Adversarially Tuned Scene Generation

Generalization performance of trained computer vision systems that use computer graphics (CG) generated data is not yet effective due to the concept of 'domain-shift' between virtual and real data. Although simulated data augmented with a few real world samples has been shown to mitigate domain shift and improve transferability of trained models, guiding or bootstrapping the virtual data generation with the distributions learnt from target real world domain is desired, especially in the fields where annotating even few real images is laborious (such as semantic labeling, and intrinsic images etc.). In order to address this problem in an unsupervised manner, our work combines recent advances in CG (which aims to generate stochastic scene layouts coupled with large collections of 3D object models) and generative adversarial training (which aims train generative models by measuring discrepancy between generated and real data in terms of their separability in the space of a deep discriminatively-trained classifier). Our method uses iterative estimation of the posterior density of prior distributions for a generative graphical model. This is done within a rejection sampling framework. Initially, we assume uniform distributions as priors on the parameters of a scene described by a generative graphical model. As iterations proceed the prior distributions get updated to distributions that are closer to the (unknown) distributions of target data. We demonstrate the utility of adversarially tuned scene generation on two real-world benchmark datasets (CityScapes and CamVid) for traffic scene semantic labeling with a deep convolutional net (DeepLab). We realized performance improvements by 2.28 and 3.14 points (using the IoU metric) between the DeepLab models trained on simulated sets prepared from the scene generation models before and after tuning to CityScapes and CamVid respectively.Comment: 9 pages, accepted at CVPR 201

An investigation into employee and organisational dynamics in a flexible work framework

The object of this research is to provide a detailed perspective of employee and organisational dynamics in a flexible work practices framework, intra- and post-pandemic. This paper aims to explore the influence of flexible work practices on the employee and the organisation. The most challenging issues during the intra-Covid-19 pandemic period were individual and organisational adaption to new work practices with the aim of sustaining optimum levels of worker morale and productivity, which became meaningful in the context of the continuation of flexible work in transformed and alternative work settings post-pandemic. During this research, non-empirical research was conducted in the arrangement of a review utilising existing empirical evidence, which provides for literature of varied methodologies. This resulted in a detailed non-structured analysis of the remote work concept and its diverse employee and organisational inferences. As a result of the research, it is shown that although improved productivity was regarded as a remote work gain, the merit of employee motivation and job satisfaction is deemed forecasters of prime organisational performance with the consideration that maintaining and supporting an operationally efficient and strengthened organisational work culture should be an organisational aim. In future, a proposed approach of synthesising remote work expertise in policies and syllabi will endorse and sustain the progression of the post-pandemic workplace. It is therefore suggested that a comprehensive PESTLE analysis be performed by utilising the proposed flexible work five-factor model towards crafting a comprehensive list of influences on employee and organisational remote work dynamics for the success of continued remote work practices

Educator's pedagogy influencing the effective use of computers for teaching purposes in classrooms: Lessons learned from secondary schools in South Africa

The use of computers in the classroom could allow both educators and learners to achieve new capabilities. There are underlying factors, however, that are obstructing the adoption rate of computer use for instructional purposes in schools. This research focused on these problems with a view to determining which critical success factors promote a higher adoption rate of computer usage in education. To investigate the secondary school educator's perceptions of the use of computers for teaching purposes and to analyse the effect of these strategies on their teaching pedagogies in the present environment. The nature of the study required a mixed methods approach to be employed, making use of both quantitative and qualitative data. Two questionnaires, one for the educators and one for the principals of the schools were hand-delivered to 60 secondary schools. Exploratory factor analysis and various internal consistency measures were used to assess and analyse the data. The analyses of the data indicated that educator pedagogies were the highest predictors on the use of computers in the classroom. Although the quantitative analyses for educator support, training and attitude were the lowest predictors on the use of computers, the qualitative analysis, nevertheless, found sufficient support for it. Educationists and policy-makers must include all principals and educators when technological innovations are introduced into schools. All these role-players need to be cognisant of the implications if innovations are not appropriately implemented. Including the use of computers in educator training programs is important so that pre-service educators can see the benefits of using the computer in their own teaching. Educator pedagogy, theories and beliefs and access to computers were the highest predictors of using computers, hence a model was developed. The model aims to strengthen the educators' initiatives to increase the likelihood that would result in enhanced teaching and learning when using computers

Self-stabilizing sorting on linear networks

A self-stabilizing system has the ability to recover from an arbitrary (possibly faulty) state to a normal state without any manual intervention. A self-stabilizing algorithm does not require any initialization. Starting from an arbitrary state, it is guaranteed to satisfy its specification in finite number of steps; We propose a self-stabilizing distributed sorting algorithm on an oriented linear network with n nodes. Each node holds some initial value(s) drawn from an arbitrary set. We assume that we start with at most k items in the network. Each node has a local memory whose space is restricted to O(k * L ) where L is the maximum number of bits to store one item. A node may collect more than one value during the process of sorting. The stabilizing time for sorting is O(n) rounds where a round is the duration for all the enabled processes to execute at least one enabled step. We claim that our algorithm is self-stabilizing for the following reasons:;If any node starts in a faulty state (meaning its value is not sorted with respect to its neighbors), the algorithm guarantees that the node will reach the legitimate state (where a legitimate state is a state in which the values are in sorted order) in a finite amount of time, and will remain in the legitimate state until another fault occurs. Each node repeatedly communicates with its neighbors to check if the values of its neighbors are sorted with respect to its own value. If the values are not in order, either the node or one of its neighbors will eventually be enabled to execute so that in finite amount of time the values will be sorted

Innovations in pedagogy – the contributions of Sonam Wangchuk and Rebecca Norman in Ladakh

The search for learning methods that integrate the individual, society and nature to promote sustainable ways of living has been the holy grail for many-an-educational framework. Here Susan Visvanathan describes a successful experiment in such an alternative educational approach in the cold desert of Ladakh in the north of India. The approach weaves together a living dialogue between traditional ways and modern scientific knowledge to achieve economic progress while still keeping the sense of community alive

The influence of the MuSK system and the L25 transgene on the Neuromuscular Junction

The MuSK system is important in the development and maintenance of the neuromuscular junction. The neuromuscular junction is a chemical synapse that is important in muscle contraction. Research has shown that aged NMJ experience structural impairments, resulting in decreased efficiency of synaptic transmission and subsequent muscle contraction. Previous studies concerning reduced gene dosage of proteins of the MuSK system focused on homozygous knockouts. However, the prenatal death of the null mice prevented study of the role of the MuSK system in aged mice. Here, I studied the influence of the MuSK system in aged mice, by comparing mice with reduced gene dosage of agrin and rapsyn from the MuSK system. In addition, I studied the influence of elevated MuSK expression. I hypothesised that reduced gene dosage of agrin and rapsyn (major proteins of the MuSK system) may exacerbate and/or prematurely reveal age associated changes of the NMJ. On the other hand, I predicted that elevated MuSK expression would delay and/or prevent age associated changes at the NMJ. With the use of fluorescence confocal microscopy and immunohistochemical techniques I quantified and analysed pre-synaptic and post-synaptic structural integrity of the NMJ in wild type controls and affected groups. The experimental results do not seem to lend evidence to my hypotheses. They suggest that reduced rapsyn or agrin dosage have no effect on the structural integrity of the neuromuscular junction. Similar neuromuscular junction integrity was also noted in MuSK elevated samples, suggesting increased MuSK dosage has no effect. The L25 transgenic line is generated by the random insertion of the growth promoter sef gene. A subset of the offspring from L25+/- and L25+/- mating developed motor symptoms reminiscent of mouse models of motor neuron disease (most likely due to the disruption of an endogenous gene). The affected L25 mice were recently found to displayed hind limb spasticity, body tremor and paralysis (Eva Kitchkin, Honours Thesis 2014). Here, using the same techniques as in the study of the MuSK system, I investigate whether symptoms from the L25 mice line involve changes in motor endplate innervation, which would imply the involvement of lower motor neurons. The results from this study suggests that the nerve terminals, as well as lower motor neurons, are not involved in the affected L25 animals

Uncovering Knowledge Management Practices In Organizations

Background: An increasing number of organizations have accepted the importance of managing their company’s knowledge in a more structured manner. There have been many knowledge management projects that have been introduced, some which have been successful, but many have failed as well. Knowledge management can be introduced in the culture of the company, which then becomes paramount when the company deals with national and international markets. Objectives: There are concerns as to how to measure the benefits of a Knowledge Management (KM) strategy and its concomitant initiatives on the performance of the company. This paper discusses findings from an empirical investigation amongst 51 organizations. Methods: A mixed methods approach was used to capture the data using many previously validated questionnaires. The questionnaire was adapted to suite the requirements of this particular study. Results: The findings suggest that by providing effectual information systems infrastructure knowledge can be captured, transformed and disseminated to organizations. Investment in business information systems supports knowledge sharing and interpersonal interaction and therefore facilitates knowledge management processes and strategies. Conclusion: The importance of this contribution is that it offers suggestions to design a KM approach by means of a new framework emanating from the findings. Finally, contributing to the theoretical analysis and findings from the empirical investigation, this article concludes with suggestions that may assist organizations to address their KM barriers

Peer and Maternal Relationship Predictors of Adolescent Romantic Conflict Resolution

The objective of the current study was to examine whether change in adolescent conflict resolution in romantic relationships is predicted by adolescents\u27 prior interactions with mothers and friends. A community sample of 191 adolescents (96 female), representative of the U.S. population, their mothers and close friends participated in this study. Data collection began when adolescents were in 10th grade (¬Average age = 15.9, SD = .52) and continued for the next five and a half years. Results indicated that teens engaged in positive problem solving, withdrawal, and compliance far more frequently than in aggressive conflict resolution strategies. Hierarchical linear modeling was used to analyze growth curves. Results indicated linear increases in problem solving and withdrawal over the course of late adolescence and early adulthood. Levels of compliance, verbal aggression, and physical aggression stayed the same on average. Of all predictors examined in this study, teens\u27 negative interactions and observed conflict with friends appeared particularly predictive of conflict resolution behavior with a romantic partner in 10th grade. Support and communication skills with friends and mothers were predictive of conflict resolution behavior over time. Implications and directions for future research are discussed