-
M2BIST-SPNet: RUL prediction for railway signaling electromechanical devices J. Supercomput. (IF 3.3) Pub Date : 2024-04-16 Xiaoxi Hu, Lei Tan, Tao Tang
-
Energy efficiency and performance analysis of a legacy atomic scale materials modeling simulator (VASP) J. Supercomput. (IF 3.3) Pub Date : 2024-04-16 Isidoro Nieves-Pírez, Alfonso Muñoz, Francisco Almeida, Vicente Blanco
-
Performance improvement of the triangular matrix product in commodity clusters J. Supercomput. (IF 3.3) Pub Date : 2024-04-15 Inmaculada Santamaria-Valenzuela, Rocío Carratalá-Sáez, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano
-
Automatic phoneme recognition by deep neural networks J. Supercomput. (IF 3.3) Pub Date : 2024-04-15 Bianca Valéria L. Pereira, Mateus B. F. de Carvalho, Pedro Augusto A. da S. de A. Nava Alves, Paulo Rogerio de A. Ribeiro, Alexandre Cesar M. de Oliveira, Areolino de Almeida Neto
-
A developed Criminisi algorithm based on particle swarm optimization (PSO-CA) for image inpainting J. Supercomput. (IF 3.3) Pub Date : 2024-04-14 Fang-Fang Li, Hui-Min Zuo, Ying-Hui Jia, Jun Qiu
-
Human–machine co-creation: a complementary cognitive approach to creative character design process using GANs J. Supercomput. (IF 3.3) Pub Date : 2024-04-13 Mohammad Lataifeh, Xavier A. Carrasco, Ashraf M. Elnagar, Naveed Ahmed, Imran Junejo
-
TimeLink: enabling dynamic runtime prediction for Flink iterative jobs J. Supercomput. (IF 3.3) Pub Date : 2024-04-13 Xiaofei Yue, Qingyang Ding, Jianming Zhu, Yanbing Ding
-
Distributed cache strategy based on LT codes under spark platform J. Supercomput. (IF 3.3) Pub Date : 2024-04-12 Jing Shang, Yifei Zhang, Jibin Wang, Zhihui Wu, Zhiwen Xiao
-
Study on spatial and temporal correlation characteristics for RIS-aided macrocell high-speed railway propagation systems J. Supercomput. (IF 3.3) Pub Date : 2024-04-12 Beiping Zhou, Keqi Zhao, Yongfeng Zhao, Yierfan Abulihaiti, Chen Yang, Linghan Fu
-
Evolving random weight neural networks based on oversampled-segmented examples for IoT intrusion detection J. Supercomput. (IF 3.3) Pub Date : 2024-04-11 Raneem Qaddoura, Hossam Faris
-
Aspect-level sentiment classification with aspect-opinion sentence pattern connection graph convolutional networks J. Supercomput. (IF 3.3) Pub Date : 2024-04-11 Hongye Li, Fuyong Xu, Zhiyu Zhang, Peiyu Liu, Wenyin Zhang
-
Extra connectivity of the data center network—RRect J. Supercomput. (IF 3.3) Pub Date : 2024-04-11 Ni An, Mengjie Lv, Weibei Fan, Lei Han, Fu Xiao
-
Enhancing network intrusion detection by lifelong active online learning J. Supercomput. (IF 3.3) Pub Date : 2024-04-11 Po-Jen Chuang, Pang-Yu Huang
-
A multi-strategy-guided sparrow search algorithm to solve numerical optimization and predict the remaining useful life of li-ion batteries J. Supercomput. (IF 3.3) Pub Date : 2024-04-10 Jiankai Xue, Bo Shen, Anqi Pan
-
Enhancing network intrusion detection: a dual-ensemble approach with CTGAN-balanced data and weak classifiers J. Supercomput. (IF 3.3) Pub Date : 2024-04-10 Mohammad Reza Abbaszadeh Bavil Soflaei, Arash Salehpour, Karim Samadzamini
-
Edge and cloud computing approaches in the early diagnosis of skin cancer with attention-based vision transformer through hyperspectral imaging J. Supercomput. (IF 3.3) Pub Date : 2024-04-10 Marco La Salvia, Emanuele Torti, Elisa Marenzi, Giovanni Danese, Francesco Leporati
-
Transforming educational insights: strategic integration of federated learning for enhanced prediction of student learning outcomes J. Supercomput. (IF 3.3) Pub Date : 2024-04-10 Umer Farooq, Shahid Naseem, Tariq Mahmood, Jianqiang Li, Amjad Rehman, Tanzila Saba, Luqman Mustafa
-
Optimizing software reliability growth models through simulated annealing algorithm: parameters estimation and performance analysis J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Baydaa Sulaiman Bahnam, Suhair Abd Dawwod, Mohammed Chachan Younis
-
IoMT-BADT: A blockchain-envisioned secure architecture with a lightweight authentication scheme for the Digital Twin environment in the Internet of Medical Things J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Ayushi Jain, Mehak Garg, Anvita Gupta, Shivangi Batra, Bhawna Narwal
-
BCDDO: Binary Child Drawing Development Optimization J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Abubakr S. Issa, Yossra H. Ali, Tarik A. Rashid
-
Advancing VANET stability: enhanced cluster head selection with iTTM and weighted CRITIC J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Ashish Kumari, Shailender Kumar, Ram Shringar Raw
-
Multiple search operators selection by adaptive probability allocation for fast convergent multitask optimization J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Zhaoqi Wang, Lei Wang, Qiaoyong Jiang, Xinhui Duan, Zhennan Wang, Liangliang Wang
-
Coherent mesh representation for parallel I/O of unstructured polyhedral meshes J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 R. Gregor Weiß, Sergey Lesnik, Flavio C. C. Galeazzo, Andreas Ruopp, Henrik Rusche
-
Federated learning-based edge computing for automatic train operation in communication-based train control systems J. Supercomput. (IF 3.3) Pub Date : 2024-04-09 Zhouhao Zhang, Hailin Jiang, Hongli Zhao, Yang Li
-
Optimal power flow solution using a learning-based sine–cosine algorithm J. Supercomput. (IF 3.3) Pub Date : 2024-04-08 Udit Mittal, Uma Nangia, Narender Kumar Jain, Saket Gupta
-
Fog-Marketing: auction-based multi-tier decentralized markets for fog resource provisioning J. Supercomput. (IF 3.3) Pub Date : 2024-04-08 Samira Shahinifar, Mohammad Taghi Kheirabadi, Ali Broumandnia, Kambiz Rahbar
-
Construction and analysis of students’ physical health portrait based on principal component analysis improved Canopy-K-means algorithm J. Supercomput. (IF 3.3) Pub Date : 2024-04-08 Rongbiao Ji, Jianke Yang, Yehui Wu, Yadong Li, Rujia Li, Jiaojiao Chen, Jianping Yang
-
Aphto: a task offloading strategy for autonomous driving under mobile edge J. Supercomput. (IF 3.3) Pub Date : 2024-04-08 JiaCheng Lin, HuanLe Rao, SongSong Liang, YuMiao Zhao, Qing Ren, GangYong Jia
-
Optimization of uncertain dependent task mapping on heterogeneous computing platforms J. Supercomput. (IF 3.3) Pub Date : 2024-04-07 Jing Zhang, Zhanwei Han
-
Approximate bilateral filters for real-time and low-energy imaging applications on FPGAs J. Supercomput. (IF 3.3) Pub Date : 2024-04-07
Abstract Bilateral filtering is an image processing technique commonly adopted as intermediate step of several computer vision tasks. Opposite to the conventional image filtering, which is based on convolving the input pixels with a static kernel, the bilateral filtering computes its weights on the fly according to the current pixel values and some tuning parameters. Such additional elaborations involve
-
Analyzing FOSS license usage in publicly available software at scale via the SWH-analytics framework J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract The Software Heritage (SWH) dataset represents an invaluable source of open-source code as it aims to collect, preserve, and share all publicly available software in source code form ever produced by humankind. Although designed to archive deduplicated small files thanks to the use of a Merkle tree as the underlying data structure, querying the SWH dataset presents challenges due to the nature
-
Two-level content-based mammogram retrieval using the ACR BI-RADS assessment code and learning-driven distance selection J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract Content-based mammogram retrieval (CBMR) is an effective approach to assist radiologists in diagnosing patients’ mammograms. Indeed, by studying the similar cases to diagnostic prone one, which are retrieved from a dataset containing other mammograms whose results are clinically proven, the final decision could be effectively made. In order to improve the final retrieved mammograms, and thereafter
-
CryptoHHO: a bio-inspired cryptosystem for data security in Fog–Cloud architecture J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract The exponential growth of Internet-of-Things (IoT) has raised several data security risks to the Fog–Cloud architecture. The performance and the computation cost of security algorithms hinder providing a secure real-time environment for IoT. This study proposes a novel two-layer cryptosystem, Cryptographic Harris Hawks Optimization (CryptoHHO), for Fog–Cloud architecture that reduces security
-
Robust enhanced collaborative filtering without explicit noise filtering J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract Graph convolutional neural networks have been successfully applied to collaborative filtering to capture high-quality user-item representations. Despite their remarkable performance, there are still limitations that hinder further improvement of recommender systems. Most existing recommendation systems utilize implicit feedback data for model training, but such data inevitably contains adversarial
-
Fault-tolerant basis of generalized fat trees and perfect binary tree derived architectures J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract The ability to uniquely identify all nodes in a network based on network distances has proven to be highly beneficial despite the computational challenges involved in discovering minimal resolving sets within an interconnection network. A subset R of vertices of a graph G is referred to as a resolving set of the graph if each node can be uniquely identified by its distance code with respect
-
e-Diagnostic system for diabetes disease prediction on an IoMT environment-based hyper AdaBoost machine learning model J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract One of the most fatal and serious diseases that humans have encountered is diabetes, an illness affecting thousands of individuals yearly. In this era of digital systems, diabetes prediction based on machine learning (ML) is gaining high momentum. One of the benefits of treating patients early in the course of their noncommunicable diseases (NCDs) is that they can avoid costly therapies when
-
ROVM integrated advanced machine learning-based malaria prediction strategy in Tripura J. Supercomput. (IF 3.3) Pub Date : 2024-04-06
Abstract Malaria is a deadly disease that can take a person's life if not predicted or cured correctly. Numerous factors like temperature, humidity, precipitation, etc., impact India's increasing cases of malaria diseases. This research presents an advanced machine learning regression technique recently developed to anticipate the prevalence of malaria in Tripura using a real-world data. The proposed
-
A sentiment analysis model based on dynamic pre-training and stacked involutions J. Supercomput. (IF 3.3) Pub Date : 2024-04-04 Shiyu Liu, Qicheng Liu
-
LMGU-NET: methodological intervention for prediction of bone health for clinical recommendations J. Supercomput. (IF 3.3) Pub Date : 2024-04-04 Gautam Amiya, Pallikonda Rajasekaran Murugan, Kottaimalai Ramaraj, Vishnuvarthanan Govindaraj, Muneeswaran Vasudevan, M. Thirumurugan, S. Sheik Abdullah, Arunprasath Thiyagarajan
-
Energy-aware application mapping methods for mesh-based hybrid wireless network-on-chips J. Supercomput. (IF 3.3) Pub Date : 2024-04-04 Alperen Cakin, Selma Dilek, Suleyman Tosun
The 2D mesh topology-based Network-on-Chip (NoC) is a prevalent structure in System-on-Chip (SoC) designs, offering implementation and fabrication benefits. However, increased NoC scale leads to longer communication paths, more hops, and higher end-to-end latency and energy consumption. To mitigate these issues, Wireless NoC (WiNoC) integrates wireless communication, enhancing data rates, energy efficiency
-
Training with One2MultiSeq: CopyBART for social media keyphrase generation J. Supercomput. (IF 3.3) Pub Date : 2024-04-04 Bengong Yu, Chunyang Gao, Shuwen Zhang
-
Brain hyperintensities: automatic segmentation of white matter hyperintensities in clinical brain MRI images using improved deep neural network J. Supercomput. (IF 3.3) Pub Date : 2024-04-04 Puranam Revanth Kumar, Rajesh Kumar Jha, P. Akhendra Kumar
-
Optimal UAV deployment with star topology in area coverage problems J. Supercomput. (IF 3.3) Pub Date : 2024-04-03
Abstract UAVs in most real-world deployments communicate with a ground control station either in a one-hop manner, which has a limited working range, or relies on infrastructure support such as satellite communication, which is expensive. Although multi-hop transmission is more economic, it is lossy and generally incurs large delays. In this paper, we consider a mixed method, where a few UAVs are equipped
-
Particle swarm optimization and FM/FM/1/WV retrial queues with catastrophes: application to cloud storage J. Supercomput. (IF 3.3) Pub Date : 2024-04-03 Sibasish Dhibar, Madhu Jain
The cloud storage service, known for its flexible and expandable nature, often has difficulties managing operating costs while ensuring dependable service and quick response times. This investigation presents a novel approach to optimizing cost efficiency in cloud storage systems by applying particle swarm optimization of the Markovian retrial queueing model in a generic setup by incorporating the
-
Trish: an efficient activation function for CNN models and analysis of its effectiveness with optimizers in diagnosing glaucoma J. Supercomput. (IF 3.3) Pub Date : 2024-04-03 Cemil Közkurt, Aykut Diker, Abdullah Elen, Serhat Kılıçarslan, Emrah Dönmez, Fahrettin Burak Demir
Glaucoma is an eye disease that spreads over time without showing any symptoms at an early age and can result in vision loss in advanced ages. The most critical issue in this disease is to detect the symptoms of the disease at an early age. Various researches are carried out on machine learning approaches that will provide support to the expert for this diagnosis. The activation function plays a pivotal
-
CBGA: A deep learning method for power grid communication networks service activity prediction J. Supercomput. (IF 3.3) Pub Date : 2024-04-02 Shangdong Liu, Longfei Zhou, Sisi Shao, Jun Zuo, Yimu Ji
The prediction of power equipment activity plays a vital role in optimizing power resource dispatch, ensuring supply and demand balance, and guiding network planning and management. However, due to the complex nonlinear, multi-scale, and multivariate characteristics of power grid communication networks service activity (PCNSA) data, it is often challenging to capture its intrinsic patterns and dynamic
-
A migration strategy based on cluster collaboration predictions for mobile edge computing-enabled smart rail system J. Supercomput. (IF 3.3) Pub Date : 2024-04-02 Junjie Cao, Zhiyong Yu, Jian Yang
As an important part of modern transportation, smart rail system need to handle a large number of delay-sensitive and task-intensive tasks in a high-speed mobile state. However, high-speed mobility challenges the traditional information processing modes a lot, such as service interruptions and information congestion. In order to solve these problems, we proposed a service migration strategy based on
-
Credit-based energy trading system using blockchain and machine learning J. Supercomput. (IF 3.3) Pub Date : 2024-04-02 Kamal Singh, Nitin Singha
In peer-to-peer (P2P) energy trading, members locally trade energy. Blockchain-based systems are employed for the above trading. These systems are limited in speed because of the time required in the consensus process to audit and verify transactions. Further energy is traded using auction, which also consumes time. In this paper, we propose a blockchain and machine learning-based system to speed up
-
Secure symbol-level precoding for reconfigurable intelligent surface-aided cell-free networks J. Supercomput. (IF 3.3) Pub Date : 2024-04-02 Hongtai Yao, Zewen Li, Yong Jin, Zhentao Hu, Qinglan Peng
With the improvement in communication network density, inter-cell interference has become severe. Due to the blurring of boundaries, cell-free networks are considered as a solution. However, it faces some challenges, such as high energy consumption due to the deployment of a large number of base stations, and security issues in complex communication scenarios. To tackle these issues, we propose a novel
-
RI-RPL: a new high-quality RPL-based routing protocol using Q-learning algorithm J. Supercomput. (IF 3.3) Pub Date : 2024-04-01 Niloofar Zahedy, Behrang Barekatain, Alfonso Ariza Quintana
-
Parallelization with load balancing of the weather scheme WSM7 for heterogeneous CPU-GPU platforms J. Supercomput. (IF 3.3) Pub Date : 2024-03-22 Thomas Jakobs, Oliver Klöckner, Gudula Rünger
-
PARamrfinder: detecting allele-specific DNA methylation on multicore clusters J. Supercomput. (IF 3.3) Pub Date : 2024-03-21 Alejandro Fernández-Fraga, Jorge González-Domínguez, María J. Martín
-
Quantum particle Swarm optimized extreme learning machine for intrusion detection J. Supercomput. (IF 3.3) Pub Date : 2024-03-21 Han Qi, Xinyu Liu, Abdullah Gani, Changqing Gong
-
Towards connection-scalable RNIC architecture J. Supercomput. (IF 3.3) Pub Date : 2024-03-21 Ning Kang, Zhan Wang, Fan Yang, Xiaoxiao Ma, Zhenlong Ma, Guojun Yuan, Guangming Tan
-
Semi-supervised attack detection in industrial control systems with deviation networks and feature selection J. Supercomput. (IF 3.3) Pub Date : 2024-03-21 Yanhua Liu, Wentao Deng, Zhihuang Liu, Fanhao Zeng
-
Graph regularized autoencoding-inspired non-negative matrix factorization for link prediction in complex networks using clustering information and biased random walk J. Supercomput. (IF 3.3) Pub Date : 2024-03-20 Tongfeng Li, Ruisheng zhang, Yabing Yao, Yunwu Liu, Jun Ma, Jianxin Tang
-
Securing IoT networks in cloud computing environments: a real-time IDS J. Supercomput. (IF 3.3) Pub Date : 2024-03-20 Soham Biswas, Md. Sarfaraj Alam Ansari
-
A deep learning approach to dysarthric utterance classification with BiLSTM-GRU, speech cue filtering, and log mel spectrograms J. Supercomput. (IF 3.3) Pub Date : 2024-03-20
Abstract Assessing the intelligibility of dysarthric speech, characterized by intricate speaking rhythms presents formidable challenges. Current techniques for objectively testing speech intelligibility are burdensome and subjective, particularly struggling with dysarthric spoken utterances. To tackle these hurdles, our method conducts an ablation analysis across speakers afflicted with speech impairment
-
Hybrid approach: combining eCCA and SSCOR for enhancing SSVEP decoding J. Supercomput. (IF 3.3) Pub Date : 2024-03-20 Soukaina Hamou, Mustapha Moufassih, Ousama Tarahi, Said Agounad, Hafida Idrissi Azami
-
Fastlomap: faster lead optimization mapper algorithm for large-scale relative free energy perturbation J. Supercomput. (IF 3.3) Pub Date : 2024-03-20 Kairi Furui, Masahito Ohue