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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Aljaidi, Mohammad
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Computer Science & IT Electrical & Electronics Engineering

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Arabic fake news detection using hybrid contextual features Turki, Hussain Mohammed; Daoud, Essam Al; Samara, Ghassan; Alazaidah, Raed; Qasem, Mais Haj; Aljaidi, Mohammad; Abuowaida, Suhaila; Alshdaifat, Nawaf
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp836-845

Abstract

Technology has advanced and social media users have grown dramatically in the last decade. Because social media makes information easily accessible, some people or organizations distribute false news for political or commercial gain. This news may influence elections and attitudes. Even though English fake news is widely detected and limited, Arabic fake news is hard to recognize owing to a lack of study and data collection. Wara Arabic bidirectional encoder representations from transformers (WaraBERT), a hybrid feature extraction approach, combines word level tokenization with two Arabic bidirectional encoder representations from transformers (AraBERT) variants to provide varied features. The study also discusses eliminating stopwords, punctuations, and tanween markings from Arabic data. This study employed two datasets. The first, Arabic fake news dataset (AFND), has 606,912 records. Second dataset Arabic news (AraNews) has 123,219 entries. WaraBERT-V1 obtained 93.83% AFND accuracy using the bidirectional long short-term memory (BiLSTM) model. However, the WaraBERT-V2 technique obtained 81.25%, improving detection accuracy above previous researchers for the AraNews dataset. These findings show that WaraBERT outperforms word list techniques (WLT), term frequency-inverse document frequency (TF-IDF), and AraBERT on both datasets.
Multi-attribute based optimal location and sizing of solar power plant in radial distribution system Kumar, Ramesh; Singh, Digambar; Aljaidi, Mohammad; Singla, Manish Kumar; Tripathi, Shashank
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9627

Abstract

Advancements in renewable energy sources (RES) have significantly increased power generation and reduced emissions. Optimally integrating RES into distribution systems can minimize power losses, emissions, and enhance voltage profile and stability. Therefore, determining the optimal location and size of RES is crucial for their effective integration. This paper presents a novel approach for identifying the optimal location and size of a solar power plant (SPP) in a distribution system, considering system power losses, voltage profile, voltage stability, and emissions simultaneously. A simple yet effective methodology combining repeated load flow and fuzzy systems is proposed. Repeated load flow is used to calculate the relevant attributes, while fuzzy decision-making is employed to determine the optimal solution. The effectiveness of the proposed method is demonstrated through its application to the IEEE-33 bus system. The results illustrate that integrating a SPP at the optimal location and size can significantly reduce power losses and emissions while improving voltage profile and stability.
Bilateral transactions impact voltage stability and nodal pricing in power networks Wakte, Ganesh; Kumar, Mukesh; Aljaidi, Mohammad; Kumar, Ramesh; Singla, Manish Kumar
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9537

Abstract

This study investigates the impact of bilateral transactions on voltage stability and nodal pricing in the Indian power grid using a modified IEEE 30-bus system. A high voltage direct current (HVDC) link is integrated into the network to enhance control and system flexibility. Two advanced transmission pricing mechanisms— megawatt (MW)-Mile and megavolt-ampere (MVA)-Mile—are employed to allocate costs based on power flow magnitude and distance. The analysis incorporates hybrid AC-DC optimal power flow (OPF) modeling under various transaction levels. Simulation results show that a 100 MW bilateral transaction reduces the voltage at the receiving bus (bus 28) by 2% (from 1.05 to 1.03 p.u.) and increases the nodal price by 6.25% (from ₹4.80 to ₹5.10/kWh). The use of HVDC technology reduces total generation cost by approximately 8.2% (from ₹85 lakhs to ₹78 lakhs) and decreases real power loss from 70 MW to 50 MW. These findings confirm that bilateral transactions influence voltage profiles and market pricing. Moreover, MW-Mile and MVA-Mile methods demonstrate effective cost allocation capabilities. The proposed approach offers a practical framework for improving grid reliability and economic transparency in evolving power markets.
Co-Authors Abuowaida, Suhaila Alazaidah, Raed Alshdaifat, Nawaf Daoud, Essam Al Kumar, Mukesh Kumar, Ramesh Qasem, Mais Haj Samara, Ghassan Singh, Digambar Singla, Manish Kumar Tripathi, Shashank Turki, Hussain Mohammed Wakte, Ganesh