High‑Temperature Image Pre‐Processing Based on ε‐Ga2O3 Photo‐Synapses by Yingtong Lin, Yuhan Zhu, Feng Wang, Yuchen Cai, Zhengqiao Li, Shuhui Li, Xueying Zhan, Jun He, Chao Jiang, Zhenxing Wang

“…Edge‐based neuromorphic computing with data pre‐processing can help alleviate these burdens and enhance overall system efficiency. …”
Get full text

A chaos based image encryption algorithm using Rubik’s cube and prime factorization process (CIERPF) by R. Vidhya, M. Brindha

“…From this random value, the initial vectors of Henon map is obtained and this is iterated to obtain the key sequences to be applied over the Rubik’s cube row and column confusion processes. …”
Get full text

Toolkit for providing economic and safe future of energy enterprises by Sergey Levchenko

“…It is noted that it is possible to accelerate the process of ESG-investment of energy enterprises by creating a favorable investment environment. …”
Get full text

Optimized Whole-Slide-Image H&E Stain Normalization: A Step Towards Big Data Integration in Digital Pathology by Jose L. Agraz, Carlos Agraz, Andrew A. Chen, Charles Rice, Robert S. Pozos, Sven Aelterman, Amanda Tan, Angela N. Viaene, MacLean P. Nasrallah, Parth Sharma, Caleb M. Grenko, Tahsin Kurc, Joel Saltz, Michael D. Feldman, Hamed Akbari, Russell T. Shinohara, Spyridon Bakas, Parker Wilson

“…Building on published graphical method, this research demonstrates a mathematical population or data-driven method that optimizes the dependency on the number of reference WSIs and corresponding aggregate sums, thereby increasing SCN process efficiency. This method expedites the analysis of color convergence 50-fold by using stain vector Euclidean distance analysis, slashing the requirement for reference WSIs by more than half. …”
Get full text

Approximate Symmetries and Conservation Laws for Mechanical Systems Described by Mixed Derivative Perturbed PDEs by Shamaoon A., Agarwal P., Cesarano C., Jain S.

“…In response to this challenge, we embarked on the rectification process. By integrating these additional terms into our model, we could modify the conserved vectors, deriving new modified conserved vectors. …”
Get full text

Short-Term Load Forecasting Based on Feature Selection and Combination Model by Yusong XU, Shanhua ZOU, Xianling LU

Get full text

Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Along with these methods, due to the capability to process data with highly nonlinear dependences between features, machine learning methods such as the k-nearest neighbor method, and the support vector machine (SVM) method, are widely used in related areas. …”
Get full text

Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…Biogas production through anaerobic digestion (AD) of industrial organic waste and wastewater offers a sustainable method for energy recovery. However, since process efficiency heavily relies on operational factors, continuous monitoring of the AD process and the implementation of necessary operational strategies are crucial. …”
Get full text

Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Dark fermentation process from low-cost renewable substrates for simultaneous wastewater treatment and hydrogen production (H2) is suitable due to economic viability and environmental sustainability. …”
Get full text

Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…Spent fuel reprocessing is an important nuclear energy process which aimed at recovering resources and managing radioactive materials to control potential hazards. …”

Design of a Machine Learning-Based Platform for Currency Market Prediction: A Fundamental Design Model by Kevin Gordillo-Orjuela, Paulo Alonso Gaona-García, Carlos Enrique Montenegro-Marín

Get full text

CLASSIFICATION AND PREDICTION OF BENTHIC HABITAT FROM SCIENTIFIC ECHOSOUNDER DATA: APPLICATION OF MACHINE LEARNING ALGORITHMS by Baigo HAMUNA, Sri PUJIYATI, Jonson Lumban GAOL, Totok HESTIRIANOTO

“…The classification and prediction process of benthic habitats uses two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), in XLSTAT Basic+ software. …”
Get full text

Modeling and Analysis of Dynamics of Rigid–Flexible Coupled Parallel Robots by Leilei Wang, Wei Xu, Fei Guo, Hao Yan, Yunxue Wang

“…Rigid–flexible coupled robots have problems such as vibration and elastic deformation caused by the flexibility of the members during the motion process, which significantly impacts the system’s motion accuracy and dynamics performance. …”
Get full text

HashTrie:a space-efficient multiple string matching algorithm by Ping ZHANG, Yan-bing LIU, Jing YU, Jian-long TAN

“…The famous multiple string matching algorithm AC consumed huge memory when the string signatures were massive,thus unable to process high speed network traffic efficiently.To solve this problem,a space-efficient multiple string matching algorithm-HashTrie was proposed.This algorithm adopted recursive hash function to store the patterns in bit-vectors in place of the state transition table in order to reduce space consumption.Further more it made use of the rank operation for fast verification.Theoretic analysis shows that the space complexity of HashTrie is O(|P|),which is linear with the size of pattern set |P|and is independent of the alphabetsize σ.The space complexity is superior to the complexity O(|P|σlog|P|)of AC.Experiments on synthetic datasets and real-world datasets(such as Snort,ClamAV and URL)show that HashTrie saves up to 99.6% storage cost compared with AC,and in the meanwhile it runs at a matching speed that is about half of AC.HashTrie is a space-efficient multiple string matching algorithm that is appropriate to search large scale pattern strings with short lengths.…”
Get full text

Research of the Combined Trajectory Planning of Descartes Space and Joint Space by Lai Xiao, Liu Yong, Luo Wenguo, Dai Yanxia, Zeng Han

“…Through the closed loop vector method,kinematics equation is established and the space trajectory is fitted based B spline function model,the motion curve of the joint space planning and the motion curve of Descartes space planning and the motion curve of combined space planning are obtained. …”
Get full text

PENGENALAN EKSPRESI RAUT WAJAH BERBASIS JARINGAN SARAF TIRUAN BACKPROPAGATION DENGAN METODE PRINCIPAL COMPONENT ANALYSIS by Harizahayu Harizahayu

Get full text

Analytical Estimation of Induced Voltage in Rotating Electrical Machines by Marius Meiswinkel, Amir Ebrahimi, Anjali Biju

“…However, even when using FEM software, this voltage estimation is a post-process calculation based on pre-calculated flux densities or vector potentials. …”
Get full text

Research on the Prediction of Pipelines Corrosion Rate Based on GA-LSSVM by CHEN Yong-hong, SU Yong-sheng, HU Ping

“…Corrosion rate is an important characteristic parameter to reflect the corrosion dynamics process of pipeline.In order to accurately evaluate the long-term operation reliability and remaining life of pipeline, the prediction of corrosion rate is particularly important.Least squares support vector machine(LSSVM)is a method based on machine learning, which is often used in classification and prediction research.Since penalty parameters γ and kernel parameters σ2 are two important parameters of LSSVM, the value of these two parameters can only be obtained by experience in calculation, causing a great impact on the calculation results.In this paper, the genetic algorithm(GA)was used to optimize the parameters, the GA-LSSVM prediction model was built and the model was applied to the prediction of pipeline corrosion rate.Compared with the results of other prediction models, the results showed that the accuracy of GA-LSSVM model and prediction results were relatively higher, which could realize the prediction of pipeline corrosion rate.…”
Get full text

PLM-ATG: Identification of Autophagy Proteins by Integrating Protein Language Model Embeddings with PSSM-Based Features by Yangying Wang, Chunhua Wang

“…Since the autophagic process is tightly regulated by the coordination of autophagy-related proteins (ATGs), precise identification of these proteins is essential. …”
Get full text

Research on Tilt Correction Algorithms of Destorted Data Matrix Code Image by GUAN Bo-yi, DONG Jing-wei, MA Xiao-feng, XU Bo

“…This algorithm saves the time and workload of Data Matrix code in the process of image restoration.…”
Get full text