Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Analysis of Object-Specific Authorization Protocol (OSAP) using coloured petri nets - Version 1.0

Analyzing security protocols is an ongoing research in the last years. Different types of tools are developed to make the analysis process more precise, fast and easy. These tools consider security protocols as black boxes that can not easily be composed. It is difficult or impossible to do a low-level analysis or combine different tools with each other using these tools. This research uses Coloured Petri Nets (CPN) to analyze OSAP trusted computing protocol. The OSAP protocol is modeled in different levels and it is analyzed using state space method. The produced model can be combined with other trusted computing protocols in future works.

Gender patterns for aspirations for transitional employment and training and development in local government

Purpose – The purpose of this paper is to determine the patterns of transitional employment (TE) aspirations and training and development (T&D) needs of women within local government. Design/methodology/approach – A quantitative survey methodology was used to identify aspirations in a sample of 1,068 employees from the Australian Local Government Association. Findings – Mature-aged women were very interested in continuous learning at work despite their limited formal education. Their training preferences consisted of informal delivery face-to-face or online in the areas of management or administration. Younger women were interested in undertaking university courses, while a minority were interested in blue collar occupations. Practical implications – Through the identification of patterns of TE and T&D aspirations, long term strategies to develop and retain women in local government may be developed. Findings suggest that mature-aged women would benefit from additional T&D to facilitate entry into management and senior administration positions, as well as strategies to facilitate a shift in organizational climate. Social implications – Mature-aged women were found to be a potentially untapped resource for management and senior administrative roles owing to their interest in developing skills in these fields and pursuing TE. Younger women may also benefit from T&D to maintain their capacity during breaks from employment. Encouragement of women in non-traditional areas may also address skill shortages in the local government. Originality/value – Mature-aged women were found to be a potentially untapped resource for management and senior administrative roles owing to their interest in developing skills in these fields and pursuing TE. Younger women may also benefit from T&D to maintain their capacity during breaks from employment. Encouragement of women in non-traditional areas may also address skill shortages in the local government.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

Cities, culture and “Transitional Economies”: Developing cultural industries in St Petersburg

In this chapter I look at some issues around the transfer of cultural industry policy between two very different national contexts, the UK and Russia. Specifically it draws on a partnership project between Manchester and St. Petersburg financed by the European Union as part of a program to promote economic development through knowledge transfer between Europe and the countries of the former Soviet Union. This specific project attempted to place the cultural industries squarely within the dimension of economic development, and drew on the expertise of Manchester’s Creative Industries Development Service and other partners to effect this policy transfer

Learning object dynamics for smooth tracking of moving lip contours

A new technique is proposed for learning the dynamic characteristics of a deformable object, applied in particular to the problem of lip-tracking. Experimental results are given which demonstrate that the use of dynamic models allows the system to track more robustly under adverse conditions and to correct spurious, poorly tracked frames

Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Aerial object following using visual fuzzy servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation

Corporate governance mechanisms and earnings management in transitional countries – evidence from Chinese listed firms

The objective of this thesis is to investigate whether the corporate governance practices adopted by Chinese listed firms are associated with the quality of earnings information. Based on a review of agency and institutional theory, this study develops hypotheses that predict the monitoring effectiveness of the board and the audit committee. Using a combination of univariate and multivariate analyses, the association between corporate governance mechanisms and earnings management are tested from 2004 to 2008. Through analysing the empirical results, a number of findings are summarised as below. First, board independence is weakened by the introduction of government officials as independent directors on the boards. Government officials acting as independent directors, claim that they meet the definition of independent director set by the regulation. However, they have some connection with the State, which is the controlling shareholder in listed SOEs affiliated companies. Consequently, the effect of the independent director’s expertise in constraining earnings management is mitigated as demonstrated by an insignificant association between board expertise and earnings management. An alternative explanation for the inefficiency of board independence may point to the pre-selection of independent directors by the powerful CEO. It is argued that a CEO can manipulate the board composition and choose the "desirable" independent directors to monitor themselves. Second, a number of internal mechanisms, such as board size, board activities, and the separation of the roles of the CEO and chair are found to be significantly associated with discretionary accruals. This result suggests that there are advantages in having a large and active board in the Chinese setting. This can offset the disadvantages associated with large boards, such as increased bureaucracy, and hence, increase the constraining effects of a large and resourceful board. Third, factor analysis identifies two factors: CEO power and board power. CEO power is the factor which consists of CEO duality and turnover, and board power is composed of board size and board activity. The results of CEO power show that if a Chinese listed company has CEO duality and turnover at the same time, it is more likely to have a high level of earnings management. The significant and negative relationship between board power and accruals indicate that large boards with frequent meetings can be associated with low level of earnings management. Overall, the factor analysis suggests that certain governance mechanisms complement each other to become more efficient monitors of opportunistic earnings management. A combination of board characteristics can increase the negative association with earnings management. Fourth, the insignificant results between audit committees and earnings management in Chinese listed firms suggests that the Chinese regulator should strengthen the audit committee functions. This thesis calls for listed firms to disclose more information on audit committee composition and activities, which can facilitate future research on the Chinese audit committee’s monitoring role. Fifth, the interactive results between State ownership and board characteristics show that dominant State ownership has a moderating effect on board monitoring power as the State totally controls 42% of the issued shares. The high percentage of State ownership makes it difficult for the non-controlling institutional shareholders to challenge the State’s dominant status. As a result, the association between non-controlling institutional ownership and earnings management is insignificant in most situations. Lastly, firms audited by the international Big4 have lower abnormal accruals than firms audited by domestic Chinese audit firms. In addition, the inverse U-shape relationship between audit tenure and earnings quality demonstrates the changing effects of audit quality after a certain period of appointment. Furthermore, this thesis finds that listing in Hong Kong Stock Exchanges can be an alternative governance mechanism to discipline Chinese firms to follow strict Hong Kong listing requirements. Management of Hong Kong listed companies are exposed to the scrutiny of international investors and Hong Kong regulators. This in turn reduces their chances of conducting self-interested earnings manipulation. This study is designed to fill the gap in governance literature in China that is related to earnings management. Previous research on corporate governance mechanisms and earnings management in China is not conclusive. The current research builds on previous literature and provides some meaningful implications for practitioners, regulators, academic, and international investors who have investment interests in a transitional country. The findings of this study contribute to corporate governance and earnings management literature in the context of the transitional economy of China. The use of alternative measures for earnings management yields similar results compared with the accruals models and produces additional findings.

Towards automatic object segmentation with sequential multiple views

Object segmentation is one of the fundamental steps for a number of robotic applications such as manipulation, object detection, and obstacle avoidance. This paper proposes a visual method for incorporating colour and depth information from sequential multiview stereo images to segment objects of interest from complex and cluttered environments. Rather than segmenting objects using information from a single frame in the sequence, we incorporate information from neighbouring views to increase the reliability of the information and improve the overall segmentation result. Specifically, dense depth information of a scene is computed using multiple view stereo. Depths from neighbouring views are reprojected into the reference frame to be segmented compensating for imperfect depth computations for individual frames. The multiple depth layers are then combined with color information from the reference frame to create a Markov random field to model the segmentation problem. Finally, graphcut optimisation is employed to infer pixels belonging to the object to be segmented. The segmentation accuracy is evaluated over images from an outdoor video sequence demonstrating the viability for automatic object segmentation for mobile robots using monocular cameras as a primary sensor.