A New Multidimensional Computerized Testing Approach: On-the-Fly Assembled Multistage Adaptive Testing Based on Multidimensional Item Response Theory by Jingwen Li, Jianan Sun, Mingyu Shao, Yinghui Lai, Chen Chen

“…Multidimensional item response theory (MIRT), a branch of mathematical and statistical latent variable modeling research, has an important position in the international testing field. …”
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Structure-guided decoupled contrastive framework for partial multi-view incomplete multi-label classification by Linqian Yang, Tao Zhuang, Xing Jin, Tianyang Cao, Xiyin Wu

“…Additionally, the SGDC integrates a structure-guided contrastive (SGC) framework that performs dynamic semantic alignment in consistent feature spaces through global structural modeling, effectively implementing structure-conscious representation learning guided by the multi-view consensus principle. …”
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From Hospital to Home: PT Griyakami's Marketing Strategy to Reach Home Care Customers by Neng Ima Rahmayanti, Eko Wulandari, Nur Hayati

“…Based on these findings, this study recommends that PT Griyakami implement a data-driven, multichannel marketing strategy, including: (1) development of a digital platform integrated with HMIS and registration features; (2) partnerships with midwives and BPJS to expand outreach; (3) flexible pricing models based on patient segmentation; and (4) structured performance monitoring using KPIs and customer satisfaction surveys. …”
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Analysis of isolated phase windings and permanent magnet assists high energy efficient hybrid‐reluctance motor for electric vehicle by Sundaramoorthy Prabhu, Arun Vijayakumar, Albert Alexander Stonier, Geno Peter, Sonam Dorji, Vivekananda Ganji

“…Abstract This article describes the electromagnetic analysis of high efficient hybrid motor, which comprises the salient features of switched reluctance motor (SRM) and spoke‐type brushless DC motor. …”
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Efficient Real-Time Pathfinding for Visually Impaired Individuals by Tadeh Ghahremanians, Hossein Mahvash Mohammadi

“…In this research, deep convolutional neural networks are employed to perform semantic segmentation of camera images, thereby facilitating the identification of patterns across the image’s feature space. …”
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Inception–Attention–BiLSTM Hybrid Network: A Novel Approach for Shear Wave Velocity Prediction Utilizing Well Logging by Jiayi Li, Yaoting Lin, Zhixian Gui, Peng Wang

“…While empirical formulas and theoretical rock physics models offer solutions, they are often limited by geological complexity, high cost, and computational inefficiency. …”
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Colonial bacterial memetic algorithm and its application on a darts playing robot by Szilárd Kovács, Csaba Budai, János Botzheim

“…This combination of natural and artificial evolutionary elements results in a robust algorithm capable of handling complex challenges in robotics, such as constraints, multiple objectives, large search spaces, and complex models, while delivering fast and accurate solutions. …”
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Frame topology fusion-based hierarchical graph convolution for automatic assessment of physical rehabilitation exercises by Shaohui Zhang, Qiuying Han, Peng Wang, Junjie Li

“…This method aims to provide a more precise assessment of rehabilitation movement quality by effectively modeling both spatial and temporal features. First, this method combines nearby and distant keypoints to construct a fused topology structure for obtaining the enhanced motion representation. …”
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Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations by Constantinos Halkiopoulos, Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou

“…Combining neuroimaging data with behavioral and cognitive features improves classification performance. However, ethical challenges, such as data privacy and bias, remain significant concerns. …”
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Fast Recognition of Table Eggs from Different Farming Systems Using Physical Traits and Multi-layer Perceptron by MC Huang, Q Lin, H Cai, H Ni

“…The Multi-layer Perceptron Neural Network achieved the best classification performance with an accuracy of 0.94167, a F1 score of 0.94118. …”
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SNMatch: An Unsupervised Method for Column Semantic-Type Detection Based on Siamese Network by Tiezheng Nie, Hanyu Mao, Aolin Liu, Xuliang Wang, Derong Shen, Yue Kou

“…Existing methods often rely on supervised learning models, which require extensive labeled data. In this paper, we propose SNMatch, an unsupervised approach based on a Siamese network for detecting column semantic types without labeled training data. …”
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Impact of ground motion characteristics on the seismic fragility of circular tunnels by Zhong-Kai Huang, Dong-Mei Zhang, Wu-Yu Zhang, Yong-Bo Li

“…The seismic performance of tunnel structure can be examined by fragility analysis, which determines the probability that demand will exceed capacity for a given hazard intensity. …”
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Asymmetric Network Based on CNN and Attention Mechanisms for Thyroid Nodule Segmentation by Zhiheng Zhang, Lin Li, Cheng Zhao, Peng Ren, Ran Zhang

“…Experimental results on a public thyroid nodule ultrasound dataset demonstrate that the proposed method significantly outperforms existing models’ overall segmentation performance, achieving a Dice Similarity Coefficient (DSC) of 0.8332 and an Intersection over Union (IOU) of 0.7473 on the test set. …”
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Cloud software code generation via knowledge graphs and multi-modal learning by Fanlong Zhang, Huanming Chen, Quan Chen, Jianqi Liu

“…By applying contrastive loss and cross-attention mechanisms, our method effectively fuses diverse modalities to strengthen code generation performance. Experiments on two processed open-source datasets demonstrate that our method, without relying on extensive pre-training, achieves superior results compared to existing pretrained models across BLEU-4, CodeBLEU, and ROUGE-L metrics, paving the way for more efficient and intelligent cloud-native software development.…”
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An experimental study of U-net variants on liver segmentation from CT scans by Halder Akash, Sau Arup, Majumder Surya, Kaplun Dmitrii, Sarkar Ram

“…This study investigates the performance of ten well-known U-Net models, including Vanilla U-Net, Attention U-Net, V-Net, U-Net 3+, R2U-Net, U2{{\rm{U}}}^{2}-Net, U-Net++, Res U-Net, Swin-U-Net, and Trans-U-Net. …”
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GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

“…The experimental results show that OCSSA has significant improvements in convergence accuracy and speed, and performs excellently. Compared with other fault diagnosis models, the accuracy of the OCSSA-LSTM fault diagnosis model can reach up to 97.5%, and it can also accurately identify actual GIS operation and maintenance data.…”
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An Efficient and Automated Classification System for Rocks Based on Visually Explainable Deep Learning by Shan Lin, Quanke Hu, Hongwei Guo, Miao Dong, Kaiyang Zhao, Hong Zheng, Zhijun Liu

“…These models also require manual feature extraction, increasing training complexity. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…YOLOv4 is a widely used OD model with a backbone for image feature extraction and a prediction layer. …”
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Density Classification with Non-Unitary Quantum Cellular Automata by Elisabeth Wagner, Federico Dell’Anna, Ramil Nigmatullin, Gavin K. Brennen

“…The second is a new quantum model that is designed to demonstrate additional quantum features and is restricted to only two-body interactions. …”
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A novel fusion architecture for detecting Parkinson’s Disease using semi-supervised speech embeddings by Tariq Adnan, Abdelrahman Abdelkader, Zipei Liu, Ekram Hossain, Sooyong Park, Md Saiful Islam, Ehsan Hoque

“…We used deep learning embeddings from Wav2Vec 2.0, WavLM, and ImageBind to capture speech dynamics indicative of PD. Our novel fusion model for PD classification aligns different speech embeddings into a cohesive feature space, outperforming baseline alternatives. …”
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