Text segmentation in unconstrained hand-drawings in whiteboard photos

In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.

Performance analysis of secure unified communications in the VMware-based cloud

Unified communications as a service (UCaaS) can be regarded as a cost-effective model for on-demand delivery of unified communications services in the cloud. However, addressing security concerns has been seen as the biggest challenge to the adoption of IT services in the cloud. This study set up a cloud system via VMware suite to emulate hosting unified communications (UC), the integration of two or more real time communication systems, services in the cloud in a laboratory environment. An Internet Protocol Security (IPSec) gateway was also set up to support network-level security for UCaaS against possible security exposures. This study was aimed at analysis of an implementation of UCaaS over IPSec and evaluation of the latency of encrypted UC traffic while protecting that traffic. Our test results show no latency while IPSec is implemented with a G.711 audio codec. However, the performance of the G.722 audio codec with an IPSec implementation affects the overall performance of the UC server. These results give technical advice and guidance to those involved in security controls in UC security on premises as well as in the cloud.

Identifying relevant information for emergency services from twitter in response to natural disaster

This project proposes a framework that identifies high‐value disaster-based information from social media to facilitate key decision-making processes during natural disasters. At present it is very difficult to differentiate between information that has a high degree of disaster relevance and information that has a low degree of disaster relevance. By digitally harvesting and categorising social media conversation streams automatically, this framework identifies highly disaster-relevant information that can be used by emergency services for intelligence gathering and decision-making.

Schizophrenia Genetic Variants are not Associated with Intelligence

Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.

Permissions in Deontic Event-Calculus

Permissions are special case of deontic effects and play important role compliance. Essentially they are used to determine the obligations or prohibitions to contrary. A formal language e.g., temporal logic, event-calculus et., not able to represent permissions is doomed to be unable to represent most of the real-life legal norms. In this paper we address this issue and extend deontic-event-calculus (DEC) with new predicates for modelling permissions enabling it to elegantly capture the intuition of real-life cases of permissions.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Collision avoidance between UAV clusters using swarm intelligence techniques

In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.

Pattern visual evoked potentials in dyslexic versus normal children

Purpose: Presence of neurophysiological abnormalities in dyslexia has been a conflicting issue. This study was performed to evaluate the role of sensory visual deficits in the pathogenesis of dyslexia. Methods: Pattern visual evoked potentials (PVEP) were recorded in 72 children including 36 children with dyslexia and 36 children without dyslexia (controls) who were matched for age, sex and intelligence. Two check sizes of 15 and 60 min of arc were used with temporal frequencies of 1.5 Hz for transient and 6 Hz for steady‑state methods. Results: Mean latency and amplitude values for 15 min arc and 60 min arc check sizes using steady state and transient methods showed no significant difference between the two study groups (P values: 0.139/0.481/0.356/0.062).Furthermore, no significant difference was observed between two methods of PVEPs in dyslexic and normal children using 60min arc with high contrast(Pvalues: 0.116, 0.402, 0.343 and 0.106). Conclusion: The sensitivity of PVEP has high validity to detect visual deficits in children with dyslexic problem. However, no significant difference was found between dyslexia and normal children using high contrast stimuli.

Cognitive Functioning in Young Adults with Depression, Anxiety Disorders, or Burnout Symptoms : Findings from a Population-based Sample

Background. Evidence of cognitive dysfunction in depressive and anxiety disorders is growing. However, the neuropsychological profile of young adults has received only little systematic investigation, although depressive and anxiety disorders are major public health problems for this age group. Available studies have typically failed to account for psychiatric comorbidity, and samples derived from population-based settings have also seldom been investigated. Burnout-related cognitive functioning has previously been investigated in only few studies, again all using clinical samples and wide age groups. Aims. Based on the information gained by conducting a comprehensive review, studies on cognitive impairment in depressive and anxiety disorders among young adults are rare. The present study examined cognitive functioning in young adults with a history of unipolar depressive or anxiety disorders in comparison to healthy peers, and associations of current burnout symptoms with cognitive functioning, in a population-based setting. The aim was also to determine whether cognitive deficits vary as a function of different disorder characteristics, such as severity, psychiatric comorbidity, age at onset, or the treatments received. Methods. Verbal and visual short-term memory, verbal long-term memory and learning, attention, psychomotor processing speed, verbal intelligence, and executive functioning were measured in a population-based sample of 21-35 year olds. Performance was compared firstly between participants with pure non-psychotic depression (n=68) and healthy peers (n=70), secondly between pure (n=69) and comorbid depression (n=57), and thirdly between participants with anxiety disorders (n=76) and healthy peers (n=71). The diagnostic procedure was based on the SCID interview. Fourthly, the associations of current burnout symptoms, measured with the Maslach Burnout Inventory General Survey, and neuropsychological test performance were investigated among working young adults (n=225). Results. Young adults with depressive or anxiety disorders, with or without psychiatric comorbidity, were not found to have major cognitive impairments when compared to healthy peers. Only mildly compromised verbal learning was found among depressed participants. Pure and comorbid depression groups did not differ in cognitive functioning, either. Among depressed participants, those who had received treatment showed more impaired verbal memory and executive functioning, and earlier onset corresponded with more impaired executive functioning. In anxiety disorders, psychotropic medication and low psychosocial functioning were associated with deficits in executive functioning, psychomotor processing speed, and visual short-term memory. Current burnout symptoms were associated with better performance in verbal working memory and verbal intelligence. However, lower examiner-rated social and occupational functioning was associated with problems in verbal attention, memory, and learning. Conclusions. Depression, anxiety disorders, or burnout symptoms may not be associated with major cognitive deficits among young adults derived from the general population. Even psychiatric comorbidity may not aggravate cognitive functioning in depressive or anxiety disorders among these young adults. However, treatment-seeking in depression was found to be associated with cognitive deficits, suggesting that these deficits relate to increased distress. Additionally, early-onset depression, found to be associated with executive dysfunction, may represent a more severe form of the disorder. In anxiety disorders, those with low symptom-related psychosocial functioning may have cognitive impairment. An association with self-reported burnout symptoms and cognitive deficits was not detected, but individuals with low social and occupational functioning may have impaired cognition.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Low birth weight in MZ twins discordant for birth weight is associated with shorter telomere length and lower IQ, but not anxiety/depression in later life

Shorter telomere length (TL) has found to be associated with lower birth weight and with lower cognitive ability and psychiatric disorders. However, the direction of causation of these associations and the extent to which they are genetically or environmentally mediated are unclear. Within-pair comparisons of monozygotic (MZ) and dizygotic (DZ) twins can throw light on these questions. We investigated correlations of within pair differences in telomere length, IQ, and anxiety/depression in an initial sample from Brisbane (242 MZ pairs, 245 DZ same sex (DZSS) pairs) and in replication samples from Amsterdam (514 MZ pairs, 233 DZSS pairs) and Melbourne (19 pairs selected for extreme high or low birth weight difference). Intra-pair differences of birth weight and telomere length were significantly correlated in MZ twins, but not in DZSS twins. Greater intra-pair differences of telomere length were observed in the 10% of MZ twins with the greatest difference in birth weight compared to the bottom 90% in both samples and also in the Melbourne sample. Intra-pair differences of telomere length and IQ, but not of TL and anxiety/depression, were correlated in MZ twins, and to a smaller extent in DZSS twins. Our findings suggest that the same prenatal effects that reduce birth weight also influence telomere length in MZ twins. The association between telomere length and IQ is partly driven by the same prenatal effects that decrease birth weight.

Susceptibility genes and neurodevelopmental mechanisms in dyslexia

Developmental dyslexia is a specific reading disability, which is characterised by unexpected difficulty in reading, spelling and writing despite adequate intelligence, education and social environment. It is the most common childhood learning disorder affecting 5-10 % of the population and thus constitutes the largest portion of all learning disorders. It is a persistent developmental failure although it can be improved by compensation. According to the most common theory, the deficit is in phonological processing, which is needed in reading when the words have to be divided into phonemes, or distinct sound elements. This occurs in the lowest level of the hierarchy of the language system and disturbs processes in higher levels, such as understanding the meaning of words. Dyslexia is a complex genetic disorder and previous studies have found nine locations in the genome that associate with it. Altogether four susceptibility genes have been found and this study describes the discovery of the first two of them, DYX1C1 and ROBO1. The first clues were obtained from two Finnish dyslexic families that have chromosomal translocations which disrupt these genes. Genetic analyses supported their role in dyslexia: DYX1C1 associates with dyslexia in the Finnish population and ROBO1 was linked to dyslexia in a large Finnish pedigree. In addition a genome-wide scan in Finnish dyslexic families was performed. This supported the previously detected dyslexia locus on chromosome 2 and revealed a new locus on chromosome 7. Dyslexia is a neurological disorder and the neurobiological function of the susceptibility genes DYX1C1 and ROBO1 are consistent with this. ROBO1 is an axon guidance receptor gene, which is involved in axon guidance across the midline in Drosophila and axonal pathfinding between the two hemispheres via the corpus callosum, as well as neuronal migration in the brain of mice. The translocation and decreased ROBO1 expression in dyslexic individuals indicate that two functional copies of ROBO1 gene are required in reading. DYX1C1 was a new gene without a previously known function. Inhibition of Dyx1c1 expression showed that it is needed in normal brain development in rats. Without Dyx1c1 protein, the neurons in the developing brain will not migrate to their final position in the cortex. These two dyslexia susceptibility genes DYX1C1 and ROBO1 revealed two distinct neurodevelopmental mechanisms of dyslexia, axonal pathfinding and neuronal migration. This study describes the discovery of the genes and our research to clarify their role in developmental dyslexia.

Pathogenicity of Blumeria graminis f. sp. hordei in Australia in 2010 and 2011

A survey of the Australian barley powdery mildew (Blumeria graminis f. sp. hordei) population was conducted in 2010 and 2011. Three hundred and sixty-two isolates of the pathogen were collected from 18 locations across all six states of Australia. Thirty-two barley differentials were used and 11 genotypes were able to differentiate the population with virulence frequencies varying from 14.5 % to 96.6 %. Twenty-seven pathotypes were detected. Fifteen of them were found in both years and they represented 92.0 % of all isolates examined. No virulence was found on a further 16 major genes for resistance (Mla1, Mla3, Mla6, Mla7, Mla9, Mla10, Mla12, Mla13, Mla23, MlaN81, Mlh, MlLa, Mlp1, Ml(IM9), Ml(St) and mlo) indicating a relatively simple population and the ready availability of diverse sources of resistance. This paper reports the powdery mildew virulences present in Australia, provides intelligence for future resistance breeding and sets a basis for further virulence studies.

Effects of self-reported wisdom on happiness: Not much more than emotional intelligence?

Wisdom and emotional intelligence are increasingly popular topics among happiness scholars. Despite their conceptual overlap, no empirical research has examined their interrelations and incremental predictive validities. The aims of this study were (a) to investigate associations between multidimensional conceptualizations of self-reported wisdom (Ardelt in Res Aging 25(3):275-324, 2003, 2004) and emotional intelligence (Davies et al. in J Pers Soc Psychol 75:989-1015, 1998) and (b) to examine the joint effects of self-reported wisdom and emotional intelligence on dimensions of happiness (life satisfaction as well as positive and negative affect). Data were provided by two samples: 175 university students and 400 online workers. Correlations between a composite wisdom score, a composite emotional intelligence score, and happiness facets were positive and moderate in size. Regression analyses showed that the effects of composite wisdom on life satisfaction and positive affect (but not negative affect) became weaker and non-significant when composite emotional intelligence was controlled. Additional analyses including three dimensions of the self-reported wisdom (cognitive, reflective, and affective wisdom) and four dimensions of emotional intelligence (self- and others-emotions appraisal, use and regulation of emotion) revealed a more differentiated pattern of results. Implications for future research on wisdom and happiness are discussed.