Structuring the Haystack

2021 ◽  
pp. 246-268
Author(s):  
Eliane Bucher ◽  
Peter Kalum Schou ◽  
Matthias Waldkirch ◽  
Eduard Grünwald ◽  
David Antons
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Methodological Approach ◽  
Mixed Methodology ◽  
Community Interactions ◽  
Trade Off ◽  
Digital Platforms ◽  
Gig Economy ◽  
And Control ◽  
Insight Into

Large-scale online communities, such as Reddit or Quora, have emerged as promising research contexts, offering insight into an unprecedented range of real-time user discourses. However, researchers striving to access, collect, and meaningfully process such conversation data face a trade-off between capturing breadth (structures, relationships) and depth (content, meaning) of community interactions. Building on a mixed-methodology design, our contribution offers an avenue to harness and combine advantages of both approaches, first by clustering the data based on a theoretically derived dictionary (discovering structure) and second by qualitatively coding and interpreting the resulting clusters (discovering meaning). We illustrate this methodological approach with data collected from a community of online workers on Reddit where we focused on how human resource management (HRM) practices transform in the gig economy and how digital platforms use a hybrid HRM system that combines elements of high-performance and control-oriented HRM philosophies.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

scholarly journals Geo-Spatial Analysis of Population Density and Annual Income to Identify Large-Scale Socio-Demographic Disparities

2021 ◽  
Vol 10 (7) ◽  
pp. 432
Author(s):  
Nicolai Moos ◽  
Carsten Juergens ◽  
Andreas P. Redecker
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Methodological Approach ◽  
Spatial Relationship ◽  
Postal Code ◽  
Annual Income ◽  
Choropleth Maps ◽  
Clustering Approach ◽  
Relationship Of ◽  
Insight Into

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons.

scholarly journals LoRa (Long-Range) High-Density Sensors for Internet of Things

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Alexandru Lavric
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
High Performance ◽  
Large Scale ◽  
Geographic Area ◽  
High Density ◽  
Monitoring And Control ◽  
Spreading Factor ◽  
Transfer Of Information ◽  
And Control

Over the past few years, there has been a growing awareness regarding the concept of Internet of Things (IoT), which involves connecting to the Internet various objects surrounding us in everyday life. The main purpose of this concept closely connected to the smart city issue is increasing the quality of life by contributing to streamlining resource consumption and protecting the environment. The LoRa communication mechanism is a physical layer of the LoRaWAN protocol, defined by the LoRa Alliance. Compared to other existing technologies, LoRa is a modulation technique enabling the transfer of information over a range of tens of kilometers. The main contribution this paper brings to the field is analyzing the scalability of the LoRa technology and determining the maximum number of sensors which can be integrated into this type of monitoring and control architecture. The sensor architecture is specific to the smart city concept that involves the integration of a large number of high-density sensors distributed on a large-scale geographic area. The reason behind this study is the need to assess the scalability of the LoRa technology, taking into consideration other factors, such as the packet payload size, the duty circle parameter, the spreading factor, and the number of nodes. The experimental results reveal that the maximum number of LoRa sensors that can communicate on the same channel is 1,500; furthermore, in order to obtain a high performance level, it is necessary to schedule and plan the network as carefully as possible. The spreading factor must be allocated according to the distance at which the sensor is placed from the gateway.

scholarly journals An error analysis in the early grades mathematics – a learning opportunity?

2014 ◽  
Vol 4 (1) ◽  
pp. 19 ◽  
Author(s):  
Roelien Herholdt ◽  
Ingrid Sapire
Keyword(s):  
Problem Solving ◽  
Error Analysis ◽  
Large Scale ◽  
Mathematical Problem ◽  
Mathematical Problem Solving ◽  
Analysis Method ◽  
Problem Solving Skills ◽  
Scale Error ◽  
And Control ◽  
Insight Into

<p>Error analysis is the study of errors in learners’ work with a view to looking for possible explanations for these errors. It is a multifaceted activity involving analysis of correct, partially correct and incorrect processes and thinking about possible remediating strategies. This paper reports on such an analysis of learner tests. The tests were administered as part of the evaluation of an intervention project that aimed to teach mathematical problem solving skills to grade 1-4 learners. Quantitative error analysis was carried out using a coding sheet for each grade. A reliability coefficient was found for each test, as were item means and discrimination indexes for each item. The analysis provided some insight into the more common procedural and conceptual errors evidenced in the learners’ scripts. Findings showed similar difficulties across intervention and control schools and highlighted particular areas of difficulty. The authors argue that this analysis is an example of large-scale error analysis, but that the analysis method could be adopted by teachers of grades 1-4.</p>

scholarly journals Energy efficient high-performance approximate adders for imprecision-tolerant signal processing applications

2021 ◽  
Vol 2107 (1) ◽  
pp. 012065
Author(s):  
K Komathy Vanitha ◽  
S Anila
Keyword(s):  
Signal Processing ◽  
Energy Efficient ◽  
High Performance ◽  
Large Scale ◽  
Approximate Computing ◽  
Process Technology ◽  
Trade Off ◽  
Large Scale Integration ◽  
Power Delay Product ◽  
Scale Integration

Abstract The trade-off between Delay and Power consumption has become a major concern as process technology reached less than 10 nm proximity in the modern Very Large-Scale Integration (VLSI) technology. This trade-off can be compensated with accuracy and is vanquished by the development of Approximate Computing (AC). In this paper, six diverse Approximate Adders (AAs) have been proposed based on logic complexity reduction at the transistor level. Simulation results reveal that the Proposed AAs has a significant amount of Power and Delay savings, lesser Power-Delay Product (PDP). The Proposed AAs:PA1, PA3, PA5, PA3 exhibits 12.85 %, 41.59%, 72.05 %, 1.91% lesser power than the Existing AAs EAA1, EAA5, EAA6, EAA9 respectively. The Proposed AAs: PA2, PA3 incorporates 37.5 %, 54.5%, of lesser number of transistors compared to Existing AAs: EAA5, EAA9 whereas PA4, PA5 incorporates 40 % of reduction in the number of transistors compared to Existing AAs: EAA6, EAA8. These results are promising for high performance and energy efficient systems for error-resilient applications such as multimedia and signal processing where a slightly degraded output quality is acceptable, which could lead to significant power reduction.

scholarly journals Work Precarity and Gig Literacies in Online Freelancing

2019 ◽  
Vol 34 (3) ◽  
pp. 457-475 ◽  
Author(s):  
Will Sutherland ◽  
Mohammad Hossein Jarrahi ◽  
Michael Dunn ◽  
Sarah Beth Nelson
Keyword(s):  
Control Mechanisms ◽  
Holding Environment ◽  
Digital Platforms ◽  
Gig Economy ◽  
Critical Literacies ◽  
Work Strategies ◽  
And Control

Many workers have been drawn to the gig economy by the promise of flexible, autonomous work, but scholars have highlighted how independent working arrangements also come with the drawbacks of precarity. Digital platforms appear to provide an alternative to certain aspects of precarity by helping workers find work consistently and securely. However, these platforms also introduce their own demands and constraints. Drawing on 20 interviews with online freelancers, 19 interviews with corresponding clients and a first-hand walkthrough of the Upwork platform, we identify critical literacies (what we call gig literacies), which are emerging around online freelancing. We find that gig workers must adapt their skills and work strategies in order to leverage platforms creatively and productively, and as a component of their ‘personal holding environment’. This involves not only using the resources provided by the platform effectively, but also negotiating or working around its imposed structures and control mechanisms.

scholarly journals Carbon Electrodes in Perovskite Photovoltaics

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 5989
Author(s):  
Preawpun Pradid ◽  
Kanyanee Sanglee ◽  
Non Thongprong ◽  
Surawut Chuangchote
Keyword(s):  
Solar Cells ◽  
High Performance ◽  
Large Scale ◽  
Carbon Materials ◽  
Low Cost ◽  
Perovskite Solar Cells ◽  
Deposition Process ◽  
Device Structures ◽  
Temperature Deposition ◽  
Insight Into

High-performance lab-scale perovskite solar cells often have a precious metal as the top electrode. However, there are drawbacks to using metal top electrodes on a large scale, such as inducing degradation processes, requiring a high-temperature deposition process under vacuum, and having low scalability. Recently many studies have shown the potentials of using a carbon electrode because of its conductivity, flexibility, low cost, and ease of fabrication. This review article presents an overview of using carbon materials to replace the top electrode in perovskite photovoltaics. We discuss various fabrication techniques, various carbon-based device structures, and the advantages of using carbon materials. A collection of research works on device performance, large-scale fabrication, and device stability is presented. As a result, this review offers insight into the future of large-scale flexible solar cells.

A Remote Intelligent Monitoring System for Large Scale Photovoltaic Power Plant

2011 ◽  
Vol 58-60 ◽  
pp. 1892-1895
Author(s):  
D. J. Yu ◽  
Y.H. Chen ◽  
Z. Zhen ◽  
Y. Qi ◽  
L. S. Lin
Keyword(s):  
High Performance ◽  
Power Plants ◽  
Large Scale ◽  
Photovoltaic Devices ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
Photovoltaic Power ◽  
Different Types ◽  
And Control ◽  
Monitor And Control

This paper designs a GPRS-based system to effectively monitor and control large scale Photovoltaic Power Plants. Single-Chip microcomputer with high performance is utilized to collect data from different types of photovoltaic devices; the collected data are then sent to the server via GPRS; the server receives and intelligently analyzes the data. The operators can monitor and control the running status of photovoltaic devices by executing a simple client tool. The implemented system has been applied in several Photovoltaic Power Plants.

scholarly journals Prioritizing Disease-Related Microbes Based on the Topological Properties of a Comprehensive Network

2021 ◽  
Vol 12 ◽  
Author(s):  
Haixiu Yang ◽  
Fan Tong ◽  
Changlu Qi ◽  
Ping Wang ◽  
Jiangyu Li ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Cross Validation ◽  
Area Under The Curve ◽  
Disease Pathogenesis ◽  
Physiological Processes ◽  
Disease Associations ◽  
Inflammatory Bowel ◽  
Leave One Out ◽  
Insight Into

Many microbes are parasitic within the human body, engaging in various physiological processes and playing an important role in human diseases. The discovery of new microbe–disease associations aids our understanding of disease pathogenesis. Computational methods can be applied in such investigations, thereby avoiding the time-consuming and laborious nature of experimental methods. In this study, we constructed a comprehensive microbe–disease network by integrating known microbe–disease associations from three large-scale databases (Peryton, Disbiome, and gutMDisorder), and extended the random walk with restart to the network for prioritizing unknown microbe–disease associations. The area under the curve values of the leave-one-out cross-validation and the fivefold cross-validation exceeded 0.9370 and 0.9366, respectively, indicating the high performance of this method. Despite being widely studied diseases, in case studies of inflammatory bowel disease, asthma, and obesity, some prioritized disease-related microbes were validated by recent literature. This suggested that our method is effective at prioritizing novel disease-related microbes and may offer further insight into disease pathogenesis.

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