Search results for "work"
showing 10 items of 14511 documents
Cell state prediction through distributed estimation of transmit power
2019
Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of…
Exploring Design Cognition in Voice-Driven Sound Sketching and Synthesis
2021
Conceptual design and communication of sonic ideas are critical, and still unresolved aspects of current sound design practices, especially when teamwork is involved. Design cognition studies in the visual domain represent a valuable resource to look at, to better comprehend the reasoning of designers when they approach a sound-based project. A design exercise involving a team of professional sound designers is analyzed, and discussed in the framework of the Function-Behavior-Structure ontology of design. The use of embodied sound representations of concepts fosters team-building and a more effective communication, in terms of shared mental models.
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…
Deep neural attention-based model for the evaluation of italian sentences complexity
2020
In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.
The moral work of becoming a professional
2021
Abstract In contemporary working life, art-based initiatives are increasingly used in organizational training and development. For artists, this has created new employment opportunities as creative entrepreneurs who provide specialist services for workplaces. In this article, we study the dynamics of such encounters through the narrated accounts of training professionals. Our data come from a professional mentoring program where the working pairs of artists and consultants shared stories about their customer projects. By using conversation analysis as a method, we analyze the way stories are interactionally accomplished in peer group sessions of the program. In particular, we analyze how pa…
A Clustering approach for profiling LoRaWAN IoT devices
2019
Internet of Things (IoT) devices are starting to play a predominant role in our everyday life. Application systems like Amazon Echo and Google Home allow IoT devices to answer human requests, or trigger some alarms and perform suitable actions. In this scenario, any data information, related device and human interaction are stored in databases and can be used for future analysis and improve the system functionality. Also, IoT information related to the network level (wireless or wired) may be stored in databases and can be processed to improve the technology operation and to detect network anomalies. Acquired data can be also used for profiling operation, in order to group devices according…
Interventions of speakers of Polish and British parliaments in the light of politeness theory
2021
Abstract The present study attempts to analyze the interventions of Speakers of Polish and British Parliaments in the selected exchanges from 2018 to 2019 in terms of discourse-sensitive politeness theory advanced by Jonathan Culpeper. He proposes to use three types of impoliteness that affect three types of interlocutors’ faces via a range of impoliteness strategies. In the analyses we consider the linguistic, personal, and cultural as well as political context of the exchanges against the background of the unique, historically rooted institutional circumstances, with a special emphasis on the role of different physical contexts of respective Parliamentary chambers. We emphasize the discur…
Migrant women, work, and investment in language learning : Two success stories
2019
Abstract In the media, migrant mothers are often portrayed as uneducated, having trouble learning a new language, and preferring to stay at home rather than entering paid employment. This article offers a contrasting point of view as a result of examining how two migrant women narrativize their experiences of language learning and working-life-related integration during a three-year period. Specific attention is paid to how the women make sense of their language use over time, and how this may have contributed to their integration into working life and the wellbeing of their families. Interview data was analyzed using the short story analytical approach, focusing on both the content and the…
Policing language in the world of new work : the commodification of workplace communication in organizational consulting
2021
Abstract This paper examines how the shift to knowledge and innovation economy has created new sites for the commodification of language and communication in the context of organizational consulting. The data come from a consultant-led development and training program of the management teams of a Finnish educational organization. In the study, the year-long training was videotaped (45 h) and followed ethnographically. By using rhetorical discourse analysis as a method, we examine how the consultant-led training activities present the role of language and communication in changing working life. The results show how the activities factualize the transformation of work and the centrality of la…
Multi-class Text Complexity Evaluation via Deep Neural Networks
2019
Automatic Text Complexity Evaluation (ATE) is a natural language processing task which aims to assess texts difficulty taking into account many facets related to complexity. A large number of papers tackle the problem of ATE by means of machine learning algorithms in order to classify texts into complex or simple classes. In this paper, we try to go beyond the methodologies presented so far by introducing a preliminary system based on a deep neural network model whose objective is to classify sentences into more of two classes. Experiments have been carried out on a manually annotated corpus which has been preprocessed in order to make it suitable for the scope of the paper. The results sho…