In order that – a data-driven study of symptoms and causes of obsolescence

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Karolina Rudnicka
Keyword(s):  
Higher Order ◽  
Human Interaction ◽  
Data Driven ◽  
Order Process ◽  
Cultural Changes ◽  
Frequency Of Use ◽  
Data Driven Approach ◽  
New Ideas ◽  
Late Modern

Abstract This paper is an empirical case study of grammatical obsolescence in progress. The main variable of study is the English purpose subordinator in order that, which is shown to be steadily decreasing in its frequency of use, starting from the beginning of the twentieth century. This work applies a data-driven approach for the investigation and description of obsolescence, recently developed by Rudnicka, Karolina. 2019. The Statistics of obsolescence: Purpose subordinators in Late Modern English. NIHIN: New Ideas in Human Interaction: Studies. Freiburg: Rombach. The methodology combines philological analysis with statistical methods used on data acquired from mega-corpora. Moving from the description of possible symptoms of obsolescence to different causes for it, the paper aims at presenting a comprehensive account of the studied phenomenon. Interestingly, a very significant role in the decline of in order that can be ascribed to the so-called higher-order processes, understood as processes influencing the constructional level from above. Two kinds of higher-order processes are shown to play an important role, namely i) an externally-motivated higher-order process exemplified by the drastic socio-cultural changes of the nineteenth and twentieth centuries, and ii) an internally-motivated higher-order process instantiated by the rise of the to-infinitive (rise of infinite clauses).

scholarly journals Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study

2020 ◽  
pp. 221-251
Author(s):  
Stefan Varga ◽  
Joel Brynielsson ◽  
Andreas Horndahl ◽  
Magnus Rosell
Keyword(s):  
Text Analysis ◽  
Ecological Validity ◽  
Data Driven ◽  
Intelligence Analysis ◽  
Prototype Tool ◽  
Analysis Task ◽  
Private Citizens ◽  
Data Driven Approach ◽  
Psychological Operations

Abstract With the availability of an abundance of data through the Internet, the premises to solve some intelligence analysis tasks have changed for the better. The study presented herein sets out to examine whether and how a data-driven approach can contribute to solve intelligence tasks. During a full day observational study, an ordinary military intelligence unit was divided into two uniform teams. Each team was independently asked to solve the same realistic intelligence analysis task. Both teams were allowed to use their ordinary set of tools, but in addition one team was also given access to a novel text analysis prototype tool specifically designed to support data-driven intelligence analysis of social media data. The results, obtained from the case study with a high ecological validity, suggest that the prototype tool provided valuable insights by bringing forth information from a more diverse set of sources, specifically from private citizens that would not have been easily discovered otherwise. Also, regardless of its objective contribution, the capabilities and the usage of the tool were embraced and subjectively perceived as useful by all involved analysts.

scholarly journals A Data-Driven Approach to Extend Failure Analysis: A Framework Development and a Case Study on a Hydroelectric Power Plant

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6400
Author(s):  
Sara Antomarioni ◽  
Marjorie Maria Bellinello ◽  
Maurizio Bevilacqua ◽  
Filippo Emanuele Ciarapica ◽  
Renan Favarão da Silva ◽  
...  
Keyword(s):  
Power Plant ◽  
Failure Analysis ◽  
Power Plants ◽  
Failure Modes ◽  
Real Life ◽  
Hydroelectric Power Plant ◽  
Data Driven ◽  
Hydroelectric Power ◽  
Data Driven Approach

Power plants are required to supply the electric demand efficiently, and appropriate failure analysis is necessary for ensuring their reliability. This paper proposes a framework to extend the failure analysis: indeed, the outcomes traditionally carried out through techniques such as the Failure Mode and Effects Analysis (FMEA) are elaborated through data-driven methods. In detail, the Association Rule Mining (ARM) is applied in order to define the relationships among failure modes and related characteristics that are likely to occur concurrently. The Social Network Analysis (SNA) is then used to represent and analyze these relationships. The main novelty of this work is represented by support in the maintenance management process based not only on the traditional failure analysis but also on a data-driven approach. Moreover, the visual representation of the results provides valuable support in terms of comprehension of the context to implement appropriate actions. The proposed approach is applied to the case study of a hydroelectric power plant, using real-life data.

scholarly journals A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 827 ◽  
Author(s):  
Serafín Alonso ◽  
Antonio Morán ◽  
Miguel Prada ◽  
Perfecto Reguera ◽  
Juan Fuertes ◽  
...  
Keyword(s):  
Energy Demand ◽  
Data Driven ◽  
Coefficient Of Performance ◽  
Key Factors ◽  
Whole Plant ◽  
Data Driven Approach ◽  
Energy Efficiency Indicator ◽  
Cooling Loads ◽  
Aggregation Operations

Large buildings cause more than 20% of the global energy consumption in advanced countries. In buildings such as hospitals, cooling loads represent an important percentage of the overall energy demand (up to 44%) due to the intensive use of heating, ventilation and air conditioning (HVAC) systems among other key factors, so their study should be considered. In this paper, we propose a data-driven analysis for improving the efficiency in multiple-chiller plants. Coefficient of performance (COP) is used as energy efficiency indicator. Data analysis, based on aggregation operations, filtering and data projection, allows us to obtain knowledge from chillers and the whole plant, in order to define and tune management rules. The plant manager software (PMS) that implements those rules establishes when a chiller should be staged up/down and which chiller should be started/stopped according different efficiency criteria. This approach has been applied on the chiller plant at the Hospital of León.

Steps towards incorporating heterogeneities into program theory: A case study of a data-driven approach

2016 ◽  
Vol 58 ◽  
pp. 88-97 ◽  
Author(s):  
Sanjeev Sridharan ◽  
Bobby Jones ◽  
Barry Caudill ◽  
April Nakaima
Keyword(s):  
Program Theory ◽  
Data Driven ◽  
Data Driven Approach

scholarly journals A Data-Driven Approach for Video Game Playability Analysis Based on Players’ Reviews

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 129
Author(s):  
Xiaozhou Li ◽  
Zheying Zhang ◽  
Kostas Stefanidis
Keyword(s):  
Video Games ◽  
Video Game ◽  
Binary Classification ◽  
Game Studies ◽  
Data Driven ◽  
Software Products ◽  
Data Driven Approach ◽  
Definition Of

Playability is a key concept in game studies defining the overall quality of video games. Although its definition and frameworks are widely studied, methods to analyze and evaluate the playability of video games are still limited. Using heuristics for playability evaluation has long been the mainstream with its usefulness in detecting playability issues during game development well acknowledged. However, such a method falls short in evaluating the overall playability of video games as published software products and understanding the genuine needs of players. Thus, this paper proposes an approach to analyze the playability of video games by mining a large number of players’ opinions from their reviews. Guided by the game-as-system definition of playability, the approach is a data mining pipeline where sentiment analysis, binary classification, multi-label text classification, and topic modeling are sequentially performed. We also conducted a case study on a particular video game product with its 99,993 player reviews on the Steam platform. The results show that such a review-data-driven method can effectively evaluate the perceived quality of video games and enumerate their merits and defects in terms of playability.

Data-driven approach to identify obsolete functions of products for design improvements

2021 ◽  
pp. 1-14
Author(s):  
Zhihua Zhao ◽  
Yupeng Li ◽  
Xuening Chu
Keyword(s):  
Time Series ◽  
Functional Performance ◽  
Smart Phone ◽  
Data Driven ◽  
Design Elements ◽  
Customer Expectations ◽  
Data Driven Approach ◽  
Identification Approach ◽  
Previous Identification

Identifying defective design elements is a prerequisite for design improvements. Previous identification methods were implemented in the context of static customer requirements (CRs). However, CRs always evolve continuously, which easily leads to a failure of existing product functions in fulfilling customer expectations; this, in turn, can lead to a decline in customer satisfaction. In this study, the phenomenon is termed as ‘function obsolescence’, and a data-driven identification approach for obsolete functions is proposed for design improvements. Firstly, product operating data are employed to construct the observing parameters of functional performance (OPs), and based on the distribution of OPs, the desired level of functional performance (DL) is defined to quantitatively characterise CRs. Secondly, the time series of DL is constructed to embody the evolution of CRs, in which a Sigmoid-like function is employed to establish a dissatisfaction function. With the time series, an obsolescence index measuring the severity of obsolescence for each function is defined to identify obsolete functions. A case study was implemented on a smart phone to identify its obsolete functions to demonstrate the effectiveness of the proposed methodology. The results show that some potentially obsolete functions can be identified by the proposed method considering the evolution of CRs.

scholarly journals A data-driven approach for characterising the charging demand of electric vehicles: A UK case study

2016 ◽  
Vol 162 ◽  
pp. 763-771 ◽  
Author(s):  
Erotokritos Xydas ◽  
Charalampos Marmaras ◽  
Liana M. Cipcigan ◽  
Nick Jenkins ◽  
Steve Carroll ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Data Driven ◽  
Data Driven Approach ◽  
Charging Demand
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