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An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

Computer Modeling in Engineering & Sciences 2024年第2期138卷 1051-1075页

作者： Shazia Shamas Surya Narayan Panda Ishu Sharma Kalpna Guleria Aman Singh Ahmad Ali AlZubi Mallak Ahmad AlZubi Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Higher Polytechnic School Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Engineering Universidad Internacional IberoamericanaAreciboPR00613USA Uttaranchal Institute of Technology Uttaranchal UniversityDehradunUttarakhand248007India Computer Science Department King Saud UniversityRiyadhSaudi Arabia Faculty of Medicine Jordan University of Science and TechnologyIrbidJordan

The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis andplanning intervention. This research work addresses the major issues pertaining to the field of medical imageprocessing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposesan improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. Thebetter resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In thisprocess, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarmintelligent techniques. The techniques experimented in this paper are K-means with Artificial Bee Colony (ABC),K-means with Cuckoo Search Algorithm (CSA), K-means with Particle Swarm Optimization (PSO), and Kmeanswith Firefly Algorithm (FFA). The testing and evaluation are performed on Early Lung Cancer ActionProgram (ELCAP) database. The simulation analysis is performed using lung cancer images set against metrics:precision, sensitivity, specificity, f-measure, accuracy,Matthews Correlation Coefficient (MCC), Jaccard, and *** detailed evaluation shows that the K-means with Cuckoo Search Algorithm (CSA) significantly improved thequality of lung cancer segmentation in comparison to the other optimization approaches utilized for lung cancerimages. The results exhibit that the proposed approach (K-means with CSA) achieves precision, sensitivity, and Fmeasureof 0.942, 0.964, and 0.953, respectively, and an average accuracy of 93%. The experimental results prove thatK-meanswithABC,K-meanswith PSO,K-meanswith FFA, andK-meanswithCSAhave achieved an improvementof 10.8%, 13.38%, 13.93%, and 15.7%, respectively, for accuracy measure in comparison to K-means segmentationfor lung cancer images. Further, it is highlighted that the proposed K-means with CSA have achieved a significantimprovement in accuracy, hence can be utilized by resea

关键词： Lesion lung cancer segmentation medical imaging meta-heuristic Artificial Bee Colony(ABC) Cuckoo Search Algorithm(CSA) Particle Swarm Optimization(PSO) Firefly Algorithm(FFA) segmentation

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The FAST all sky HI survey(FASHI):The first release of catalog

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 112-133页

作者： Chuan-Peng Zhang Ming Zhu Peng Jiang Cheng Cheng Jing Wang Jie Wang Jin-Long Xu Xiao-Lan Liu Nai-Ping Yu Lei Qian Haiyang Yu Mei Ai Yingjie Jing Chen Xu Ziming Liu Xin Guan Chun Sun Qingliang Yang Menglin Huang Qiaoli Hao FAST Collaboration Guizhou Radio Astronomical observatory Guizhou UniversityGuiyang 550000China National Astronomical Observatories Chinese Academy of Sciences(CAS)Beijing 100101China Chinese Academy of Sciences South America Center for Astronomy National Astronomical ObservatoriesCASBeijing 100101China Kavli Institute for Astronomy and Astrophysics Peking UniversityBeijing 100871China

The FAST All Sky HI survey(FASHI)was designed to cover the entire sky observable by the Five-hundred-meter Aperture Spherical radio Telescope(FAST),spanning approximately 22000 square degrees of declination between-14°and+66°,and in the frequency range of 1050-1450 MHz,with the expectation of eventually detecting more than 100000 HI *** August 2020 and June 2023,FASHI had covered more than 7600 square degrees,which is approximately 35%of the total sky observable by *** has a median detection sensitivity of around 0.76 m Jy beam-1and a spectral line velocity resolution of~6.4 km s-1at a frequency of~1.4 *** of now,a total of 41741 extragalactic HI sources have been detected in the frequency range 1305.5-1419.5 MHz,corresponding to a redshift limit of z■*** cross-matching FASHI sources with the Siena Galaxy Atlas(SGA)and the Sloan Digital Sky Survey(SDSS)catalogs,we found that 16972(40.7%)sources have spectroscopic redshifts and 10975(26.3%)sources have only photometric *** of the remaining 13794(33.0%)HI sources are located in the direction of the Galactic plane,making their optical counterparts difficult to identify due to high extinction or high contamination of Galactic stellar *** on current survey results,the FASHI survey is an unprecedented blind extragalactic H I *** has higher spectral and spatial resolution and broader coverage than the arecibo Legacy Fast ALFA Survey(ALFALFA).When completed,FASHI will provide the largest extragalactic HI catalog and an objective view of HI content and large-scale structure in the local universe.

关键词： surveys redshifts galaxies telescope radio lines HI line

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Federated Learning on Internet of Things:Extensive and Systematic Review

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Computers, Materials & Continua 2024年第5期79卷 1795-1834页

作者： Meenakshi Aggarwal Vikas Khullar Sunita Rani Thomas AndréProla Shyama Barna Bhattacharjee Sarowar Morshed Shawon Nitin Goyal Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Department of CSE&IT BPS Mahila VishwavidyalayaKhanpur KalanSonipatHaryana131305India Engineering Research&Innovation Group Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaAreciboPR00613USA Department of Project Management Universidade Internacional do CuanzaEstrada Nacional 250Bairro KaluapandaCuito-BiéAngola Department of Computer Science and Engineering University of Science and Technology Chittagong(USTC)Chattogram4202Bangladesh Deptartment of EEE University of Science and Technology Chittagong(USTC)Chattogram4202Bangladesh Department of Computer Science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendragarhHaryana123031India

The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data ***,FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world *** paper systematically reviewed the available literature using the PRISMA guiding *** study aims to provide a detailed overview of the increasing use of FL in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze FL-IoT-based *** was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally *** measures were published in English and with the keywords“FL”and“IoT”.The methodology begins with an overview of recent advances in FL and the IoT,followed by a discussion of how these two technologies can be *** be more specific,we examine and evaluate the capabilities of FL by talking about communication protocols,frameworks and *** then present a comprehensive analysis of the use of FL in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart *** key findings from this analysis of FL IoT services and applications are also ***,we performed a comparative analysis with FL IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)*** concluded that FL has better performance,especially in terms of privacy protection and resource *** is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy *** facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and re

关键词： Internet of Things federated learning PRISMA framework of FL applications of FL data privacy communication

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Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble

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Computers, Materials & Continua 2024年第2期78卷 2047-2066页

作者： Muhammad Rizwan Muhammad Faheem Mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran Ashraf Department of Artificial Intelligence The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Information Technology Khwaja Fareed University of Engineering and ITRYKhan64200Pakistan Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Signal Theory and Communications and Telematic Engineering Unviersity of ValladolidPaseo de Belén 15Valladolid47011Spain Faculty of Social Science and Humanities Universidad Europea del Atlántico Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaCampeche24560México Fundación Universitaria Internacional de Colombia Bogotá111611Colombia Universidad Internacional Iberoamericana AreciboPuerto Rico00613USA Universidade Internacional do Cuanza Cuito46703Angola Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541South Korea

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media *** study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the ***,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic *** baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the *** FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to ***,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual *** proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText *** proposed model better captures the contextual features of the relatively small sample class and aids in the detection of

关键词： Depression classification deep learning FastText machine learning

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An analysis of the scale heights in the lower topside ionosphere based on the arecibo incoherent scatter radar measurements

An analysis of the scale heights in the lower topside ionosp...

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中国科学院地质与地球物理研究所2007学术年会

作者：刘立波 Mike P.Sulzer Institute of Geology and Geophysics Chinese Academy of Sciences arecibo observatory National Astronomy and Ionosphere CenterCornell UniversityAreciboPRUSA.

We statistically analyze the ionospheric scale heights in the lower topside ionosphere based on the electron density(N) and temperature profiles observed from the incoherent scatter radar(ISR) at arecibo(293.2°E,18.3°N),Puerto *** this study,a database containing the arecibo ISR observations from 1966 to 2002 has been used in order to investigate the diurnal and seasonal variations and solar activity dependences of the vertical scale height(VSH),which is deduced from the electron concentration profiles defined as the value of -dh/d(ln(N)),and the effective scale height(H),which is defined as the scale height in the Chapman-αfunction to approximate the N *** a measure of the slope of the height profiles of the topside electron density,the derived VSH and H show marked diurnal and seasonal variations and solar activity dependences. Their features are discussed in terms of thermal structures in the lower topside ionosphere. We also investigate the quantitative relationships between H,VSH,and plasma scale height(H) over *** similarities and differences in these scale heights are *** suggest that both the contributions from topside temperature structure and diffusion processes can also greatly control VSH and H through changing the profile shape.

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The F-region and topside ionosphere response to a strong geomagnetic storm at arecibo

The F-region and topside ionosphere response to a strong geo...

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中国空间科学学会空间物理学专业委员会第十五届全国日地空...

作者： Yun Gong Qihou Zhou Shaodong Zhang Nestor Aponte Michael Sulzer Sixto Gonzalez Electrical and Computer Engineering Department Miami University State Key Laboratory of Space Weather Chinese Academy of Sciences School of Electronic Information Wuhan University School of Electrical Engineering Zhengzhou University arecibo observatory AreciboPuerto RicoUSA

We analyze the data derived from the arecibo incoherent scatter radar to investigate the response of the F-region and topside ionosphere to a strong geomagnetic storm that occurred during the period of August 5-6,*** wind is extremely enhanced at early stage of the *** peak velocity reaches approximately 300 m/s at an altitude of 340 km,which is seldom seen at arecibo *** the storm,large variation of strong meridional wind and electric field controlled and enhanced the vertical ion *** disturbed vertical ion drifts result in large ionospheric perturbations in the F and topside *** collapses have been observed in HmF2 during the storm ***2 rapidly increased after the storm and then dramatically decreased around *** 610 km,the ratio of H+over electron density exhibit increasingly large variation during the course of a night for similar change in vertical ion *** explanation for such a behavior is that vertical transport dominates over charge exchange later at night due to the lower concentration in O+.

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HiFAST:An H?data calibration and imaging pipeline for FAST

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Science China(Physics,Mechanics & Astronomy) 2024年第5期Mechanics & Astronomy) .卷 186-203页

作者： Yingjie Jing Jie Wang Chen Xu Ziming Liu Qingze Chen Tiantian Liang Jinlong Xu Yixian Cao Jing Wang Huijie Hu Chuan-Peng Zhang Qi Guo Liang Gao Mei Ai Hengqian Gan Xuyang Gao Jinlin Han Ligang Hou Zhipeng Hou Peng Jiang Xu Kong Fujia Li Zerui Liu Li Shao Hengxing Pan Jun Pan Lei Qian Jinghai Sun Ningyu Tang Qingliang Yang Bo Zhang Zhiyu Zhang Ming Zhu National Astronomical Observatories Chinese Academy of Sciences Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University School of Astronomy and Space Science University of Chinese Academy of Sciences Guizhou Radio Astronomical observatory Guizhou University Max Planck Institute for Extraterrestrial Physics Kavli Institute for Astronomy and Astrophysics Peking University Institute of Computational Cosmology Department of PhysicsUniversity of Durham CAS Key Laboratory of FAST National Astronomical ObservatoriesChinese Academy of Sciences Deep Space Exploration Laboratory/Department of Astronomy University of Science and Technology of China School of Astronomy and Space Science University of Science and Technology of China Astrophysics Department of PhysicsUniversity of Oxford College of Earth Sciences Guilin University of Technology Department of Physics Anhui Normal University School of Astronomy and Space Science Nanjing University Key Laboratory of Modern Astronomy and Astrophysics Nanjing University

The Five-hundred-meter Aperture Spherical radio Telescope（FAST） has the largest aperture and a 19-beam L-band receiver,making it powerful for investigating the neutral hydrogen atomic gas（H?） in the *** present HiFAST（https://***）,a dedicated,modular,and self-contained calibration and imaging pipeline for processing the H?data of *** pipeline consists of frequency-dependent noise diode calibration,baseline fitting,standing wave removal using an FFT-based method,flux density calibration,stray radiation correction,and gridding to produce data *** modules can be combined as needed to process the data from most FAST observation modes:tracking,drift scanning,On-The-Fly mapping,and most of their *** HiFAST,the root-mean-square（RMS） noises of the calibrated spectra from all 19 beams were only slightly（～5%） higher than the theoretical *** results for the extended source M33 and the point sources are consistent with the results from *** moment maps（0,1 and 2） of M33 agree well with the results from the arecibo Galaxy Environment Survey（AGES） with a fractional difference of less than 10%.For a common sample of 221 sources with signal-to-noise ratio S/N>10 from the arecibo Legacy Fast ALFA（ALFALFA） survey,the mean value of fractional difference in the integrated flux density,Sint,between the two datasets is approximately 0.005%,with a dispersion of 15.4%.Further checks on the integrated flux density of 23 sources with seven observations indicate that the variance in the flux density of the source with luminous objects(Sint>2.5 Jy km s-1) is less than 5%.Our tests suggest that the FAST telescope,with the efficient,precise,and user-friendly pipeline HiFAST,will yield numerous significant scientific findings in the investigation of the H? in the universe.

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HiFAST:An HIdata calibration and imaging pipeline for FAST

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 182-199页

作者： Yingjie Jing Jie Wang Chen Xu Ziming Liu Qingze Chen Tiantian Liang Jinlong Xu Yixian Cao Jing Wang Huijie Hu Chuan-Peng Zhang Qi Guo Liang Gao Mei Ai Hengqian Gan Xuyang Gao Jinlin Han Ligang Hou Zhipeng Hou Peng Jiang Xu Kong Fujia Li Zerui Liu Li Shao Hengxing Pan Jun Pan Lei Qian Jinghai Sun Ningyu Tang Qingliang Yang Bo Zhang Zhiyu Zhang Ming Zhu National Astronomical Observatories Chinese Academy of SciencesBeijing 100012China Institute for Frontiers in Astronomy and Astrophysics Beijing Normal UniversityBeijing 02206China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China Guizhou Radio Astronomical observatory Guizhou UniversityGuiyang 55000China Max Planck Institute for Extraterrestrial Physics Garching 85748Germany Kavli Institute for Astronomy and Astrophysics Peking UniversityBeijing 100871China Institute of Computational Cosmology Department of PhysicsUniversity of DurhamDurham DHI 3LEUK CAS Key Laboratory of FAST National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Deep Space Exploration Laboratory/Department of Astronomy University of Science and Technology of ChinaHefei 230026China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China Astrophysics Department of PhysicsUniversity of OxfordOxford OX/3RHUK College of Earth Sciences Guilin University of TechnologyGuilin 541004China Department of Physics Anhui Normal UniversityWuhu 241002China School of Astronomy and Space Science Nanjing UniversityNanjing 210023China Key Laboratory of Modern Astronomy and Astrophysics Nanjing UniversityNanjing 20023China

The Five-hundred-meter Aperture Spherical radio Telescope(FAST)has the largest aperture and a 19-beam L-band receiver,making it powerful for investigating the neutral hydrogen atomic gas(HI)in the *** present HiFAST(https://***),a dedicated,modular,and self-contained calibration and imaging pipeline for processing the H?data of *** pipeline consists of frequency-dependent noise diode calibration,baseline fitting,standing wave removal using an FFT-based method,flux density calibration,stray radiation correction,and gridding to produce data *** modules can be combined as needed to process the data from most FAST observation modes:tracking,drift scanning,On-The-Fly mapping,and most of their *** HiFAST,the root-mean-square(RMS)noises of the calibrated spectra from all 19 beams were only slightly(~5%)higher than the theoretical *** results for the extended source M33 and the point sources are consistent with the results from *** moment maps(0,1 and 2)of M33 agree well with the results from the arecibo Galaxy Environment Survey(AGES)with a fractional difference of less than 10%.For a common sample of 221 sources with signal-to-noise ratio S/N>10 from the arecibo Legacy Fast ALFA(ALFALFA)survey,the mean value of fractional difference in the integrated flux density,Sint,between the two datasets is approximately 0.005%,with a dispersion of 15.4%.Further checks on the integrated flux density of 23 sources with seven observations indicate that the variance in the flux density of the source with luminous objects(Sint>2.5 Jy km s-1)is less than 5%.Our tests suggest that the FAST telescope,with the efficient,precise,and user-friendly pipeline HiFAST,will yield numerous significant scientific findings in the investigation of the H?in the universe.

关键词： fractional luminous correction

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大型天文设备管理中的大学与工商业合作(英文)

大型天文设备管理中的大学与工商业合作(英文)

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第十五届中国科协年会——500米口径球面射电望远镜与地...

作者： Juan F.Arratia Student Research Development Center Ana G.Mendez University System arecibo observatory

Introduction:The management of a Large Astronomical Facility is a very critical component in the development of the region where is *** case study of the arecibo observatory in Puerto Rico can give us a reference for the FAST facility in Qiannan Buyi and Miao Autonomous *** presentation started with visualizing the location of Puerto Rico in the middle of the Caribbean region,two hour flying time from Miami in the US *** territory is only

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永远的阿雷西博天文台

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飞碟探索 2020年第6期 104-109页

作者：本刊编辑部 arecibo observatory a facility of the NSF

2020年11月初,全世界的科学家都在屏息等待,为天文学界最著名的望远镜之一——拥有近60年历史的阿雷西博天文台(arecibo observatory)的命运而挂心,不知它是否能够幸存下来——2根用以支撑结构的电缆相继损坏,工程师们一直在焦灼地寻找...

2020年11月初,全世界的科学家都在屏息等待,为天文学界最著名的望远镜之一——拥有近60年历史的阿雷西博天文台(arecibo observatory)的命运而挂心,不知它是否能够幸存下来——2根用以支撑结构的电缆相继损坏,工程师们一直在焦灼地寻找一种安全的方法来修理它。

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