Knowing that language is often used as a classifier of human intelligence and the development of systems that understand human language remains a challenge all the time (Kryeziu & Shehu, 2022). Natural Language Processing is a very active field of study, where transformers have a key role. Transformers function based on neural networks and they are increasingly showing promising results. One of the first major contributions to transfer learning in Natural Language Processing was the use of pre-trained word embeddings in (...) 2010 (Joseph, Lev, & Yoshua, 2010). Pre-trained models like ELMo (Matthew, et al., 2018) and BERT (Delvin, et al., 2019) are trained on large corpora of unlabeled text and as a result learning from text representations has achieved good performance on many of the underlying tasks on datasets from different domains. Pre-training in the language model has proven that there has been an improvement in some aspects of natural language processing, based on the paper (Dai & Le, 2015). In present paper, we will pre-train BERT on the task of Masked Language Modeling (MLM) with the Albanian language dataset (alb_dataset) that we have created for this purpose (Kryeziu et al., 2022). We will compare two approaches: training of BERT using the available OSCAR dataset and using our alb_dataset that we have collected. The paper shows some discrepancies during training, especially while evaluating the performance of the model. (shrink)

Aquaculture plays a significant role in both economic development and food production. Maintaining an ecological environment with good water quality is essential to ensure the production efficiency and quality of aquaculture. Effective management of water quality can prevent abnormal conditions and contribute significantly to food security. Detecting anomalies in the aquaculture environment is crucial to ensure that the environment is maintained correctly to meet healthy and proper requirements for fish farming. This article focuses on the use of deep learning techniques (...) to detect anomalies in water quality data in the aquaculture environment. Four deep learning anomaly detection techniques, including Autoencoder, Variational Autoencoder, Long-Short Term Memory Autoencoder, and Spectral-Residual Convolutional Neural Network, were analysed using multiple real-world sensor datasets collected from IoT aquaculture systems. Extensive experiments were conducted for temperature, dissolved oxygen, and pH parameters, and the evaluation analysis revealed that the Long-Short Term Memory Autoencoder anomaly detection method showed promising results in detecting anomalies for the temperature and oxygen datasets, while the Spectral-Residual Convolutional Neural Network demonstrated the best performance on the pH datasets. (shrink)

Peer Assessment is a potentially promising pedagogical approach for enhancing the e-learning and supporting student self-regulated learning. The purpose of this paper is by reviewing the research on current trends on the use of ICT in Education, in particular on peer assessment in e-learning, to propose a new peer assessment methodology using the social media platforms in the digital environment. We conclude that a blended approach is more suitable as it is not possible to have a fully automatic peer assessment (...) methodology. The proposed online model needs to be subject of particular careful monitoring and evaluation from teachers. (shrink)

In the last period, especially during the COVID-19 pandemics, individuals as well as institutions globally and in North Macedonia particularly, have failed to correctly respond to the new challenges related to cyber security, online attacks, and fake news. Being that in a state of isolation and quarantine most governmental institutions have heavily relied on online tools to communicate among each other and with the public, it is quite evident that they have not been well prepared to adopt new technologies. This (...) paper aims to bridge together the needs for technology during the COVID-19 pandemics versus the security challenges that many forget to mention. The primary focus of this paper is to elaborate on the security challenges associated with technology with several examples from incidents around the world and from North Macedonia. As such, it represents a perspective paper with focus on current and emerging advances on IT security for running the “new normal” world. (shrink)