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.     

基于启发式BP算法的软件缺陷预测模型

针对软件缺陷预测时缺陷数据集中存在的类别分布不平衡问题，结合上采样算法SMOTE与Edited Nearest Neighbor (ENN) 数据清洗策略，提出了一种基于启发式BP神经网络算法的软件缺陷预测模型。模型中采用上采样算法SMOTE增加少数类样本以改善项目中的数据不平衡状况，并针对采样后数据噪声问题进行ENN数据清洗，结合基于启发式学习的模拟退火算法改进四层BP神经网络后建立分类预测模型，在AEEEM数据库上使用交叉验证对提出的方案进行性能评估，结果表明所提出的算法能够有效提高模型在预测类不平衡数据时的分类准确度。     

An industrial case study on variability handling in large enterprise software systems

ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices.     

Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.     

APP软件性能效率研究

性能效率是APP软件的重要质量属性，但目前缺乏APP软件性能效率的通用模型。分析了APP软件的性能特征，基于ISO/IEC 25010标准提出了APP软件的性能效率模型，定义了APP软件性能效率的子特性和度量指标。基于提出的APP软件性能效率模型，通过实验对APP软件的性能效率进行了度量及相关分析。     

An architecture to support scalable distributed virtual environment systems on grid

A Distributed Virtual Environment (DVE) system offers a computer-generated virtual world in which individuals located at different places in the physical world can interact with one another. In order to achieve real-time response for a large user base, DVE systems need to have a scalable architecture. In this paper, we present the design of a grid-enabled service oriented framework for facilitating the construction of scalable DVE systems on computing grids. A service component called “gamelet” is proposed, whose distinctive mark is its high mobility for supporting dynamic load sharing. We propose a gamelet migration protocol which can ensure the transparency and efficiency of gamelet migration, and an adaptive gamelet load-balancing (AGLB) algorithm for making gamelet redistribution decisions at runtime. The algorithm considers both the synchronization costs of the DVE system and network latencies inherent in the grid nodes. The activities of the users and the heterogeneity of grid resources are also considered in order to carry out load sharing more effectively. We evaluate the performance of the proposed mechanisms through a multiplayer online game prototype implemented using the Globus toolkit. The results show that our approach can achieve faster response times and higher throughputs than some existing approaches. This research is supported in part by the China National Grid project (863 program) and the HKU Foundation Seed Grant 28506002.     

指纹考勤管理软件的研究与实现

针对企、事业单位原有的考勤系统，如打卡钟、磁卡、IC卡等考勤方式存在代打卡、卡丢失等不足和缺陷的实际，结合指纹识别技术，建立一套考勤、薪资、人事管理于一体的软件系统。给出了系统的体系结构和功能实现，能使企业考勤管理更加简便快捷、客观公正。并提出了进一步的发展方向和展望。     

VFP环境下报表设计研究

Visual FoxPro是小型数据库应用系统开发工具,而报表设计是数据库应用系统开发的一个重要组成部分,直接决定系统的输出是否能够满足用户的需要。为此详细研究了报表设计方法,结合Microsoft的OLE技术,引入面向对象方法,提出了一种新的报表设计方法。实践应用证明,该方法非常适合设计复杂的报表。     

大型弧形闸门静力特性有限元分析

以某水电站溢洪道弧形闸门为例,建立了大型弧形闸门的有限元分析模型,应用ANSYS软件对其在各种工况下的支铰反力、闸门应力、位移挠度以及屈曲失稳等静力特性进行了计算分析,为完善闸门结构的设计提供了依据,对同类闸门结构的设计计算有参考意义。     

动力环境集中监控系统可靠性的提高

为实现电源设备乃至通信机房的少人或无人值守和集中维护,必须建立一套完善的电信局动力环境集中监控系统。文中结合番禺区电信局的实际,讨论了提高系统运行可靠性的几点措施,包括硬件方面与软件方面的手段,关键在于加强系统的运行管理。