Improving drug repositioning with negative data labeling using large language models by Milan Picard, Mickael Leclercq, Antoine Bodein, Marie Pier Scott-Boyer, Olivier Perin, Arnaud Droit

“…We then applied a machine learning ensemble to this new dataset to assess the repurposing potential of the remaining 11,043 drugs in the DrugBank database. …”
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Autism Spectrum Disorder Classification with Interpretability in Children Based on Structural MRI Features Extracted Using Contrastive Variational Autoencoder by Ruimin Ma, Ruitao Xie, Yanlin Wang, Jintao Meng, Yanjie Wei, Yunpeng Cai, Wenhui Xi, Yi Pan

“…With the development of the machine learning and neuroimaging technology, extensive research has been conducted on machine classification of ASD based on structural Magnetic Resonance Imaging (s-MRI). …”
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An improved clustering algorithm based on local density by Xiaohui GUAN, Yaguan QIAN, Xinxin SUN

“…Clustering analysis is an important and challenging research field in machine learning and data mining.A fast and effective clustering algorithm based on the idea of local density was proposed by Alex.But the number of clusters and cluster centers in the algorithm were determined by hand.Therefore,the candidates of cluster centers based on local density were firstly selected and then density connectivity method was used to optimize the candidates.The classes of samples are the same as the nearest center with bigger local density.Experiments show that the proposed method has a better cluster efficiency and can handle the problems of uncertain cluster number and cluster centers.…”
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Part of Speech Tagging: Shallow or Deep Learning? by Robert Östling

“… Deep neural networks have advanced the state of the art in numerous fields, but they generally suffer from low computational efficiency and the level of improvement compared to more efficient machine learning models is not always significant. We perform a thorough PoS tagging evaluation on the Universal Dependencies treebanks, pitting a state-of-the-art neural network approach against UDPipe and our sparse structured perceptron-based tagger, efselab. …”
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A Hybrid System for Subjectivity Analysis by Samir Rustamov

“…We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. …”
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Rough sets theory and its extensions for attribute reduction: a review by Sadegh Eskandari

“…Several efforts have been made to make close the rough sets theory and machine learning tasks. In this regard several extensions and modifications of the original theory are proposed. …”
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Fault Diagnosis of Planetary Gearbox based on 1-DCNN by Xuanyi Xue, Xinyu Pang

“…Traditional machine learning methods have disadvantages such as low recognition rate and complicated feature extraction operations in the planetary gearbox fault diagnosis. …”
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The Control Data Method: A New Method of Modeling in Population Dynamics by Lin-Fei Nie, Zhi-Dong Teng

“…Using a the approximation property and the machine learning approach of artificial neural networks, a tuning algorithm of unknown parameters is obtained and the factual data of predator-prey can be asymptotically stabilized using a neural network controller. …”
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Smart Approach for Botnet Detection Based on Network Traffic Analysis by Alaa Obeidat, Rola Yaqbeh

“…In this article, we suggest a method for identifying the behavior of data traffic using machine learning classifiers including genetic algorithm to detect botnet activities. …”
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Intelligent cloud guidance technology based on natural language learning by Renjie TANG, Tao JIANG, Qiaojie YANG

“…The main problems existing in the current guidance system were analyzed.According to the intelligent guidance system researched in the current academic circles,a self-learning system for the disease which based on a large number of patient condition descriptions using a variety of machine learning algorithms was creatively proposed.The platform used Web crawler technology to obtain setting of the international and domestic medical institution departments and a large number of patient descriptions,which form a pathological knowledge base and a disease self-reported knowledge base.At the same time,the algorithm was innovatively constructed to combine the attention model with TextCNN to improve the accuracy of the consultation.…”
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A convergent Deep Learning algorithm for approximation of polynomials by Després, Bruno

“…We propose a novel algorithm, where the functional equation is solved with a converging iterative algorithm which can be realized as a Machine Learning training method iteratively with respect to the number of layers. …”
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A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification by Ismaili Burim, Besimi Adrian

“…This paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics.…”
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Key Technology of SSL Encrypted Application Identification Under Imbalance of Application Class by Xuejiao Chen, Pan Wang, Shidong3 Liu

“…The hybrid method effectively combines the advantages of static feature matching and machine learning methods,to achieve the balance of classification method on accuracy and speed.…”
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Research on manufacturing energy consumption optimization platform technology based on knowledge-base by Weiwei YANG, Sining WANG, Guide ZHENG, Yaqiong SONG

“…China’s manufacturing industry accounts for the largest proportion of the economy and involves a huge scale.It is of practical significance for enterprises to gradually realize energy consumption optimization through digital technology.Taking automobile manufacturing as an example, a scheme of energy consumption optimization based on knowledge-base was proposed, including the analysis of the characteristics of energy consumption in manufacturing industry, the key technologies of energy consumption optimization and the presentation of application practice.Starting with the production equipment of the enterprise, the law affecting energy consumption was found and a knowledge-base was build through the information of manufacturing execution system and equipment operation status of the enterprise, and the optimization of energy consumption was realized through machine learning algorithms such as neural network and correlation analysis.…”
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Modeling and Simulation of Real Estate Valuation Based on Genetic Neural Network Model by Shuli Shen

“…Based on this, the relationship model between characteristic variables and house prices is constructed by using the machine learning method. At the same time, genetic algorithm is used to screen the specific values. …”
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Malware prediction technique based on program gene by Da XIAO, Bohan LIU, Baojiang CUI, Xiaochen WANG, Suoxing ZHANG

“…With the development of Internet technology,malicious programs have risen explosively.In the face of executable files without source,the current mainstream malware detection uses feature detection based on similarity,with lack of analysis of malicious sources.To resolve this status,the definition of program gene was raised,a generic method of extracting program gene was designed,and a malicious program prediction method was proposed based on program gene.Utilizing machine learning and deep-learning algorithms,the forecasting system has good prediction ability,with the accuracy rate of 99.3% in the deep-learning model,which validates the role of program gene theory in the field of malicious program analysis.…”
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The early warning paradox by Hugh Logan Ellis, Edward Palmer, James T. Teo, Martin Whyte, Kenneth Rockwood, Zina Ibrahim

“…Machine learning models in healthcare aim to predict critical outcomes but often overlook existing Early Warning Systems’ impact. …”
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Improved KNN Algorithm Based on Preprocessing of Center in Smart Cities by Haiyan Wang, Peidi Xu, Jinghua Zhao

“…The KNN algorithm is one of the most famous algorithms in machine learning and data mining. It does not preprocess the data before classification, which leads to longer time and more errors. …”
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Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by M. N. Afzal Khan, Nada Zahour, Usman Tariq, Ghinwa Masri, Ismat F. Almadani, Hasan Al-Nashah

“…Accurately identifying and discriminating between different brain states is a major emphasis of functional brain imaging research. Various machine learning techniques play an important role in this regard. …”
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Advanced analysis of soil pollution in southwestern Ghana using Variational Autoencoders (VAE) and positive matrix factorization (PMF) by Raymond Webrah Kazapoe, Daniel Kwayisi, Seidu Alidu, Samuel Dzidefo Sagoe, Aliyu Ohiani Umaru, Ebenezer Ebo Yahans Amuah, Millicent Obeng Addai, Obed Fiifi Fynn

“…Integrating chemometric and machine learning techniques provides a dynamic system that can monitor pollution shifts early, to aid remediation efforts in highly affected areas.…”
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