With the development of composite materials,their lightweight and high-strength characteristics have caused more widespread use from aerospace applications to automotive and rail transportation sectors,significantly r...With the development of composite materials,their lightweight and high-strength characteristics have caused more widespread use from aerospace applications to automotive and rail transportation sectors,significantly reducing the energy consumption during the operation of EMUs(Electric Multiple Units).This study aims to explore the application of composite materials in the lightweight design of EMU front skirts and proposes a design method based on threedimensional Hashin failure criteria and the Cheetah Optimizer(CO)to achieve maximum lightweight efficiency.The UMAT subroutine was developed based on the three-dimensional Hashin failure criteria to calculate failure parameters,which were used as design parameters in the CO.The model calculations and result extraction were implemented in MATLAB,and the Cheetah Optimizer iteratively determined the optimal laminating angle design that minimized the overall failure factor.After 100 iterations,ensuring structural integrity,the optimized design reduced the weight of the skirt panel by 60% compared to the original aluminum alloy structure,achieving significant lightweight benefits.This study provides foundational data for the lightweight design of EMUs.展开更多
Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradi...Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradientinformation, and are inspired by the bio-inspired and socially motivated heuristics. Metaheuristic optimizationalgorithms are increasingly applied to complex feature selection problems in high-dimensional medical datasets.Among these, Teaching-Learning-Based optimization (TLBO) has proven effective for continuous design tasks bybalancing exploration and exploitation phases. However, its binary version (BTLBO) suffers from limited exploitationability, often converging prematurely or getting trapped in local optima, particularly when applied to discrete featureselection tasks. Previous studies reported that BTLBO yields lower classification accuracy and higher feature subsetvariance compared to other hybrid methods in benchmark tests, motivating the development of hybrid approaches.This study proposes a novel hybrid algorithm, BTLBO-Cheetah Optimizer (BTLBO-CO), which integrates the globalexploration strength of BTLBO with the local exploitation efficiency of the Cheetah Optimization (CO) algorithm. Theobjective is to enhance the feature selection process for cancer classification tasks involving high-dimensional data. Theproposed BTLBO-CO algorithm was evaluated on six benchmark cancer datasets: 11 tumors (T), Lung Cancer (LUC),Leukemia (LEU), Small Round Blue Cell Tumor or SRBCT (SR), Diffuse Large B-cell Lymphoma or DLBCL (DL), andProstate Tumor (PT).The results demonstrate superior classification accuracy across all six datasets, achieving 93.71%,96.12%, 98.13%, 97.11%, 98.44%, and 98.84%, respectively.These results validate the effectiveness of the hybrid approachin addressing diverse feature selection challenges using a Support Vector Machine (SVM) classifier.展开更多
In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for n...In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.展开更多
This article reports a first case of calcinosis circumscripta in a captive African cheetah(Acinonyx jubatus).Histopathology demonstrated well defined multiple cystic structures containing granular,dark basophilic mate...This article reports a first case of calcinosis circumscripta in a captive African cheetah(Acinonyx jubatus).Histopathology demonstrated well defined multiple cystic structures containing granular,dark basophilic materials with peripheral granulomatous reaction,characterized by presence of multinucleated giant cells surrounded by a varying amounts of fibrous connective tissues.Special staining with von Kossa revealed black stained deposits confirming the presence of calcium salts.展开更多
Cheetahs and other apex predators are threatened by human-wildlife conflict and habitat degradation. Bush encroachment creates one of the biggest forms of habitat change, thus it is important to understand the impact ...Cheetahs and other apex predators are threatened by human-wildlife conflict and habitat degradation. Bush encroachment creates one of the biggest forms of habitat change, thus it is important to understand the impact this has on habitat use. We investigated habitat preferences of five male cheetahs in Namibian farmlands degraded by bush encroachment. Cheetahs were tracked using satellite based Global System for Mobile (GSM) collars providing a higher resolution on ranging behavior. We aimed to investigate: 1) habitat characteristics;2) evidence for habitat selection;3) temporal activity partitioning;and 4) whether revisits to locations were related to habitat type. There were differences in habitat characteristics, showing that cheetahs were able to utilise different habitats. Fecal pellet counts revealed that warthog, oryx, scrub hare and kudu were most abundant. The cheetahs spent more time in high visibility shrubland, suggesting they selected rewarding patches within predominantly bush-encroached landscapes. The usage in marginal habitat was strikingly influenced by habitat type, with both previously cleared and open vegetated areas showing high proportions in edge use. Individuals exhibited significant temporal activity partitioning, showing peaks between late afternoon and early morning hours. This finding could be key to managing human-wildlife conflict by showing that increased protection such as the use of herders and livestock guarding dogs should be used as mitigation methods to minimize the impact of cheetah specific temporal patterns at all times as defined in this research. Visits to the same locations were not correlated to habitat type;revisits may be dictated by other reasons such as social interaction, prey density or avoidance of other predators. Findings from this study will help build existing knowledge on the effects bush encroachment has on cheetah habitat preference.展开更多
The quality of skeleton system for the cheetah robot goes hand in hand with its bionic result of its shape, structure and functions. In view of the skeleton system constitution and structural characteristic of the che...The quality of skeleton system for the cheetah robot goes hand in hand with its bionic result of its shape, structure and functions. In view of the skeleton system constitution and structural characteristic of the cheetah, the team applied structure design, stimulation analysis and parameter optimization to developing the cheetah robot. In addition, after the invention of cheetah robot＇s anterior lumbar vertebra based on its functional attribute and connectivity attribute, the Solidworks Simulation was utilized to analyze the design, according to which improvement on the lumbar vertebra was made. Plus, the advantages of the CAD and CAE made the high efficiency of design work and high quality of the cheetah robot possible.展开更多
Neurological signs like ataxia and hind limb paresis have often been reported in cheetahs (Acinonyx jubatus), lions (Panthera leo) and snow leopards (Panthera unica). As a cause, copper and Vitamin A deficiencies have...Neurological signs like ataxia and hind limb paresis have often been reported in cheetahs (Acinonyx jubatus), lions (Panthera leo) and snow leopards (Panthera unica). As a cause, copper and Vitamin A deficiencies have been discussed. Many cases were seen in cheetahs and lions in the United Arab Emirates (UAE) within the last years. The aim of this study was to find correlations between nutrition, serum, and tissue levels, focusing on copper and Vitamin A. Blood and tissue samples of affected and unaffected animals were analyzed at the Central Veterinary Research Laboratory in Dubai, UAE. Animals were split into three different groups (A, B and C) according to their diets. Minerals were determined in serum, tissue, food and water samples, and serum was additionally analyzed for Vitamin A and E. Liver, kidney and spinal cord samples were taken for histopathological investigations. Mean serum copper and liver copper levels of animals fed pure chicken muscle meat without supplements were significantly lower (0.41 ± 0.71 μM/L;2.16 ± 0.95 ppm wet weight) than in animals fed a whole carcass prey diet (12.16 ± 3.42 μM/L;16.01 ± 17.51 ppm wet weight) (p < 0.05). Serum Vitamin A and E levels were highest in animals fed whole carcass prey diets (1.85 ± 0.68;27.31 ± 5.69 μM/L). Liver zinc concentrations were highest in animals fed pure chicken meat only (43.75 ± 16.48 ppm wet weight). In histopathology, demyelination of the spinal cord was found in all of the affected animals and most commonly when fed a diet based on poultry without supplements.展开更多
With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powere...With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.展开更多
道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合...道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合确定困难导致聚类效果欠佳,因此,提出了一种基于改进DBSCAN的道路障碍物点云聚类方法 .首先,在确定Eps领域时利用孤立核函数来改进传统的距离度量方式,提高了DBSCAN聚类对不同密度区域的适应性和准确性.其次,针对猎豹优化算法(Cheetah Optimizer,CO)在信息共享和迭代更新方面的不足,提出了一种基于及时更新机制与兼容度量策略的CO优化算法(Timely Updating Mechanisms and Compatible Metric Strategies for CO Algorithms,TCCO),通过实时更新操作确保每次迭代的优秀信息得到及时沟通共享,并在全局更新时基于非支配排序与拥挤距离优化淘汰机制,平衡全局搜索和局部开发能力,提高了收敛速度和收敛精度.最后,利用孤立度量改进Eps领域,并利用TCCO优化DBSCAN聚类,自适应确定参数,提高了聚类精度和效率.在八个UCI数据集上进行测试,仿真结果表明,提出的TCCO-DBSCAN算法与CO-DBSCAN,SSA-DBSCAN,DBSCAN,KMC方法相比,F-Measure,ARI,NMI指标均有明显提升,且聚类精度更优.通过激光雷达点云数据障碍物聚类的实验验证,证明TCCO-DBSCAN能够有效地适应点云数据密度变化,获得更好的道路障碍物聚类效果,为辅助驾驶中障碍物检测提供支持.展开更多
文摘With the development of composite materials,their lightweight and high-strength characteristics have caused more widespread use from aerospace applications to automotive and rail transportation sectors,significantly reducing the energy consumption during the operation of EMUs(Electric Multiple Units).This study aims to explore the application of composite materials in the lightweight design of EMU front skirts and proposes a design method based on threedimensional Hashin failure criteria and the Cheetah Optimizer(CO)to achieve maximum lightweight efficiency.The UMAT subroutine was developed based on the three-dimensional Hashin failure criteria to calculate failure parameters,which were used as design parameters in the CO.The model calculations and result extraction were implemented in MATLAB,and the Cheetah Optimizer iteratively determined the optimal laminating angle design that minimized the overall failure factor.After 100 iterations,ensuring structural integrity,the optimized design reduced the weight of the skirt panel by 60% compared to the original aluminum alloy structure,achieving significant lightweight benefits.This study provides foundational data for the lightweight design of EMUs.
基金funded by the Deanship of Research andGraduate Studies at King Khalid University through the Large Research Project under grant number RGP2/417/46.
文摘Metaheuristic optimization methods are iterative search processes that aim to efficiently solve complexoptimization problems. These basically find the solution space very efficiently, often without utilizing the gradientinformation, and are inspired by the bio-inspired and socially motivated heuristics. Metaheuristic optimizationalgorithms are increasingly applied to complex feature selection problems in high-dimensional medical datasets.Among these, Teaching-Learning-Based optimization (TLBO) has proven effective for continuous design tasks bybalancing exploration and exploitation phases. However, its binary version (BTLBO) suffers from limited exploitationability, often converging prematurely or getting trapped in local optima, particularly when applied to discrete featureselection tasks. Previous studies reported that BTLBO yields lower classification accuracy and higher feature subsetvariance compared to other hybrid methods in benchmark tests, motivating the development of hybrid approaches.This study proposes a novel hybrid algorithm, BTLBO-Cheetah Optimizer (BTLBO-CO), which integrates the globalexploration strength of BTLBO with the local exploitation efficiency of the Cheetah Optimization (CO) algorithm. Theobjective is to enhance the feature selection process for cancer classification tasks involving high-dimensional data. Theproposed BTLBO-CO algorithm was evaluated on six benchmark cancer datasets: 11 tumors (T), Lung Cancer (LUC),Leukemia (LEU), Small Round Blue Cell Tumor or SRBCT (SR), Diffuse Large B-cell Lymphoma or DLBCL (DL), andProstate Tumor (PT).The results demonstrate superior classification accuracy across all six datasets, achieving 93.71%,96.12%, 98.13%, 97.11%, 98.44%, and 98.84%, respectively.These results validate the effectiveness of the hybrid approachin addressing diverse feature selection challenges using a Support Vector Machine (SVM) classifier.
基金supported by the Deanship of Postgraduate Studies and Scientific Research at Majmaah University in Saudi Arabia under Project Number(ICR-2024-1002).
文摘In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.
文摘This article reports a first case of calcinosis circumscripta in a captive African cheetah(Acinonyx jubatus).Histopathology demonstrated well defined multiple cystic structures containing granular,dark basophilic materials with peripheral granulomatous reaction,characterized by presence of multinucleated giant cells surrounded by a varying amounts of fibrous connective tissues.Special staining with von Kossa revealed black stained deposits confirming the presence of calcium salts.
文摘Cheetahs and other apex predators are threatened by human-wildlife conflict and habitat degradation. Bush encroachment creates one of the biggest forms of habitat change, thus it is important to understand the impact this has on habitat use. We investigated habitat preferences of five male cheetahs in Namibian farmlands degraded by bush encroachment. Cheetahs were tracked using satellite based Global System for Mobile (GSM) collars providing a higher resolution on ranging behavior. We aimed to investigate: 1) habitat characteristics;2) evidence for habitat selection;3) temporal activity partitioning;and 4) whether revisits to locations were related to habitat type. There were differences in habitat characteristics, showing that cheetahs were able to utilise different habitats. Fecal pellet counts revealed that warthog, oryx, scrub hare and kudu were most abundant. The cheetahs spent more time in high visibility shrubland, suggesting they selected rewarding patches within predominantly bush-encroached landscapes. The usage in marginal habitat was strikingly influenced by habitat type, with both previously cleared and open vegetated areas showing high proportions in edge use. Individuals exhibited significant temporal activity partitioning, showing peaks between late afternoon and early morning hours. This finding could be key to managing human-wildlife conflict by showing that increased protection such as the use of herders and livestock guarding dogs should be used as mitigation methods to minimize the impact of cheetah specific temporal patterns at all times as defined in this research. Visits to the same locations were not correlated to habitat type;revisits may be dictated by other reasons such as social interaction, prey density or avoidance of other predators. Findings from this study will help build existing knowledge on the effects bush encroachment has on cheetah habitat preference.
文摘The quality of skeleton system for the cheetah robot goes hand in hand with its bionic result of its shape, structure and functions. In view of the skeleton system constitution and structural characteristic of the cheetah, the team applied structure design, stimulation analysis and parameter optimization to developing the cheetah robot. In addition, after the invention of cheetah robot＇s anterior lumbar vertebra based on its functional attribute and connectivity attribute, the Solidworks Simulation was utilized to analyze the design, according to which improvement on the lumbar vertebra was made. Plus, the advantages of the CAD and CAE made the high efficiency of design work and high quality of the cheetah robot possible.
文摘Neurological signs like ataxia and hind limb paresis have often been reported in cheetahs (Acinonyx jubatus), lions (Panthera leo) and snow leopards (Panthera unica). As a cause, copper and Vitamin A deficiencies have been discussed. Many cases were seen in cheetahs and lions in the United Arab Emirates (UAE) within the last years. The aim of this study was to find correlations between nutrition, serum, and tissue levels, focusing on copper and Vitamin A. Blood and tissue samples of affected and unaffected animals were analyzed at the Central Veterinary Research Laboratory in Dubai, UAE. Animals were split into three different groups (A, B and C) according to their diets. Minerals were determined in serum, tissue, food and water samples, and serum was additionally analyzed for Vitamin A and E. Liver, kidney and spinal cord samples were taken for histopathological investigations. Mean serum copper and liver copper levels of animals fed pure chicken muscle meat without supplements were significantly lower (0.41 ± 0.71 μM/L;2.16 ± 0.95 ppm wet weight) than in animals fed a whole carcass prey diet (12.16 ± 3.42 μM/L;16.01 ± 17.51 ppm wet weight) (p < 0.05). Serum Vitamin A and E levels were highest in animals fed whole carcass prey diets (1.85 ± 0.68;27.31 ± 5.69 μM/L). Liver zinc concentrations were highest in animals fed pure chicken meat only (43.75 ± 16.48 ppm wet weight). In histopathology, demyelination of the spinal cord was found in all of the affected animals and most commonly when fed a diet based on poultry without supplements.
文摘With the rapid advancement of robotics and Artificial Intelligence(AI),aerobics training companion robots now support eco-friendly fitness by reducing reliance on nonrenewable energy.This study presents a solar-powered aerobics training robot featuring an adaptive energy management system designed for sustainability and efficiency.The robot integrates machine vision with an enhanced Dynamic Cheetah Optimizer and Bayesian Neural Network(DynCO-BNN)to enable precise exercise monitoring and real-time feedback.Solar tracking technology ensures optimal energy absorption,while a microcontroller-based regulator manages power distribution and robotic movement.Dual-battery switching ensures uninterrupted operation,aided by light and I/V sensors for energy optimization.Using the INSIGHT-LME IMU dataset,which includes motion data from 76 individuals performing Local Muscular Endurance(LME)exercises,the system detects activities,counts repetitions,and recognizes human movements.To minimize energy use during data processing,Min-Max normalization and two-dimensional Discrete Fourier Transform(2D-DFT)are applied,boosting computational efficiency.The robot accurately identifies upper and lower limb movements,delivering effective exercise guidance.The DynCO-BNN model achieved a high tracking accuracy of 96.8%.Results confirm improved solar utilization,ecological sustainability,and reduced dependence on fossil fuels—positioning the robot as a smart,energy-efficient solution for next-generation fitness technology.
文摘道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合确定困难导致聚类效果欠佳,因此,提出了一种基于改进DBSCAN的道路障碍物点云聚类方法 .首先,在确定Eps领域时利用孤立核函数来改进传统的距离度量方式,提高了DBSCAN聚类对不同密度区域的适应性和准确性.其次,针对猎豹优化算法(Cheetah Optimizer,CO)在信息共享和迭代更新方面的不足,提出了一种基于及时更新机制与兼容度量策略的CO优化算法(Timely Updating Mechanisms and Compatible Metric Strategies for CO Algorithms,TCCO),通过实时更新操作确保每次迭代的优秀信息得到及时沟通共享,并在全局更新时基于非支配排序与拥挤距离优化淘汰机制,平衡全局搜索和局部开发能力,提高了收敛速度和收敛精度.最后,利用孤立度量改进Eps领域,并利用TCCO优化DBSCAN聚类,自适应确定参数,提高了聚类精度和效率.在八个UCI数据集上进行测试,仿真结果表明,提出的TCCO-DBSCAN算法与CO-DBSCAN,SSA-DBSCAN,DBSCAN,KMC方法相比,F-Measure,ARI,NMI指标均有明显提升,且聚类精度更优.通过激光雷达点云数据障碍物聚类的实验验证,证明TCCO-DBSCAN能够有效地适应点云数据密度变化,获得更好的道路障碍物聚类效果,为辅助驾驶中障碍物检测提供支持.
