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This study aims to analyse the work done in the field of Night Vision Robots using IR and Object Detection from 2011 to 2021, using the bibliometric methods. This paper presents a Scopus database review on "Night Vision Bot using Dynamic IR and Object Detection". The necessity for doing this bibliometric survey is that to know how the technology in the field of mobile robotics and night vision, as well as to object detection, has evolved over the years. This paper shows the importance of Night Vision Robot from the year 2011 and continued up to 2021 April. The database analysis for the robot is done through Scopus and VOSviewer Version 1.6.16. Through this database survey, it is revealed that the maximum number of publications are Conference Paper and most of them are from the field of Engineering and Computer Science, India has the greatest number of publications followed by China. Methods: The Scopus database was used to obtain the articles for the above topic. The research papers were considered from the year 2011 to 2021. The Scopus analyzer can be used for the analysis of the database with different categories like Source, Subject Area, Country, etc. The analysis such as co-authorship, co-occurrences, citation analysis etc. is done by using VOSviewer Version 1.6.16. Results: In the study, a total of 69 articles on Night Vision Robot were obtained between the years 2011 and 2021. The statistical analysis and network analysis shows that the maximum number of papers were published in the year 2020. India is the highest contributor followed by China and Australia. Conclusion: The outcome of the Scopus database is 69 articles with the English Language having the largest number of articles. The Statistic Analysis helps to understand the potential of topic. It is done for Authors, Documents, Country, affiliations, funding sponsors. The Network Analysis indicates the interconnections between different parameters such as Coauthor, sources. It indicates that this is a new concept, and the research has been done mostly in the last year, so there is lot of future potential and scope for development. [ABSTRACT FROM AUTHOR]

Despite the fact that great progress has been made on single image deraining tasks, it is still challenging for existing models to produce satisfactory results directly, and it often requires a single or multiple refinement stages to gradually improve the quality. However, in this paper, we demonstrate that existing image-level refinement with a stage-independent learning design is problematic with the side effect of over/under-deraining. To resolve this issue, we for the first time propose the mechanism of learning to carry out refinement on the unsatisfactory features, and propose a novel attentive feature refinement (AFR) module. Specifically, AFR is designed as a two-branched network for simultaneous rain-distribution-aware attention map learning and attention guided hierarchy-preserving feature refinement. Guided by task-specific attention, coarse features are progressively refined to better model the diversified rainy effects. By using a separable convolution as the basic component, our AFR module introduces little computation overhead and can be readily integrated into most rainy-to-clean image translation networks for achieving better deraining results. By incorporating a series of AFR modules into a general encoder-decoder network, AFR-Net is constructed for deraining and it achieves new state-of-the-art results on both synthetic and real images. Furthermore, by using AFR-Net as a teacher model, we explore the use of knowledge distillation to successfully learn a student model that is also able to achieve state-of-the-art results but with a much faster inference speed (i.e., it only takes 0.08 second to process a $512\times 512$ rainy image). Code and pre-trained models are available at $\langle $ https://github.com/RobinCSIRO/AFR-Net $\rangle $. [ABSTRACT FROM AUTHOR]

Graphs are commonly used to represent objects, such as images and text, for pattern classification. In a dynamic world, an object may continuously evolve over time, and so does the graph extracted from the underlying object. These changes in graph structure with respect to the temporal order present a new representation of the graph, in which an object corresponds to a set of time-variant graphs. In this paper, we formulate a novel time-variant graph classification task and propose a new graph feature, called a graph-shapelet pattern, for learning and classifying time-variant graphs. Graph-shapelet patterns are compact and discriminative graph transformation subsequences. A graph-shapelet pattern can be regarded as a graphical extension of a shapelet—a class of discriminative features designed for vector-based temporal data classification. To discover graph-shapelet patterns, we propose to convert a time-variant graph sequence into time-series data and use the discovered shapelets to find graph transformation subsequences as graph-shapelet patterns. By converting each graph-shapelet pattern into a unique tokenized graph transformation sequence, we can measure the similarity between two graph-shapelet patterns and therefore classify time-variant graphs. Experiments on both synthetic and real-world data demonstrate the superior performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The latent friend recommendation in online social media is interesting, yet challenging, because the user-item ratings and the user–user relationships are both sparse. In this paper, we propose a new dual implicit mining-based latent friend recommendation model that simultaneously considers the implicit interest topics of users and the implicit link relationships between the users in the local topic cliques. Specifically, we first propose an algorithm called all reviews from a user and all tags from their corresponding items to learn the implicit interest topics of the users and their corresponding topic weights, then compute the user interest topic similarity using a symmetric Jensen–Shannon divergence. After that, we adopt the proposed weighted local random walk with restart algorithm to analyze the implicit link relationships between the users in the local topic cliques and calculate the weighted link relationship similarity between the users. Combining the user interest topic similarity with the weighted link relationship similarity in a unified way, we get the final latent friend recommendation list. The experiments on real-world datasets demonstrate that the proposed method outperforms the state-of-the-art latent friend recommendation methods under four different types of evaluation metrics. [ABSTRACT FROM AUTHOR]

Computer science, like technology in general, is seen as a masculine field and the under-representation of women an intransigent problem. In this paper, we argue that the cultural belief in Australia that computer science is a domain for men results in many girls and women being chased away from that field as part of a border protection campaign by some males – secondary school teachers, boys and men playing games online and young men on campus at university. We draw on American feminist philosopher, Iris Marion Young’s analysis of the ‘five faces’ of oppression to suggest strategies whereby Australian universities could support women in computer science and educate men about respectful behaviour and gender equity. [ABSTRACT FROM PUBLISHER]

A new classification system for computing education papers is presented and applied to every computing education paper published between January 2004 and January 2007 at the two premier computing education conferences in Australia and New Zealand. We find that while simple reports outnumber other types of paper, a healthy proportion of papers address and answer a research question. We find that more papers deal with programming courses than with other courses, and that more than half of all publications are situated in single subjects. To the extent that differing circumstances permit, we compare our results with those of an earlier study of the SIGCSE conference, and find that the Australasian publications include fewer simple reports and more papers describing analysis and experiment. We note a reasonable number of publications on multi-institutional work, which we interpret as evidence of a sense of computing education community within Australia and New Zealand. [ABSTRACT FROM AUTHOR]

Over the past few years Australian universities have sought to establish generic graduate attributes statements to meet the demands of external stakeholders. Within the area of information and communication technology (ICT), for example, professional organizations and employers want new ICT graduates to be able to talk with clients, create persuasive arguments and present work confidently. To meet such requirements, Australian ICT educators have explored a variety of methods to implement graduate attributes. The selection and content of delivery models, however, vary according to university policies and departmental cultures. In this paper we critically examine the dedicated, infused, and embedded approaches to the delivery of generic graduate attributes. To do this, we first trace the development of graduate attributes. Secondly, we present three diverse approaches by two ICT departments within the same university and discuss factors that lead to sustainable generic graduate attribute programmes. We conclude our paper with issues to consider when adopting implementation models and map out suggestions for further research. [ABSTRACT FROM AUTHOR]

This paper investigates the Australian literature relating to female under-representation in the information technology (IT) sphere of careers and education. This summary of the current body of literature presented through the lens of the nature of the discipline includes emerging theories that explore the masculinization of the discipline, followed by a discussion of the lack of a sustainable impact on declining female student numbers of earlier Australian intervention programmes. A position is presented on the marginalization of this line of research within the IT discipline, as well as media representations of gendered messages about IT. Finally, student career choice literature is used to explore the author's premise that many young women in 21st century Australia, when faced with an array of career choices, appear to be exercising this power of choice to exclude IT from their list of possible futures. [ABSTRACT FROM AUTHOR]

Electronic Meeting Systems (EMS) are intended to support group collaboration in completing tasks. While there have been many case studies and laboratory experiments on how EMS can support group tasks, large scale macro investigations exploring EMS adoption and use have been practically non-existent. Furthermore, while several barriers to EMS adoption and use have been suggested, their validation across organizations remains unexplored. We undertook a global initiative to explore information technology support for task-oriented collaboration in the US, Australia, Hong Kong, and Norway. In this paper, we focus specifically on assessing the adoption and use of EMS, and barriers to their adoption and use in organizations across the four regions. Our results suggest that EMS currently have limited adoption and are used infrequently across all the four regions. A further investigation into barriers to EMS adoption and use suggests that significant numbers of respondents do agree with a list of fourteen suggested barriers. However, while there is significant agreement between two countries (US & Australia) over how these barriers are ranked, there is no significant agreement between the remaining pairs of countries. Implications of our findings are discussed for practitioners and researchers. [ABSTRACT FROM AUTHOR]

In a Finnish study of four different academic disciplines, Ylijoki (2000) found that in Computer Science there was a disparity between the conceptions held by undergraduate students and staff about their discipline; students viewed it as being far more pragmatic and results focused than did their instructors. Not surprisingly, here at our Australian university where the undergraduate Computer Science program emphasizes programming and problem solving skills, the authors had noticed a similar inconsistency between staff and student beliefs. This paper reports on an effort to realign these conceptions and broaden student experience using an assessment task. Centered on solutions to the popular 'Sudoku' puzzle (Sudoku, 2005), the task was designed and introduced into an Intelligent Systems course, a final year elective of a Computer Science degree. The goal was to expose students to some of the 'pure' rather than applied aspects of the Computer Science discipline (Becher & Trowler, 2001), by using assessment to encourage experimental learning (Kolb & Fry, 1975). The assessment specification instructed students to design and conduct several 'in silica' Computer Science experiments to solve and/or create Sudoku puzzles. Importantly, students were asked to keep a Research Diary documenting their thoughts, attempts, backtracking and progresses as they attempted the assignment. Most unique from a student's perspective was that 'failure' to solve the given problem by experimentation was a viable option; their efforts would be rewarded given they conducted themselves 'scientifically' in their attempt. The inclusion of a Research Diary as part of the assessment proved beneficial to both students and staff, particularly as the Diaries focused students on the doing, rather than on the results achieved. For staff, these journals allowed the privilege of seeing what students were thinking and doing as they engaged in the problem. An early analysis of Diary entries shows evidences of students 'thinking scientifically', that is, understanding and thinking about the problem before formalizing an approach to a solution. In addition, Diary entries also show evidences of students 'behaving scientifically' as they reported conducting experiments and analyzing their results, before concluding about their experiences. For students, regardless of whether they able to complete the task, the Research Diaries were valuable testaments to their efforts and experimentations. [ABSTRACT FROM PUBLISHER]

The career paths of students are influenced and shaped by the subject choices that are made in the final years of secondary schooling. This paper presents the findings of an empirical study that identified the key factors influencing the decision of rural / regional Australian students to choose or not choose to study Information Processing and Technology. The findings revealed that career oriented, extrinsic factors play an important role in motivating the selection of I.P.T. at school and, by implication, information technology at university. There are few apparent gender differences but there is limited evidence to suggest that males may be more influenced by extrinsic motivators and females by intrinsic motivators. Although the factors used in the study were initially identified largely via informal processes, they all appear to influence the decision to take I.P.T. The focus on career-related factors and the instrumentality of taking I.P.T. could explain the drop-off in students taking the subject. This has potentially significant implications as regards the future supply of good information technology professionals. [ABSTRACT FROM AUTHOR]