Data analytics on blockchains
Published in: IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
May 01, 2023
In recent years, blockchains have been exploited in areas way beyond finance, enabling numerous innovative usage scenarios and applications. However, the extension of the existing systems and applications in order to support data persistence on a blockchain is time-consuming. Therefore, this paper proposes a model-driven based approach leveraging smart contracts with the goal to automate data persistence on blockchains. The approach is evaluated in data analytics use cases. According to our res...
On persisting EMF data using blockchains
Published in: International Conference on Internet of Things: Systems, Management and Security (IOTSMS)
Nov 29, 2022
In recent years, blockchain technology in synergy with smart contracts has opened new horizons within almost any field from entertainment to healthcare. However, in order to enable innovative usage scenarios, significant efforts are needed to adapt the existing systems and solutions, so the full potential of blockchain-based tools can be leveraged. In this paper, we propose a model-driven framework which provides automated persistence of domain-specific data within Ethereum blockchain platform,...
Multiple Object Tracking in Robotic Applications: Trends and Challenges
Published in: Applied Sciences Journal
Sep 20, 2022
The recent advancement in autonomous robotics is directed toward designing a reliable system that can detect and track multiple objects in the surrounding environment for navigation and guidance purposes. This paper aims to survey the recent development in this area and present the latest trends that tackle the challenges of multiple object tracking, such as heavy occlusion, dynamic background, and illumination changes. Our research includes Multiple Object Tracking (MOT) methods incorpora...
Problematic Social Media Use and Academic Performance among University Students: An Evaluation from The Middle East
Published in: Open Nursing Journal
Aug 26, 2022
Optimum Design Configuration of Dapped-End Beam Under Dynamic Loading Using TOPSIS Method
Published in: 8th World Congress on Mechanical, Chemical, and Material Engineering
Jul 19, 2022
Base station anomaly prediction leveraging model-driven framework for classification in Neo4j
Published in: International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom)
Jul 12, 2022
Machine learning is one of key-enablers in case of novel usage scenarios and adaptive behavior within next generation mobile networks. In this paper, it is examined how model-driven approach can be adopted to automatize machine learning tasks aiming mobile network data analysis. The framework is evaluated on classification task for purpose of base station anomaly detection relying on Neo4j graph database. According to the experiments performed on publicly available dataset, such approach shows ...
Model-Driven Approach to Fading-Aware Wireless Network Planning Leveraging Multiobjective Optimization and Deep Learning
Published in: Mathematical Problems in Engineering
Apr 08, 2022
Dragana Krstic
Nenad Petrovic
Issam Al-Azzoni
Efficient resource planning is recognized as one of the key enablers making the large-scale deployment of next-generation wireless networks available for mass usage. Modelling, planning, and software simulation tools reduce both the time needed and costs of their tuning and realization. In this paper, we propose a model-driven framework for proactive network planning relying on synergy of deep learning and multiobjective optimization. The predictions about service demand and energy consumption ...