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Publikováno v:
Applied Computer Systems, Vol 26, Iss 1, Pp 1-11 (2021)
Energy efficiency in mobile computing is really an important issue these days. Owing to the popularity and prevalence of Android operating system among the people, a great number of Android smartphone applications have been developed and proliferated
Autor:
Madara Gasparoviča-Asīte, Jurijs Kornienko, Amanda Siliņa, Vitaly Zabiniako, Oksana Ņikiforova
Publikováno v:
Applied Computer Systems, Vol 26, Iss 1, Pp 22-30 (2021)
Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification of its improvement potential. However, the application of Machine Learning methods for the
Publikováno v:
Applied Computer Systems, Vol 26, Iss 1, Pp 38-43 (2021)
Every software development company makes software development based on a specific approach. There are a number of approaches to software development, both disciplined and agile. Each approach includes a set of different activities. Sometimes, the spe
Publikováno v:
Applied Computer Systems, Vol 25, Iss 2, Pp 172-179 (2020)
The authors consider the construction of a nonlinear multiple regression model, its confidence and prediction intervals to evaluate the efforts of mobile application development in the planning phase based on the multivariate normalizing transformati
Autor:
Engr Waseem Akhtar Mufti
Publikováno v:
Applied Computer Systems, Vol 25, Iss 2, Pp 117-123 (2020)
Waseem Akhtar Mufti
Waseem Akhtar Mufti
Applications of the Internet of Things (IoT) are famously known for connecting devices via the internet. The main purpose of IoT systems (wireless or wired) is to connect devices together for data collection, buffering and data gateway. The collected
Publikováno v:
Applied Computer Systems, Vol 25, Iss 2, Pp 145-152 (2020)
Machine learning (ML) methods are nowadays widely used to automate geophysical study. Some of ML algorithms are used to solve lithological classification problems during uranium mining process. One of the key aspects of using classical ML methods is
Publikováno v:
Applied Computer Systems, Vol 25, Iss 2, Pp 77-86 (2020)
The objective of the paper is to identify predictive models in stock market prediction focusing on a scenario of the emerging markets. An exploratory analysis and conceptual modelling based on the extant literature during 1933 to 2020 have been used
Autor:
Pavlo Radiuk
Publikováno v:
Applied Computer Systems, Vol 25, Iss 1, Pp 43-50 (2020)
The achievement of high-precision segmentation in medical image analysis has been an active direction of research over the past decade. Significant success in medical imaging tasks has been feasible due to the employment of deep learning methods, inc
Publikováno v:
Applied Computer Systems, Vol 25, Iss 1, Pp 33-42 (2020)
Predicting the stock market remains a challenging task due to the numerous influencing factors such as investor sentiment, firm performance, economic factors and social media sentiments. However, the profitability and economic advantage associated wi
Publikováno v:
Applied Computer Systems, Vol 24, Iss 2, Pp 94-103 (2019)
Extracting core elements of Topological Functioning Model (TFM) from use case scenarios requires processing of both structure and natural language constructs in use case step descriptions. The processing steps are discussed in the present paper. Anal