Article
Biology
Weibai Pan, Ying An, Yuxia Guan, Jianxin Wang
Summary: This paper proposes a multi-task channel attention network (MCA-net) for myocardial infarction (MI) detection and location using 12-lead electrocardiograms (ECGs). By integrating features from different leads and introducing a multi-task framework, the MCA-net outperforms state-of-the-art methods in terms of accuracy. It effectively assists cardiologists in diagnosing and locating MI.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Multidisciplinary Sciences
Wondale Tsega, Worku Awoke, Ashenafi Kibret Sendekie, Ephrem Mebratu Dagnew, Habtamu Bayih
Summary: This study assessed the utilization of ECG and Echo findings and outcomes of patients with MI in tertiary care hospitals in Northwest Ethiopia. The study found that the mortality rate of patients with MI was higher than in other reports, and there was a higher degree of inconsistency between ECG and Echo findings. The treatment of patients with MI should be tailored to their specific risk factors and causes.
Article
Biotechnology & Applied Microbiology
Ryunosuke Uchiyama, Yoshifumi Okada, Ryuya Kakizaki, Sekito Tomioka
Summary: This paper proposes a new convolutional neural network model for detecting and localizing myocardial infarction without the need for complex preprocessing. Experimental results demonstrated that the proposed model achieved higher or comparable performance in MI detection and localization compared to existing state-of-the-art methods.
BIOENGINEERING-BASEL
(2022)
Article
Cardiac & Cardiovascular Systems
Philip Broughton, Miguel Troncoso, Alexa Corker, Alexus Williams, Dawson Bolus, Gualberto Munoz, Caroline McWhorter, Hallie Roerden, Penny Huebsch, Kristine Y. DeLeon-Pennell
Summary: This study aimed to generate a quantitative profile of electrocardiograms (ECGs) to confirm the success of permanent coronary artery ligation surgeries. The results showed that the QRS complex and R-S amplitude were significantly different after ligation compared to baseline. Changes in the QRS complex at 1 and 5 minutes were linked to surgical success, while the R-S amplitude remained non-significant. The area under the QRS complex 1 minute after ligation could improve reproducibility in myocardial infarction surgeries.
AMERICAN JOURNAL OF PHYSIOLOGY-HEART AND CIRCULATORY PHYSIOLOGY
(2022)
Article
Engineering, Mechanical
Rakesh Kumar Jha, Preety D. Swami
Summary: This paper proposes a data-driven approach for estimating the remaining useful life (RUL) of rolling bearings. By constructing health indicators (HI) using the maximum variance subband of the wavelet features, reducing feature dimensions using principal component analysis, and using support vector regression (SVR) models to predict the future degradation profile, the RUL of the bearings can be accurately predicted.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2022)
Article
Chemistry, Analytical
Wenhan Liu, Jiewei Ji, Sheng Chang, Hao Wang, Jin He, Qijun Huang
Summary: In this paper, an evolving neural network named EvoMBN is proposed for myocardial infarction (MI) diagnosis, utilizing a genetic algorithm (GA) to automatically learn the optimal MBN architectures and designing a novel Lead Squeeze and Excitation (LSE) block for feature summarization.
Article
Geosciences, Multidisciplinary
Yan Cong, Rui-lian Yu, Yu Yan, Bo-sen Weng, Gong-ren Hu, Jing-wei Sun, Jian-yong Cui, Yao-yi Huang
Summary: This study determined the concentrations of heavy metals in Tieguanyin tea plants and identified agricultural activities as the main source of heavy metals pollution in tea.
Article
Agronomy
Ya Tian, Limin Xie, Mingyang Wu, Biyun Yang, Captoline Ishimwe, Dapeng Ye, Haiyong Weng
Summary: This study evaluated the potential of multicolor fluorescence imaging combined with PCA and SVM for early detection of salt stress in plants. By analyzing Arabidopsis with this method, it was proven that multicolor fluorescence imaging can effectively differentiate control and salt-stressed plants, providing an important tool for monitoring and studying plant stress.
Article
Environmental Sciences
Yue Yang, Xu Shang, Zheng Chen, Kun Mei, Zhenfeng Wang, Randy A. Dahlgren, Minghua Zhang, Xiaoliang Ji
Summary: A support vector regression (SVR) model was developed to predict nitrogen isotopic composition of nitrate in water bodies, outperforming multivariate linear regression and general regression neural network models in terms of accuracy.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Multidisciplinary Sciences
Zhijiang Lou, Youqing Wang, Shan Lu, Pei Sun
Summary: A new method called minimalist module analysis (MMA) is proposed in this study to address the issue of redundant correlations between process variables in traditional multivariate statistical-based process monitoring (MSPM) methods. Simulation tests demonstrate that MMA achieves superior performance in fault detection and localization.
SCIENTIFIC REPORTS
(2021)
Article
Engineering, Biomedical
Sahar Ramezani Moghadam, Babak Mohammadzadeh Asl
Summary: Electrocardiogram (ECG) is used to detect myocardial infarction (MI) by extracting morphological features from ECG signals. A random forest classifier with 100 trees is used for classification and feature selection. The proposed method achieves improved results in detecting and localizing MI compared to the state-of-the-art, with high accuracy, sensitivity, specificity, positive predictive value, and F-score.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Biomedical
Sibghatullah Khan, Ram Bilas Pachori
Summary: A novel methodology for posterior myocardial infarction (PMI) detection using Fourier-Bessel series expansion based empirical wavelet transform (FBSEEWT) was proposed in this study. The derived VCG signals were analyzed using decision tree (DT), support vector machine (SVM), and K-nearest neighbor (KNN) classifiers, achieving an overall classification accuracy of 97.92%. This method shows potential for accurate and robust PMI detection in clinical settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Letter
Cardiac & Cardiovascular Systems
Patrizio Pascale, Anna Giulia Pavon, Jan Bogaert, Johan Bennett, Pierre Monney, Olivier Muller, Juerg Schwitter, Pier Giorgio Masci
Summary: ST-segment elevation in the anterior precordial leads is a hallmark of anterior myocardial infarction, but in rare cases it can be caused by isolated infarction of the right ventricle. This study aimed to provide clues for recognizing and understanding this diagnostic pitfall through the analysis of 4 patients with STE in the anterior leads.
CLINICAL RESEARCH IN CARDIOLOGY
(2021)
Article
Environmental Sciences
Susmita Goswami, Abhishek K. Rai
Summary: This study examined the spatial variation of groundwater quality in the coastal state of Odisha by analyzing twelve major hydro-geochemical parameters derived from water samples. The results classified different types of groundwater and identified plausible sources that control water quality in the region using cluster analysis and principal component analysis. The concentration of major ions was found to vary in a specific order. The study also assessed the Water Quality Index and examined the sodium absorption ratio and Kelly's ratio. The findings revealed that a significant portion of the groundwater samples had low to medium salinity and were suitable for irrigation. Mining activities were less likely to impact subsurface water quality. Water-rock interactions and evaporation-crystallization were identified as the dominant factors controlling groundwater away from the coastal areas.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2022)
Article
Behavioral Sciences
Claudia C. Schmidt, Elisabeth I. S. Achilles, Gereon R. Fink, Peter H. Weiss
Summary: Apraxia is a multi-componential syndrome characterized by deficits in higher motor functions, primarily caused by left hemisphere lesions. This study analyzed different profiles of apraxia and related motor-cognitive processes following LH stroke, revealing specific lesion patterns associated with various components. The results suggest that apraxia represents impaired motor-cognitive processes that partially dissociate from language processes and are associated with distinct lesion patterns following LH stroke.
Article
Engineering, Electrical & Electronic
Vinod Kumar, Musheer Ahmad, Adesh Kumari, Saru Kumari, M. K. Khan
Summary: Vehicular cloud computing is a new area of research that equips vehicles with networking and sensing capacities to improve vehicle-to-vehicle or vehicle-to-infrastructure communication, which is beneficial for traffic management and road safety. This technology presents a smart structure for vehicular communication, maintaining autonomous traffic, improved vehicle control, and enhanced system security.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Dheerendra Mishra, Vinod Kumar, Dharminder Dharminder, Saurabh Rana
IET INTELLIGENT TRANSPORT SYSTEMS
(2020)
Article
Telecommunications
Vinod Kumar, Musheer Ahmad, Dheerendra Mishra, Saru Kumari, Muhammad Khurram Khan
VEHICULAR COMMUNICATIONS
(2020)
Article
Computer Science, Information Systems
Adesh Kumari, Srinivas Jangirala, M. Yahya Abbasi, Vinod Kumar, Mansaf Alam
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2020)
Article
Computer Science, Information Systems
Vinod Kumar, Rajendra Kumar, S. K. Pandey
Summary: The paper proposed a key distribution protocol based on the Chinese Remainder Theorem that significantly reduced computational complexity, increased security, improved efficiency in handling large groups, and effectively prevented illegal access.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Vinod Kumar, Rajendra Kumar, S. K. Pandey
Summary: Smart Grid is a modernized power grid system that requires a secure and robust key management scheme to ensure confidentiality during communication in the Advanced Metering Infrastructure (AMI). This paper proposes a tailored key management scheme for Home Area Networks (HAN) in AMI, which significantly reduces rekeying overhead and enhances privacy protection.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Akber Ali Khan, Vinod Kumar, Musheer Ahmad, Saurabh Rana
Summary: The development of IoT technology presents new challenges for smart grid systems. To enhance security and privacy in smart grids, lightweight authentication and key agreement protocols are proposed. Analyzing and verifying these new protocols can improve the efficiency of smart grid systems.
JOURNAL OF SYSTEMS ARCHITECTURE
(2021)
Article
Telecommunications
Akber Ali Khan, Vinod Kumar, Musheer Ahmad, B. B. Gupta, Musheer Ahmad, Ahmed A. Abd El-Latif
Summary: This article introduces the two-way communication of the Internet of Energy to address the security, efficiency, and reliability in energy reform. A mutual authenticated key agreement framework is proposed in the vehicle-grid system using elliptic curve cryptography and hash function to maintain secure communication with reliable computation and communication costs. The proposed protocol is shown to be secure through formal and informal methods, and is more efficient in terms of computation and communication costs compared to related protocols in the same environment.
TELECOMMUNICATION SYSTEMS
(2021)
Article
Computer Science, Hardware & Architecture
Vinod Kumar, Mahmoud Shuker Mahmoud, Ahmed Alkhayyat, Jangirala Srinivas, Musheer Ahmad, Adesh Kumari
Summary: This article presents a secure and lightweight authentication scheme (RAPCHI) for Internet of medical Things (IoMT) in cloud-healthcare infrastructure (CHI) during a pandemic. The proposed framework provides resistance against various security threats and is compared to existing frameworks, demonstrating its superiority in terms of security, computation, and communication. The formal security analysis and simulation tests validate RAPCHI's security against man-in-the-middle and replay attacks.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Chemistry, Analytical
Vikas Kumar, Rahul Kumar, Akber Ali Khan, Vinod Kumar, Yu-Chi Chen, Chin-Chieh Chang
Summary: The Internet of Things (IoT) is a future trend that connects physical things with the cyber world through the Internet. While IoT technology brings convenience to our daily lives, it also poses security and privacy risks, particularly in RFID-tag-connected devices. To address these concerns, we propose a robust authentication framework for IoT-based RFID infrastructure, which satisfies all security requirements and improves communication performance.
Article
Computer Science, Information Systems
Akber Ali Khan, Vinod Kumar, Musheer Ahmad
Summary: Smart grid adjusts power generation by supervising consumer behavior and promoting cultural heritage. Ensuring environmental security and privacy are key concerns in smart systems, with authentication protocols enabling secure communication.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Telecommunications
Akber Ali Khan, Vinod Kumar, Jangirala Srinivas, Saru Kumari, Mridul Kumar Gupta
Summary: This article presents a secure and efficient architecture for satellite network systems using elliptic curve cryptography and a hash function. The proposed protocol ensures secure communication and key agreement, and is resistant to various security threats. It also includes different security features and capabilities, and allows easy password updates. The random oracle model is used to demonstrate its security, and security verification is performed against man in the middle and replay attacks using AVISPA software. The proposed protocol is shown to have lower computation and transmission overhead compared to competing methods.
TELECOMMUNICATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Akber Ali Khan, Vinod Kumar, Musheer Ahmad, Srinivas Jangirala
Summary: This paper proposes a key agreement and authentication framework for vehicular to grid networks based on elliptic curve cryptography and the hash function, aiming to achieve secure and efficient communication in the Energy Internet.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Vinod Kumar, Ammar Mohammed Ali Al-Tameemi, Adesh Kumari, Musheer Ahmad, Mayadah Waheed Falah, Ahmed A. Abd El-Latif
Summary: The Vehicular Cloud Environment (VCE) is a new research field that combines cloud computing and vehicular networks to enable communication between vehicles and roadside infrastructure. A hybrid technical solution utilizing vehicle resources, cloud infrastructure, and IoT is necessary for effective vehicular communication networking. Security and privacy are significant challenges in VCE due to the integration of unknown vehicles and infrastructure via the public network. In this regard, we propose a provably secure authentication system for VCE employing smartphones. The proposed system demonstrates both security and efficiency in terms of communication and processing overhead.
Article
Computer Science, Information Systems
Samiulla Itoo, Akber Ali Khan, Vinod Kumar, Ahmed Alkhayyat, Musheer Ahmad, Jangirala Srinivas
Summary: In the traditional medical healthcare system, sharing patient data is challenging. Blockchain technology and cloud computing can address this issue and provide better privacy and security.
Article
Computer Science, Artificial Intelligence
Jin Zhang, Zekang Bian, Shitong Wang
Summary: This study proposes a novel style linear k-nearest neighbor method to extract stylistic features using matrix expressions and improve the generalizability of the predictor through style membership vectors.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qifeng Wan, Xuanhua Xu, Jing Han
Summary: In this study, we propose an innovative approach for dimensionality reduction in large-scale group decision-making scenarios that targets linguistic preferences. The method combines TF-IDF feature similarity and information loss entropy to address challenges in decision-making with a large number of decision makers.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Hegui Zhu, Yuchen Ren, Chong Liu, Xiaoyan Sui, Libo Zhang
Summary: This paper proposes an adversarial attack method based on frequency information, which optimizes the imperceptibility and transferability of adversarial examples in white-box and black-box scenarios respectively. Experimental results validate the superiority of the proposed method and its application in real-world online model evaluation reveals their vulnerability.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jing Tang, Xinwang Liu, Weizhong Wang
Summary: This paper proposes a hybrid generalized TODIM approach in the Fine-Kinney framework to evaluate occupational health and safety hazards. The approach integrates CRP, dynamic SIN, and PLTSs to handle opinion interactions and incomplete opinions among decision makers. The efficiency and rationality of the proposed approach are demonstrated through a numerical example, comparison, and sensitivity studies.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Shigen Shen, Chenpeng Cai, Zhenwei Li, Yizhou Shen, Guowen Wu, Shui Yu
Summary: To address the damage caused by zero-day attacks on SIoT systems, researchers propose a heuristic learning intrusion detection system named DQN-HIDS. By integrating Deep Q-Networks (DQN) into the system, DQN-HIDS gradually improves its ability to identify malicious traffic and reduces resource workloads. Experiments demonstrate the superior performance of DQN-HIDS in terms of workload, delayed sample queue, rewards, and classifier accuracy.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
Summary: In this paper, we propose a Chinese text classification algorithm based on deep active learning for the power system, which addresses the challenge of specialized text classification. By applying a hierarchical confidence strategy, our model achieves higher classification accuracy with fewer labeled training data.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Kaan Deveci, Onder Guler
Summary: This study proves the lack of robustness in nonlinear IF distance functions for ranking intuitionistic fuzzy sets (IFS) and proposes an alternative ranking method based on hypervolume metric. Additionally, the suggested method is extended as a new multi-criteria decision making method called HEART, which is applied to evaluate Turkey's energy alternatives.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Fu-Wing Yu, Wai-Tung Ho, Chak-Fung Jeff Wong
Summary: This research aims to enhance the energy management in commercial building air-conditioning systems, specifically focusing on chillers. Ridge regression is found to outperform lasso and elastic net regression when optimized with the appropriate hyperparameter, making it the most suitable method for modeling the system coefficient of performance (SCOP). The key variables that strongly influence SCOP include part load ratios, the operating numbers of chillers and pumps, and the temperatures of chilled water and condenser water. Additionally, July is identified as the month with the highest potential for performance improvement. This study introduces a novel approach that balances feature selection, model accuracy, and optimal tuning of hyperparameters, highlighting the significance of a generic and simplified chiller system model in evaluating energy management opportunities for sustainable operation. The findings from this research can guide future efforts towards more energy-efficient and sustainable operations in commercial buildings.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Xiaoyan Chen, Yilin Sun, Qiuju Zhang, Xuesong Dai, Shen Tian, Yongxin Guo
Summary: In this study, a method for dynamically non-destructive grasping of thin-skinned fruits is proposed. It utilizes a multi-modal depth fusion convolutional neural network for image processing and segmentation, and combines the evaluation mechanism of optimal grasping stability and the forward-looking non-destructive grasp control algorithm. The proposed method greatly improves the comprehensive performance of grasping delicate fruits using flexible hands.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Yuxuan Yang, Siyuan Zhou, He Weng, Dongjing Wang, Xin Zhang, Dongjin Yu, Shuiguang Deng
Summary: The study proposes a novel model, POIGDE, which addresses the challenges of data sparsity and elusive motives by solving graph differential equations to capture continuous variation of users' interests. The model learns interest transference dynamics using a time-serial graph and an interval-aware attention mechanism, and applies Siamese learning to directly learn from label representations for predicting future POI visits. The model outperforms state-of-the-art models on real-world datasets, showing potential in the POI recommendation domain.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
S. Karthika, P. Rathika
Summary: The widespread development of monitoring devices in the power system has generated a large amount of power consumption data. Storing and transmitting this data has become a significant challenge. This paper proposes an adaptive data compression algorithm based on the discrete wavelet transform (DWT) for power system applications. It utilizes multi-objective particle swarm optimization (MO-PSO) to select the optimal threshold. The algorithm has been tested and outperforms other existing algorithms.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Jiaqi Guo, Haiyan Wu, Xiaolei Chen, Weiguo Lin
Summary: In this study, an adaptive SV-Borderline SMOTE-SVM algorithm is proposed to address the challenge of imbalanced data classification. The algorithm maps the data into kernel space using SVM and identifies support vectors, then generates new samples based on the neighbors of these support vectors. Extensive experiments show that this method is more effective than other approaches in imbalanced data classification.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Qiumei Zheng, Linkang Xu, Fenghua Wang, Yongqi Xu, Chao Lin, Guoqiang Zhang
Summary: This paper proposes a new semantic segmentation network model called HilbertSCNet, which combines the Hilbert curve traversal and the dual pathway idea to design a new spatial computation module to address the problem of loss of information for small targets in high-resolution images. The experiments show that the proposed network performs well in the segmentation of small targets in high-resolution maps such as drone aerial photography.
APPLIED SOFT COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Mojtaba Ashour, Amir Mahdiyar
Summary: Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making problems, but the sheer number of AHP methods presents challenges for scholars and practitioners in selecting the most suitable method. This paper reviews articles published between 2010 and 2023 proposing hybrid, improved, or modified AHP methods, classifies them based on their contributions, and provides a comprehensive summary table and roadmap to guide the method selection process.
APPLIED SOFT COMPUTING
(2024)
Review
Computer Science, Artificial Intelligence
Gerardo Humberto Valencia-Rivera, Maria Torcoroma Benavides-Robles, Alonso Vela Morales, Ivan Amaya, Jorge M. Cruz-Duarte, Jose Carlos Ortiz-Bayliss, Juan Gabriel Avina-Cervantes
Summary: Electric power system applications are complex optimization problems. Most literature reviews focus on studying electrical paradigms using different optimization techniques, but there is a lack of review on Metaheuristics (MHs) in these applications. Our work provides an overview of the paradigms underlying such applications and analyzes the most commonly used MHs and their search operators. We also discover a strong synergy between the Renewable Energies paradigm and other paradigms, and a significant interest in Load-Forecasting optimization problems. Based on our findings, we provide helpful recommendations for current challenges and potential research paths to support further development in this field.
APPLIED SOFT COMPUTING
(2024)