This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic ...This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.展开更多
This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an ele...This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.展开更多
As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optim...As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.展开更多
In audio stream containing multiple speakers, speaker diarization aids in ascertaining "who speak when". This is an unsupervised task as there is no prior information about the speakers. It labels the speech...In audio stream containing multiple speakers, speaker diarization aids in ascertaining "who speak when". This is an unsupervised task as there is no prior information about the speakers. It labels the speech signal conforming to the identity of the speaker, namely, input audio stream is partitioned into homogeneous segments. In this work, we present a novel speaker diarization system using the Tangent weighted Mel frequency cepstral coefficient(TMFCC) as the feature parameter and Lion algorithm for the clustering of the voice activity detected audio streams into particular speaker groups. Thus the two main tasks of the speaker indexing, i.e., speaker segmentation and speaker clustering, are improved. The TMFCC makes use of the low energy frame as well as the high energy frame with more effect, improving the performance of the proposed system. The experiments using the audio signal from the ELSDSR corpus datasets having three speakers, four speakers and five speakers are analyzed for the proposed system. The evaluation of the proposed speaker diarization system based on the tracking distance, tracking time as the evaluation metrics is done and the experimental results show that the speaker diarization system with the TMFCC parameterization and Lion based clustering is found to be superior over existing diarization systems with 95% tracking accuracy.展开更多
This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution pric...This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.展开更多
There has been an explosion of cloud services as organizations take advantage of their continuity,predictability,as well as quality of service and it raises the concern about latency,energy-efficiency,and security.Thi...There has been an explosion of cloud services as organizations take advantage of their continuity,predictability,as well as quality of service and it raises the concern about latency,energy-efficiency,and security.This increase in demand requires new configurations of networks,products,and service operators.For this purpose,the software-defined network is an efficient technology that enables to support the future network functions along with the intelligent applications and packet optimization.This work analyzes the offline cloud scenario in which machines are efficiently deployed and scheduled for user processing requests.Performance is evaluated in terms of reducing bandwidth,task execution times and latencies,and increasing throughput.A minimum execution time algorithm is used to compute the completion time of all the available resources which are allocated to the virtual machine and lion optimization algorithm is applied to packets in a cloud environment.The proposed work is shown to improve the throughput and latency rate.展开更多
This paper focuses on the unsupervised detection of the Higgs boson particle using the most informative features and variables which characterize the“Higgs machine learning challenge 2014”data set.This unsupervised ...This paper focuses on the unsupervised detection of the Higgs boson particle using the most informative features and variables which characterize the“Higgs machine learning challenge 2014”data set.This unsupervised detection goes in this paper analysis through 4 steps:(1)selection of the most informative features from the considered data;(2)definition of the number of clusters based on the elbow criterion.The experimental results showed that the optimal number of clusters that group the considered data in an unsupervised manner corresponds to 2 clusters;(3)proposition of a new approach for hybridization of both hard and fuzzy clustering tuned with Ant Lion Optimization(ALO);(4)comparison with some existing metaheuristic optimizations such as Genetic Algorithm(GA)and Particle Swarm Optimization(PSO).By employing a multi-angle analysis based on the cluster validation indices,the confusion matrix,the efficiencies and purities rates,the average cost variation,the computational time and the Sammon mapping visualization,the results highlight the effectiveness of the improved Gustafson-Kessel algorithm optimized withALO(ALOGK)to validate the proposed approach.Even if the paper gives a complete clustering analysis,its novel contribution concerns only the Steps(1)and(3)considered above.The first contribution lies in the method used for Step(1)to select the most informative features and variables.We used the t-Statistic technique to rank them.Afterwards,a feature mapping is applied using Self-Organizing Map(SOM)to identify the level of correlation between them.Then,Particle Swarm Optimization(PSO),a metaheuristic optimization technique,is used to reduce the data set dimension.The second contribution of thiswork concern the third step,where each one of the clustering algorithms as K-means(KM),Global K-means(GlobalKM),Partitioning AroundMedoids(PAM),Fuzzy C-means(FCM),Gustafson-Kessel(GK)and Gath-Geva(GG)is optimized and tuned with ALO.展开更多
Tanzania is considered a country with the largest number of African lions (Panthera leo). However, the continued absence of ecological population estimates and understanding of the associated factors influencing lion ...Tanzania is considered a country with the largest number of African lions (Panthera leo). However, the continued absence of ecological population estimates and understanding of the associated factors influencing lion distribution hinders the development of conservation planning. This is particularly true in the Ruaha-Rungwa landscape, where it was estimated that more than 10% of the global lion population currently resides. By using a call-back survey method, we aimed to provide population estimates (population size and density) of African lions in the Ruaha National Park, between wet (March 2019) and dry (October 2019) seasons. We also assessed the key factors that influenced the distribution of the observed lions towards call-back stations. Ferreira & Funston’s (2010) formula was used to calculate population size and in turn used to estimate density in the sampled area, while the Generalized Linear Model (GLMM) with zero-inflated Poisson error distribution was used to determine factors that influence the distribution of the observed lions to call-back stations. The population size we calculated for the sampled area of 3137.2 km<sup>2 </sup>revealed 286 lions (95% CI, 236 - 335) during the wet season, and 196 lions (95% CI, 192 - 200) during the dry season. The density of lions was 9.1/100 km<sup>2 </sup>during the wet season, and 6.3/100 km<sup>2</sup> during the dry season. Distance to water source had a significant negative effect on the distribution of the observed lions to the call-back stations, while habitat had a marginal effect. Our findings show that, although lion population estimates were larger during the wet season than the dry season, the season had no effect on the distribution of the observed lions to call-back stations. We suggest that the proximity to water sources is important in study design. Further, we suggest that density and population size are useful indices in identifying conservation area priorities and lion coexistence strategies.展开更多
A case of toxaemia secondary to pyloric foreign body obstruction in two four-month-old African lion cubs were presented in this article. The lion cubs were presented to the school of veterinary medicine with a complai...A case of toxaemia secondary to pyloric foreign body obstruction in two four-month-old African lion cubs were presented in this article. The lion cubs were presented to the school of veterinary medicine with a complaint of weight loss and stunted growth despite having a normal appetite and seizures. Defi nitive diagnosis was made based on gross pathology after attempting various symptomatic treatments. This article therefore is meant to discourage the use of blankets as bedding in holding enclosures for warmth and comfort post-weaning in captive lion cubs and indeed wild cats in general as they tend to eat bedding that has been soiled with food.展开更多
Data on lion skull measurements taken were collected and analyzed to determine trends in trophy size as an indicator of population size, and area of origin among the concessioned hunting areas in Zambia for the period...Data on lion skull measurements taken were collected and analyzed to determine trends in trophy size as an indicator of population size, and area of origin among the concessioned hunting areas in Zambia for the period 1967-2000. A comparison of trophy quality was also made with Tanzania and Zimbabwe which were the other two key sources of lion trophies in Africa. It was assumed that a comprehensive analysis of lion trophy sizes obtained from trophy hunting would be used as an indicator of hunting pressure on lion populations in Zambia. This approach was used because trophy size is an index of abundance particularly for species such as lion which are difficult to count using conventional census methods. Record lion trophies from Safari Club International rating were also collected and assessed to compare trophy quality obtained from Zambia and those of Tanzania and Zimbabwe for the same period 1967-2000 (33 years). Results obtained suggested that Zambia’s contribution to the record trophies under Safari Club International did not decline in the intervening period 1967-2000 and could not be used as an effective indicator of lion population in Zambia. At regional level, Zambia had second highest 24%, after Tanzania 56%, while Zimbabwe was third, 20%. It was found that the size of skulls could not be used as an effective indicator of population size as the record trophies did not decline while the population was alleged to have declined on the continent. Other factors, such as genetic, low prey densities, snaring, poisoning and problem animal control needed to be investigated to determine their impact on the lion population status.展开更多
The present work aims to study the influence of antioxidants activity of lion’s foot (Alchemilla vulgaris) leaves at different concentrations to give more protection against chronic liver disease. Results indicated t...The present work aims to study the influence of antioxidants activity of lion’s foot (Alchemilla vulgaris) leaves at different concentrations to give more protection against chronic liver disease. Results indicated that dried lion’s foot leaves had rich in total polyphenolic and flavonoids content (395.65 and 183.10 mg/100g, respectively). These results were reflected to the antioxidant activity (DPPH);it’s noticed that the antioxidant activity of dried lion’s foot leaves was high (131.74%). The major polyphenolic components were benzoic acid (1084.63 ppm) followed by ellagic acid, catechol, and catechin (614.16, 580.54, and 566.53 ppm, respectively) then salicylic acid and protocatechuic acid (479.71 and 444.43 ppm, respectively). On the same trend, flavonoids fractions indicated the highest content in luteo-6-arabinase 8-glucose, apig. 6-rhamnase 8-glucose, acatein, narengin and luteolin (40.01;15.04;8.07;6.64 and 6.42 ppm, respectively). Fifty-six male albino rats were used in biological experiments. Rats fed on basal diet for two weeks before the performance of the experiment. At the beginning, rats divided into eight main group were fed on diets for 45 days as follows: Negative control group (first group) was fed on basal diet. Forty nine rats were fed on basal diet and induced by CCl4, in paraffin oil (50% v/v, 2 ml/Kg) twice weeks subcutaneous injection to induce chronic damage in the liver, then divided into 7 groups numbered from group 2 to group 8. Positive control group rats fed on basal diet till final experiment (second group). Group 3 and 4 rats treated with 50 and 100 ppm ethanolic leaves extracts, respectively. Also, group 5 and 6 treated with 50 and 100 ppm aqueous leaves extracts, respectively. All extracts were fed on orally every day. While, rats in group 7 treated with 1% and 2% dried lion’s foot leaves. At the end of the experimental period, serums were collected to determine liver and renal functions. The liver was removed surgically for histopathological observation. The results revealed that CCl4 intoxication impaired liver function. Serum AST, ALT, ALP and total bilirubin levels were elevated by CCl4 administration, while significant decreasing was noticed in serum albumin in CCl4 group. Histopathologically, CCl4 caused congestion of central vain, fatty change of hepatocytes, and focal inflammatory cells in filtration. Treatment with lion’s foot with different forms and concentration attenuated these adverse effects and markedly ameliorated histopathological and biochemical alterations caused by CCl4 especially with 2% powder and 100 ppm ethanol extract administration. Therefore, the results of this study concluded that lion’s foot can be proposed to protect hepatotoxicity induced by CCl4 in rats. The results also revealed that the hepatoprotection effect of lion’s foot may be attributed to its antioxidant contents and free radical scavenger effect.展开更多
Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a c...Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a network.However,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH node.Consequently,early battery depletion is produced near the sink.To overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this study.LOA-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean distance.CH selection is performed using LOA.Route establishment is implemented using residual energy information.An extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and throughput.The performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and throughput.The proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and RISA-RPL.LOA-RPL is also highly energy-efficient compared with other similar routing protocols.展开更多
On February 22z a national dance drama 一 A wakening Lion , which was created by the Guangzhou Song and Dance Theater, was again staged in the Guangzhou Opera House.The dance drama consists of the background of Sanyua...On February 22z a national dance drama 一 A wakening Lion , which was created by the Guangzhou Song and Dance Theater, was again staged in the Guangzhou Opera House.The dance drama consists of the background of Sanyuanli Struggle against British Invaders and the core element of the national intangible cultural heritage ——Cantonese lion dance. It won the 11^th Lotus Dance Award in December 2018. And it was popular with young audiences. When it was performed firstly to the public, the tickets were quickly sold out.展开更多
ZTE Corporation, a leading globa provider of telecommunications equipment and network solutions, received the "Leone D'Oro per la Comunicazione" award from the Fondazione Italia Cina in November 2010.
基金supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea government(MSIT)(No.RS-2023-00218176)the Soonchunhyang University Research Fund.
文摘This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.
文摘This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.
基金supported by the National Natural Science Foundation of China(61771293)the Key Project of Shangdong Province(2019JZZY010111)。
文摘As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.
文摘In audio stream containing multiple speakers, speaker diarization aids in ascertaining "who speak when". This is an unsupervised task as there is no prior information about the speakers. It labels the speech signal conforming to the identity of the speaker, namely, input audio stream is partitioned into homogeneous segments. In this work, we present a novel speaker diarization system using the Tangent weighted Mel frequency cepstral coefficient(TMFCC) as the feature parameter and Lion algorithm for the clustering of the voice activity detected audio streams into particular speaker groups. Thus the two main tasks of the speaker indexing, i.e., speaker segmentation and speaker clustering, are improved. The TMFCC makes use of the low energy frame as well as the high energy frame with more effect, improving the performance of the proposed system. The experiments using the audio signal from the ELSDSR corpus datasets having three speakers, four speakers and five speakers are analyzed for the proposed system. The evaluation of the proposed speaker diarization system based on the tracking distance, tracking time as the evaluation metrics is done and the experimental results show that the speaker diarization system with the TMFCC parameterization and Lion based clustering is found to be superior over existing diarization systems with 95% tracking accuracy.
基金the National Key Research and Development Program of China(Grant No.2020YFB1707804)the 2018 Key Projects of Philosophy and Social Sciences Research(Grant No.18JZD032)Natural Science Foundation of Hebei Province(Grant No.G2020403008).
文摘This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.
基金This research was supported by the Sejong University Research Fund Korea and University of Shaqra,Saudi Arabia.
文摘There has been an explosion of cloud services as organizations take advantage of their continuity,predictability,as well as quality of service and it raises the concern about latency,energy-efficiency,and security.This increase in demand requires new configurations of networks,products,and service operators.For this purpose,the software-defined network is an efficient technology that enables to support the future network functions along with the intelligent applications and packet optimization.This work analyzes the offline cloud scenario in which machines are efficiently deployed and scheduled for user processing requests.Performance is evaluated in terms of reducing bandwidth,task execution times and latencies,and increasing throughput.A minimum execution time algorithm is used to compute the completion time of all the available resources which are allocated to the virtual machine and lion optimization algorithm is applied to packets in a cloud environment.The proposed work is shown to improve the throughput and latency rate.
文摘This paper focuses on the unsupervised detection of the Higgs boson particle using the most informative features and variables which characterize the“Higgs machine learning challenge 2014”data set.This unsupervised detection goes in this paper analysis through 4 steps:(1)selection of the most informative features from the considered data;(2)definition of the number of clusters based on the elbow criterion.The experimental results showed that the optimal number of clusters that group the considered data in an unsupervised manner corresponds to 2 clusters;(3)proposition of a new approach for hybridization of both hard and fuzzy clustering tuned with Ant Lion Optimization(ALO);(4)comparison with some existing metaheuristic optimizations such as Genetic Algorithm(GA)and Particle Swarm Optimization(PSO).By employing a multi-angle analysis based on the cluster validation indices,the confusion matrix,the efficiencies and purities rates,the average cost variation,the computational time and the Sammon mapping visualization,the results highlight the effectiveness of the improved Gustafson-Kessel algorithm optimized withALO(ALOGK)to validate the proposed approach.Even if the paper gives a complete clustering analysis,its novel contribution concerns only the Steps(1)and(3)considered above.The first contribution lies in the method used for Step(1)to select the most informative features and variables.We used the t-Statistic technique to rank them.Afterwards,a feature mapping is applied using Self-Organizing Map(SOM)to identify the level of correlation between them.Then,Particle Swarm Optimization(PSO),a metaheuristic optimization technique,is used to reduce the data set dimension.The second contribution of thiswork concern the third step,where each one of the clustering algorithms as K-means(KM),Global K-means(GlobalKM),Partitioning AroundMedoids(PAM),Fuzzy C-means(FCM),Gustafson-Kessel(GK)and Gath-Geva(GG)is optimized and tuned with ALO.
文摘Tanzania is considered a country with the largest number of African lions (Panthera leo). However, the continued absence of ecological population estimates and understanding of the associated factors influencing lion distribution hinders the development of conservation planning. This is particularly true in the Ruaha-Rungwa landscape, where it was estimated that more than 10% of the global lion population currently resides. By using a call-back survey method, we aimed to provide population estimates (population size and density) of African lions in the Ruaha National Park, between wet (March 2019) and dry (October 2019) seasons. We also assessed the key factors that influenced the distribution of the observed lions towards call-back stations. Ferreira & Funston’s (2010) formula was used to calculate population size and in turn used to estimate density in the sampled area, while the Generalized Linear Model (GLMM) with zero-inflated Poisson error distribution was used to determine factors that influence the distribution of the observed lions to call-back stations. The population size we calculated for the sampled area of 3137.2 km<sup>2 </sup>revealed 286 lions (95% CI, 236 - 335) during the wet season, and 196 lions (95% CI, 192 - 200) during the dry season. The density of lions was 9.1/100 km<sup>2 </sup>during the wet season, and 6.3/100 km<sup>2</sup> during the dry season. Distance to water source had a significant negative effect on the distribution of the observed lions to the call-back stations, while habitat had a marginal effect. Our findings show that, although lion population estimates were larger during the wet season than the dry season, the season had no effect on the distribution of the observed lions to call-back stations. We suggest that the proximity to water sources is important in study design. Further, we suggest that density and population size are useful indices in identifying conservation area priorities and lion coexistence strategies.
文摘A case of toxaemia secondary to pyloric foreign body obstruction in two four-month-old African lion cubs were presented in this article. The lion cubs were presented to the school of veterinary medicine with a complaint of weight loss and stunted growth despite having a normal appetite and seizures. Defi nitive diagnosis was made based on gross pathology after attempting various symptomatic treatments. This article therefore is meant to discourage the use of blankets as bedding in holding enclosures for warmth and comfort post-weaning in captive lion cubs and indeed wild cats in general as they tend to eat bedding that has been soiled with food.
文摘Data on lion skull measurements taken were collected and analyzed to determine trends in trophy size as an indicator of population size, and area of origin among the concessioned hunting areas in Zambia for the period 1967-2000. A comparison of trophy quality was also made with Tanzania and Zimbabwe which were the other two key sources of lion trophies in Africa. It was assumed that a comprehensive analysis of lion trophy sizes obtained from trophy hunting would be used as an indicator of hunting pressure on lion populations in Zambia. This approach was used because trophy size is an index of abundance particularly for species such as lion which are difficult to count using conventional census methods. Record lion trophies from Safari Club International rating were also collected and assessed to compare trophy quality obtained from Zambia and those of Tanzania and Zimbabwe for the same period 1967-2000 (33 years). Results obtained suggested that Zambia’s contribution to the record trophies under Safari Club International did not decline in the intervening period 1967-2000 and could not be used as an effective indicator of lion population in Zambia. At regional level, Zambia had second highest 24%, after Tanzania 56%, while Zimbabwe was third, 20%. It was found that the size of skulls could not be used as an effective indicator of population size as the record trophies did not decline while the population was alleged to have declined on the continent. Other factors, such as genetic, low prey densities, snaring, poisoning and problem animal control needed to be investigated to determine their impact on the lion population status.
文摘The present work aims to study the influence of antioxidants activity of lion’s foot (Alchemilla vulgaris) leaves at different concentrations to give more protection against chronic liver disease. Results indicated that dried lion’s foot leaves had rich in total polyphenolic and flavonoids content (395.65 and 183.10 mg/100g, respectively). These results were reflected to the antioxidant activity (DPPH);it’s noticed that the antioxidant activity of dried lion’s foot leaves was high (131.74%). The major polyphenolic components were benzoic acid (1084.63 ppm) followed by ellagic acid, catechol, and catechin (614.16, 580.54, and 566.53 ppm, respectively) then salicylic acid and protocatechuic acid (479.71 and 444.43 ppm, respectively). On the same trend, flavonoids fractions indicated the highest content in luteo-6-arabinase 8-glucose, apig. 6-rhamnase 8-glucose, acatein, narengin and luteolin (40.01;15.04;8.07;6.64 and 6.42 ppm, respectively). Fifty-six male albino rats were used in biological experiments. Rats fed on basal diet for two weeks before the performance of the experiment. At the beginning, rats divided into eight main group were fed on diets for 45 days as follows: Negative control group (first group) was fed on basal diet. Forty nine rats were fed on basal diet and induced by CCl4, in paraffin oil (50% v/v, 2 ml/Kg) twice weeks subcutaneous injection to induce chronic damage in the liver, then divided into 7 groups numbered from group 2 to group 8. Positive control group rats fed on basal diet till final experiment (second group). Group 3 and 4 rats treated with 50 and 100 ppm ethanolic leaves extracts, respectively. Also, group 5 and 6 treated with 50 and 100 ppm aqueous leaves extracts, respectively. All extracts were fed on orally every day. While, rats in group 7 treated with 1% and 2% dried lion’s foot leaves. At the end of the experimental period, serums were collected to determine liver and renal functions. The liver was removed surgically for histopathological observation. The results revealed that CCl4 intoxication impaired liver function. Serum AST, ALT, ALP and total bilirubin levels were elevated by CCl4 administration, while significant decreasing was noticed in serum albumin in CCl4 group. Histopathologically, CCl4 caused congestion of central vain, fatty change of hepatocytes, and focal inflammatory cells in filtration. Treatment with lion’s foot with different forms and concentration attenuated these adverse effects and markedly ameliorated histopathological and biochemical alterations caused by CCl4 especially with 2% powder and 100 ppm ethanol extract administration. Therefore, the results of this study concluded that lion’s foot can be proposed to protect hepatotoxicity induced by CCl4 in rats. The results also revealed that the hepatoprotection effect of lion’s foot may be attributed to its antioxidant contents and free radical scavenger effect.
基金This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(No.2019H1D8A1105622)the Soonchunhyang University Research Fund.
文摘Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a network.However,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH node.Consequently,early battery depletion is produced near the sink.To overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this study.LOA-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean distance.CH selection is performed using LOA.Route establishment is implemented using residual energy information.An extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and throughput.The performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and throughput.The proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and RISA-RPL.LOA-RPL is also highly energy-efficient compared with other similar routing protocols.
文摘On February 22z a national dance drama 一 A wakening Lion , which was created by the Guangzhou Song and Dance Theater, was again staged in the Guangzhou Opera House.The dance drama consists of the background of Sanyuanli Struggle against British Invaders and the core element of the national intangible cultural heritage ——Cantonese lion dance. It won the 11^th Lotus Dance Award in December 2018. And it was popular with young audiences. When it was performed firstly to the public, the tickets were quickly sold out.
文摘ZTE Corporation, a leading globa provider of telecommunications equipment and network solutions, received the "Leone D'Oro per la Comunicazione" award from the Fondazione Italia Cina in November 2010.