On Acquisition and Analysis of a Dataset Comprising of Gait, Ear and Semantic data

In outdoor scenarios such as surveillance where there is very little control over the environments, complex computer vision algorithms are often required for analysis. However constrained environments, such as walkways in airports where the surroundings and the path taken by individuals can be controlled, provide an ideal application for such systems. Figure 1.1 depicts an idealised constrained environment. The path taken by the subject is restricted to a narrow path and once inside is in a volume where lighting and other conditions are controlled to facilitate biometric analysis. The ability to control the surroundings and the flow of people greatly simplifes the computer vision task, compared to typical unconstrained environments. Even though biometric datasets with greater than one hundred people are increasingly common, there is still very little known about the inter and intra-subject variation in many biometrics. This information is essential to estimate the recognition capability and limits of automatic recognition systems. In order to accurately estimate the inter- and the intra- class variance, substantially larger datasets are required [40]. Covariates such as facial expression, headwear, footwear type, surface type and carried items are attracting increasing attention; although considering the potentially large impact on an individuals biometrics, large trials need to be conducted to establish how much variance results. This chapter is the first description of the multibiometric data acquired using the University of Southampton's Multi-Biometric Tunnel [26, 37]; a biometric portal using automatic gait, face and ear recognition for identification purposes. The tunnel provides a constrained environment and is ideal for use in high throughput security scenarios and for the collection of large datasets. We describe the current state of data acquisition of face, gait, ear, and semantic data and present early results showing the quality and range of data that has been collected. The main novelties of this dataset in comparison with other multi-biometric datasets are: 1. gait data exists for multiple views and is synchronised, allowing 3D reconstruction and analysis; 2. the face data is a sequence of images allowing for face recognition in video; 3. the ear data is acquired in a relatively unconstrained environment, as a subject walks past; and 4. the semantic data is considerably more extensive than has been available previously. We shall aim to show the advantages of this new data in biometric analysis, though the scope for such analysis is considerably greater than time and space allows for here

Alien Registration- Bustard, John H. (Saint Agatha, Aroostook County)

https://digitalmaine.com/alien_docs/33120/thumbnail.jp

Design Thinking Innovation Within the Quadruple Helix Approach: a Proposed Framework to Enhance Student Engagement Through Active Learning in Digital Marketing Pedagogy

The purpose of this paper is to develop a framework for enhancing student engagement through active learning and design thinking workshops online. The COVID-19 pandemic has increased the need for digital engagement exponentially, yet the important experiences of collaborative and active learning (AL) have become more challenging to facilitate and support in circumstances of remote access during classes. As such, design thinking (DT) online presented a unique opportunity to explore this collaborative approach to engaging in user-centred design and design innovation. To explore a specific curriculum design dilemma and validate the methodology adopted, online DT workshops were conducted with two different cohorts of students toward co-creating more student-centred forms of learning in two digital marketing (DM) courses. The approach was guided by the POLARIS active learning framework to embed the framework’s seven perspectives (Purpose, Objectives, Learning landscape, Activities and assessment, Resources, Inter-relation with stakeholders, and Student engagement) which were considered to better enhance student engagement in an online learning environment. Using the framework proposed, which additionally integrates Quadruple Helix Model (QHM) actors, would facilitate further DT innovation towards co-creating new value in digital marketing pedagogy, curriculum design, and beyond

The innovation imperative in smart cities and smart tourism: a call for collaboration toward building and sharing knowledge of patterns of success in sustainable living and climate renewal

The imperative of addressing the dual complexities of climate change and the wider sustainability challenge has never been of more importance (Hoegh-Guldberg et al., 2019). Without meaningful, purposeful and actionable steps being embraced by the global community and adopted by civil society, climate change will continue unabated and cause average global temperatures to increase beyond 3°C, with significantly adverse impacts on every ecosystem (Zhenmin and Espinosa, 2019). According to the UN (2020) “it is still possible, using a wide array of technological measures and changes in behaviour, to limit the increase in global mean temperature to two degrees Celsius above pre-industrial levels.

From WOM to aWOM - The evolution of unpaid influence: A perspective article

Purpose. Advances in artificial intelligence (AI) natural language processing may see the emergence of algorithmic word of mouth (aWOM), content created and shared by automated tools. As AI tools improve, aWOM will increase in volume and sophistication, displacing eWOM as an influence on customer decision-making. The purpose of this paper is to provide an overview of the socio technological trends that have encouraged the evolution of informal infulence strategies from WOM to aWOM. Design/methodology/approach. This paper examines the origins and path of development of influential customer communications from word of mouth (WOM) to electronic word of mouth (eWOM) and the emerging trend of aWOM. The growth of aWOM is theorized as a result of new developments in AI natural language processing tools along with autonomous distribution systems in the form of software robots and virtual assistants. Findings. aWOM may become a dominant source of information for tourists, as it can support multimodal delivery of useful contextual information. Individuals, organizations and social media platforms will have to ensure that aWOM is developed and deployed responsibly and ethically. Practical implications. aWOM may emerge as the dominant source of information for tourist decision-making, displacing WOM or eWOM. aWOM may also impact online opinion leaders, as they may be challenged by algorithmically generated content. aWOM tools may also generate content using sensors on personal devices, creating privacy and information security concerns if users did not give permission for such activities. Originality/value. This paper is the first to theorize the emergence of aWOM as autonomous AI communication within the framework of unpaid influence or WOM. As customer engagement will increasingly occur in algorithmic environments that comprise person–machine interactions, aWOM will influence future tourism research and practice

Captive reptile mortality rates in the home and implications for the wildlife trade

The trade in wildlife and keeping of exotic pets is subject to varying levels of national and international regulation and is a topic often attracting controversy. Reptiles are popular exotic pets and comprise a substantial component of the live animal trade. High mortality of traded animals raises welfare concerns, and also has implications for conservation if collection from the wild is required to meet demand. Mortality of reptiles can occur at any stage of the trade chain from collector to consumer. However, there is limited information on mortality rates of reptiles across trade chains, particularly amongst final consumers in the home. We investigated mortality rates of reptiles amongst consumers using a specialised technique for asking sensitive questions, additive Randomised Response Technique (aRRT), as well as direct questioning (DQ). Overall, 3.6% of snakes, chelonians and lizards died within one year of acquisition. Boas and pythons had the lowest reported mortality rates of 1.9% and chameleons had the highest at 28.2%. More than 97% of snakes, 87% of lizards and 69% of chelonians acquired by respondents over five years were reported to be captive bred and results suggest that mortality rates may be lowest for captive bred individuals. Estimates of mortality from aRRT and DQ did not differ significantly which is in line with our findings that respondents did not find questions about reptile mortality to be sensitive. This research suggests that captive reptile mortality in the home is rather low, and identifies those taxa where further effort could be made to reduce mortality rate