions between January and May 2023. Mildew grades were defined through manual a nalysis to construct a multimodal dataset for the rice mildew process. This stud y proposes a combined model (CNN-LSTM-A) that integrates convolutional neural ne tworks (CNN), long short-term memory (LSTM) networks, and attention mechanisms t o predict the mildew grade of stored rice. The proposed model was compared with LSTM, CNN-LSTM, and LSTM-Attention models. The results indicate that the propose d model outperforms the others, achieving a prediction accuracy of 98% . The model demonstrates superior accuracy and more stable performance."
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