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Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

Journal of Bionic Engineering 2024年第1期21卷 447-485页

作者： Sanjay Bhardwaj Da-Hye Kim Dong-Seong Kim Department of IT Convergence Engineering ICT Convergence Research CenterKumoh National Institute of TechnologyGumiSouth Korea

In industrial wireless networks,data transmitted from source to destination are highly *** often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet ***,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless *** term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for *** a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base *** includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue *** features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue *** analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and *** results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC ***,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ***,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other *** results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet *** proposed a

关键词： Dragonfly Damselfly Interaction Queuing delay Optimization Industrial wireless networks

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Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1729-1755页

作者： Awais Khan Chomyong Kim Jung-Yeon Kim Ahsan Aziz Yunyoung Nam Department of ict Convergence Soonchunhyang UniversityAsan31538Korea ict Convergence Research center Soonchunhyang UniversityAsan31538Korea Emotional and Intelligent Child Care Convergence Research center Soonchunhyang UniversityAsan31538Korea

Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by *** posture assessment remains challenging because of the complex nature of the human body and variations in sleep ***,this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification,thereby enhancing the analysis of body position and *** method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras,which depict six commonly adopted postures:supine,left log,right log,prone head,prone left,and prone *** study involves 10 participants under two conditions:with and without ***,the database is normalized into a video *** subsequent step entails training a fine-tuned,pretrained Visual Geometry Group(VGG16)and ResNet50 *** the third phase,the extracted features are utilized for *** fourth step of the proposed approach employs a serial fusion technique based on the normal distribution to merge the vectors derived from both the RGB and thermal ***,the fused vectors are passed to machine learning classifiers for final *** dataset,which includes human sleep postures used in this study’s experiments,achieved a 96.7%accuracy rate using the Quadratic Support Vector Machine(QSVM)without the ***,the Linear SVM,when utilized with a blanket,attained an accuracy of 96%.When normal distribution serial fusion was applied to the blanket features,it resulted in a remarkable average accuracy of 99%.

关键词： Human sleep posture VGG16 deep learning ResNet50 fusion machine learning

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Quantitative and qualitative research on service quality evaluation system in NGN

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The Journal of China Universities of Posts and Telecommunications 2009年第5期16卷 71-77页

作者： LIU Lu ZHOU Wen-an SONG Jun-de ict and ssme center Beijing University of Posts and Telecommunications Beijing 100876 China

With the development of next generation network （NGN）, reasonable service quality evaluation is essential in network management. Based on NGN service characteristics, this article presents a comprehensive service quality evaluation system from two perspectives： quantitative and qualitative. From the quantitative point of view, this article brings forward the normalized service level achievement function （NSLA function） at technical layer. Also, with mean opinion score （MOS） mode, it proposes customer satisfaction assessment methods at customer perception layer. From the qualitative perspective, a hierarchical model is established, which forms mapping relations from the upper customer perception to the lower service quality parameters, and then the influence of different service parameters on customer satisfaction degree can b＇e denoted by the fuzzy analysis hierarchy process （FAHP） algorithm. Quantitative and qualitative evaluations together form a comprehensive solution which is universal, customer-oriented and flexible. Demonstrated by the representative voice service, the proposed system is proved reliable and applicable to service evaluation in NGN.

关键词： customer satisfaction degree key quality indicator (KQI) NSLA function quality of experience index (QoE index) FAHP

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Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3353-3385页

作者： Murugan Palanikumar Nasreen Kausar Dragan Pamucar Seifedine Kadry Chomyong Kim Yunyoung Nam Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesChennai602105India Department of Mathematics Faculty of Arts and ScienceYildiz Technical UniversityEsenlerIstanbul34220Turkey Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgrade11000Serbia College of Engineering Yuan Ze UniversityTaoyuan City320315TaiwanChina Department of Applied Data Science Noroff University CollegeKristiansand4612Norway Artificial Intelligence Research center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos1102-2801Lebanon ict Convergence Research center Soonchunhyang UniversityAsan31538South Korea Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538South Korea

In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this *** is provided of the scoring function,accuracy function and operational laws of the log q-rung *** algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming ***,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify *** chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile *** numbers q are used to express the results of the *** demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.

关键词： Vague set aggregating operators euclidean distance hamming distance decision making

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Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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Computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research center MeridenConnecticut06450USA School of ict Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

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Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

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Journal of Meteorological Research 2024年第2期38卷 262-284页

作者： Yunjae CHO Hyun Mee KIM Eun-Gyeong YANG Yonghee LEE Jae-Bum LEE Soyoung HA Department of Atmospheric Sciences Yonsei UniversitySeoul 03722Republic of Korea Air Quality Forecasting center National Institute of Environmental ResearchIncheon 22689Republic of Korea National center for Atmospheric Research BoulderCO 80305USA University of Maryland Baltimore County BaltimoreMD 21250USA Global Modeling and Assimilation Office NASA Goddard Space Flight CenterGreenbeltMD 20771USA

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality *** data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the *** this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean *** nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological *** the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner *** indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological *** to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with *** effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the ***,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

关键词： meteorological data assimilation regional air quality forecast particulate matter concentration optimal model domain forecast error WRF-Chem

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Advancing Malaria Prediction in Uganda through AI and Geospatial Analysis Models

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Journal of Geographic Information System 2024年第2期16卷 115-135页

作者： Maria Assumpta Komugabe Richard Caballero Itamar Shabtai Simon Peter Musinguzi center for Information Systems & Technology Claremont Graduate University Claremont California USA Department of Information Technology Faculty of Business and ICT University of Kisubi Entebbe Uganda Faculty of Health Sciences University of Kisubi Entebbe Uganda Department of Agriculture Production Faculty of Agriculture Kyambogo University Kyambogo Uganda Department of Agriculture and Natural Sciences Faculty of Agriculture Uganda Martyrs University Kampala Uganda

The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R2 of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.

关键词： Malaria Predictive Modeling Geospatial Analysis Climate Factors Preventive Measures

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Performance of the EDACS-ADP incorporating high-sensitivity troponin assay:Do components of major adverse cardiac events matter?

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World Journal of Emergency Medicine 2024年第3期15卷 175-180页

作者： Yedalm Yoo Shin Ahn Bora Chae Won Young Kim Department of Emergency Medicine Asan Medical CenterUniversity of Ulsan College of MedicineSeoul 05505Republic of Korea

BACKGROUND:The accelerated diagnostic protocol(ADP)using the Emergency Department Assessment of Chest pain Score(EDACS-ADP),a tool to identify patients at low risk of a major adverse cardiac event(MACE)among patients presenting with chest pain to the emergency department,was developed using a contemporary troponin *** study was performed to validate and compare the performance of the EDACS-ADP incorporating high-sensitivity cardiac troponin I between patients who had a 30-day MACE with and without unstable angina(MACE I and II,respectively).METHODS:A single-center prospective observational study of adult patients presenting with chest pain suggestive of acute coronary syndrome was *** performance of EDACS-ADP in predicting MACE was assessed by calculating the sensitivity and negative predictive ***:Of the 1,304 patients prospectively enrolled,399(30.6%;95%confidence interval[95%CI]:27.7%–33.8%)were considered low-risk using the *** them,the rates of MACE I and II were 1.3%(5/399)and 1.0%(4/399),*** EDACS-ADP showed sensitivities and negative predictive values of 98.8%(95%CI:97.2%–99.6%)and 98.7%(95%CI:97.0%–99.5%)for MACE I and 98.7%(95%CI:96.8%–99.7%)and 99.0%(95%CI:97.4%–99.6%)for MACE II,***:EDACS-ADP could help identify patients as safe for early ***,when unstable angina was added to the outcome,the 30-day MACE rate among the designated lowrisk patients remained above the level acceptable for early discharge without further evaluation.

关键词： Chest pain Major adverse cardiac event Acute coronary syndrome Emergency department

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Stable operation of highly loaded pure Si-Fe anode under ambient pressure via carboxy silane-directed robust solid electrolyte interphase

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Journal of Energy Chemistry 2024年第7期94卷 568-576页

作者： Guntae Lim Dong Guk Kang Hyeon Gyu Lee Yen Hai Thi Tran Kihun An Junghyun Choi Kwang Chul Roh Do Youb Kim Seung-Wan Song Department of Chemical Engineering&Applied Chemistry Chungnam National University Daejeon 34134Republic of Korea Energy Storage Materials center Korea Institute of Ceramic Engineering&TechnologyJinju 52851Republic of Korea Advanced Energy Materials Research center Korea Research Institute of Chemical TechnologyDaejeon 34114Republic of Korea

Incorporation of higher content Si anode material beyond 5 wt% to Li-ion batteries(LIBs)is challenging,owing to large volume change,swelling,and solid electrolyte interphase(SEI)instability ***,a strategy of diacetoxydimethylsilane(DAMS)additive-directed SEI stabilization is proposed for a stable operation of Si-0.33FeSi_(2)(named as Si-Fe)anode without graphite,which provides siloxane inorganics and organics enrichment that compensate insufficient passivation of fluoroethylene carbonate(FEC)additive and reduce a dependence on *** stable cycling performance of highly loaded(3.5 mA h cm^(-2))pure Si-Fe anode is achieved with 2 wt%DAMS combined with 9 wt%FEC additives under ambient pressure,yielding high capacity 1270 mA h g^(-1)at 0.5 C and significantly improved capacity retention of 81% after 100 cycles,whereas short circuit and rapid capacity fade occur with FEC only ***-directed robust SEI layer dramatically suppresses swelling and particles crossover through separator,and therefore prevents short circuit,demonstrating a possible operation of pure Si or Sidominant anodes in the next-generation high-energy-density and safe LIBs.

关键词： High-energy Li-ion battery Pure Si-Fe anode without graphite Silane additive SEI layer Suppressed swelling

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基于Swin-Transformer迭代展开的有限角CT图像重建用于PTCT成像

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光学学报 2024年第8期44卷 296-307页

作者：袁伟席雅睿谭川东刘川江朱国荣刘丰林重庆大学ict研究中心光电技术及系统教育部重点实验室重庆400044 重庆大学工业CT无损检测教育部工程研究中心重庆400044

针对相对平行直线扫描CT(PTCT)图像重建存在的有限角伪影问题,提出一种学习局部和非局部正则项的深度迭代展开方法。该方法将具有固定迭代次数的梯度下降算法迭代展开到神经网络,利用具有坐标注意力(CA)机制的卷积模块和Swin-Transforme... 详细信息

针对相对平行直线扫描CT(PTCT)图像重建存在的有限角伪影问题,提出一种学习局部和非局部正则项的深度迭代展开方法。该方法将具有固定迭代次数的梯度下降算法迭代展开到神经网络,利用具有坐标注意力(CA)机制的卷积模块和Swin-Transformer模块作为迭代模块交替级联部署,构成端到端的深度重建网络。卷积模块学习局部正则化,其中CA用于减少图像过平滑;Swin-Transformer模块学习非局部正则化,提高网络对图像细节的恢复能力;在相邻模块间,使用迭代连接(IC)增强模型提取深层特征的能力,提高每次迭代的效率。通过消融实验验证了网络各部分的有效性,并在两种类型的数据集上进行实验,结果证明了本文方法的效果。实验结果表明,本文方法在抑制PTCT重建图像有限角伪影的同时,能较好地保留重建图像细节,提高重建图像质量。

关键词： X射线光学计算机断层成像相对平行直线扫描图像重建有限角深度学习

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