Diachronic dialectology: new methods and case studies

2021 ◽  
Vol 119 (S1) ◽  
pp. 1-250
Author(s):  
Tamsin Blaxter
Keyword(s):  
2017 ◽  
Vol 33 (1) ◽  
pp. 16-18

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Strategic forecasting is seen as a rebirth of long-range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Practical implications The paper provides strategic insights and practical thinking that have influenced some of the world’s leading organizations. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.


2020 ◽  
Vol 25 (2) ◽  
pp. 387-395
Author(s):  
Marten van der Meulen ◽  
Nicoline van der Sijs

Abstract The influence of prescriptivism on DutchWeerman (2003) unequivocally rejected the possibility for language to be malleable. At the time, there was little empirical research to challenge or support this claim. Over the last two decades, however, a fairly large body of research has delved into this issue. In light of this, we review some of Weerman’s views, and discuss new findings of the recent literature, both for Dutch and other languages. We show how new methods and insights have led to a re-evaluation of the effects of prescriptivism. We furthermore argue that, rather than categorically dismissing effects of prescriptivism, researchers should focus on case studies with different parameters, including linguistic level, prohibition strength and time period.


2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Mark Fuge ◽  
Bud Peters ◽  
Alice Agogino

Every year design practitioners and researchers develop new methods for understanding users and solving problems. This increasingly large collection of methods causes a problem for novice designers: How does one choose which design methods to use for a given problem? Experienced designers can provide case studies that document which methods they used, but studying these cases to infer appropriate methods for a novel problem is inefficient. This research addresses that issue by applying techniques from content-based and collaborative filtering to automatically recommend design methods, given a particular problem. Specifically, we demonstrate the quality with which different algorithms recommend 39 design methods out of an 800+ case study dataset. We find that knowing which methods occur frequently together allows one to recommend design methods more effectively than just using the text of the problem description itself. Furthermore, we demonstrate that automatically grouping frequently co-occurring methods using spectral clustering replicates human-provided groupings to 92% accuracy. By leveraging existing case studies, recommendation algorithms can help novice designers efficiently navigate the increasing array of design methods, leading to more effective product design.


2021 ◽  
Vol 11 (16) ◽  
pp. 7648
Author(s):  
Jela Abasova ◽  
Pavol Tanuska ◽  
Stefan Rydzi

CRISP-DM (cross-industry standard process for data mining) methodology was developed as an intuitive tool for data scientists, to help them with applying Big Data methods in the complex technological environment of Industry 4.0. The review of numerous recent papers and studies uncovered that most of papers focus either on the application of existing methods in case studies, summarizing existing knowledge, or developing new methods for a certain kind of problem. Although all of these types of research are productive and required, we identified a lack of complex best practices for a specific field. Therefore, our goal is to propose best practices for the data analysis in production industry. The foundation of our proposal is based on three main points: the CRISP-DM methodology as the theoretical framework, the literature overview as an expression of current needs and interests in the field of data analysis, and case studies of projects we were directly involved in as a source of real-world experience. The results are presented as lists of the most common problems for selected phases (‘Data Preparation’ and ‘Modelling’), proposal of possible solutions, and diagrams for these phases. These recommendations can help other data scientists avoid certain problems or choose the best way to approach them.


Author(s):  
M. Ersin Yu¨mer ◽  
Ender Cig˘erog˘lu ◽  
H. Nevzat O¨zgu¨ven

Mistuning affects forced response of bladed disks drastically; therefore, its identification plays an essential role in the forced response analysis of realistic bladed disk assemblies. Forced response analysis of mistuned bladed disk assemblies has drawn wide attention of researchers but there are a very limited number of studies dealing with identification of mistuning, especially if the component under consideration is a blisk (integrally bladed disk). This paper presents two new methods to identify mistuning of a rotor from the assembly modes via utilizing neural networks. It is assumed that a tuned mathematical model of the rotor under consideration is readily available, which is always the case for today’s realistic bladed disk assemblies. In the first method, a data set of selected mode shapes and natural frequencies is created by a number of simulations performed by mistuning the tuned mathematical model randomly. A neural network created by considering the number of modes, is then trained with this data set. Upon training the network, it is used to identify mistuning of the rotor from measured data. The second method further improves the first one by using it as starting point of an optimization routine and carries out an optimization to identify mistuning. To carry out identification analysis by means of the proposed methods, there are no limitations on the number of modes or natural frequencies to be used. Thus, they are suitable for incomplete data as well. Moreover, since system modes are used rather than blade alone counterparts, the techniques are ready to be used for analysis of blisks. Case studies are performed to demonstrate the capabilities of the new methods, using two different mathematical models to create training data sets; a lumped-parameter model and a relatively realistic reduced order model. Throughout the case studies, the effects of using incomplete mode families and random errors in assembly modes are investigated.


2020 ◽  
Author(s):  
Kaushik Das

<div>Increasing share of renewables poses new challenges towards planning and operation of power systems all</div><div>over the world, thereby, requiring new methods and tools. This article explains the value of balancing tool chain</div><div>which encompasses operation of market and power system from day-ahead planning until the real-time dynamic</div><div>simulation. The salient features for such a balancing tool chain is discussed in this article. A Balancing Tool</div><div>Chain has been developed and validated based on balancing principles of Denmark and Europe. The efficacy of</div><div>the balancing tool chain is demonstrated through very detailed case studies of massive penetration of offshore</div><div>wind power in North Sea countries towards 2050. Using detailed case studies, recommendations are provided</div><div>towards balancing of North Sea countries in terms of operational and balancing practices as well as dimensioning</div><div>of reserves for future scenarios.</div>


Author(s):  
Spilios D Fassois ◽  
John S Sakellariou

An overview of the principles and techniques of time-series methods for fault detection, identification and estimation in vibrating structures is presented, and certain new methods are introduced. The methods are classified, and their features and operation are discussed. Their practicality and effectiveness are demonstrated through brief presentations of three case studies pertaining to fault detection, identification and estimation in an aircraft panel, a scale aircraft skeleton structure and a simple nonlinear simulated structure.


2020 ◽  
pp. 65-93
Author(s):  
B. Zorina Khan

Academics and policymakers alike tend to motivate their claims about innovation prizes with a cluster of popular, but previously unexamined, historical anecdotes. As a result, canonical case studies like the award for gauging longitude at sea, the success of efforts to induce new methods of food preservation in France, and “Daguerrotype patent buyouts” have had a disproportionate effect on our understanding of institutions and incentives for inventive activity. Closer attention to the specific details derived from the primary records reveals key misapprehensions and inaccuracies, implying that the oft-recited conclusions about technological prizes are largely misleading.


Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 338 ◽  
Author(s):  
Laure Nuninger ◽  
Philip Verhagen ◽  
Thérèse Libourel ◽  
Rachel Opitz ◽  
Xavier Rodier ◽  
...  

The amount of information available to archaeologists has grown dramatically during the last ten years. The rapid acquisition of observational data and creation of digital data has played a significant role in this “information explosion”. In this paper, we propose new methods for knowledge creation in studies of movement, designed for the present data-rich research context. Using three case studies, we analyze how researchers have identified, conceptualized, and linked the material traces describing various movement processes in a given region. Then, we explain how we construct ontologies that enable us to explicitly relate material elements, identified in the observed landscape, to the knowledge or theory that explains their role and relationships within the movement process. Combining formal pathway systems and informal movement systems through these three case studies, we argue that these systems are not hierarchically integrated, but rather intertwined. We introduce a new heuristic tool, the “track graph”, to record observed material features in a neutral form which can be employed to reconstruct the trajectories of journeys which follow different movement logics. Finally, we illustrate how the breakdown of implicit conceptual references into explicit, logical chains of reasoning, describing basic entities and their relationships, allows the use of these constituent elements to reconstruct, analyze, and compare movement practices from the bottom up.


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