AI-Driven Advancements in Bioinformatics: Transforming Healthcare and Science by Sunil Namdev Thitame, Ashwini Ashok Aher

“…This review evaluates the fundamental AI enabled bioinformatics approaches with their deployment for genomic and protein structure prediction and drug discovery algorithms and diagnostic solutions. …”
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Secure and efficient batch authentication scheme based on dynamic revocation mechanism in space information network by Yinghui ZHANG, Lingyun HU, Yixin LI, Jianting NING, Dong ZHENG

“…A secure and efficient batch authentication scheme based on dynamic revocation mechanism was proposed for the problem of cross-domain authentication of a large number of mobile users in space information networks.Early key negotiation was achieved by predicting the satellite trajectory and updating the session key in real time.Algorithms were designed for a single as well as a large number of mobile terminals to perform signing and verification, which effectively reduce the computational burden of satellites.Cuckoo filters were adopted by the new scheme to achieve dynamic revocation and malicious access control of mobile terminals.Finally, under the Diffie-Hellman assumption, the proposed scheme was proved to be resistant to replay and man-in-the-middle attacks based on a random oracle model and automated validation of internet security protocols and applications.Security goals such as traceability and revocability were achieved by the scheme, thus improving the efficiency of transmission and computation by more than 80% and 20%, respectively, compared with the existing optimal scheme.…”
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Enhanced pixel-level detection of food regions using a self-attention mechanism by Takuya Futagami

“…This study aims to increase the accuracy of pixel-level detection of food regions extraction algorithms based on saliency detection, which predicts noticeable image areas that are attractive to the human eye. …”
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Analysis of Dynamic Transaction Fee Blockchain Using Queueing Theory by Koki Inami, Tuan Phung-Duc

“…The processing fee varies significantly depending on other transactions; it is difficult to predict the fee, and it may be significantly high. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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Smart Manufacturing through Machine Learning: A Review, Perspective, and Future Directions to the Machining Industry by A. S. Rajesh, M. S. Prabhuswamy, Srinivasan Krishnasamy

“…The current paper presents a comprehensive survey and summary of different machine learning algorithms which are being employed in various traditional and nontraditional machining processes, and also, an outlook of the manufacturing paradigm is presented. …”
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A multi-chroma format cascaded coding method for full-chroma image in AVS2 by Liping ZHAO, Tao LIN, Kailun ZHOU, Keli HU, Chunmei LIN

“…In the second generation of audio video coding standard (AVS2),a multi-chroma format cascaded coding method (MCFCC) for full-chroma (4:4:4 sampling format) images coding was proposed.The MCFCC algorithm firstly converts the 4:4:4 sampling format image into 4:2:0 sampling format image,then the 4:2:0 sampling format image was processed by 4:2:0 sampling format intra prediction,transform,quantization,inverse quantization,inverse transform,entropy coding and a weighted 4:4:4 sampling format distortion calculation method in the rate-distortion optimization process,finally 4:4:4 sampling format in-loop filtering and offset algorithms were applied to the 4:4:4 sampling format image after up sampling.The experimental results show that,for full-chroma natural images,the MCFCC algorithm achieves higher coding efficiency at very low additional encoding complexity and very low additional design and implementation cost.…”
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A Gaussian Process Latent Variable Model for Subspace Clustering by Shangfang Li

“…Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. …”
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Modularized Learning for Hate Speech Detection in Korean: Integrating Emotions and Multi-Faceted Attributes by Hyeun Jeong Min

“…Built on pre-trained Korean language models, our framework extracts features related to emotion, multiple attributes, and similarity, and then employs a classifier for final prediction. Experimental results demonstrate that our proposed method outperforms existing algorithms by achieving a higher f1-score in hate speech recognition.…”
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A Framework for Determining the Big Five Personality Traits Using Machine Learning Classification through Graphology by null Samsuryadi, Rudi Kurniawan, Julian Supardi, null Sukemi, Fatma Susilawati Mohamad

“…These results indicated that the proposed framework can be well applied to predict the personality of the Big Five model through handwriting analysis features.…”
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Teaching deep networks to see shape: Lessons from a simplified visual world. by Christian Jarvers, Heiko Neumann

“…This suggests that different learning algorithms with sparser, more local weight changes are required to make networks more sensitive to shape and improve their capability to describe human vision.…”
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The influence of eye model parameter variations on simulated eye-tracking outcomes by Joshua Fischer, David van den Heever, Johan van der Merwe

“…The outcomes showed that variations in anterior corneal asphericity significantly influence simulated eye-tracking outcomes of both interpolation and model-based gaze estimation algorithms. Other, more commonly varied parameters such as the corneal radius of curvature and foveal offset angle had little influence on simulated outcomes.  …”
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Dual branch guided contrastive learning for unsupervised pedestrian re-identification by REN Hangjia, LIANG Fengmei

“…The current unsupervised pedestrian re-identification algorithms using residual networks can only extract rough global features, but it can’t adequately reflect subtle local features. …”
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Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. …”
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Neural mechanisms for the attention-mediated propagation of conceptual information in the human brain. by David Acunzo, Damiano Grignolio, Clayton Hickey

“…However, neuroscientific investigation has focused closely on the identification of the systems and algorithms that support attentional control or that instantiate the effect of attention on sensation and perception. …”
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The use of web resources for metabolomics in horticultural crops by Esra Karakas, Mustafa Bulut, Alisdair R. Fernie

“…Moreover, the application of machine learning algorithms to these web resources has further optimized data interpretation, enabling more accurate prediction of metabolic profiles. …”
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Dynamic Simulation and Comprehensive Quantitative Evaluation of Rural Tourism Core Competitiveness Based on Neural Network by Shiyuan Gan

“…This paper first designs the neural network algorithm model, then analyzes the dynamic simulation model and comprehensive quantitative analysis, and then uses the artificial neural network algorithm to analyze and predict the core competitiveness of rural tourism. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). …”
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Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features by Yanping Yang, Jiacheng Shen, Sulan Wei, Maosong Ye, Xing Zhao, Jian Zhou, Lin Tong, Jie Hu, Yuanlin Song, Shengdi Wu, Nuo Xu

“…The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. …”
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Clinical utility of artificial intelligence–augmented endobronchial ultrasound elastography in lymph node staging for lung cancerCentral MessagePerspective by Yogita S. Patel, BSc, Anthony A. Gatti, PhD, Forough Farrokhyar, MPhil, PhD, Feng Xie, PhD, Waël C. Hanna, MDCM, MBA

“…NeuralSeg was able to predict 98 of 143 true negatives and 34 of 44 true positives, resulting in an overall accuracy of 70.59% (95% CI, 63.50-77.01), sensitivity of 43.04% (95% CI, 31.94-54.67), specificity of 90.74% (95% CI, 83.63-95.47), positive predictive value of 77.27% (95% CI, 64.13-86.60), negative predictive value of 68.53% (95% CI, 64.05-72.70), and area under the curve of 0.820 (95% CI, 0.758-0.883). …”
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