Scene invariant crowd counting

This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd counting across a wide range of environments. The use of local features allows the proposed algorithm to calculate local occupancy statistics, and Gaussian process regression is used to scale to conditions which are unseen in the training data, also providing confidence intervals for the crowd size estimate. A new crowd counting database is introduced to the computer vision community to enable a wider evaluation over multiple scenes, and the proposed algorithm is tested on seven datasets to demonstrate scene invariance and high accuracy. To the authors' knowledge this is the first system of its kind due to its ability to scale between different scenes and viewpoints.

A visual description of early-number counting, addition and subtraction knowledge

Early-number is a rich fabric of interconnected ideas that is often misunderstood and thus taught in ways that do not lead to rich understanding. In this presentation, a visual language is used to describe the organisation of this domain of knowledge. This visual language is based upon Piaget’s notion of reflective abstraction (Dubinsky, 1991; Piaget, 1977/2001), and thus captures the epistemological associations that link the problems, concepts and representations of the domain. The constructs of this visual language are introduced and then applied to the early-number domain. The introduction to this visual language may prompt reflection upon its suitability and significance to the description of other domains of knowledge. Through such a process of analysis and description, the visual language may serve as a scaffold for enhancing pedagogical content knowledge and thus ultimately improve learning outcomes.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Tool-supported dataflow analysis of a security-critical embedded device

Defence organisations perform information security evaluations to confirm that electronic communications devices are safe to use in security-critical situations. Such evaluations include tracing all possible dataflow paths through the device, but this process is tedious and error-prone, so automated reachability analysis tools are needed to make security evaluations faster and more accurate. Previous research has produced a tool, SIFA, for dataflow analysis of basic digital circuitry, but it cannot analyse dataflow through microprocessors embedded within the circuit since this depends on the software they run. We have developed a static analysis tool that produces SIFA compatible dataflow graphs from embedded microcontroller programs written in C. In this paper we present a case study which shows how this new capability supports combined hardware and software dataflow analyses of a security critical communications device.

Hydrogen gas sensing performance of a Pt/graphene/SiC device

In this work, we present the development of a Pt/graphene/SiC device for hydrogen gas sensing. A single layer of graphene was deposited on 6H-SiC via chemical vapor deposition. The presence of graphene C-C bonds was observed via X-ray photoelectron spectroscopy analysis. Current-voltage characteristics of the device were measured at the presence of hydrogen at different temperatures, from 25°C to 170°C. The dynamic response of the device was recorded towards hydrogen gas at an optimum temperature of 130°C. A voltage shift of 191 mV was recorded towards 1% hydrogen at −1 mA constant current.

Secure authentication procedure with mobile device for ubiquitous health environments

Medical industries have brought Information Technology (IT) in their systems for both patients and medical staffs due to the numerous benefits of IT we experience at presently. Moreover, the Mobile healthcare (M-health) system has been developed as the first step of Ubiquitous Health Environment (UHE). With the mobility and multi-functions, M-health system will be able to provide more efficient and various services for both doctors and patients. Due to the invisible feature of mobile signals, hackers have easier access to hospital networks than wired network systems. This may result in several security incidents unless security protocols are well implemented. In this paper, user authentication and authorization procedures will applied as a featured component at each level of M-health systems inthe hospital environment. Accordingly, M-health system in the hospital will meet the optimal requirements as a countermeasure to its vulnerabilities.

Frank-starling control of a left ventricular assist device

A physiological control system was developed for a rotary left ventricular assist device (LVAD) in which the target pump flow rate (LVADQ) was set as a function of left atrial pressure (LAP), mimicking the Frank-Starling mechanism. The control strategy was implemented using linear PID control and was evaluated in a pulsatile mock circulation loop using a prototyped centrifugal pump by varying pulmonary vascular resistance to alter venous return. The control strategy automatically varied pump speed (2460 to 1740 to 2700 RPM) in response to a decrease and subsequent increase in venous return. In contrast, a fixed-speed pump caused a simulated ventricular suction event during low venous return and higher ventricular volumes during high venous return. The preload sensitivity was increased from 0.011 L/min/mmHg in fixed speed mode to 0.47L/min/mmHg, a value similar to that of the native healthy heart. The sensitivity varied automatically to maintain the LAP and LVADQ within a predefined zone. This control strategy requires the implantation of a pressure sensor in the left atrium and a flow sensor around the outflow cannula of the LVAD. However, appropriate pressure sensor technology is not yet commercially available and so an alternative measure of preload such as pulsatility of pump signals should be investigated.

Videogame control device impact on the play experience

New types of control devices for videogames have emerged and expanded the demographics of the game playing public, yet little is known about which populations of gamers prefer which style of interaction and why. This paper presents data from a study that seeks to clarify the influence the control interface has on the play experience. Three commercial control devices were categorised using an existing typology, according to how the interface maps physical control inputs with the virtual gameplay actions. The devices were then used in a within-groups experimental design aimed at measuring differences in play experience across 64 participants. Descriptive analysis is undertaken on the performance, play experience and preference results for each device. Potential explanations for these results are discussed, as well as the direction of future work.

Efficacy of oral or intrauterine device-delivered progestin in patients with complex endometrial hyperplasia with atypia or early endometrial adenocarcinoma : a meta-analysis and systematic review of the literature

Objectives: To investigate the efficacy of progestin treatment to achieve pathological complete response (pCR) in patients with complex atypical endometrial hyperplasia (CAH) or early endometrial adenocarcinoma (EC). Methods: A systematic search identified 3245 potentially relevant citations. Studies containing less than ten eligible CAH or EC patients in either oral or intrauterine treatment arm were excluded. Only information from patients receiving six or more months of treatment and not receiving other treatments was included. Weighted proportions of patients achieving pCR were calculated using R software. Results: Twelve studies met the selection criteria. Eleven studies reported treatment of patients with oral (219 patients, 117 with CAH, 102 with grade 1 Stage I EC) and one reported treatment of patients with intrauterine progestin (11 patients with grade 1 Stage IEC). Overall, 74% (95% confidence interval [CI] 65-81%) of patients with CAH and 72% (95% CI 62-80%) of patients with grade 1 Stage I EC achieved a pCR to oral progestin. Disease progression while on oral treatment was reported for 6/219 (2.7%), and relapse after initial complete response for 32/159 (20.1%) patients. The weighted mean pCR rate of patients with grade 1 Stage I EC treated with intrauterine progestin from one prospective pilot study and an unpublished retrospective case series from the Queensland Centre of Gynaecologic Oncology (QCGC) was 68% (95% CI 45- 86%). Conclusions: There is a lack of high quality evidence for the efficacy of progestin in CAH or EC. The available evidence however suggests that treatment with oral or intrauterine progestin is similarly effective. The risk of progression during treatment is small but longer follow-up is required. Evidence from prospective controlled clinical trials is warranted to establish how the efficacy of progestin for the treatment of CAH and EC can be improved further.

Intravascular device-related research : future priority areas for cancer nursing

The majority of cancer nurses have to manage intravascular devices (IVDs) on a daily basis, thus placing nurses in the strongest position to generate and use best available evidence to inform this area of practice and to ensure that patients are receiving the best care available. Our literature clearly reflects that cancer nurses are concerned about complications associated with IVDs (eg, extravasation,1 IVD-related bloodstream infection [IVD-BSI],2,3 and thrombosis4). Although enormous attention is given to this area, a number of nursing practices are not sufficiently based on empirical evidence.5,6 Nurses need to set goals and priorities for future research and investments. Priority areas for future research are suggested here for your consideration.

The magic of numbers and the amazing disappearing act : the politics of counting youth homelessness

No-one wants to see young people who are no longer able to stay at home with their parents living in situations that are neither stable nor safe. Most Australians also appreciate that youth homelessness is typically a result of factors beyond the control of young people like poverty, lack of affordable housing, parental divorce or separation, family conflict and violence, sexual abuse, or mental health problems.1 Since the Burdekin Report of 1989 first put the issue on the national agenda, youth homelessness has been a point of some political sensitivity as the numbers of young homeless stayed stubbornly high through the 1990s and into the 2000s.

Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.