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The purpose of this paper is to investigate the track evolution and surface characteristics of selective laser melting Ti₆Al₄V.

In the present paper, Ti₆Al₄V single-track, multi-track and bulk sample were formed at different scanning speed by selective laser melting (SLM). Then, the surface morphology, three-dimension profile and surface roughness were evaluated. The width of the single and multi-track was measured and compared.

The results showed that the heat accumulation played a great role on the evolution of tracks and surface characteristics from single-track to multi-track and to bulk. The surface morphology of the subsequent tracks became more regular when the single-track was irregular at the same high scanning speed. The width of last track Wn was always larger than that of the first track W1. The Ra of the top of the bulk increased with the increase of the scanning speed, this trend was as same as the Ra of the single-track, but the trend of Ra of the side was opposite.

The effect of heat accumulation on the track evolution and surface characteristics is obtained. The results can help to derive a smooth surface with a regular and continuous track in SLM.

The paper attempts to design an efficient algorithm for bearing track correlation of multi‐sensor on the same platform using grey incidence analysis which is on the basis of the line segment Hausdorff distance.

Starting from the line segment, Hausdorff distance that has been extended to calculate the distance between line segment sets by many scholars has been used for face recognition achieving good results. The degree of grey incidence is defined based on the above distance and properties which include normality, symmetry and closeness, are proved. Furthermore, a grey incidence matrix is built. With only the azimuth information detected by bearing sensors track correlation is difficult to judge, however grey incidence analysis can quickly and accurately determine whether two tracks are from the same target, and so an algorithm is designed to solve this dilemma. In the last part of the paper simulation experiment is conducted.

The results are convincing: not only the algorithm proposed in the paper can solve the problem of track correlation of bearing‐only sensors, but also the algorithm can judge the correlation degree of both tracks even in the case of intensive targets.

The method exposed in the paper can be used to judge correlation degree of tracks detected by different sensors even for less information, and also be used to determine the similarity of two waveforms in the field of engineering.

The paper succeeds in introducing the line segment Hausdorff distance into grey incidence analysis and on the basis of that an algorithm is designed to solve the problem of track correlation.

This paper aims to extend the scope of previous studies on education-occupation mismatch to explicitly focus on the role high school track choices have on the risk of being mismatched in the labor market.

The paper uses the most exhaustive available database regarding the early-career paths of university graduates in Romania. Using a novel matching technique, entropy balancing (EB), our study relies on multinomial logit models and logit regressions to estimate the effect of the completed high school track on the likelihood of being mismatched in the labor market. The empirical analysis focuses on two types of education-occupation mismatches: horizontal and vertical mismatches.

We show that studying a different field in college compared to the completed high school track increases the risk of being skill mismatched in the first job after graduation. Five years after college graduation, the influence of the high school track fades, while being skill mismatched in the first employment plays a more important role. In contrast, we find no evidence that pursuing a college major unrelated to the completed high school track increases the probability of being overeducated. However, being overeducated in the first job increases the risk of being overeducated five years later.

The study brings new reliable evidence on the extent to which high school track choices may contribute to the risk of being mismatched in the labor market.

In this chapter, we draw on our study involving interviews with Australians who identify as current self-trackers to discuss why and how they monitor themselves. Our approach for analysing self-tracking practices is based on a sociomaterial perspective, viewing enactments of voluntary self-tracking as shifting heterogeneous assemblages, bringing together diverse actors who are both human and non-human. We use vignettes to illustrate the ways in which our participants enacted self-tracking and to identify some of the diverse meanings and motivations that mediate decisions to self-track and resultant uses of the information thus generated. We found that a varied range of self-tracking practices were taken up by our interviewees, including not only digital devices and methods, but also recording their details using pen-and-paper, or simply maintaining mental awareness and using memory. We identified several agential capacities in our participants’ accounts of why and how they monitor themselves. These capacities are interrelated, but can be loosely grouped under the headings of ‘self-improvement’, ‘exerting control’ and ‘identifying patterns and achieving goals’. They are motivators and facilitators of monitoring practices. The broader sociocultural contexts in which monitoring of the body/self is undertaken were also revealed in the participants’ accounts. These include ideas about the moral virtues of self-responsibility and the individual management of life circumstances to avoid chaos and risk, and the notion that monitoring practices can successfully achieve these virtues.

Visual stimuli are integral for the destination selection process, as well as for the delivery of unique, novel and compelling tourist experiences. Emerging techniques, such as eye-tracking, are effective for mapping tourists' visual interests and paths, presenting an opportunity to identify patterns of visual attention, which provide insights into the underlying cognitive processes which underpin experiences. Building on a systematic review of the progress and development of eye-tracking in tourism field, this chapter summarises five main current research contexts for application and five future research directions. It also narrows the gap between eye-tracking and cognitive psychology by critically examining bottom-up and top-down attentional mechanisms.

This chapter provides an insider perspective on the Quantified Self (QS) community. It is argued that the overall approach and methods used in the QS community have not been adequately described. Consequently, the aim of the chapter is to give an account of the work performed by self-trackers in what we coin the 1-Person-Laboratory (1PL). Additionally, the chapter describes other aspects of the 1PL, for example the methods, procedures and instrumentation that are being used and the knowledge sharing taking place in the QS community. With a point of departure in empirical cases it is demonstrated how QS self-trackers put their own questions, observations and subjective experience front and centre by using their own instrumentation and data sets in their personal laboratories. In the 1PL, the causalities that are looked for are not aimed at generalisation to an entire population; on the contrary, the causal connections on the level of the person are essential for discovery by the individual.