Challenges and opportunities in ESG investments

Accepted manuscrip

Challenges and Opportunities in Applying Semantics to Improve Access Control in the Field of Internet of Things

The increased number of IoT devices results in continuously generated massive amounts of raw data. Parts of this data are private and highly sensitive as they reflect owner’s behavior, obligations, habits, and preferences. In this paper, we point out that flexible and comprehensive access control policies are “a must” in the IoT domain. The Semantic Web technologies can address many of the challenges that the IoT access control is facing with today. Therefore, we analyze the current state of the art in this area and identify the challenges and opportunities for improved access control in a semantically enriched IoT environment. Applying semantics to IoT access control opens a lot of opportunities, such as semantic inference and reasoning, easy data sharing, data trading, new approaches to authentication, security policies based on a natural language and enhances the interoperability using a common ontology

Company classification using zero-shot learning

In recent years, natural language processing (NLP) has become increasingly important in a variety of business applications, including sentiment analysis, text classification, and named entity recognition. In this paper, we propose an approach for company classification using NLP and zero-shot learning. Our method utilizes pre-trained transformer models to extract features from company descriptions, and then applies zero-shot learning to classify companies into relevant categories without the need for specific training data for each category. We evaluate our approach on publicly available datasets of textual descriptions of companies, and demonstrate that it can streamline the process of company classification, thereby reducing the time and resources required in traditional approaches such as the Global Industry Classification Standard (GICS). The results show that this method has potential for automation of company classification, making it a promising avenue for future research in this area.Comment: 6 pages, 1 figure, 4 tables, conference paper, to be published in the 20th International Conference on Informatics and Information Technologies (CIIT 2023

Network Simulator Tools and GPU Parallel Systems

In this paper we discuss the possibilities for parallel implementations of network simulators. Specifically we investigate the options for porting parts of the simulator on GPU in order to utilize its resources and obtain faster simulations. We discuss few issues which are unsuitable for the GPU architecture, and we propose a possible work around for each of them. We introduce a design of parallel module that interconnects with a network simulator, while maintaining transparency in aspect of the simulation modeler

The Potential of the Sharing Economy in a Developing Country: The Case of North Macedonia

The growth of the sharing economy is important for developing countries because it creates value, economic growth, technological innovation, environmental sustainability, and social inclusion. Macedonian citizens have a long tradition of sharing things between friends, relatives, and neighbours. However, the new concept of sharing economy that enables strangers globally to share goods and services is still not developed and used by the Macedonian citizens. The goal of this study is by empirical analysis to give the state and potential of the usage of sharing economy by Macedonian citizens from the perspectives of providers and consumers. The results of the observational study and survey address future actions to boost the development of the sharing economy