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The purpose of this paper is to provide crystal size distribution (CSD) using photogrammetric and image analysis techniques. A new algorithm is proposed to detect CSDs and a comparison is carried out with conventional watershed segmentation algorithm.

Polished granite plates were prepared to designate the metrics of CSD measurements. There are many important metrics for measurements on CSD. Some of them are orientation, size, position, area, aspect ratio, convexity, circularity, perimeter, convex hull, bounding box, eccentricity, shape, max-min length of CSD's fitted and corrected ellipse, and population density in a per unit area. Prior to image processing stage, camera calibration was performed to remove the image distortion errors. Image processing techniques were applied to corrected images for detecting the CSD parameters.

The proposed algorithm showed the improved preservation of size and shape characteristics of the crystal material when compared to the watershed segmentation. According to the experimental results, proposed algorithm revealed promising results in identifying CSDs more easily and efficiently.

This paper describes CSD of granitic rocks by using automated grain boundary detection methods in polished plate images. Some metrics of CSDs were detected by employing a new procedure. A computer-based image analysis technique was developed to measure the CSDs on the granitic rock plates. A validation is done by superimposing digitally detected CSD metrics to original samples.

The purpose of this paper is to develop an automated phase segmentation model from complex microstructure. The mechanical and physical properties of metals and alloys are influenced by their microstructure, and therefore the investigation of microstructure is essential. Coexistence of random or sometimes patterned distribution of different microstructural features such as phase, grains and defects makes microstructure highly complex, and accordingly identification or recognition of individual phase, grains and defects within a microstructure is difficult.

In this perspective, computer vision and image processing techniques are effective to help in understanding and proper interpretation of microscopic image. Microstructure-based image processing mainly focuses on image segmentation, boundary detection and grain size approximation. In this paper, a new approach is presented for automated phase segmentation from 2D microstructure images. The benefit of the proposed work is to identify dominated phase from complex microstructure images. The proposed model is trained and tested with 373 different ultra-high carbon steel (UHCS) microscopic images.

In this paper, Sobel and Watershed transformation algorithms are used for identification of dominating phases, and deep learning model has been used for identification of phase class from microstructural images.

For the first time, the authors have implemented edge detection followed by watershed segmentation and deep learning (convolutional neural network) to identify phases of UHCS microstructure.

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

It is a challenging task to analysis oxide wear particles when they are stuck together with other types of wear particles in complex ferrography images. Hence, this paper aims to propose a method of ferrography image segmentation to analysis oxide wear debris in complex ferrography images.

First, ferrography images are segmented with watershed transform. Then, two region merging rules are proposed to improve the initial segmentation results. Finally, the features of each particle are extracted to detect and assess the oxide wear particles.

The results show that the proposed method outperforms other methods of ferrography image segmentation, and the overlapping wear particles in complex ferrography images can be well separated. Moreover, the features of each separated wear particles can be easily extracted to analysis the oxide wear particles.

The proposed method provides a useful approach for the automatic detection and assessment of oxide wear particles in complex ferrography images.

The colours, edges and position information of wear debris are considered in the proposed method to improve the segmentation result. Moreover, the proposed method can not only detect oxide wear particles in ferrography images but also evaluate oxide wear severity in ferrography images.

In the platform era the informal employment in China is tremendously huge in quantities. This paper sets out the changes of traditional regulatory rules status, the new web of rules and, with a particular focus on, the impacts of main actors’ interacts, from an industrial relations ‘web of rule’ perspective. The subjects involved in this paper are multiple, including labour law, collective labour relations institution, enterprise human resources management, CSRs and NGOs in production supply chains. It argues the inappropriate impacts on the perseverance of right and interests of workers are consequences of the current national labour law and collective labour relations institutions. It witnesses the emerging innovative methods, employment relations system in a self-dependent economic transaction, the rule of production supply chain in a multi-stake-holder context and the new intervening method of NGOs. It is in scrutiny of the commence of such a transformation in China, nevertheless, transforming from the authoritarian regime to a more fair market establishing via the intervention of multiple social forces, and consequently the transformation from informal employments to formal ones in a comprehensively complex domestic and global context.

The purpose of this paper is to describe a multisource system for nondestructive inspection of welded elements exploited in aircraft industry developed in West Pomeranian University of Technology, Szczecin in the frame of CASELOT project. The system task is to support the operator in flaws identification of welded aircraft elements using data obtained from X-ray inspection and 3D triangulation laser scanners.

For proper defects detection a set of special processing algorithms were developed. For easier system exploitation and integration of all components a user friendly interface in LabVIEW environment was designed.

It is possible to create the fully independent, intelligent system for welds’ flaws detection. This kind of technology might be crucial in further development of aircraft industry.

In this paper a number of innovative solutions (new algorithms, algorithms’ combinations) for defects’ detection in welds are presented. All of these solutions are the basis of presented complete system. One of the main original solution is a combination of the systems based on 3D triangulation laser scanner and X-ray testing.

The purpose of this paper is to develop an ontological foundation for future studies, based in part on integrating some prior albeit incomplete work in this area.

This manuscript is based on a literature review, as well as on conceptual and theoretical enhancements from this subject field.

As the future does not exist (it is always something yet to come), the ontological foundations for studying the future must be based on the current reality of the physical, biological and social-psychological worlds of experience and ideas. From this basis, 10 postulates are provided that are based on that current reality and are applied to studying the future. Thus, by characterizing the current reality and how it is understood by people, meaningful statements about the future are possible.

For each ontological postulate, one or more implications for the study of the future are provided as guidelines for practice.

This manuscript integrates and builds on prior offerings about ontological concerns into a comprehensive framework that legitimates and focuses the practices of studying the future.

This chapter reviews 30 years of Advances in Group Processes. Its primary purpose is to study the part the series has played in the advances in the study of group processes that have taken place between 1984 and 2014.

This chapter places the 30 years of Advances in Group Processes in the context of the changes that took place between small groups research in the 1950s and group processes research in the 1980s and beyond.

Analyzing the policies of Advances in Group Processes and its contents, this chapter reflects on its role in the advances in group processes that have taken place since the 1980s. Between 1950 and 1980, small group research reinvented, reconceptualized, and reinvigorated itself as group process research. Between the two periods, small group research, its applied research, and its research programs became increasingly theory-driven and its concept of the group and its levels increasingly analytic. As a consequence of these changes, the concept of the field itself became increasingly analytic. The changes between the two periods in its theory, research, application, programs, and in its concept of the group and the way the field was conceptualized led to marked advances in group process research in the 90s and beyond – to more theory, more impact of it on application, and more, and more cumulative, growth of it. Advances in Group Processes was at once a reflection of the changes that took place between the two periods and a driving force in the advances in group processes research that have taken place ever since.

Advances in Group Processes is a fundamental resource for the development of theory and research on small groups and group processes. This chapter provides an overview of its contributions and places them in the context of the development of the field as a whole.

Previous research has shown that “Scan-vs-BIM” object recognition systems, which fuse three dimensional (3D) point clouds from terrestrial laser scanning (TLS) or digital photogrammetry with 4D project building information models (BIM), provide valuable information for tracking construction works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structural works only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking secondary and temporary objects would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. The paper aims to discuss these issues.

Two techniques for recognizing concrete construction secondary and temporary objects in TLS point clouds are implemented and tested using real-life data collected from a reinforced concrete building construction site. Both techniques represent significant innovative extensions of existing “Scan-vs-BIM” object recognition frameworks.

The experimental results show that it is feasible to recognise secondary and temporary objects in TLS point clouds with good accuracy using the two novel techniques; but it is envisaged that superior results could be achieved by using additional cues such as colour and 3D edge information.

This article makes valuable contributions to the problem of detecting and tracking secondary and temporary objects in 3D point clouds. The power of Scan-vs-BIM object recognition approaches to address this problem is demonstrated, but their limitations are also highlighted.

The abnormalities of glaucoma have high impact on deciding and representing the causes that effects severity of blindness in human beings. The simulation experimental results would help the ophthalmologist in diagnosing of glaucoma abnormality accurately. The significant effect of glaucoma has a huge impact on the quality of human life, and its growth rate in world population tremendously increases. Glaucoma is considered as second largest cause for the blindness in the world; hence identification of it marks the importance of its detection at the earliest.

The prime objective of the work proposed is to build up a human intervention free image preparing framework for glaucoma screening. The disc calculation is assessed on retinal image dataset called retinal Image for glaucoma Analysis. The proposed method briefs a novel optic disc division calculation depending on applying a level-set strategy on a confined optic disc image. In the instance of low quality image, a twofold level set is designed, in which the principal level set is viewed as restriction for the optic disc. To keep the veins from meddling with the level-set procedure, an inpainting strategy has been applied. Also a significant commitment is to include the varieties in notion adopted by the ophthalmologists in distinguishing the disc localization and diagnosing the glaucoma. Most of the past investigations are prepared and tested depending on just a single feature, which can be thought to be one-sided for the ophthalmologist.

In continuation, the correctness has been determined depending on the quantity of image that matched with the investigation pattern adopted by the ophthalmologist. The 175 retinal images were utilized to test the results of proposed work with the manual markings of ophthalmologists. The error-free calculation in marking the optic disc region and centroid was 98.95% in comparison with the existing result of 87.34%.

In continuation, the correctness has been determined depending on the quantity of image that matched with the investigation pattern adopted by the ophthalmologist. The 175 retinal images were utilized to test the results of proposed work with the manual markings of ophthalmologists. The error-free calculation in marking the optic disc region and centroid was 98.95% in comparison with the existing result of 87.34%.