This extended paper contributes a methodology and a detailed analysis of app installation and functionality on a ‘vintage’ device. Experimental results are presented that demonstrate barriers to the reuse of vintage Apple devices, and solutions are posited. 230 apps across 23 unique app categories were tested to determine if they could be downloaded, installed, and opened, and whether they appeared functional on a vintage Apple device. Only 29 (12.6%) of the apps could be downloaded directly, and in contrast 140 (60.9%) of the apps were downloadable with the aid of another Apple device. In total, 141 (61.3%) of applications downloaded either directly or indirectly were considered functional and capable of running on the device. We discuss measures Apple and developers could take to support legacy devices users, prolong device use, enable reuse and, potentially, prevent functional devices from becoming e-waste.

A growing sense of unfairness permeates our quasi-digital society. Despite drivers supporting and motivating ethical practice in the digital technology ecosystem, there are compounding barriers to fairness that, at every level, impact technology innovation, delivery and access. Amongst these are barriers and omissions at the earliest stages of technology intentionality and design; systemic inadequacies in sensing systems that deteriorate performance for individuals based on ethnicity, age and physicality; system design, co-requisite and interface decisions that limit access; biases and inequities in datasets and algorithms; and limiting factors in system function and security. Additionally, there are concerns about unethical and illegal practices amongst digital technology providers: for example, in planned obsolescence and anti-competitive behaviors, failings in data practices and security, and in responses to problematic use and behaviors. It is critical that these failings are identified and addressed to better evolve a fairer future digital technology ecosystem. This paper contributes a perspective on technological stewardship and innovation; it identifies the compounding nature of barriers to fairness in the current digital technology ecosystem, and contrasts these with the non-compounding fairness drivers that, in general, establish minimum requirements.

Anaphylaxis is an increasingly prevalent life-threatening allergic condition that requires people with anaphylaxis and their caregivers to be trained in the avoidance of allergen triggers and in the administration of adrenaline autoinjectors. The prompt and correct administration of autoinjectors in the event of an anaphylactic reaction is a significant challenge in the management of anaphylaxis. Unfortunately, many people do not know how to use autoinjectors and either fail to use them or fail to use them correctly. This is due in part to deficiencies in training and also to the lack of a system encouraging continuous practice with feedback. Assistive smartphone healthcare technologies have demonstrated potential to support the management of chronic conditions such as diabetes and cardiovascular disease, but there have been deficiencies in their evaluation and there has been a lack of application to anaphylaxis. This paper describes AllergiSense, a smartphone app and sensing system for anaphylaxis management, and presents the results of a randomized, controlled, prepost evaluation of AllergiSense injection training and feedback tools with healthy participants. Participants whose training was supplemented with AllergiSense injection feedback achieved significantly better practiced injections with 90.5% performing correct injections compared to only 28.6% in the paper-only control group. In addition, the results provide insights into possible self-efficacy failings in traditional training and the benefits of embedding self-efficacy theory into the technology design process.

Biofeedback is a technique that teaches a user to control physiological signals by using mental processes. It has been used to treat mental and physical disorders such as stress, anxiety, diabetes, hypertension, headache, Raynaud's syndrome and other health problems. Biofeedback has conventionally been used at the office of the therapist. Mobile biofeedback may improve the outcomes as there would not be restrictions of place and time. The acquisition board is based on the open hardware Arduino and communicated by Bluetooth to the cellular phone which was programmed to implement thermal and electrodermal response (EDR) biofeedback. Five participants were part of this study, they were able to increase the temperature of the index finger and increase EDR levels using the equipment. Both techniques of biofeedback showed to decrease anxiety and stress greater than doing a relaxing activity. Stress levels were assessed by State-Trait Anxiety Inventory (STAI) questionnaire used to record stress and anxiety traits. This study suggests that biofeedback might be implemented on mobile devices as a therapeutic tool for stress and anxiety.

A new method for the compression of angiogram video sequences is presented. The method is based on the philosophy that diagnostically significant areas of the image should be allocated the greatest proportion of the total allocated bit budget. The approach uses a three-dimensional wavelet-coder based on the popular set partitioning in hierarchical trees algorithm. Incorporated into this framework are a region-of-interest (ROI) detection stage and a texture-modeling stage. The combined result is an approach that models the high-frequency wavelet coefficients for some diagnostically unimportant regions of the image in an extremely efficient manner. This allows additional bits to be used within the ROI to improve the quality of the diagnostically significant areas. Results are compared for a number of real data sets and evaluated by trained cardiologists.

We propose a new charging scheme for multi-domain differentiated services (DiffServ) networks. Our scheme considers the existence of non-DiffServ networks on the route of transmission. The charging agent at the edge of the source domain inserts in the DiffServ traffic charging measurement (CM) packets which contain traffic and charging information. The CM packets are subsequently returned by the charging agents at the downstream DiffServ domains. The charges can be easily calculated according to the feedback information in the returned CM packets. In addition to the above, we propose two signaling mechanisms for our charging schemes. We show that our scheme is simple, fair and scalable.

Summary form only given. A novel method for the compression of angiogram video sequences is presented. The approach consists of a 3D wavelet encoding algorithm, incorporating a region of interest (ROI) estimation model to provide higher-quality image reconstruction in areas considered to be diagnostically significant. This is coupled with a texture modelling procedure, which provides a model for some of the high frequency wavelet coefficients corresponding to diagnostically insignificant regions. This allows some of the wavelet coefficients to be represented extremely efficiently. The results are evaluated by trained cardiologists and show some promise.

Summary form only given. All pipelines are subject to corrosion and require inspection in accordance with regulatory requirements to ensure human safety. Intelligent pipeline inspection gauges (PIGs) have provided reliable online inspection of pipelines, supplying operators with detailed information about pipeline condition. We present a method for the diagnostically lossless compression of pipeline inspection data and discuss important pipeline features, e.g. welds, cracks and erosion objects. The dataset, transverse field inspection (TFI) data, is a new type of pipeline inspection data in contrast to the traditional magnetic flux leakage (MFL) inspection data. The nature of the data makes feature preservation essential. TFI pipeline features have been collected, classified and analysed and examples are shown. Feature detection is desirable in order to identify regions of diagnostic interest. Incorporation of region-of-interest (ROI) into the SPIHT encoding scheme enables the allocation of a greater proportion of the total allowance of bits to the regions of the image identified as diagnostically significant. Our quality assessment is based on the preservation of important defect parameters to ensure diagnostically lossless performance. We present results comparing performance between ROI SPIHT and non-ROI SPIHT.

This paper presents residential video service quality of service (QoS) results obtained from an experimental testbed employing constant bitrate MPEG-2 transport streams on a real ADSL/ATM access network testbed. The experimental design addresses the choice of MPEG encoding parameters and the spatio-temporal characterization of video test content. The Institute Telecommunications Science video quality metric is used for objective video fidelity measurement. Our results demonstrate the complex multilayer propagation of QoS parameters, using deterministic and exponentially distributed cell losses, and their relationship to video quality and video bitrate. The paper provides a basis for developing and comparing these results with similar video service systems; for example, using MPEG encoded video over IP. These results provide an important insight into the factors relevant to the provisioning and management of new multi-service network infrastructures.

This paper describes a multistage perceptual quality assessment (MPQA) model for compressed images. The motivation for the development of a perceptual quality assessment is to measure (in)visible differences between original and processed images. The MPQA produces visible distortion maps and quantitative error measures informed by considerations of the human visual system (HVS). Original and decompressed images are decomposed into different spatial frequency bands and orientations modeling the human cortex. Contrast errors are calculated for each frequency and orientation, and masked as a function of contrast sensitivity and background uncertainty. Spatially masked contrast error measurements are then made across frequency bands and orientations to produce a single perceptual distortion visibility map (PDVM). A perceptual quality rating (PQR) is calculated from the PDVM and transformed into a one to five scale, PQR(1-5), for direct comparison with the mean opinion score, generally used in subjective ratings. The proposed MPQA model is based on existing perceptual quality assessment models, while it is differentiated by the inclusion of contrast masking as a function of background uncertainty. A pilot study of clinical experiments on wavelet-compressed digital angiogram has been performed on a sample set of angiogram images to identify diagnostically acceptable reconstruction. Our results show that the PQR(1-5) of diagnostically acceptable lossy image reconstructions have better agreement with cardiologists' responses than objective error measurement methods, such as peak signal-to-noise ratio A Perceptual thresholding and CSF-based Uniform quantization (PCU) method is also proposed using the vision models presented in this paper. The vision models are implemented in the thresholding and quantization stages of a compression algorithm and shown to produce improved compression ratio performance with less visible distortion than that of the embedded zerotrees wavelet (EZWs).