From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.

Sampling accuracy of reef resource inventory technique

A new technique called the reef resource inventory (RRI) was developed to map the distribution and abundance of benthos and substratum on reefs. The rapid field sampling technique uses divers to visually estimate the percentage cover of categories of benthos and substratum along 2x20 in plotless strip-transects positioned randomly over the tops, and systematically along the edge of reefs. The purpose of this study was to compare the relative sampling accuracy of the RRI against the line intercept transect technique (LIT), an international standard for sampling reef benthos and substratum. Analysis of paired sampling with LIT and RRI at 51 sites indicated sampling accuracy was not different (P > 0.05) for 8 of the 12 benthos and substratum categories used in the study. Significant differences were attributed to small-scale patchiness and cryptic coloration of some benthos; effects associated with sampling a sparsely distributed animal along a line versus an area; difficulties in discriminating some of the benthos and substratum categories; and differences due to visual acuity since LIT measurements were taken by divers close to the seabed whereas RRI measurements were taken by divers higher in the water column. The relative cost efficiency of the RRI technique was at least three times that of LIT for all benthos and substratum categories and as much as 10 times higher for two categories. These results suggest that the RRI can be used to obtain reliable and accurate estimates of relative abundance of broad categories of reef benthos and substratum.

Radical nursing and the emergence of technique as healthcare technology

The integration of technology in care is core business in nursing and this role requires that we must understand and use technology informed by evidence that goes much deeper and broader than actions and behaviours. We need to delve more deeply into its complexity because there is nothing minor or insignificant about technology as a major influence in healthcare outcomes and experiences. Evidence is needed that addresses technology and nursing from perspectives that examine the effects of technology, especially related to increasing demands for efficiency, the relationship of technology to nursing and caring, and a range of philosophical questions associated with empowering people in their healthcare choices. Specifically, there is a need to confront in practice the ways technique influences care. Technique is the creation of a kind of thinking that is necessary for contemporary healthcare technology to develop and be applied in an efficient and rational manner. Technique is not an entity or specific thing, but rather a way of thinking that seeks to shape and organize nursing activity, and manage efficiently individual difference(s) in care. It emphasizes predetermined causal relationships, conformity, and sameness of product, process, and thought. In response is needed a radical vision of nursing that attempts in a real sense to ensure we meet the needs of individuals and their community. Activism and advocacy are needed, and a willingness to create a certain detachment from the imperatives that technique demands. It is argued that our responsibility as nurses is to respond in practice to the errors, advantages, difficulties, and temptations of technology for the benefit of those who most need our assistance and care.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: A time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O₂Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O₂Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O₂Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Bond Characteristics of Strengthened and Retrofitted Steel by Smart CFRP Technique

Usage of new smart materials in retrofitting of structures has become popular within last decade. Carbon fiber reinforced polymer (CFRP) has been widely used in retrofitting and strengthening of concrete structures and its usage in metallic structures is still in the developing stage. The variation of mechanical properties of CFRP and the consequent effects on strengthening and retrofitting CFRP systems are yet to be investigated under different loading and environmental conditions. This paper presents the results of CFRP strengthened and retrofitted corroded steel plate double strap joints under tension. An accelerated corrosion cell has been developed to accelerate the corrosion of the steel samples and CFRP strengthened samples. The results show a direct comparison of bond characteristics of CFRP strengthened and retrofitted steel double strap joints.

The influence of pre-processing on the estimation of readability of web documents

This paper investigates the effect that text pre-processing approaches have on the estimation of the readability of web pages. Readability has been highlighted as an important aspect of web search result personalisation in previous work. The most widely used text readability measures rely on surface level characteristics of text, such as the length of words and sentences. We demonstrate that different tools for extracting text from web pages lead to very different estimations of readability. This has an important implication for search engines because search result personalisation strategies that consider users reading ability may fail if incorrect text readability estimations are computed.

Application of inverse filtering technique in power system studies

This paper demonstrates the application of inverse filtering technique for power systems. In order to implement this method, the control objective should be based on a system variable that needs to be set on a specific value for each sampling time. A control input is calculated to generate the desired output of the plant and the relationship between the two is used design an auto-regressive model. The auto-regressive model is converted to a moving average model to calculate the control input based on the future values of the desired output. Therefore, required future values to construct the output are predicted to generate the appropriate control input for the next sampling time.

Fabrication and characterization of plasma polymer thin films from monoterpene alcohols for applications in organic electronics and biotechnology

After more than twenty years of basic and applied research, the use of nanotechnology in the design and manufacture of nanoscale materials is rapidly increasing, particularly in commercial applications that span from electronics across renewable energy areas, and biomedical devices. Novel polymers are attracting significant attention for they promise to provide a low−cost high−performance alternative to existing materials. Furthermore, these polymers have the potential to overcome limitations imposed by currently available materials thus enabling the development of new technologies and applications that are currently beyond our reach. This work focuses on the development of a range of new low−cost environmentally−friendly polymer materials for applications in areas of organic (flexible) electronics, optics, and biomaterials. The choice of the monomer reflects the environmentally−conscious focus of this project. Terpinen−4−ol is a major constituent of Australian grown Melaleuca alternifolia (tea tree) oil, attributed with the oil's antimicrobial and anti−inflammatory properties. Plasma polymerisation was chosen as a deposition technique for it requires minimal use of harmful chemicals and produces no hazardous by−products. Polymer thin films were fabricated under varied process conditions to attain materials with distinct physico−chemical, optoelectrical, biological and degradation characteristics. The resultant materials, named polyterpenol, were extensively characterised using a number of well−accepted and novel techniques, and their fundamental properties were defined. Polyterpenol films were demonstrated to be hydrocarbon rich, with variable content of oxygen moieties, primarily in the form of hydroxyl and carboxyl functionalities. The level of preservation of original monomer functionality was shown to be strongly dependent on the deposition energy, with higher applied power increasing the molecular fragmentation and substrate temperature. Polyterpenol water contact angle contact angle increased from 62.7° for the 10 W samples to 76.3° for the films deposited at 100 W. Polymers were determined to resist solubilisation by water, due to the extensive intermolecular and intramolecular hydrogen bonds present, and other solvents commonly employed in electronics and biomedical processing. Independent of deposition power, the surface topography of the polymers was shown to be smooth (Rq <0.5 nm), uniform and defect free. Hardness of polyterpenol coatings increased from 0.33 GPa for 10 W to 0.51 GPa for 100 W (at 500 μN load). Coatings deposited at higher input RF powers showed less mechanical deformation during nanoscratch testing, with no considerable damage, cracking or delamination observed. Independent of the substrate, the quality of film adhesion improved with RF power, suggesting these coatings are likely to be more stable and less susceptible to wear. Independent of fabrication conditions, polyterpenol thin films were optically transparent, with refractive index approximating that of glass. Refractive index increased slightly with deposition power, from 1.54 (10 W) to 1.56 (100 W) at 500 nm. The optical band gap values declined with increasing power, from 2.95 eV to 2.64 eV, placing the material within the range for semiconductors. Introduction of iodine impurity reduced the band gap of polyterpenol, from 2.8 eV to 1.64 eV, by extending the density of states more into the visible region of the electromagnetic spectrum. Doping decreased the transparency and increased the refractive index from 1.54 to 1.70 (at 500 nm). At optical frequencies, the real part of permittivity (k) was determined to be between 2.34 and 2.65, indicating a potential low-k material. These permittivity values were confirmed at microwave frequencies, where permittivity increased with input RF energy – from 2.32 to 2.53 (at 10 GHz ) and from 2.65 to 2.83 (at 20 GHz). At low frequencies, the dielectric constant was determined from current−voltage characteristics of Al−polyterpenol−Al devices. At frequencies below 100 kHz, the dielectric constant varied with RF power, from 3.86 to 4.42 at 1 kHz. For all samples, the resistivity was in order of 10⁸−10⁹ _m (at 6 V), confirming the insulating nature of polyterpenol material. In situ iodine doping was demonstrated to increase the conductivity of polyterpenol, from 5.05 × 10⁻⁸ S/cm to 1.20 × 10⁻⁶ S/cm (at 20 V). Exposed to ambient conditions over extended period of time, polyterpenol thin films were demonstrated to be optically, physically and chemically stable. The bulk of ageing occurred within first 150 h after deposition and was attributed to oxidation and volumetric relaxation. Thermal ageing studies indicated thermal stability increased for the films manufactured at higher RF powers, with degradation onset temperature associated with weight loss shifting from 150 ºC to 205 ºC for 10 W and 100 W polyterpenol, respectively. Annealing the films to 405 °C resulted in full dissociation of the polymer, with minimal residue. Given the outcomes of the fundamental characterisation, a number of potential applications for polyterpenol have been identified. Flexibility, tunable permittivity and loss tangent properties of polyterpenol suggest the material can be used as an insulating layer in plastic electronics. Implementation of polyterpenol as a surface modification of the gate insulator in pentacene-based Field Effect Transistor resulted in significant improvements, shifting the threshold voltage from + 20 V to –3 V, enhancing the effective mobility from 0.012 to 0.021 cm²/Vs, and improving the switching property of the device from 10⁷ to 10⁴. Polyterpenol was demonstrated to have a hole transport electron blocking property, with potential applications in many organic devices, such as organic light emitting diodes. Encapsulation of biomedical devices is also proposed, given that under favourable conditions, the original chemical and biological functionality of terpinen−4−ol molecule can be preserved. Films deposited at low RF power were shown to successfully prevent adhesion and retention of several important human pathogens, including P. aeruginosa, S. aureus, and S. epidermidis, whereas films deposited at higher RF power promoted bacterial cell adhesion and biofilm formation. Preliminary investigations into in vitro biocompatibility of polyterpenol demonstrated the coating to be non−toxic for several types of eukaryotic cells, including Balb/c mice macrophage and human monocyte type (HTP−1 non-adherent) cells. Applied to magnesium substrates, polyterpenol encapsulating layer significantly slowed down in vitro biodegradation of the metal, thus increasing the viability and growth of HTP−1 cells. Recently, applied to varied nanostructured titanium surfaces, polyterpenol thin films successfully reduced attachment, growth, and viability of P. aeruginosa and S. aureus.

Biofuels from food processing wastes

Food processing industry generates substantial high organic wastes along with high energy uses. The recovery of food processing wastes as renewable energy sources represents a sustainable option for the substitution of fossil energy, contributing to the transition of food sector towards a low-carbon economy. This article reviews the latest research progress on biofuel production using food processing wastes. While extensive work on laboratory and pilot-scale biosystems for energy production has been reported, this work presents a review of advances in metabolic pathways, key technical issues and bioengineering outcomes in biofuel production from food processing wastes. Research challenges and further prospects associated with the knowledge advances and technology development of biofuel production are discussed.

Robust automatic face clustering in news video

Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

Insights into students' conceptual understanding using textual analysis: A case study in signal processing

Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Optimisation of in-cell accelerated solvent extraction technique for the determination of organochlorine pesticides in river sediments

Organochlorine pesticides (OCPs) are ubiquitous environmental contaminants with adverse impacts on aquatic biota, wildlife and human health even at low concentrations. However, conventional methods for their determination in river sediments are resource intensive. This paper presents an approach that is rapid and also reliable for the detection of OCPs. Accelerated Solvent Extraction (ASE) with in-cell silica gel clean-up followed by Triple Quadrupole Gas Chromatograph Mass Spectrometry (GCMS/MS) was used to recover OCPs from sediment samples. Variables such as temperature, solvent ratio, adsorbent mass and extraction cycle were evaluated and optimised for the extraction. With the exception of Aldrin, which was unaffected by any of the variables evaluated, the recovery of OCPs from sediment samples was largely influenced by solvent ratio and adsorbent mass and, to some extent, the number of cycles and temperature. The optimised conditions for OCPs extraction in sediment with good recoveries were determined to be 4 cycles, 4.5 g of silica gel, 105 ᴼC, and 4:3 v/v DCM: hexane mixture. With the exception of two compounds (α-BHC and Aldrin) whose recoveries were low (59.73 and 47.66 % respectively), the recovery of the other pesticides were in the range 85.35 – 117.97% with precision < 10 % RSD. The method developed significantly reduces sample preparation time, the amount of solvent used, matrix interference, and is highly sensitive and selective.

vSpeak: Edge detection based feature extraction for sign to text conversion

This paper presents 'vSpeak', the first initiative taken in Pakistan for ICT enabled conversion of dynamic Sign Urdu gestures into natural language sentences. To realize this, vSpeak has adopted a novel approach for feature extraction using edge detection and image compression which gives input to the Artificial Neural Network that recognizes the gesture. This technique caters for the blurred images as well. The training and testing is currently being performed on a dataset of 200 patterns of 20 words from Sign Urdu with target accuracy of 90% and above.