Related papers: Towards an Assessment-oriented Model for External …
Data quality is commonly defined as fitness for use. The problem of identifying quality of data is faced by many data consumers. Data publishers often do not have the means to identify quality problems in their data. To make the task for…
Artificial Intelligence is increasingly introduced into systems engineering activities, particularly within requirements engineering, where quality assessment and validation remain heavily dependent on expert judgment. While recent AI tools…
Systematic benchmark evaluation plays an important role in the process of improving technologies for Question Answering (QA) systems. While currently there are a number of existing evaluation methods for natural language (NL) QA systems,…
This paper provides an extension of MDA called Context-aware Quality Model Driven Architecture (CQ-MDA) which can be used for quality control in pervasive computing environments. The proposed CQ-MDA approach based on ContextualArchRQMM…
With so many articles of varying qualities being produced every moment, it is a very urgent task to screen outstanding articles and commit them to social media. To our best knowledge, there is a lack of datasets and mature research works in…
Information-driven networks include a large category of networking systems, where network nodes are aware of information delivered and thus can not only forward data packets but may also perform information processing. In many situations,…
Intelligent systems and advanced automation are involved in information collection and evaluation, in decision-making and in the implementation of chosen actions. In such systems, human responsibility becomes equivocal. Understanding human…
This paper advances theory on the process of collaboration between entities and its implications on the quality of services, information, and/or products (SIPs) that the collaborating entities provide to each other. It investigates the…
The large increase in the number of Internet of Things (IoT) devices have revolutionised the way data is processed, which added to the current trend from cloud to edge computing has resulted in the need for efficient and reliable data…
The Internet of Things (IoT) paradigm is expected to bring ubiquitous intelligence through new applications in order to enhance living and other environments. Several research and standardization studies are now focused on the Middleware…
Context: Software quality is a complex concept. Therefore, assessing and predicting it is still challenging in practice as well as in research. Activity-based quality models break down this complex concept into concrete definitions, more…
The growth of machine learning (ML) models and associated datasets triggers a consequent dramatic increase in energy costs for the use and training of these models. In the current context of environmental awareness and global sustainability…
Software intensive systems play a crucial role in most, if not all, aspects of modern society. As such, both their sustainability and their role in supporting sustainable processes, must be realized by design. To this aim, the architecture…
Due to the existence of quality degradations introduced in various stages of visual signal acquisition, compression, transmission and display, image quality assessment (IQA) plays a vital role in image-based applications. According to…
Training large language models (LLMs) for external tool usage is a rapidly expanding field, with recent research focusing on generating synthetic data to address the shortage of available data. However, the absence of systematic data…
Data Quality (DQ) describes the degree to which data characteristics meet requirements and are fit for use by humans and/or systems. There are several aspects in which DQ can be measured, called DQ dimensions (i.e. accuracy, completeness,…
The paper describes a Multisource AI Scorecard Table (MAST) that provides the developer and user of an artificial intelligence (AI)/machine learning (ML) system with a standard checklist focused on the principles of good analysis adopted by…
To facilitate effective translation modeling and translation studies, one of the crucial questions to address is how to assess translation quality. From the perspectives of accuracy, reliability, repeatability and cost, translation quality…
Automated and robust portrait quality assessment (PQA) is of paramount importance in high-impact applications such as smartphone photography. This paper presents FHIQA, a learning-based approach to PQA that introduces a simple but effective…
Component-based design paradigm is of paramount importance due to prolific growth in the complexity of modern-day systems. Since the components are developed primarily by multi-party vendors and often assembled to realize the overall…