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关键词： Pancreatic cancer   Cancers and neoplasms   Computed axial tomography   Cancer detection and diagnosis   Artificial intelligence   Deep learning   Imaging techniques   Malignant tumors  

摘要： Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due to the complex nature of CT scan images and variations in tumor shape, size, and location of the pancreatic tumor also make it challenging to detect and classify different types of tumors. Thus, to address this challenge we proposed a four-stage framework of computer-aided diagnosis systems. In the preprocessing stage, the input image resizes into 227 x 227 dimensions then converts the RGB image into a grayscale image, and enhances the image by removing noise without blurring edges by applying anisotropic diffusion filtering. In the segmentation stage, the preprocessed grayscale image a binary image is created based on a threshold, highlighting the edges by Sobel filtering, and watershed segmentation to segment the tumor region and we also implement the U-Net method for segmentation. Then refine the geometric structure of the image using morphological operation and extracting the texture features from the image using a gray-level co-occurrence matrix computed by analyzing the spatial relationship of pixel intensities in the refined image, counting the occurrences of pixel pairs with specific intensity values and spatial relationships. The detection stage analyzes the tumor region's extracted features characteristics by labeling the connected components and selecting the region with the highest density to locate the tumor area, achieving a good accuracy of 99.64%. In the classification stage, the system classifies the detected tumor into the normal, pancreatic tumor, then into benign, pre-malignant, or malignant using a proposed reduced 11-layer AlexNet model. The classification stage attained an accuracy level of 98.72%, an AUC of 0.9979, and an overall system average processing time of 1.51 seconds, demonstrating the cap

关键词： 江南文化   松江文明   色彩分析   纺织品设计  

摘要： 首先从地理区域、历史传承和价值观念等多个角度,探讨江南文化与松江文明之间的内在联系;其次,结合色彩特点梳理江南文化的历代发展与历史演变;最后,基于江南文化色彩的研究,设计出一系列以松江文明为主题的纺织品。这些纺织品不仅体现了松江文明的地域特色,还为现代纺织品的设计提供了新思路和灵感。

关键词： Grape leaf disease classification   Deep learning   EfficientNetV2L   Data augmentation  

摘要： Grape cultivation is essential to the global agricultural economy, but grape plants are highly vulnerable to diseases such as downy mildew, powdery mildew, black rot, and anthracnose. These diseases cause significant yield losses and impact plant health, necessitating accurate and timely identification for effective management and to maintain vineyard productivity. Conventional grape leaf disease identification relies on visual inspections by trained agronomists, a process that is time-consuming, labor-intensive, and susceptible to human error. Recent advancements have introduced machine learning and deep learning techniques, utilizing models like VGG, ResNet, and EfficientNet, and leveraging annotated datasets to automate disease classification. Existing methodologies often face challenges such as scalability, handling class imbalances, and adapting to environmental variability. Additionally, some approaches may lack sufficient accuracy or efficiency for real-time applications in the field, limiting their practical utility. This study proposes using the EfficientNetV2L deep learning model to address these limitations by leveraging transfer learning and extensive data augmentation. The EfficientNetV2L model is designed to balance model size and accuracy, providing robust performance across various scales of input images and ensuring reliable disease classification. The proposed model employs a pre-trained EfficientNetV2L architecture, enhanced with custom fully connected layers and comprehensive data augmentation techniques such as resizing, rescaling, and random transformations. The training process incorporates techniques like early stopping and checkpointing to optimize performance and prevent overfitting, ensuring the model’s robustness and generalizability.

关键词： Computer-Aided Design   Generative Artificial Intelligence   Co-creation   Prompt Tuning   Modular Decomposition   Information   Complexity  

摘要： Collaboration between humans and generative artificial intelligence (GenAI) can result in effective problem-solving methods for smart manufacturing. From this point of view, this study presents how to solve computer-aided design (CAD) problems using GenAI-human collaboration, where a GenAI tool generates structured code (syntax) for CAD while a designer articulates the design intent (semantics). The focus is to see how the information type, model complexity, and prompt structure collectively affect the collaboration. A set of case studies demonstrate that a modular modeling approach with low-level information improves prompt efficiency and modeling accuracy, especially in complex scenarios. This strategy also enables novice and expert users to collaborate with GenAI in solving challenging real-world CAD tasks effectively. The findings support the development of advanced human-AI co-creation systems and encourage future research in areas such as reverse engineering, multi-part assemblies, and collaborative CAD workflows coupled with complex design constraints.

关键词： 针织物   摇粒绒面料   聚酰亚胺   保暖性能   压缩性能   透湿性能   透气性能   掉纤维性能  

摘要： 为探讨聚酰亚胺纤维在摇粒绒面料中应用的可能性,以14.6、28.2 tex聚酰亚胺/棉30/70混纺纱、50 D/34 F SORONA长丝为原料,制备了3种针织摇粒绒面料,并对其基本性能、压缩性能、保暖性能、透湿性能、透气性能和掉纤维性能进行了测试和分析。结果表明,所制备的3种面料保暖性能均超过50%,且表现出较好的结构稳定性、透湿透气性能与压缩性能,其中以双罗纹组织制备的针织摇粒绒面料的保暖性能、透湿性能、透气性能和压缩性能最佳,且掉纤维性能可满足使用要求。该研究可为聚酰亚胺保暖面料的开发提供参考。

关键词： confirmatory factor analysis   dementia   EOLD-CAD   nursing home   surrogate report  

摘要： Objectives The End-of-Life Dementia-Comfort Assessment in Dying (EOLD-CAD) scale is one of the few outcome instruments designed to capture symptom burden and well-being among nursing home residents with dementia;however, psychometric evaluations of the EOLD-CAD are limited. Although the instrument is often used to assess outcomes prospectively, it was originally developed and tested as a postmortem assessment. The purpose of this study is to evaluate the instrument properties of the EOLD-CAD using staff reports from a large sample of nursing home residents with cognitive impairment prior to death. Methods Using data from the multi-state UPLIFT clinical trial, this study evaluated the psychometric properties of the EOLD-CAD from 168 nursing home staff members reporting outcomes for 611 living residents with moderate to severe cognitive impairment. Staff also reported on resident quality-of-life using two different single item measures. We conducted confirmatory factor analysis (CFA) and assessed construct validity, inter-item reliability, and observer report bias. Results CFA produced a four-factor solution. All factor loadings were > 0.40, ranging from 0.61-0.95 for Physical Distress, 0.71-0.91 for Dying Symptoms, 0.61-0.78 for Emotional Distress, and 0.89-0.94 for Well-Being. Model indices suggest a good fit to the data with root mean square error of approximation (RMSEA) = 0.053 (95% CI = (0.044, 0.062 comparative fit index (CFI) = 0.971, and standardized root mean square residual (SRMR) = 0.093, with the SRMR slightly above the conventional threshold of > 0.08. Based on intraclass correlation coefficients (ICC patterns of observer reports were identified among staff who provided data for multiple residents. ICCs were notably high (> 0.60) for Well-Being items. The EOLD-CAD elicited a Cronbach's alpha of 0.73, and the instrument was negatively correlated with items measuring resident quality of life. Conclusions We found that when the EOLD-CAD was completed by nur

关键词： CAD file enrichment   assembly   impact assessment   collaborative product development   MBD  

摘要： Multidisciplinary collaboration is key to product development; however, integrating multiple perspectives and design intent within the outcome of this process remains challenging. Although 3D product models are widely employed, they still lack relevant production details. A previous work established a coherent framework for enriching CAD files with assembly process information. This work offers the industrial perception and alignment of such a system through a preliminary impact assessment survey. Insights from experts and practitioners confirmed the solution’s suitability to address these gaps, revealing organizational connotations and offering recommendations for improvement. These findings provide a user-centred perspective to guide the future implementation of the approach into established product development processes

关键词： 配气机构   动力学   凸轮   挺柱   接触应力  

摘要： 通过对顶置凸轮轴直驱式配气机构的动力学试验,对气门升程、速度和加速度等运动特性参数进行了有效测量,并对试验数据加以分析研究,对凸轮与挺柱间的接触应力进行设计校核,对配气机构设计方案进行校验优化改进,并且通过试验手段找出判定气门机构飞脱的有效方法。

关键词： 印染纺织   市场需求   市场预测  

摘要： 随着全球化的深入发展和消费者意识的不断增强,印染纺织品市场正在经历前所未有的变革。经济增长与消费能力的提升推动了全球纺织品需求的增加,并显示出对高质量和环保纺织品的强烈需求。同时,环保意识的增强和可持续发展政策的实施也在塑造着供应链和生产流程,需要不断适应这些变化以维持竞争力。探讨全球印染纺织品市场的需求动态,分析经济增长、消费模式变化及环保法规如何影响纺织品的生产与市场分布,提供深入的市场需求分析框架,以期为业界提供策略调整的依据,支持行业的可持续发展。