Ahmed Ibrahim Alzahrani's research while affiliated with King Saud University and other places

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Publications (14)

Figure 1. The Study Research Model.
Cont.
Construct Reliability.
Convergent Validity Measurement Results.
+2 Fornell-Larcker Criterion.
The Impact of Social Media Shared Health Content on Protective Behavior against COVID-19
Article
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  • Jan 2023
The use of social media has increased during the COVID-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in society and may influence public protective behavior against the COVID-19 pandemic. The purpose of this study is to identify the factors affecting public protective behavior w...
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A non-invasive machine learning mechanism for early disease recognition on Twitter: The case of anemia
Article
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  • Nov 2022
Social media sites, such as Twitter, provide the means for users to share their stories, feelings, and health conditions during the disease course. Anemia, the most common type of blood disorder, is recognized as a major public health problem all over the world. Yet very few studies have explored the potential of recognizing anemia from online post...
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IS Diffusion: A Dynamic Control and Stakeholder Perspective
Article
  • Nov 2021
Our research uses a novel perspective of control balancing and stakeholder orientation to explore an information system (IS) phenomenon called enterprise IS diffusion. Employing a case-based, grounded theory approach, we analyse four large-scale IS implementation projects in a Canadian government organization. Our findings offer a synergistic appro...
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End users' resistance behaviour paradigm in pre-deployment stage of ERP systems: evidence from Bangladeshi manufacturing industry
Article
  • Aug 2021
Purpose This study proposes a research model to identify the relevant constructs of employee resistance and symbolic adoption in pre-implementation stage of enterprise resource planning systems in manufacturing industries, drawing suitable support from the existing body of literature. The proposed model is a combination of the status quo bias theor...
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Fig. 4 Performance of wind variable selection methods. (a) Comparison...
Descriptive statistics of the training and testing sets of wind speed.
Multistep short-term wind speed prediction using nonlinear auto-regressive neural network with exogenous variable selection
Article
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  • Nov 2020
Precise wind speed prediction is a key factor in many energy applications, especially when wind energy is integrated with power grids. However, because of the intermittent and nonsta-tionary nature of wind speed, modeling and predicting it is a challenge. In addition, using uncorre-lated multivariate variables as exogenous input variables often adv...
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Customer relationship management systems (CRMS) in the healthcare environment: A systematic literature review
Article
  • Apr 2020
Customer relationship management (CRM) is an innovative technology that seeks to improve customer satisfaction, loyalty, and profitability by acquiring, developing, and maintaining effective customer relationships and interactions with stakeholders. Numerous researches on CRM have made significant progress in several areas such as telecommunication...
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Fig. 2 Two steps hybrid correction concept.
Fig. 3 Methodology flowchart.
Fig. 4 (a) Distance from log-point to defect, (b) o'clock orientation.
Fig. 5 Sample of the studied dataset.
MSE and OEE for the KNN, SVR, and Hybrid calibration models.
Two steps hybrid calibration algorithm of support vector regression and K-nearest neighbors
Article
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  • Jan 2020
Errors in the measurements of pipeline nondestructive tools may lead to faulty decisions causing economic and environmental loss, or system failures. Calibration models are an effective tool that is used to enhance the quality of corrosion measurements affected by inline inspection tools sizing accuracy. Parametric calibration models are limited to...
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FIGURE 1. Network architecture of the proposed solution and its components.
FIGURE 2. Authentication procedure.
FIGURE 3. Authentication process between the two devices of different...
FIGURE 4. Sequence of messages exchanged for symmetric key...
+5 FIGURE 5. Attack models.
Resource Efficient Authentication and Session Key Establishment Procedure for Low-Resource IoT Devices
Article
Full-text available
  • Nov 2019
The Internet of Things (IoT) can includes many resource-constrained devices, with most usually needing to securely communicate with their network managers, which are more resource-rich devices in the IoT network. We propose a resource-efficient security scheme that includes authentication of devices with their network managers, authentication betwe...
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Figure 2. Privacy categories in wireless sensor networks.
Figure 7. Flow chart of our proposed model.
Network Parameters.
Comparison of packet delivery ratio after equal intervals.
+1 Comparison of safety period after equal intervals.
An Enhanced Source Location Privacy based on Data Dissemination in Wireless Sensor Networks (DeLP)
Article
Full-text available
  • May 2019
Wireless Sensor Network is a network of large number of nodes with limited power and computational capabilities. It has the potential of event monitoring in unattended locations where there is a chance of unauthorized access. The work that is presented here identifies and addresses the problem of eavesdropping in the exposed environment of the sens...
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Investigating the Schedulability of Periodic Real-Time Tasks in Virtualized Cloud Environment
Article
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  • Feb 2019
In this study, we developed a computing architecture and algorithms for supporting soft realtime task scheduling in a cloud computing environment through the dynamic provisioning of virtual machines. The architecture integrated three modified soft real-time task scheduling algorithms, namely, Earliest Deadline First (EDF), Earliest Deadline until Z...
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Figure 1: Proposed recurrent hybrid neural network model with...
Table 1 Analysis of optimal scaling factor in time-series filter
Figure 5: Error histogram for proposed recurrent hybrid model. 
Figure 6: Error histogram for normal recurrent model. 
Analysis of recurrent neural networks for henon simulated time-series forecasting
Article
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  • Apr 2018
Forecasting of chaotic time-series has increasingly become a challenging subject. Non-linear models such as recurrent neural networks have been successfully applied in generating short term forecasts, but perform poorly in long term forecasts due to the vanishing gradient problem when the forecasting period increases. This study proposes a robust m...
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TABLE 1 . Loading and Cross-Loading of Items 
TABLE 2 . Constructs, Items, and Confirmatory Factor Analysis Results 
Use of E-Learning by University Students in Malaysian Higher Educational Institutions: A Case in Universiti Teknologi Malaysia
Article
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  • Feb 2018
This research examines university students’ intention to utilize e-learning. In this research, we apply and use the theory of technology acceptance model (TAM). We employ structural equation modelling (SEM) approach with a SmartPLS software to investigate students’ adoption process. Findings indicates that the content of e-learning and self-efficac...
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Photodynamic therapy in the treatment of symptomatic oral lichen planus: A systematic review
Article
  • Dec 2017
Background: The aim of this systematic review was to assess the efficacy of photodynamic therapy (PDT) in the treatment of symptomatic oral lichen planus (OLP). Methods: This systematic review aimed to address the following focused question: “Is PDT effective in the treatment of symptomatic OLP?” Indexed databases; MEDLINE, EMBASE and CENTRAL were...
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Citations

... This gives way to a whole new avenue of future research agendas. A majority of existing studies on infodemics and false information related to social media and the pandemic have presupposed the frequency of usage and exposure as an antecedent to fear [33][34][35]. The originality of this study stems from the notion that social media, when understood correctly, need not be the driver of cognitive impairment but rather serves as a platform for open dialogue, wherein adverse effects of exposure to misinformation can be countered by discussion and plurality of opinion. ...
Reference: Empirical Study on Social Media Exposure and Fear as Drivers of Anxiety and Depression during the COVID-19 Pandemic
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... is can reduce the enterprise's risk in financial control and continuously improve the financial management system of the enterprise to promote its overall development [7]. ...
Reference: A Deep Learning Model for ERP Enterprise Financial Management System
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... Senjyu et al. [6] suggested utilizing RNN to anticipate wind speed and use that information to prognosticate the output supremacy of wind generators. According to [7], the author employs an inter short-term wind speed projection technique that makes use of multivariate exogenous input factors. Because wind speed displays high intermodulation distortion and features typically, to improve forecast performance [8]. ...
Reference: A New ANN Technique for Short-Term Wind Speed Forecasting Based on SCADA System Data in Turkey
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... The greater the durability of competitive advantage, the more challenging it is for rivals to nullify it. Ref. [50] observed that a strong relationship with customers is one of the core competencies of an organization and a potential source of competitive advantage. Nearly all organizations exhibit a strong correlation between a firm's competitive edge and its performance, and these advantages contribute to the success of the business. ...
Reference: Effect of Sustainable Supply Chain Management and Customer Relationship Management on Organizational Performance in the Context of the Egyptian Textile Industry
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... On the other hand, handwritten text recognition technologies became an active area in pattern recognition and computer vision by using different Machine Learning (ML) algorithms, such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN) [4]. Nevertheless, models that use Convolutional Neural Networks (CNNs) have achieved important results in different handwritten datasets for different languages [27,42,50,61]. Indeed, the CNNs automatically detect and extract the distinctive and representative features of images, surpassing the traditional ML algorithms that need to manually extract the image features [23,56]. ...
Reference: Handwritten computer science words vocabulary recognition using concatenated convolutional neural networks
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... • Scalable mutual authentication and key establishment protocol [48] check the reliability of authentication and cryptographic material creation and management. For the large-scale Internet security-sensitive protocols and applications, it uses an industrial-strength automated analysis tool. ...
Reference: A Survey on Next Generation IoT Networks from Green IoT Perspective
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... The experimental results validated that the established technique performed accurately in logical way and offered superior level with the help of BAN (Burrows-Abadi-Needham) logic. Sahil Garg, et.al (2020) presented a lightweight authentication and key agreement protocol for the IoT environment on the basis of a hierarchical approach which offered robustness and security [17]. This protocol was depending upon lightweight operations namely EEC (elliptic curve cryptography), hash functions and XOR operations. ...
Reference: International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING Symmetric and Asymmetric Encryption Schemes for Internet of Things: A Survey
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... In the second case is a key distribution protocol in a sensor network using sensor network encryption protocol (SNEP) for securing messages. [24] presented an enhanced source location privacy based on data dissemination in WSN. The study identified and addressed the issue of eavesdropping in the exposed environment of the sensor network, which rendered it vulnerable for the adversary or attacker to trace the packets to find the originator source node, hence compromising the contextual privacy. ...
Reference: Comparative Review of Routing Protocols for Energy-Efficient and Security in Wireless Sensor Network
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... ANOVA is an effective analysis technique, since it accepts more than two groups to find the significant differences, and because we have 4 groups, the ANOVA test is selected. The procedures of this analysis are adopted from [37][38][39][40][41][42][43][44]. ...
Reference: Hyperparameter Optimization of Evolving Spiking Neural Network for Time-Series Classification
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... Among all machine learning techniques, the most popular nowadays are deep learning techniques, such as DNN, CNN, LSTM, Recurrent Neural Network (RNN) [29], and hybrid approaches, such as neuro-fuzzy [30], fuzzy SVM [31], Hybrid Heterogeneous SVM (H-SVM) [32], and Fuzzy-Weighted K-Nearest Neighbors (FwkNN) [33]. These methods have been widely implemented in a variety of application domains exhibiting satisfactory results in the literature. ...
Reference: Optimizing deep neuro-fuzzy classifier with a novel evolutionary arithmetic optimization algorithm
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