Article
Chemistry, Analytical
Nhat-Tien Nguyen, Thien T. T. Le, Huy-Hung Nguyen, Miroslav Voznak
Summary: Underwater wireless sensor networks are currently undergoing extensive research for various human benefits, with the proposed energy-efficient clustering multi-hop routing protocol (EECMR) showing effectiveness in balancing energy consumption and increasing network lifetime.
Article
Computer Science, Artificial Intelligence
R. Muthukkumar, Lalit Garg, K. Maharajan, M. Jayalakshmi, Nz Jhanjhi, S. Parthiban, G. Saritha
Summary: This article proposes a genetic algorithm-based energy-aware multi-hop clustering scheme for solving the energy constraint issue in heterogeneous wireless sensor networks. The scheme improves network lifetime and energy efficiency by selecting optimal cluster heads and positions and implementing multi-hop communication.
PEERJ COMPUTER SCIENCE
(2022)
Article
Computer Science, Information Systems
Vishal Kumar Arora, Vishal Sharma
Summary: The proposed Energy Balanced Multi-hop Routing Scheme (EBMRS) effectively improves the energy efficiency of Wireless Sensor Networks and increases network lifetime by 40%. By optimizing Cluster-Head selection and data transmission communication, the scheme prevents unbalanced cluster formation.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Jianhua Huang, Tianqi Li, Zhigang Shi
Summary: This paper proposes an energy-efficient multi-hop routing protocol called UASGRP by using uneven annulus sector grid clustering and multi-hop relay transmission mechanism to balance the energy consumption of nodes effectively. Simulation results demonstrate that UASGRP outperforms other grid-based clustering schemes in energy consumption balance and scalability for networks of various sizes.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Shahid Iqbal, Adnan Ahmed, Mohammad Siraj, Majid Al Tamimi, Ali Raza Bhangwar, Pardeep Kumar
Summary: Technological advancements and miniaturization of sensor have enabled the use of tiny size sensors nodes to monitor patients' physiological data in real-time at low cost. However, short range wireless nodes and body movements cause frequent topological changes and network partitioning, leading to delays and loss of critical patient data in wireless body sensor networks (WBSNs). This paper proposes a Predicting routing protocol PLQE to address reliable data transmission and network partitioning due to node mobility. Simulation results show that the proposed scheme outperforms existing routing protocols in terms of packet delivery ratio, end-to-end delay, throughput, and normalized routing load.
Article
Telecommunications
Madhvi Saxena, Ankit Joshi, Subrata Dutta, Kailash Chandra Mishra, Arindam Giri, Sarmistha Neogy
Summary: The paper investigates data collection and forwarding in wireless sensor networks, proposing and designing two algorithms to improve network lifetime and energy efficiency.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Naoki Matsuhashi, Chisa Takano, Masaki Aida
Summary: In multi-hop wireless networks, hierarchical structures and clustering algorithms are extensively studied for scalable routing control. However, autonomous and decentralized implementation of these algorithms is challenging due to the constraints of distributed systems. This paper proposes an autonomous and decentralized spectral clustering algorithm that can be applied to any network topology by creating a spatial structure using differential equation-based temporal evolution equations. It demonstrates stable cluster formation in both static and dynamic network models.
Article
Computer Science, Hardware & Architecture
R. Nithya, Roobaea Alroobaea, Ahmed Binmahfoudh, Zairi Ismael Rizman
Summary: The research focuses on improving energy efficiency and network performance in wireless sensor networks by proposing the HEMUR model, BTAC method, and GISEDC method. These methods contribute to efficient energy allocation, improved routing efficiency, and minimized energy consumption.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Telecommunications
Afia Naeem, Abdul Rehman Javed, Muhammad Rizwan, Sidra Abbas, Jerry Chun-Wei Lin, Thippa Reddy Gadekallu
Summary: Wireless Sensor Networks (WSNs) consist of multiple sensor nodes deployed ad-hocly to sense or observe physical phenomena by collecting real-time data. A hybrid approach named DARE-SEP is proposed in this study, which combines various features to improve network lifetime. Results show a 10% increase in energy efficiency compared to traditional routing protocols, enhancing network lifespan.
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING
(2021)
Article
Computer Science, Information Systems
Mohamed Elshrkawey, Hassan Al-Mahdi, Walid Atwa
Summary: This paper proposes a routing algorithm based on a novel RPSO algorithm and a new fitness function. The evaluation and comparison results demonstrate that this algorithm outperforms others in terms of convergence speed and global optimum identification, and it successfully improves performance metrics such as network lifetime, energy consumption, and data throughput in wireless sensor networks.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Hardware & Architecture
K. Phani Rama Krishna, Ramakrishna Thirumuru
Summary: This research proposes a Multi-Hop, Trivial, and Protected Routing Solution for Constrained Wireless Sensor Networks. It utilizes the Chaotic Particle-swarm Krill Herd method to select energy-efficient cluster heads and the Self-Adaptive Step Glow Worm Swarm Optimization Algorithm to choose the optimal path. Moreover, the Hamming Residue Technique is employed to counteract malicious attacks in the WSN.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2023)
Article
Computer Science, Information Systems
Mohd Adnan, Liu Yang, Tazeem Ahmad, Yang Tao
Summary: This paper proposed a clustering protocol based on fuzzy logic to achieve load balancing, energy consumption minimization, and network lifetime prolongation in wireless sensor networks. By forming unequal clusters and utilizing multi-hop transmission, the protocol effectively addressed the issue of imbalanced energy distribution among nodes in WSNs.
Article
Computer Science, Information Systems
Geeranuch Woraphonbenjakul, Quang Tuan Do, Sungrae Cho
Summary: This paper proposes an improved threshold-sensitive stable election protocol (TSEP) for wireless sensor networks design. By assigning probability weights based on residual energy, the proposed protocol categorizes sensor nodes into four different initial energy levels, resulting in significant improvements in stability period and network lifetime compared to previous protocols.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2023)
Article
Chemistry, Analytical
Fatma H. El-Fouly, Ahmed Y. Khedr, Md Haidar Sharif, Eissa Jaber Alreshidi, Kusum Yadav, Huseyin Kusetogullari, Rabie A. Ramadan
Summary: This paper proposes an energy-efficient and reliable clustering protocol (ERCP) for Wireless Sensor Networks (WSNs). The protocol achieves energy savings and reliable message delivery through efficient clustering technique and reliable inter-cluster routing technique.
Article
Computer Science, Hardware & Architecture
Manish Kumar Singh, Amit Choudhary, Sandeep Gulia, Anurag Verma
Summary: This paper proposes a hybrid data routing protocol for UAV-assisted wireless sensor networks, optimizing the UAV's flight trajectory while achieving energy-efficient data communication, and utilizing multi-objective optimization algorithms to achieve the optimal flight trajectory.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Amin Rezaeipanah, Gholamreza Ahmadi
Summary: Breast cancer is the most common type of cancer among women worldwide. Early detection and treatment are crucial for improving the survival rate. This paper proposes an automatic breast cancer diagnosis technique using a genetic algorithm to optimize the Multi Layer Perceptron neural network. The algorithm achieves high accuracy in classifying breast cancer and compares favorably with other methods in the literature.
Article
Biochemical Research Methods
Musa Mojarad, Fariba Sarhangnia, Amin Rezaeipanah, Hamin Parvin, Samad Nejatian
Summary: This paper identifies inter-cell and inter-tissue communications for various diseases using an innovative approach, utilizing graph topological structure characteristics and clustering ensemble similarity criterion. Experimental results show that the proposed method yields promising results in detecting relationships between diseases by exploiting maximum inter-cell or inter-tissue similarity in each cluster.
CURRENT BIOINFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Shenghao Jiang, Saeed Mashdoor, Hamid Parvin, Bui Anh Tuan, Kim-Hung Pho
Summary: The paper introduces a particle swarm optimization algorithm inspired by birds' classical conditioning learning behavior, which divides particles into multiple categories and adjusts the exploration-exploitation strategy based on the diversity within each category. The algorithm also speeds up particles' movement in improper spaces and slows down their speed in valuable spaces, aiming to efficiently explore the search space.
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Hao Fan, Kaijun Wu, Hamid Parvin, Akram Beigi, Kim-Hung Pho
Summary: Recommender Systems play a crucial role in addressing the challenges in the field of E-Commerce. Recent Hybrid Recommender Systems combine the strengths of traditional methods and address issues such as cold start, scalability, and sparsity.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2021)
Article
Computer Science, Artificial Intelligence
Saeed Talatian Azad, Gholamreza Ahmadi, Amin Rezaeipanah
Summary: The paper presents an intelligent ensemble classification method based on Multi-Layer Perceptron neural network for breast cancer diagnosis. This method goes through two stages of parameter optimization and ensemble classification, successfully improving classification accuracy and reducing misclassification costs.
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Kim-Hung Pho, Hamidreza Akbarzadeh, Hamid Parvin, Samad Nejatian, Hamid Alinejad-Rokny
Summary: In this paper, a method called MLCC is proposed for improving the performance of clustering, utilizing innovative similarity metrics to generate cluster-cluster and point-point similarity matrices, which are then used to create a consensus partition through hierarchical clustering. Experimental results demonstrate that MLCC outperforms traditional methods in terms of accuracy and robustness, with reasonable computational cost.
Article
Computer Science, Artificial Intelligence
Rahmad Syah, Siswi Wulandari, Arbansyah, Amin Rezaeipanah
Summary: This paper utilized a Multi-Layer Perceptron Neural Network (MLP-NN) based on Evolutionary Algorithms (EA) to automatically classify breast cancer, and evaluated its performance using stacked generalization technique. Experimental results demonstrated the superior performance of IEC-MLP with ensemble classifiers compared to other algorithms.
INTELIGENCIA ARTIFICIAL-IBEROAMERICAL JOURNAL OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Yun Li, Yibin Song, Amin Rezaeipanah
Summary: RoboCup is a significant human endeavor in the robotics and artificial intelligence field, with the RoboCup3D competition providing a platform for teams to work with humanoid robots without hardware. Teams in the RoboCup3D league aim to increase shoot numbers to gain an advantage over opponents, utilizing a curved path strategy for robot movement in walking situations. The Q-learning algorithm is used to adjust robot movement parameters based on the noise in the vision preceptor, with the IK module applied for shooting when the robot is in an optimal position relative to the ball and goal.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Information Systems
Ebrahim Heidary, Hamid Parvin, Samad Nejatian, Karamollah Bagherifard, Vahideh Rezaie
Summary: This paper introduces a new hybrid method for extractive text summarization based on text structure, which improves sentence feature selection process and leads to the generation of unambiguous, concise, consistent, and coherent summaries.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Computer Science, Information Systems
Yixuan Wang, Liping Yuan, Harish Garg, Ali Bagherinia, Hamid Parvin, Kim-Hung Pho, Zulkefli Mansor
Summary: This paper proposes a new fuzzy clustering ensemble method that introduces Reliability Based weighted co-association matrix Fuzzy C-Means (RBFCM), Reliability Based Graph Partitioning (RBGP) and Reliability Based Hyper Clustering (RBHC) as three new fuzzy clustering consensus functions to improve performance and robustness.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Computer Science, Information Systems
Ebrahim Heidary, Hamid Parvin, Samad Nejatian, Karamollah Bagherifard, Vahideh Rezaie, Zulkefli Mansor, Kim-Hung Pho
Summary: Automatic summarization is a crucial tool for quick access to important goals and features of text documents. This study introduces a novel method using genetic algorithms and repetitive patterns for selective text summarization, improving precision and consistency in the summary text.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Computer Science, Information Systems
Yingfu Cai, Sultan Noman Qasem, Harish Garg, Hamid Parvin, Kim-Hung Pho, Zulkefli Mansor
Summary: Invariants are essential relationships between program variables, useful for software checking and verification. Two types of invariant detectors are dynamic and static, with Daikon software implementing a dynamic variant detection algorithm. By applying special techniques from genetic algorithms, differences in runtime for the Daikon tool can be reduced between adjacent trace files.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)