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A Survey of Artificial Hummingbird Algorithm and Its Variants: Statistical Analysis, Performance Evaluation, and Structural Reviewing

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Archives of Computational Methods in Engineering 2025年第1期32卷 269-310页

作者： Hosseinzadeh, Mehdi Rahmani, Amir Masoud Husari, Fatimatelbatoul Mahmoud Alsalami, Omar Mutab Marzougui, Mehrez Nguyen, Gia Nhu Lee, Sang-Woong Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer Engineering College of Computer Science King Khalid University Abha61413 Saudi Arabia School of Computer Science Duy Tan University Da Nang Viet Nam Pattern Recognition and Machine Learning Lab Gachon University 1342 Seongnamdaero Sujeonggu Seongnam13120 Korea Republic of

In the last few decades, metaheuristic algorithms that use the laws of nature have been used dramatically in numerous and complex optimization problems. The artificial hummingbird algorithm (AHA) is one of the metaheuristic algorithms that was invented in 2022 based on the foraging and migration behavior of the hummingbird for modeling and solving optimization problems. The algorithm initially starts with an initial random population of solutions. It then uses iterative processes and hummingbird position updates to balance exploration and exploitation toward the most optimal solutions. This paper has a detailed and extensive review of the AHA algorithm considering the aspects of hybrid, improved, binary, multi-objective, and optimization problems. In addition, a wide range of applications of AHA in various fields such as feature selection, image processing, scheduling, Internet of Things, classification, clustering, financial and economic issues, forecasting, wireless sensor networks, and many engineering challenges are explored. The statistical and numerical results showed that the AHA algorithm with deep learning methods, Levy flight, and opposition-based learning had the best performance. Also, the AHA algorithm is most widely used in solving multimodal optimization problems and continuous functions. © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2024.

关键词： Optimization

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Automated Pipeline for Regional Epicardial Adipose Tissue Distribution Analysis in the Left Atrium

Automated Pipeline for Regional Epicardial Adipose Tissue Di...

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15th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2024, Held in Conjunction with MICCAI 2024

作者： Lluch, Èric Castañeda, Eduardo Weiss, Maximilian E. R. Vizitiu, Anamaria Jacob, Athira Jami, Jitin Audigier, Chloé Meister, Felix Mihalef, Viorel Passerini, Tiziano Siemens Healthineers Digital Technologies and Innovation Erlangen Germany Pattern Recognition Lab Department of Computer Science Friedrich-Alexander University Erlangen-Nürnberg Erlangen Germany Siemens SRL Brasov Romania Siemens Healthineers Digital Technology and Innovation Princeton United States Machine-Learning and Data Analytics Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Advanced Clinical Imaging Technology Siemens Healthineers AG Lausanne Switzerland

ISBN: (纸本)9783031877551

Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting approximately 3% of the global population and rising to 11% in individuals over 80 years old. The distribution of epicardial adipose tissue (EAT) around the atria plays a significant role in the pathophysiology of AF, yet its regional analysis remains underexplored. This paper introduces an automated pipeline capable of segmenting 14 atrial regions from patient CT angiograms, a notable advancement over previous attempts to automate the creation of synthetic anatomical or physics-based twins. Our fully automatic pipeline requires no human supervision and provides the regional EAT quantification successfully on 91.9% of the analyzed patients for which the LA and its structures were automatically segmented (1797 out of 1954 patients), including the automatic segmentation of the aorta and pericardium to assess EAT volume around the left atrium. By applying principal component analysis of the regional EAT to analyze a separate dataset of 84 individuals who were clinically labeled, we identified a distinct group that contained all the patients with AF. This finding suggests that there is a significant link between the pattern of fat distribution and AF. This novel approach has the potential to enhance our understanding of AF and improve patient outcomes by enabling large-scale, regional fat analysis in an automated manner on all patients with accurate segmentation of left atrial structures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Principal component analysis

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6G-Enabled Internet of Things:Vision,Techniques,and Open Issues

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Computer Modeling in Engineering & Sciences 2022年第12期133卷 509-556页

作者： Mehdi Hosseinzadeh Atefeh Hemmati Amir Masoud Rahmani Pattern Recognition and Machine Learning Lab Gachon UniversitySeongnam13120Korea Department of Computer Engineering Science and Research BranchIslamic Azad UniversityTehran***Iran Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

There are changes in the development of wireless technology systems every decade.6G(sixth generation)wireless networks improve on previous generations by increasing dependability,accelerating networks,increasing available bandwidth,decreasing latency,and increasing data transmission speed to standardize communication *** purpose of this article is to comprehend the current directions in 6G studies and their relationship to the Internet of Things(IoT).Also,this paper discusses the impacts of 6G on IoT,critical requirements and trends for 6G-enabled IoT,new service classes of 6G and IoT technologies,and current 6G-enabled IoT studies selected by the systematic literature review(SLR)method published from 2018 to *** addition,we present a technical taxonomy for the classification of 6G-enabled IoT,which includes self-organization systems,energy efficiency,channel assessment,and ***,according to the articles reviewed,we consider the evaluation factors in this domain,including data transmission,delay,energy consumption,and ***,we focus on open issues and future research challenges in 6G-enabled *** mention important future challenges and directions,we can point to migration,data storage,data resource,data security,data sharing,data offloading,availability,scalability,portability,user experience,reliability,authentication,and authorization.

关键词： Internet of Things 6G wireless network machine learning artificial intelligence

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Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

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Computers, Materials & Continua 2022年第6期71卷 5603-5618页

作者： Shahid Mehmood Imran Ahmad Muhammad Adnan Khan Faheem Khan T.Whangbo Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Education sector has witnessed several changes in the recent *** changes have forced private universities into fierce competition with each other to get more students *** competition has resulted in the adoption of marketing practices by private universities similar to commercial *** get competitive gain,universities must observe and examine the students’feedback on their own social media sites along with the social media sites of their *** study presents a novel framework which integrates numerous analytical approaches including statistical analysis,sentiment analysis,and text mining to accomplish a competitive analysis of social media sites of the *** techniques enable local universities to utilize social media for the identification of the most-discussed topics by students as well as based on the most unfavorable comments received,major areas for improvement.A comprehensive case study was conducted utilizing the proposed framework for competitive analysis of few top ranked international universities as well as local private universities in Lahore *** results show that diversity of shared content,frequency of posts,and schedule of updates,are the key areas for improvement for the local *** on the competitive intelligence gained several recommendations are included in this paper that would enable local universities generally and Riphah international university(RIU)Lahore specifically to promote their brand and increase their attractiveness for potential students using social media and launch successful marketing campaigns targeting a large number of audiences at significantly reduced cost resulting in an increased number of enrolments.

关键词： Social media higher education sentiment analysis content analysis competitive analysis text mining

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labeling, cutting, grouping: An efficient text line segmentation method for medieval manuscripts 15

Labeling, cutting, grouping: An efficient text line segmenta...

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15th IAPR International Conference on Document Analysis and recognition, ICDAR 2019

作者： Alberti, Michele Vogtlin, Lars Pondenkandath, Vinaychandran Seuret, Mathias Ingold, Rolf Liwicki, Marcus University of Fribourg Switzerland Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Machine Learning Group Luleå University of Technology Sweden

ISBN: (纸本)9781728128610

This paper introduces a new way for text-line extraction by integrating deep-learning based pre-classification and state-of-the-art segmentation methods. Text-line extraction in complex handwritten documents poses a significant challenge, even to the most modern computer vision algorithms. Historical manuscripts are a particularly hard class of documents as they present several forms of noise, such as degradation, bleed-through, interlinear glosses, and elaborated scripts. In this work, we propose a novel method which uses semantic segmentation at pixel level as intermediate task, followed by a text-line extraction step. We measured the performance of our method on a recent dataset of challenging medieval manuscripts and surpassed state-of-the-art results by reducing the error by 80.7%. Furthermore, we demonstrate the effectiveness of our approach on various other datasets written in different scripts. Hence, our contribution is two-fold. First, we demonstrate that semantic pixel segmentation can be used as strong denoising pre-processing step before performing text line extraction. Second, we introduce a novel, simple and robust algorithm that leverages the high-quality semantic segmentation to achieve a text-line extraction performance of 99.42% line IU on a challenging dataset. © 2019 IEEE.

关键词： Semantic Segmentation

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Emotion Based Signal Enhancement Through Multisensory Integration Using machine learning

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Computers, Materials & Continua 2022年第6期71卷 5911-5931页

作者： Muhammad Adnan Khan Sagheer Abbas Ali Raza Faheem Khan T.Whangbo Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming *** is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place,the signal having more strength under the influence of emotions effects the response *** research inmultisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or ***,there is a need to integrate the emotional state of the agent with incoming stimuli for signal enhancement or *** this study,two different neural network-based learning algorithms have been employed to learn the impact of emotions on signal enhancement or *** was observed that the performance of a proposed system for multisensory integration increases when emotion features were present during enhancement or depression of multisensory signals.

关键词： Multisensory integration sensory enhancement depression emotions

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Resource Management approaches to Internet of Vehicles

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Multimedia Tools and Applications 2023年第30期82卷 46811-46844页

作者： Hosseinzadeh, Mehdi Abbasi, Shirin Rahmani, Amir Masoud Pattern Recognition and Machine Learning Lab Gachon University 1342 Seongnamdaero Sujeonggu Seongnam13120 Korea Republic of Computer Engineering Department Science and Research Branch Islamic Azad University Tehran Iran Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan

The Internet of Vehicles (IoV) has become a significant issue in designing smart cities. Many applications and services are provided in IoV for various purposes. They need the resources for the computation and data collection. One of the open issues in IoV is resource management because of resource limitation, resource heterogeneity, and dynamic networks. To our knowledge, no systematic and thorough research in resource management methodologies was conducted in IoV, despite the critical nature of resource management challenges. This paper analyzes the recently published studies on resource management in IoV. Our analysis shows that resource allocation has the most utilization rate of resource management approaches at 30%. The most critical parameter in resource allocation is cost, which includes energy, time, price, and processing capacity. The analytical reports show those cost parameters have the most evaluation in the approaches by 19%. Furthermore, we propose a taxonomy for resource management in IoV and extract challenges and open issues in this field. It can be a start point to suggest new methods for resource management in IoV. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Resource allocation

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A survey of historical document image datasets

A survey of historical document image datasets

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作者： Nikolaidou, Konstantina Seuret, Mathias Mokayed, Hamam Liwicki, Marcus EISLAB Machine Learning Group Luleå University of Technology Aurorum 1 Norrbotten Luleå97187 Sweden Pattern Recognition Lab Computer Vision Group Friedrich-Alexander-Universität Martensstr. 3 Bavaria Erlangen91058 Germany

This paper presents a systematic literature review of image datasets for document image analysis, focusing on historical documents, such as handwritten manuscripts and early prints. Finding appropriate datasets for historical document analysis is a crucial prerequisite to facilitate research using different machine learning algorithms. However, because of the very large variety of the actual data (e.g., scripts, tasks, dates, support systems, and amount of deterioration), the different formats for data and label representation, and the different evaluation processes and benchmarks, finding appropriate datasets is a difficult task. This work fills this gap, presenting a meta-study on existing datasets. After a systematic selection process (according to PRISMA guidelines), we select 65 studies that are chosen based on different factors, such as the year of publication, number of methods implemented in the article, reliability of the chosen algorithms, dataset size, and journal outlet. We summarize each study by assigning it to one of three pre-defined tasks: document classification, layout structure, or content analysis. We present the statistics, document type, language, tasks, input visual aspects, and ground truth information for every dataset. In addition, we provide the benchmark tasks and results from these papers or recent competitions. We further discuss gaps and challenges in this domain. We advocate for providing conversion tools to common formats (e.g., COCO format for computer vision tasks) and always providing a set of evaluation metrics, instead of just one, to make results comparable across studies. © 2022, The Author(s).

关键词： Deterioration

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A fire hawk optimizer-based energy-efficient clustering scheme in underwater acoustic sensor networks (UASNs)

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Ad Hoc Networks 2025年 176卷

作者： Sang-Woong Lee Musaed Alhussein Khursheed Aurangzeb Mohammad Sadegh Yousefpoor Efat Yousefpoor Mehdi Hosseinzadeh Pattern Recognition and Machine Learning Lab School of Computing Gachon University Seongnam 13120 Republic of Korea Department of Computer Engineering College of Computer and Information Sciences King Saud University P.O. Box 51178 Riyadh 11543 Saudi Arabia Center of Research and Strategic Studies Lebanese French University Kurdistan Region Iraq School of Computer Science Duy Tan University Da Nang Vietnam Jadara Research Center Jadara University Irbid 21110 Jordan

An underwater acoustic sensor network (UASN) is suitable for gathering data from aquatic environments, including lakes, rivers, seas, and oceans. This network faces several issues due to the distinct features of underwater environments and the limitations of acoustic channels. These challenges include energy limitations, unreliable communication links, and dynamic network topologies. Additionally, the difficulty of recharging or replacing batteries in underwater conditions makes energy optimization essential for prolonging the network lifespan. Currently, many energy-efficient approaches in UASNs emphasize node clustering and multi-hop communication, but most of these methods rely on distributed algorithms. This paper introduces a novel energy-efficient clustering framework called FHOEEC ( F ire H awk O ptimization-based E nergy- E fficient C lustering), which integrates both distributed and centralized strategies. The clustering process is divided into three stages: (1) cluster formation, (2) selection of cluster heads, and (3) cluster maintenance. During the periodic neighbor discovery phase, FHOEEC examines two key aspects: the format of the hello packet and its propagation process. FHOEEC aims to create an energy-efficient, cluster-based network structure. To achieve this, the sink node utilizes the fire hawk optimization (FHO) algorithm to decide on the optimal range and number of clusters. To establish these clusters, a fitness function considers a weighted combination of three sub-functions: intra-cluster and inter-cluster distances, the proportion of isolated clusters compared to others, and cluster density. In the final stage, intra-cluster and inter-cluster communication paths are established by focusing on energy balance. This ensures that nodes with energy levels below a specified threshold are excluded from serving as intermediate nodes. Simulation results and performance evaluations show that FHOEEC outperforms three existing clustering methods–CCCS, G

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Intelligent Model for Predicting the Quality of Services Violation

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Computers, Materials & Continua 2022年第5期71卷 3607-3619页

作者： Muhammad Adnan Khan Asma Kanwal Sagheer Abbas Faheem Khan T.Whangbo Pattern Recognition and Machine Learning Lab. Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Cloud computing is providing IT services to its customer based on Service level agreements(SLAs).It is important for cloud service providers to provide reliable Quality of service(QoS)and to maintain SLAs *** service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for *** users’major concerns;the factors for service reliability are based on response time,accessibility,availability,and *** this paper,we,therefore,experiment with the parallel mutant-Particle swarm optimization(PSO)for the detection and predictions of QoS violations in terms of response time,speed,accessibility,and *** paper also compares Simple-PSO and Parallel *** simulation results,it is observed that the proposed Parallel MutantPSO solution for cloud QoS violation prediction achieves 94%accuracy which is many accurate results and is computationally the fastest technique in comparison of conventional PSO technique.

关键词： Accountability particle swarm optimization mutant particle swarm optimization quality of service service level agreement

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