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Around a third of the total population of Europe suffers from mental disorders. The use of electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose mental disorders has recently been shown to be a prominent research area, as exposed by several reviews focused on the field. Nevertheless, previous to the application of ML algorithms, EEG data should be correctly preprocessed and prepared via Feature Engineering (FE). In fact, the choice of FE techniques can make the difference between an unusable ML model and a simple, effective model. In other words, it can be said that FE is crucial, especially when using complex, non-stationary data such as EEG. To this aim, in this paper we present a Systematic Mapping Study (SMS) focused on FE from EEG data used to identify mental disorders. Our SMS covers more than 900 papers, making it one of the most comprehensive to date, to the best of our knowledge. We gathered the mental disorder addressed, all the FE techniques used, and the Artificial Intelligence (AI) algorithm applied for classification from each paper. Our main contributions are: (i) we offer a starting point for new researchers on these topics, (ii) we extract the most used FE techniques to classify mental disorders, (iii) we show several graphical distributions of all used techniques, and (iv) we provide critical conclusions for detecting mental disorders. To provide a better overview of existing techniques, the FE process is divided into three parts: (i) signal transformation, (ii) feature extraction, and (iii) feature selection. Moreover, we classify and analyze the distribution of existing papers according to the mental disorder they treat, the FE processes used, and the ML techniques applied. As a result, we provide a valuable reference for the scientific community to identify which techniques have been proven and tested and where the gaps are located in the current state of the art. [ABSTRACT FROM AUTHOR]

The number of references per paper, perhaps the best single index of a journal's scholarliness, has been studied in different disciplines and periods. In this paper we present a four decade study of eight engineering journals. A data set of over 70,000 references was generated after automatic data gathering and manual inspection for errors. Results show a significant increase in the number of references per paper, the average rises from 8 in 1972 to 25 in 2013. This growth presents an acceleration around the year 2000, consistent with a much easier access to search engines and documents produced by the generalization of the Internet. [ABSTRACT FROM AUTHOR]

The article presents the outcome of the discussions by members of the steering committee of the International Electrical and Electronic Engineering Requirements Engineering (RE) Conference, regarding paper classification and evaluation criteria for RE papers. Section two of the article sketches the rationale for the classification. Section three presents the classification, and section four concludes with a discussion of background ideas and related work.

The article offers information about the Global Conference on Wireless and Optical Communications held on 18th till 20th September, 2017 in Spain organized by University of Malaga and Mehran University of Engineering and Technology. It talks about water management Cyber Physical System, controlling actuator with the internet, monitoring sensors, the speed in the network, having an interactive physiotherapy by packaging them into virtual reality and lightning detection system.

This paper was triggered by concerns about the methodological soundness of many RE papers. We present a conceptual framework that distinguishes design papers from research papers, and show that in this framework, what is called a research paper in RE is often a design paper. We then present and motivate two lists of evaluation criteria, one for research papers and one for design papers. We apply both of these lists to two samples drawn from the set of all submissions to the RE’03 conference. Analysis of these two samples shows that most submissions of the RE’03 conference are design papers, not research papers, and that most design papers present a solution to a problem but neither validate this solution nor investigate the problems that can be solved by this solution. We conclude with a discussion of the soundness of our results and of the possible impact on RE research and practice. [ABSTRACT FROM AUTHOR]

An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive entities or collective ones that consist of several collaborating entities. Rigorous engineering requires appropriate methods and tools that help guaranteeing that an adaptive system lives up to its intended purpose. This paper introduces the special section on "Rigorous Engineering of Collective Adaptive Systems." It presents the 11 contributions of the section categorizing them into five distinct research lines: correctness by design and synthesis, computing with bio-inspired communication, new system models, machine learning, and programming and analyzing ensembles. [ABSTRACT FROM AUTHOR]

Origami, an ancient form of papercraft, provides a way to develop functional structures for engineering applications. In this paper, we report an approach to design and manufacture a stretchable circuit board (SCB) with origami structures. The benefits of developable, flat-foldable, and rigid-foldable origami-based structures as SCBs are discussed, and a representative structure, Miura fold (or Miura-ori), is chosen to be investigated. Under the constraints induced by the mounted components' dimensions, the Miura-ori structures for specific applications can be defined. We propose three methods for better fabrication, including direct folding, stiffness modification, and kirigami enhancement, to improve a planar sheet's foldability. A wearable ECG (electrocardiogram) system based on MO-SCB (Miura-ori enabled SCB) technology is built, and the stretchable portion is made of commercial FPCBs (flexible printed circuit board), providing desired stretchability and reliability. The proposed technology routine is compatible with industrial production and may pave the application of stretchable electronics. [ABSTRACT FROM AUTHOR]

The quality of requirements is typically considered as an important factor for the quality of the end product. For traditional up-front requirements specifications, a number of standards have been defined on what constitutes good quality : Requirements should be complete, unambiguous, specific, time-bounded, consistent, etc. For agile requirements specifications, no new standards have been defined yet, and it is not clear yet whether traditional quality criteria still apply. To investigate what quality criteria for assessing the correctness of written agile requirements exist, we have conducted a systematic literature review. The review resulted in a list of 16 selected papers on this topic. These selected papers describe 28 different quality criteria for agile requirements specifications. We categorize and analyze these criteria and compare them with those from traditional requirements engineering. We discuss findings from the 16 papers in the form of recommendations for practitioners on quality assessment of agile requirements. At the same time, we indicate the open points in the form of a research agenda for researchers working on this topic. [ABSTRACT FROM AUTHOR]

The German engineer H.A. Janssen gave one of the first accounts of the often peculiar behavior of granular material in a paper published in German in 1895. From simple experiments with corn he inferred the saturation of pressure with height in a granular system. Subsequently, Janssen derived the equivalent of the barometric formula for granular material from the main assumption that the walls carry part of the weight. The following is a translation of this article. The wording is chosen as close as possible to the original. While drawings are copied from the original, figures displaying data are redone for better readability. The translation is complemented by some bibliographical notes and an assessment of earlier work, wherein Hagen predicted the saturation of pressure with depth in 1852, and Huber-Burnand demonstrated that saturation qualitatively as early as in 1829. We conclude with a brief discussion of more recent developments resting on Janssen's work. [ABSTRACT FROM AUTHOR]

His main interests include resource optimization technique, adaptive resource provisioning, multi-objective optimization, computational intelligence, incomplete information processing, cloud computing, and security. The evaluation showed that these apps had an acceptable score on the System Usability Scale (SUS). The paper "Influence of Belbin's Role Theory on Database Design: Experimenting with Software Engineering Students" explores the benefits of using Belbin's role theory of team and individual related tasks in the software development process, particularly for Database Design (DB) Design. The authors argued that the usability evaluation described in this work can serve as a reference for developers seeking to improve learning monitoring and personalization services in software applications. [Extracted from the article]

Nanotechnology is a research field that has potential to drive the progress of mankind for the next few decades. Its application is found in every discipline, ranging from material science to space communication. Owing to its potential for ubiquity, and capability of replacing many general purpose technologies, co-existence of several paradigms are expected in nanotechnology. Flow Vergence (FV) gradient has been recently introduced as a metric to mine the network of scientific literature for detecting the paradigm shifts. In this paper, we have performed citation network analysis of scientific publications in nanotechnology from research area 'engineering' for identification of paradigms related to the same. Flow vergence gradient revealed 18 subnetworks that deal with 25 likely pivots of paradigm shifts. Major paradigm shifts can be found in the field of targeted drug delivery. Nanonetworks, a crossover of IT, BT and nanotechnology is the another interesting paradigm shift identified. An extended subnetwork analysis has been conducted to identify the competing or complementary nature of the emerging paradigms in the subnetworks. A framework for this has also been introduced. This analysis revealed that most of the paradigms in the targeted delivery are competing paradigms. Complementary paradigms are also identified in nano electronics and targeted drug delivery. Policy implications from this identification for various target groups are also discussed. [ABSTRACT FROM AUTHOR]

Provides an overview of selected papers that deals with different aspects of tool data integration techniques from a meta-modeling point of view, presented at the European Software Engineering Conference 2003 Workshop on Tool Integration in System Development, which took place on September 1-2, 2003 in Helsinki, Finland. Survey of model integration and transformation approaches; Suggested systematic approach for the development of the architecture of integrated development environments; List of sessions where the papers were presented.

Experimental Philosophy (X-Phi) is now a fully-fledged methodological project with applications in almost all areas of analytic philosophy, including, as of recently, aesthetics. Another methodological project which has been attracting attention in the last few years is conceptual engineering (CE). Its areas of implementation are now diverse, but as was the case initially with experimental philosophy, aesthetics has unfortunately been left out (or perhaps aestheticians have failed to pay attention to CE) until now. In this paper, I argue that if conceptual engineers are interested in expanding their project to the field of aesthetics, which would greatly benefit the field, then they should rely on the existing experimental work of aestheticians. Experimental philosophers have only recently started to join forces with conceptual engineers in various fields, as well as to explore the methodological implications of such an alliance. This paper goes a step further by not only arguing that CE has potential in aesthetics, but that the way to realize this potential is to piggyback, so to speak, on the work of experimental aestheticians. In other words, instead of building a CE project in aesthetics from the ground up, this paper describes the support that CE can and should derive from current experimental aesthetics, thereby making the former's development more efficiently realizable. Furthermore, I argue that doing so would also be beneficial to experimental aesthetics. Currently, the integration of X-Phi to the wider field of aesthetics is losing ground because certain objections—notably, the objection that X-Phi cannot be of relevance to normative questions—have not been properly refuted. By pairing up with a normative programme like CE, though, experimental aestheticians should finally be able to put these objections to rest. [ABSTRACT FROM AUTHOR]

A response from the author of the article "Feather structure, biomechanics and biomimetics: the incredible lightness of being" that was published in the 2014, volume 155 issue, is presented.

This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key mechanism to access the transformative capabilities of LLM AI in the learning process. This paper charts the evolving trajectory of LLM AI as a tool poised to reshape educational practices and assumptions. In particular, this paper breaks down the potential of prompt engineering practices to enhance learning by fostering personalized, engaging, and equitable educational experiences. The paper underscores how the natural language capabilities of LLM AI tools can help students and educators transition from passive recipients to active co-creators of their learning experiences. Critical thinking skills, particularly information literacy, media literacy, and digital citizenship, are identified as crucial for using LLM AI tools effectively and responsibly. Looking forward, the paper advocates for continued research to validate the benefits of prompt engineering practices across diverse learning contexts while simultaneously promoting potential defects, biases, and ethical concerns related to LLM AI use in education. It calls upon practitioners to explore and train educational stakeholders in best practices around prompt engineering for LLM AI, fostering progress towards a more engaging and equitable educational future. [ABSTRACT FROM AUTHOR]

The creation of blockchain-based software applications requires today considerable technical knowledge, particularly in software design and programming. This is regarded as a major barrier in adopting this technology in business and making it accessible to a wider audience. As a solution, low-code and no-code approaches have been proposed that require only little or no programming knowledge for creating full-fledged software applications. In this paper we extend a review of academic approaches from the discipline of model-driven engineering as well as industrial low-code and no-code development platforms for blockchains. This includes a content-based, computational analysis of relevant academic papers and the derivation of major topics. In addition, the topics were manually evaluated and refined. Based on these analyses we discuss the spectrum of approaches in this field and derive opportunities for further research. [ABSTRACT FROM AUTHOR]

The article discusses the IEEE International Requirements Engineering Conference (RE). This issue contains an introduction of the best papers presented during the conference on requirements activities in the fields of systems and software engineering. The conference was held at the University of Paris 1-Pantheon Sorbonne.

The article presents information on European Control Conferences that took place during 1991-2001. First European Control Conference was held in Grenoble, France in July 1991. Noteworthy is a high percentage of screened papers, which seems to be due to the fact that this was the first conference and a substantial part of papers were preplanned to some extent because they were presented at the 28 so-called invited sessions. The Seventh European Control Conference took place in Cambridge, Great Britain on September 14, 2003. The European Union recently pays much attention to increasing the standing of the European researchers in the international science and engineering. This was the main goal of organizing in 1990 the European Union Control Association.

Developers often encounter challenges with their introductory programming tasks as part of the development process. Unfortunately, rectifying these mistakes manually can be time-consuming and demanding. Automated program repair (APR) techniques offer a potential solution by synthesizing fixes for such errors. Previous research has investigated the utilization of both symbolic and neural techniques within the APR domain. However, these approaches typically demand significant engineering efforts or extensive datasets and training. In this paper, we explore the potential of using a large language model trained on code, specifically, we assess ChatGPT's capability to detect and repair bugs in simple Python programs. The experimental evaluation encompasses two benchmarks: QuixBugs and Textbook. Each benchmark consists of simple Python functions that implement well-known algorithms and each function contains a single bug. To gauge repair performance in various settings, several benchmark variations were introduced including addition of plain English documentation and code obfuscation. Based on thorough experiments, we found that ChatGPT was able to correctly detect and fix about 50% of the methods, when code is documented. Repair performance drops to 25% when code is obfuscated, and 15% when documentation is removed and code is obfuscated. Furthermore, when compared to existing APR systems, ChatGPT considerably outperformed them. [ABSTRACT FROM AUTHOR]

Water hyacinth (Eichhornia crassipes) is considered a prospective free-floating aquatic plant potentially used to address current issues on food, energy, and the environment. It can grow quickly and easily in various tropical and subtropical environments as long as it has access to adequate light and water to support photosynthetic growth. Ecosystems are threatened by their invasive growth and remarkable capacity for adaptation. However, managing this plant can result in valuable products. This paper demonstrates particle technologies that might be used to utilize water hyacinths, including brake pads, fertilizer, bioenergy, animal feed, phytoremediation agents, bioplastics, and adsorbents. This study is accompanied by a discussion based on the conducted experiments and currently available literature, providing readers with a clearer understanding. Water hyacinth's capacity to absorb macro- and micro-nutrients, nitrogen, and phosphorus makes it a good plant for phytoremediation. The prospect of producing cellulose makes it prospective as a biomass energy source and livestock feeding. Further, it can be transformed into high-cellulose content particles for applications in bioplastics, brake pads, and adsorbents. The current reports regarding education of water hyacinth to student also were added. Finally, issues and suggestions for future development related to the use of water hyacinths are discussed. This study is expected to provide comprehensive knowledge on how to turn invasive water hyacinth plants into valuable products. [ABSTRACT FROM AUTHOR]

Many engineering problems are essentially expensive multi-/many-objective optimization problems, and surrogate-assisted evolutionary algorithms have gained widespread attention in dealing with them. As the objective dimension increases, the error of predicting solutions based on surrogate models accumulates. Existing algorithms do not have strong selection pressure in the candidate solution obtaining and adaptive sampling stages. These make the effectiveness and area of application of the algorithms unsatisfactory. Therefore, this paper proposes a two-risk archive algorithm, which contains a strategy for mining high-risk and low-risk archives and a four-state adaptive sampling criterion. In the candidate solution mining stage, two types of Kriging models are trained, then conservative optimization models and non-conservative optimization models are constructed for model searching, followed by archive selection to obtain more reliable two-risk archives. In the adaptive sampling stage, in order to improve the performance of the algorithms, the proposed criterion considers environmental assessment, demand assessment, and sampling, where the sampling approach involves the improvement of the comprehensive performance in reliable environments, convergence and diversity in controversial environments, and surrogate model uncertainty. Experimental results on numerous benchmark problems show that the proposed algorithm is far superior to seven state-of-the-art algorithms in terms of comprehensive performance. [ABSTRACT FROM AUTHOR]

Dynamic Tensor Inversion (DTI) is an emerging issue in recent research, prevalent in artificial intelligence development frameworks such as TensorFlow and PyTorch. Traditional numerical methods suffer significant lagging error when addressing this issue. To address this, Zeroing-type Neural Dynamics (ZND) and Gradient-type Neural Dynamics (GND) are employed to tackle the DTI. However, these two methods exhibit inherent limitations in the resolution process, i.e. high computational complexity and low solution accuracy, respectively. Motivated by this technology gap, this paper proposes an Adaptive Coefficient Gradient Neural Dynamics (ACGND) for dynamically solving the DTI with an efficient and precise manner. Through a series of simulation experiments and validations in engineering applications, the ACGND demonstrates advantages in resolving DTI. The ACGND enhances computational efficiency by circumventing matrix inversion, thereby reducing computational complexity. Moreover, its incorporation of adaptive coefficients and activation functions enables real-time adjustments of the computational solution, facilitating rapid convergence to theoretical solutions and adaptation to non-statinary scenarios. Code is available at https://github.com/Maia2333/ACGND-Code-Implementation. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of finding the necessary and sufficient conditions to be satisfied by the engineering moduli of an anisotropic material for the elastic energy to be positive for each state of strain or stress. The problem is solved first in the most general case of a triclinic material and then each possible case of elastic syngony is treated as a special case. The method of analysis is based upon a rather forgotten theorem of linear algebra and, in the most general case, the calculations, too much involved, are carried out using a formal computation code. New, specific bounds, concerning some of the technical constants, are also found. [ABSTRACT FROM AUTHOR]

Mechanical equipment usually operates in noisy and variable load environments, which presents serious challenges for existing intelligent diagnostic models. In addition, there are few labelled fault samples in real engineering scenarios, which makes it difficult to perform accurate fault identification for mechanical equipment. Thus, to solve the problem of diagnostic model performance degradation under small sample, noisy and variable load environments, this paper proposes a Multiscale Dilated Convolution and Swin-Transformer (MSDC-Swin-T) method for small sample gearbox fault diagnosis. First, we design the Coordinate Reconstruction Attention Mechanism (CRAM), which enhances the capture of impulse information by coordinate reconstruction. In addition, a multiscale convolutional token embedding module is constructed to extract local features at different scales, and its ability for capturing important features is adaptively enhanced by CRAM. Then, Swin-Transformer is utilized for modeling global dependencies, thus mining more subtle fault features. Finally, the effectiveness and stability of the MSDC-Swin-T is proved on two gearbox datasets. The experiments show that MSDC-Swin-T has superior diagnostic performance under small sample with noise and variable load environments. The diagnostic accuracy is better than the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The paper reveals a small chapter of the history of the development of metallurgical science and technology in the Soviet Union. The point at issue is the development of scientific contacts between the American and Soviet metallurgical scientists in the second half of the 1950s. The successes of the USSR in the space race had demonstrated to the Western countries the real scientific and economic power of the country and thus shown both the unconstructiveness of the policy of isolation and the benefits of economic cooperation. The high level of development of metallurgical science and technology in the USSR had thus surprised the American specialists. The Ural Polytechnic Institute was one of those universities visited by the American guests. This paper is devoted to this chapter of history and continues the material published earlier. [ABSTRACT FROM AUTHOR]

Complexity is often regarded as a "problem" to solve. Instead of attempting to solve complexity, we follow systems engineering practices and switch back to the problem domain, where a major obstacle is the impossibility to universally define complexity. As a workaround, we explored complexity characterization and its existing shortcomings, including: lack of standardization, inconsistent semantics, system-centricity, insufficiently transparent reasoning, and lack of validation. To address these shortcomings, we proposed a compilatory framework to characterize complexity using the Five Ws information-gathering method. The answer to the WHO question proposed four complexity viewpoints; the answer to the WHY question proposed a two-dimensional structure for complexity drivers; and the answer to the WHAT question derived generalized complexity challenges. As a preliminary step to show the potential of the framework to characterize complexity, we used and validated it as a tool to structure general literature related to complexity. In general, our findings suggest that papers with complexity solutions do not frame their research within the complexity problem domain, hindering the contribution evaluation. Through the viewpoints, we identified general research gaps of six solution directions. From the drivers, we noted three observations in the discourse of complexity origins: (1) a system-driven tendency, (2) a preference for concreteness vs. abstraction, and (3) an unclear distinction between origins and effects. Through the challenges' findings we explored two hypotheses: (1) a system-centric preference; and (2) a solution-oriented vision, both of which were supported by the results (most challenges relate to the system viewpoint and challenges are defined based on solution directions). [ABSTRACT FROM AUTHOR]

Due to the influence of the Next Generation Science Standards (NGSS), the National Research Council's (NRC) Framework for K-12 Science Education, and a socio-workforce push to increase diverse representation in STEM fields, engineering education has become more prevalent in K-12 classrooms over the past decade. Although this shift is seemingly optimistic, critical consideration must be given to the ways engineering education tends to be reductive and positivistic, mimicking engineering practices decontextualized from high-stakes socio-political and socio-ecological realities through the adherence of a closed, systematic design process. Teaching and learning that is situated within the confines of normative engineering learning fail to nurture and cultivate students' intellectual health and ontological security, and further promotes destructive settler ecologics. This study took up efforts to disrupt and desettle engineering education, which opened space for children to critically speculate about real-world engineering entanglements deeply connected to their futurities. The aims of this paper are to (1) establish the need for anticolonial engineering, and engineering education, (2) promote approaches for doing so (3) and elevate the just worlding engineering design principles put forward by radically caring children committed to socio-ecological and multispecies justice. The learning shared in this paper suggests not only why science and engineering fields and education should be reformed, but also provides guidance for evolving the designing of shared worlds, for kincentric flourishing. [ABSTRACT FROM AUTHOR]

This theme section brings together the latest research at the intersection of artificial intelligence (AI) and model-driven engineering (MDE). Over the past years, we have witnessed a substantial rise of AI successfully applied to different domains, including software development and MDE. Dedicated events at the intersection of AI and MDE have been created, too, such as the MDE Intelligence workshop series co-located with the MODELS conference. This theme section covers research contributions integrating AI components into MDE approaches—increasing the current benefits of MDE processes and tools and pushing the limits of "classic" MDE with the goal to provide software and systems engineers with the right techniques to develop the next generation of highly complex model-based systems—and applications of MDE to the development of AI components. In total, nine submissions were accepted in the theme section after a thorough peer-reviewing process. [ABSTRACT FROM AUTHOR]

Ontologies constitute the semantic model of Knowledge Graphs (KGs). This structural association indicates the potential existence of methodological analogies in the development of ontologies and KGs. The deployment of fully and well-defined methodologies for KG development based on existing ontology engineering methodologies (OEMs) has been suggested and efficiently applied. However, most of the modern/recent OEMs may not include tasks that (i) empower knowledge workers and domain experts to closely collaborate with ontology engineers and KG specialists for the development and maintenance of KGs, (ii) satisfy special requirements of KG development, such as (a) ensuring modularity and agility of KGs, (b) assessing and mitigating bias at schema and data levels. Toward this aim, the paper presents a methodology for the Collaborative and Hybrid Engineering of Knowledge Graphs (CHEKG), which constitutes a hybrid (schema-centric/top-down and data-driven/bottom-up), collaborative, agile, and iterative approach for developing modular and fair domain-specific KGs. CHEKG contributes to all phases of the KG engineering lifecycle: from the specification of a KG to its exploitation, evaluation, and refinement. The CHEKG methodology is based on the main phases of the extended Human-Centered Collaborative Ontology Engineering Methodology (ext-HCOME), while it adjusts and expands the individual processes and tasks of each phase according to the specialized requirements of KG development. Apart from the presentation of the methodology per se, the paper presents recent work regarding the deployment and evaluation of the CHEKG methodology for the engineering of semantic trajectories as KGs generated from unmanned aerial vehicles (UAVs) data during real cultural heritage documentation scenarios. [ABSTRACT FROM AUTHOR]

Model-driven engineering (MDE) is believed to have a significant impact in software quality. However, researchers and practitioners may have a hard time locating consolidated evidence on this impact, as the available information is scattered in several different publications. Our goal is to aggregate consolidated findings on quality in MDE, facilitating the work of researchers and practitioners in learning about the coverage and main findings of existing work as well as identifying relatively unexplored niches of research that need further attention. We performed a tertiary study on quality in MDE, in order to gain a better understanding of its most prominent findings and existing challenges, as reported in the literature. We identified 22 systematic literature reviews and mapping studies and the most relevant quality attributes addressed by each of those studies, in the context of MDE. Maintainability is clearly the most often studied and reported quality attribute impacted by MDE. Eighty out of 83 research questions in the selected secondary studies have a structure that is more often associated with mapping existing research than with answering more concrete research questions (e.g., comparing two alternative MDE approaches with respect to their impact on a specific quality attribute). We briefly outline the main contributions of each of the selected literature reviews. In the collected studies, we observed a broad coverage of software product quality, although frequently accompanied by notes on how much more empirical research is needed to further validate existing claims. Relatively, little attention seems to be devoted to the impact of MDE on the quality in use of products developed using MDE. [ABSTRACT FROM AUTHOR]