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In this paper, we propose a novel Artificial Neural Network (ANN) to predict software effort from use case diagrams based on the Use Case Point (UCP) model. The inputs of this model are software size, productivity and complexity, while the output is the predicted software effort. A multiple linear regression model with three independent variables (same(More)
We developed an algorithm for processing networked vital signs (VS) to remotely identify in real-time when a patient enters and leaves a given operating room (OR). The algorithm addresses two types of mismatches between OR occupancy and VS: a patient is in the OR but no VS are available (e.g., patient is being hooked up), and no patient is in the OR but(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t Software estimation is a tedious and daunting task in project(More)
Software effort estimation is one of the most important tasks in software engineering. Software developers conduct software estimation in the early stages of the software life cycle to derive the required cost and schedule for a project. In the requirements stage, where most software estimation is conducted, the available information is usually imprecise or(More)
Software effort prediction is an important task in the software development life cycle. Many models including regression models, machine learning models, algorithmic models, expert judgment and estimation by analogy have been widely used to estimate software effort and cost. In this work, a Tree boost (Stochastic Gradient Boosting) model is put forward to(More)
It is very important to conduct software estimation in the early stages of the software life cycle, because it helps managers bid on projects and allocate resources efficiently. This paper presents a novel regression model to estimate the software effort based on the use case point size metric. The use case point model takes use case diagrams as input and(More)
Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. So far, no model has proved to be successful at effectively and consistently predicting software development cost. A novel neuro-fuzzy Constructive Cost Model (COCOMO) is proposed for software cost estimation. This(More)
Software cost estimation is a crucial element in project management. Failing to use a proper cost estimation method might lead to project failures. According to the Standish Chaos Report, 65% of software projects are delivered over budget or after the delivery deadline. Conducting software cost estimation in the early stages of the software life cycle is(More)