Tunnels and tunneling

A tunnel is defined as a sub-terranean or sub-aqueous way, for purposes of passage. The term is also applied, in mining, to horizontal excavations, such as are commonly called drifts, headings, adits, etc., and used as underground roads, or passages for water or air. Tunneling, at the present day, has become of such importance, that it is in its-self a profession. The subject of Tunnels and Tunneling properly treated would require a large volume, but taking into consideration the time and space allotted to the preparation of this thesis, I shall be brief; and in order to treat it to the best advantage, I shall place it under the following heads = Historical and Descriptive; Explosives and Blasting; Drills and Drilling. The history of tunnels has been selected from the best authorities --page 3

Gamification in Education: A Study of Design-Based Learning in Operationalizing a Game Studio for Serious Games

The gamification of learning has proven educational benefits, especially in secondary education. Studies confirm the successful engagement of students with improved time on task, motivation and learning outcomes. At the same time, there remains little research on games and learning at the postsecondary level of education where traditional pedagogies remain the norm. Studies that have been conducted remain almost exclusively restricted to science programs, including medicine and engineering. Moreover, postsecondary subject-matter experts who have created their own gamified experiences often are forced to do so on an ad hoc basis either on their own, teaching themselves game engines, or with irregular support from experts in the field. But to ensure a well-designed, developed, and high-quality educational experience that leads to desired outcomes for a field, a sustainable infrastructure needs to be developed in institutions that have (or can partner with) others that have an established game design program. Moreover, such a design-based learning approach can be embedded within an existing studio model to help educate participants while producing an educational product. As such, this qualitative case study provides an example of the process of operationalizing a game design studio from pre-production through post-production, drawing from the design and development of the educational video game The Museum of the Lost VR (2022). The results, resources, and classification system presented are scalable and provide models for different sized institutions. Methods to develop a sustainable infrastructure are presented to ensure interdisciplinary partnerships across departments and institutions with game design programs to collaborate and create educational experiences that optimize user experience and learning outcomes

Object size determines the spatial spread of visual time

A key question for temporal processing research is how the nervous system extracts event duration, despite a notable lack of neural structures dedicated to duration encoding. This is in stark contrast to the orderly arrangement of neurons tasked with spatial processing. In the current study, we examine the linkage between the spatial and temporal domains. We use sensory adaptation techniques to generate aftereffects where perceived duration is either compressed or expanded in the opposite direction to the adapting stimulus’ duration. Our results indicate that these aftereffects are broadly tuned, extending over an area approximately five times the size of the stimulus. This region is directly related to the size of the adapting stimulus – the larger the adapting stimulus the greater the spatial spread of the aftereffect. We construct a simple model to test predictions based on overlapping adapted vs non-adapted neuronal populations and show that our effects cannot be explained by any single, fixed-scale neural filtering. Rather, our effects are best explained by a self scaled mechanism underpinned by duration selective neurons that also pool spatial information across earlier stages of visual processing

On the information-theoretic formulation of network participation

The participation coefficient is a widely used metric of the diversity of a node's connections with respect to a modular partition of a network. An information-theoretic formulation of this concept of connection diversity, referred to here as participation entropy, has been introduced as the Shannon entropy of the distribution of module labels across a node's connected neighbors. While diversity metrics have been studied theoretically in other literatures, including to index species diversity in ecology, many of these results have not previously been applied to networks. Here we show that the participation coefficient is a first-order approximation to participation entropy and use the desirable additive properties of entropy to develop new metrics of connection diversity with respect to multiple labelings of nodes in a network, as joint and conditional participation entropies. The information-theoretic formalism developed here allows new and more subtle types of nodal connection patterns in complex networks to be studied

Validation of Measured Damping Trends for Flight-Like Vehicle Panel/Equipment including a Range of Cable Harness Assemblies

This validation study examines the effect on vibroacoustic response resulting from the installation of cable bundles on a curved orthogrid panel. Of interest is the level of damping provided by the installation of the cable bundles and whether this damping could be potentially leveraged in launch vehicle design. The results of this test are compared with baseline acoustic response tests without cables. Damping estimates from the measured response data are made using a new software tool that leverages a finite element model of the panel in conjunction with advanced optimization techniques. While the full test series is not yet complete, the first configuration of cable bundles that was assessed effectively increased the viscous critical damping fraction of the system by as much as 0.02 in certain frequency ranges

Adaptation reveals multi-stage coding of visual duration

YesIn conflict with historically dominant models of time perception, recent evidence suggests that the encoding of our environment’s temporal properties may not require a separate class of neurons whose raison d'être is the dedicated processing of temporal information. If true, it follows that temporal processing should be imbued with the known selectivity found within non-temporal neurons. In the current study, we tested this hypothesis for the processing of a poorly understood stimulus parameter: visual event duration. We used sensory adaptation techniques to generate duration aftereffects: bidirectional distortions of perceived duration. Presenting adapting and test durations to the same vs different eyes utilises the visual system’s anatomical progression from monocular, pre-cortical neurons to their binocular, cortical counterparts. Duration aftereffects exhibited robust inter-ocular transfer alongside a small but significant contribution from monocular mechanisms. We then used novel stimuli which provided duration information that was invisible to monocular neurons. These stimuli generated robust duration aftereffects which showed partial selectivity for adapt-test changes in retinal disparity. Our findings reveal distinct duration encoding mechanisms at monocular, depth-selective and depthinvariant stages of the visual hierarchy.The Wellcome Trust [WT097387]

Understanding children’s constructions of meanings about other children: implications for inclusiveeducation

This paper explores the factors that influence the way children construct meanings about other children, and especially those who seem to experience marginalisation, within school contexts. The research involved an ethnographic study in a primary school in Cyprus over a period of 5 months. Qualitative methods were used, particularly participant observations and interviews with children. Interpretation of the data suggests that children's perceptions about other children, and especially those who come to experience marginalisation, are influenced by the following factors: other children and the interactions between them; adults’ way of behaving in the school; the existing structures within the school; and the cultures of the school and the wider educational context. Even though the most powerful factor was viewed to be the adults’ influence, it was rather the interweaving between different factors that seemed to lead to the creation of particular meanings for other children. In the end, it is argued that children's voices should be seen as an essential element within the process of developing inclusive practices.<br/

On Time Series Classification with Dictionary-Based Classifiers

A family of algorithms for time series classification (TSC) involve running a sliding window across each series, discretising the window to form a word, forming a histogram of word counts over the dictionary, then constructing a classifier on the histograms. A recent evaluation of two of this type of algorithm, Bag of Patterns (BOP) and Bag of Symbolic Fourier Approximation Symbols (BOSS) found a significant difference in accuracy between these seemingly similar algorithms. We investigate this phenomenon by deconstructing the classifiers and measuring the relative importance of the four key components between BOP and BOSS. We find that whilst ensembling is a key component for both algorithms, the effect of the other components is mixed and more complex. We conclude that BOSS represents the state of the art for dictionary-based TSC. Both BOP and BOSS can be classed as bag of words approaches. These are particularly popular in Computer Vision for tasks such as image classification. We adapt three techniques used in Computer Vision for TSC: Scale Invariant Feature Transform; Spatial Pyramids; and Histogram Intersection. We find that using Spatial Pyramids in conjunction with BOSS (SP) produces a significantly more accurate classifier. SP is significantly more accurate than standard benchmarks and the original BOSS algorithm. It is not significantly worse than the best shapelet-based or deep learning approaches, and is only outperformed by an ensemble that includes BOSS as a constituent module