scholarly journals Extraction of transforming sequences and sentence histories from writing process data: a first step towards linguistic modeling of writing

2022 ◽  
Author(s):  
Cerstin Mahlow ◽  
Malgorzata Anna Ulasik ◽  
Don Tuggener
Keyword(s):  
Language Processing ◽  
Writing Process ◽  
Software Tool ◽  
Building Blocks ◽  
Linear Process ◽  
Small Scale ◽  
Process Data ◽  
Written Text ◽  
Product And Process ◽  
Linguistic Structures

AbstractProducing written texts is a non-linear process: in contrast to speech, writers are free to change already written text at any place at any point in time. Linguistic considerations are likely to play an important role, but so far, no linguistic models of the writing process exist. We present an approach for the analysis of writing processes with a focus on linguistic structures based on the novel concepts of transforming sequences, text history, and sentence history. The processing of raw keystroke logging data and the application of natural language processing tools allows for the extraction and filtering of product and process data to be stored in a hierarchical data structure. This structure is used to re-create and visualize the genesis and history for a text and its individual sentences. Focusing on sentences as primary building blocks of written language and full texts, we aim to complement established writing process analyses and, ultimately, to interpret writing timecourse data with respect to linguistic structures. To enable researchers to explore this view, we provide a fully functional implementation of our approach as an open-source software tool and visualizations of the results. We report on a small scale exploratory study in German where we used our tool. The results indicate both the feasibility of the approach and that writers actually revise on a linguistic level. The latter confirms the need for modeling written text production from the perspective of linguistic structures beyond the word level.

scholarly journals PyroMEMS as Future Technological Building Blocks for Advanced Microenergetic Systems

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 118
Author(s):  
Jean-Laurent Pouchairet ◽  
Carole Rossi
Keyword(s):  
Building Block ◽  
Building Blocks ◽  
Small Scale ◽  
Technological Evolution ◽  
Research Groups ◽  
Function Block ◽  
The Past ◽  
New Methods ◽  
Safety And Reliability ◽  
Electronically Controllable

For the past two decades, many research groups have investigated new methods for reducing the size and cost of safe and arm-fire systems, while also improving their safety and reliability, through batch processing. Simultaneously, micro- and nanotechnology advancements regarding nanothermite materials have enabled the production of a key technological building block: pyrotechnical microsystems (pyroMEMS). This building block simply consists of microscale electric initiators with a thin thermite layer as the ignition charge. This microscale to millimeter-scale addressable pyroMEMS enables the integration of intelligence into centimeter-scale pyrotechnical systems. To illustrate this technological evolution, we hereby present the development of a smart infrared (IR) electronically controllable flare consisting of three distinct components: (1) a controllable pyrotechnical ejection block comprising three independently addressable small-scale propellers, all integrated into a one-piece molded and interconnected device, (2) a terminal function block comprising a structured IR pyrotechnical loaf coupled with a microinitiation stage integrating low-energy addressable pyroMEMS, and (3) a connected, autonomous, STANAG 4187 compliant, electronic sensor arming and firing block.

scholarly journals Geostatistical Learning: Challenges and Opportunities

2021 ◽  
Vol 7 ◽  
Author(s):  
Júlio Hoffimann ◽  
Maciel Zortea ◽  
Breno de Carvalho ◽  
Bianca Zadrozny
Keyword(s):  
Statistical Learning ◽  
Spatial Correlation ◽  
Language Processing ◽  
Real Data ◽  
Model Errors ◽  
Process Data ◽  
Applied Machine Learning ◽  
Geophysical Surveys ◽  
Challenges And Opportunities ◽  
Geophysical Processes

Statistical learning theory provides the foundation to applied machine learning, and its various successful applications in computer vision, natural language processing and other scientific domains. The theory, however, does not take into account the unique challenges of performing statistical learning in geospatial settings. For instance, it is well known that model errors cannot be assumed to be independent and identically distributed in geospatial (a.k.a. regionalized) variables due to spatial correlation; and trends caused by geophysical processes lead to covariate shifts between the domain where the model was trained and the domain where it will be applied, which in turn harm the use of classical learning methodologies that rely on random samples of the data. In this work, we introduce the geostatistical (transfer) learning problem, and illustrate the challenges of learning from geospatial data by assessing widely-used methods for estimating generalization error of learning models, under covariate shift and spatial correlation. Experiments with synthetic Gaussian process data as well as with real data from geophysical surveys in New Zealand indicate that none of the methods are adequate for model selection in a geospatial context. We provide general guidelines regarding the choice of these methods in practice while new methods are being actively researched.

scholarly journals Online Communities and Open Innovation

Economics ◽  
2015 ◽  
pp. 652-666
Author(s):  
Alberto Francesconi ◽  
Riccardo Bonazzi ◽  
Claudia Dossena
Keyword(s):  
Solar System ◽  
Absorptive Capacity ◽  
Online Communities ◽  
Open Innovation ◽  
Online Community ◽  
Software Tool ◽  
Linear Process ◽  
Innovation Approach

Online communities are becoming an important way to support firms towards an open innovation approach. However, knowledge shared in an online community represents only a potential for firm's innovation aims. The effectiveness of exploration and exploitation of this knowledge depends on firm's absorptive capacity. In this work the authors focus on the time an idea, shared within an online community, takes to be transformed from a ‘potential' into a ‘realized' innovation by a firm. In particular, conceiving knowledge as a trajectory across pole of attraction rather than a linear process, the authors develop a model inspired by the solar system metaphor. Preliminary results from a case study are presented. They suggest firms may improve the effectiveness of absorptive capacity exploiting the mediation role of a software tool.

scholarly journals Responsive and Adaptive Design for Survey Optimization

2018 ◽  
Vol 34 (3) ◽  
pp. 581-597 ◽  
Author(s):  
Asaph Young Chun ◽  
Steven G. Heeringa ◽  
Barry Schouten
Keyword(s):  
Adaptive Design ◽  
Survey Design ◽  
Special Section ◽  
Cost Optimization ◽  
Auxiliary Information ◽  
Building Blocks ◽  
Quality Data ◽  
Future Research ◽  
Efficient Production ◽  
Process Data

Abstract We discuss an evidence-based approach to guiding real-time design decisions during the course of survey data collection. We call it responsive and adaptive design (RAD), a scientific framework driven by cost-quality tradeoff analysis and optimization that enables the most efficient production of high-quality data. The notion of RAD is not new; nor is it a silver bullet to resolve all the difficulties of complex survey design and challenges. RAD embraces precedents and variants of responsive design and adaptive design that survey designers and researchers have practiced over decades. In this paper, we present the four pillars of RAD: survey process data and auxiliary information, design features and interventions, explicit quality and cost metrics, and a quality-cost optimization tailored to survey strata. We discuss how these building blocks of RAD are addressed by articles published in the 2017 JOS special issue and this special section. It is a tale of the three perspectives filling in each other. We carry over each of these three perspectives to articulate the remaining challenges and opportunities for the advancement of RAD. We recommend several RAD ideas for future research, including survey-assisted population modeling, rigorous optimization strategies, and total survey cost modeling.

Phonotactics and Syllable Structure in Infant Speech Perception

2016 ◽  
Author(s):  
Tania S. Zamuner ◽  
Viktor Kharlamov
Keyword(s):  
Speech Perception ◽  
Language Acquisition ◽  
Language Processing ◽  
Syllable Structure ◽  
Structure Form ◽  
Modeling Studies ◽  
Wide Range ◽  
Infant Speech Perception ◽  
Sound Patterns ◽  
Linguistic Structures

Phonotactics and syllable structure form an integral part of phonological competence and may be used to discover other aspects of language. Given the importance of such knowledge to the process of language acquisition, numerous studies have investigated the development of phonotactic and syllabic knowledge in order to determine when infants become sensitive to these sound patterns and how they may use this knowledge in language processing. Considering that infants’ first exposure to linguistic structures comes from speech perception, we provide an overview of the perception-related issues that have been investigated experimentally and point out issues that have not yet been addressed in the literature. We begin with phonotactic development, examining a wide range of sound patterns, followed by a discussion of the acquisition of syllable structure and a brief summary of various outstanding issues that may be of interest to the reader, including production-related investigations and phonological modeling studies.

Optimized DA-reconfigurable FIR filters for software defined radio channelizer applications

Circuit World ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
C. Srinivasa Murthy ◽  
K. Sridevi
Keyword(s):  
Energy Efficiency ◽  
Power Dissipation ◽  
Software Defined Radio ◽  
Filter Design ◽  
Finite Impulse Response ◽  
Software Tool ◽  
Building Blocks ◽  
Fir Filter ◽  
Content Type ◽  
Filter Length

Purpose In this paper, the authors present different methods for reconfigurable finite impulse response (RFIR) filter design. Distributed arithmetic (DA)-based reconfigurable FIR filter design is suitable for software-defined radio (SDR) applications. The main contribution of reconfiguration is reuse of registers, multipliers, adders and to optimize various parameters such as area, power dissipation, speed, throughput, latency and hardware utilizations of flip-flops and slices. Therefore, effective design of building blocks will be optimized for RFIR filter with all the above parameters. Design/methodology/approach The modified, direct form register structure of FIR filter contributes the reuse concept and allows utilization of less number of registers and parallel computation operations. The disadvantage of DA and other conventional methods is delay increases proportionally with filter length. This is due to different partial products generated by adders. The usage of adder and multipliers in DA-FIR filter restricts the area and power dissipation because of their complexity of generation of sum and carry bits. The hardware implementation time of an adder can be reduced by parallel prefix adder (PPA) usage based on Ling equation. PPA uses shift-add multiplication, which is a repetitive process of addition, and this process is known as Bypass Zero feed multiplicand in direct multiplication, and the proposed technique optimizes area-power product efficiently. The modified DA (MDA)-based RFIR filter is designed for 64 taps filter length (N). The design is developed by using Verilog hardware description language and implemented on field-programmable gate array. Also, this design validates SDR channel equalizer. Findings Both RFIR and SDR are integrated as single system and implemented on Artix-7 development board of XC7A100tCSG324 and exploited the advantages in area-delay, power-speed products and energy efficiency. The theoretical and practical comparisons have been carried out, and the results are compared with existing DA-RFIR designs in terms of throughput, latency, area-delay, power-speed products and energy efficiency, which are improved by 14.5%, 23%, 6.5%, 34.2% and 21%, respectively. Originality/value The DA-based RFIR filter is validated using Chipscope Pro software tool on Artix-7 FPGA in Xilinx ISE design suite and compared constraint parameters with existing state-of-art results. It is also tested the filtering operation by applying the RFIR filter on Audio signals for removal of noisy signals and it is found that 95% of noise signals are filtered effectively.

Concurrent Robust Product and Process Design

1999 ◽  
Author(s):  
Lars Lindkvist ◽  
Rikard Söderberg
Keyword(s):  
Process Design ◽  
Evaluation Criteria ◽  
Software Tool ◽  
The Body ◽  
Assembly Process ◽  
Critical Dimensions ◽  
Cad System ◽  
Start Up ◽  
Assembly Evaluation ◽  
Product And Process

Abstract This paper presents a method for assembly evaluation. The method uses two evaluation criteria, robustness and variation analysis, and is supported by a software tool developed by the authors. The robustness evaluation aims at detecting design and assembly solutions that are sensitive to variation and may cause problems during production. Using this method in early product and process design phases helps to find more robust concepts, resulting in shorter production start-up time and better precision. The method’s use is exemplified in a concept study of the assembly process of the door to the body of a (fictitious) jeep. The study shows that the proposed method can be used to obtain an objective comparison between different concepts. This comparison includes both general robustness and the expected variation in the critical dimensions. The results can be used, together with economical and practical aspects, to determine which concept is best suited for the assembly process. The software used is implemented in the MS Windows environment and has an JGES interface that enables the user to import CAD geometry from an arbitrary CAD system. It can perform different types of robustness evaluations as well as traditional variation analyses.

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