Article concerning activity detection
We are pleased to inform you that article “Ensemble of RNN Classifiers for Activity Detection Using a Smartphone and Supporting Nodes” has been
published in Sensors and is available online:
We are pleased to inform you that article “Ensemble of RNN Classifiers for Activity Detection Using a Smartphone and Supporting Nodes” has been
published in Sensors and is available online:
Unlocking new insights from complex, vast, diverse, and massive quantities of data to accelerate digital transformation, innovation, and social sustainability is the primary objective of Big Data Analytics. It uses a palette of advanced techniques and approaches from emerging fields such as Data Mining, Machine Learning and Deep Learning for extracting valuable information. Various tools support and optimize knowledge discovery engineering.
In such a context, the short-term training aims to broaden the students’ interest in data-driven projects as a novel paradigm in Industry 4.0 and Society 5.0, by answering a series of questions:
What acts in the Big Data value-chain paradigm?
What are the key technologies behind Big Data Analytics (BDA)?
What tools and software enable meaningful insight from big data?
What tools and software can be used for BDA with no or minimal coding skills?
Besides these questions, the training provides practical guides to particular tools that support and automate end-to-end data analytics, from data collection, cleansing, and transformation through model building, evaluation, and tuning, to visualization and communication of results.
The training is competences oriented utilizing learning-by-doing and case-based methods. The course is offered to computer science students from University of Nis (Serbia), University of Library Studies and Information Technologies (Bulgaria) and University of Bielsko-Biala (Poland).
All information about this event can be found in 2022_Scientific Study_iBigWorld.
The dataset was provided for classification of activity using sensors placed in four places: waist, chest, arm and leg.
The dataset contains eight classes:
The repository can be found in: https://github.com/drOneMB/activity-detection
Nowadays, the Big Data can be found in most of modern organisation and companies. Its utilisation gives an advantage over competitors and allows to adapt to new trends. There is no surprise that established organizations, to follow a trend, are shifting to Node.js platforms from their legacy systems. Node.js is used by companies like PayPal, Yahoo, eBay, Netflix.
So, what is NodeJS?
Its real time web application using push technology over web sockets. It allows two-way connections (client and server). Advantage of Node.js is JavaScript language that makes easier to build both back-end and front-end using the same code. Node.js uses non-blocking, event driven I/O to offer efficiency and remain lightweight in terms of in-memory usage. It is especially effective processing multiple requests (with not high computing complexity) that makes it perfect tool for ingestion phase of Big Data pipelines.
You can find more info at article:
https://www.projectpro.io/article/10-reasons-why-you-should-use-nodejs/129
Today on University of Bielsko-Biala our graduate defend its MSc thesis.
The following publication ‘Sentiment and stock market analysis of listed companies using Big Data tools’ introduces the topic of Big Data with sentiment analysis. Big Data is having an increasingly important role in the modern world over time. With the help of huge data sets, many companies are able to predict customer demand and create personalised offers for them, or even react in advance to possible production failures. However, working with Big Data brings many challenges. Processing, storing and analysing huge sets of information requires special technologies to handle huge data records, as ordinary tools would not be able to handle such a amount of data.
One extensive source of Big Data is social networks. Users of such applications leave a lot of information about themselves, which is stored in extensive data stores, which correctly analysed, helps to present relevant offers, advertisements, information specifically personalised and designed exactly for the user.
In this study, research was carried out analysing the impact of Twitter users’ online statements on the share prices of selected companies. The research work was carried out over a period of one month. Conclusions were also presented for each company analysed.
However, the result of the research does not indicate a direct connection between the sentiment of the users’ statements and the increase or decrease in the value of the shares of the companies in question on the stock exchange. With such a complex process as stock market asset valuation, it should also be analysed with other factors, such as company valuations or the current global economic situation, which sets further directions for future work.
contact: lukasz1081@wp.pl
Multiplier Event E1 has been an integral part of the iBIGworld project’s dissemination and exploitation of results activities. Therefore, we’ve hosted successive event E1 as the Transnational Conference “State-of-the-Art on Big Data: challenges, competencies, and requirements” at 07.06.2022, Hotel “Na Bloniach”, Bielsko-Biala, Poland
The aim of the event was to communicate the activities and results of the project within a wider audience consisting of stakeholders and members of target groups. As BigData is cutting edge technology issues that affect everyone, the event also aimed to elaborate on all new perspectives and challenges in the sector that are identified by the European, academic, vocational and expert communities. The speakers were carefully selected in order to encompass an integrated view of all sectors, showing evidence of the interaction between them.
For the event we’ve managed to gather a total number of participants over 60, locals over 50 and internationals over 5. We’ve had local participants mainly from local SMEs specializing in the field of Big Data and participants from Ukrainian HEIs who were visiting UBB.
For the event we’ve had the following objectives:
The targeted public was made up of the following categories:
Dean of the Faculty of Mechanical Engineering and Computer Science for Education dr Dariusz Więcek has started the event. He has greeted the event participants on behalf of UBB authorities. The head of the department of Computer Science and Automatics prof. dr hab. Mikolaj Karpiński presented the academic and research facilities of the department. Dr Marcin Bernaś has introduced the participants to the world of Big Data, presented the basic notions and challenges considered. The local coordinator of the project prof. dr hab Vasyl Martsenyuk presented the project’s general objectives, target groups, and outcomes of the stage O1 focusing on survey analysis. Then dr Marcin Bernas has presented the outcomes of the stage O2 joining the Data Science competencies with the topics of the Big Data course oriented to use case study. Prof. Georgi Dimitrov from ULSIT (Bulgaria) has reported remotely on the expierience when developing Big Data framework implemented as a eLearning platform which includes 12 sequential topics strengthened with various learning activities and use cases from real world. Then prof. dr hab. Vasyl Martsenyuk presented the approach when developing the teacher and business guidelins for Big Data training course as the main outcomes for the stage O4: Piloting. Dr Marcin Bernaś offered the platform for Smart BigData Job Hub (https://ibigworld.ath.edu.pl/index.php/en/). It will enable to dissemination, mainstreaming, and sustaining the most relevant results of the project. By delivering, disseminating and fully operating the Smart BigData Job Hub platform, iBIGworld facilitates access to information which is relevant to Big Data employability opportunities, creates closer links between business and community, eases transition to workforce and contributes to the creation of a sustainable learning community that identifies Big Data cutting-edge industrial needs enabling the reforming of academic curricula.
The students team which participated in C3 has also presented the project that was implemented as a result of C3 and devoted to developing Orange+Kaggle+Python platform for Big Data in a real case.
Expert Panels were devoted to presenting some good practices in Big Data which could be also involved as use cases from real world to the project. Da Vinci firm presented two IT solutions based on Big Data. Da Vinci medicine caused the real interest and discussion among the participants. The company Precisely focused the attention on microservices vs monolith architecture when developing Big Data solutions. They presented their own paradigmat when developing effective code for microservices using functional programming. Record SI has paid the attention of the participants by the presentation its worth expierience when developing Big Data solutions for local governments in Poland during the decades of years. Currently they offer platform which is fully web-integrated with great facilities for data extraction and visualising.
On 7- 8 June 2022, the event Perspektywy -Woman in Tech Summit took place in Warsaw. Due to the nomination to the Top 100 Women in AI in Poland, Aleksandra Kłos-Witkowska, PhD, was invited to participate in this event. Apart from workshops and interesting lectures, a seminar was organised, where Aleksandra Kłos-Witkowska gave a presentation
“Innovations for Big Data in a Real World” (iBigWorld) Project_(2020-1-PL01-KA203-082197) ”
On May 21, 2022 Transnational Meeting M3 was held in Nis (Serbia). The Meeting was conducted on the basis of Science Technology Park Nis https://ntp.rs/en/
The third project meeting was organized by University of Niš (Uni) in Serbia. The purpose of this meeting was to track the progress of the project, to discuss the experience from the training activities C1, C2, and C3. Also, feedback on the ongoing activities for the development of the Foresight Study (03) and the Guide for Instructors (04) was considered.
The participants from UNi, University of Bielsko-Biala (UBB), and University of Library Studies and Information Technology (ULSIT) took an active part at the meeting. The team from Taras Shevchenko National University of Kyiv (TSNUK) participated at M3 remotely.
All details can be found in ReportM3
During the period May 16 – May 20, 2022 Student’s Training C3 was held. The event was hosted by the University of Nis (UNi) in Serbia.
The third training activity involved the organization of the Big Data course offered to computer science students in UNi. The agenda of the event can be found through the link https://docs.google.com/document/d/174j69vz0DD5EIptav-d7rT0JLHMji-Ag/edit?usp=sharing&ouid=101046534126028994548&rtpof=true&sd=true
University of Bielsko-Biala (UBB), University of Library Studies and Information Technologies (ULSIT), UNi have sent four students each in the ICT field. The instructors of the course were trainers from all universities. The training was conducted according to the already established methodologies and teaching materials. The trainers were representatives of UNi teachers. Teachers from ULSIT and
UBB attended the classes and assisted in their conduct.
The format was tailored to the academic classes at the university.
Craft topics was related to the goals and objectives of the project:
– Database based on an advanced reference in the case of BigData (covering 01 – A1.1. Data collection and A1.2. Analysis)
– How to analyze requirements with a Big Data and how to find the best solution to the problem (covering 02 and 03)
– How to best prepare Big Data professionals in the Data Lake ecosystem (O3 and O4 outputs)
– How to help managers find the best way using their Big Data resources
Students from UBB, ULSIT, and UNi joined the activity. Certification of attendance was provided to all the participants.
All details can be found in ReportC3