This paper outlines an approach to manage and quantify the risks associated with changes made to spreadsheets. The methodology focuses on structural differences between spreadsheets and suggests a technique by which a risk analysis can be achieved in an automated environment. The paper offers an example that demonstrates how contiguous ranges of data can be mapped into a generic list of formulae, data and metadata. The example then shows that comparison of these generic lists can establish the structural differences between spreadsheets and quantify the level of risk that each change has introduced. Lastly the benefits, drawbacks and limitations of the technique are discussed in a commercial context.
There have been many articles and mishaps published about the risks of uncontrolled spreadsheets in today's business environment, including non-compliance, operational risk, errors, and fraud all leading to significant loss events. Spreadsheets fall into the realm of end user developed applications and are often absent the proper safeguards and controls an IT organization would enforce for enterprise applications. There is also an overall lack of software programming discipline enforced in how spreadsheets are developed. However, before an organization can apply proper controls and discipline …
Few major commercial or economic decisions are made today which are not underpinned by analysis using spreadsheets. It is virtually impossible to avoid making mistakes during their drafting and some of these errors remain, unseen and uncorrected, until something turns the spotlight on them. By then it may be too late. The challenge is to find a way of creating spreadsheets which will preserve the benefit of their power and flexibility while making their creation more transparent and safer. Full documentation and documented version and quality control, section by section, of the eventual spread…
Virtual Reality (VR) can enhance the display and interaction of mobile knowledge work and in particular, spreadsheet applications. While spreadsheets are widely used yet are challenging to interact with, especially on mobile devices, using them in VR has not been explored in depth. A special uniqueness of the domain is the contrast between the immersive and large display space afforded by VR, contrasted by the very limited interaction space that may be afforded for the information worker on the go, such as an airplane seat or a small work-space. To close this gap, we present a tool-set for enh…
Fatigue is a broad, multifactorial concept that includes the subjective perception of reduced physical and mental energy levels. It is also one of the key factors that strongly affect patients' health-related quality of life. To date, most fatigue assessment methods were based on self-reporting, which may suffer from many factors such as recall bias. To address this issue, in this work, we recorded multi-modal physiological data (including ECG, accelerometer, skin temperature and respiratory rate, as well as demographic information such as age, BMI) in free-living environments and developed au…
AktivTalk: Digitizing the Talk Test for Voice-Based Exercise Intensity Self-Assessment and Exploring Automated Classification from Speech
Ludwig Boltzmann Institute for Digital Health and Prevention（路德维希·玻尔兹曼数字健康与预防研究所）；University of Innsbruck（因斯布鲁克大学）；University of Southern Denmark（南丹麦大学）
Supervised systems require human labels for training. But, are humans themselves always impartial during the annotation process? We examine this question in the context of automated assessment of human behavioral tasks. Specifically, we investigate whether human ratings themselves can be trusted at their face value when scoring video-based structured interviews, and whether such ratings can impact machine learning models that use them as training data. We present preliminary empirical evidence that indicates there might be biases in such annotations, most of which are visual in nature.
In the recent years, various 3D mixed reality serious games have been developed for different applications such as physical training, rehabilitation, and education. Task performance in a serious game is a measurement of how efficiently and accurately users accomplish the game's objectives. Prior research includes a graph-based representation of tasks, e.g. Hierarchical Task Network (HTN), which only models a game's tasks but does not perform assessment. In this paper, we propose Assessment HTN (A-HTN), which both models the task efficiently and incorporates assessment logic for game objectives…
Nowadays many software development frameworks implement Behavior-Driven Development (BDD) as a mean of automating the test of interactive systems under construction. Automated testing helps to simulate user's action on the User Interface and therefore check if the system behaves properly and in accordance to Scenarios that describe functional requirements. However, most of tools supporting BDD requires that tests should be written using low-level events and components that only exist when the system is already implemented. As a consequence of such low-level of abstraction, BDD tests can hardly…
Coaching technology, wearables and exergames can provide quantitative feedback based on measured activity, but there is little evidence of qualitative feedback to aid technique improvement. To achieve personalised qualitative feedback, we demonstrated a proof-of-concept prototype combining kinesiology and computational intelligence that could help improving tennis swing technique utilising three-dimensional tennis motion data acquired from multi-camera video. Expert data labelling relied on virtual 3D stick figure replay. Diverse assessment criteria for novice to intermediate skill levels and …
Newcastle University（纽卡斯尔大学）；Great North Childrens Hospital（大北方儿童医院）；Georgia Institute of Technology（佐治亚理工学院）
Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify infant movements using a Gestalt approach, identifying infants at high risk of developing PS. Training and maintenance of assessment skills are essential and expensive for the correct use of GMA, yet many practitioners lack these skills, preventing larger-scale screening and leading to significant risks of missing opportunities for early detection and…
Diverse disciplines are interested in how the coordination of interacting agents' movements, emotions, and physiology over time impacts social behavior. Here, we describe a new multivariate procedure for automating the investigation of this kind of behaviorally-relevant "interactional synchrony", and introduce a novel interactional synchrony measure based on features of dynamic time warping (DTW) paths. We demonstrate that our DTW path-based measure of interactional synchrony between facial action units of two people interacting freely in a natural social interaction can be used to predict how…
Institute of Electronics and Computer Science (EDI)（电子与计算机科学研究所（EDI））；Riga Stradins University（里加斯特拉迪什大学）
Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. Unfortunately, medical staff does not always follow the World Health Organization (WHO) hand washing guidelines in their everyday work. To this end, we present neural networks for automatically recognizing the different washing movements defined by the WHO. We train the neural network on a part of a large (2000+ videos) real-world labeled dataset with the different washing movements. The preliminary results show that using pre-trained neural network models such as MobileNetV2 and Xception for th…
