Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981724
Y. Ushakov, M. Ushakova, A. Shukhman, P. Polezhaev, L. Legashev
Modern video conferences are increasingly moving to the WebRTC technology, which works in a browser. Almost all modern video conferencing systems provide functionality for maintenance, transcoding, and recording of several video streams. The proposed platform provides the opportunity to teach students using video conferences and integrates into Moodle. The goal of this research is to study its operation based on Janus - the open source WebRTC server.
{"title":"WebRTC based Platform for Video Conferencing in An Educational Environment","authors":"Y. Ushakov, M. Ushakova, A. Shukhman, P. Polezhaev, L. Legashev","doi":"10.1109/AICT47866.2019.8981724","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981724","url":null,"abstract":"Modern video conferences are increasingly moving to the WebRTC technology, which works in a browser. Almost all modern video conferencing systems provide functionality for maintenance, transcoding, and recording of several video streams. The proposed platform provides the opportunity to teach students using video conferences and integrates into Moodle. The goal of this research is to study its operation based on Janus - the open source WebRTC server.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122393788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981773
Geoffrey Attard, C. de Raffaele, Serengul Smith
The use of Tangible User Interfaces (TUI) as an educational technology has gained sustained interest over the years with common agreement on its innate ability to engage and intrigue students in active-learning pedagogies. Whilst encouraging results have been obtained in research, the widespread adoption of TUI architectures is still hindered by a myriad of implementation burdens imposed by current toolkits. To this end, this paper presents an innovative TUI toolkit: TangiBoard, which enables the deployment of an interactive TUI system using low-cost, and presently available educational technology. Apart from curtailing setup costs and technical expertise required for adopting TUI systems, the toolkit provides an application framework to facilitate system calibration and development integration with GUI applications. This is enabled by a robust computer vision application that tracks a contributed passive marker set providing a range of tangible interactions to TUI frameworks. The effectiveness of this toolkit was evaluated by computer systems developers with respect to alternate toolkits for TUI design. Open-source versions of the TangiBoard toolkit together with marker sets are provided online through research license.
{"title":"TangiBoard: A Toolkit to Reduce the Implementation Burden of Tangible User Interfaces in Education","authors":"Geoffrey Attard, C. de Raffaele, Serengul Smith","doi":"10.1109/AICT47866.2019.8981773","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981773","url":null,"abstract":"The use of Tangible User Interfaces (TUI) as an educational technology has gained sustained interest over the years with common agreement on its innate ability to engage and intrigue students in active-learning pedagogies. Whilst encouraging results have been obtained in research, the widespread adoption of TUI architectures is still hindered by a myriad of implementation burdens imposed by current toolkits. To this end, this paper presents an innovative TUI toolkit: TangiBoard, which enables the deployment of an interactive TUI system using low-cost, and presently available educational technology. Apart from curtailing setup costs and technical expertise required for adopting TUI systems, the toolkit provides an application framework to facilitate system calibration and development integration with GUI applications. This is enabled by a robust computer vision application that tracks a contributed passive marker set providing a range of tangible interactions to TUI frameworks. The effectiveness of this toolkit was evaluated by computer systems developers with respect to alternate toolkits for TUI design. Open-source versions of the TangiBoard toolkit together with marker sets are provided online through research license.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122869918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981799
M. Ghiasi, Shaghayegh Gharehgozli
Fuzzy Logic revolution started during 1965 by Prof Lotfi A. Zadeh [1], [2] have evolved uncertainty and indeterminacy analytics forever. Sentiment analysis of published content on social networks is an essential key to analyze and predict social engagement polarities determined by provider's attitude and viewpoint toward a subject, being a profile, topic or single post. This paper uses precious works of Prof Lotfi A. Zadeh to propose a quantitative sentiment calculation method by introducing fuzziness and context dynamism on language-specific lexicons found on published short informal textual content on three holistic contexts of owner, user and the post itself.
1965年由Lotfi A. Zadeh教授发起的模糊逻辑革命[1]，[2]永远演变了不确定性和不确定性分析。对社交网络上发布的内容进行情感分析是分析和预测由提供者对一个主题(个人资料、主题或单个帖子)的态度和观点决定的社会参与极性的关键。本文利用Lotfi a . Zadeh教授的宝贵著作，对已发表的非正式短文本内容中的特定语言词汇引入模糊性和语境动态性，提出了一种定量情感计算方法。
{"title":"Social Sentiment Analysis Using Fuzzy Logic: Addressing context effect on sentiment analysis by fuzzy lexicon dynamism","authors":"M. Ghiasi, Shaghayegh Gharehgozli","doi":"10.1109/AICT47866.2019.8981799","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981799","url":null,"abstract":"Fuzzy Logic revolution started during 1965 by Prof Lotfi A. Zadeh [1], [2] have evolved uncertainty and indeterminacy analytics forever. Sentiment analysis of published content on social networks is an essential key to analyze and predict social engagement polarities determined by provider's attitude and viewpoint toward a subject, being a profile, topic or single post. This paper uses precious works of Prof Lotfi A. Zadeh to propose a quantitative sentiment calculation method by introducing fuzziness and context dynamism on language-specific lexicons found on published short informal textual content on three holistic contexts of owner, user and the post itself.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121289235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981750
N. N. Voit, M. Ukhanova, S. Brigadnov, S. Kirillov, S. Bochkov
This paper reviewed and investigated the main approaches, methods and means of extracting design documentation from PLM systems widely used in production. The authors proposed a new method for extracting data from design solutions of CAD, which allows extracting data and parameters as a result of analyzing design solutions, highlighting the history of building a three-dimensional model of a complex technical product, describes the main models and algorithms. The authors proposed a theoretical assessment of the effectiveness of the designer's activities using the system for extracting design characteristics from PLM.
{"title":"Method for extracting product design characteristics from life cycle management systems of complex technical objects","authors":"N. N. Voit, M. Ukhanova, S. Brigadnov, S. Kirillov, S. Bochkov","doi":"10.1109/AICT47866.2019.8981750","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981750","url":null,"abstract":"This paper reviewed and investigated the main approaches, methods and means of extracting design documentation from PLM systems widely used in production. The authors proposed a new method for extracting data from design solutions of CAD, which allows extracting data and parameters as a result of analyzing design solutions, highlighting the history of building a three-dimensional model of a complex technical product, describes the main models and algorithms. The authors proposed a theoretical assessment of the effectiveness of the designer's activities using the system for extracting design characteristics from PLM.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124528988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we present work on intelligent multimodal search and archive system, in which the scientific findings obtained in the work on recognition of Kazakh and Russian speeches, language identification and spoken term detection methods were applied. The paper describes the goals and objectives, the architecture, as well as the subsystem modules of the developed system. The VITA Search system allows for accurately determining the exact time of the required spoken information in the data in Kazakh and Russian languages from various broadcast channels. The speech recognition unit uses the Kaldi toolkit to generate lattices from the raw audio data. An acoustic model trained using deep neural networks shows significant results. The word error rate on the train set for recognition of Kazakh speech was 3.86, and for Russian speech - 9.85. Moreover, we integrated a language identification model trained using Long Short-Term Memory Recurrent Neural Networks in order to select the correct model for the input audio. Regarding spoken term detection, we applied word and proxy-based approaches to search for keyword terms among the lattices.
{"title":"VITA Search - An Intelligent Multimodal Search and Archive System for Online Media Resources","authors":"Zhanibek Kozhirbayev, Zhandos Yessenbayev, Bagdat Myrzakhmetov","doi":"10.1109/AICT47866.2019.8981781","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981781","url":null,"abstract":"In this paper we present work on intelligent multimodal search and archive system, in which the scientific findings obtained in the work on recognition of Kazakh and Russian speeches, language identification and spoken term detection methods were applied. The paper describes the goals and objectives, the architecture, as well as the subsystem modules of the developed system. The VITA Search system allows for accurately determining the exact time of the required spoken information in the data in Kazakh and Russian languages from various broadcast channels. The speech recognition unit uses the Kaldi toolkit to generate lattices from the raw audio data. An acoustic model trained using deep neural networks shows significant results. The word error rate on the train set for recognition of Kazakh speech was 3.86, and for Russian speech - 9.85. Moreover, we integrated a language identification model trained using Long Short-Term Memory Recurrent Neural Networks in order to select the correct model for the input audio. Regarding spoken term detection, we applied word and proxy-based approaches to search for keyword terms among the lattices.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"279 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132315583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981778
Alibek Zhakubayev, A. Yazıcı
In this article, a new methodology is proposed by using the relationships between meteorological events and asthma cases of asthma patients in a region compared to other regions in a country. We focus on the impact of weather conditions on asthma in order to estimate asthma cases using machine learning methods based on meteorological events only. In order to increase the success of the estimates, in addition to the 10 features identified by the National Environmental Information Centers, we create some new semi-synthetic features by using the multiplication and addition operations on the features given after the scaling. Then, we use machine learning methods and the R-square coefficient approach to learn the effective features using the features obtained from publicly available data sets for Russia. After determining the effective features, we use three different machine learning algorithms: random forest, linear regression, and kernel ridge regression algorithms. We use transfer learning to store effective features obtained from a dataset for Russia and then apply them to a dataset for Kazakhstan. Our hypothesis is that a combination of the selected semi-synthetic properties of the random forest algorithm has the best performance accuracy for this application. The model successfully identifies (predicts) very high, high, medium, low or very low numbers of people with asthma for the first time in the region.
{"title":"Learning the Relationship between Asthma and Meteorological Events by Using Machine Learning Methods","authors":"Alibek Zhakubayev, A. Yazıcı","doi":"10.1109/AICT47866.2019.8981778","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981778","url":null,"abstract":"In this article, a new methodology is proposed by using the relationships between meteorological events and asthma cases of asthma patients in a region compared to other regions in a country. We focus on the impact of weather conditions on asthma in order to estimate asthma cases using machine learning methods based on meteorological events only. In order to increase the success of the estimates, in addition to the 10 features identified by the National Environmental Information Centers, we create some new semi-synthetic features by using the multiplication and addition operations on the features given after the scaling. Then, we use machine learning methods and the R-square coefficient approach to learn the effective features using the features obtained from publicly available data sets for Russia. After determining the effective features, we use three different machine learning algorithms: random forest, linear regression, and kernel ridge regression algorithms. We use transfer learning to store effective features obtained from a dataset for Russia and then apply them to a dataset for Kazakhstan. Our hypothesis is that a combination of the selected semi-synthetic properties of the random forest algorithm has the best performance accuracy for this application. The model successfully identifies (predicts) very high, high, medium, low or very low numbers of people with asthma for the first time in the region.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130024286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981770
M. Farkhadov, N. Petukhova, A. Eliseev, Mukhabbat Farkhadova
In this paper we classify and analyze dialogue scenarios in automated human-machine systems with speech recognition. We take into account how to identify and correct recognition errors. Also, we evaluate and compare the scenarios according to how long the dialogue lasts, provided that the dialogue completes successfully with at least some given probability. Based on the results of our work, we formulated recommendations for developers of speech dialogue systems to choose a dialogue scenario; the actual scenario depends on how reliable the used speech blocks are.
{"title":"How to Design Dialogue Scenarios and Estimate Main Dialogue Parameters for a Voice-Controlled Man-Machine Interface","authors":"M. Farkhadov, N. Petukhova, A. Eliseev, Mukhabbat Farkhadova","doi":"10.1109/AICT47866.2019.8981770","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981770","url":null,"abstract":"In this paper we classify and analyze dialogue scenarios in automated human-machine systems with speech recognition. We take into account how to identify and correct recognition errors. Also, we evaluate and compare the scenarios according to how long the dialogue lasts, provided that the dialogue completes successfully with at least some given probability. Based on the results of our work, we formulated recommendations for developers of speech dialogue systems to choose a dialogue scenario; the actual scenario depends on how reliable the used speech blocks are.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115373558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981768
Matskevichus Mariia, Gladilin Peter
The model selection aims to estimate the performance of different model candidates in order to choose the most appropriate one. In this study we suggest exploiting specific features of time series for the optimal forecasting model selection such as length, seasonality, trend strength and others. To demonstrate reliability of feature-based approach, forecasting error distribution of LSTM Recurrent Neural Network, Linear Regression model, Holt-Winters model and ARIMA model trained on 250 time series with various characteristics were compared. Results of statistical experiments have demonstrated a significant dependence of a forecasting model on the characteristics of a series. Proposed model selection approach allows formulating a priori recommendations for choosing the optimal forecasting model for the specific time series.
{"title":"Model Selection Approach for Time Series Forecasting","authors":"Matskevichus Mariia, Gladilin Peter","doi":"10.1109/AICT47866.2019.8981768","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981768","url":null,"abstract":"The model selection aims to estimate the performance of different model candidates in order to choose the most appropriate one. In this study we suggest exploiting specific features of time series for the optimal forecasting model selection such as length, seasonality, trend strength and others. To demonstrate reliability of feature-based approach, forecasting error distribution of LSTM Recurrent Neural Network, Linear Regression model, Holt-Winters model and ARIMA model trained on 250 time series with various characteristics were compared. Results of statistical experiments have demonstrated a significant dependence of a forecasting model on the characteristics of a series. Proposed model selection approach allows formulating a priori recommendations for choosing the optimal forecasting model for the specific time series.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125884757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981764
R. Aliguliyev, Narmin A. Adigozalova
With fast increasing number of scientific publications, evaluation of the scientific performance of researchers has recently become an important issue. Nowadays, while the h-index and other Hirsh type indices take into consideration citation count of publications in the h-core, however, publication and citation count in the h-tail is omitted. This paper analyzes Hirsh type indices and proposes two new indices, the $h_{t}$ -index and the $A_{t}$ -index. The $h_{t}$ -index is defined as the h-index and the $A_{t}$ -index is defined as the A-index for the papers in the h-tail. These indices give information about the publications' quality in the h-tail. The proposed indices allow comparing researchers with the same h- and A-indices. For evaluation of the proposed indices experiment is conducted for 30 researchers in the fields of Data Mining. Results of the experiment demonstrated that if h-index and A-index of researchers are the same, then it is acceptable to compare them for their $h_{t}$ -index and $A_{t}$ -index.
{"title":"$h_{t}$ -index and $A_{t}$ -index for Evaluating Scientific Performance of Researchers","authors":"R. Aliguliyev, Narmin A. Adigozalova","doi":"10.1109/AICT47866.2019.8981764","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981764","url":null,"abstract":"With fast increasing number of scientific publications, evaluation of the scientific performance of researchers has recently become an important issue. Nowadays, while the h-index and other Hirsh type indices take into consideration citation count of publications in the h-core, however, publication and citation count in the h-tail is omitted. This paper analyzes Hirsh type indices and proposes two new indices, the $h_{t}$ -index and the $A_{t}$ -index. The $h_{t}$ -index is defined as the h-index and the $A_{t}$ -index is defined as the A-index for the papers in the h-tail. These indices give information about the publications' quality in the h-tail. The proposed indices allow comparing researchers with the same h- and A-indices. For evaluation of the proposed indices experiment is conducted for 30 researchers in the fields of Data Mining. Results of the experiment demonstrated that if h-index and A-index of researchers are the same, then it is acceptable to compare them for their $h_{t}$ -index and $A_{t}$ -index.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128629577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/AICT47866.2019.8981767
Aaro Hazak
Use of advanced ICT in combination with efficient management of intellectual capital in modern computerised knowledge work is key for generating innovation to achieve socio-economic development. This paper studies how some work organizational institutional factors and personal characteristics are linked to shaping various distractors of computerised work results in creative knowledge employees, with the purpose of pointing to the driving forces of some key ICT related and other obstacles in achieving desired results in intellectual work. This paper provides ordered probit regression results on data from an Estonian survey of creative knowledge employees doing computerised work. Our findings reveal that emotional tiredness, sleepiness, work environment issues, managerial problems and unclear work tasks appear as the most dominant distractors of work results perceived by creative knowledge employees. The intensity of perceiving the adverse effect of those factors appears to be triggered primarily by the age and gender of the employee, their sleep patterns and availability of flexible work arrangements. The findings of this paper may help to design better the principles of knowledge management in computerised work to capture the intellectual potential of creative employees more efficiently. Moreover, knowing the triggers of distractors for achieving desired creative work results by knowledge employees may point to areas where the development and use of ICT could be particularly promising.
{"title":"Distractors of Computerised Creative Knowledge Work","authors":"Aaro Hazak","doi":"10.1109/AICT47866.2019.8981767","DOIUrl":"https://doi.org/10.1109/AICT47866.2019.8981767","url":null,"abstract":"Use of advanced ICT in combination with efficient management of intellectual capital in modern computerised knowledge work is key for generating innovation to achieve socio-economic development. This paper studies how some work organizational institutional factors and personal characteristics are linked to shaping various distractors of computerised work results in creative knowledge employees, with the purpose of pointing to the driving forces of some key ICT related and other obstacles in achieving desired results in intellectual work. This paper provides ordered probit regression results on data from an Estonian survey of creative knowledge employees doing computerised work. Our findings reveal that emotional tiredness, sleepiness, work environment issues, managerial problems and unclear work tasks appear as the most dominant distractors of work results perceived by creative knowledge employees. The intensity of perceiving the adverse effect of those factors appears to be triggered primarily by the age and gender of the employee, their sleep patterns and availability of flexible work arrangements. The findings of this paper may help to design better the principles of knowledge management in computerised work to capture the intellectual potential of creative employees more efficiently. Moreover, knowing the triggers of distractors for achieving desired creative work results by knowledge employees may point to areas where the development and use of ICT could be particularly promising.","PeriodicalId":329473,"journal":{"name":"2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127190674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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