Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

随车起重机伸缩臂截面多目标优化

为了提高某火箭炮弹药装填车随车起重机伸缩臂的结构刚度,减轻结构质量,建立了随车起重机伸缩臂参数化模型,并对伸缩臂在水平受载状态下进行仿真分析。以伸缩臂截面尺寸参数为设计变量,借助最优拉丁超立方试验设计建立样本空间,构造响应面多项式函数近似模型。在此基础上,利用NSGA-Ⅱ型遗传算法对伸缩臂自身重量、挠度进行多目标优化。优化结果表明:伸缩臂质量减轻了24.5%,减重效果明显。文中所采用的将参数化建模、有限元分析和数值寻优相结合的优化方法,可为起重机伸缩臂截面优化提供一定的参考。     

自密实高性能混凝土在结构工程中的应用

对外经济贸易大学学生公寓楼工程,建筑面积93 628 m2,地下二层,地上十层,剪力墙结构,其中消防通道部分框架—剪力墙体系,主框架梁跨度13m,截面600 mm×2700,框架柱截面为800mm×1300,剪力墙厚度为250mm,根据结构构件的特点该部位墙、柱、梁均采用C60自密实高性能混凝土约450m3。     

Applying data mining to learn system dynamics in a biological model

Data mining consists of a set of powerful methods that have been successfully applied to many different application domains, including business, engineering, and bioinformatics. In this paper, we propose an innovative approach that uses genetic algorithms to mine a set of temporal behavior data output by a biological system in order to determine the kinetic parameters of the system. Analyzing the behavior of a biological network is a complicated task. In our approach, the machine learning method is integrated with the framework of system dynamics so that its findings are expressed in a form of system dynamics model. An application of the method to the cell division cycle model has shown that the method can discover approximate parametric values of the system and reproduce the input behavior.     

基于水力水文学法的大渡河上游生态流量确定

利用湿周法、Tennant法、Tessman法、逐月最小径流法分别计算大渡河上游的最小生态流量,并通过鱼类繁殖产卵所需的流量验证4种方法的合理性。结果表明,Tennant法、Tessman法、逐月最小径流法能保证足木足断面鱼类繁殖产卵所需的最低流量,大金断面4种方法均能满足。推荐3—8月采用Tennant法,9月至次年2月选择湿周法,计算得到的最小生态流量过程能够满足鱼类及栖息地保护的要求,又对人类取用水影响最小。     

Pricing Exotic Option Under Jump-Diffusion Models by the Quadrature Method

This paper extends the quadrature method to price exotic options under jump-diffusion models. We compute the transition density of jump-extended models using convolution integrals. Furthermore, a simpler and more efficient lattice grid is introduced to implement the recursion more directly in matrix form. It can be shown that a lot of running time can be saved. At last, we apply the developed approach to the different jump-extended models to demonstrate its universality and provide a detailed comparison for the discrete path-dependent options to demonstrate its advantages in terms of speed and accuracy.

     

微纳米气泡臭氧高级氧化工艺处理电镀废水的中试

对江苏省某电镀园区污水厂尾水使用微纳米气泡臭氧高级氧化工艺进行深度处理中试研究,要求处理后达到《地表水环境质量标准》(GB3838—2002)Ⅴ类标准。半连续流试验结果表明,单独臭氧氧化处理无法有效去除有机物,加入双氧水催化臭氧微纳米气泡处理后可以使COD达标。在臭氧与双氧水投加量摩尔比为2时,投加64.6mg/L臭氧后,COD_Cr由37.1mg/L降至24.7mg/L,去除率可达33.4%,O/C为5.2。臭氧浓度对COD的去除有影响,低浓度臭氧对COD有更高的去除率(46.3%)。同时,推测臭氧和双氧水改变了原水中铁离子的价态,通过絮凝沉淀可有效地去除水中的镍。采用臭氧浓度为150mg/L、臭氧与双氧水摩尔比为2的工况进行连续流试验,臭氧投加量为55mg/L、连续运行5h、进水COD_Cr约为45mg/L时,出水COD_Cr基本稳定在18.5~21.8mg/L,COD去除率为54%~58.3%,O/C为1.38~1.62,可达标排放。由结果可知:相较于半连续流试验,同样的投加条件下,连续流的氧化效能更高,推测是由于流态变化;同时,半连续流中试试验虽然水量较大(500L),但要完全模拟连续流试验结果还是存在局限性。最后,根据连续流结果估算双氧水催化臭氧工艺的处理成本为0.86元/(t水)。     

基于卡尔曼滤波的电力虚假数据注入攻击检测方法

能源互联网的主体是基于状态估计下的电力系统。虚假数据注入攻击（FDIA）通过恶意篡改或注入电力数据,进而引发错误的状态估计结果。这种攻击方式存在引发大面积停电事故的风险,严重影响能源互联网的正常运行。在matpower 4.0中的IEEE-14节点系统上,利用以残差方程为基础的标准残差检测法和目标函数极值法,对FDIA进行了检测实验。提出了一种基于卡尔曼滤波的FDIA检测方法,并在MATLAB上进行了验证。实验结果表明,该方法可以在短时间内发现FDIA的发生。