A Method for Improving the Monitoring Quality and Network Lifetime of Hybrid Self-Powered Wireless Sensor Networks by Peng Wang, Yonghua Xiong

“…Finally, a method based on an improved nutcracker optimizer algorithm is proposed to solve the optimal working sequence of nodes, schedule the “sleep or work” state of nodes, and extend the network lifetime. …”
Get full text

ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data. by Brett A McKinney, Bill C White, Diane E Grill, Peter W Li, Richard B Kennedy, Gregory A Poland, Ann L Oberg

“…For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. …”
Get full text

First Report of Ganoderma ryvardenii causing Basal Stem Rot (BSR) disease on oil palm (Elaeis guineensis Jacq.) in Ghana [version 2; peer review: 1 approved, 2 approved with reserv... by Frank K. Ackah, Grace C. van der Puije, Emmanuellah Lekete-Lawson, Enoch A. Osekre

“…Molecular assays were performed on each sample using nucleic acid as a template. ITS and GanET sequence analysis were performed along with the formation of a phylogenetic tree using the FASTA algorithm with the Fungus database from EBI and NCBI GenBank. …”
Get full text

Active Learning for Medical Article Classification with Bag of Words and Bag of Concepts Embeddings by Radosław Pytlak, Paweł Cichosz, Bartłomiej Fajdek, Bogdan Jastrzębski

“…The evaluation uses the support vector machine, naive Bayes, and random forest algorithms and is performed on datasets from 15 systematic medical literature review studies. …”
Get full text

Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Performing specific operations on data in sequence of steps provided flexibility and adaptability in processing the data, making it easy to train, evaluate, and validate the learning algorithms. …”
Get full text

Three-Dimensional Trajectory Tracking Control for Stratospheric Airship Based on Deep Reinforcement Learning by Xixiang Yang, Fangchao Bai, Xiaowei Yang, Yuelong Pan

“…According to the discrete state and action space, a Markov decision process model for the three-dimensional trajectory tracking control problem was established. The Boltzmann random distribution of reward value and probability of wind direction angle were taken as the action selection criteria of the Q-learning algorithm, the cerebellar model articulation controller (CMAC) neural network was constructed for the discrete action value, and the optimal action sequence was fast obtained. …”
Get full text

HDIEA: high dimensional color image encryption architecture using five-dimensional Gauss-logistic and Lorenz system by Bharti Ahuja, Rajesh Doriya, Sharad Salunke, Mohammad Farukh Hashmi, Aditya Gupta, Neeraj Dhanraj Bokde

“…The Runge–Kutta technique is used to discretise the Lorenz system in order to construct a pseudo-random sequence generation for the control parameter that has a greater degree of randomness. …”
Get full text

Utilizing machine learning and bioinformatics analysis to identify drought stress responsive genes in wheat (Triticum aestivum L.) by Jiabei He, Jiabei He, Baoyue Cui, Baoyue Cui, Pingzeng Liu, Pingzeng Liu, Xianyong Meng, Xianyong Meng, Jun Yan, Jun Yan

“…Among the various machine learning models, the random forest algorithm performed best in identifying drought stress-responsive genes. …”
Get full text

A Power-Efficient 50 MHz-BW 76.8 dB Signal-to-Noise-and-Distortion Ratio Continuous-Time 2-2 MASH Delta-Sigma Analog-to-Digital Converter with Digital Calibration by Zhiyu Li, Xueqian Shang, Haigang Feng, Xinpeng Xing

“…In order to reduce power consumption, the loop filter adopts a feedforward structure, and the operational amplifier uses complementary differential input pairs and feedforward compensation. The pseudo-random sequence injection and Least Mean Squares (LMS) algorithm are adopted to calibrate the digital noise cancelation filter to match the analog transfer function. …”
Get full text

Design optimization of university ideological and political education system based on deep learning by Shangle Ai, Huanhuan Ding

“…The hybrid model combines the advantages of CNN in feature extraction and the ability of LSTM in processing sequence data to realize accurate analysis of IPE data. …”
Get full text

A photovoltaic power forecasting method based on the LSTM-XGBoost-EEDA-SO model by Ying Xu, Xinrong Ji, Zhengyang Zhu

“…Secondly, the power sequence is decomposed into multi-scale subsequences using Ensemble Empirical Mode Decomposition (EEMD), which are then reconstructed into low-frequency components (reflecting trend features) and high-frequency components (capturing random fluctuations) based on sample entropy. …”
Get full text

Bats of a feather: Range characteristics and wing morphology predict phylogeographic breaks in volant vertebrates by Sydney K. Decker, Kaiya L. Provost, Bryan C. Carstens

“…We estimate phylogeographic breaks using Monmonier’s maximum difference barrier algorithm and conduct a random forests analysis using the presence of a phylogeographic break as a response variable. …”
Get full text

Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

“…To deal with the complicated time and space based aspects of 6G network traffic, an AI based hybrid model is developed that combines random forest (RF), gated recurrent units (GRU), and a mechanism for paying attention is proposed. …”
Get full text

BPS spectroscopy with reinforcement learning by Federico Carta, Asa Gauntlett, Finley Griffin, Yang-Hui He

“…We analyse the performance of the RL model on random BPS quivers and show that it converges to a solution various orders of magnitude faster than a systematic brute-force scan. …”
Get full text

A novel approach to pseudorandom number generation using Hamiltonian conservative chaotic systems by Vinod Patidar, Tanu Singh

“…High-quality random number generators are required for various applications such as cryptography, secure communications, Monte Carlo simulations, and randomized algorithms. …”
Get full text

Development and Validation of a Radiomics Nomogram Based on Magnetic Resonance Imaging and Clinicoradiological Factors to Predict HCC TACE Refractoriness by Dong Y, Hu J, Meng X, Yang B, Peng C, Zhao W

“…Relevant indices of TACE refractoriness were selected. ML algorithms, including a support vector machine, random forest, logistic regression and adaptive boosting, were used to construct the radiomics, clinical prediction, and combined models. …”
Get full text

Prediction of induction chemotherapy efficacy in patients with locally advanced nasopharyngeal carcinoma using habitat subregions derived from multi-modal MRI radiomics by Mulan Pan, Lu Lu, Xingyu Mu, Xingyu Mu, Guanqiao Jin

“…Eleven machine learning algorithms were employed to develop radiomics models based on the CE-T1WI and T2-FS sequences, respectively. …”
Get full text

Efficient lightweight cryptographic solutions for enhancing data security in healthcare systems based on IoT by Abdul Muhammed Rasheed, Retnaswami Mathusoothana Satheesh Kumar

“…This study presents three efficient cryptographic methods: (1) a hybrid encryption algorithm that incorporates a Fibonacci sequence and a 6D hyper-chaotic system to improve confusion and diffusion; (2) hybrid lightweight encryption that utilizes logistic parity-based chaotic maps for secure data transformation; and (3) combined transformation and expansion (CTE)-based lightweight cryptography that employs dynamic chaotic systems for strong encryption. …”
Get full text

Multiparametric MRI-based radiomics for preoperative prediction of parametrial invasion in early-stage cervical cancer by Chongshuang Yang, Man Li, Xin Yi, Lin Wang, Guangxian Kuang, Chunfang Zhang, Benyong Yao, Zhihong Qin, Tianliang Shi, Qiang Jiang

“…Feature selection was performed using the correlation coefficient, recursive feature cancellation, and the least absolute shrinkage and selection operator algorithm. Radiomics models based on single-sequence, dual-sequence, and multi-sequence combinations were then constructed. …”
Get full text

Convergence of root ectomycorrhizal fungal communities across Pinaceae developmental stages in temperate forests in northeastern China by Dongxue Zhao, Yulian Wei, Ting Cao, Yiwei Yuan, Jiarui Yu, Zhen Bai, Haisheng Yuan

“…As Pinaceae matured, EMF alpha diversity notably increased, while their Bray-Curtis dissimilarity significantly decreased. A random forest algorithm identified stage-specific taxa, marking the age-related transition from structural divergence to similarity in root EMF communities. …”
Get full text