Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…This study aimed to identify potential therapeutic targets for the treatment of AD using comprehensive bioinformatics methods and machine learning algorithms. By integrating differential gene expression analysis, weighted gene co-expression network analysis, Mfuzz clustering, single-cell RNA sequencing, and machine learning algorithms including LASSO regression, SVM-RFE, and random forest, five hub genes related to AD, including PLCB1, NDUFAB1, KRAS, ATP2A2, and CALM3 were identified. …”
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Adaptive Image Denoising Method Based on Diffusion Equation and Deep Learning by Shaobin Ma, Lan Li, Chengwen Zhang

“…Finally, the algorithm is compared with other excellent denoising algorithms. …”
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Multi-Objective Optimal Design of Dropping Shock of Series Cushioning Packaging System by Yang Xue, Wei-Sheng Song, Hong-Tao Miao, Jing Wang, Yu Li

“…The performances of the solution sets obtained by the evolutionary algorithms are studied based on several performance indicators. …”
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Classification Performance Comparison of BERT and IndoBERT on SelfReport of COVID-19 Status on Social Media by Irwan Budiman, Mohammad Reza Faisal, Astina Faridhah, Andi Farmadi, Muhammad Itqan Mazdadi, Triando Hamonangan Saragih, Friska Abadi

“…The classification of social media messages can be achieved through the application of classification algorithms. Many deep learning-based algorithms, such as Convolutional Neural Networks (CNN) or Long Short-Term Memory (LSTM), have been used for text classification. …”
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Rough Set Approach toward Data Modelling and User Knowledge for Extracting Insights by Xiaoqun Liao, Shah Nazir, Junxin Shen, Bingliang Shen, Sulaiman Khan

“…The validity of the proposed classification algorithms is tested using different performance metrics such as F-score, precision, accuracy, recall, specificity, and misclassification rates. …”
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Emergency Trajectory Structure for UAVs by Maëva Ongale-Obeyi, Damien Goubinat, Daniel Delahaye, Pierre-Loïc Garoche

“…It is important to note that the algorithms chosen address only a simplified version of the problem. …”
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Early Stroke Prediction Methods for Prevention of Strokes by Mandeep Kaur, Sachin R. Sakhare, Kirti Wanjale, Farzana Akter

“…The cascaded prediction algorithms are time-consuming in producing the results and cannot work on the raw data and without making use of the properties of EEG. …”
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Diagnosis of Cognitive and Mental Disorders: A New Approach Based on Spectral–Spatiotemporal Analysis and Local Graph Structures of Electroencephalogram Signals by Arezoo Sanati Fahandari, Sara Moshiryan, Ateke Goshvarpour

“…Methods: Our investigation will utilize algorithms based on Granger causality and local graph structures to improve classification accuracy. …”
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Improving ICP-Based Scanning Sonar Image Matching Performance Through Height Estimation of Feature Point Using Shaded Area by Gwonsoo Lee, Sukmin Yoon, Yeongjun Lee, Jihong Lee

“…We propose integrating these two approaches and validate the proposed algorithm through simulations, experimental basin tests, and real-world data collection, demonstrating its effectiveness.…”
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Decision Tree Ensembles to Predict Coronavirus Disease 2019 Infection: A Comparative Study by Amir Ahmad, Ourooj Safi, Sharaf Malebary, Sami Alesawi, Entisar Alkayal

“…The machine learning algorithms were applied on a Covid-19 dataset based on commonly taken laboratory tests to predict Covid-19 positive cases. …”
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Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

“…Purpose – This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper is to pre-process a relatively large data of NO2 from Internet of Thing (IoT) sensors with time-corresponding weather and traffic data and to use the data to develop NO2 prediction models using BA-GS-LSSVM and popular standalone algorithms to allow for a fair comparison. …”
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Calibrating Path Choices and Train Capacities for Urban Rail Transit Simulation Models Using Smart Card and Train Movement Data by Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos, Jinhua Zhao

“…The calibration is formulated as an optimization problem with a black-box objective function. Seven algorithms from four branches of SBO solving methods are evaluated. …”
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Comparative Analysis of Neural-Network and Fuzzy Auto-Tuning Sliding Mode Controls for Overhead Cranes under Payload and Cable Variations by Muhammad A. Shehu, Ai-jun Li, Bing Huang, Yu Wang, Bojian Liu

“…Control applications were conducted, and results based on graphical, integral absolute error (IAE), and integral time absolute error (ITAE) proved the effectiveness of the proposed algorithms. It was observed that the response of the controller with back-propagation-trained neural-network was more effective relative to that of the fuzzy algorithm.…”
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Exploiting Multiple Channels for Low Latency and Semireliable Broadcasting in Cognitive Wireless Sensor Networks by Tae-Sung Kim, Sok-Hyong Kim, Bo-Kyum Kim, Young-Yong Kim

“…Channel assignment algorithms can be applied in cognitive radio enabled networks which performs dynamic channel configuration for utilizing multiple channels. …”
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Intelligent Segment Routing: Toward Load Balancing with Limited Control Overheads by Shu Yang, Ruiyu Chen, Laizhong Cui, Xiaolei Chang

“…Finally, we evaluate the IRTE in different real-world topologies, and the results show that the IRTE outperforms traditional algorithms, e.g., the maximum bandwidth is 24.6% lower than that of traditional algorithms when evaluating on BellCanada topology.…”
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Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…We also analyze the effect of different graph embedding algorithms and prior knowledge on algorithmic results. …”
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Teaching a neural network modeling socio-economic development of the region by S. V. Romanchukov, O. G. Berestneva, L. A. Petrova

“…At the same time, however, it should be noted that the resources of an individual research team may be (and most likely will be) insufficient to create their own software solution for the implementation of machine learning algorithms from scratch. The use of third-party cloud-based software platforms (primarily IBM and Google infrastructures) allows to bypass the problem of the research team’s lack of expensive material and technical base, however they impose a number of limitations dictated by the requirements of the existing machine learning algorithms and the specific architecture provided platforms This puts the research team in front of the need to prepare the accumulated data set for processing: reducing the dimension, checking the data for compliance with the platform requirements and eliminating potential problem areas: “data leaks”, “learning distortions” and others. …”
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Safety Assessment and a Parametric Study of Forward Collision-Avoidance Assist Based on Real-World Crash Simulations by MohammadReza Seyedi, MohammadReza Koloushani, Sungmoon Jung, Arda Vanli

“…The results also showed that the available AEB algorithms were more effective for the average speed equal to or less than 80 kmph. …”
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Hierarchical Spatial Clustering in Multihop Wireless Sensor Networks by Zhidan Liu, Wei Xing, Yongchao Wang, Dongming Lu

“…With such metric, we propose a clustering algorithm named as HSC to group the most similar sensor nodes in a distributed way. …”
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Prediction of the remaining useful life of a milling machine using machine learning by Abbas Al-Refaie, Majd Al-atrash, Natalija Lepkova

“…A web application for maintenance was finally developed with several ML algorithms at the evaluation stage. Maintenance engineers can utilize the developed smart web application to monitor the machine's health state and predict failure occurrence. …”
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