ESX: A Self-Generated Control Policy for Remote Access With SSH Based on eBPF by Yuan Zhong, Pengfei Chen, Huxing Zhang

“…To mitigate these issues, we introduce Extend Security boX (ESX), a novel solution that combines a lightweight system call restriction system with machine learning method. ESX utilizes rule learning through itemset mining to analyze user behavior and generate system call control lists, thereby significantly reducing system vulnerability. …”
Get full text

Testing convolutional neural network based deep learning systems: a statistical metamorphic approach by Faqeer ur Rehman, Clemente Izurieta

“…Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains, i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity, etc. …”
Get full text

Neural circuits underlying context-dependent competition between defensive actions in Drosophila larvae by Maxime Lehman, Chloé Barré, Md Amit Hasan, Benjamin Flament, Sandra Autran, Neena Dhiman, Peter Soba, Jean-Baptiste Masson, Tihana Jovanic

“…Using neuronal manipulations, machine learning-based behavioral detection, electron microscopy (EM) connectomics and calcium imaging in Drosophila larvae, we map second-order interneurons that are differentially involved in the competition between defensive actions in response to competing aversive cues. …”
Get full text

Technical Diagnostics of Industrial Robots Using Vibration Signals: Case Study on Detecting Base Unfastening by Daria Fedorova, Vladimír Tlach, Ivan Kuric, Tomáš Dodok, Ivan Zajačko, Karol Tucki

“…These selected features were then used as inputs to various machine learning models to evaluate the hypothesis that these parameters can reliably indicate fastening releasing events. …”
Get full text

Adaptive Ensemble Learning Model-Based Binary White Shark Optimizer for Software Defect Classification by Jameel Saraireh, Mary Agoyi, Sofian Kassaymeh

“…In recent decades, Data-mining techniques and machine learning for classifying problematic software projects have emerged to improve software quality. …”
Get full text

Identification of Buffalo Breeds Using Self-Activated-Based Improved Convolutional Neural Networks by Yuanzhi Pan, Hua Jin, Jiechao Gao, Hafiz Tayyab Rauf

“…Moreover, feature maps extracted from CNN are further transferred to obtain rich feature vectors. Different machine learning (Ml) classifiers are adopted to classify the feature vectors. …”
Get full text

Gut–brain axis and neuropsychiatric health: recent advances by Ceymi Doenyas, Gerard Clarke, Renáta Cserjési

“…There is also evidence that the gut–brain axis plays a role in obesity and machine learning algorithms may assist in differentiating between obese and overweight individuals based on their microbiota data. …”
Get full text

Predicting the Spatial-Temporal Distribution of Human Brucellosis in Europe Based on Convolutional Long Short-Term Memory Network by Li Shen, Chenghao Jiang, Minghao Sun, Xuan Qiu, Jiaqi Qian, Shuxuan Song, Qingwu Hu, Heilili Yelixiati, Kun Liu

“…Taking major European countries as an example, this study established the temporal and spatial distribution sequence of brucellosis, analyzed the temporal and spatial distribution characteristics of brucellosis, and quantitatively predicted its epidemic law by using different traditional or machine learning models. This paper indicates that the epidemic of brucellosis in major European countries has statistical periodic characteristics, and in the same cycle, brucellosis has the characteristics of piecewise trend. …”
Get full text

Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation by Xiaoming Zhang, Lean Yu, Hang Yin

“…Abstract Machine learning methods are widely used to evaluate the risk of small- and medium-sized enterprises (SMEs) in supply chain finance (SCF). …”
Get full text

Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing by Hongwei Song, Ming Li, Chaoquan Wu, Qingchuan Wang, Shunke Wei, Mingxing Wang, Wenhui Ma

“…This method consists of an application of machine learning techniques on the probability density function (PDF) and the power spectral density (PSD) of the power spectrum output of an ultrasonic Doppler sensor in the pipe. …”
Get full text

Scaled Fenwick Trees by Matthew Cushman

“…Computing sums of ranges of arrays of numbers is a common computational problem encountered in data compression, coding, machine learning, computational vision, and finance, among other fields. …”
Get full text

A Review of AI Applications in Unconventional Oil and Gas Exploration and Development by Feiyu Chen, Linghui Sun, Boyu Jiang, Xu Huo, Xiuxiu Pan, Chun Feng, Zhirong Zhang

“…It also explains how machine learning improves reservoir simulation and history matching. …”
Get full text

A Computational Approach to Understanding Agglutinative Structures in Urdu by Muhammad Shoaib Tahir, Mahnoor Amjad

“…Furthermore, the research explores the limitations of traditional rule-based models in handling Urdu’s morphological complexity and advocates for the adoption of machine learning and deep learning techniques. These modern approaches, particularly Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs), show promise in accurately modeling Urdu's agglutinative morphology, though they require extensive linguistic data and computational resources. …”
Get full text

Assessing the capture of sociodemographic information in electronic medical records to inform clinical decision making. by Rawan Abulibdeh, Karen Tu, Debra A Butt, Anthony Train, Noah Crampton, Ervin Sejdić

“…The association between the completeness rates of the sociodemographic data and the various clinics, electronic medical record vendors, and physician characteristics was analyzed. Supervised machine learning models were used to determine the absence or presence of each characteristic for all adult patients over the age of 18 in the database. …”
Get full text

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network by Qingguo Wei, Chang Li, Yijun Wang, Xiaorong Gao

“…Abstract Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either a traditional machine learning algorithm or a deep learning network. …”
Get full text

Modeling the gameplay actions of elite volleyball players and teams based on statistical match reports by Sergii Iermakov, Tetiana Yermakova, Krzysztof Prusik

“…The pandas library was used for data analysis and statistical operations, and 'scikit-learn' for machine learning. Results. Models are presented that best predict the results for teams and volleyball players. …”
Get full text

Quantum distance approximation for persistence diagrams by Bernardo Ameneyro, Rebekah Herrman, George Siopsis, Vasileios Maroulas

“…The space of persistence diagrams can be endowed with various metrics, which admit a statistical structure and allow to use these summaries for machine learning algorithms, e.g. the Wasserstein distance. …”
Get full text

A comprehensive image dataset for the identification of lemon leaf diseases and computer vision applicationsMendeley Data by A K M Fazlul Kobir Siam, Prayma Bishshash, Md. Asraful Sharker Nirob, Sajib Bin Mamun, Md Assaduzzaman, Sheak Rashed Haider Noori

“…The dataset will not only act as a benchmark in developing accurate machine learning models for early disease detection, but it will also contribute to the cause of sustainable lemon cultivation practices by facilitating timely and effective disease management interventions.…”
Get full text

Does Using Artificial Intelligence in Citizen Science Support Volunteers’ Learning? An Experimental Study in Ornithology by Khrystyna Pankiv, Laure Kloetzer

“…This research investigates how the use of machine learning (ML) classification models affects the learning of novice birders. …”
Get full text

Experimental and analytical study on axial behaviour of square corrugated concrete filled single and double skin tube stub columns by Aya Mohsen Handousa, Mohamed Abdellatief, Fikry Abdo Salem, Nabil Mahmoud, Mohamed Ghannam

“…Furthermore, the study proposed two machine-learning models, namely Artificial Neural Network (ANN) and Gaussian Process Regression (GPR), to estimate the ultimate compressive strength of square CFDST columns. …”
Get full text