ISMAC: An Intelligent System for Customized Clinical Case Management and Analysis by Mingyu You, Chong Chen, Guo-Zheng Li, Shi-Xing Yan, Sheng Sun, Xue-Qiang Zeng, Qing-Ce Zhao, Liao-Yu Xu, Su-Ying Huang

“…Varying data analysis and mining methods, grouped as Basic Analysis, Association Rule, Feature Reduction, Cluster, Pattern Classification, and Pattern Prediction, are implemented in the system. With a flexible dataset retrieval mechanism, ISMAC is a powerful and convenient system for clinical case analysis and clinical knowledge discovery.…”
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An Adaptive Scalable Data Pipeline for Multiclass Attack Classification in Large-Scale IoT Networks by Selvam Saravanan, Uma Maheswari Balasubramanian

“…The proposed approach is evaluated with the latest dataset, IoT23, which consists of benign and several attack instances from various IoT devices. …”
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Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis by Zheng Gao, Ting Jiang, Mingming Zhang, Hao Wu, Ming Tang

“…Additionally, we explore the application of this system for sentiment analysis using the IMDb movie review dataset. By encoding semantically similar symbols to adjacent frequencies, the system’s noise tolerance is effectively improved, facilitating accurate sentiment analysis. …”
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Temporomandibular Disorders Related to Stress and HPA-Axis Regulation by Kordian Staniszewski, Henning Lygre, Ersilia Bifulco, Siv Kvinnsland, Lisa Willassen, Espen Helgeland, Trond Berge, Annika Rosén

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FastContext: A tool for identification of adapters and other sequence patterns in next generation sequencing (NGS) data by E. Viesná, V. Fishman

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Improvement of Hypertension after Parathyroidectomy of Patients Suffering from Primary Hyperparathyroidism by P. D. Broulik, A. Brouliková, S. Adámek, P. Libanský, J. Tvrdoň, K. Broulikova, J. Kubinyi

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AFF-LightNet: A Lightweight Ship Detection Architecture Based on Attentional Feature Fusion by Yingxiu Yuan, Xiaoyan Yu, Xianwei Rong, Xiaozhou Wang

“…We conduct extensive experiments on the publicly available dataset SeaShips and compare it with existing methods. …”
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Influence of Inlet Angle of Guide Vane on Hydraulic Performance of an Axial Flow Pump Based on CFD by Lei Xu, Dongtao Ji, Wei Shi, Bo Xu, Weigang Lu, Linguang Lu

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Shadi Park Renovation with Social Development Emphasis: A Case Study Halabja City, Iraq by Mihraban Othman Mustafa, Masoumeh Faraji, Zaniar Jamal Salih, Muhammed Saeed Rasheed

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Reliability and Validity of the Y-balance Test in Young Adults with Chronic Low Back Pain by Yousef Alshehre, Khalid Alkhathami, Kelli Brizzolara, Mark Weber, Sharon Wang-Price

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Plasma Glycosaminoglycans: A new Promising tool for Assessment of Non-Metastatic Renal Cell Carcinoma Patients Following Nephrectomy by Awais ALi, Abdelkarem Omneya, Kashif Adil

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FE-YOLO: An Efficient Deep Learning Model Based on Feature-Enhanced YOLOv7 for Microalgae Identification and Detection by Gege Ding, Yuhang Shi, Zhenquan Liu, Yanjuan Wang, Zhixuan Yao, Dan Zhou, Xuexiu Zhu, Yiqin Li

“…Finally, we captured and constructed a microalgae dataset containing 6300 images of seven species of microalgae, addressing the issue of a lack of microalgae cell datasets. …”
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Alterations of amino acids in older adults with Alzheimer’s Disease and Vascular Dementia by Xin Ma, Xin-Meng Wang, Guo-Zhang Tang, Yi Wang, Xue‑Chun Liu, Shuai-Deng Wang, Peng Peng, Xiu-Hong Qi, Xin-Ya Qin, Yue‑Ju Wang, Chen-Wei Wang, Jiang-Ning Zhou

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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

“…The study encompasses the development of predictive models using a comprehensive dataset of experimental observations. The machine learning technique, support vector regression is trained and evaluated to assess their accuracy and reliability in predicting bearing response. …”
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Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine by Yun Deng, Lifan Xiao, Yuanyuan Shi

“…This study uses 206 hyperspectral soil samples from the state-owned Yachang and Huangmian Forest Farms in Guangxi, using the SPXY algorithm to partition the dataset in a 4:1 ratio, to provide an effective spectral data preprocessing method and a novel SOM content prediction model for the study area and similar regions. …”
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Cernunnos/XLF Deficiency: A Syndromic Primary Immunodeficiency by Funda Erol Çipe, Cigdem Aydogmus, Arzu Babayigit Hocaoglu, Merve Kilic, Gul Demet Kaya, Elif Yilmaz Gulec

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EMFF-Net: Edge-Enhancement Multi-Scale Feature Fusion Network by Xuhui Guan, Jiwang Zhou, Jian Chen, Xiaodan Xu, Yizhang Jiang, Kaijian Xia

“…Extensive qualitative and quantitative experiments on five benchmark datasets and two private datasets demonstrate that the EMFF-Net proposed in this paper significantly improves segmentation accuracy across six metrics. …”
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Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation by Oezdemir Cetin, Berkay Canel, Gamze Dogali, Unal Sakoglu

“…To address the issue of insufficient training data, data augmentation techniques have been implemented, enhancing the diversity and volume of the training set. The dataset for this study was created from MRI data of 20 subjects. …”
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Development of an Ensemble Intelligent Model for Assessing the Strength of Cemented Paste Backfill by Yuantian Sun, Guichen Li, Junfei Zhang, Junbo Sun, Jiahui Xu

“…The BSVM is then trained on a dataset collected from the experimental results. To explain the importance of each input variable on the UCS of CPB, the variable importance is obtained using a sensitivity study with the BSVM as the objective function. …”
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Classification of Silicon (Si) Wafer Material Defects in Semiconductor Choosers using a Deep Learning ShuffleNet-v2-CNN Model by Rajesh Doss, Jayabrabu Ramakrishnan, S. Kavitha, S. Ramkumar, G. Charlyn Pushpa Latha, Kiran Ramaswamy

“…This proposed model identifies and classifies the defects based on the wafer map images from the WM-811K dataset. The proposed model is composed of a pretrained deep transfer learning model called ShuffleNet-v2 with convolutional neural network (CNN) architecture. …”
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