FBiLSTM-Attention short-term load forecasting based on fuzzy logic by Yan ZHANG, Zepeng KANG, Xiaozhi GAO, Nan YANG, Zhaolei WANG

“…Aiming at the problem of high uncertainty in power load data due to various factors, a fuzzy logic based FBiLSTM Attention short-term load forecasting model was proposed by combining the uncertainty of load data with deep learning algorithms to improve the accuracy of load forecasting. …”
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Prediction of white matter hyperintensities evolution one-year post-stroke from a single-point brain MRI and stroke lesions information by Muhammad Febrian Rachmadi, Maria del C. Valdés-Hernández, Stephen Makin, Joanna Wardlaw, Henrik Skibbe

“…Given the predominantly vascular nature of WMH, in this study, we evaluate the impact of incorporating stroke lesion information to a probabilistic deep learning model to predict the evolution of WMH 1-year after the baseline image acquisition, taken soon after a mild stroke event, using T2-FLAIR brain MRI. …”
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GPS TRAJECTORY CLUSTERING FOR SPATIO – TEMPORAL BEHAVIOR ANALYSIS: THE APPLICATION OF HEATMAP TECHNIQUES AND SPATIO- TEMPORAL DUAL GRAPH NEURAL NETWORK by Mais Muhanad, Wadhah R.Baiee

“…Additionally, this thesis introduces a framework for time estimation based on graph-based deep learning, termed Spatio-Temporal Dual Graph Neural II Networks (STDGNN). …”
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Refined matrix completion for spectrum estimation of heart rate variability by Lei Lu, Tingting Zhu, Ying Tan, Jiandong Zhou, Jenny Yang, Lei Clifton, Yuan-Ting Zhang, David A. Clifton

“…Benchmarking on five public datasets, our model shows effectiveness and reliability in estimating uncertainties in HRV spectrum, and has superior performance against five deep learning models. The results underscore the potential of our developed matrix completion-based statistical machine learning model in providing reliable HRV spectrum uncertainty estimation.…”
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Codeine 3-O-demethylase catalyzed biotransformation of morphinan alkaloids in Escherichia coli: site directed mutagenesis of terminal residues improves enzyme expression, stability... by Garrick W. K. Spencer, Xu Li, Kenny W. L. Lam, George Mutch, Fiona H. Fry, Sally L. Gras

“…Statistical analysis of biotransformation yield, enzyme expression and stability, predicted using changes in Gibbs free energy (ΔΔG) with deep-learning-based model DDmut, suggested that altered enzyme stability and/or expression of soluble protein may contribute to the observed improvements in biotransformation. …”
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Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model. by Gülcan Gencer, Kerem Gencer

“…This paper offers a hybrid SE (Squeeze-and-Excitation)-Enhanced Hybrid Model for detecting retinal disorders from OCT images, including DME, Drusen, and CNV, using artificial intelligence and deep learning.<h4>Methods</h4>The model integrates SE blocks with EfficientNetB0 and Xception architectures, which provide high success in image classification tasks. …”
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Advances in antiviral strategies targeting mosquito-borne viruses: cellular, viral, and immune-related approaches by Ayyaz Khan, Zakirullah, Shahid Wahab, Seong-Tshool Hong

“…Additionally, it explores immunomodulatory therapies to enhance antiviral responses and emphasizes the potential of drug repurposing, bioinformatics, artificial intelligence, and deep learning in identifying novel antiviral candidates. …”
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Communication System Using Natural Language for Robotic Laparoscope Guidance by Pan Yan, Bernhard Lukas, Fan Cheng, Beckendorf Lukas, Wilhelm Dirk, Feußner Hubertus, Groh Georg

“…To solve these challenges, our proposed communication system uses the fine-tuned deep learning model to recognize the speaker information, and the robot assistant takes action only when it detects the commands from the responsible clinician. …”
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Human lineage mutations regulate RNA-protein binding of conserved genes NTRK2 and ITPR1 involved in human evolution by Min Zhao, Weichen Song, Shunying Yu, Wenxiang Cai, Guan Ning Lin

“…Background The role of human lineage mutations (HLMs) in human evolution through post-transcriptional modification is unclear.Aims To investigate the contribution of HLMs to human evolution through post-transcriptional modification.Methods We applied a deep learning model Seqweaver to predict how HLMs impact RNA-binding protein affinity.Results We found that only 0.27% of HLMs had significant impacts on RNA-binding proteins at the threshold of the top 1% of human common variations. …”
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SynC2S: An Efficient Method for Synthesizing Tabular Data With a Learnable Pre-Processing by Jiwoo Kim, Seri Park, Junsung Koh, Dongha Kim

“…Recently, numerous methods based on deep learning have been developed, while a clear understanding of their effectiveness is still insufficient, and the necessity for more efficient frameworks persists. …”
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Spam detection using hybrid model on fusion of spammer behavior and linguistics features by Amna Iqbal, Muhammad Younas, Saman Iftikhar, Fakeeha Fatima, Rabia Saleem

“…The unified representation of features is another challenging task in spam detection. Various deep learning approaches have been proposed for review spamming, including different neural networks (Convolutional Neural Network, CNN). …”
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Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image by Dong Zhao, Long Xu, Linjie Chen, Yihua Yan, Ling-Yu Duan

“…This paper makes effort to retrieve/recover missing information of overexposure by exploiting deep learning for its powerful nonlinear representation which makes it widely used in image reconstruction/restoration. …”
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Pervasive glacier retreats across Svalbard from 1985 to 2023 by Tian Li, Stefan Hofer, Geir Moholdt, Adam Igneczi, Konrad Heidler, Xiao Xiang Zhu, Jonathan Bamber

“…Using 124919 calving front positions for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, generated with deep learning, we identify pervasive calving front retreats for non-surging glaciers over the past 38 years. …”
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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

“…This paper reviews how deep learning helps predict gas distribution and classify rock types. …”
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VulMPFF: A Vulnerability Detection Method for Fusing Code Features in Multiple Perspectives by Xiansheng Cao, Junfeng Wang, Peng Wu, Zhiyang Fang

“…Source code vulnerabilities are one of the significant threats to software security. Existing deep learning-based detection methods have proven their effectiveness. …”
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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. …”
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Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets by Viet Anh Truong, Ngoc Sang Dinh, Thanh Long Duong, Ngoc Thien Le, Cong Dinh Truong, Linh Tung Nguyen

“…Past research has predominantly focused on utilizing meta-heuristic algorithms to optimize neural network structures, while the exploration of deep learning in optimization has remained relatively limited. …”
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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. Combining the two methods is expected to enhance the performance of an SSVEP-based brain-computer interface (BCI) by exploiting their advantages. …”
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TopoQual polishes circular consensus sequencing data and accurately predicts quality scores by Minindu Weerakoon, Sangjin Lee, Emily Mitchell, Haynes Heaton

“…TopoQual leverages techniques including partial order alignments (POA), topologically parallel bases, and deep learning algorithms to polish consensus sequences. …”
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Food Sales Prediction Using MLP, RANSAC, and Bagging by Hussam Mezher Merdas, Ayad Hameed Mousa

“…Some studies used classical machine learning algorithms, some used deep learning algorithms, and others used ensemble techniques. …”
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