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Rule-augmented LLM framework for detecting unreasonableness in ICU 用于ICU不合理诊断的规则增强LLM框架

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-26 DOI: 10.1016/j.displa.2025.103196

Senhao Du , Yu Huang , Qiwen Yuan , Yongliang Dai , Zhendong Shi , Menghan Hu

{"title":"Rule-augmented LLM framework for detecting unreasonableness in ICU","authors":"Senhao Du , Yu Huang , Qiwen Yuan , Yongliang Dai , Zhendong Shi , Menghan Hu","doi":"10.1016/j.displa.2025.103196","DOIUrl":"10.1016/j.displa.2025.103196","url":null,"abstract":"<div><div>This paper proposes a rule-augmented model system for detecting unreasonable activities in Intensive Care Unit (ICU) hospitalization, mainly leveraging a large language model (LLM). The system is built on DeepSeek-R1-32B and integrates existing unreasonable activities in ICU hospitalization into health insurance systems through prompt learning techniques. Compared to traditional fixed-threshold rules, the large model augmented with rules possesses the ability to identify errors and exhibits a certain degree of emergent capabilities. In addition, it provides detailed and interpretable explanations for detected unreasonableness, helping the health insurance fund supervision perform efficient and accurate reviews. The framework includes two main sub-models: a discriminator for rule judgment, and an evaluator accuracy enhancement. Training data were derived from anonymized records from multiple hospitals and pre-processed to form the first domestic dataset tailored to unreasonable ICU billing detection tasks. The experimental results validate the effectiveness and practical value of the proposed system.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103196"},"PeriodicalIF":3.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LED dynamic lighting method based on synergistic regulation of color performance and non-visual effects 基于色彩表现与非视觉效果协同调节的LED动态照明方法

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-26 DOI: 10.1016/j.displa.2025.103235

Zhihao Liu , Zongxi Xie , Chaohui Zhuang , Min Hu , Zhengfei Zhuang , Tongsheng Chen

{"title":"LED dynamic lighting method based on synergistic regulation of color performance and non-visual effects","authors":"Zhihao Liu , Zongxi Xie , Chaohui Zhuang , Min Hu , Zhengfei Zhuang , Tongsheng Chen","doi":"10.1016/j.displa.2025.103235","DOIUrl":"10.1016/j.displa.2025.103235","url":null,"abstract":"<div><div>In lighting and display applications, traditional phosphor-converted LED is difficult to simultaneously ensure color rendering, chromaticity accuracy and non-visual effect control due to its inherent spectral energy distribution. Long-term exposure to high-intensity lighting affects human circadian rhythms. To address this issue, this paper proposes a dynamic control method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II). This method precisely controls the mixing ratio of five wavelengths of LED through pulse width modulation (PWM) technology, and realizes the dynamic adjustment of melanopic stimulation intensity while ensuring accurate color rendering. Experimently, the optimal combination of comprehensive evaluation was selected from 27 LEDs by least-squares fitting, with its peak wavelength covered 450–650 nm. The Melanopic to Photopic Ratio (M/P Ratio) was optimized in different directions in the temperature ranges of 2700–5000 K and 4000–6500 K, and the spectral output strategy was adaptively adjusted according to different chromaticity deviation levels. Our results demonstrate that under excellent color rendering conditions with the Television Lighting Consistency Index (TLCI) greater than 80, the optimization of the M/P Ratio increases by 19.4 % compared to natural reference illuminants in the low Correlated Color Temperature (CCT) range and by 15.3 % in the high CCT range, with CCT matching accuracy within 50 K and chromaticity distance below 0.007. This performance significantly outperforms both conventional white LEDs and daylight references.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103235"},"PeriodicalIF":3.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-stage attention based symmetric framework for stereo video quality assessment 基于双阶段注意力的立体视频质量评价对称框架

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-25 DOI: 10.1016/j.displa.2025.103232

Kairui Zhang , Xiao Ke , Xin Chen

{"title":"Dual-stage attention based symmetric framework for stereo video quality assessment","authors":"Kairui Zhang , Xiao Ke , Xin Chen","doi":"10.1016/j.displa.2025.103232","DOIUrl":"10.1016/j.displa.2025.103232","url":null,"abstract":"<div><div>The compelling creative capabilities of stereo video have captured the attention of scholars towards its quality. Given the substantial challenge posed by asymmetric distortion in stereoscopic visual perception within the realm of stereoscopic video quality evaluation (SVQA), this study introduces the novel <span><math><mrow><msup><mrow><mi>D</mi></mrow><mrow><mn>3</mn></mrow></msup><mi>N</mi><mi>e</mi><mi>t</mi></mrow></math></span> (Dual Branch, dual-stage Attention, Dual Task) framework for stereoscopic video quality assessment. Leveraging its innovative dual-task architecture, <span><math><mrow><msup><mrow><mi>D</mi></mrow><mrow><mn>3</mn></mrow></msup><mi>N</mi><mi>e</mi><mi>t</mi></mrow></math></span> employs a dual-branch independent prediction mechanism for the left and right views. This approach not only effectively addresses the prevalent issue of asymmetric distortion in stereoscopic videos but also pinpoints which view drags the overall score down. To surmount the limitations of existing models in capturing global detail attention, <span><math><mrow><msup><mrow><mi>D</mi></mrow><mrow><mn>3</mn></mrow></msup><mi>N</mi><mi>e</mi><mi>t</mi></mrow></math></span> incorporates a two-stage distorted attention fusion module. This module enables multi-level fusion of video features at both block and pixel levels, bolstering the model’s attention towards global details and its processing capabilities, consequently enhancing the overall performance of the model. <span><math><mrow><msup><mrow><mi>D</mi></mrow><mrow><mn>3</mn></mrow></msup><mi>N</mi><mi>e</mi><mi>t</mi></mrow></math></span> has exhibited exceptional performance across mainstream and cross-domain datasets, establishing itself as the current state-of-the-art (SOTA) technology.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103232"},"PeriodicalIF":3.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metal oxide TFTs gate driver and analog PWM pixel circuit employing progressive slope-compensated ramp signal for micro-LED displays 用于微型led显示器的金属氧化物TFTs栅极驱动器和采用递进斜率补偿斜坡信号的模拟PWM像素电路

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-23 DOI: 10.1016/j.displa.2025.103230

Lirong Zhang , Lei Zhou , Zhong Zheng , Zhaohua Zhou , Miao Xu , Lei Wang , Weijing Wu , Junbiao Peng

{"title":"Metal oxide TFTs gate driver and analog PWM pixel circuit employing progressive slope-compensated ramp signal for micro-LED displays","authors":"Lirong Zhang , Lei Zhou , Zhong Zheng , Zhaohua Zhou , Miao Xu , Lei Wang , Weijing Wu , Junbiao Peng","doi":"10.1016/j.displa.2025.103230","DOIUrl":"10.1016/j.displa.2025.103230","url":null,"abstract":"<div><div>A new metal oxide thin film transistors (MO TFT) gate driver has been presented for micro light-emitting diode (Micro-LED) displays with line-by-line driving method, where progressive and adjustable slope-compensated ramp signals are employed into each row of pixel array. A compensated analog pulse width modulation (PWM) pixel circuit is presented to construct the Micro-LED driving framework. This proposed gate driver with one input module and three output modules provides all the control signals for pixel array without any external integrated circuits (ICs), which simplifying the driving system. The experimented results show that the gate driver outputs integrated signals, including SCAN, EM and PWM. And the pixel circuit with single Micro-LED chip could achieve different grayscale levels from (100 to 3000 cd/m<sup>2</sup>), successfully. The slope and current of Micro-LED (<em>I<sub>LED</sub></em>) can be adjusted by applying an external bias, where the slope ranges from −0.35 to −0.57 within a bias range of −6 to −7 V, while <em>I<sub>LED</sub></em> varies from 17.3 to 61.7 μA under a bias range of 3 to 9 V. Then, the error rate of slope and brightness can achieve within 2 % and 5 % with <em>V<sub>th</sub></em> shift of about ±0.7 V after undergoing 1.5 h positive and negative bias stress test of TFT, respectively. Moreover, the proposed gate driver and pixel circuit have been verified to operate normally at high speeds with SCAN output width of 8.68 us, 6.51 us and 4.32 us, which is suitable for high-resolution Micro-LED displays.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103230"},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-output compact gate driver circuit design with embedded combinational logic for oxide TFT-based AMOLED displays 基于氧化物tft的AMOLED显示器双输出紧凑型门驱动电路的嵌入式组合逻辑设计

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-23 DOI: 10.1016/j.displa.2025.103231

Pu Liang , Yuxuan Zhu , Haohang Zeng , Congwei Liao , Shengdong Zhang

引用次数: 0

Less is more: An effective method to extract object features for visual dynamic SLAM 少即是多：一种有效的视觉动态SLAM目标特征提取方法

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-23 DOI: 10.1016/j.displa.2025.103224

Jianbo Zhang , Liang Yuan , Teng Ran , Jun Jia , Shuo Yang , Long Tang

{"title":"Less is more: An effective method to extract object features for visual dynamic SLAM","authors":"Jianbo Zhang , Liang Yuan , Teng Ran , Jun Jia , Shuo Yang , Long Tang","doi":"10.1016/j.displa.2025.103224","DOIUrl":"10.1016/j.displa.2025.103224","url":null,"abstract":"<div><div>Visual Simultaneous Localization and Mapping (VSLAM) is an essential foundation in augmented reality (AR) and mobile robotics. Dynamic scenes in the real world are a main challenge for VSLAM because it contravenes the fundamental assumptions based on static environments. Joint pose optimization with dynamic object modeling and camera pose estimation is a novel approach. However, it is challenging to model the motion of both the camera and the dynamic object when they are moving simultaneously. In this paper, we propose an efficient feature extraction approach for modeling dynamic object motion. We describe the object comprehensively through a more optimal feature selection strategy, which improves the performance of object tracking and pose estimation. The proposed approach combines image gradients and feature point clustering on dynamic objects. In the back-end optimization stage, we introduce rigid constraints on the dynamic object to optimize the poses using the graph model and obtain a high accuracy. The experimental results on the KITTI datasets demonstrate that the performance of the proposed approach is efficient and accurate.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103224"},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LCDiff: Line art colorization with coarse-to-fine diffusion and mask-guided voting LCDiff：线条艺术着色与粗到细的扩散和蒙版引导投票

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-23 DOI: 10.1016/j.displa.2025.103223

Gaolin Yang , Ping Shi , Jiye Zhang , Jian Xiao , Hao Zhang

引用次数: 0

Graph-based joint detection and tracking with Euclidean edges for multi-object video analysis 基于欧几里得边缘的图联合检测与跟踪多目标视频分析

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-22 DOI: 10.1016/j.displa.2025.103229

Nozha Jlidi , Sameh Kouni , Olfa Jemai , Tahani Bouchrika

{"title":"Graph-based joint detection and tracking with Euclidean edges for multi-object video analysis","authors":"Nozha Jlidi , Sameh Kouni , Olfa Jemai , Tahani Bouchrika","doi":"10.1016/j.displa.2025.103229","DOIUrl":"10.1016/j.displa.2025.103229","url":null,"abstract":"<div><div>Human detection and tracking are crucial tasks in computer vision, involving the identification and monitoring of individuals within specific areas, with applications in robotics, surveillance, and autonomous vehicles. These tasks face challenges due to variable environments, overlapping subjects, and computational limitations. To address these, we propose a novel approach using Graph Neural Networks (GNN) for joint detection and tracking (JDT) of humans in videos. Our method converts video into a graph, where nodes represent detected individuals, and edges represent connections between nodes across different frames. Node associations are established by measuring Euclidean distances between neighboring nodes, and the closest nodes are selected to form edges. This process is iteratively applied across all pairs of frames, resulting in a comprehensive graph structure for tracking. Our GNN-based JDT model was evaluated on the MOT16, MOT17, and MOT20 datasets, achieving MOTA of 85.2, ML of 11, IDF1 of 46, and MT of 65.7 on the MOT16 dataset, MOTA of 86.7 and IDF1 of 72.7 on the MOT17 dataset, and MOTA of 73.5 and IDF1 of 71.2 on the MOT20 dataset. The results demonstrate that our model outperforms existing state-of-the-art methods in both accuracy and efficiency. Through this innovative graph-based method, we contribute a robust and scalable solution to the field of human detection and tracking.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103229"},"PeriodicalIF":3.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning enriched channel interactions for image dehazing and beyond 学习丰富的通道交互图像去雾和超越

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-22 DOI: 10.1016/j.displa.2025.103212

Abdul Hafeez Babar , Md Shamim Hossain , Weihua Tong , Naijie Gu , Zhangjin Huang

{"title":"Learning enriched channel interactions for image dehazing and beyond","authors":"Abdul Hafeez Babar , Md Shamim Hossain , Weihua Tong , Naijie Gu , Zhangjin Huang","doi":"10.1016/j.displa.2025.103212","DOIUrl":"10.1016/j.displa.2025.103212","url":null,"abstract":"<div><div>Atmospheric haze degrades image clarity and impairs the performance of downstream computer visions tasks. Convolutional neural networks have demonstrated strong dehazing capabilities by exploiting neighborhood spatial patterns, while Vision Transformers excel at modeling long-range dependencies. However, existing methods suffers two challenges. First, inadequate modeling of inter-channel correlations leads to wavelength-dependent color distortions. Second, insufficient preservation of frequency-specific components results in blurred textures under non-uniform haze distributions. To tackle these limitations, we present the Dual-Domain Channel Attention Network (DDCA-Net), which integrates Spatial Channel Attention (SCA) and Frequency Channel Attention (FCA). The SCA module explicitly models spatial inter-channel dependencies to correct color imbalances, and the FCA module employs a multi-branch frequency decomposition mechanism to selectively restore high-frequency details attenuated by haze. This dual domain approach enables the precise reconstruction of fine-grained structures while enhancing overall image clarity. Extensive evaluations of nine benchmark datasets demonstrate consistent improvements over state-of-the-art methods. In particular, DDCA-Net achieves PSNR gains of 0.32 dB on RESIDE Indoor, 0.88 dB on SateHaze1K, and 1.79 dB on LOL-v2. Furthermore, our model yields significant boosts in downstream object detection and segmentation, confirming its practical utility. The code is available at <span><span>https://github.com/hafeezbabar/DDCA-Net</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103212"},"PeriodicalIF":3.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MAFM-Gaze: Multi-scale adaptive feature modulation for in-vehicle gaze estimation maff - gaze：基于多尺度自适应特征调制的车载凝视估计

IF 3.4 2区工程技术

Displays Pub Date : 2025-09-20 DOI: 10.1016/j.displa.2025.103226

Gan Zhang, Yafei Wang, Runze Yan, Xianping Fu

{"title":"MAFM-Gaze: Multi-scale adaptive feature modulation for in-vehicle gaze estimation","authors":"Gan Zhang, Yafei Wang, Runze Yan, Xianping Fu","doi":"10.1016/j.displa.2025.103226","DOIUrl":"10.1016/j.displa.2025.103226","url":null,"abstract":"<div><div>Gaze estimation is a critical component of Driver Monitoring and Assistance Systems (DMAS), as it effectively identifies driver distraction and fatigue during driving, thus enhancing driving safety. Existing methods face challenges in achieving accurate gaze estimation in driving scenarios, due to complex factors such as illumination variation, facial occlusion, and extreme head poses. Therefore, an in-vehicle gaze estimation method with multi-scale adaptive feature modulation (MAFM-Gaze) is proposed in this paper. In MAFM-Gaze, the model takes only facial images as input and employs a pruned cross-stage partial (CSP) network to extract multi-scale features efficiently. A 3D Spatially Adaptive Feature Modulation (3D-SAFM) module is integrated into the feature mixing network, incorporating a multi-head concept with independent computation to fully exploit multi-scale features at each level, thereby enriching the current layer with critical global information and long-range dependencies. Additionally, a 3D Multi-scale Feature Fusion Module (3D-MFFM) is introduced to extract scale-invariant information and capture deeper interrelationships among multi-scale features. Experimental results shown that our model outperforms existing state-of-the-art in-vehicle gaze estimation methods, achieving a mean angular error of 6.65°with a compact model size of only 44.6MB. The code will be available at <span><span>https://github.com/zhanggan123456/MAFM-Gaze</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"91 ","pages":"Article 103226"},"PeriodicalIF":3.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0