scholarly journals Consistency between Use Case, Sequence and Timing Diagram for Real Time Software Systems

2014 ◽  
Vol 85 (16) ◽  
pp. 17-23 ◽  
Author(s):  
Rumpa Hazra ◽  
Shouvik Dey
Keyword(s):  
Real Time ◽  
Software Systems ◽  
Use Case ◽  
Timing Diagram ◽  
Case Sequence

scholarly journals Using Actors and Use Cases for Software Size Estimation

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 592
Author(s):  
Radek Silhavy ◽  
Petr Silhavy ◽  
Zdenka Prokopova
Keyword(s):  
Project Planning ◽  
Use Cases ◽  
New Method ◽  
Software Systems ◽  
Software Project ◽  
Use Case ◽  
Size Estimation ◽  
Software Size Estimation ◽  
Use Case Points

Software size estimation represents a complex task, which is based on data analysis or on an algorithmic estimation approach. Software size estimation is a nontrivial task, which is important for software project planning and management. In this paper, a new method called Actors and Use Cases Size Estimation is proposed. The new method is based on the number of actors and use cases only. The method is based on stepwise regression and led to a very significant reduction in errors when estimating the size of software systems compared to Use Case Points-based methods. The proposed method is independent of Use Case Points, which allows the elimination of the effect of the inaccurate determination of Use Case Points components, because such components are not used in the proposed method.

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 Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks

2014 ◽  
Vol 23 (01) ◽  
pp. 27-35 ◽  
Author(s):  
S. de Lusignan ◽  
S-T. Liaw ◽  
C. Kuziemsky ◽  
F. Mold ◽  
P. Krause ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Predictive Analytics ◽  
Regulatory Compliance ◽  
Use Cases ◽  
Data Sources ◽  
Use Case ◽  
Crowd Sourcing ◽  
Big Data Processing

Summary Background: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowd-sourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the “internet of things”, and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

Real Time Risk Management in Cloud Computation

2013 ◽  
pp. 123-145
Author(s):  
Kashif Kifayat ◽  
Thar Baker Shamsa ◽  
Michael Mackay ◽  
Madjid Merabti ◽  
Qi Shi
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Risk Management ◽  
Real Time ◽  
Use Case ◽  
The Real ◽  
Security Issues ◽  
Processing Resources ◽  
Cloud Computation ◽  
Time Assessment

The rise of Cloud Computing represents one of the most significant shifts in Information technology in the last 5 years and promises to revolutionise how we view the availability and consumption of computing storage and processing resources. However, it is well-known that along with the benefits of Cloud Computing, it also presents a number of security issues that have restricted its deployment to date. This chapter reviews the potential vulnerabilities of Cloud-based architectures and uses this as the foundation to define a set of requirements for reassessing risk management in Cloud Computing. To fulfill these requirements, the authors propose a new scheme for the real-time assessment and auditing of risk in cloud-based applications and explore this with the use case of a triage application.

Measuring the Impact of the Semantic-Based Process Mining Approach

2020 ◽  
pp. 217-237
Keyword(s):  
Knowledge Base ◽  
Real Time ◽  
Learning Process ◽  
Conceptual Analysis ◽  
Process Mining ◽  
Levels Of Analysis ◽  
Use Case ◽  
Abstraction Levels ◽  
The Impact

This chapter looks at the extent to which the semantic-based process mining approach of this book supports the conceptual analysis of the events logs and resultant models. Qualitatively, the chapter leverages the use case study of the research learning process domain to determine how the proposed method support the discovery, monitoring, and enhancement of the real-time processes through the abstraction levels of analysis. Also, the chapter quantitatively assesses the level of accuracy of the classification process to predict behaviours of unobserved instances within the underlying knowledge base. Overall, the work looks at the implications of the semantic-based approach, validation of the classification results, and their influence compared to other existing benchmark techniques/algorithms used for process mining.

Use case-based evaluation of workflow optimization strategy in real-time computation system

2019 ◽  
Vol 76 (1) ◽  
pp. 708-725
Author(s):  
Saima Gulzar Ahmad ◽  
Hikmat Ullah Khan ◽  
Samia Ijaz ◽  
Ehsan Ullah Munir
Keyword(s):  
Real Time ◽  
Use Case ◽  
Optimization Strategy ◽  
Workflow Optimization ◽  
Case Based
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