The analysis of interactive furniture design system based on artificial intelligence by Xiaohong Jiang

“…This enhances the AI-assisted design system’s ability to generate diverse design solutions while avoiding the limitations of traditional systems. Compared to other deep learning architectures (e.g., encoder-decoder networks), GAN excels in generating realistic and creative furniture design solutions. …”
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Unsupervised Context-Linking Retriever for Question Answering on Long Narrative Books by Mohammad A. Ateeq, Sabrina Tiun, Hamed Abdelhaq, Wandeep Kaur

“…This paper introduces the Unsupervised Context Linking Retriever (UCLR), a novel approach that efficiently retrieves relevant passages from long narrative texts without requiring labeled (question, passage) pairs. UCLR uses an encoder-decoder model to generate synthetic (question, answer) pairs, measuring the relevance of passages by comparing the error between the generated pair and the reference pair, which serves as a synthetic training signal. …”
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Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…Additionally, a fixed-point quantization study confirms that a 16-bit representation of reliability values introduces negligible error, offering further scope for area and power optimization. Comparative analysis with existing turbo decoder designs shows that the proposed RCODD-based architecture is uniquely positioned to serve low-power, high-reliability applications such as satellite telecomm and systems, while remaining scalable to higher-throughput needs.…”
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TriNet: A Hybrid Feature Integration Approach for Motor Imagery Classification in Brain-Computer Interface by Hafza Faiza Abbasi, Muhammad Ahmed Abbasi, Shen Jianbo, Xiang Liping, Xiaojun Yu

“…From healthcare to innovative computer gaming, integrating BCI for intelligent control has become an emergent scope. However, optimizing motor imagery (MI) classification in non-invasive BCI remains a significant challenge due to the poor quality of the acquired signal. …”
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Cross-Domain Carotid Artery Segmentation Using Folding Fan ResNet and Quadratic Mapping Loss by Zhaozheng Chen, Zhiyin Liu, Bernard Chiu

“…QML addresses arterial mislocalization by deferring the optimization of incorrectly localized boundaries while prioritizing adjustments to correctly segmented regions. …”
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On Linear Coding Schemes for Stabilizing LTI Control with Multiple Sensors by Anna N. Kim

“…For a first-order ARMA modeled plant with Gaussian statistics, when there are two sensors observing the plant, nonlinear encoding is shown to result in smaller cost at time instant T = 1 compared to the linear schemes, if transmissions are carried out over parallel Gaussian independent channels. …”
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A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…This limitation results in insufficient collaborative optimization between local details and macroscopic structures during denoising, further reducing the noise suppression accuracy. …”
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Enhancing medical response efficiency in real-time large crowd environments via smart coverage and deep learning for stable ecological health monitoring by Asma A. Alhashmi, Ghada Moh. Samir Elhessewi, Mukhtar Ghaleb, Nazir Ahmad, Nojood O. Aljehane, Tareq M. Alkhaldi, Hamad Almansour, Samah Al Zanin

“…The comparison analysis of the MRELC-SCHO approach revealed a superior accuracy value of 98.56% compared to existing models.…”
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Ellipsoidal <i>K</i>-Means: An Automatic Clustering Approach for Non-Uniform Data Distributions by Alaa E. Abdel-Hakim, Abdel-Monem M. Ibrahim, Kheir Eddine Bouazza, Wael Deabes, Abdel-Rahman Hedar

“…Extensive experiments conducted on UCI datasets demonstrated SAELLC’s superior performance compared to six well-known clustering algorithms. The results highlight its remarkable ability to handle diverse data distributions and automatically identify the optimal number of clusters, making it a robust choice for advanced clustering analysis.…”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…When comparing SGTR and SGTR+, our model performs better in terms of R@K, mR@20, and parameter count, while SGTR and SGTR+ exhibit better results in mR@50 and mR@100. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…GA is employed as the optimal feature search strategy, where the initial feature subset is binary encoded (1 for selected feature, 0 for unselected feature), and an initial population is randomly generated. …”
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A survey on deep learning based joint source-channel coding by Tianjie MU, Xiaohui CHEN, Yiyun WANG, Lupeng MA, Dong LIU, Jing ZHOU, Wenyi ZHANG

“…Classical information theory shows that separate source-channel coding is asymptotically optimal over a point-to-point channel.As modern communication systems are becoming more sensitive to delays and bandwidth,it becomes difficult to adopt the assumption that such separate designs have unlimited computing power for encoding and decoding.Compared to joint source-channel coding,separate coding has proven to be sub-optimal when the bandwidth is limited.However,conventional joint source-channel coding schemes require complicated design.In contrast,data-driven deep learning brings new designing ideas into the paradigm.A summary of relevant research results was provided,which will help to clarify the way in which deep learning methods solve the joint source-channel coding problem and to provide an overviewof new research directions.Source compression schemes and end-to-end communication system models were firstly introduced,both based on deep learning,then two kinds of joint coding designs under different types of source,and potential problems of joint source-channel coding based on deep learning and possible future research directions were introduced.…”
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Designing an innovative closed-loop supply chain network considering economic and environmental aspects by Maryam Rahmaty

“…For this purpose, a priority-based encoding is presented, and the Pareto front resulting from solving different problems is compared. …”
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Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Usin... by Yan Zhuang, Junyan Zhang, Xiuxing Li, Chao Liu, Yue Yu, Wei Dong, Kunlun He

“…Its performance was compared against robustly optimized BERT pretraining approach, extreme language network, and various BERT-based fine-tuning pipelines. …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…This framework synergistically integrates an optimized bidirectional hierarchical gated recurrent unit (BiHGRU), a Transformer encoder, and a novel Greenness and Water Content Composite Index, with critical parameters optimized by particle swarm optimization (PSO). …”
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ViTAU: Facial paralysis recognition and analysis based on vision transformer and facial action units by Jia GAO, Wenhao CAI, Junli ZHAO, Fuqing DUAN

“…To accurately determine the specific affected regions, we use the pixel2style2pixel (pSp) encoder and the StyleGAN2 generator to encode and decode images and extract feature maps that represent facial characteristics. …”
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Adjusted imbalance ratio leads to effective AI-based drug discovery against infectious disease by Ons Masmoudi, Afef Abdelkrim, Emna Harigua-Souiai

“…To address this, we implemented a K-ratio random undersampling approach (K-RUS) to determine optimal imbalance ratios (IRs), and compared them to conventional resampling approaches. …”
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Engineering Quantum Error Correction Codes Using Evolutionary Algorithms by Mark A. Webster, Dan E. Browne

“…We perform a search for optimal distance Calderbank&#x2013;Steane&#x2013;Shor codes and compare their distance to the best known codes. …”
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International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The study meticulously constructed and trained the TF-CNN-BiLSTM model using TensorFlow with the Adam optimizer and mean squared error loss function. The training process was optimized with learning rate reduction and early stopping callbacks to prevent overfitting. …”

Solving the traffic signaling problem using the iterated local search metaheuristic by Elvir Misini, Uran Lajçi, Kadri Sylejmani, Atlantik Limani, Fjolla Gashi, Lavdim Kurtaj, Arben Ahmeti, Erzen Krasniqi

“…Abstract Traffic lights are pivotal for urban mobility in large cities, with optimal scheduling at intersections being a complex task. …”
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