AbstractThis paper presents a developed higher education quality assessment model (HEQAM) that can be applied for enhancement of university services. This is because there no universal unified standard used to assess the criteria institutes. The analytical hierarchy process identify priority and weights their alternatives. has 3 levels with 8 main objectives 53 It included e-services criteria, which one recent modern components, in addition new sub-criteria enhancing model. produces...

In higher education, predicting the academic performance of students is associated with formulating optimal educational policies that vehemently impact economic and financial development. online platforms, captured clickstream information can be exploited in ascertaining their performance. current study, time-series sequential classification problem students’ prediction explored by deploying a deep long short-term memory (LSTM) model using freely accessible Open University Learning Analytics...

We argue that citations, as they have different reasons and functions, should not all be treated in the same way. Using large, annotated dataset of about 10K citation contexts by human experts, extracted from Association for Computational Linguistics repository, we present a deep learning–based context classification architecture. Unlike existing state-of-the-art feature-based models, our proposed convolutional neural network (CNN) with fastText-based pre-trained embedding vectors uses only...

Based on Petri net (PN) models of automated manufacturing systems, this paper proposes a deadlock prevention method to obtain maximally permissive (optimal) supervisor while minimizing its structure. The optimal can be achieved by forbidding all first-met bad markings (FBMs) and permitting legal in PN model. An FBM obtained via single transition's firing at marking is or that inevitably evolves into deadlock. A lexicographic multiobjective integer programming problem with multiple objectives...

The integration of innovative data mining and decision-making techniques in the context higher education is a bold initiative towards enhanced performance. Predictive descriptive analytics add interesting insights for significant aspects education. purpose this article to summarize novel approach adoption artificial intelligence (AI) forecasting academic added value applying AI advanced decision making realization that scientific standard problems academia, like enhancement performance...

Traffic flow monitoring plays a crucial role in Intelligent Transportation Systems (ITS) by dealing with real-time data on traffic situations and allowing effectual management optimization. A typical approach used for frequently depends collection analysis of the through manual process that is not only resource-intensive, but also time-consuming process. Recently, Artificial Intelligence (AI) approaches like ensemble learning demonstrate promising outcomes numerous ITS applications. With...

Wireless Sensor Networks (WSNs) play a major part in numerous applications such as smart agriculture, healthcare, and environmental monitoring. Safeguarding protected communication this network is dominant. Securing data transmission WSNs needs strong key distribution device to defend against malicious attacks well illegal access. Traditional techniques like pre-shared or centralized management are often unreasonable owing resource limitations, particularly large-scale sensor systems. To...

Cloud computing recently emerged as a new paradigm that aims to deploy services via Internet. Under hybrid cloud environment, bursting is technique combines local (organizations or in-house) resources with public resources, these are leased based on pay-per-use basis. It used process the overload work within resource accelerate execution time of distributed applications respect required level QoS, also achieve efficient use private resources. When applied, important issues determining how...

Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to complex anatomical structures diverse disease manifestations. The aim of this study is investigate use deep learning techniques, generative adversarial networks (GANs), combination with convolutional neural (CNNs), for classification pathologies medical imaging data. dataset composed images obtained through computed tomography (CT) scans, covering...

The performance of an optical switch that handles contention resolution using a fiber delay line (FDL) is modeled and evaluated. We propose simple buffer contains only single FDL for resolution. analytical model derived the based on this verified simulations. can be utilized with both packet burst switching schemes to characterize switches augmented architecture.

Graph is a fundamental data structure that captures relationships between different entities. In practice, graphs are widely used for modeling complicated in application domains such as social networks, protein transportation bibliographical knowledge bases and many more. Currently, with millions billions of nodes edges have become very common. principle, graph analytics an important big discovery technique. Therefore, the increasing abundance large graphs, designing scalable systems...

We investigated the scientific research dissemination by analyzing publications and citation data, implying that not all citations are significantly important. Therefore, as alluded to existing state-of-the-art models employ feature-based techniques measure scholarly between multiple entities, our model implements convolutional neural network (CNN) with fastText-based pre-trained embedding vectors, utilizes only context its input distinguish important non-important citations. Moreover, we...