scholarly journals Lessons Learnt from Gauging Software Metrics of Cabin Software in a Commercial Airliner

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Stefan Burger ◽  
Oliver Hummel
Keyword(s):  
Real Time ◽  
Software Metrics ◽  
Current Practice ◽  
Time Constraints ◽  
Software Systems ◽  
Safety Standards ◽  
Lessons Learnt ◽  
Very High

In order to achieve high safety standards, avionic software needs to be developed with very high requirements regarding safety, reliability, and determinism as well as real-time constraints, which are often in conflict with the development of maintainable software systems. Nevertheless, the ability to change the software of an airplane is of increasing importance, since it consists of a multitude of partially hardware-specific subsystems which may need replacement during a plane’s lifespan of typically numerous decades. Thus, as a first step towards optimizing maintainability of avionic software we have benchmarked the cabin software of a commercial airliner with common software metrics. Such a benchmarking of avionic software contributes valuable insights into the current practice of developing critical software and the application of software metrics in this context. We conclude from the obtained results that it is important to pay more attention to long-term maintainability of aviation software. Additionally we have derived some initial recommendations for the development of future avionic software systems.

Aerodynamics – A discipline swept away?

2010 ◽  
Vol 114 (1160) ◽  
pp. 599-609 ◽  
Author(s):  
C.-C. Rossow
Keyword(s):  
High Performance ◽  
Applied Research ◽  
Air Transport ◽  
Swept Wing ◽  
Safety Standards ◽  
New Challenges ◽  
Natural Laminar Flow ◽  
Very High ◽  
Technological Perspective

Abstract This contribution is based on the Lanchester Lecture of the Royal Aeronautical Society held in Manchester, UK, in October 2009. The lecture reflected on further possible perspectives for aeronautical research, in particular with respect to aerodynamics. The air transport system of today has matured to very high performance and safety standards. However, due to the ongoing global developments of economy and ecology, new challenges have to be faced. Thus, the relevance of all engineering aeronautical disciplines contributing to the final aircraft configuration is now closely scrutinised, and especially aerodynamics is challenged whether any investment in further research is still justified. In this contribution, it is argued that, when carefully exploited, aerodynamics still offers a substantial technological perspective, well beyond the concepts for the next generation of aircraft as currently being pursued. As an example, the aerodynamics of a forward swept-wing are discussed and it is outlined that, when combining the transonic characteristics of a forward swept-wing with the advantages of natural laminar-flow, considerable improvements in efficiency may be gained. However, this potential may only be leveraged through a strategic, long-term orientation of fundamental and applied research.

A Literature Review Study of Software Defect Prediction using Machine Learning Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 300 ◽  
Author(s):  
Feidu Akmel ◽  
Ermiyas Birihanu ◽  
Bahir Siraj
Keyword(s):  
Machine Learning ◽  
Software Metrics ◽  
Quality Standard ◽  
Machine Learning Techniques ◽  
Software Systems ◽  
Health Care Insurance ◽  
Software Defect ◽  
Learning Techniques ◽  
Software Product

Software systems are any software product or applications that support business domains such as Manufacturing,Aviation, Health care, insurance and so on.Software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from other for this reason it is better to apply the software metrics to measure the quality of software. Attributes that we gathered from source code through software metrics can be an input for software defect predictor. Software defect are an error that are introduced by software developer and stakeholders. Finally, in this study we discovered the application of machine learning on software defect that we gathered from the previous research works.

SATELLITE DATA FOR INVESTIGATION OF RECENT STATE AND PROCESSES IN THE SIVASH BAY

2017 ◽  
Author(s):  
Ekaterina Shchurova ◽  
Ekaterina Shchurova ◽  
Rimma Stanichnaya ◽  
Rimma Stanichnaya ◽  
Sergey Stanichny ◽  
...  
Keyword(s):  
Satellite Data ◽  
Water Exchange ◽  
High Salinity ◽  
Meteorological Data ◽  
Sea Surface ◽  
Azov Sea ◽  
Seasonal Wind ◽  
Ice Regime ◽  
Very High

Sivash bay is the shallow-water lagoon of the Azov Sea. Restricted water exchange and high evaporation form Sivash as the basin with very high salinity. This factor leads to different from the Azov Sea thermal and ice regimes of Sivash. Maine aim of the study presented to investigate recent state and changes of the characteristics and processes in the basin using satellite data. Landsat scanners TM, ETM+, OLI, TIRS together with MODIS and AVHRR were used. Additionally NOMADS NOAA and MERRA meteorological data were analyzed. The next topics are discussed in the work: 1. Changes of the sea surface temperature, ice regime and relation with salinity. 2. Coastal line transformation – long term and seasonal, wind impact. 3. Manifestation of the Azov waters intrusions through the Arabat spit, preferable wind conditions.

Positive Emotions

2009 ◽  
pp. 12-24 ◽  
Author(s):  
Michael A. Cohn ◽  
Barbara L. Fredrickson
Keyword(s):  
Positive Emotions ◽  
Well Being ◽  
Life Outcomes ◽  
Short Term ◽  
Future Success ◽  
Broaden And Build Theory ◽  
Mental And Physical Health ◽  
Very High ◽  
Future Growth

Positive emotions include pleasant or desirable situational responses, ranging from interest and contentment to love and joy, but are distinct from pleasurable sensation and undifferentiated positive affect. These emotions are markers of people's overall well-being or happiness, but they also enhance future growth and success. This has been demonstrated in work, school, relationships, mental and physical health, and longevity. The broaden-and-build theory of positive emotions suggests that all positive emotions lead to broadened repertoires of thoughts and actions and that broadening helps build resources that contribute to future success. Unlike negative emotions, which are adapted to provide a rapid response to a focal threat, positive emotions occur in safe or controllable situations and lead more diffusely to seeking new resources or consolidating gains. These resources outlast the temporary emotional state and contribute to later success and survival. This chapter discusses the nature of positive emotions both as evolutionary adaptations to build resources and as appraisals of a situation as desirable or rich in resources. We discuss the methodological challenges of evoking positive emotions for study both in the lab and in the field and issues in observing both short-term (“broaden”) and long-term (“build”) effects. We then review the evidence that positive emotions broaden perception, attention, motivation, reasoning, and social cognition and ways in which these may be linked to positive emotions' effects on important life outcomes. We also discuss and contextualize evidence that positive emotions may be detrimental at very high levels or in certain situations. We close by discussing ways in which positive emotions theory can be harnessed by both basic and applied positive psychology research.

scholarly journals A Novel Rail-Network Hardware Simulator for Embedded System Programming

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Balaji M ◽  
Chandrasekaran M ◽  
Vaithiyanathan Dhandapani
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Real Time ◽  
Learning Outcomes ◽  
Real World ◽  
Time Constraints ◽  
Network Simulator ◽  
Practical Applications ◽  
Rail Network ◽  
Knowledge Enhancement

A Novel Rail-Network Hardware with simulation facilities is presented in this paper. The hardware is designed to facilitate the learning of application-oriented, logical, real-time programming in an embedded system environment. The platform enables the creation of multiple unique programming scenarios with variability in complexity without any hardware changes. Prior experimental hardware comes with static programming facilities that focus the students’ learning on hardware features and programming basics, leaving them ill-equipped to take up practical applications with more real-time constraints. This hardware complements and completes their learning to help them program real-world embedded systems. The hardware uses LEDs to simulate the movement of trains in a network. The network has train stations, intersections and parking slots where the train movements can be controlled by using a 16-bit Renesas RL78/G13 microcontroller. Additionally, simulating facilities are provided to enable the students to navigate the trains by manual controls using switches and indicators. This helps them get an easy understanding of train navigation functions before taking up programming. The students start with simple tasks and gradually progress to more complicated ones with real-time constraints, on their own. During training, students’ learning outcomes are evaluated by obtaining their feedback and conducting a test at the end to measure their knowledge acquisition during the training. Students’ Knowledge Enhancement Index is originated to measure the knowledge acquired by the students. It is observed that 87% of students have successfully enhanced their knowledge undergoing training with this rail-network simulator.

scholarly journals Copula-based software metrics aggregation

2021 ◽  
Author(s):  
Maria Ulan ◽  
Welf Löwe ◽  
Morgan Ericsson ◽  
Anna Wingkvist
Keyword(s):  
Open Source Software ◽  
Software Metrics ◽  
Information Quality ◽  
Empirical Studies ◽  
Probabilistic Approach ◽  
Software Systems ◽  
Quality Model ◽  
Quality Models ◽  
Joint Distributions ◽  
Abstract Notion

AbstractA quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance.

Prediction of aircraft engine emissions using ADS-B flight data

2021 ◽  
pp. 1-25
Author(s):  
A. Filippone ◽  
B. Parkes ◽  
N. Bojdo ◽  
T. Kelly
Keyword(s):  
Real Time ◽  
Water Vapour ◽  
Long Range ◽  
Aircraft Engine ◽  
Software Systems ◽  
Engine Emissions ◽  
Flight Data ◽  
Seasonal Basis ◽  
Emissions Inventories ◽  
Aviation Emissions

ABSTRACT Real-time flight data from the Automatic Dependent Surveillance–Broadcast (ADS-B) has been integrated, through a data interface, with a flight performance computer program to predict aviation emissions at altitude. The ADS-B, along with data from Mode-S, are then used to ‘fly’ selected long-range aircraft models (Airbus A380-841, A330-343 and A350-900) and one turboprop (ATR72). Over 2,500 flight trajectories have been processed to demonstrate the integration between databases and software systems. Emissions are calculated for altitudes greater than 3,000 feet (609m) and exclude landing and take-off cycles. This proof of concept fills a gap in the aviation emissions inventories, since it uses real-time flights and produces estimates at a very granular level. It can be used to analyse emissions of gases such as carbon dioxide ( $\mathrm{CO}_2$ ), carbon monoxide (CO), nitrogen oxides ( $\mathrm{NO}_x$ ) and water vapour on a specific route (city pair), for a specific aircraft, for an entire fleet, or on a seasonal basis. It is shown how $\mathrm{NO}_x$ and water vapour emissions concentrate around tropospheric altitudes only for long-range flights, and that the cruise range is the biggest discriminator in the absolute value of these and other exhaust emissions.

scholarly journals Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4597
Author(s):  
Zi-Xuan Yu ◽  
Meng-Shi Li ◽  
Yi-Peng Xu ◽  
Sheraz Aslam ◽  
Yuan-Kang Li
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Positive Impact ◽  
Environmental Aspects ◽  
Component Size ◽  
Cost Of Energy ◽  
Four Seasons ◽  
Demand Response Program ◽  
Real Time Pricing

The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand response (DR) program according to the national grid prices of Iran. In addition to the long-term planning of MG, the day-ahead operation of MG is also analyzed to get a better understanding of the DR program for daily electricity dispatch. For this purpose, four different days corresponding to the four seasons are selected for further analysis. In addition, various impacts of the proposed DR program on the MG planning results, including sizing and best configuration, net present cost (NPC) and cost of energy (COE), and emission generation by the utility grid, are investigated. The optimization results show that the implementation of the DR program has a positive impact on the technical, economic, and environmental aspects of MG. The NPC and COE are reduced by about USD 3700 and USD 0.0025/kWh, respectively. The component size is also reduced, resulting in a reduction in the initial cost. Carbon emissions are also reduced by 185 kg/year.

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