TIBW: Task-Independent Backdoor Watermarking with Fine-Tuning Resilience for Pre-Trained Language Models by Weichuan Mo, Kongyang Chen, Yatie Xiao

“…This paper presents a novel watermarking scheme, TIBW (Task-Independent Backdoor Watermarking), that embeds robust, task-independent backdoor watermarks into pre-trained language models. By implementing a Trigger–Target Word Pair Search Algorithm that selects trigger–target word pairs with maximal semantic dissimilarity, our approach ensures that the watermark remains effective even after extensive fine-tuning. …”
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Approximation-Aware Training for Efficient Neural Network Inference on MRAM Based CiM Architecture by Hemkant Nehete, Sandeep Soni, Tharun Kumar Reddy Bollu, Balasubramanian Raman, Brajesh Kumar Kaushik

“…This architecture includes a mapping algorithm that modulates inputs and map AFC to crossbar arrays directly, eliminating the need to predict approximated weights for evaluating output. …”
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Comprehensive optimization of passenger trains operation based on an automated system for managing the profitability of passenger traffic by G. L. Venediktov, V. M. Kochetkov

“…On the example of real data of the operation of this train, the effectiveness of the automated system for managing the profitability of passenger traffic, created on the basis of complex optimization algorithms, was evaluated. …”
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Training size predictably improves machine learning-based epileptic seizure forecasting from wearables by Mustafa Halimeh, Michele Jackson, Tobias Loddenkemper, Christian Meisel

“…Evaluations were made using improvement over chance (IoC) and the Brier skill score (BSS), which measured the improvement of the NN Brier score compared to the Brier score of a rate-matched random (RMR) forecast.Results: Performance quantified by IoC and BSS increased with training data following precise power-law scaling laws, thereby exceeding prior reported performance levels from smaller datasets. …”
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Automatic motion recognition technology based on fuzzy clustering algorithm and VR video image by Ganbin Xu, Jianwei Lin

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Application of machine learning algorithm for prediction of abortion among reproductive age women in Ethiopia by Angwach Abrham Asnake, Alemayehu Kasu Gebrehana, Hiwot Altaye Asebe, Beminate Lemma Seifu, Bezawit Melak Fente, Meklit Melaku Bezie, Mamaru Melkam, Sintayehu Simie Tsega, Yohannes Mekuria Negussie, Zufan Alamrie Asmare

“…This study used 7 machine learning algorithms for the classification of abortion. The dataset was randomly split into training and testing sets, with 80% allocated for training and 20% for testing. …”
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Novel data visualization and risk analytic algorithm in a low-middle income country by Hina Inam, Fatima Amjad, Abdul Ahad Sohail, Qalab Abbas

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Sentiment Analysis of X Users Toward Electric Motorcycles Using SVM and BERT Algorithms by Calvin Adiwinata, Afiyati Afiyati

“…The objective was to evaluate algorithm performance in classifying public sentiment, with metrics including accuracy, precision, recall, and computational efficiency. …”
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…The proposed approach is rigorously evaluated on multiple publicly available mitosis detection datasets, including Mitosis WSI CCMCT Training Set, Mitosis-AIC, Mitosis Detection, and Mitosis and Non-Mitosis datasets. …”
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instancespace: A Python package for insightful algorithm testing through Instance Space Analysis by Yusuf Berdan Güzel, Kushagra Khare, Nathan Harvey, Kian Dsouza, Dong Hyeog Jang, Junheng Chen, Cheng Ze Lam, Mario Andrés Muñoz

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An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes by Hou Xiaoping, Yu Jiashun, Yuan Jianlong, Fu Xiaobo, Fan Xinran, Han Chao, Liu Zhigang, Qian Guang, Zhou Qiang

“…In order to evaluate the practicability of the algorithm, we applied it to surface wave data from an industrial prospecting project. …”
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Applying neural networks as direct controllers in position and trajectory tracking algorithms for holonomic UAVs by Cezary Kownacki, Slawomir Romaniuk, Marcin Derlatka

“…The research’s novelty lies in applying these algorithms directly for control. A position-tracking algorithm based on the artificial potential field method generated extensive training and validation datasets, simulating the tracked point’s diverse trajectory shapes and velocities. …”
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Fuzzy operator infrared image deblurring algorithm for image blurring in dragon boat races by Xiao Tang, Yuan Shen, Genwei Zhu

“…The experiment showed that the models trained utilizing original and synthesized datasets had very small differences in peak signal-to-noise ratio and structural similarity performance indicators, and the evaluation results were close. …”
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Smart prediction-planning algorithm for connected and autonomous vehicle based on social value orientation by Donglei Rong, Yuefeng Wu, Wenjun Du, Chengcheng Yang, Sheng Jin, Min Xu, Fujian Wang

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Sensor-Based Bermudagrass Yield Prediction Models Using Random Forest Algorithm in Oklahoma by Gabriel Camargo de Campos Jezus, Lucas Freires Abreu, Daryl Brian Arnall, Lucas Martins Stolerman, Alexandre Caldeira Rocateli

“…Current literature states that (i) machine learning algorithms are promising in agriculture, and (ii) proximity and multispectral sensors can be employed to predict biomass. …”
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Research on Tool Wear Monitoring Based on ET-GD and K-nearest Neighbor Algorithm by QIN Yiyuan, LIU Xianli, YUE Caixu, GUO Bin, DING Mingna

“…The optimized features are used to train logical regression extreme random tree support vector regression and K-nearest neighbor algorithm models and verified by ten fold cross validation method and test set. …”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Dynamic display algorithm of sonar data based on grayscale distribution model and computational intelligence by Hongquan Lei, Diquan Li, Haidong Jiang

“…To verify the effectiveness of the proposed method, a test set was used to evaluate the trained target recognition model. The precision of the model recognition was 87.95%, the recall was 87.97%, and the F1 value was 0.8794, which is significantly higher than the traditional model (Such as Otsu and SVM is below 80%). …”
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Optimizing Solid Oxide Fuel Cell Performance Using Advanced Meta-Heuristic Algorithms by Siva Ram Rajeyyagari, Srinivas Nowduri

“…The main novelty of this work lies in the application of six meta-heuristic algorithms for optimizing the weights and biases of the trained RBF network. …”
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Forecasting the progression of Alzheimer's disease using neural networks and a novel preprocessing algorithm by Jack Albright, Alzheimer's Disease Neuroimaging Initiative

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