Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of various Neural Networks trained on a custom dataset. It can be automated into assisting designers, allowing them to focus on the other more complicated parts of the system they are designing by quickly generating what would rather be straightforward busywork. Over the past 20 years, the boom in how much the internet is used and the sheer volume of pages on it demands a high level of work and time to create them. For the efficiency of the process, we proposed a multi-model-based architecture on image captioning, consisting of Convolutional neural network (CNN) and Long short-term memory (LSTM) models. Our proposed approach trained on our custom-made database can be automated into assisting designers, allowing them to focus on the other more complicated part of the system. We trained our model in several batches over a custom-made dataset consisting of over 6300 files and were finally able to achieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50 hand-drawn images at 87.86%     

面向智慧小镇建设的机房电气管线多目标优化布置方法

常规的管线布置优化方法难以在优化过程中得到全局搜索的最优解,导致安全性能无法得到保障,因此面向智慧小镇建设设计一个新的机房电气管线多目标优化布置方法。设置电气管线约束条件,将电压均值、单位时间内电流量、电气管线损耗恢复能力作为目标函数。优化管线布置全局搜索,使用交叉操作的方式不断得到更优解。建立多目标优化电气管线模型,得到电气管线多目标优化的数学模型。通过实验数据可知,该管线布置方法在算法测试中优于常规的3种算法,且在安全性能的检测中只与标准最优值相差6.22×10⁴,3个常规方法与标准最优值的差距为6.813×10⁴、7.6×10⁴、8.32×10⁴,因此可知该多目标优化的管线布置方法可以得到更优解。     

基于PID-二分组合控制算法的分布参数空气源热泵仿真模型的研究

采用分布参数法建立双级压缩空气源热泵系统热力学模型,建立一种基于PID-二分组合控制算法的全系统循环分布参数模型,并结合实验数据验证该模型的准确性。结果表明：系统模型在双级压缩制热模式下制热性能系数（COP）的模拟数据与实验数据的平均偏差为5.41%,两者在不同运行模式下的最大偏差不超过15%,均在可信范围之内,模型能准确反映系统性能随外界参数变化的规律;该模型与单独使用比例积分微分（PID）控制算法的分布参数法模型相比,总迭代次数较原模型减少约2.96倍,极大减少了模型的计算量,可在保证模型精度的情况下提升模型的计算速度。     

Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

The inspection of water conveyance tunnels plays an important role in water diversion projects. Siltation is an essential factor threatening the safety of water conveyance tunnels. Accurate and efficient identification of such siltation can reduce risks and enhance safety and reliability of these projects. The remotely operated vehicle (ROV) can detect such siltation. However, it needs to improve its intelligent recognition of image data it obtains. This paper introduces the idea of ensemble deep learning. Based on the VGG16 network, a compact convolutional neural network (CNN) is designed as a primary learner, called Silt-net, which is used to identify the siltation images. At the same time, the fully-connected network is applied as the meta-learner, and stacking ensemble learning is combined with the outputs of the primary classifiers to obtain satisfactory classification results. Finally, several evaluation metrics are used to measure the performance of the proposed method. The experimental results on the siltation dataset show that the classification accuracy of the proposed method reaches 97.2%, which is far better than the accuracy of other classifiers. Furthermore, the proposed method can weigh the accuracy and model complexity on a platform with limited computing resources.     

露天煤矿边坡工程岩体结构分析与计算机模拟研究

分析了岩体结构的自然特性，介绍了分形维数的求解方法及其计算机模拟程序，并给出了工程实例。     

液动冲击器孔内工作记录仪的研制

从钻进工程实际出发 ,提出了液动冲击器孔内工作记录仪的功能与技术指标 ,论述了记录仪的组成、工作原理与机械结构。利用记录仪 ,可以获知液动冲击器在孔内的工作情况 ,为优化钻进规程和改进钻具设计提供依据     

矿井提升机紧急制动时管道流动特性的计算机模拟

本文建立了提升机制动系统管路的物理模型、数学模型,基于特征线法进行了数学模拟计算,发现制动系统管路的阻尼对于紧急制动时贴闸油压的测试有很大的影响,这对矿井提升机的监控有着重大意义。     

任务驱动教学法在计算机教学中的探索与实践

结合计算机教学实践介绍了任务驱动教学法,分析了任务驱动教学法的优势、教学任务设计的原则及任务驱动教学法的实施步骤等.     

散状物料输送机称重的图像处理方法初步研究

散状物料实时称重系统依据计算机视觉理论,对摄像机模型进行标定,获得摄像机内外参数,利用数字图像处理技术获得目标图像的边缘,根据获得的边缘数据和特征点的匹配推算出目标物体点距离参考面的深度;由深度数据求得所测物料的重量。通过采用照相图片处理实验证明了方法的可行性。     

矿用智能风速仪

利用单片机设计了一种较为简单的便携式风速仪,使测量结果的精度得到了 较大的提高。