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Classification and Feature Selection of Alzheimer’s Disease for MRI Data Utilizing Convolutional Neural Network and Support Vector Machine
Alzheimer's disease (AD) is a neurological disease that affect numerous people. According to the literature, forecasting this type of disease can be...
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iDOCEM
In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design...
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Interactive search-based Product Line Architecture design
Software Product Line (SPL) is an approach derived from other engineering fields that use reuse techniques for a family of products in a given...
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Formally understanding Rust’s ownership and borrowing system at the memory level
Rust is an emergent systems programming language highlighting memory safety through its Ownership and Borrowing System (OBS). Formalizing OBS in...
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An agent-based persuasion model using emotion-driven concession and multi-objective optimization
Multi-attribute negotiation is essentially a multi-objective optimization (MOO) problem, where models of agent-based emotional persuasion (EP) can...
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Requirements for modelling tools for teaching
Modelling is an important activity in software development and it is essential that students learn the relevant skills. Modelling relies on dedicated...
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Exploiting recurrent graph neural networks for suffix prediction in predictive monitoring
Predictive monitoring is a subfield of process mining that aims to predict how a running case will unfold in the future. One of its main challenges...
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Deep learning-based classification and application test of multiple crop leaf diseases using transfer learning and the attention mechanism
Crop diseases are among the major natural disasters in agricultural production that seriously restrict the growth and development of crops,...
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Real-time scheduling of power grid digital twin tasks in cloud via deep reinforcement learning
As energy demand continues to grow, it is crucial to integrate advanced technologies into power grids for better reliability and efficiency. Digital...
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ASDMG: business topic clustering-based architecture smell detection for microservice granularity
Microservices architecture smells can significantly affect the quality of microservices due to poor design decisions, especially the granularity...
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Optimizing regression testing with AHP-TOPSIS metric system for effective technical debt evaluation
Regression testing is essential to ensure that the actual software product confirms the expected requirements following modification. However, it can...
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Optimizing pre-copy live virtual machine migration in cloud computing using machine learning-based prediction model
One of the preconditions for efficient cloud computing services is the continuous availability of services to clients. However, there are various...
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From large language models to small logic programs: building global explanations from disagreeing local post-hoc explainers
The expressive power and effectiveness of large language models (LLMs) is going to increasingly push intelligent agents towards sub-symbolic models...
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AutoRAG: Grounding Text and Symbols
In safety critical domains such as the healthcare domain, systems for natural language question answering demand special correctness guarantees....
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Navigating in a space of game views
Game-theoretic modeling entails selecting the particular elements of a complex strategic situation deemed most salient for strategic analysis....
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A clarity and fairness aware framework for selecting workers in competitive crowdsourcing tasks
Crowdsourcing is a powerful technique for accomplishing tasks that are difficult for machines but easy for humans. However, ensuring the quality of...
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Fixing Dockerfile smells: an empirical study
Docker is the de facto standard for software containerization. A Dockerfile contains the requirements to build a Docker image containing a target...
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Periodic and random incremental backup policies in reliability theory
For a 24/7 database system, backups should be implemented right after a large volume of data has been updated, putting their backup windows in...
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Augmenting Cervical Cancer Analysis with Deep Learning Classification and Topography Selection Using Artificial Bee Colony Optimization
According to the research and study, cervical cancer has risen to develop the fourth most communal malignancy to strike women. Five different forms...
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Enhancing Forecasting Accuracy with a Moving Average-Integrated Hybrid ARIMA-LSTM Model
This research provides a time series forecasting model that is hybrid which combines Long Short-Term Memory (LSTM) and Autoregressive Integrated...
