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This paper aims to perform thermal and mechanical characterization for silver-based sintered thermal joints. Layer quality affects thermal and mechanical performance, and it is important to achieve information about how materials and process parameters influence them.

Thermal investigation of the thermal joints analysis method was focused on determination of thermal resistance, where temperature measurements were performed using infrared camera. They were performed in two modes: steady-state analysis and dynamic analysis. Mechanical analysis based on measurements of mechanical shear force. Additional characterizations based on X-ray image analysis (image thresholding), optical microscope of polished cross-section and scanning electron microscope image analysis were proposed.

Sample surface modification affects thermal resistance. Silver metallization exhibits the lowest thermal resistance and the highest mechanical strength compared to the pure Si surface. The type of dynamic analysis affects the results of the thermal resistance.

Investigation of the layer quality influence on mechanical and thermal performance provided information about different joint types.

Image segmentation is one of the most essential tasks in image processing applications. It is a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc. However, an accurate segmentation is a critical task since finding a correct model that fits a different type of image processing application is a persistent problem. This paper develops a novel segmentation model that aims to be a unified model using any kind of image processing application. The proposed precise and parallel segmentation model (PPSM) combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions. Moreover, a parallel boosting algorithm is proposed to improve the performance of the developed segmentation algorithm and minimize its computational cost. To evaluate the effectiveness of the proposed PPSM, different benchmark data sets for image segmentation are used such as Planet Hunters 2 (PH2), the International Skin Imaging Collaboration (ISIC), Microsoft Research in Cambridge (MSRC), the Berkley Segmentation Benchmark Data set (BSDS) and Common Objects in COntext (COCO). The obtained results indicate the efficacy of the proposed model in achieving high accuracy with significant processing time reduction compared to other segmentation models and using different types and fields of benchmarking data sets.

The proposed PPSM combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions.

On the basis of the achieved results, it can be observed that the proposed PPSM–minimum cross-entropy thresholding (PPSM–MCET)-based segmentation model is a robust, accurate and highly consistent method with high-performance ability.

A novel hybrid segmentation model is constructed exploiting a combination of Gaussian, gamma and lognormal distributions using MCET. Moreover, and to provide an accurate and high-performance thresholding with minimum computational cost, the proposed PPSM uses a parallel processing method to minimize the computational effort in MCET computing. The proposed model might be used as a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc.

This work presents a system based on an ensemble of Convolutional Neural Networks (CNNs) and descriptors for bioimage classification that has been validated on different datasets of color images. The proposed system represents a very simple yet effective way of boosting the performance of trained CNNs by composing multiple CNNs into an ensemble and combining scores by sum rule. Several types of ensembles are considered, with different CNN topologies along with different learning parameter sets. The proposed system not only exhibits strong discriminative power but also generalizes well over multiple datasets thanks to the combination of multiple descriptors based on different feature types, both learned and handcrafted. Separate classifiers are trained for each descriptor, and the entire set of classifiers is combined by sum rule. Results show that the proposed system obtains state-of-the-art performance across four different bioimage and medical datasets. The MATLAB code of the descriptors will be available at https://github.com/LorisNanni.

To identify the Transcendental Essence of Humanity, the purpose of this paper is to describe in brief what kind of research became possible when the theory of, e.g. autopoiesis, Husserl’s Transcendental Consciousness and the theory of Rhodes and Thame came together to form a “transcendental” interview methodology.

Critical conceptual implications are drawn to form a new research method to explore a de-subjectified inner domain and to search for a possible common essence of humanity.

A Transcendental Emotional Reference was found practically alien to contemporary perspectives. Still, the reference governs the emotional structure of human experience. This different perspective answers basic questions of morality, organization theory and leadership.

The findings of the new research open a new and transparent perspective answering Grey’s question: “What is it to be human?” (Grey, p. 47, 2014.) A perspective shedding new light on the humanities. A research limitation is the number of respondents. Still, being transcendental the findings are theoretically valid for all.

The paper is based on a unique research enabling 32+ (ongoing research) respondents to explore their own and universally shared Transcendental domain.

This opening chapter sets a frame for the chapters of this volume, dealing with how the dynamic dialectic interplay between forceful global societal forces and context shape humanity’s education response in various parts of the world. “Context” as a perennial threshold concept in Comparative and International Education is explicated. It will then be explained how, during its long historical evolution, scholars in the field each time had to contend new contexts, or reconceived the notion of “context” in a new way. Subsequently the problems of an overly fixation on the historical and the present, to the detriment of the future, and inertia are extant in the field, will be explained. The unprecedented, seismic changes currently impacting on the societal context worldwide, will then be enumerated. These changes can be subsumed under the collective name of globalization. The concept globalization is then clarified, and the take of the scholarly community on the impact of globalization on education is then mapped and interrogated. The authors’ stance on this is stated, namely that a dynamic interplay between global focus and contextual realities shape education in various parts of the world. It is in this theoretical frame that the remainder of the chapters of the volume is presented, combing out the main features of education development in each part of the world, as a dialectic between global forces and contextual imperatives.

This paper examines the role of government procurement as a social policy mechanism within a multilateral open trading system. Government regulations globally are being transformed to foster more responsible business conduct in multinational enterprises (MNEs). Yet, concern that sustainability may present a discriminatory barrier to trade has stalled the progress of sustainable public procurement (SPP) at the international level, raising questions regarding the role and scope of the World Trade Organisation’s (WTO) Government Procurement Agreement (GPA) to align taxpayer-funded contracts with the United Nations (UN) Sustainable Development Goals.

With a focus on social sustainability, this paper reviews the grey and academic literature to assess the changing landscape of public procurement policy and supply chain legislation in high-income countries.

Frontrunner nations are adopting a mandatory approach to sustainable public procurement and due diligence legislation is elevating supply chain risk from reputational damage to legal liability. While technological innovation and the clean, green production of manufactured goods dominates the sustainable public procurement literature, the social aspects of sustainability poverty, inequality and human rights remain underrepresented.

The scope of this paper is limited to the examination of government procurement covered by the WTO-GPA (2012). Smaller value contracts, under the WTO-GPA thresholds and the category of defence are beyond the scope of the paper.

The paper focusses on the underserved topic of social sustainability in business-to-government (B2G) – business to government – supply chains arguing that for responsible business conduct to become a competitive advantage, it must be more meaningfully rewarded on the demand-side of all taxpayer-funded contracts in organisation for economic co-operation and development countries. The paper introduces the idea of priceless procurement as a mechanism to build system capacity in the evaluation of non-financial sustainability objectives.

To build the capacity to stimulate competition based on social and environmental policy objectives, the paper introduces the concept of priceless procurement in B2G contracts.

This paper aims to introduce a novel method for the analysis of open cell porous components fabricated by laser-based powder bed metal additive manufacturing (AM) for the purpose of quality control. This method uses photogrammetric analysis, the extraction of geometric information from an image through the use of algorithms. By applying this technique to porous AM components, a rapid, low-cost inspection of geometric properties such as material thickness and pore size is achieved. Such measurements take on greater importance, as the production of porous additive manufactured orthopaedic devices increases in number, causing other, slower and more expensive methods of analysis to become impractical.

Here the development of the photogrammetric method is discussed and compared to standard techniques including scanning electron microscopy, micro computed tomography scanning and the recently developed focus variation (FV) imaging. The system is also validated against test graticules and simple wire geometries of known size, prior to the more complex orthopaedic structures.

The photogrammetric method shows an ability to analyse the variability in build fidelity of AM porous structures for use in inspection purposes to compare component properties. While measured values for material thickness and pore size differed from those of other techniques, the new photogrammetric technique demonstrated a low deviation when repeating measurements, and was able to analyse components at a much faster rate and lower cost than the competing systems, with less requirement for specific expertise or training.

The advantages demonstrated by the image-based technique described indicate the system to be suitable for implementation as a means of in-line process control for quality and inspection applications, particularly for high-volume production where existing methods would be impractical.