Hybrid swarm and GA based approach for software test case selection

Being a crucial step and deciding factor for software reliability, software testing has evolved a long way and always attracted researchers due to various inherent challenges. The quality of a software application depends on the effectiveness of the testing carried out during development and maintenance phase. Testing is a crucial but time consuming activity that influences the overall cost of software development. Thus a minimal but efficient test suite selection is the need of the hour. This paper presents a hybrid technique based on swarm based search technique and GA (Genetic Algorithm) for selection of promising test cases to reduce the overall development cost and time of the application. We took component based software into consideration as they offer some inherent advantages over traditional software development paradigms

Tobacco and Covid-19

The relationship between tobacco use and COVID-19 has been a subject of ongoing research. Evidence suggests that tobacco may contribute to an increased susceptibility to respiratory infections, potentially exacerbating the severity of COVID-19 symptoms

Datasets Used in Fifteen Years of Automated Requirements Traceability Research

Datasets are crucial to advance automated software traceability research. Acquiring such datasets come in a high cost and require expert knowledge to manually collect and validate them. Obtaining such software development datasets has been one of the most frequently reported barrier for researchers in the software engineering domain in general. This problem is even more acute in field of requirement traceability, which plays crucial role in safety critical and highly regulated systems. Therefore, the main motivation behind this work is to analyze the current state of art of datasets used in the field of software traceability. This work presents a first-of-its-kind literature study to review and assess the datasets that have been used in software traceability research over the last fifteen years. It articulates several attributes related to these datasets such as their characteristics, threats and diversity. Firstly, 202 primary studies (refer Appendix A) were identified for purpose of this study, which were used to derive 73 unique datasets. These 73 datasets were studied in-depth and several attributes (size, type, domain, availability, artifacts) were extracted (refer Appendix B). Based on analysis of the primary studies, a threat to validity reference model, tailored to Software traceability datasets was derived (refer to figure 4.4). Furthermore, to put some light upon the dataset diversity trend in the Software traceability community, a metric called Dataset Diversity Ratio was derived for 38 authors (refer to figure 4.5) who have published more than one publication in field of software traceability

Numerical Prediction of Automotive Underhood Airflows using an Uncalibrated Fan Body Force Model

Underhood vehicle airflow simulations are an important part of the overall vehicle thermal management process, especially in the preliminary stages of the vehicle development program when performing experimental work on cooling system prototypes can prove to be expensive, time-consuming, or simply impossible due to the absence of any physical vehicle prototypes. Accurate prediction of the automotive fan performance, which forms a critical component of the cooling module, is a prerequisite for the optimum sizing and design of heat exchangers, and the rest of the under-hood installations. The coupled and complex nature of the under-hood flow environment necessitates consideration of the entire front-end cooling module, and preferably the entire vehicle, in a single simulation to judge the fan performance. Direct modelling of the rotating fan blades in a full vehicle simulation can yield unacceptably long run times, hence the norm is to use simplified numerical models which can capture the general fan behaviour at a reduced cost. Industrial practice is to calibrate these fan models with experimental or high-fidelity simulated fan performance data, which slows down the design process and is expensive. This work solves this problem by using an uncalibrated body force fan modelling approach, which only requires fan geometry information and no a-priori fan performance data. The approach has previously shown promising results for aircraft engine fan applications, however it’s suitability for automotive fan applications is tested for the first time. The model performs with a comparable accuracy as the current state-of-the-art calibrated fan modelling techniques. It predicts the radiator airflow rate to within 8% of the experimentally-measured value at idle. At high vehicle speed, the accuracy improves to 1%. Success in this project facilitates a low-cost, reliable and rapid aerothermal analysis tool for designing vehicle cooling systems

Hybrid Micro Grid Systems - Drivers & Challenges

Increasing environmental concerns, consumer expectations in terms of reliability & better quality of power supply and improving economics of distributed energy resources (DER) based on renewable, is making Micro Grid a viable proposition. Hybrid Micro grid utilising diversity of various energy resources including Wind, Solar, Biomass, and Energy Storage Batteries is found to be a better solution than single source Micro grid system. However, integration of multiple resources poses many issues & challenges. Moreover, present distribution system offers many technical & operational glitches for successful integration of Micro Grid Technologies. Paper addresses such challenges, issues and solutions. The Micro Grid resources optimization is generally being done based on self-sufficiency criterion which utilizes the grid support only in the event of contingencies like fault, generation disruptions (DER) etc. Paper also discusses various resources optimization techniques to serve the net load requirements in all time of the Day (TOD). Keywords: Distributed Energy, Black Start, net load, Islanding, MGCC, PSO, Genetic Algorith

Regulation Of Nuclear Localization Of The Sole Sumo-Conjugating Enzyme, Ubc9

The covalent and reversible conjugation of small ubiquitin-like modifier (SUMO) proteins to hundreds of different cellular proteins is catalyzed by a cascade of enzymes including an E1-activating enzyme (SAE1/SAE2), an E2-conjugating enzyme (Ubc9) and multiple E3 ligases. As the only E2 enzyme for SUMO-conjugation, Ubc9 localizes mainly in the nucleus and plays an essential role in regulation of many cellular processes including cell cycle progression through mitosis, cell migration, genome stability, stress response, transcription, and nuclear transport in eukaryotic cells. It is hypothesized that the nuclear localization of Ubc9 is required for efficient sumoylation inside the nucleus because both the sole SUMO E1 enzyme and SUMO-conjugates are mainly in the nucleus. However, we still have a poor understanding of how Ubc9 is accumulated in the nucleus. Although the nuclear import receptor Importin 13 (Imp13) can mediate the nuclear import of Ubc9 using in vitro nuclear import assays, little is known about how Ubc9 nuclear localization is regulated in vivo. Here, we hypothesize that Imp13 is the major nuclear import receptor for Ubc9 and thus required for efficient global sumoylation in vivo. Consistent with this hypothesis, we found that knockdown of Imp13 by RNA interference (RNAi) causes a decrease of global sumoylation and also an increased cytoplasmic distribution of Ubc9. Furthermore, the Ubc9 mutant (R17E) with a defect in Imp13-interaction showed a significant increase of cytoplasmic distribution when compared to Ubc9 wild-type (WT). Moreover, overexpression of Imp13 greatly enhanced the nuclear localization of Ubc9-WT but not Ubc9-R17E mutant, whereas overexpression of Imp13 mutant (D426R) with a defect in Ubc9 binding could not promote the nuclear accumulation of Ubc9-WT. Lastly, we demonstrated that the Ubc9 mutants (R17E, R13A and H20D) with a defect in SUMO-binding have an elevated cytoplasmic distribution when compared to Ubc9-WT, suggesting that the non-covalent interaction between Ubc9 and SUMO is also important for Ubc9 nuclear accumulation. Hence, our results support a model that both Imp13-mediated nuclear import and the SUMO-binding activity of Ubc9 are critical for Ubc9 nuclear localization and efficient global sumoylation in mammalian cells

Optimization Models for Cost Efficient and Environmentally Friendly Supply Chain Management

This dissertation aims to provide models which will help companies make sustainable logistics management and transportation decisions. These models are extensions of the economic lot sizing model with the availability of multiple replenishment modes. The objective of the models is to minimize total replenishment costs and emissions. The study provides applications of these models on contemporary supply chain problems. Initially, the impact of carbon regulatory mechanisms on the replenishment decisions are analyzed for a biomass supply chain under fixed charge replenishment costs. Then, models are extended to consider multiple-setups replenishment costs for age dependent perishable products. For a cost minimization objective, solution algorithms are proposed to solve cases where one, two or multiple replenishment modes are available. Finally, using a bi-objective model, tradeoffs in costs and emissions are analyzed in a perishable product supply chain