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.     

Thermal and hydraulic performance of a modified two-stage evaporative cooler

The thermal and hydraulic performance of a modified two-stage evaporative cooler is evaluated. Variables considered are the mode of operation, packing thickness, mass flow rate of the water flowing to the precooler, and the mass flux of water flowing over the packing media. The effectiveness of the system increased with the increase of the mass flow rate of water flowing to the precooler, decreasing the mass flux of water flowing to the packing, and with the increase of the packing thickness. The effectiveness of the system with structured packing was higher than that with sheathy leaf base or natural fiber packing.The air-side pressure drop per unit length in the direction of air flow was nearly constant when the structured packing was used. For the sheathy leaf and natural fiber packings, the air pressure drop increased at a uniform rate as the mass flux of water flowing over the packing increased. The air pressure drop was lowest for the setup with the structured packing.     

Measuring the errors of form of industrial surfaces: prediction and optimization

To acquire maximum information on the geometrical errors of industrially made surfaces at a minimum cost, a method for estimating conditional probabilities of a random signal (Bayesian prediction) is applied to three-dimensional metrology. First, a surface is interpolated between data acquired on a coordinate measuring machine (CMM). Then, for a given probability, limit surfaces are computed that bind a region of space containing the known data and the most probable interpolation of the missing data of the surface. These bounds can be treated as the surface; their points can be considered as if they were actual CMM data when fitting a tolerance zone or a datum feature to the data. For Bayesian prediction, the basic hypotheses on the signal are stationarity, ergodicity, and gaussian density. Deviations from these hypotheses and their consequences on the prediction are taken into account and corrections are proposed.     

Activation of Nrf2/HO-1 by Peptide YD1 Attenuates Inflammatory Symptoms through Suppression of TLR4/MYyD88/NF-κB Signaling Cascade

In this study, we investigate the immunomodulatory effects of a novel antimicrobial peptide, YD1, isolated from Kimchi, in both in vitro and in vivo models. We establish that YD1 exerts its anti-inflammatory effects via up-regulation of the Nrf2 pathway, resulting in the production of HO-1, which suppresses activation of the NF-κB pathway, including the subsequent proinflammatory cytokines IL-1β, IL-6, and TNF-α. We also found that YD1 robustly suppresses nitric oxide (NO) and prostaglandin E2 (PGE₂) production by down-regulating the expression of the upstream genes, iNOS and COX-2, acting as a strong antioxidant. Collectively, YD1 exhibits vigorous anti-inflammatory and antioxidant activity, presenting it as an interesting potential therapeutic agent.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Urban water demand,climatic variation,and irrigation-water insecurity: interactive stressors and lessons for water governance from the Angat River basin (Philippines)

Climatic variation and intersectoral water competition increasingly challenge the effective provision of irrigation services. This article explores their combined effects on irrigation allocation from the Angat Reservoir (Philippines), where domestic water use in Metro Manila has overtaken regional irrigation as the dominant right-holder. Rules protecting Metro Manila’s large right to water ‘interact’ with dry spells to affect irrigation security in wet and dry seasons. Historically, irrigators were uncompensated because re-allocation’s cause was contested as (1) an unforeseeable climatic event (releasing domestic utilities of liability), or (2) produced by urban demand (requiring compensation). Trade-off rules must be prepared to navigate combinatory effects.     

Separation of crude palm oil components by semipreparative supercritical fluid chromatography

Successful separation of triglycerides, diglycerides, free fatty acids, carotenes, tocopherol, and tocotrienols from crude palm oil has been achieved by supercritical fluid chromatography (SFC) with a combination of a C18 and a silica gel column. The separation was carried out by the programmed extraction elution method. Free fatty acids were separated into five components by gas-liquid chromatography; tocopherol and tocotrienols were also separated into four components by SFC analysis, and the pure fractionated carotenes were obtained by preparative SFC. Thus, by using supercritical fluid chromatography, crude palm oil components can be separated and fractionated, based on differences in their functional groups.     

A survey on video content rating: taxonomy,challenges and open issues

Multimedia Tools and Applications - Rating a video based on its content is one of the most important solutions to classify videos for audience age groups. In this regard, Film content rating and TV...