Surviving the electronic panopticon: New lessons in democracy, surveillance, and community in young adult fiction

The ability of new information and communication technologies to pierce previously impenetrable physical, personal, and social boundaries has particular relevance to contemporary society and young people as there is now more information that can be collected, accessed, and distributed about individuals and groups. The ability to know about each other has become a central feature of many young people’s lives. The need to know is further complicated by other questions – Who knows? What do they know? What are the implications of this knowledge?. These questions are a consequence of society having become more mobile and networked enabling increased surveillance, tracking, and spreading of dis/information. With the acceleration of new pervasive and immersive technologies, these questions have taken on a new urgency and significance that go beyond an Orwellian Big Brother scenario. This chapter extends Foucault’s notion of the panopticon to take account of the challenges of an AmI environment of smart networked devices. By drawing on examples of recent young adult fiction, I examine some of the ways in which these texts invite their readers to reflect and speculate on the uneasy relationship between surveillance and democracy and what this means for individual rights and freedom, and a sense of place and belonging.

A biomechanical study of spherical grip

Use of the hand is vital in working life due to the grabbing and pinching it performs. Spherical grip is the most commonly used, due to similarity to the gripping of a computer mouse. Knowledge of its execution and the involved elements is essential. Analysis of this exertion with surface electromyography devices (to register muscular activity) and accelerometer devices (to register movement values ) can provide multiple variables. Six subjects performed ball gripping and registered real-time electromyography (thenar region, hypothenar region, first dorsal interosseous, flexors of the wrist, flexor carpi ulnaris and extensors of the wrist muscles) and accelerometer (thumb, index, middle, ring, pinky and palm) values. The obtained data was resampled “R software” and processed “Matlab Script” based on an automatic numerical sequence recognition program. Electromyography values were normalized on the basis of maximum voluntary contraction, whilst modular values were calculated for the acceleration vector. After processing and analysing the obtained data and signal, it was possible to identify five stages of movement in accordance with the module vector from the palm. The statistical analysis of the variables was descriptive: average and standard deviations. The outcome variables focus on the variations of the modules of the vector (between the maximum and minimum values of each module and phase) and the maximum values of the standardized electromyography of each muscle. Analysis of movement through accelerometer and electromyography variables can give us an insight into the operation of spherical grip. The protocol and treatment data can be used as a system to complement existing assessments in the hand.

An MRF based abnormal event detection approach using motion and appearance features

Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.

Machine learning for activity recognition : hip versus wrist data

Problem addressed Wrist-worn accelerometers are associated with greater compliance. However, validated algorithms for predicting activity type from wrist-worn accelerometer data are lacking. This study compared the activity recognition rates of an activity classifier trained on acceleration signal collected on the wrist and hip. Methodology 52 children and adolescents (mean age 13.7 +/- 3.1 year) completed 12 activity trials that were categorized into 7 activity classes: lying down, sitting, standing, walking, running, basketball, and dancing. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the right hip and the non-dominant wrist. Features were extracted from 10-s windows and inputted into a regularized logistic regression model using R (Glmnet + L1). Results Classification accuracy for the hip and wrist was 91.0% +/- 3.1% and 88.4% +/- 3.0%, respectively. The hip model exhibited excellent classification accuracy for sitting (91.3%), standing (95.8%), walking (95.8%), and running (96.8%); acceptable classification accuracy for lying down (88.3%) and basketball (81.9%); and modest accuracy for dance (64.1%). The wrist model exhibited excellent classification accuracy for sitting (93.0%), standing (91.7%), and walking (95.8%); acceptable classification accuracy for basketball (86.0%); and modest accuracy for running (78.8%), lying down (74.6%) and dance (69.4%). Potential Impact Both the hip and wrist algorithms achieved acceptable classification accuracy, allowing researchers to use either placement for activity recognition.

The pattern of coupling dynamics between postural motion, isotonic hand movements and physiological tremor

This study was designed to examine differences in the coupling dynamics between upper limb motion, physiological tremor and whole body postural sway in young healthy adults. Acceleration of the hand and fingers, forearm EMG activity and postural sway data were recorded. Estimation of the degree of bilateral and limb motion-postural sway coupling was determined by cross correlation, coherence and Cross-ApEn analyses. The results of the analysis revealed that, under postural tremor conditions, there was no significant coupling between limbs, muscles or sway across all metrics of coupling. In contrast, performing a rapid alternating flexion/extension movement about the wrist joint (with one or both limbs) resulted in stronger coupling between limb motion and postural sway. These results support the view that, for physiological tremor responses, the control of postural sway is maintained independent to tremor in the upper limb. However, increasing the level of movement about a distal segment of one arm (or both) leads to increased coupling throughout the body. The basis for this increased coupling would appear to be related to the enhanced neural drive to task-specific muscles within the upper limb.

Effect of mobile phone distraction on car-following behaviour

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Language and literacy in mathematics: stepping stones or stumbling blocks in accelerating junior-secondary students

The authors have collaborated in the development and initial evaluation of a curriculum for mathematics acceleration. This paper reports upon the difficulties encountered with documenting student understanding using pen-and-paper assessment tasks. This leads to a discussion of the impact of students’ language and literacy on mathematical performance and the consequences for motivation and engagement as a result of simplifying the language in the tests, and extending student work to algebraic representations. In turn, implications are drawn for revisions to assessment used within the project and the language and literacy focus included within student learning experiences.

Reliability in the Parameterization of the Functional Reach Test in Elderly Stroke Patients: A Pilot Study

BACKGROUND: Postural instability is one of the major complications found in stroke survivors. Parameterising the functional reach test (FRT) could be useful in clinical practice and basic research. OBJECTIVES: To analyse the reliability, sensitivity, and specificity in the FRT parameterisation using inertial sensors for recording kinematic variables in patients who have suffered a stroke. DESIGN: Cross-sectional study. While performing FRT, two inertial sensors were placed on the patient's back (lumbar and trunk). PARTICIPANTS: Five subjects over 65 who suffer from a stroke. MEASUREMENTS: FRT measures, lumbosacral/thoracic maximum angular displacement, maximum time of lumbosacral/thoracic angular displacement, time return initial position, and total time. Speed and acceleration of the movements were calculated indirectly. RESULTS: FRT measure is  12.75±2.06 cm. Intrasubject reliability values range from 0.829 (time to return initial position (lumbar sensor)) to 0.891 (lumbosacral maximum angular displacement). Intersubject reliability values range from 0.821 (time to return initial position (lumbar sensor)) to 0.883 (lumbosacral maximum angular displacement). FRT's reliability was 0.987 (0.983-0.992) and 0.983 (0.979-0.989) intersubject and intrasubject, respectively. CONCLUSION: The main conclusion could be that the inertial sensors are a tool with excellent reliability and validity in the parameterization of the FRT in people who have had a stroke.

FGF-2 induces the proliferation of human periodontal ligament cells and modulates their osteoblastic phenotype by affecting Runx2 expression in the presence and absence of osteogenic inducers

The exact phenotype of human periodontal ligament cells (hPDLCs) remains a controversial area. Basic fibroblast growth factor (FGF‑2) exhibits various functions and its effect on hPDLCs is also controversial. Therefore, the present study examined the effect of FGF‑2 on the growth and osteoblastic phenotype of hPDLCs with or without osteogenic inducers (dexamethasone and β‑glycerophosphate). FGF‑2 was added to defined growth culture medium and osteogenic inductive culture medium. Cell proliferation, osteogenic differentiation and mineralization were measured. The selected differentiation markers, Runx2, collagen type Ⅰ, α1 (Col1a1), osteocalcin (OCN) and epidermal growth factor receptor (EGFR), were investigated by reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). Runx2 and OCN protein expression was measured by western blotting. FGF‑2 significantly increased the proliferation of hPDLCs, but did not affect alkaline phosphatase activity. RT‑qPCR analysis revealed enhanced mRNA expression of Runx2, OCN and EGFR, but suppressed Col1a1 gene expression in the absence of osteogenic inducers, whereas all these gene levels had no clear trend in their presence. The Runx2 protein expression was clearly increased, but the OCN protein level showed no evident trend. The mineralization assay demonstrated that FGF‑2 inhibited mineralized matrix deposition with osteogenic inducers. These results suggested that FGF‑2 induces the growth of immature hPDLCs, which is a competitive inhibitor of epithelial downgrowth, and suppresses their differentiation into mineralized tissue by affecting Runx2 expression. Therefore, this may lead to the acceleration of periodontal regeneration.

Perceiving the interactive body in dance: Enhancing kinesthetic empathy through art objects

Through a consideration of audience experience of embodiment in contemporary dance performance, this project used kinesthetic empathy as a theoretical construct to inform choreographic decision-making. The research outcome challenged the traditional performer/audience relationship through an interactive dance performance work entitled Planets. This acted as a platform that allowed both audience and performer to collaboratively listen to, process and form movement in a shared kinesthetic state. This connection was enabled through the distribution of interactive art objects, which responded to the shifting proximity between performer and audience. The performance was thus experienced through following a shared goal as instigated by the interactive technology. Through practice-led research, knowledge from kinesthetic empathy, embodied cognition and the mirror neuron system were used to develop the project’s aim in encouraging interactive audiences to engage in movement. This aim influenced studio explorations of movement through an enquiry into the kinesthetic self in dance. Investigations used movement quality, tension, mobility and acceleration to access a familiar movement vocabulary appropriate for a broad interactive audience. This informed the role of the researcher as performer. Planets was developed as a collaborative project between Michael Smith and interactive visual designer Andy Bates and performed over three nights at the Ars Electronica Festival 2014 in Linz, Austria. Supported by documented footage from Planets and audience responses to the performances, this paper draws together the theoretical underpinnings behind the development of the work and includes the experiential perspective of the performer.

Teleoperation of a 7 DOF humanoid robot arm using human arm accelerations and EMG signals

We present our work on tele-operating a complex humanoid robot with the help of bio-signals collected from the operator. The frameworks (for robot vision, collision avoidance and machine learning), developed in our lab, allow for a safe interaction with the environment, when combined. This even works with noisy control signals, such as, the operator’s hand acceleration and their electromyography (EMG) signals. These bio-signals are used to execute equivalent actions (such as, reaching and grasping of objects) on the 7 DOF arm.

An improved computational method in structural dynamics

Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.

Quantification of functional hand grip using electromyography and inertial sensor-derived accelerations: Clinical implications

Background Assessing hand injury is of great interest given the level of involvement of the hand with the environment. Knowing different assessment systems and their limitations generates new perspectives. The integration of digital systems (accelerometry and electromyography) as a tool to supplement functional assessment allows the clinician to know more about the motor component and its relation to movement. Therefore, the purpose of this study was the kinematic and electromyography analysis during functional hand movements. Method Ten subjects carried out six functional movements (terminal pinch, termino-lateral pinch, tripod pinch, power grip, extension grip and ball grip). Muscle activity (hand and forearm) was measured in real time using electromyograms, acquired with the Mega ME 6000, whilst acceleration was measured using the AcceleGlove. Results Electrical activity and acceleration variables were recorded simultaneously during the carrying out of the functional movements. The acceleration outcome variables were the modular vectors of each finger of the hand and the palm. In the electromyography, the main variables were normalized by the mean and by the maximum muscle activity of the thenar region, hypothenar, first interosseous dorsal, wrist flexors, carpal flexors and wrist extensors. Conclusions Knowing muscle behavior allows the clinician to take a more direct approach in the treatment. Based on the results, the tripod grip shows greater kinetic activity and the middle finger is the most relevant in this regard. Ball grip involves most muscle activity, with the thenar region playing a fundamental role in hand activity. Clinical relevance Relating muscle activation, movements, individual load and displacement offers the possibility to proceed with rehabilitation by individual component.

Reliability and criterion-related validity with a smartphone used in timed-up-and-go test

Background The capacity to diagnosys, quantify and evaluate movement beyond the general confines of a clinical environment under effectiveness conditions may alleviate rampant strain on limited, expensive and highly specialized medical resources. An iPhone 4® mounted a three dimensional accelerometer subsystem with highly robust software applications. The present study aimed to evaluate the reliability and concurrent criterion-related validity of the accelerations with an iPhone 4® in an Extended Timed Get Up and Go test. Extended Timed Get Up and Go is a clinical test with that the patient get up from the chair and walking ten meters, turn and coming back to the chair. Methods A repeated measure, cross-sectional, analytical study. Test-retest reliability of the kinematic measurements of the iPhone 4® compared with a standard validated laboratory device. We calculated the Coefficient of Multiple Correlation between the two sensors acceleration signal of each subject, in each sub-stage, in each of the three Extended Timed Get Up and Go test trials. To investigate statistical agreement between the two sensors we used the Bland-Altman method. Results With respect to the analysis of the correlation data in the present work, the Coefficient of Multiple Correlation of the five subjects in their triplicated trials were as follows: in sub-phase Sit to Stand the ranged between r = 0.991 to 0.842; in Gait Go, r = 0.967 to 0.852; in Turn, 0.979 to 0.798; in Gait Come, 0.964 to 0.887; and in Turn to Stand to Sit, 0.992 to 0.877. All the correlations between the sensors were significant (p < 0.001). The Bland-Altman plots obtained showed a solid tendency to stay at close to zero, especially on the y and x-axes, during the five phases of the Extended Timed Get Up and Go test. Conclusions The inertial sensor mounted in the iPhone 4® is sufficiently reliable and accurate to evaluate and identify the kinematic patterns in an Extended Timed Get and Go test. While analysis and interpretation of 3D kinematics data continue to be dauntingly complex, the iPhone 4® makes the task of acquiring the data relatively inexpensive and easy to use.

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.