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.     

A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis

A large-scale dynamically weighted directed network (DWDN) involving numerous entities and massive dynamic interaction is an essential data source in many big-data-related applications, like in a terminal interaction pattern analysis system (TIPAS). It can be represented by a high-dimensional and incomplete (HDI) tensor whose entries are mostly unknown. Yet such an HDI tensor contains a wealth knowledge regarding various desired patterns like potential links in a DWDN. A latent factorization-of-tensors (LFT) model proves to be highly efficient in extracting such knowledge from an HDI tensor, which is commonly achieved via a stochastic gradient descent (SGD) solver. However, an SGD-based LFT model suffers from slow convergence that impairs its efficiency on large-scale DWDNs. To address this issue, this work proposes a proportional-integral-derivative (PID)-incorporated LFT model. It constructs an adjusted instance error based on the PID control principle, and then substitutes it into an SGD solver to improve the convergence rate. Empirical studies on two DWDNs generated by a real TIPAS show that compared with state-of-the-art models, the proposed model achieves significant efficiency gain as well as highly competitive prediction accuracy when handling the task of missing link prediction for a given DWDN.      

Real-time organic aerosol chemical speciation in the indoor environment using extractive electrospray ionization mass spectrometry

Understanding the sources and composition of organic aerosol (OA) in indoor environments requires rapid measurements, since many emissions and processes have short timescales. However, real-time molecular-level OA measurements have not been reported indoors. Here, we present quantitative measurements, at a time resolution of five seconds, of molecular ions corresponding to diverse aerosol-phase species, by applying extractive electrospray ionization mass spectrometry (EESI-MS) to indoor air analysis for the first time, as part of the highly instrumented HOMEChem field study. We demonstrate how the complex spectra of EESI-MS are screened in order to extract chemical information and investigate the possibility of interference from gas-phase semivolatile species. During experiments that simulated the Thanksgiving US holiday meal preparation, EESI-MS quantified multiple species, including fatty acids, carbohydrates, siloxanes, and phthalates. Intercomparisons with Aerosol Mass Spectrometer (AMS) and Scanning Mobility Particle Sizer suggest that EESI-MS quantified a large fraction of OA. Comparisons with FIGAERO-CIMS shows similar signal levels and good correlation, with a range of 100 for the relative sensitivities. Comparisons with SV-TAG for phthalates and with SV-TAG and AMS for total siloxanes also show strong correlation. EESI-MS observations can be used with gas-phase measurements to identify co-emitted gas- and aerosol-phase species, and this is demonstrated using complementary gas-phase PTR-MS observations.     

旗袍三围规格的优化设计研究

旗袍需要拥有合身的廓形,贴体程度要求高且强调人体曲线美感,而旗袍的松量设计直接影响其外观造型的优美程度及穿着舒适感。文章首先采用正交实验法针对相同款式旗袍设计了9种不同水平组合的三围松量设置方案,并制作成相同款式不同三围规格的旗袍样衣;然后利用心理学标尺,对9件旗袍样衣的静态造型和穿着舒适感分别进行主观评价,并利用直观分析法和方差分析法综合分析主观评价结果;最后对分析结果进行验证,最终找出外观造型优美程度高和穿着舒适感佳的三围松量水平组合,为旗袍三围规格的优化设计提供理论依据。     

RDNOx-PC1助剂在不完全再生装置上的工业应用

在巴陵石化1.05 Mt/a催化裂化装置上进行了降低不完全再生装置烟气氮氧化物（NOx）排放助剂RDNOx-PC1的工业应用试验。结果表明：RDNOx-PC1助剂可在锅炉出口CO浓度较低的情况下降低烟气NOx的排放浓度，有利于充分回收CO燃烧热量、减少CO排放；在相同CO出口浓度下，总结标定相对空白标定时烟气NOx排放浓度降低约20%，达到不大于200 mg/m3的排放标准要求。助剂的应用对催化裂化产品分布无明显的影响，主要产品的组成和性质基本保持不变。     

Theoretical and experimental studies of a new aniline derivative corrosion inhibitor for mild steel in acid medium

4-Chloro-N-(pyridin-2-ylmethyl)aniline (CPYA) was synthesized by a simple and inexpensive method and tested as a corrosion inhibitor in acid medium for mild steel by using gravimetric studies and electrochemical measurements. An average maximum efficiency of 96.0% was achieved at 4.59 mmol/L. Corrosion kinetic and thermodynamic parameters were also analyzed. Surface analyses (atomic force microscopy and scanning electron microscopy) show that protection is enabled by adsorption on the metal, forming a film. Quantum chemical calculations were performed to access information regarding the molecular structure in the corrosive medium and to support interpretation of the results obtained by experimental methods.     

Optical spectroscopic and electrochemical characterization of oxide films on a ferritic stainless steel

Colored oxide films that form on ferritic stainless steel in a high-temperature, oxidizing environment and correspond to different chemical compositions can cause a deterioration of pitting resistance and corrosion performance. Herein, optical spectroscopic and electrochemical techniques have been used to reveal the relationship between color, chemical composition, and corrosion resistance of oxide films formed in the temperature range from 400°C to 800°C for 30 min and at 800°C for 10, 20, 30, and 60 min. The substrate with a thin and dense passivation film leads to a low pitting potential but high corrosion resistance. Oxide films of yellowish or brownish color formed below 600°C are mainly iron oxides, which correspond to low corrosion resistance. No passivation characteristics can be observed for polarization curves of oxide films formed at 500°C and 600°C. The color of oxide films varies from blue to dark gray with the increase of oxidation time at 800°C. Corrosion resistance changes with different proportions of Fe₃O₄, Cr₂O₃, and FeCr₂O₄. The gray oxide films formed at 800°C for 30 min exhibit the lowest pitting susceptibility and the highest corrosion resistance.