Playing Pairs with Pepper

As robots become increasingly prevalent in almost all areas of society, the factors affecting humans trust in those robots becomes increasingly important. This paper is intended to investigate the factor of robot attributes, looking specifically at the relationship between anthropomorphism and human development of trust. To achieve this, an interaction game, Matching the Pairs, was designed and implemented on two robots of varying levels of anthropomorphism, Pepper and Husky. Participants completed both pre- and post-test questionnaires that were compared and analyzed predominantly with the use of quantitative methods, such as paired sample t-tests. Post-test analyses suggested a positive relationship between trust and anthropomorphism with $80\%$ of participants confirming that the robots' adoption of facial features assisted in establishing trust. The results also indicated a positive relationship between interaction and trust with $90\%$ of participants confirming this for both robots post-testComment: Presented at AI-HRI AAAI-FSS, 2018 (arXiv:1809.06606

How Can a Robot Signal Its Incapability to Perform a Certain Task to Humans in an Acceptable Manner?

In this paper, a robot that is using politeness to overcome its incapability to serve is presented. The mobile robot “Alex” is interacting with human office colleagues in their environment and delivers messages, phone calls, and companionship. The robot's battery capacity is not sufficient to survive a full working day. Thus, the robot needs to recharge during the day. By doing so it is unavailable for tasks that involve movement. The study presented in this paper supports the idea that an incapability of fullfiling an appointed task can be overcome by politeness and showing appropriate behaviour. The results, reveal that, even the simple adjustment of spoken utterances towards a more polite phrasing can change the human's perception of the robot companion. This change in the perception can be made visible by analysing the human's behaviour towards the robot

K-Means Fingerprint Clustering for Low-Complexity Floor Estimation in Indoor Mobile Localization

Indoor localization in multi-floor buildings is an important research problem. Finding the correct floor, in a fast and efficient manner, in a shopping mall or an unknown university building can save the users' search time and can enable a myriad of Location Based Services in the future. One of the most widely spread techniques for floor estimation in multi-floor buildings is the fingerprinting-based localization using Received Signal Strength (RSS) measurements coming from indoor networks, such as WLAN and BLE. The clear advantage of RSS-based floor estimation is its ease of implementation on a multitude of mobile devices at the Application Programming Interface (API) level, because RSS values are directly accessible through API interface. However, the downside of a fingerprinting approach, especially for large-scale floor estimation and positioning solutions, is their need to store and transmit a huge amount of fingerprinting data. The problem becomes more severe when the localization is intended to be done on mobile devices which have limited memory, power, and computational resources. An alternative floor estimation method, which has lower complexity and is faster than the fingerprinting is the Weighted Centroid Localization (WCL) method. The trade-off is however paid in terms of a lower accuracy than the one obtained with traditional fingerprinting with Nearest Neighbour (NN) estimates. In this paper a novel K-means-based method for floor estimation via fingerprint clustering of WiFi and various other positioning sensor outputs is introduced. Our method achieves a floor estimation accuracy close to the one with NN fingerprinting, while significantly improves the complexity and the speed of the floor detection algorithm. The decrease in the database size is achieved through storing and transmitting only the cluster heads (CH's) and their corresponding floor labels.Comment: Accepted to IEEE Globecom 2015, Workshop on Localization and Tracking: Indoors, Outdoors and Emerging Network

Self-esteem: defining, measuring and promoting an elusive concept

Self-esteem has been a much debated construct in the educational sphere and interest in the area continues to flourish in classroom and research contexts. While the merits of targeting self-esteem have long been accentuated (Emler, 2001; MacIntyre, 2005; Cooper and Jacobs, 2011), the validity of the construct has also been questioned in light of modest empirical support. Recently, clearer definitions of the concepts involved and more reliable means of assessing these variables have helped allay doubts about its validity. However, a number of challenges persist in this regard, most notably in the context of learners with special educational needs (SEN). In light of recent calls for schools to explicitly plan for, monitor and measure the self-esteem of pupils with SEN alongside cognitive-academic outcomes (National Council for Special Education (NCSE), 2014), a review of research and practices in this area is timely. It is hoped that this review will provide some guidance for teachers in terms of defining, measuring and promoting self-esteem outcomes

Using Pupil Diameter to Measure Cognitive Load

In this paper, we will present a method for measuring cognitive load and online real-time feedback using the Tobii Pro 2 eye-tracking glasses. The system is envisaged to be capable of estimating high cognitive load states and situations, and adjust human-machine interfaces to the user's needs. The system is using well-known metrics such as average pupillary size over time. Our system can provide cognitive load feedback at 17-18 Hz. We will elaborate on our results of a HRI study using this tool to show it's functionality.Comment: Presented at AI-HRI AAAI-FSS, 2018 (arXiv:1809.06606

The interaction between voice and appearance in the embodiment of a robot tutor

Robot embodiment is, by its very nature, holistic and understanding how various aspects contribute to the user perception of the robot is non-trivial. A study is presented here that investigates whether there is an interaction effect between voice and other aspects of embodiment, such as movement and appearance, in a pedagogical setting. An on-line study was distributed to children aged 11–17 that uses a modified Godspeed questionnaire. We show an interaction effect between the robot embodiment and voice in terms of perceived lifelikeness of the robot. Politeness is a key strategy used in learning and teaching, and here an effect is also observed for perceived politeness. Interestingly, participants’ overall preference was for embodiment combinations that are deemed polite and more like a teacher, but are not necessarily the most lifelike. From these findings, we are able to inform the design of robotic tutors going forward

Carotenoids - Effective Radical Scavengers for Healthy and Beautiful Skin

Free radicals are involved in various diseases and skin aging. To reduce and prevent this risk, our body produces antioxidants that can neutralize free radicals. However, some antioxidants need to be taken up with food, so a balanced and varied diet is essential for human health and beauty, along with sufficient exercise. Vegetables, especially curly kale, show very good antioxidative capacity due to the presence of carotenoids. As the recommended daily intake of vegetables is usually not consumed, dietary supplements are a good possibility to ingest carotenoids in a controlled and natural way. The positive effect of carotenoid-based dietary supplements on the skin has already been shown in several studies on healthy volunteers. Innovative non-invasive measuring methods have shown that oil extracts from vegetables significantly reduce not only free radicals in the skin but also the age-related breakdown of collagen and have a positive effect on skin parameters such as wrinkle volume. Thus, a balanced mixture of different natural carotenoids contributes to maintaining health and beauty

Efficient Delay Tracking Methods with Sidelobes Cancellation for BOC-Modulated Signals

In positioning applications, where the line of sight (LOS) is needed with high accuracy, the accurate delay estimation is an important task. The new satellite-based positioning systems, such as Galileo and modernized GPS, will use a new modulation type, that is, the binary offset carrier (BOC) modulation. This type of modulation creates multiple peaks (ambiguities) in the envelope of the correlation function, and thus triggers new challenges in the delay-frequency acquisition and tracking stages. Moreover, the properties of BOC-modulated signals are yet not well studied in the context of fading multipath channels. In this paper, sidelobe cancellation techniques are applied with various tracking structures in order to remove or diminish the side peaks, while keeping a sharp and narrow main lobe, thus allowing a better tracking. Five sidelobe cancellation methods (SCM) are proposed and studied: SCM with interference cancellation (IC), SCM with narrow correlator, SCM with high-resolution correlator (HRC), SCM with differential correlation (DC), and SCM with threshold. Compared to other delay tracking methods, the proposed SCM approaches have the advantage that they can be applied to any sine or cosine BOC-modulated signal. We analyze the performances of various tracking techniques in the presence of fading multipath channels and we compare them with other methods existing in the literature. The SCM approaches bring improvement also in scenarios with closely-spaced paths, which are the most problematic from the accurate positioning point of view.</p

Misconceptions about traumatic brain injury among probation services

Purpose: The prevalence of traumatic brain injury (TBI) among offender populations is significantly higher than among the general population. Despite this, no study has yet assessed the knowledge of members of the probation service surrounding traumatic brain injury (TBI). Method: Knowledge was assessed among members of the Probation Board for Northern Ireland (PBNI) using a cross-sectional online version of the Common Misconceptions about TBI (CM-TBI) questionnaire. Mean total misconception scores, along with scores on four subdomains (recovery, sequelae, insight, and hidden injury) were calculated. Analysis of variance was used to explore differences in misconceptions based on the collected demographic information. Results: The overall mean percentage of misconceptions for the group was 22.37%. The subdomain with the highest rate of misconceptions (38.21%) was insight into injury which covered misconceptions around offenders’ self-awareness of injuries. Those who knew someone with a brain injury scored significantly higher in the CM-TBI total score (F(1,63)= 6.639, p = .012), the recovery subdomain (F(1,63) = 10.080, p = .002), and the insight subdomain (F(1,63) = 5.834, p = .019). Additionally, significant training deficits around TBI were observed among the probation service. Conclusions: This study is the first of its kind to examine the level of understanding around TBI within probation services. The findings reflect potential barriers to identification and rehabilitation of TBI for offenders coming into contact with the criminal justice system. A lack of identification coupled with misconceptions about TBI could lead to inaccurate court reporting with a subsequent impact on sentencing

Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios