Multifactor Algorithm for Test Case Selection and Ordering

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls short. The current research is motivated by this concept and proposes a multifactor algorithm incorporated with genetic operators and powerful features. A factor-based prioritizer is introduced for proper handling of tied test cases that emerged while implementing re-ordering. Besides this, a Cost-based Fine Tuner (CFT) is embedded in the study to reveal the stable test cases for processing. The effectiveness of the outcome procured through the proposed minimization approach is anatomized and compared with a specific heuristic method (rule-based) and standard genetic methodology. Intra-validation for the result achieved from the reduction procedure is performed graphically. This study contrasts randomly generated sequences with procured re-ordered test sequence for over '10' benchmark codes for the proposed prioritization scheme. Experimental analysis divulged that the proposed system significantly managed to achieve a reduction of 35-40% in testing effort by identifying and executing stable and coverage efficacious test cases at an earlier phase

Effect of Temperature and Strain Rate Variation on Tensile Properties of a Defective Nanocrystalline Copper-Tantalum Alloy

358-366Nanocrystalline alloys of immiscible in nature are emerging topics of interest for researchers due to better mechanical stability at high temperatures. Nanocrystalline Copper-Tantalum alloy is of particular interest for research exploration due to its high strength, limited solubility and high-temperature stability. In the present work, the mechanical properties of nanocrystalline 90/10 copper-tantalum (9Cu-Ta) alloy have been investigated using the molecular dynamics approach. Embedded atom method (EAM) of potential has been used to analyze the mechanical properties at high temperatures due to the high stability of EAM in molecular dynamic simulation. At high-temperature defects plays a very important role therefore a specific 9Cu-Ta nanostructure having 3% vacancies has been selected to explore its performance under a particular type of point defect. This study has been conducted under uniaxial tensile loading. The tensile properties of this defective nanocrystalline alloy have been compared at specific temperatures i.e. 300 K, 600 K, 800 K, 1000 K and 1200 K. The study revealed that the variation in temperature from 300 K to 1200 K results in the shifting of the stress-strain graph to lower stress values. It has also been noticed that the variation in ultimate tensile strength is the least in comparison to yield strength and elastic constant for the same variation in temperature. These results indicate the importance of avoiding thermal agitations during the synthesis and surface modification of nanocrystalline copper-tantalum alloy

Dry Beneficiation of Coking Coal Fines using an Advanced Air Cyclone

An attempt is made on coking coal fines dry beneficiation of below 2 mm size, with VSK separator consisting of advanced air cyclone. The results of these investigations reveal that simple size with 250 micron can give a product with 18% ash at 17.4% yield, whereas by using VSK separator the product obtained contains 17.8% ash with 48.1% yield from a feed sample containing 23.3% ash. Since the preliminary investigations has shown encouraging results on reduction of ash, large scale continuous tests can provide better yield for various samples

Comminution Characters of Fault Zone Rocks and Secure Outcomes in the Blockchain Record-Keeping System for Industrial Applications

This paper is an attempt to find the energy required for the comminution of fault zone rocks and also to determine the energy required to grind ore from infinite size to the desired particle size in non-traditional approach, for various value additions. The results in the present investigations also confirm about the brittleness test and friability tests, whose values depend on the drop weight and its height for different types of fault zone rock. Also the results of its brittleness tests determine the grindability of fault zone rocks. All the outcome results are then secured with the help of decentralized and immutable record-keeping system using Blockchain technology. The Blockchain network in the present investigations not only allows any users to enhance the performance but also it will secure the experimental outcomes in immutable distributed ledgers through smart contracts to increase transparency between users in a trusted manner

Trusted and Transparent Blockchain-enabled E-waste Optimization to Recover Precious Metals with Microwave Heating

623-629Blockchain technology facilitates trust and transparency in the decision-making process and enables the transaction's verifiability by reading immutable distributed ledgers. It has been innovatively applied this technology in the E-waste optimization for the recovery of precious metals using microwave heat treatment. This present paper presents the maximum recovery of precious and base metals from E-waste with a numerical technique called surface response methodology, and was compared with the actual experimental results. The main goal of this paper is to recover the precious metals like copper and gold with its adjacent metals from unwanted and discarded printed circuit boards, integrated circuits, and standards connectors, with the input variables of microwave power, maximum temperature, and aqua leaching ratio. The obtained empirical information of recovered metals was recorded in immutable distributed ledgers so that every member of the blockchain network can be read and verified through the stored records. These records were also utilized to minimize the error and maximize the precious metal outcomes. The result with blockchain network also shows that identical resemblance between the experimental and statistical predicted data obtained with surface methodology. Further, Smart Contracts has been created and deployed to store and retrieve empirical records in the Hyperledger Fabric Blockchain Platform and then measured the performance using Hyperledger Caliper Benchmark

Trusted and Transparent Blockchain-enabled E-waste Optimization to Recover Precious Metals with Microwave Heating

Blockchain technology facilitates trust and transparency in the decision-making process and enables the transaction's verifiability by reading immutable distributed ledgers. It has been innovatively applied this technology in the E-waste optimization for the recovery of precious metals using microwave heat treatment. This present paper presents the maximum recovery of precious and base metals from E-waste with a numerical technique called surface response methodology, and was compared with the actual experimental results. The main goal of this paper is to recover the precious metals like copper and gold with its adjacent metals from unwanted and discarded printed circuit boards, integrated circuits, and standards connectors, with the input variables of microwave power, maximum temperature, and aqua leaching ratio. The obtained empirical information of recovered metals was recorded in immutable distributed ledgers so that every member of the blockchain network can be read and verified through the stored records. These records were also utilized to minimize the error and maximize the precious metal outcomes. The result with blockchain network also shows that identical resemblance between the experimental and statistical predicted data obtained with surface methodology. Further, Smart Contracts has been created and deployed to store and retrieve empirical records in the Hyperledger Fabric Blockchain Platform and then measured the performance using Hyperledger Caliper Benchmar

Eff ect of participatory women’s groups facilitated by Accredited Social Health Activists on birth outcomes in rural eastern India: a cluster-randomised controlled trial

Background A quarter of the world’s neonatal deaths and 15% of maternal deaths happen in India. Few community-based strategies to improve maternal and newborn health have been tested through the country’s government-approved Accredited Social Health Activists (ASHAs). We aimed to test the eff ect of participatory women’s groups facilitated by ASHAs on birth outcomes, including neonatal mortality. Methods In this cluster-randomised controlled trial of a community intervention to improve maternal and newborn health, we randomly assigned (1:1) geographical clusters in rural Jharkhand and Odisha, eastern India to intervention (participatory women’s groups) or control (no women’s groups). Study participants were women of reproductive age (15–49 years) who gave birth between Sept 1, 2009, and Dec 31, 2012. In the intervention group, ASHAs supported women’s groups through a participatory learning and action meeting cycle. Groups discussed and prioritised maternal and newborn health problems, identifi ed strategies to address them, implemented the strategies, and assessed their progress. We identifi ed births, stillbirths, and neonatal deaths, and interviewed mothers 6 weeks after delivery. The primary outcome was neonatal mortality over a 2 year follow up. Analyses were by intention to treat. This trial is registered with ISRCTN, number ISRCTN31567106. Findings Between September, 2009, and December, 2012, we randomly assigned 30 clusters (estimated population 156 519) to intervention (15 clusters, estimated population n=82 702) or control (15 clusters, n=73 817). During the follow-up period (Jan 1, 2011, to Dec 31, 2012), we identifi ed 3700 births in the intervention group and 3519 in the control group. One intervention cluster was lost to follow up. The neonatal mortality rate during this period was 30 per 1000 livebirths in the intervention group and 44 per 1000 livebirths in the control group (odds ratio [OR] 0.69, 95% CI 0·53–0·89). Interpretation ASHAs can successfully reduce neonatal mortality through participatory meetings with women’s groups. This is a scalable community-based approach to improving neonatal survival in rural, underserved areas of India

Effect of participatory women's groups facilitated by Accredited Social Health Activists on birth outcomes in rural eastern India: A cluster-randomised controlled trial

Background: A quarter of the world's neonatal deaths and 15% of maternal deaths happen in India. Few community-based strategies to improve maternal and newborn health have been tested through the country's government-approved Accredited Social Health Activists (ASHAs). We aimed to test the effect of participatory women's groups facilitated by ASHAs on birth outcomes, including neonatal mortality. Methods: In this cluster-randomised controlled trial of a community interve

Intracluster correlation coefficients and coefficients of variation for perinatal outcomes from five cluster-randomised controlled trials in low and middle-income countries: results and methodological implications

Background: Public health interventions are increasingly evaluated using cluster-randomised trials in which groups rather than individuals are allocated randomly to treatment and control arms. Outcomes for individuals within the same cluster are often more correlated than outcomes for individuals in different clusters. This needs to be taken into account in sample size estimations for planned trials, but most estimates of intracluster correlation for perinatal health outcomes come from hospital-based studies and may therefore not reflect outcomes in the community. In this study we report estimates for perinatal health outcomes from community-based trials to help researchers plan future evaluations.Methods: We estimated the intracluster correlation and the coefficient of variation for a range of outcomes using data from five community-based cluster randomised controlled trials in three low-income countries: India, Bangladesh and Malawi. We also performed a simulation exercise to investigate the impact of cluster size and number of clusters on the reliability of estimates of the coefficient of variation for rare outcomes.Results: Estimates of intracluster correlation for mortality outcomes were lower than those for process outcomes, with narrower confidence intervals throughout for trials with larger numbers of clusters. Estimates of intracluster correlation for maternal mortality were particularly variable with large confidence intervals. Stratified randomisation had the effect of reducing estimates of intracluster correlation. The simulation exercise showed that estimates of intracluster correlation are much less reliable for rare outcomes such as maternal mortality. The size of the cluster had a greater impact than the number of clusters on the reliability of estimates for rare outcomes.Conclusions: The breadth of intracluster correlation estimates reported here in terms of outcomes and contexts will help researchers plan future community-based public health interventions around maternal and newborn health. Our study confirms previous work finding that estimates of intracluster correlation are associated with the prevalence of the outcome of interest, the nature of the outcome of interest ( mortality or behavioural) and the size and number of clusters. Estimates of intracluster correlation for maternal mortality need to be treated with caution and a range of estimates should be used in planning future trials

Community mobilisation with women's groups facilitated by Accredited Social Health Activists (ASHAs) to improve maternal and newborn health in underserved areas of Jharkhand and Orissa: study protocol for a cluster-randomised controlled trial

Background: Around a quarter of the world's neonatal and maternal deaths occur in India. Morbidity and mortality are highest in rural areas and among the poorest wealth quintiles. Few interventions to improve maternal and newborn health outcomes with government-mandated community health workers have been rigorously evaluated at scale in this setting.The study aims to assess the impact of a community mobilisation intervention with women's groups facilitated by ASHAs to improve maternal and newborn health outcomes among rural tribal communities of Jharkhand and Orissa.Methods/design: The study is a cluster-randomised controlled trial and will be implemented in five districts, three in Jharkhand and two in Orissa. The unit of randomisation is a rural cluster of approximately 5000 population. We identified villages within rural, tribal areas of five districts, approached them for participation in the study and enrolled them into 30 clusters, with approximately 10 ASHAs per cluster. Within each district, 6 clusters were randomly allocated to receive the community intervention or to the control group, resulting in 15 intervention and 15 control clusters. Randomisation was carried out in the presence of local stakeholders who selected the cluster numbers and allocated them to intervention or control using a pre-generated random number sequence. The intervention is a participatory learning and action cycle where ASHAs support community women's groups through a four-phase process in which they identify and prioritise local maternal and newborn health problems, implement strategies to address these and evaluate the result. The cycle is designed to fit with the ASHAs' mandate to mobilise communities for health and to complement their other tasks, including increasing institutional delivery rates and providing home visits to mothers and newborns. The trial's primary endpoint is neonatal mortality during 24 months of intervention. Additional endpoints include home care practices and health care-seeking in the antenatal, delivery and postnatal period. The impact of the intervention will be measured through a prospective surveillance system implemented by the project team, through which mothers will be interviewed around six weeks after delivery. Cost data and qualitative data are collected for cost-effectiveness and process evaluations