The automated essay scoring (AES) has significant importance in machine grading of student essays particularly in standardized exams like the Graduate Record Examination (GRE). However, some issues in AES have remained unsolved over the past several years. The current approaches have scrutinized AES from both classification and regression perspectives. This study discusses the cutting edge architectures such as RoBERTa, XLNet, and BERT and compares their automated essay scoring performance. ASAP, a publicly accessible dataset is used for this purpose. The obtained results indicate that the natural language understanding (NLU) model proposed in this paper depicts significantly improved performance than all the other existing approaches.
Understanding learner behavior is the key to the success of any learning process. The more we know about learners, the more likely we are to personalize learning experiences and provide successful feedback. This paper presents a feedback rules model called SECA: (i) Scenario, that defines the context behavior in a microlearning environment, (ii) Event, provided by a predictive model, (iii) Condition, that evaluates the events, and (iv) Action, that provides the learner’s feedback. The proposal is achieved through a controlled experiment in which a microlearning environment is available to collect data from a ubiquitous context, and predictive analytics are applied to guide the definition of a set of feedback rules intended to support the learner’s learning process. In the end, we presented an exemplified set of feedback rules, which could be used to provide automatic recommendations and improve the learner experience. Thus, the experiment allows us to analyze the learner behavior in a ubiquitous microlearning context from a feedback perspective.
This study provides a review of solar energy in Iraq, as Iraq is one of the oil-rich countries that are considered more intelligent in the field of alternative energy for the post-oil era, especially as it is located near the solar belt, which makes the solar radiation of high intensity and brightness a period of the year. We must replace non-renewable energy resources (traditional or fossil fuels) with renewable (sustainable) energy resources. This renewable energy (solar energy) is possible, clean, unlimited and environmentally friendly, and it can be used in many applications of lighting, water heating and heating in the winter, and this Reduces the electricity needed during winter for this application. And if we talk about Mosul, the climate of Mosul It’s marked by high summer and cold temperatures .degrees Celsius in the middle of the day, and in December, January and February, temperatures range from -1 degrees Celsius to 8 degrees Celsius. As Iraq is suffering from electricity shortages during this time, so the Iraqi government and the local government of Mosul in particular must take serious decisions and steps to confront and overcome these challenges, and develop developed strategies, and programs of specialized and expert people to meet the increases in demands on electric power. Renewable energies such as solar and wind energy which could play a significant role in Iraq’s future , especially the solar energy covered in this study.
The agricultural sector is unpredictable and complicated for farmers to manage it, especially with all the immoderate challenges that condemn the development of agricultural production. Regarding Morocco, water scarcity remains the major challenge that face the sector and put at risk the irrigation based fields-that represents approximately the half of the agricultural GDP-, the nutritional needs of the Moroccan population as well as the global sustainable growth. A way to handle this issue is adopting green IT that enable farmers to establish one of the latest trends in the global smart irrigation systems which are Green Internet Of Things or G-IoT driven smart irrigation. These technologies are currently highly requested and used in the Moroccan agricultural context contributing to the economic and environmental performance. Consequently, the aim of this study is to inspect the factors that affect the farmer's intention to adopt Green IoT based irrigation systems in the Moroccan case. The study is conducted on a literature review based on studies concerning the same subject matter in an international level, and contribute to the research development by proposing a theoretical model related to farmers’ Green IoT adoption.
Detecting communities of common behaviors, interests, and interactions in social networks is essential to model a network's structure. Overlapping community detection is an NP-Hard problem. Several solutions have been proposed; however, most of these techniques are computationally expensive. We have developed a fast-hierarchical algorithm using the notion of segmentation by weighted aggregation. Experimental results on synthetic and real benchmark networks show that the proposed algorithm effectively finds communities (Clusters) with varied overlap and non-exhaustiveness structures. Our method outperforms the state-of-the-art hierarchical clustering algorithms measured by the F-measure and the computational time.
