Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism by Sakorn Mekruksavanich, Wikanda Phaphan, Anuchit Jitpattanakul

“…Despite advances in machine learning and deep learning, capturing the intricate spatial and temporal patterns in EEG data remains challenging. This study introduced a novel deep learning framework combining a convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and convolutional block attention module (CBAM). …”
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Knowledge Discovery in Databases of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer by Mathilde Resell, Elisabeth Pimpisa Graarud, Hanne-Line Rabben, Animesh Sharma, Lars Hagen, Linh Hoang, Nan T. Skogaker, Anne Aarvik, Magnus K. Svensson, Manoj Amrutkar, Caroline S. Verbeke, Surinder K. Batra, Gunnar Qvigstad, Timothy C. Wang, Anil Rustgi, Duan Chen, Chun-Mei Zhao

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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

“…The sensitivity to neuron number in the hidden layers for DSLG was more pronounced compared to the PSLG pattern, and the mean square error (MSE) was calculated for this evaluation. …”
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Scene Semantic Recognition Based on Modified Fuzzy C-Mean and Maximum Entropy Using Object-to-Object Relations by Ahmad Jalal, Abrar Ahmed, Adnan Ahmed Rafique, Kibum Kim

“…An Artificial Neural Network recognizes the multiple objects using the different patterns of objects. …”
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Understanding the ancient classic and famous prescriptions via the property of Chinese materia medica by Dan Qin, Dan Qin, He Zhang, Bin Du, Hui Wang, Ligang Liu, Yun Wang

“…Existing research predominantly focuses on individual prescriptions, and there is lack of systematic exploration of medication patterns within the official ACFPs catalog. The property of Chinese materia medica (PCMM), a multidimensional representation of medicinal properties, offers a novel perspective for systematically analyzing TCM formulas.ObjectiveIn this study, we aim to investigate the implicit medication patterns of ACFPs from the PCMM perspective, establish a feature extraction model based on the property combination of Chinese materia medica (PCCMM), and evaluate its effectiveness in representing and reconstructing ACFPs.MethodsBased on the Chinese Pharmacopoeia (ChP), we constructed a CMM–PCCMM network as the forward feature extraction process. …”
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A Method for Localization of Cellular Users From Call Detail Records by Steven W. Ellingson

“…The performance of the proposed method is evaluated by “best server” analysis of measurements acquired from drive testing in the vicinity of Winter Garden, Florida, observing three 700 MHz-band LTE cellular networks serving this area. …”
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Adversarial denoising of EEG signals: a comparative analysis of standard GAN and WGAN-GP approaches by Imad Eddine Tibermacine, Samuele Russo, Francesco Citeroni, Giuseppe Mancini, Abdelaziz Rabehi, Amal H. Alharbi, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Christian Napoli, Christian Napoli, Christian Napoli

“…The results further suggest that GAN-based frameworks can be easily scaled to next-generation wireless networks and complex electrophysiological datasets, offering robust and dynamic solutions to long-standing challenges in EEG denoising.…”
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Smart intrusion detection model to identify unknown attacks for improved road safety and management by Faisal Alshammari, Abdullah Alsaleh

“…ACIDS integrates convolutional neural networks (CNN) for hierarchical feature extraction, the synthetic minority over-sampling technique (SMOTE) to address class imbalance and an open-set classification framework to detect novel attack patterns. …”
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Can attention-deficit/hyperactivity disorder be considered a form of cerebellar dysfunction? by Valeria Isaac, Vladimir Lopez, Maria Josefina Escobar

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Forecasting temperature and rainfall using deep learning for the challenging climates of Northern India by Syed Nisar Hussain Bukhari, Kingsley A. Ogudo

“…The major research focus is to develop and evaluate a model capable of capturing complex temporal dependencies in localized time-series weather data. …”
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Pears Internal Quality Inspection Based on X-Ray Imaging and Multi-Criteria Decision Fusion Model by Zeqing Yang, Jiahui Zhang, Zhimeng Li, Ning Hu, Zhengpan Qi

“…The proposed method combines manual feature-based classifiers, including Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG), with a deep convolutional neural network (DCNN) model within an MCD-based fusion framework. …”
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Pore scale fracturing fluid occurrence mechanisms in multi-scale matrix-fracture system of shale gas reservoir by XIA Haibang, HAN Kening, SONG Wenhui, WANG Wei, YAO Jun

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Estimation of Fractal Dimensions and Classification of Plant Disease with Complex Backgrounds by Muhammad Hamza Tariq, Haseeb Sultan, Rehan Akram, Seung Gu Kim, Jung Soo Kim, Muhammad Usman, Hafiz Ali Hamza Gondal, Juwon Seo, Yong Ho Lee, Kang Ryoung Park

“…Furthermore, to improve the capability of our proposed system, we performed fractal dimension estimation to evaluate the structural complexity of healthy and diseased leaf patterns. …”
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Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search by Peifeng Wu, Yaqiang Chen

“…Experimental results demonstrate that the proposed model outperforms conventional methods across various evaluation metrics, offering superior accuracy and robustness in recognizing fraudulent patterns in corporate accounting data.…”
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The use of mobile phone surveys for rapid mortality monitoring: A national study in Burkina Faso by Kassoum Dianou, Abdramane B. Soura, Bruno Lankoandé, Hervé Bassinga, Shammi Luhar, Ashira Menashe-Oren, Kelly McCain, Malebogo Tlhajoane, Georges Reniers, Bruno Masquelier

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A Multi-Phase DRL-Driven SDN Migration Framework Addressing Budget, Legacy Service Compatibility, and Dynamic Traffic by Kai Yuan Tan, Saw Chin Tan, Teong Chee Chuah

“…By integrating a DRL model with a clustering algorithm, SMART determines the migration sequence to minimize link utilization and reduce the number of SDN-enabled nodes required for effective traffic load distribution under dynamic traffic patterns. Extensive evaluations on the Abilene and GEANT network topologies demonstrate that SMART outperforms three existing approaches, achieving most of the SDN benefits by migrating only 36% and 52% of legacy nodes, respectively. …”
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The use of artificial intelligence to analyze and optimize financial flows by М. А. Miakisheva

“…In the scientific literature, there are contradictions between theoretical models of using AI and the practical possibilities of their implementation, as well as disagreements in evaluating the effectiveness of various types of neural networks for financial forecasting. …”
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Mobile Phone Network Data in the COVID-19 era: A systematic review of applications, socioeconomic factors affecting compliance to non-pharmaceutical interventions, privacy implicat... by Mohammed Okmi, Tan Fong Ang, Muhammad Faiz Mohd Zaki, Chin Soon Ku, Koo Yuen Phan, Irfan Wahyudi, Lip Yee Por

“…However, because these datasets represent only discrete instances of measurement, they miss continuous temporal shifts in human activities, failing to record the majority of human mobility patterns in real-time. Bolstered by the rapid expansion of telecommunication networks and the ubiquitous use of smartphones, mobile phone network data (MPND) played a pivotal role in fighting and controlling the spread of COVID-19.…”
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A Machine Learning Approach for User Behavior Analysis in Developing Websites by Aeesha Shaheen

“…After training, the accuracy of network assesses using test data, and evaluate the effectiveness of forecasting. …”
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Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

“…ANNS are inspired by the neural architecture of human brain capable of learning and recognizing patterns in unchartered data after trained examples, on the other hand GAs come from fundamental principles underlying natural selection perform optimization process based-on evolutionary methods which includes fitness evaluation, comparison, selection, crossover, and mutation. …”
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