The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

The study aims to identify the students’ attitudes toward recent techniques’ use in teaching; using power point software and data show to facilitate teaching approaches as well as following the approach of lecture in giving subjects, do these techniques facilitate, increase, and tackle the difficulties of subjects, do these attitudes positive or negative?, and to what extent these techniques raise up students’ motivation.   

Autorías: Mariam Liwa Abdel Fattah, Liqaa Abdullah Ali. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2023. Artículo de Revista en Dialnet.

The researcher attempts to examine Barman model in acquiring the historical concepts among fourth-grade students at literary classrooms. To this end, the researcher held the null hypothesis, there is no significant difference between the experimental groups who was taught based on Barman model and the control group that taught based on the traditional method in acquiring the historical concepts on the post-test. To testify the effectiveness of Barman model, the researcher administered a questionnaire included (60) items on bunch of female-students who were selected from al-khamaeal preparatory school in al-hurriyah district in Baghdad. The author utilized different statistical tools to analyze the collected data.    &

Objective(s): To evaluate students’ communication skills and their academic performance; to compare between the students relative to communication skills and their academic performance in the University of Baghdad and to identify the relationship between students’ communication skills, academic performance and their socio-demographic characteristics of age, gender, grade and socioeconomic status. Methodology: A descriptive design, using the evaluation approach, is carried through the present study to evaluate colleges’ students’ communication skills and their academic performance in the University of Baghdad for the period of January 7th 2019 to August 28th 2019. A non-probability, purposive sample, of (80) university students, i

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip