Lost in translation (and rotation) : rapid extrinsic calibration for 2D and 3D LIDARs

This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.

Study of mechanical deformations on tough skinned vegetables during mechanical peeling process

Peeling is an essential phase of post harvesting and processing industry; however undesirable processing losses are unavoidable and always have been the main concern of food processing sector. There are three methods of peeling fruits and vegetables including mechanical, chemical and thermal, depending on the class and type of fruit. By comparison, the mechanical methods are the most preferred; mechanical peeling methods do not create any harmful effects on the tissue and they keep edible portions of produce fresh. The main disadvantage of mechanical peeling is the rate of material loss and deformations. Obviously reducing material losses and increasing the quality of the process has a direct effect on the whole efficiency of food processing industry, this needs more study on technological aspects of these operations. In order to enhance the effectiveness of food industrial practices it is essential to have a clear understanding of material properties and behaviour of tissues under industrial processes. This paper presents the scheme of research that seeks to examine tissue damage of tough skinned vegetables under mechanical peeling process by developing a novel FE model of the process using explicit dynamic finite element analysis approach. A computer model of mechanical peeling process will be developed in this study to stimulate the energy consumption and stress strain interactions of cutter and tissue. The available Finite Element softwares and methods will be applied to establish the model. Improving the knowledge of interactions and involves variables in food operation particularly in peeling process is the main objectives of the proposed study. Understanding of these interrelationships will help researchers and designer of food processing equipments to develop new and more efficient technologies. Presented work intends to review available literature and previous works has been done in this area of research and identify current gap in modelling and simulation of food processes.

Dynamics of rod and cone photoreceptor interactions under mesopic light levels

Visual adaptation regulates contrast sensitivity during dynamically changing light conditions (Crawford, 1947; Hecht, Haig & Chase, 1937). These adaptation dynamics are unknown under dim (mesopic) light levels when the rod (R) and long (L), medium (M) and short (S) wavelength cone photoreceptor classes contribute to vision via interactions in shared non-opponent Magnocellular (MC), chromatically opponent Parvocellular (PC) and Koniocellular (KC) visual pathways (Dacey, 2000). This study investigated the time-course of adaptation and post-receptoral pathways mediating receptor specific rod and cone interactions under mesopic illumination. A four-primary photostimulator (Pokorny, Smithson & Quinlan, 2004) was used to independently control the activity of the four photoreceptor classes and their post-receptoral visual athways in human observers. In the first experiment, the contrast sensitivity and time-course of visual adaptation under mesopic illumination were measured for receptoral (L, S, R) and post-receptoral (LMS, LMSR, L-M) stimuli. An incremental (Rapid-ON) sawtooth conditioning pulse biased detection to ON-cells within the visual pathways and sensitivity was assayed relative to pulse onset using a briefly presented incremental probe that did not alter adaptation. Cone.Cone interactions with luminance stimuli (L cone, LMS, LMSR) reduced sensitivity by 15% and the time course of recovery was 25± 5ms-1 (μ ± SEM). PC mediated (+L-M) chromatic stimuli sensitivity loss was less (8%) than for luminance and recovery was slower (μ = 2.95 ± 0.05 ms-1), with KC mediated (S cone) chromatic stimuli showing a high sensitivity loss (38%) and the slowest recovery time (1.6 ± 0.2 ms-1). Rod-Rod interactions increased sensitivity by 20% and the time course of recovery was 0.7 ± 0.2 ms-1 (μ ± SD). Compared to these interaction types, Rod-Cone interactions reduced sensitivity to a lesser degree (5%) and showed the fastest recovery (μ = 43 ± 7 ms-1). In the second experiment, rod contribution to the magnocellular, parvocellular and koniocellular post-receptoral pathways under mesopic illumination was determined as a function of incremental stimulus duration and waveform (rectangular; sawtooth) using a rod colour match procedure (Cao, Pokorny & Smith, 2005; Cao, Pokorny, Smith & Zele, 2008a). For a 30% rod increment, a cone match required a decrease in [L/(L+M)] and an increase in [L+M] and [S/(L+M)], giving a greenish-blue and brighter appearance for probe durations of 75 ms or longer. Probe durations less than 75 ms showed an increase in [L+M] and no change in chromaticity [L/(L+M) or S/(L+M)], uggesting mediation by the MC pathway only for short duration rod stimuli. s We advance previous studies by determining the time-course and nature of photoreceptor specific retinal interactions in the three post-receptoral pathways under mesopic illumination. In the first experiment, the time-course of adaptation for ON cell processing was determined, revealing opponent cell facilitation in chromatic PC and KC pathways. The Rod-Rod and Rod-Cone data identify previously unknown interaction types that act to maintain contrast sensitivity during dynamically changing light conditions and improve the speed of light adaptation under mesopic light levels. The second experiment determined the degree of rod contribution to the inferred post-eceptoral pathways as a function of the temporal properties of the rod signal. r The understanding of the mechanisms underlying interactions between photoreceptors under mesopic illumination has implications for the study of retinal disease. Visual function has been shown to be reduced in persons with age-related maculopathy (ARM) risk genotypes prior to clinical signs of the disease (Feigl, Cao, Morris & Zele, 2011) and disturbances in rod-mediated adaptation have been shown in early phases of ARM (Dimitrov, Guymer, Zele, Anderson & Vingrys, 2008; Feigl, Brown, Lovie-Kitchin & Swann, 2005). Also, the understanding of retinal networks controlling vision enables the development of international lighting standards to optimise visual performance nder dim light levels (e.g. work-place environments, transportation).

Four years on – are the Gazelles still running? A longitudinal study of firm performance after a period of rapid growth

Gazelles, or very rapidly growing firms, are important because they contribute disproportionately to economic growth. There is a concern that some of these firms pursue growth too aggressively resulting in lower subsequent performance. We investigate the relationship between growth and subsequent profitability for gazelle firms, and how this is moderated by firm strategy. Previous empirical research regarding the growth-profitability relationship for firms in general is rather inconclusive, with only one study specifically investigating gazelle firms. Likewise, there are theoretical arguments both for and against growth leading to profitability that equally apply to gazelle firms. Further, while contingency theory might suggest the relationship depends on the firm’s strategy, earlier studies have not investigated this relationship. We address these questions using longitudinal data (seven years) for a sample of 964 Danish Gazelle firms. Our study finds a clear positive relationship between growth and subsequent profitability among gazelle firms. Moreover, this relationship is stronger for firms pursuing a broad market strategy rather than a focus or niche strategy. An important managerial implication is that the growth strategy should be clearly integrated with the general strategic orientation of the firm.

The acquisition of an artificial logographic script and bilingual working memory : Evidence for L1-specific orthographic processing skills transfer in Chinese-English bilinguals

Studies of orthographic skills transfer between languages focus mostly on working memory (WM) ability in alphabetic first language (L1) speakers when learning another, often alphabetically congruent, language. We report two studies that, instead, explored the transferability of L1 orthographic processing skills in WM in logographic-L1 and alphabetic-L1 speakers. English-French bilingual and English monolingual (alphabetic-L1) speakers, and Chinese-English (logographic-L1) speakers, learned a set of artificial logographs and associated meanings (Study 1). The logographs were used in WM tasks with and without concurrent articulatory or visuo-spatial suppression. The logographic-L1 bilinguals were markedly less affected by articulatory suppression than alphabetic-L1 monolinguals (who did not differ from their bilingual peers). Bilinguals overall were less affected by spatial interference, reflecting superior phonological processing skills or, conceivably, greater executive control. A comparison of span sizes for meaningful and meaningless logographs (Study 2) replicated these findings. However, the logographic-L1 bilinguals’ spans in L1 were measurably greater than those of their alphabetic-L1 (bilingual and monolingual) peers; a finding unaccounted for by faster articulation rates or differences in general intelligence. The overall pattern of results suggests an advantage (possibly perceptual) for logographic-L1 speakers, over and above the bilingual advantage also seen elsewhere in third language (L3) acquisition.

Evidence for carbonate platform failure during rapid sea-level rise; ca 14 000 year old bioclastic flow deposits in the Lesser Antilles

Bioclastic flow deposits offshore from the Soufrie`re Hills volcano on Montserrat in the Lesser Antilles were deposited by the largest volume sediment flows near this active volcano in the last 26 kyr. The volume of these deposits exceeds that of the largest historic volcanic dome collapse in the world, which occurred on Montserrat in 2003. These flows were most probably generated by a large submarine slope failure of the carbonate shelf comprising the south west flank of Antigua or the east flank of Redonda; adjacent islands that are not volcanically active. The bioclastic flow deposits are relatively coarse-grained and either ungraded or poorly graded, and were deposited by non cohesive debris flow and high density turbidity currents. The bioclastic deposit often comprises multiple sub-units that cannot be correlated between core sites; some located just 2 km apart. Multiple sub-units in the bioclastic deposit result from either flow reflection, stacking of multiple debris flow lobes, and/or multi-stage collapse of the initial landslide. This study provides unusually precise constraints on the age of this mass flow event that occurred at ca 14 ka. Few large submarine landslides have been well dated, but the slope failures that have been dated are commonly associated with periods of rapid sea-level change.

A tensor encoding model for semantic processing

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.

Thermal performance of non-load bearing LSF walls using numerical studies

Fire safety of light gauge cold-formed steel frame (LSF) wall systems is significant to the build-ing design. Gypsum plasterboard is widely used as a fire safety material in the building industry. It contains gypsum (CaSO4.2H2O), Calcium Carbonate (CaCO3) and most importantly free and chemically bound water in its crystal structure. The dehydration of the gypsum and the decomposition of Calcium Carbonate absorb heat, which gives the gypsum plasterboard fire resistant qualities. Recently a new composite panel system was developed, where a thin insulation layer was used externally between two plasterboards to improve the fire performance of LSF walls. In this research, finite element thermal models of both the traditional LSF wall panels with cavity insulation and the new LSF composite wall panels were developed to simulate their thermal behaviour under standard and realistic design fire conditions. Suitable thermal properties of gypsum plaster-board, insulation materials and steel were used. The developed models were then validated by comparing their results with fire test results. This paper presents the details of the developed finite element models of non-load bearing LSF wall panels and the thermal analysis results. It has shown that finite element models can be used to simulate the thermal behaviour of LSF walls with varying configurations of insulations and plasterboards. The results show that the use of cavity insulation was detrimental to the fire rating of LSF walls while the use of external insulation offered superior thermal protection. Effects of real fire conditions are also presented.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.