Saving Cultural Heritage with Digital Make-Believe: Machine Learning and Digital Techniques to the Rescue

The application of digital methods for content-based curation and dissemination of cultural heritage data offers unique advantages for physical sites at risk of damage. In areas affected by 2011 Arab spring, digital may be the only approach to create believable cultural experiences. We propose a framework incorporating computational methods such as: digital image processing, multi-lingual text analysis, and 3D modelling, to facilitate enhanced data archive, federated search, and analysis. Potential use cases include experiential search, damage assessment, virtual site reconstruction, and provision of augmented information for education and cultural preservation. This paper presents initial findings from an empirical evaluation of existing scene classification methods, applied to detection of cultural heritage sites in the Palmyra region. Results indicate that deep learning offers an appropriate solution to semantic annotation of publicly available cultural heritage image data

Design, Development and Evaluation of a Virtual Environment with children for Moral, Social & Emotional Leaning

Virtual environments have the potential to be an important teaching tool for emotionally-sensitive issues capable of producing a sense of presence, perspective-taking and introspection in users in a risk-free, rapid feedback experience. In designing such experiences, it is essential that users are regularly engaged in a collaborative design process. However, engaging in design, development and evaluation can in itself provide a learning experience. Here, we present our approach to engaging children in the design, development and evaluation of a virtual learning environment, specifically a Serious Game, focused on inculcating empathy, ethical reasoning and reflection for coping with bullying. We demonstrate that children’s involvement not only contributed to an improved virtual environment, but significantly, engaging in the design process provided children with a novel and effective learning opportunity. Through using innovative child-centered participatory design practices, this research provides perceptive insights into how engaging children in design can be employed as a learning experience for emotionally-sensitive learning as well as an approach to gathering user design input. The material outlined in this article is directly linked to virtual worlds for positive change— meeting the needs of children, empowering them to be consulted and take responsibility for issues that affect them at school

SAVASA project @ TRECVID 2012: interactive surveillance event detection

In this paper we describe our participation in the interactive surveillance event detection task at TRECVid 2012. The system we developed was comprised of individual classifiers brought together behind a simple video search interface that enabled users to select relevant segments based on down~sampled animated gifs. Two types of user -- `experts' and `end users' -- performed the evaluations. Due to time constraints we focussed on three events -- ObjectPut, PersonRuns and Pointing -- and two of the five available cameras (1 and 3). Results from the interactive runs as well as discussion of the performance of the underlying retrospective classifiers are presented

SAVASA project @ TRECVid 2013: semantic indexing and interactive surveillance event detection

In this paper we describe our participation in the semantic indexing (SIN) and interactive surveillance event detection (SED) tasks at TRECVid 2013 [11]. Our work was motivated by the goals of the EU SAVASA project (Standards-based Approach to Video Archive Search and Analysis) which supports search over multiple video archives. Our aims were: to assess a standard object detection methodology (SIN); evaluate contrasting runs in automatic event detection (SED) and deploy a distributed, cloud-based search interface for the interactive component of the SED task. Results from the SIN task, underlying retrospective classifiers for the surveillance event detection and a discussion of the contrasting aims of the SAVASA user interface compared with the TRECVid task requirements are presented

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Co-design with Children: Using Participatory Design for Design Thinking and Social and Emotional Learning

This paper discusses leveraging design thinking techniques for involving children in serious game design in Japanese elementary schools. Our action research project approach accomplished two different goals: (1) to inculcate design thinking in pupils, and (2) to sensitize children on bullying victimization. Our approach uses a range of participatory design methods to distill design ideas from children and to support their design thinking aiming to boost children’s creative confidence and develop social and emotional skills. Key findings from our project are: (1) children made valuable design contributions including realistic bullying scenarios, language content, user interface design, storyline progression, character profiles, coping strategies etc., and (2) participatory design and design thinking stimulated ethical reasoning, reflection and empathy in children on bullying victimization. Our approach is unique in the current design thinking landscape, because it moves from designing “thing” (object) to designing “think” (bullying sensitization). Future research should focus on highlighting ways how participatory design and design thinking enrich and complement each other. The significance of our paper stems from the simple standpoint that those participating in a design should gain from participating in the design process. Takeaways for practitioners are: (1) building relationships with stakeholders, especially children (2) empathy and user research techniques, (2) translating field data into usable insights, (3) idea-generation and rapid concept development, (4) product co-prototyping, (5) user engagement and co-creation, (6) multiple perspectives on effective communication

Medical Formulation Recognition (MFR) using Deep Feature Learning and One Class SVM

Specials medications are personalized formulations manufactured on demand for patients with unique prescription requirements and constitute an essential component of patient treatment. Specials are becoming increasingly in demand due to the need for personalized and precision medicine. The timely provision of optimal personalized medicine, however, is challenging, subject to strict regulatory processes, and is expert intensive. In this paper, we propose a new medical formulation engine (MFE) that performs semantic search across multiple disparate formulations archives to enable data driven formulation intelligence. We develop a new platform for medical formulations recognition (MFR) that curates a new dataset comprising formulations and non-formulations (clinical) text and uses a novel pipeline encompassing deep feature extraction and one-class support vector machine learning. The proposed MFR framework demonstrates promising performance and can be used as a benchmark for future research in formulations recognition

A Virtual Environment for Accessible Desktop Navigation

Virtual reality is an emergent technology with the potential to offer valuable contributions to ambient assisted living. For example, it can be utilised to enhance equality of access to, and ease of use of technology. This paper introduces virtual reality technology, and presents a prototype system for intuitive file navigation and manipulation. Through a discussion and end user evaluation of system use cases, we offer commentary on the system’s potential for increasing computing confidence and competency in non-computer literate populations. Findings indicate virtual reality constitutes a viable tool for aiding users with reduced computer literacy and confidence in relation to everyday computing tasks, and therefore could be deployed as an assistive technology within such populations

EMED: enhancement of melanoma early diagnosis

Malignant melanoma is an aggressive cutaneous cancer originating in melanocytes, the cells which produce skin pigmentation. When treating malignant melanoma prompt diagnosis is paramount, as the depth of vertical invasion (Breslow thickness) is inversely correlated with survival rates. The development of computerised systems for assisted recognition of malignant melanoma can aid enhanced early diagnosis of this disease and help reduce the subjectivity associated with clinical diagnostic procedures. We describe and evaluate key elements of a prototype system for classifying benign pigmented skin lesions and cutaneous malignant melanoma, with emphasis placed on the extraction of existing clinical criteria. The system utilises image processing methods to enable specific features to be defined. Statistical- and intelligence- based classification techniques are then employed to automate identification of significant features, with the aim of reducing feature analysis variability. After lesion boundary determination, a total of 77 parameters for describing the visual appearance (shape asymmetry, border irregularity, colour and differential distribution, and dimension) of pigmented skin lesions are extracted from digital epiluminescence microscopy images and assessed using a double-blind study. A variety of classification methodologies (specifically C5.0 induction, classification and regression induction, and a neural network model) are applied to assess the diagnostic capability of these parameters and to compare system performance against the diagnostic accuracy achieved by two experts using clinical visual inspection methodologies. It is concluded that the parameters generated may have high discriminative value when differentiating between benign and malignant lesions. When using our full feature set on a data set comprising 30 lesions, diagnostic accuracy achieved via the automated classifiers constituted a significant improvement when compared with clinical diagnostic accuracy achieved by our experts

Automated Representation of Non-Emotional Expressivity to Facilitate Understanding of Facial Mobility: Preliminary Findings

We present an automated method of identifying and representing non-emotional facial expressivity in video data. A benchmark dataset is created using the framework of an existing clinical test of upper and lower face movement, and initial findings regarding automated quantification of facial motion intensity are discussed. We describe a new set of features which combine tracked interest point statistics within a temporal window, and explore the effectiveness of those features as methods of quantifying changes in non-emotional facial expressivity of movement in the upper part of the face. We aim to develop this approach as a protocol which could inform clinical diagnosis and evaluation of treatment efficacy of a number of neurological conditions including Parkinson’s Disease