Multi-objective Optimal Allocation of Renewable Energy Distributed Generations and Shunt Capacitors in Radial Distribution System using Corona Virus Herd Optimization by Oluwaseyi Wasiu Adebiyi, Muniru Olajide Okelola, Sunday Adeleke Salimon

“…Furthermore, the highest level of greenhouse gas emission reduction was achieved (says 99.69%) when high priority was placed on the reduction in TGHGe; this shows the significant impact of renewable energy in the distribution system. …”
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FXLMS with Multiple Error Switching for Active Noise-Cancelling Casings by Krzysztof MAZUR, Stanisław WRONA, Anna CHRAPOŃSKA, Jarosław RZEPECKI, Marek PAWEŁCZYK

“…Passive noise reduction methods require thick and heavy barriers to be effective for low frequencies and those clasical ones are thus not suitable for reduction of low frequency noise generated by devices. …”
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A novel anthropometric method to accurately evaluate tissue deformation by Chongyang Ye, Xiaolu Li, Haiyan Song, Yu Shi, Ruixin Liang, Jun Zhang, Ka Po Lee, Zhaolong Chen, Beibei Zhou, Raymond Kai-Yu Tong, Kit-Lun Yick, Sun-Pui Ng, Joanne Yip

“…Moreover, a novel anthropometric method based on image recognition algorithms that systematically measures and evaluates tissue deformation while minimizing the impact of the effects of motion is proposed. …”
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Representation Learning of Multi-Spectral Earth Observation Time Series and Evaluation for Crop Type Classification by Andrea González-Ramírez, Clement Atzberger, Deni Torres-Roman, Josué López

“…To develop accurate solutions for RS-based applications, often supervised shallow/deep learning algorithms are used. However, such approaches usually require fixed-length inputs and large labeled datasets. …”
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Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study by Bingtian Dong, Ruiling He, Shenghong Ju, Yuping Chen, Ivica Grgurevic, Jianzhong Ma, Ying Guo, Huizhen Fan, Qiang Yan, Chuan Liu, Huixiong Xu, Anita Madir, Kristian Podrug, Jia Wang, Linxue Qian, Zhengzi Geng, Shanghao Liu, Tao Ren, Guo Zhang, Kun Wang, Meiqin Su, Fei Chen, Sumei Ma, Liting Zhang, Zhaowei Tong, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Hui Liu, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Li Bian, Ping An, Xin Zhang, Shaoting Zhang, Jinhua Shao, Xiangman Zhang, Wei Rao, Chaoxue Zhang, Christoph Frank Dietrich, Won Kim, Xiaolong Qi

“…Shapley Additive exPlanations method was used to interpret the model predictions. Results We analyzed data from 502 patients with compensated cirrhosis who underwent EGD screening. …”
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adm: An R package for constructing abundance‐based species distribution models by Admir Cesar deOliveira Junior, Santiago José Elías Velazco

“…Here, we present the adm R package developed to support the construction of ADM, including data preparation, model fitting, prediction and model exploration. This package offers several modelling approaches (i.e. algorithms) that can be fine‐tuned and customized. …”
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Yield Response of Different Rice Ecotypes to Meteorological, Agro-Chemical, and Soil Physiographic Factors for Interpretable Precision Agriculture Using Extreme Gradient Boosting a... by Md. Sabbir Ahmed, Md. Tasin Tazwar, Haseen Khan, Swadhin Roy, Junaed Iqbal, Md. Golam Rabiul Alam, Md. Rafiul Hassan, Mohammad Mehedi Hassan

“…Moreover, this study found a different set of those factors with respect to the yield response of different rice ecotypes. Machine learning algorithms named Extreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) have been used for predicting the yield response. …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…Despite the large number of negative users, the frequency of connections between active users was significantly higher than between negative users. Multiple algorithms were utilized for emotional analysis and prediction. …”
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Understanding the environmental health implications of tourism on carbon emissions in China by Jinhua Shao, Sheng Fang, Meiling Zhao, Wanxin Qian, Cai Wang

“…Studying the impact of China’s tourism industry on carbon emissions is of great significance in scientifically formulating emission reduction policies and helping China to realize its carbon reduction goals. …”
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Optimization Model for Safeguarding Vulnerable Components in Integrated Energy Systems Based on Weighted Betweenness by ZHANG Chenwei, WANG Ying, LI Yaping, ZHANG Kaifeng

“…Then, the lower-level model is solved using a local linearization technique, and a “genetic-mixed integer linear programming” algorithm is proposed for solving the model with high precision and efficiency. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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An adaptive non-equidistant grey model with four parameters and its applications in deformation monitoring by Shuang Yang, Changchun Li, Jiao Fu, Huanqin Ma

“…Second, the particle swarm optimization algorithm is used to optimize the background value so that it can be adaptively adjusted according to the sequence characteristics as well as to obtain a mutually matching model structure based on the integral theory. …”
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Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

“…However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors.The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers.This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. …”
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Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

“…Time series and state estimation are the Supervised Learning techniques executed for charge diagnostics and State of Charge (SOC) predictions. The results show remarkable performance metrics of the Transformer models, achieving over 94% accuracy in Model evaluation compared to traditional Deep Learning algorithms.…”
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Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning by Si Xie, Mo Wu, Yu Shang, Wenbin Tuo, Jun Wang, Qinzhen Cai, Chunhui Yuan, Cong Yao, Yun Xiang

“…Clinical data were selected through Lasso regression analysis, followed by the application of eight machine learning algorithms to develop early warning model. The accuracy of the model was assessed using validation and prospective cohort. …”
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Evaluating Leaf Water Potential of Maize Through Multi-Cultivar Dehydration Experiments and Segmentation Thresholding by Shuanghui Zhao, Yanqun Zhang, Pancen Feng, Xinlong Hu, Yan Mo, Hao Li, Jiusheng Li

“…In contrast, there was little difference in the predictive effectiveness of the models constructed for each cultivar and all three cultivars. …”
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MOIRA-UNIMORE Bearing Data Set for Independent Cart Systems by Abdul Jabbar, Marco Cocconcelli, Gianluca D’Elia, Davide Borghi, Luca Capelli, Jacopo Cavalaglio Camargo Molano, Matteo Strozzi, Riccardo Rubini

“…The primary objective is to advance research in machine health monitoring, predictive maintenance, and stochastic modeling by providing the first data set of its kind. …”
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A novel molecular classification system based on the molecular feature score identifies patients sensitive to immune therapy and target therapy by Yang Li, Yang Li, Yinan Ding, Yinan Ding, Jinghao Wang, Xiaoxia Wu, Xiaoxia Wu, Dinghu Zhang, Dinghu Zhang, Han Zhou, Han Zhou, Pengfei Zhang, Pengfei Zhang, Guoliang Shao, Guoliang Shao

“…Subsequently, machine learning algorithms were used to predict the classifications and prognoses. …”
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Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed‐Cohort Study Based on 16,189 Participants by Cong Lai, Zhensheng Hu, Jintao Hu, Zhuohang Li, Lin Li, Mimi Liu, Zhikai Wu, Yi Zhou, Cheng Liu, Kewei Xu

“…Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. …”
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Advancing sustainability: The impact of emerging technologies in agriculture by Ashoka Gamage, Ruchira Gangahagedara, Shyamantha Subasinghe, Jeewan Gamage, Chamini Guruge, Sera Senaratne, Thevin Randika, Chamila Rathnayake, Zammil Hameed, Terrence Madhujith, Othmane Merah

“…The integration of data analytics and machine learning algorithms is transforming supply chain management and enhancing the capabilities of predictive analytics in the context of crop diseases. …”
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