Search

Modern tools for natural language generation may enable novel forms of scholarly fraud based on the automatic generation of fake review reports for academic papers, i.e., of a few sentences broadly related to the textual content of a submission and written with the style of an anonymous reviewer. A tool capable of generating such reports automatically and for free could enable various forms of unethical behavior by publishers and researchers. In this work we experiment with a simple heuristic that makes use of widely available and easy to use tools for natural language generation, including the Generative Pretrained Transformer 2 (GPT-2), in order to craft fake reviews automatically. We also perform a small user study for assessing the credibility of those reviews. Our analysis suggests that academic frauds based on fake reviews may indeed be feasible and ready to be deployed in the wild.

Language is a valuable source of clinical information in Alzheimer's Disease, as it declines concurrently with neurodegeneration. Consequently, speech and language data have been extensively studied in connection with its diagnosis. This paper summarises current findings on the use of artificial intelligence, speech and language processing to predict cognitive decline in the context of Alzheimer's Disease, detailing current research procedures, highlighting their limitations and suggesting strategies to address them. We conducted a systematic review of original research between 2000 and 2019, registered in PROSPERO (reference CRD42018116606). An interdisciplinary search covered six databases on engineering (ACM and IEEE), psychology (PsycINFO), medicine (PubMed and Embase) and Web of Science. Bibliographies of relevant papers were screened until December 2019. From 3,654 search results 51 articles were selected against the eligibility criteria. Four tables summarise their findings: study details (aim, population, interventions, comparisons, methods and outcomes), data details (size, type, modalities, annotation, balance, availability and language of study), methodology (pre-processing, feature generation, machine learning, evaluation and results) and clinical applicability (research implications, clinical potential, risk of bias and strengths/limitations). While promising results are reported across nearly all 51 studies, very few have been implemented in clinical research or practice. We concluded that the main limitations of the field are poor standardisation, limited comparability of results, and a degree of disconnect between study aims and clinical applications. Attempts to close these gaps should support translation of future research into clinical practice., Comment: Pre-print submitted to the Journal of Alzheimer's Disease

Background Minimally invasive surgery (MIS), unlike open surgery in which surgeons can perform surgery directly, is performed using miniaturized instruments with indirect but careful observation of the surgical site. Objective Instrument detection is a crucial requirement in conventional and robot-assisted MIS, which can also be very useful during surgical training. In this paper, we propose a novel framework of using two three-layer convolutional neural networks (CNNs) in a series to detect surgical instrument in in-vivo video frames. Methods The two convolutional neural networks proposed in this paper have different tasks. (i) The former CNN is trained to detect the edges points of the instrument shaft directly from images patches. (ii) The latter is trained to locate the instrument tip also from images patches after the former detection finishes. Results We validated our method on the publicly available EndoVisSub dataset and a standard dataset, and it detected tools with an accuracy of 91.2% and 75% respectively. Conclusion Our two-step detection method achieves better performance than other existing approaches in terms of detection accuracy.

In this paper, we present our study regarding facilitating storytelling of older adults living in the nursing home with their children. The paper was driven by the following research questions: (1) What life stories would the older adults like to share? And (2) In which ways, could design enable the older adults to tell their stories? We designed a tangible device named Slots-Story, and conducted a preliminary evaluation to refine it. In the field study, eight pairs of participants (each pair consisted of an elderly adult and his/her child) were recruited to use the prototype for around ten days. Semi-structured interviews were conducted before and after the implementation. In total 344 stories were collected. Thematic, structural, and interaction analyses were conducted with the stories. In the discussion, we conclude the paper with design considerations for promoting older adults’ storytelling with their children.

Globally the manufacturing industry is undergoing a shift in the way product specifications are defined, used, and re-used from conventional drawing-based systems to a comprehensive 3D digital product model. This transformation is at the heart of the digitization processes. The true benefits lie in the adoption of this technology throughout the product lifecycle. However, this digital transformation is partial and many of the stages in the product lifecycle are still heavily reliant on traditional drawings. This is due to the involvement of several uncertainties in the process of adoption of model-based definition. In this paper, a framework is proposed for the systematic assessment of the prevailing uncertainties in the adoption of model-based definition and enterprise. The framework proposed in this paper is aimed at identifying, categorizing, prioritizing, and mitigating the uncertainties in this process.

Based on experiences with the development of a new research-based website on Universal Design meant to inspire and qualify the work of the Danish building sector, this paper examines the types of knowledge requested by professionals in the building sector when working with Universal Design. The Danish Transport, Construction and Housing Authority commissioned a website with the aim of increasing the building sector’s knowledge of Universal Design and supporting a change in attitude towards universal design. The site is intended to function as a platform for disseminating knowledge about Universal Design that can support the regulatory system. The empirical material of the study consists of data from qualitative interviews with actors from the building sector and workshops with the advisory board of the website. The analysis shows that, on one hand, the sector requires good examples of Universal Design and knowledge about users and their needs and, on the other hand, it needs detailed help such as comprehensive checklists to ensure the appropriate process is undertaken. However, technical information about, for example, the gradient of a ramp, does not contribute to an architectural idea and will not change any mindsets in regard to Universal Design. This paper reflects on the duality of requests from the sector using the theoretical concept of liminality. The paper describes and argues for the chosen approach for the website, namely focusing on inspiring and assisting professionals in the building sector to enhance their level of knowledge and support a change in practice towards Universal Design.

One of the main characteristics of humankind is the ability to interpret via natural language incomplete, imprecise, vague, subjective, fragmentary, or scarce information i.e. information in uncertainty and transform it to actions, reason and decision-making [9]. Fuzzy sets theory firstly introduced the treatment of such concepts in 1965 with the foremost influential paper "Fuzzy Sets" [29]. The groundbreaking standpoint of fuzzy systems allows the treatment of uncertain information with the utilization of a strict mathematical framework [8]. Ever since the publication of the pivotal paper from Zadeh, a plethora of contributions have shaped the fuzzy sets theory scope and applications, from developments in engineering, mathematics, computer, decision, life, physical, health, social sciences and humanities [17 (...)

Today, virtual reality and augmented reality can allow people to interact with products and places in a very realistic way. In this direction, the use of immersive virtual tours (VTs) can improve the users’ experience, their perceptions, attitudes and even intended behaviours as potential or actual consumers. The paper focuses on a traditional Italian cheese product and defines a transdisciplinary, multimodal approach where VT helps the remote customer experience based on a VT application to virtually visit a Parmigiano Reggiano cheese dairy, using cutting-edge virtual reality set-up. The paper describes how to create a virtual tour of industrial plants by mapping the main actions, from the storytelling definition, to the plant digitization, until the creation of the virtual, immersive and multimodal application using Unity3D. The VT combines visual experience with gesture recognition and audio stimulation, adding also olfactory cues, in order to create an interactive and realistic experience.

Nowadays companies have to face a competitive market that requires small volumes with a high level of customisations. In this context, assembly quality and timeliness is crucial. To guarantee flexibility and personalization, manual operations still have a crucial role for a lot of manufacturing sectors, so that workers’ conditions and ergonomics are important factors to achieve a better product quality and overall cost reduction. Ergonomics evaluation in manufacturing is a challenging and expensive activity that requires a transdisciplinary approach, to merge technical and social sciences to finally have a consolidated and reliable evaluation. This paper compared two digital human simulations tools offered by Siemens Tecnomatix: Jack and Process Simulate. They were applied on the same industrial case study, concerning the hood assembly of an agricultural machine, comparing results on ergonomics reports and usage time. Results confirmed the advantage of adopting a digital approach to predict the human effort and ergonomic risk related to a series of tasks. At the same time, they showed the major strengths and weaknesses of the two analysed tools and defined how they can be successfully adopted by companies. The paper finally provided guidelines to drive companies in choosing the best tool according to their needs.

This paper argues that energy consideration should be central to software development. It speculates that including the notion of energy awareness in programming language design for domain specific languages (DSLs) is a novel way in which energy-aware and energy-efficient applications can be developed. It outlines the design criteria and rationale for using a language-focused approach for energy-awareness. It proposes Lantern, a DSL for supporting energy awareness in Cyber-Physical Systems software development. Lantern allows the development of applications that better manage and reduce the carbon footprint of devices. The design of Lantern is aimed at supporting the general development of Cyber-Physical Systems. This paper focuses on the scenario of smart homes, using statically defined locations within a specified environment.

The identification of research topics and trends is an important scientometric activity, as it can help guide the direction of future research. In the Semantic Web area, initially topic and trend detection was primarily performed through qualitative, top-down style approaches, that rely on expert knowledge. More recently, data-driven, bottom-up approaches have been proposed that offer a quantitative analysis of the evolution of a research domain. In this paper, we aim to provide a broader and more complete picture of Semantic Web topics and trends by adopting a mixed methods methodology, which allows for the combined use of both qualitative and quantitative approaches. Concretely, we build on a qualitative analysis of the main seminal papers, which adopt a top-down approach, and on quantitative results derived with three bottom-up data-driven approaches (Rexplore, Saffron, PoolParty), on a corpus of Semantic Web papers published between 2006 and 2015. In this process, we both use the latter for “fact-checking” on the former and also to derive key findings in relation to the strengths and weaknesses of top-down and bottom-up approaches to research topic identification. Although we provide a detailed study on the past decade of Semantic Web research, the findings and the methodology are relevant not only for our community but beyond the area of the Semantic Web to other research fields as well.

This paper presents a general overview and a long-term comparison in fuzzy logic research published between 1965 and 2017, obtained via Web of Science. The paper analyzes the growth, impact, trends and regional localization of fuzzy re-search. Conventional, sophisticated among others bibliometric indicators have applies. It aggregates the information according to different levels and criteria including researchers, publications, institutions, or countries. A global perspective have been provided through comparisons of regional aggregates and compound annual growth rates that strengthen the indicators applied in this article. The results permit to visualize the influence, importance, evolution and performance of the fuzzy research as well its contribution to, and transversality with other fields. The findings show that China continues to be a leader in number of contributions. There has been a recent relative decline in the United States contributions overall. Asian and African contribu-tions to scientific literature have grown noticeably. The results also provide a framework for the use of indicators adjusted to specific contexts and relevant information for future research.

The combination of smart contracts with blockchain technology enables the authentication of the contract and limits the risks of non-compliance. In principle, smart contracts can be processed more efficiently compared to traditional paper-based contracts. However, current smart contracts have very limited capabilities with respect to normative representations, making them too distant from actual contracts. In order to reduce this gap, the paper presents an architectural analysis to see the role of computational artifacts in terms of various ex-ante and ex-post enforcement mechanisms. The proposed framework is assessed using scenarios concerning data-sharing operations bound by legal requirements from the General Data Protection Regulation (GDPR) and data-sharing agreements.

Online Analytical Processing (OLAP) comprises tools and algorithms that allow querying multidimensional databases. It is based on the multidimensional model, where data can be seen as a cube such that each cell contains one or more measures that can be aggregated along dimensions. In a Big Data scenario, traditional data warehousing and OLAP operations are clearly not sufficient to address current data analysis requirements, for example, social network analysis. Furthermore, OLAP operations and models can expand the possibilities of graph analysis beyond the traditional graph-based computation. Nevertheless, there is not much work on the problem of taking OLAP analysis to the graph data model. This paper proposes a formal multidimensional model for graph analysis, that considers the basic graph data, and also background information in the form of dimension hierarchies. The graphs in this model are node- and edge-labelled directed multi-hypergraphs, called graphoids, which can be defined at several different levels of granularity using the dimensions associated with them. Operations analogous to the ones used in typical OLAP over cubes are defined over graphoids. The paper presents a formal definition of the graphoid model for OLAP, proves that the typical OLAP operations on cubes can be expressed over the graphoid model, and shows that the classic data cube model is a particular case of the graphoid data model. Finally, a case study supports the claim that, for many kinds of OLAP-like analysis on graphs, the graphoid model works better than the typical relational OLAP alternative, and for the classic OLAP queries, it remains competitive., Comment: This is a draft version of the work that will appear in Volume 24(2) of the Intelligent Data Analysis Journal, in early 2020

Made available in DSpace on 2020-12-10T19:46:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) A multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise comparisons, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model. Sao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, Brazil Sao Paulo State Univ, Dept Prod, BR-12516410 Guaratingueta, SP, Brazil FAPESP: 2017/22963-6

This paper introduces an intelligent trajectory generator and a generalised proportional integral (GPI) control law for the movement of two carts on a circular motorised rail. The objective is to continuously monitor a person performing physical rehabilitation exercises and moving freely inside the circle. Each cart is equipped with an red-green-blue depth (RGB-D) device so that the patient is monitored from two points of view. One RGB-D device is dedicated to track the body part being exercised, while the other focuses on the person’s face to detect his/her emotional state. The proposed feedback control scheme is based on an exact feed-forward action combined with a velocity vector structural estimation using a model-based integral state reconstructor. Furthermore, the proposed intelligent trajectory generator comprises the references required to move the carts based on the instantaneous position of the patient and the current position of both carts. It also establishes the role (master or slave) of each cart, the direction that each cart must follow, and it generates smooth trajectories that avoid collisions between the carts. Moreover, the paper introduces a description of the displacements of both carts and the positioning of the tilt and pan angles of each RGB-D sensor so as to track the patient’s face and the body from the best viewpoints. The performance of the intelligent trajectory generation and the control of the two carts were analysed with numerical simulations. A comparison was made between the developed GPI control and a standard proportional integral derivative (PID) control. The simulation results show the effectiveness of the trajectory planner, and demonstrate that the GPI control has a better dynamic response than the PID control as well as a better performance in terms of the integral squared tracking error, the integral absolute tracking error, and the integral time absolute tracking error., This work was partially supported by Spanish Ministerio de Ciencia e Innovacion, Agencia Estatal de Investigacion (AEI)/European Regional Development Fund (FEDER, UE) under PID2019-106084RB-I00 and DPI2016-80894-R grants, by CIBERSAM of the Instituto de Salud Carlos III, and by VALU3S EU project (H2020-ECSEL grant agreement no 876852).

Many modern combinatorial solvers have a variety of parameters through which a user can customise their behaviour. Algorithm configuration is the process of selecting good values for these parameters in order to improve performance. Time and again algorithm configuration has been shown to significantly improve the performance of many algorithms for solving challenging computational problems. Automated systems for tuning parameters regularly out-perform human experts, sometimes but orders of magnitude. Online algorithm configurators, such as ReACTR, are able to tune a solver online without incurring costly offline training. As such ReACTR’s main focus is on runtime minimisation while solving combinatorial problems. To do this ReACTR adopts a one-pass methodology where each instance in a stream of instances to be solved is considered only as it arrives. As such ReACTR’s performance is sensitive to the order in which instances arrive. It is still not understood which instance orderings positively or negatively effect the performance of ReACTR. This paper investigates the effect of instance ordering and grouping by empirically evaluating different instance orderings based on difficulty and feature values. Though the end use is generally unable to control the order in which instances arrive it is important to understand which orderings impact Re- ACTR’s performance and to what extent. This study also has practical benefit as such orderings can occur organically. For example as business grows the problems it may encounter, such as routing or scheduling, often grow in size and difficulty. ReACTR’s performance also depends strongly configuration selection procedure used. This component controls which configurations are selected to run in parallel from the internal configuration pool. This paper evaluates various ranking mechanisms and different ways of combining them to better understand how the candidate selection procedure affects realtime algorithm configuration. We show that certain selection procedures are superior to others and that the order which instances arrive in determines which selection procedure performs best. We find that both instance order and grouping can significantly affect the overall solving time of the online automatic algorithm configurator ReACTR. One of the more surprising discoveries is that having groupings of similar instances can actually negatively impact on the overall performance of the configurator. In particular we show that orderings based on nearly any instance feature values can lead to significant reductions in total runtime over random instance orderings. In addition, certain candidate selection procedures are more suited to certain orderings than others and selecting the correct one can show a marked improvement in solving times.

This paper introduces the Internet-of-Things (IoT) and describes its evolution from a concept proposed by Kevin Ashton in 1999 through its public emergence in 2005 in a United Nations ITU report entitled “The Internet of Things”, to the present day where IoT devices are available as off-the-shelf products from major manufacturers. Using a systematic study of public literature, the paper presents a five-phase categorisation of the development of the Internet-of-Things from its beginnings to the present day. Four mini case studies are included to illustrate some of the issues involved. Finally, the paper discusses some of the big issues facing future developers and marketers of Internet-of-Things based products ranging from artificial intelligence (AI) through to customer privacy and acceptance finishing with an optimistic assessment of the future of the Internet-of-Things.

Designer thinking has received much attention as an innovative problem-solving approach. However, it is also a vague and unclear activity which can only be studied through the input and output results in a design process. This paper proposes that the visual design state is the external performance of design thinking, which is used to clarify vague design thinking. In this paper, a method for expressing and capturing design states based on multi-fuzzy cognitive mapping is presented. First, an agent model is built to capture the design states, and the weight values of the multi-fuzzy cognitive map matrix are calculated. The tightness of the design state route is then deduced. An example is presented to demonstrate the use of this method, which is able to support the designer with the necessary design resources and an intelligent design environment.

The definition of intelligent environments (IEs) (Augusto et al. in Hum Comput Inf Sci 3(1):12, 2013) has always been focused around their users, aiming at helping them in a smart and transparent way, and avoiding bothering them or acting against their will. The complexity of IEs, whose technologies range from sensors to machine learning, from distributed architectures to tangible interfaces, from communication protocols to data analysis, challenges researchers from various fields to contribute innovative and effective solutions. In this quest for technical solutions to the myriad requirements of an IEs, user expectations are often left behind, and while researchers tend to focus on niche technical aspects, they risk of losing the big picture of an IE “helping users in their daily life”. This paper analyzes the recent literature of the IEs’ research community, aiming at highlighting to which extent users are taken into account, or are involved, into the reported research works. Evidence shows that, while most papers refer to users in their description, only a small minority actually involve them in the design, testing or experimentation phases.

This paper describes our tools and method for an evaluation of the practical and logical implications of combining common linked data vocabularies into a single local logical model for the purpose of reasoning or performing quality evaluations. These vocabularies need to be unified to form a combined model because they reference or reuse terms from other linked data vocabularies and thus the definitions of those terms must be imported. We found that strong interdependencies between vocabularies are common and that a significant number of logical and practical problems make this model unification inconsistent. In addition to identifying problems, this paper suggests a set of recommendations for linked data ontology design best practice. Finally we make some suggestions for improving OWL’s support for distributed authoring and ontology reuse.

The task of selecting the most suitable classification algorithm for each data set under analysis is still today a unsolved research problem. This paper therefore proposes a meta-learning based framework that helps both, practitioners and non-experts data mining users to make informed decisions about the goodness and suitability of each available technique for their data set at hand. In short, the framework is supported by an experimental database that is fed with the meta-features extracted from training data sets and the performance obtained by a set of classifiers applied over them, with the aim of building an algorithm recommender using regressors. This will allow the end-user to know, for a new unseen data set, the predicted accuracy of this set of algorithms ranked by this value. The experimentation performed and discussed in this paper is addressed to evaluate which meta-features are more significant and useful for characterising data sets with the end goal of building algorithm recommenders and to test the feasibility of these recommenders. The study is carried out on data sets from the educational arena, in particular, targeted to predict students' performance in e-learning courses.

Researchers have identified problems with the validity of software engineering research findings. In particular, it is often impossible to reproduce data analyses, due to lack of raw data, or sufficient summary statistics, or undefined analysis procedures. The aim of this paper is to raise awareness of the problems caused by unreproducible research in software engineering and to discuss the concept of reproducible research (RR) as a mechanism to address these problems. RR is the idea that the outcome of research is both a paper and its computational environment. We report some recent studies that have cast doubts on the reliability of research outcomes in software engineering. Then we discuss the use of RR as a means of addressing these problems. We discuss the use of RR in software engineering research and present the methodology we have used to adopt RR principles. We report a small working example of how to create reproducible research. We summarise advantages of and problems with adopting RR methods. We conclude that RR supports good scientific practice and would help to address some of the problems found in empirical software engineering research.

Linear Discriminant Analysis (LDA) is a very common\ud technique for dimensionality reduction problems as a preprocessing\ud step for machine learning and pattern classification\ud applications. At the same time, it is usually used as a\ud black box, but (sometimes) not well understood. The aim of\ud this paper is to build a solid intuition for what is LDA, and\ud how LDA works, thus enabling readers of all levels be able\ud to get a better understanding of the LDA and to know how to\ud apply this technique in different applications. The paper first\ud gave the basic definitions and steps of how LDA technique\ud works supported with visual explanations of these steps.\ud Moreover, the two methods of computing the LDA space, i.e.\ud class-dependent and class-independent methods, were explained\ud in details. Then, in a step-by-step approach, two numerical\ud examples are demonstrated to show how the LDA\ud space can be calculated in case of the class-dependent and\ud class-independent methods. Furthermore, two of the most\ud common LDA problems (i.e. Small Sample Size (SSS) and\ud non-linearity problems) were highlighted and illustrated, and\ud state-of-the-art solutions to these problems were investigated and explained. Finally, a number of experiments was conducted\ud with different datasets to (1) investigate the effect of\ud the eigenvectors that used in the LDA space on the robustness\ud of the extracted feature for the classification accuracy,\ud and (2) to show when the SSS problem occurs and how it can\ud be addressed.

Advanced automation is needed in future mobile networks to provide adequate service quality economically and with high reliability. In this paper, a system is presented that takes into account the network context, analyses uncertain information, and infers network configurations by means of probabilistic reasoning. The system introduced in this paper is an experimental platform integrating a mobile network simulator, a Markov Logic Network (MLN) model, and an OWL 2 ontology into a runtime environment that can be monitored via a Resource Description Framework (RDF)-based user interface. In this approach, the OWL ontology contains a semantic representation of the relevant concepts, and the MLN model evaluates elements of uncertain information. Experiments based on a prototype implementation demonstrate the value of semantic modelling and probabilistic reasoning in network status characterization, optimization, and visualization.

In 2012, the University of Huddersfield Press presented a paper at the 16th International Conference on Electronic Publishing on its new open access journals platform. At the time, the Press was one of the only New University Presses (NUP) in the UK and one of the first to publish open access journals, open access monographs and sound recordings. This article discusses a number of emerging business models for NUPs before developing Hahn’s programme and publication level business plan, which is then related to the sustainability of the Press at Huddersfield. The article will demonstrate how the Press is able to show value to the University in order to secure funding. The paper will conclude with a discussion around the need for collaboration between library-led NUPs. Although this paper concentrates on the experiences of the University of Huddersfield Press, it will be relevant to other emerging or planned NUPs.

One of the important issues related with all types of data analysis, either statistical data analysis, machine learning, data mining, data science or whatever form of data-driven modeling, is data quality. The more complex the reality to be analyzed is, the higher the risk of getting low quality data. Unfortunately real data often contain noise, uncertainty, errors, redundancies or even irrelevant information. Useless models will be obtained when built over incorrect or incomplete data. As a consequence, the quality of decisions made over these models, also depends on data quality. This is why pre-processing is one of the most critical steps of data analysis in any of its forms. However, pre-processing has not been properly systematized yet, and little research is focused on this. In this paper a survey on most popular pre-processing steps required in environmental data analysis is presented, together with a proposal to systematize it. Rather than providing technical details on specific pre-processing techniques, the paper focus on providing general ideas to a non-expert user, who, after reading them, can decide which one is the more suitable technique required to solve his/her problem.

We describe a systematic approach called reframing, defined as the process of preparing a machine learning model (e.g., a classifier) to perform well over a range of operating contexts. One way to achieve this is by constructing a versatile model, which is not fitted to a particular context, and thus enables model reuse. We formally characterise reframing in terms of a taxonomy of context changes that may be encountered and distinguish it from model retraining and revision. We then identify three main kinds of reframing: input reframing, output reframing and structural reframing. We proceed by reviewing areas and problems where some notion of reframing has already been developed and shown useful, if under different names: re-optimising, adapting, tuning, thresholding, etc. This exploration of the landscape of reframing allows us to identify opportunities where reframing might be possible and useful. Finally, we describe related approaches in terms of the problems they address or the kind of solutions they obtain. The paper closes with a re-interpretation of the model development and deployment process with the use of reframing., We thank the anonymous reviewers for their comments, which have helped to improve this paper significantly. This work was supported by the REFRAME project, granted by the European Coordinated Research on Long-term Challenges in Information and Communication Sciences Technologies ERA-Net (CHIST-ERA), funded by their respective national funding agencies in the UK (EPSRC, EP/K018728), France and Spain (MINECO, PCIN-2013-037). It has also been partially supported by the EU (FEDER) and Spanish MINECO grant TIN2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII/2015/013.

[EN] Ultrasound diagnosis is a widely used medical tool. Among the various ultrasound techniques, ultrasonic imaging is particularly relevant. This paper presents an improvement to a two-dimensional (2D) ultrasonic system using measurements taken from perpendicular planes, where digital signal processing techniques are used to combine one-dimensional (1D) A-scans were acquired by individual transducers in arrays located in perpendicular planes. An algorithm used to combine measurements is improved based on the wavelet transform, which includes a denoising step during the 2D representation generation process. The inclusion of this new denoising stage generates higher quality 2D representations with a reduced level of speckling. The paper includes different 2D representations obtained from noisy A-scans and compares the improvements obtained by including the denoising stage., This work was supported by Spanish Government MEC Project TIN2013-47272-C2-1-R and by ITACA (Universitat Politècnica de València).

This paper gives a comprehensive overview over the problem of Semantic Interoperability in the Cultural Heritage domain, with a particular tbcus on solutions centered around extensional, i.e., instance-based, ontology matching methods. It presents three typical scenarios requiring interoperability, one with homogeneous collections, one with heterogeneous collections, and one with multi-lingual collections. It discusses two different ways to evaluate potential alignments, one based on the application of re-indexing, one using a reference alignment. To these scenarios we apply extensional matching with different similarity measures, which gives interesting insight into the applicability of this matching approach. Finally, we firmly position our work in the Cultural Heritage context through an extensive discussion of the relevance for, and isstles related to this specific field. The findings are as unspectacular as expected, but nevertheless important: the provided methods can really improve interoperability in a number of important cases, but they are not universal solutions to all related problems. This paper provides a solid foundation for any future work on Semantic Interoperability in the Cultural Heritage domain, in particular tbr anybody intending to apply extensional methods.

This paper outlines the approach taken to iteratively evaluate a set of VR/AR (virtual reality / augmented reality) applications for five different manual-work applications – terrestrial spacecraft assembly, assembly-line design, remote maintenance of trains, maintenance of nuclear reactors, and large-machine assembly process design – and examines the evaluation data for evidence of the effectiveness of the evaluation framework as well as the benefits to the development process of feedback from iterative evaluation. ManuVAR is an EU-funded research project that is working to develop an innovative technology platform and a framework to support high-value, high-knowledge manual work throughout the product lifecycle. The results of this study demonstrate the iterative improvements reached throughout the design cycles, observable through the trending of the quantitative results from three successive trials of the applications and the investigation of the qualitative interview findings. The paper discusses the limitations of evaluation in complex, multi-disciplinary development projects and finds evidence of the effectiveness of the use of the particular set of complementary evaluation methods incorporating a common inquiry structure used for the evaluation – particularly in facilitating triangulation of the data.

Argumentation is essential in our daily life since we argue all the time in scientific communities, parliaments, courts m etc. In the field of education, argumentation and argument skills reflect the students' abilities to outline a claim in a logical and convincing way and provide supportable reasons for that claim as well as identifying the often implicit assumptions that underlie the claim. This paper introduces an innovative agent-based ITS teaching environment "ALES", which concerns natural argument analysis. ALES offers two phases; learning phase and evaluation phase. The learning phase encompasses two learning strategies, learning by search and learning by assessment, in which different representative reports that follow the student progress can be produced easily. During learning by search, ALES utilizes mining techniques to expose and retrieve the underlying experts' analyses that are most relevant to the subject of search. Learning by assessment provides guidance through partial and total feedback, which guide the student analysis based on the pre-selected scheme. The evaluation phase aims to assess the student's analysis comparable to the pre-existed expert's analysis. The paper aims to (i) describe the constituent models of ALES and their functions, (ii) present the encompassed tutoring scenarios associated with an illustration of the teaching pedagogy, (iii) present a comparative study between ALES and other systems in the same field.

In recent years the field of automated planning has significantly\ud advanced and several powerful domain-independent\ud planners have been developed. However, none of these systems\ud clearly outperforms all the others in every known\ud benchmark domain. This observation motivated the idea of\ud configuring and exploiting a portfolio of planners to perform\ud better than any individual planner: some recent planning systems\ud based on this idea achieved significantly good results in\ud experimental analysis and International Planning Competitions.\ud Such results let us suppose that future challenges of the\ud Automated Planning community will converge on designing\ud different approaches for combining existing planning algorithms.\ud This paper reviews existing techniques and provides an exhaustive\ud guide to portfolio-based planning. In addition, the\ud paper outlines open issues of existing approaches and highlights\ud possible future evolution of these techniques.

Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

Modern smart environments are equipped with a multitude of devices and sensors aimed at intelligent services. The presence of these diverse devices has raised a major problem of managing complex environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the respective smart environments using user defined goals. Generally, the solution advocates that the user goals can be represented by combining devices smart appliances and sensor/actuators in particular states. 'Domotic Effects' is a high level modeling approach, which provides Ambient Intelligence AmI designers and integrators with a high level abstract layer that enables the definition of user goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. This paper describes an approach for the automatic evaluation of domotic effects combined through Boolean expressions, that can provide efficient and intelligent monitoring of the domotic structure of the environment. “Effects Evaluation” addresses the problem of finding the new values of all the domotic effects defined for the environment when one or more devices change their state or one or more sensor value is recorded in the environment, hence determining a new overall state of the environment. The paper also presents an architecture to implement the evaluation of domotic effects. Results obtained from carried out experiments prove the feasibility of the approach and highlight responsiveness of the implemented effect evaluation.