Color and Grey-Level Co-Occurrence Matrix Analysis for Predicting Sensory and Biochemical Traits in Sweet Potato and Potato by Judith Ssali Nantongo, Edwin Serunkuma, Gabriela Burgos, Mariam Nakitto, Joseph Kitalikyawe, Thiago Mendes, Fabrice Davrieux, Reuben Ssali

“…A quick analytical method for the sensory traits could expedite the selection process in breeding programs. In this paper, the relationship between sensory panel and instrumental color plus texture features was evaluated. …”
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Distinguishing Dyslexia, Attention Deficit, and Learning Disorders: Insights from AI and Eye Movements by Alae Eddine El Hmimdi, Zoï Kapoula

“…Key parameters, such as amplitude, latency, duration, and velocity, are extracted and processed to remove outliers and standardize values. …”
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An Intelligent Technique for Android Malware Identification Using Fuzzy Rank-Based Fusion by Altyeb Taha, Ahmed Hamza Osman, Yakubu Suleiman Baguda

“…The suggested ANDFRF primarily consists of two steps: in the first step, five machine learning algorithms, comprising K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Logistic Regression (LR), XGbooost (XGB) and Light Gradient Boosting Machine (LightGBM), were utilized as base classifiers for the initial identification of Android Apps either as goodware or malware apps. …”
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Steel Roll Eye Pose Detection Based on Binocular Vision and Mask R-CNN by Xuwu Su, Jie Wang, Yifan Wang, Daode Zhang

“…Subsequently, the binarized image of the steel coil end face was processed using the RGB vector space image segmentation method. …”
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Using machine learning for the assessment of ecological status of unmonitored waters in Poland by Andrzej Martyszunis, Małgorzata Loga, Karol Przeździecki

“…Decision Tree, Random Forest, KNN, Support Vector Machine, Multinomial Naive Bayes, XGBoost models have been tested and the results indicated most suitable techniques. …”
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Plasmodium P-Type Cyclin CYC3 Modulates Endomitotic Growth during Oocyst Development in Mosquitoes. by Magali Roques, Richard J Wall, Alexander P Douglass, Abhinay Ramaprasad, David J P Ferguson, Mbinda L Kaindama, Lorenzo Brusini, Nimitray Joshi, Zineb Rchiad, Declan Brady, David S Guttery, Sally P Wheatley, Hiroyuki Yamano, Anthony A Holder, Arnab Pain, Bill Wickstead, Rita Tewari

“…During its life cycle it undergoes two types of mitosis: endomitosis in asexual stages and an extremely rapid mitotic process during male gametogenesis. Both schizogony (producing merozoites) in host liver and red blood cells, and sporogony (producing sporozoites) in the mosquito vector, are endomitotic with repeated nuclear replication, without chromosome condensation, before cell division. …”
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Transformer-based ensemble model for dialectal Arabic sentiment classification by Omar Mansour, Eman Aboelela, Remon Talaat, Mahmoud Bustami

“…The study compares machine learning models such as support vector machine (SVM), naïve Bayes (NB), decision tree (DT), and extreme gradient boosting (XGBoost) with deep learning models such as convolutional neural networks (CNN) and bidirectional long short-term memory (BLSTM) networks. …”
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Decoding a Cognitive Performance State From Behavioral Data in the Presence of Auditory Stimuli by Saman Khazaei, Rose T. Faghih

“…Deriving an informative observation vector as well as the adaptive model and decoder would be essential in decoding the hidden performance. …”
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Enhanced Subspace Iteration Technique for Probabilistic Modal Analysis of Statically Indeterminate Structures by Hongfei Cao, Xi Peng, Bin Xu, Fengjiang Qin, Qiuwei Yang

“…The essence of this proposed method revolves around efficiently constructing reduced basis vectors during the subspace iteration process, utilizing flexibility disassembly perturbation and the Krylov subspace. …”
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A robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model by Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, Hanieh Shabanian

“…This study introduces a novel model combining multivariate variational mode decomposition (MVMD), gated recurrent unit (GRU), and relevance vector machine (RVM), along with the Boruta feature selection algorithm (BFSA), for precise groundwater level forecasting. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Assessment of the State of Anti-Measles Immunity in Medicine Personnel of a Children's Hospital by T. G. Tkachenko, A. V. Dmitriev, R. A. Gudkov, N. V. Fedina

“…Investigation of the intensity of immunity to measles by ELISA using the VectoKor-IgG test system (Vector-Best, Russia). The surveyed were divided into 4 age groups (20–29, 30–39, 40–49 and 50 years and older). …”
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Machine Learning-Based Classification of Turkish Music for Mood-Driven Selection by Nazime Tokgöz, Ali Değirmenci, Ömer Karal

“…The objective is to facilitate the process of choosing Turkish music according to one’s mood. …”
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Comprehensive Benefit Evaluation for Prefabricated Buildings Based on NSGA-II and Simulated Annealing Optimization Projection Pursuit Method by Fang Wang, Binbin Dai, Shiyu Song

“…The market promotion process of prefabricated construction has been slow, and it is significant to clarify the comprehensive benefits to enhance the willingness of construction units to support and the market share of prefabricated buildings. …”
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Degradation of cellular mir-27 by a novel, highly abundant viral transcript is important for efficient virus replication in vivo. by Lisa Marcinowski, Mélanie Tanguy, Astrid Krmpotic, Bernd Rädle, Vanda J Lisnić, Lee Tuddenham, Béatrice Chane-Woon-Ming, Zsolt Ruzsics, Florian Erhard, Corinna Benkartek, Marina Babic, Ralf Zimmer, Joanne Trgovcich, Ulrich H Koszinowski, Stipan Jonjic, Sébastien Pfeffer, Lars Dölken

“…Expression of the 3'-UTR of m169 by an adenoviral vector was sufficient to mediate its function, indicating that no other viral factors are essential in this process. …”
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Health literacy prediction models based on machine learning methods: a scoping review by PAN Xiang, TONG Yingge, LI Yixuan, NI Ke, CHENG Wenqian, XIN Mengyu, HU Yuying

“…Conclusion: Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.…”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. …”
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Simplified MS2 phage-like particle production including a novel maturation protein internal fusion affinity tag by Enos C. Kline, Rose Duong, Qin Wang, Barry R. Lutz

“…Expanding on prior improvements, this study establishes a revised set of plasmid vectors for Emesvirus zinderi (MS2) derived PLPs that streamline vector manipulations for rapid prototyping of new particles, provide validation of an alternative affinity tag for purification, and contributes a high-throughput low-volume spin column purification strategy. …”
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Seismic Vulnerability Assessment of Reinforced Concrete Educational Buildings Using Machine Learning Algorithm by Tapan Kumar, Mohammad Al Amin Siddique, Raquib Ahsan

“…Random forest regression (RFR), support vector regression (SVR), and artificial neural networks (ANNs) are employed to determine the SSR of existing educational RC buildings. …”
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Selecting a Programming Scheme for Memristor Elements by E. A. Bukvarev, K. S. Fomina, S. A. Shchanikov

“…An array of memristive elements can be used in prospective neural computing systems as a programmable resistance (analog multiplication factor) when performing operations of analog vector multiplication, discrete in time. To form the required resistance, the memristor should be subjected to a programming procedure. …”
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