A Secure and Efficient White-Box Implementation of SM4 by Xiaobo Hu, Yanyan Yu, Yinzi Tu, Jing Wang, Shi Chen, Yuqi Bao, Tengyuan Zhang, Yaowen Xing, Shihui Zheng

“…We employ fourth-order non-linear encoding to reduce the loss of efficiency while utilizing a random sequence to shuffle lookup table access, thereby severing the potential link between memory data and the intermediate values of SM4. …”
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A Novel Authentication Management for the Data Security of Smart Grid by Imtiaz Parvez, Maryamossadat Aghili, Hugo Riggs, Aditya Sundararajan, Arif I. Sarwat, Anurag K. Srivastava

“…In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. …”
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A review on amino acid based protein classification using supervised artificial intelligence (AI) models by Rida Zulfiqar, Talha Ahmed Khan, Abdullah Ayub Khan, Rubaika Akhtar, Sajid Ullah

“…Numerous sequences connect each protein to one of the numerous predetermined groups. …”
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Unsupervised learning analysis on the proteomes of Zika virus by Edgar E. Lara-Ramírez, Gildardo Rivera, Amanda Alejandra Oliva-Hernández, Virgilio Bocanegra-Garcia, Jesús Adrián López, Xianwu Guo

“…Methods In this work, unsupervised Random Forest (URF), followed by the application of dimensional reduction algorithms such as principal component analysis (PCA), Uniform Manifold Approximation and Projection (UMAP), t-distributed stochastic neighbor embedding (t-SNE), and autoencoders were used to uncover hidden patterns from polymorphic amino acid sites extracted on the proteome ZIKV multi-alignments, without the need of an underlying evolutionary model. …”
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The "one-group-one-cipher" cryptograph of block-cipher based on chaotic by XUAN Lei1, YAN Ji-ning1

“…The"one-group-one-cipher"algorithm used the sequence from chaotic mapping as sub-key for block cipher was presented to solve the problem of weak keys existing in currently combined cipher algorithms.The randomness of abstracted key sequence was validated in aspects of Shannon entropy.The"one-group-one-cipher"algorithm was de-signed and implemented based on hyper-chaos generalized Hénon mapping and IDEA algorithms, and its security was analyzed theoretically.Analysis shows that the algorithm is so secure that it can withstand brute force attack, and it was perfect secrecy.The disadvantages of key’s reuse of block ciphers are avoided, and the practicality and feasibility of chaos ciphers and one-time pad are improved.…”
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An LDPC Encoder Architecture With Up to 47.5 Gbps Throughput for DVB-S2/S2X Standards by Decai Liu, Yanfei Luo, Yunfeng Li, Zhijie Wang, Zhengxuan Li, Qianwu Zhang, Junjie Zhang, Yingchun Li

“…In this paper, by extracting the periodicity of the parity-check matrix, we introduce a fast encoding algorithm that can efficiently process the multiplication of the information sequence and a large-dimensional sparse matrix, and propose an encoder architecture with low encoding delay and high throughput. …”
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Image Processing Method Based on Chaotic Encryption and Wavelet Transform for Planar Design by Yiying Liu, Young Chun Ko

“…The plaintext image is decomposed in odd-even sequence using the boosting algorithm to get the sequence with an even index and the sequence with an odd index; then, the diffusion algorithm is applied to the two sequences by the prediction and update algorithm, and this process is repeated many times to get the two ciphertext sequences after scrambling, merging these two sequences, and matrixing them to get the ciphertext image. …”
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Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence by Pragya, A. Amalin Prince, Jac Fredo Agastinose Ronickom

“…We used AI algorithms like random forest regressor (RFR), extreme gradient boost regressor (XGBR), and one-dimensional convolutional neural network (1D-CNN) to predict the binding affinity. …”
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Evaluation of drug-drug interaction between Suraxavir Marboxil (GP681) and itraconazole, and assessment of the impact of gene polymorphism by Mai Han, Gang Cui, Yan Zhao, Xianbo Zuo, Xiaoxue Wang, Xin Zhang, Na Mi, Jiangli Jin, Chunyan Xiao, Jing Wang, Wei Wu, Yajuan Li, Jintong Li

“…No significant increase in adverse events was observed during co-administration. Using random forest algorithm, we estimated effects of cytochrome P450 enzymes followed the order of CYP 3A4 > CYP 1A2 > CYP 2C19. …”
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Identifying functional groups among the diverse, recombining antigenic var genes of the malaria parasite Plasmodium falciparum from a local community in Ghana. by Mary M Rorick, Edward B Baskerville, Thomas S Rask, Karen P Day, Mercedes Pascual

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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

“…Four machine learning algorithms (Random Forest, Support Vector Classification, Gradient Boosting, and Extremely Randomized Tree Classifier) were applied to create eight classification models based on bacterial abundance at the genus level and KEGG pathways. …”
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Playing hide and seek with primates: A comparative study of Theory of Mind by Aurore San‑Galli, Marie Devaine, Cinzia Trapanese, Shelly Masi, Sébastien Bouret, Jean Daunizeau

“…Critically, we varied the sophistication of these algorithms, yielding three conditions, ranging from a control (a simple random biased sequence) to a mildly sophisticated ToM agent (1-ToM). …”
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Continuous Speech-Based Fatigue Detection and Transition State Prediction for Air Traffic Controllers by Susmitha Vekkot, Surya Teja Chavali, Charan Tej Kandavalli, Rama Sai Abhishek Podila, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi

“…The evaluation was carried out using various learning algorithms such as XGBoost, Adaboost, Random Forest, HistogramGB, and 1D-CNN. …”
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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study by Shengyu Liu, Anran Wang, Xiaolei Xiu, Ming Zhong, Sizhu Wu

“…MethodsThis study comprehensively evaluated 7 NER models—hidden Markov models, conditional random fields, BERT for Biomedical Text Mining, Big Transformer Models for Efficient Long-Sequence Attention, Decoding-enhanced BERT with Disentangled Attention, Robustly Optimized BERT Pretraining Approach, and Gemma—across 3 medical datasets: Revised Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA), BioCreative V CDR, and Anatomical Entity Mention (AnatEM). …”
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Identification of Key Genes Related to Intramuscular Fat Content of Psoas Major Muscle in Saba Pigs by Integrating Bioinformatics and Machine Learning Based on Transcriptome Data by Zixia Huang, Yongli Yang, Jinhua Lai, Qiang Chen, Xiaoyi Wang, Shuyan Wang, Mingli Li, Shaoxiong Lu

“…Four potential fat-deposition-related genes (<i>DGAT2</i>, <i>PCK1</i>, <i>MELK</i>, and <i>FASN</i>) were further screened via the intersection of the candidate genes identified by the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and the top five genes ranked by the Random Forest (RF) method based on the 20 hub genes and were validated in the test gene set (GSE207279). …”
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Encryption Of Speech Signal With Multiple Secret Keys by Dalila Slimani, Fatiha Merazka

“…The original key is generated, randomly, using a pseudo noise sequence generator, and the two other keys are obtained by using the main key. …”
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Research on Anomaly Detection Model for Power Consumption Data Based on Time-Series Reconstruction by Zhenghui Mao, Bijun Zhou, Jiaxuan Huang, Dandan Liu, Qiangqiang Yang

“…The detection module employs a random forest algorithm optimized by grid search to detect residuals and ultimately identify outliers. …”
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Enhancing AES image encryption with a three-dimensional hyperchaotic system for increased security and efficiency. by Mingyi Huo, Yanpei Zheng, Jun Huang

“…The crux of this framework is the incorporation of a novel TDHCS, distinguished by its intricate nonlinear dynamics and robust randomness. The AES encryption process is simplified based on the high-level random chaotic sequences generated by TDHCS. …”
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A novel 2D MTMHM based key generation for enhanced security in medical image communication by C. Sivaranjani Devi, Rengarajan Amirtharajan

“…The generated random key sequences trigger the proposed medical image encryption algorithm, which integrates a shuffling-diffusion process. …”
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