Assisting the Design of virtualwork processes via on-line reverse engineering

The design of virtual workplaces that can support virtual work processes has traditionally been either adhoc, or has been influenced by the virtual architecture or requirements engineering disciplines. The problem with these approaches is the difficulty in obtaining, and subsequently retaining and reusing, ready-made configurations of collaborative work processes. Such configurations naturally occur during the actual use of CVEs for conducting projects. Can we predict some elements of the evolution of a new collaborative process, based on similarities and analogies with processes formalised and supported before? Can we capture and utilise the evolutionary component in the workspace design process, so that we can provide better support to the developers of collaborative workspaces? The paper presents a new approach for supporting design and redesign of virtual workspaces, based on combining data mining techniques for refining lower level models with a reverse engineering cycle to create upper level models

Interactive visualization with user perspective: A new concept

With an astonishing amount of data generated for processing on a daily basic, it is essential to provide an effective methodology for understanding, reasoning and supporting decision making of large information spaces. This paper presents a new concept that provides an intelligent and interactive visualization in supporting large scale analysis. This aims to provide a much greater flexibility and control for the users to interactively customize the visualizations according to their preferences. A simple prototype is also presented to demonstrate the concept on hierarchical structures. Copyright © 2010 ACM

A Multi Agent Recommender System that Utilises Consumer Reviews in its Recommendations

Consumer reviews, opinions and shared experiences in the use of a product form a powerful source of information about consumer preferences that can be used for making recommendations. A novel approach, which utilises this valuable information sources first time to create recommendations in recommender agents was recently developed by Aciar et al. (2007). This paper presents a general framework of this approach. The proposed approach is demonstrated using digital camera reviews as an example

Comparison of visualization methods of genome-wide SNP profiles in childhood acute lymphoblastic leukaemia

Data mining and knowledge discovery have been applied to datasets in various industries including biomedical data. Modelling, data mining and visualization in biomedical data address the problem of extracting knowledge from large and complex biomedical data. The current challenge of dealing with such data is to develop statistical-based and data mining methods that search and browse the underlying patterns within the data. In this paper, we employ several data reduction methods for visualizing genome- wide Single Nucleotide Polymorphism (SNP) datasets based on state-of-art data reduction techniques. Visualization approach has been selected based on the trustworthiness of the resultant visualizations. To deal with large amounts of genetic variation data, we have chosen to apply different data reduction methods to deal with the problem induced by high dimensionality. Based on the trustworthiness metric we found that neighbour Retrieval Visualizer (NeRV) outperformed other methods. This method optimizes the retrieval quality of Stochastic neighbour Embedding. The quality measure of the visualization (i.e. NeRV) showed excellent results, even though the dataset was reduced from 13917 to 2 dimensions. The visualization results will assist clinicians and biomedical researchers in understanding the systems biology of patients and how to compare different groups of clusters in visualizations. © 2008, Australian Computer Society, Inc

Enabling effective tree exploration using visual cues

© 2018 Elsevier Ltd This article presents a new interactive visualization for exploring large hierarchical structures by providing visual cues on a node link tree visualization. Our technique provides topological previews of hidden substructures with three types of visual cues including simple cues, tree cues and treemap cues. We demonstrate the visual cues on Degree-of-Interest Tree (DOITree) due to its familiar mapping, its capability of providing multiple focused nodes, and its dynamic rescaling of substructures to fit the available space. We conducted a usability study with 28 participants that measured completion time and accuracy across five different topology search tasks. The simple cues had the fastest completion time across three of the node identification tasks. The treemap cues had the highest rate of correct answers on four of the five tasks, although only reaching statistical significance for two of these. As predicted, user ratings demonstrated a preference for the easy to understand tree cues followed by the simple cue, despite this not consistently reflected in performance results

Opening new dimensions for e-Tourism

In this paper we describe an e-Tourism environment that takes a community-driven approach to foster a lively society of travelers who exchange travel experiences, recommend tourism destinations or just listen to catch some interesting gossip. Moreover, business transactions such as booking a trip or getting assistance from travel advisors or community members are constituent parts of this environment. All these happen in an integrated, game-like e-Business application where each e-Tourist is impersonated as an avatar. More precisely, we apply 3D Electronic Institutions, a framework developed and employed in the area of multi-agent systems, to the tourism domain. The system interface is realized by means of a 3D game engine that provides sophisticated 3D visualization and enables humans to interact with the environment. We present "itchy feet", a prototype implementing this 3D e-Tourism environment to showcase first visual impressions. This new environment is a perfect research playground for examining heterogeneous societies comprising humans and software agents, and their relationship in e-Tourism. © Springer-Verlag London Limited 2006

Smart scalable ML-blockchain framework for large-scale clinical information sharing

Large-scale clinical information sharing (CIS) provides significant advantages for medical treatments, including enhanced service standards and accelerated scheduling of health services. The current CIS suffers many challenges such as data privacy, data integrity, and data availability across multiple healthcare institutions. This study introduces an innovative blockchain-based electronic healthcare system that incorporates synchronous data backup and a highly encrypted data-sharing mechanism. Blockchain technology, which eliminates centralized organizations and reduces the number of fragmented patient files, could make it easier to use machine learning (ML) models for predictive diagnosis and analysis. In turn, it might lead to better medical care. The proposed model achieved an improved patient-centered CIS by personalizing the separation of information with an intelligent ”allowed list“ for clinician data access. This work introduces a hybrid ML-blockchain solution that combines traditional data storage and blockchain-based access. The experimental analysis evaluated the proposed model against the competing models in comparative and quantitative studies in large-scale CIS examples in terms of model viability, stability, protection, and robustness, with improved results

Evaluation on interactive visualization data with scatterplots

Scatterplots and scatterplot matrix methods have been popularly used for showing statistical graphics and for exposing patterns in multivariate data. A recent technique, called Linkable Scatterplots, provides an interesting idea for interactive visual exploration which provides a set of necessary plot panels on demand together with interaction, linking and brushing. This article presents a controlled study with a mixed-model design to evaluate the effectiveness and user experience on the visual exploration when using a Sequential-Scatterplots who a single plot is shown at a time, Multiple-Scatterplots who number of plots can be specified and shown, and Simultaneous-Scatterplots who all plots are shown as a scatterplot matrix. Results from the study demonstrated higher accuracy using the Multiple-Scatterplots visualization, particularly in comparison with the Simultaneous-Scatterplots.​ While the time taken to complete tasks was longer in the Multiple-Scatterplots technique, compared with the simpler Sequential-Scatterplots, Multiple-Scatterplots is inherently more accurate. Moreover, the Multiple-Scatterplots technique is the most highly preferred and positively experienced technique in this study. Overall, results support the strength of Multiple-Scatterplots and highlight its potential as an effective data visualization technique for exploring multivariate data

Robotic bronchoscopy for peripheral pulmonary lesions: A multicenter pilot and feasibility study (BENEFIT)

BACKGROUND: The diagnosis of peripheral pulmonary lesions (PPL) continues to present clinical challenges. Despite extensive experience with guided bronchoscopy, the diagnostic yield has not improved significantly. Robotic-assisted bronchoscopic platforms have been developed potentially to improve the diagnostic yield for PPL. Presently, limited data exist that evaluate the performance of robotic systems in live human subjects. RESEARCH QUESTION: What is the safety and feasibility of robotic-assisted bronchoscopy in patients with PPLs? STUDY DESIGN AND METHODS: This was a prospective, multicenter pilot and feasibility study that used a robotic bronchoscopic system with a mother-daughter configuration in patients with PPL 1 to 5 cm in size. The primary end points were successful lesion localization with the use of radial probe endobronchial ultrasound (R-EBUS) imaging and incidence of procedure related adverse events. Robotic bronchoscopy was performed in patients with the use of direct visualization, electromagnetic navigation, and fluoroscopy. After the use of R-EBUS imaging, transbronchial needle aspiration was performed. Rapid on-site evaluation (ROSE) was used on all cases. Transbronchial needle aspiration alone was sufficient when ROSE was diagnostic; when ROSE was not diagnostic, transbronchial biopsy was performed with the use of the robotic platform, followed by conventional guided bronchoscopic approaches at the discretion of the investigator. RESULTS: Fifty-five patients were enrolled at five centers. One patient withdrew consent, which left 54 patients for data analysis. Median lesion size was 23 mm (interquartile range, 15 to 29 mm). R-EBUS images were available in 53 of 54 cases. Lesion localization was successful in 51 of 53 patients (96.2%). Pneumothorax was reported in two of 54 of the cases (3.7%); tube thoracostomy was required in one of the cases (1.9 %). No additional adverse events occurred. INTERPRETATION: This is the first, prospective, multicenter study of robotic bronchoscopy in patients with PPLs. Successful lesion localization was achieved in 96.2% of cases, with an adverse event rate comparable with conventional bronchoscopic procedures. Additional large prospective studies are warranted to evaluate procedure characteristics, such as diagnostic yield. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT03727425; URL: www.clinicaltrials.gov