Article
Mathematics, Interdisciplinary Applications
Li Huang, Chunming Ye, Jie Gao, Po-Chou Shih, Franley Mngumi, Xun Mei
Summary: This paper investigates a special scheduling problem for nurse staff under hierarchical management, proposing a solution and conducting experiments to validate it. The results show that hybrid algorithms outperform single algorithms in terms of generational distance and spacing of Pareto solutions, especially in the case of relative fair rostering objective.
Article
Engineering, Civil
Asad Ali, Farhan Aadil, Muhammad Fahad Khan, Muazzam Maqsood, Sangsoon Lim
Summary: Vehicular ad-hoc networks (VANETs) pose challenges for robust and scalable communication. Existing clustering techniques generate excessive clusters, leading to resource consumption and increased communication overhead. To address this, a novel clustering algorithm based on the Harris Hawks Optimization algorithm (HHOCNET) is proposed. Simulations show that HHOCNET outperforms state-of-the-art schemes in optimizing the multi-objective clustering problem in VANETs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Jingjing Guo, Huamin Gao, Zhiquan Liu, Feiran Huang, Junwei Zhang, Xinghua Li, Jianfeng Ma
Summary: This paper proposes an intelligent clustering routing approach (ICRA) for UAV ad hoc networks, which achieves efficient clustering and routing in UAV ad hoc networks and outperforms existing schemes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jia Cai, Tianhua Luo, Guanglong Xu, Yi Tang
Summary: Biologically inspired computing is a method that uses elegantly modeled techniques motivated by the behaviors of creatures in nature to solve real-world problems. This paper investigates an improved Harris hawks optimizer (HHO) by introducing the grey wolf optimizer (GWO) and improving the balance between exploration and exploitation. The proposed approach combines different cognitive hunting behaviors of Harris' hawks and grey wolf packs and selects the best solutions through iterations. Experimental results demonstrate the effectiveness and efficiency of the proposed method.
COGNITIVE COMPUTATION
(2022)
Article
Engineering, Multidisciplinary
Chong Liu, Wen-Ze Wu, Wanli Xie
Summary: As a combination of the differential equation prediction model and intelligent optimization algorithm, the grey intelligent prediction algorithm has been developed with a multiobjective correction strategy. The algorithm utilizes new weakened accumulation operation, Bernoulli parameter, discretization technique, and multiobjective grey wolf optimizer to enhance predictive ability, improve uniformity and unbiasedness, and alleviate overfitting. Experimental results show that the proposed model outperforms other comparative models in terms of prediction performance and stability.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Energy & Fuels
Ghassan Husnain, Shahzad Anwar, Gulbadan Sikander, Armughan Ali, Sangsoon Lim
Summary: This study presents a bio-inspired, cluster-based routing algorithm using the intelligent, probability-based, and nature-inspired whale optimization algorithm (p-WOA) for vehicular communication. The proposed method outperforms existing techniques in terms of the number of cluster heads (CH) and demonstrates superior performance through calculations of Packet Delivery Ratio (PDR), average throughput, and latency. The study confirms that VANETs employing ITS applications can optimize their clusters by a factor of 75, reducing communication costs and extending cluster lifespan.
Article
Computer Science, Information Systems
Ali Khan, Somaiya Khan, Athar Shahzad Fazal, Zhongshan Zhang, Adnan Omer Abuassba
Summary: A novel intelligent cluster routing scheme (CRSF) is proposed for flying ad hoc networks, with cluster head selection based on fitness and cluster management inspired by moth flame optimization, improving efficiency and stability of network communication. Additionally, routing mechanism for UAV communication and CH re-selection mechanism are introduced for effective topology management to maintain stable clusters.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Telecommunications
Abir Mchergui, Tarek Moulahi, Sherali Zeadally
Summary: Advancements in communications, smart transportation systems, and computer systems have opened up new possibilities for intelligent solutions in traffic safety and convenience. Artificial Intelligence (AI) is currently being utilized in the field of Vehicular Ad hoc NETworks (VANETs) to enhance conventional data-driven methods and improve passenger comfort, safety, and road experience.
VEHICULAR COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Khouloud Zouaidia, Salim Ghanemi, Mohamed Saber Rais, Lamine Bougueroua, Wgrzyn-Wolska Katarzyna
Summary: Wind power is considered one of the fastest growing alternative energies, expected to continue its rapid growth. A new hybrid architecture for wind speed forecasting showed superior adaptability and predictive performance, outperforming benchmark models in reducing error metrics values.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Green & Sustainable Science & Technology
Weifan Zhong, Lijing Du
Summary: Despite the development of traffic safety measures, traffic accidents on urban roads remain a major cause of death. The prediction of casualties in such accidents has not been thoroughly explored in previous research. This paper proposes a practicable model for traffic forecast problems, using ten variables as independent factors. Four different algorithms combined with a support vector machine (SVM) are employed to predict the casualties of collisions. Results based on 4285 valid urban road traffic collisions show that the SSA-SVM method performs effectively compared to the other three algorithms.
Article
Computer Science, Theory & Methods
ZhiSheng Wang, Shu-Chuan Chu, JianPo Li, Jeng-Shyang Pan
Summary: In this paper, an energy-adaptive clustering method based on Taguchi-based-GWO optimizer (EACM-TGWO) is proposed for wireless sensor networks with a mobile sink. The method determines the optimal number of cluster heads (CHs) based on the energy consumption characteristics of the network and uses a fitness function to select CHs. The Taguchi-based grey wolf optimizer (TGWO) algorithm is employed to search for the optimal set of CHs. Simulation results demonstrate that EACM-TGWO outperforms other algorithms in terms of balancing energy consumption and saving network energy.
Article
Engineering, Civil
Youngje Choi, Jungwon Ji, Eunkyung Lee, Sunmi Lee, Sooyeon Yi, Jaeeung Yi
Summary: Climate change affects water demand and supply, leading to more severe droughts and floods. To address this, the South Korean government added a water supply function to the Hwacheon reservoir that was originally built for hydropower. However, a water supply rule curve is missing. In this study, we develop a rule curve using optimization techniques and evaluate its performance compared to the firm supply method. The results show that the developed rule curve performs better and the Improved Grey Wolf Optimizer algorithm is the most effective.
WATER RESOURCES MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Haiyang Yu, Runkun Liu, Zhiheng Li, Yilong Ren, Han Jiang
Summary: This study focuses on balancing efficiency and coverage by establishing an RSU deployment strategy based on traffic demand. Simulation results show that covering 25% of the road segments with RSUs can serve most vehicles and reduce the delay of VANETs. Furthermore, road networks with high traffic demand require more RSUs to achieve the same effect, and early RSU investment is more cost effective.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Raju Pal, Mukesh Saraswat, Sandeep Kumar, Anand Nayyar, Pushpendra Kumar Rajput
Summary: This study proposes a multi-objective binary Grey wolf optimizer for optimizing the clustering centers in wireless sensor networks. By simultaneously optimizing multiple objectives, such as energy utilization and network stability, this method outperforms other state-of-the-art clustering protocols in terms of improving network performance and extending network lifetime.
Article
Computer Science, Information Systems
Xiaoqing Zhang, Yuye Zhang, Zhengfeng Ming
Summary: The dynamic grey wolf optimizers improve the iterative convergence rate by eliminating the waiting period for updating the search wolf's position. Research shows that, for the same improved algorithm, the performance of the dynamic GWO-based algorithm is generally better than that of the static GWO-based algorithm.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2021)
Article
Management
Naila Fares, Jaime Lloret, Vikas Kumar, Guilherme F. Frederico, Anil Kumar, Jose Arturo Garza-Reyes
Summary: This study analyzed the resilience of customer demand management post-COVID-19, using fast fashion as an example. The results revealed that maintaining customer loyalty is the highest priority, followed by e-commerce endorsement, a customer-focused assortment of items, and flexible store operations.
BENCHMARKING-AN INTERNATIONAL JOURNAL
(2023)
Article
Computer Science, Information Systems
Ritesh Yaduwanshi, Sushil Kumar, Arvind Kumar, Omprakash Kaiwartya, Deepti Deepti, Mohammad Aljaidi, Jaime Lloret
Summary: This paper proposes an efficient geocast routing (EGR) approach for highway IoV-traffic environment considering the shadowing fading condition. EGR utilizes a temporal link quality model and geometrical localization to solve the GPS outage problem and selects the next forwarding vehicle from the forward region based on temporal link quality for geocast routing. Simulation results show that EGR outperforms existing approaches in handling wireless communication link breakage and throughput issues in highway traffic environment, as well as ensuring faster message delivery.
Article
Computer Science, Information Systems
Khalid Haseeb, Fahad A. Alzahrani, Mohammad Siraj, Zahid Ullah, Jaime Lloret
Summary: This paper proposes an algorithm for mobile networks using fog computing to reduce network disconnectivity and improve energy efficiency. The algorithm transmits aggregated data using adjustable transmission power and reduces data load among devices with the support of fog nodes and a secured authentication scheme. Simulation experiments demonstrate the significance of the proposed algorithm in enhancing performance.
Article
Computer Science, Information Systems
Amjad Mehmood, Zeeshan Iqbal, Arqam Ali Shah, Carsten Maple, Jaime Lloret
Summary: The use of UAVs in search and rescue operations has been found to be highly advantageous. This article focuses on deploying a UAV network with a long battery life and complete coverage of the disaster area. The proposed intelligent cluster-based multi-unmanned aerial vehicle (ICBM-UAV) protocol allows for efficient communication and the quick discovery of victims through clustering techniques, reducing workload and improving network life.
Article
Computer Science, Information Systems
Shamsher Ullah, Zheng Jiangbin, Muhammad Tanveer Hussain, Muhammad Wasif Sardar, Muhammad Umar Farooq, Salabat Khan
Summary: The risks of misusing new and developing technology are increasing. It is a challenge to protect the identity and prevent misuse risk in e-communication with low computations. Researchers propose blind signature, blind singcryption, and ID-based signcryption schemes for secure and efficient communication. The schemes analyzed in this paper achieve desired features and low overheads, making them suitable for low-power environments.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Samrah Mehraj, Subreena Mushtaq, Shabir A. Parah, Kaiser J. Giri, Javaid A. Sheikh, Amir H. Gandomi, Mohammad Hijji, Brij B. Gupta, Khan Muhammad
Summary: Heritage multimedia is a valuable cultural asset that provides insights into earlier generations and their creative approach, lifestyle, and historical ideologies. It is also an important resource for boosting the local economy, sustainable communities, and tourism and business sectors. With the advancements in technology and 5G networks, protecting heritage media from unauthorized consumers is crucial. This study proposes a robust and blind watermarking-framework for cultural images (RBWCI) that uses the discrete cosine transform domain for ownership verification and copyright protection.
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
(2023)
Article
Computer Science, Hardware & Architecture
Shuai Liu, Xiyu Xu, Yang Zhang, Khan Muhammad, Weina Fu
Summary: This article introduces a reliable sample selection strategy for weakly supervised visual tracking and verifies its importance in improving model performance. Experiments demonstrate that a scientific sample quality assessment method is of great help to data-based weakly supervised learning systems.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Computer Science, Information Systems
Vinoth Kumar Krishnamoorthy, Usha Nandini Duraisamy, Amruta S. Jondhale, Jaime Lloret, Balaji Venkatesalu Ramasamy
Summary: This paper introduces an indoor object tracking method using received signal strength indicator (RSSI) measurements and wireless sensor network (WSN). The author proposes a range-free radial basis function neural network (RBFN) and Kalman filtering (KF) based algorithm named RBFN+KF to reduce the location estimation errors caused by random variations in RSSI measurements. The simulation results show that the RBFN+KF algorithm achieves lower location estimation errors compared to trilateration, multilayer perceptron (MLP), and RBFN-based estimations. Additionally, it is also observed that the RBFN-based approach is more energy efficient than trilateration and MLP-based localization approaches.
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
(2023)
Article
Computer Science, Artificial Intelligence
Syed Furqan Qadri, Hongxiang Lin, Linlin Shen, Mubashir Ahmad, Salman Qadri, Salabat Khan, Maqbool Khan, Syeda Shamaila Zareen, Muhammad Azeem Akbar, Md Belal Bin Heyat, Saqib Qamar
Summary: This study proposes a patch-based deep learning approach for automatic CT vertebral segmentation. The method extracts discriminative features from unlabeled data using a stacked sparse autoencoder and achieves accurate segmentation of CT vertebrae.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2023)
Article
Chemistry, Analytical
Sandra Viciano-Tudela, Lorena Parra, Paula Navarro-Garcia, Sandra Sendra, Jaime Lloret
Summary: This article proposes a new system for characterizing essential oils using low-cost sensor networks and machine learning techniques. The study found that using k-nearest neighbors algorithm, the accuracy, recall, F1-score, and precision values for identifying essential oils were 1, 0.99, 0.99, and 1, respectively.
Review
Engineering, Multidisciplinary
Muhammad Sajjad, Fath U. Min Ullah, Mohib Ullah, Georgia Christodoulou, Faouzi Alaya Cheikh, Mohammad Hijji, Khan Muhammad, Joel J. P. C. Rodrigues
Summary: Facial expression recognition (FER) is a complex research topic with applications in various fields, such as healthcare and security. Computational FER mimics human facial expression coding skills to assist human-computer interaction. This study thoroughly analyzes and surveys the existing literature on FER, highlights the working flow of FER methods, discusses limitations in existing surveys, investigates FER datasets, and comprehensively discusses measures to evaluate FER performance.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Mathematics
Mohammad Hijji, Hikmat Yar, Fath U. Min Ullah, Mohammed M. Alwakeel, Rafika Harrabi, Fahad Aradah, Faouzi Alaya Cheikh, Khan Muhammad, Muhammad Sajjad
Summary: Nowadays, people prefer to use private transport due to its low cost, comfortable ride, and personal preferences, resulting in a reduction in the use of public transportation. However, the use of personal transport has led to numerous road accidents due to drivers' conditions such as drowsiness, stress, tiredness, and age. To address this issue, an efficient deep learning-assisted intelligent fatigue and age detection system (FADS) was proposed to detect and identify different states of the driver. The system outperformed state-of-the-art techniques in experiments conducted on custom and publicly available datasets.
Article
Mathematics
Mohammad Hijji, Abbas Khan, Mohammed M. Alwakeel, Rafika Harrabi, Fahad Aradah, Faouzi Alaya Cheikh, Muhammad Sajjad, Khan Muhammad
Summary: Due to the large distance and relative motion, vehicle license plate images are often low resolution and blurry. Traditional techniques have been developed to upgrade the low-quality images, but most studies focus on super-resolution rather than motion de-blurring. This work extends SRGAN by adding an intelligent motion-deblurring method (SRGAN-LP) and achieves improved results with higher quantitative and qualitative values.
Article
Computer Science, Hardware & Architecture
Amjad Rehman, Ibrahim Abunadi, Khalid Haseeb, Tanzila Saba, Jaime Lloret
Summary: Artificial intelligence (AI) is experiencing significant growth in the areas of smart cities, agriculture, food management, and weather forecasting, primarily due to the limitations of computing power on sensing devices. The integration of AI with IoT and ubiquitous sensors has led to improvements in the agricultural sector and reduced management costs. However, optimizing resource management and data load for forwarding nodes near edge boundaries remains a challenging issue due to limited wireless technology resources.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Mathematical & Computational Biology
Mubashir Ahmad, Saira, Omar Alfandi, Asad Masood Khattak, Syed Furqan Qadri, Iftikhar Ahmed Saeed, Salabat Khan, Bashir Hayat, Arshad Ahmad
Summary: Facial expression is a form of communication that has applications in various computer vision areas. A deep learning approach, specifically SSAE-FER, is used to accurately detect and classify expressions. By utilizing unsupervised pre-training and supervised fine-tuning, SSAE-FER successfully extracts features from input images and achieves high accuracy on JAFFE and CK+ datasets. It outperforms other comparative methods in the same domain.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Jia Ke, Ying Wang, Mingyue Fan, Xiaojun Chen, Wenlong Zhang, Jianping Gou
Summary: This study integrates the emotional correlation analysis model and Self-organizing Map (SOM) to construct fine-grained user emotion vector based on review text and perform visual cluster analysis, which helps platform merchants quickly mine user clustering and characteristics.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Shi Qiu, Huping Ye, Xiaohan Liao, Benyue Zhang, Miao Zhang, Zimu Zeng
Summary: This paper proposes a multilevel-based algorithm for hyperspectral image interpretation, which achieves semantic segmentation through multidimensional information fusion, and introduces a context interpretation module to improve detection performance.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jianteng Xu, Qingguo Bai, Zhiwen Li, Lili Zhao
Summary: This study constructs two optimization models for the omnichannel closed-loop supply chain by leveraging the combined power of leader-follower game and mean-variance theories. The focus is on analyzing the performance of manufacturers who distribute products through physical stores. The results show that the risk-averse attitude of the physical store has a positive impact on the overall system profitability, but if the introduced physical store belongs to another firm, total profit experiences a decline.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Jiahao Xiong, Weihua Ou, Zhonghua Liu, Jianping Gou, Wenjun Xiao, Haitao Liu
Summary: This paper proposes a novel remote photoplethysmography framework, named GraphPhys, which utilizes graph neural network to extract physiological signals and introduces Average Relative GraphConv for the task of remote physiological signal measurement. Experimental results show that the methods based on GraphPhys significantly outperform the original methods.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
Article
Computer Science, Hardware & Architecture
Zhiyao Tong, Yiyi Hu, Chi Jiang, Yin Zhang
Summary: The rise of illicit activities involving blockchain digital currencies has become a growing concern. In order to prevent illegal activities, this study combines financial risk control with machine learning to identify and predict the risks of users with poor credit. Experimental results demonstrate high performance in user financial credit analysis.
COMPUTERS & ELECTRICAL ENGINEERING
(2024)
