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Saving energy in residential and commercial buildings is of great interest due to diminishing resources. Heating ventilation and air conditioning systems, and electric lighting are responsible for a significant share of energy usage, which makes it desirable to optimise their operations while maintaining user comfort. Such optimisation requires accurate occupancy estimations. In contrast to current, often invasive or unreliable methods we present an approach for accurate occupancy estimation using a wireless sensor network (WSN) that only collects non-sensitive data and a novel, hierarchical analysis method. We integrate potentially uncertain contextual information to produce occupancy estimates at different levels of granularity and provide confidence measures for effective building management. We evaluate our framework in real-world deployments and demonstrate its effectiveness and accuracy for occupancy monitoring in both low-and high-traffic area scenarios. Furthermore, we show how the system is used for analysing historical data and identify effective room misuse and thus a potential for energy saving.

Graphical authentication systems typically claim to be more usable than PIN or password-based systems, but these claims often follow limited, single-stage paradigm testing on a young, student population. We present a more demanding test paradigm in which multiple codes are learned and tested over a three-week period. We use this paradigm with two user populations, comparing the performance of younger and older adults. We first establish baseline performance in a study in which populations of younger and older adults learn PIN codes and we follow this with a second study in which younger and older adults use two face-based graphical authentication systems employing young faces vs. old faces as code components.As expected, older adults show relatively poor performance when compared to younger adults, irrespective of the authentication material, but this age-related deficit can be markedly reduced by the introduction of age-appropriate faces. We conclude firstly that this paradigm provides a good basis for the future evaluation of memory-based authentication systems and secondly that age-appropriate face-based authentication is viable in the security marketplace.

One common practice in relation to alphanumeric passwords is to write them down or share them with a trusted friend or colleague. Graphical password schemes often claim the advantage that they are significantly more secure with respect to both verbal disclosure and writing down. We investigated the reality of this claim in relation to the Passfaces graphical password scheme. By collecting a corpus of naturalistic descriptions of a set of 45 faces, we explored participants' ability to associate descriptions with faces across three conditions in which the decoy faces were selected: (1) at random; (2) on the basis of their visual similarity to the target face; and (3) on the basis of the similarity of the verbal descriptions of the decoy faces to the target face. Participants were found to perform significantly worse when presented with visual and verbally grouped decoys, suggesting that Passfaces can be further secured for description. Subtle differences in both the nature of male and female descriptions, and male and female performance were also observed.

No abstract

Investigating Teenagers' Ability to Detect Phishing Messages line 1: 1st Given Name Surname line 2: dept. name of organization (of Affiliation) line 3: name of organization (of Affiliation) line 4: City, Country line 5: email address or ORCID line 1: 2nd Given Name Surname line 2: dept. name of organization (of Affiliation) line 3: name of organization (of Affiliation) line 4: City, Country line 5: email address or ORCID line 1: 3rd Given Name Surname line 2: dept. name of organization (of Affiliation) line 3: name of organization

Quality assessment in cricket is a complex task that is performed by understanding the combination of individual activities a player is able to perform and by assessing how well these activities are performed. We present a framework for inexpensive and accessible, automated recognition of cricketing shots. By means of body-worn inertial measurement units, movements of batsmen are recorded, which are then analysed using a parallelised, hierarchical recognition system that automatically classifies relevant categories of shots as required for assessing batting quality. Our system then generates meaningful visualisations of key performance parameters, including feet positions, attack/defence, and distribution of shots around the ground. These visualisations are the basis for objective skill assessment thereby focusing on specific personal improvement points as identified through our system. We evaluated our framework through a deployment study where 6 players engaged in batting exercises. Based on the recorded movement data we could automatically identify 20 classes of unique batting shot components with an average F1-score greater than 88%. This analysis is the basis for our detailed analysis of our study participants’ skills. Our system has the potential to rival expensive vision-based systems but at a fraction of the cost.

We then operationalised these qualities as a set of design goals-Assured Anonymity, Constructive Moderation, Adequate Slowness and Controlled Access-in the design and development of a secure anonymous employee voice system. Our novel take on the Enterprise Social Network aims to foster good citizenship whilst also promoting frank yet constructive discussion. We reflect on a two-week deployment of our system, the diverse range of candid discussions that emerged around important workplace issues and the potential for change within the host organization. We conclude by reflecting on the ways in which our approach shaped discourse and supported the creation of a trusted environment for employee voice.