Designing to maintain human agency in context-aware systems

This paper describes a series of design games, specifically aimed at exploring shifts in human agency, how they are managed, and the impact this will have on the design of future context-aware applications. The games focussed on understanding information handling issues in dental practice with participants from the University of Queensland Dental School playing an active role in the activities. Participatory design activities reveal how technology solution impact on dental practices. By finding methods of representing technological possibilities in ways which can easily be understood we enhance the contribution that dentists can make to the design process.

Maintaining human agency in the design on context-aware systems : Design games in a dental surgery

This paper describes a series of design games, specifically aimed at exploring shifts in human agency in order to inform the design of context-aware applications. The games focused on understanding information handling issues in dental practice with participants from a university dental school playing an active role in the activities. Participatory design activities help participants to reveal potential implicit technical resources that can be presented explicitly in technologies in order to assist humans in managing their interactions with and amidst technical systems gracefully.

Variations in MIMO-OFDM channel capacity due to random human movement in an indoor environment

Channel measurements and simulations have been carried out to observe the effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity. An in-house built MIMO-OFDM packet transmission demonstrator equipped with four transmitters and four receivers has been utilized to perform channel measurements at 5.2 GHz. Variations in the channel capacity dynamic range have been analysed for 1 to 10 pedestrians and different antenna arrays (2 × 2, 3 × 3 and 4 × 4). Results show a predicted 5.5 bits/s/Hz and a measured 1.5 bits/s/Hz increment in the capacity dynamic range with the number of pedestrian and the number of antennas in the transmitter and receiver array.

Stem cell regulatory gene expression in human adult dental pulp and periodontal ligament cells undergoing odontogenic/osteogenic differentiation

Introduction During development and regeneration, odontogenesis and osteogenesis are initiated by a cascade of signals driven by several master regulatory genes. Methods In this study, we investigated the differential expression of 84 stem cell–related genes in dental pulp cells (DPCs) and periodontal ligament cells (PDLCs) undergoing odontogenic/osteogenic differentiation. Results Our results showed that, although there was considerable overlap, certain genes had more differential expression in PDLCs than in DPCs. CCND2, DLL1, and MME were the major upregulated genes in both PDLCs and DPCs, whereas KRT15 was the only gene significantly downregulated in PDLCs and DPCs in both odontogenic and osteogenic differentiation. Interestingly, a large number of regulatory genes in odontogenic and osteogenic differentiation interact or crosstalk via Notch, Wnt, transforming growth factor β (TGF-β)/bone morphogenic protein (BMP), and cadherin signaling pathways, such as the regulation of APC, DLL1, CCND2, BMP2, and CDH1. Using a rat dental pulp and periodontal defect model, the expression and distribution of both BMP2 and CDH1 have been verified for their spatial localization in dental pulp and periodontal tissue regeneration. Conclusions This study has generated an overview of stem cell–related gene expression in DPCs and PDLCs during odontogenic/osteogenic differentiation and revealed that these genes may interact through the Notch, Wnt, TGF-β/BMP, and cadherin signalling pathways to play a crucial role in determining the fate of dental derived cell and dental tissue regeneration. These findings provided a new insight into the molecular mechanisms of the dental tissue mineralization and regeneration

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.

Enhanced human bone marrow stromal cell affinity for modified poly(L-lactide) surfaces by the upregulation of adhesion molecular genes

To enhance and regulate cell affinity for poly (l-lactic acid) (PLLA) based materials, two hydrophilic ligands, poly (ethylene glycol) (PEG) and poly (l-lysine) (PLL), were used to develop triblock copolymers: methoxy-terminated poly (ethylene glycol)-block-poly (l-lactide)-block-poly (l-lysine) (MPEG-b-PLLA-b-PLL) in order to regulate protein absorption and cell adhesion. Bone marrow stromal cells (BMSCs) were cultured on different composition of MPEG-b-PLLA-b-PLL copolymer films to determine the effect of modified polymer surfaces on BMSC attachment. To understand the molecular mechanism governing the initial cell adhesion on difference polymer surfaces, the mRNA expression of 84 human extracellular matrix (ECM) and adhesion molecules was analysed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). It was found that down regulation of adhesion molecules was responsible for the impaired BMSC attachment on PLLA surface. MPEG-b-PLLA-b-PLL copolymer films improved significantly the cell adhesion and cytoskeleton expression by upregulation of relevant molecule genes significantly. Six adhesion genes (CDH1, ITGL, NCAM1, SGCE, COL16A1, and LAMA3) were most significantly influenced by the modified PLLA surfaces. In summary, polymer surfaces altered adhesion molecule gene expression of BMSCs, which consequently regulated cell initial attachment on modified PLLA surfaces.

Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

Vitronectin modulates human mesenchymal stem cell response to insulin-like growth factor-I and transforming growth factor beta 1 in a serum-free environment

The use of animal sera for the culture of therapeutically important cells impedes the clinical use of the cells. We sought to characterize the functional response of human mesenchymal stem cells (hMSCs) to specific proteins known to exist in bone tissue with a view to eliminating the requirement of animal sera. Insulin-like growth factor-I (IGF-I), via IGF binding protein-3 or -5 (IGFBP-3 or -5) and transforming growth factor-beta 1 (TGF-beta(1)) are known to associate with the extracellular matrix (ECM) protein vitronectin (VN) and elicit functional responses in a range of cell types in vitro. We found that specific combinations of VN, IGFBP-3 or -5, and IGF-I or TGF-beta(1) could stimulate initial functional responses in hMSCs and that IGF-I or TGF-beta(1) induced hMSC aggregation, but VN concentration modulated this effect. We speculated that the aggregation effect may be due to endogenous protease activity, although we found that neither IGF-I nor TGF-beta(1) affected the functional expression of matrix metalloprotease-2 or -9, two common proteases expressed by hMSCs. In summary, combinations of the ECM and growth factors described herein may form the basis of defined cell culture media supplements, although the effect of endogenous protease expression on the function of such proteins requires investigation.

Labelled silhouettes for human pose estimation

This paper proposes a new method of using foreground silhouette images for human pose estimation. Labels are introduced to the silhouette images, providing an extra layer of information that can be used in the model fitting process. The pixels in the silhouettes are labelled according to the corresponding body part in the model of the current fit, with the labels propagated into the silhouette of the next frame to be used in the fitting for the next frame. Both single and multi-view implementations are detailed, with results showing performance improvements over only using standard unlabelled silhouettes.

Automatic tracking, super-resolution and recognition of human faces from surveillance video

Identifying an individual from surveillance video is a difficult, time consuming and labour intensive process. The proposed system aims to streamline this process by filtering out unwanted scenes and enhancing an individual's face through super-resolution. An automatic face recognition system is then used to identify the subject or present the human operator with likely matches from a database. A person tracker is used to speed up the subject detection and super-resolution process by tracking moving subjects and cropping a region of interest around the subject's face to reduce the number and size of the image frames to be super-resolved respectively. In this paper, experiments have been conducted to demonstrate how the optical flow super-resolution method used improves surveillance imagery for visual inspection as well as automatic face recognition on an Eigenface and Elastic Bunch Graph Matching system. The optical flow based method has also been benchmarked against the ``hallucination'' algorithm, interpolation methods and the original low-resolution images. Results show that both super-resolution algorithms improved recognition rates significantly. Although the hallucination method resulted in slightly higher recognition rates, the optical flow method produced less artifacts and more visually correct images suitable for human consumption.

Research training and national innovation systems in Australia, Finland and the United States : a policy and systems study supported by 30 case studies of research students in the fields of geospatial science, wireless communication, biosciences, and materials science and engineering

Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.