A technological acceptance of e-learning tools used in practical and laboratory teaching,according to the European higher education area 1

The application of scientific tools to analyse the use of Internet-based e-learning tools in academic settings is in general an ignored area. E-learning tools are actually an emergent topic as a result of the new ideas introduced by the European Higher Education Area. Lifelong learning, or the promotion of student initiative, is the new paradigm of a learner-centred education. In this context, e-learning tools can represent an effective way of supporting this new trend in education. Assuming the premise that successful use of these web-based tools depends primarily on a user's behaviour, the objective of this research is to examine the technology acceptance model (TAM) of web-based e-learning tools used in practical and laboratory teaching. The research hypotheses derived from this model have empirically been validated using the responses to a survey on e-learning usage among 220 users. These responses have been examined through partial least square. The obtained results strongly support the extended TAM in predicting a student's intention to use e-learning and define a set of external variables with a significant influence in the original TAM variables. Surprisingly, perceived ease of use did not posit a significant impact on student attitude or intention towards e-learning tool usage. Therefore, early evaluation of e-learning material is considered essential to providing a framework for further improvements of the tool.     

Visualizing the application of filters: A comparison of blocking,blurring, and colour-coding whiteboard information

Through a mixed-design experiment we compare how emergency-department clinicians perform when solving realistic work tasks with an electronic whiteboard where the application of information filters is visualized either by blocking, colour-coding or blurring information. We find that clinicians perform significantly faster and with less effort and temporal demand when using the blocking interface. However, we also find that the colour-coding interface provides clinicians with a better overview of the information displayed by the electronic whiteboard. The blurring interface did not perform as well as previous research has shown and we discuss the differences between these results and ours. Finally, we find that the clinicians worked much less in parallel than we had expected and discuss the reasons for this.     

ICT and Integrated Care: Some Dilemmas of Standardising Inter-Organisational Communication

There is a growing interest in the issues of how to organise healthcare work along individual patient cases rather than along the demarcation lines of healthcare organisations. Health information systems, such as electronic patient records, are seen as important change agents, since they are asserted to help the coordination of care across organisations through fast and accurate exchange of clinical data. The paper explores how a semi-standardised discharge letter is employed to communicate about the patient between two organisational settings, the hospital and the general practitioner. It is shown that the discharge letter plays a double role as informational tool and accounting device. And it is argued that further standardisation of the discharge letter content – in order to facilitate electronic exchange – is likely to strengthen the letters role as a tool for organisational accountability and weaken it as a clinical tool. The paper concludes that this finding adds to the theoretical understanding of how computers support cooperative work, and that understanding how healthcare professionals present themselves as accountable and trustworthy should be of major concern when designing healthcare ICTs.     

Automated Game Analysis via Probabilistic Model Checking: a case study

It has been recognised for some time that there are close links between the various logics developed for the analysis of multi-agent systems and the many game-theoretic models developed for the same purpose. In this paper, we contribute to this burgeoning body of work by showing how a probabilistic model checking tool can be used for the automated analysis of game-like multi-agent systems in which both agents and environments can act with uncertainty. Specifically, we show how a variation of the well-known alternating offers negotiation protocol of Rubinstein can be encoded as a model for the PRISM model checker and its behaviour analysed through automatic verification of probabilistic CTL's properties.     

Applying fuzzy multi-objective linear programming to project management decisions with the interactive two-phase method

The aim of this paper is to develop an interactive two-phase method that can help the Project Manager (PM) with solving the fuzzy multi-objective decision problems. Therefore, in this paper, we first revisit the related papers and focus on how to develop an interactive two-phase method. Next, we establish to consider the imprecise nature of the data by fulfilling the possibilistic programming model, and we also assume that each objective work has a fuzzy goal. Finally, for reaching our objective, the detailed numerical example is presented to illustrate the feasibility of applying the proposed approach to PM decision problems at the end of this paper. Results show that our model can be applied as an effective tool. Furthermore, we believe that this approach can be applied to solve other multi-objective decision making problems.     

Responses to ambivalence toward social networking sites: A typological perspective

A common assumption in prior research on social networking sites (SNS) has been that users' orientations toward SNS use are positioned somewhere along a bipolar, univalent continuum, stretching from negative to positive orientation. However, considering recent findings unfolding the intricacy and variety of SNS use patterns, such a linear conceptualization of users' orientations is too simplistic with limited ability to explain the intricate patterns of SNS use. To alleviate this deficiency in this paper, we draw on the ambivalence literature and explain that users can simultaneously experience both positive and negative orientations toward SNS use based on the positive and negative aspects of their SNS use experience. Focusing on post- adoptive SNS use context, we theorise archetypes of SNS users' attitudinal responses to ambivalence, and their associated behavioural outcomes in terms of SNS use patterns. We first follow a typological perspective and develop typologies of attitudinal and behavioural responses to ambivalence toward SNS use. Then, we offer six hypotheses that explain the relations between the archetypes of attitudinal responses to ambivalence toward SNS use and users' SNS use patterns. Lastly, we empirically test our hypotheses using latent profile analysis and ANCOVA applied to two-wave data collected from 370 ambivalent SNS users. The findings support the hypotheses and validate our typologies. The findings ultimately point to likely choices from a range of post-adoption SNS use patterns as plausible outcomes of SNS users' attitudinal responses to ambivalence.     

Using interactive evolutionary computation to generate creative building designs

In this paper we describe how we have exploited Evolutionary Computation (EC) to generate creative building designs. The algorithm has been implemented to create a design tool for architects called Design Inspiration system (DIS). The interactive design inspiration tool is able to generate initial design concepts of architectural plans. Our approach illustrates what we regard as an ideal strategy towards an organic architecture that is inspired from living organisms and not concerned with architectural style. The current capabilities of the system are demonstrated by the example of designing a library building. The paper ends by describing a comprehensive experiment with a total of 28 volunteer architects as a cognitive performance measurement tool, capable of accurately positioning participants’ performance using the design system. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

A generic tool to federate WAN servers

On a Wide Area Network (WAN), services are more efficient if they are supported by several servers located near their respective clients. In this article, we present a generic tool which facilitates the federation of servers over a WAN. This tool is in charge of both dynamically managing the federation and propagating requests to all the federation’s servers. It may be applied to any kind of widely available service. As far as we know, there is no generic tool that can be used by WAN services to federate their servers. We present the benefits these services could derive from our federation tool. The federation adapts dynamically in case of server addition, server failure and network topology modification. Each server has a global view of the federation which is used especially to propagate requests to the federation. We present the general model and the design of the tool. The tool is built upon group communication objects. And we present some implementation issues in a CORBA (Common Object Request Broker Architecture) environment. The tool is generic in that it may be applied to any service. In this paper we show how a specific service may use the generic federation tool especially to propagate typed requests. Finally, we present an application of this tool for federating CORBA traders.     

Machine Learning and the foundations of inductive inference

The problem of valid induction could be stated as follows: are we justified in accepting a given hypothesis on the basis of observations that frequently confirm it? The present paper argues that this question is relevant for the understanding of Machine Learning, but insufficient. Recent research in inductive reasoning has prompted another, more fundamental question: there is not just one given rule to be tested, there are a large number of possible rules, and many of these are somehow confirmed by the data — how are we to restrict the space of inductive hypotheses and choose effectively some rules that will probably perform well on future examples? We analyze if and how this problem is approached in standard accounts of induction and show the difficulties that are present. Finally, we suggest that the explanation-based learning approach and related methods of knowledge intensive induction could be, if not a solution, at least a tool for solving some of these problems.     

The Construction of Smooth Models using Irregular Embeddings Determined by a Gamma Test Analysis

One of the key problems in forming a smooth model from input-output data is the determination of which input variables are relevant in predicting a given output. In this paper, we show how the Gamma test can be used to select that combination of input variables which can best be employed to form a smooth model of an output. For time series prediction this amounts to the selection of an appropriate irregular embedding. We give some simple zero noise examples of time series analysis, and illustrate how using these techniques a binary message encoded into a chaotic carrier can be retrieved without knowledge of the dynamics used to generate the carrier. Provided the underlying dynamics are such as to produce a smooth embedding model with bounded partial derivatives, the sampling distribution is dense in input space, and any associated distribution of measurement error has the first few moments bounded, so that the typical prerequisite conditions of the Gamma test are satisfied, we conclude that the Gamma test is an effective tool in the determination of irregular time series embeddings. These techniques can also be useful in practical applications which involve filtering seismic data to detect anomalous events.     

Morphological and stance interpolations in database for simulating bipedalism of virtual humans

We present a computer tool for testing walk hypotheses for human beings. This tool aims to generate plausible walking movements according to anatomical knowledge. To this end, we introduce an interpolation method based, on one hand, on morphological data and, on the other hand, on stance hypotheses and on footprint hypotheses. We want to test these hypotheses for application to the reconstruction of early hominid walking. We interpolate from a specific representation of the movement—a characteristic relative displacement. First, we use a motion capture system to acquire real movements of a walk cycle, and we propose to represent them by using a generic parametric model. Thus, we create a database of movements. The interpolation process produces, thanks to this database, a retargeted motion adapted to the morphology of the considered targeted skeleton. The interpolation is done according to three main hypotheses. The first concerns the reference stance, the second the lateral spacing between the feet, and the third the length of the step. In the introduction, we refer to related work. Then we propose the two following points of our method: the 3D representation of our motion representation and the multidimensional interpolation method applied to this representation. The interpolation method addresses morphological adaptation, and the use of an inverse kinematics solver addresses the computation of skeleton movements. The self-coherent validation process aims to test the coherence of the proposed method. The results propose an application to a virtual skeleton of Lucy (Australopithecus afarensis A.L. 288-1) reconstructed from real data. Finally, the relevance of the method for anthropological investigations and for animation purposes is discussed and future work is discussed with respect to the limitations of the proposed method.     

Business process model abstraction: a definition, catalog, and survey

The discipline of business process management aims at capturing, understanding, and improving work in organizations by using process models as central artifacts. Since business-oriented tasks require different information from such models to be highlighted, a range of abstraction techniques has been developed over the past years to manipulate overly detailed models. At this point, a clear understanding of what distinguishes these techniques and how they address real world use cases has not yet been established. In this paper we systematically develop, classify, and consolidate the use cases for business process model abstraction and present a case study to illustrate the value of this technique. The catalog of use cases that we present is based on a thorough evaluation of the state of the art, as well as on our cooperation with end users in the health insurance sector. It has been subsequently validated by experts from the consultancy and tool vendor domains. Based on our findings, we evaluate how the existing business process model abstraction approaches support the discovered use cases and reveal which areas are not adequately covered, as such providing an agenda for further research in this area.     

A novel tool for summarization of arthroscopic videos

Arthroscopic surgery is a minimally invasive procedure that uses a small camera to generate video streams, which are recorded and subsequently archived. In this paper we present a video summarization tool and demonstrate how it can be successfully used in the domain of arthroscopic videos. The proposed tool generates a keyframe-based summary, which clusters visually similar frames based on user-selected visual features and appropriate dissimilarity metrics. We discuss how this tool can be used for arthroscopic videos, taking advantage of several domain-specific aspects, without losing its ability to work on general-purpose videos. Experimental results confirm the feasibility of the proposed approach and encourage extending it to other application domains.     

A Visual Analytics Approach to Understanding Spatiotemporal Hotspots

As data sources become larger and more complex, the ability to effectively explore and analyze patterns among varying sources becomes a critical bottleneck in analytic reasoning. Incoming data contain multiple variables, high signal-to-noise ratio, and a degree of uncertainty, all of which hinder exploration, hypothesis generation/exploration, and decision making. To facilitate the exploration of such data, advanced tool sets are needed that allow the user to interact with their data in a visual environment that provides direct analytic capability for finding data aberrations or hotspots. In this paper, we present a suite of tools designed to facilitate the exploration of spatiotemporal data sets. Our system allows users to search for hotspots in both space and time, combining linked views and interactive filtering to provide users with contextual information about their data and allow the user to develop and explore their hypotheses. Statistical data models and alert detection algorithms are provided to help draw user attention to critical areas. Demographic filtering can then be further applied as hypotheses generated become fine tuned. This paper demonstrates the use of such tools on multiple geospatiotemporal data sets.     

MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains

MobiGuide is a ubiquitous, distributed and personalized evidence-based decision-support system (DSS) used by patients and their care providers. Its central DSS applies computer-interpretable clinical guidelines (CIGs) to provide real-time patient-specific and personalized recommendations by matching CIG knowledge with a highly-adaptive patient model, the parameters of which are stored in a personal health record (PHR). The PHR integrates data from hospital medical records, mobile biosensors, data entered by patients, and recommendations and abstractions output by the DSS. CIGs are customized to consider the patients’ psycho-social context and their preferences; shared decision making is supported via decision trees instantiated with patient utilities. The central DSS “projects” personalized CIG-knowledge to a mobile DSS operating on the patients’ smart phones that applies that knowledge locally. In this paper we explain the knowledge elicitation and specification methodologies that we have developed for making CIGs patient-centered and enabling their personalization. We then demonstrate feasibility, in two very different clinical domains, and two different geographic sites, as part of a multi-national feasibility study, of the full architecture that we have designed and implemented. We analyze usage patterns and opinions collected via questionnaires of the 10 atrial fibrillation (AF) and 20 gestational diabetes mellitus (GDM) patients and their care providers. The analysis is guided by three hypotheses concerning the effect of the personal patient model on patients and clinicians’ behavior and on patients’ satisfaction. The results demonstrate the sustainable usage of the system by patients and their care providers and patients’ satisfaction, which stems mostly from their increased sense of safety. The system has affected the behavior of clinicians, which have inspected the patients’ models between scheduled visits, resulting in change of diagnosis for two of the ten AF patients and anticipated change in therapy for eleven of the twenty GDM patients.     

Is Someone in this Office Available to Help Me?

Robots are increasingly autonomous in our environments, but they still must overcome limited sensing, reasoning, and actuating capabilities while completing services for humans. While some work has focused on robots that proactively request help from humans to reduce their limitations, the work often assumes that humans are supervising the robot and always available to help. In this work, we instead investigate the feasibility of asking for help from humans in the environment who benefit from its services. Unlike other human helpers that constantly monitor a robot’s progress, humans in the environment are not supervisors and a robot must proactively navigate to them to receive help. We contribute a study that shows that several of our environment occupants are willing to help our robot, but, as expected, they have constraints that limit their availability due to their own work schedules. Interestingly, the study further shows that an available human is not always in close proximity to the robot. We present an extended model that includes the availability of humans in the environment, and demonstrate how a navigation planner can incorporate this information to plan paths that increase the likelihood that a robot can find an available helper when it needs one. Finally, we discuss further opportunities for the robot to adapt and learn from the occupants over time.     

Physicians’ motivations to use mobile health monitoring: a cross-country comparison

While mobile device receives increasing attention as a practical tool to remotely check patients’ health, little research has shed light on physicians’ acceptance of this information and communication technology. This study attempts to fill this research gap by examining how Japanese and Spanish physicians perceive a series of factors associated with mobile diabetes monitoring acceptance, and whether any differences exist in these perceptions between the countries due to different levels of physician scarcity, which is operationalised as the number of physicians available per 10,000 population. The hypotheses were tested by empirical surveys in Japan and Spain. In total, 471 and 497 usable responses were obtained from Japanese and Spanish physicians, respectively. In both countries, physicians were likely to embrace clinical expectations (perceived value) and appreciate the ability to check patients’ health remotely (ubiquitous control) as the main benefits of mobile diabetes monitoring. In terms of cross-country comparison, the influence of personal innovativeness on perceived value and ubiquitous control was stronger in Japan (greater physician scarcity), compared with Spain (less physician scarcity).     

A Controlled Experiment to Evaluate On-Line Process Guidance

Process-centered software engineering environments are expected to improve an individual's comprehension of work activities, as well as improve communication and reduce conflicts among teams of software developers. We chose to investigate individual responses when using such an environment before looking for a group response. A controlled experiment compared off-line and on-line implementations of measurement-based process guidance to test three hypotheses: first, individuals accomplish their work more efficiently when using on-line process guidance as compared to off-line guidance; second, individuals are willing to use an on-line system for guidance; and third, individuals adjust their behavior based on quantitative quality models. The subjects worked alone on two testing exercises. Subjects used either an off-line or an on-line guidance technique during the first exercise, and the other technique during the second exercise. The results did not confirm the hypotheses. On average, subjects worked more efficiently when using off-line guidance, preferred off-line guidance, and ignored quantitative quality models. Post hoc analysis identified a strong correlation between subject experience level and preference for the type of guidance, a result that deserves further investigation.     

Robust heart rate variability analysis by generalized entropy minimization

Typical heart rate variability (HRV) times series are cluttered with outliers generated by measurement errors, artifacts and ectopic beats. Robust estimation is an important tool in HRV analysis, since it allows clinicians to detect arrhythmia and other anomalous patterns by reducing the impact of outliers. A robust estimator for a flexible class of time series models is proposed and its empirical performance in the context of HRV data analysis is studied. The methodology entails the minimization of a pseudo-likelihood criterion function based on a generalized measure of information. The resulting estimating functions are typically re-descending, which enable reliable detection of anomalous HRV patterns and stable estimates in the presence of outliers. The infinitesimal robustness and the stability properties of the new method are illustrated through numerical simulations and two case studies from the Massachusetts Institute of Technology and Boston’s Beth Israel Hospital data, an important benchmark data set in HRV analysis.