LION(evoLedv sIng mOmeNumt)是Google公司通过启发式程序搜索的方式发现的优化器,是一种独特的基于学习的优化算法。LION算法通过在上步动量和本步梯度之间维持两个不同的插值,并有效结合了解耦的权重衰减技术,实现了超越传统符号梯度...LION(evoLedv sIng mOmeNumt)是Google公司通过启发式程序搜索的方式发现的优化器,是一种独特的基于学习的优化算法。LION算法通过在上步动量和本步梯度之间维持两个不同的插值,并有效结合了解耦的权重衰减技术,实现了超越传统符号梯度下降类算法的性能。LION算法在许多大规模深度学习问题中展现了较强的优势,得到了广泛的应用。然而,尽管已有工作已经证明了LION的收敛性,但尚未有研究给出一个全面的收敛速度分析。已有研究证明,LION能够解决一类特定的盒约束优化问题,本文着重证明了,在?1范数度量下,LION收敛到这类问题的Karush-Kuhn-Tucker(KKT)点的速度为(Q√dK^(-1/4)),其中d为问题维度,K为算法的迭代步数。更进一步,我们移除了约束条件,证明LION在一般无约束问题上以相同的速度收敛至目标函数的驻点。与已有研究工作相比,本文证明的收敛速度达到了关于问题维度d的最优依赖关系;关于迭代步数K,这一速度还达到了非凸优化问题中随机梯度类算法能实现的最优理论下界。此外,这一理论下界以梯度的?2范数度量,而LION所属的符号梯度下降类算法通常度量的是更大的?1范数。由于在不同的梯度范数度量下关于问题维度d得到的收敛速度结果会有所差异,为了验证本文证明的收敛速度关于维度d同样是最优的,我们在多种深度学习任务上设计了全面的实验,不仅证明了LION与同样匹配理论下界的随机梯度下降法相比具有更低的训练损失和更强的性能,而且还验证了LION算法在迭代过程中梯度的ℓ_(1)/ℓ_(2)范数比始终处于Q(√d)的量级,从而在经验上说明了本文证明的收敛速度同样匹配关于d的最优下界。展开更多
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
Substitution boxes(S-boxes)are key components of symmetrical cryptosystems,acting as nonlinear substitutionfunctions that hide the relationship between the encrypted text and input key.This confusion mechanism is vita...Substitution boxes(S-boxes)are key components of symmetrical cryptosystems,acting as nonlinear substitutionfunctions that hide the relationship between the encrypted text and input key.This confusion mechanism is vitalfor cryptographic security because it prevents attackers from intercepting the secret key by analyzing the encryptedtext.Therefore,the S-box design is essential for the robustness of cryptographic systems,especially for the dataencryption standard(DES)and advanced encryption standard(AES).This study focuses on the application of theffreffy algorithm(FA)and metaheuristic lion optimization algorithm(LOA),thereby proposing a hybrid approachcalled the metaheuristic lion ffreffy(ML-F)algorithm.FA,inspired by the blinking behavior of ffreffies,is a relativelynew calculation technique that is effective for various optimization problems.However,FA offen experiences earlyconvergence,limiting the ability to determine the global optimal solution in complex search areas.To address thisproblem,the ML-F algorithm was developed by combining the strengths of FA and LOA.This study identiffesa research gap in enhancing S-box nonlinearity and resistance to differential attacks,which the proposed ML-Faims to address.The main contributions of this paper are the enhanced cryptographic robustness of the S-boxesdeveloped with ML-F,consistently outperforming those generated by FA and other methodsregarding nonlinearityand overall cryptographic properties.The LOA,inspired by the social hunting behavior of lions,uses the collectiveintelligence of a pride of lions to explore and exploit the search space more effectively.The experimental analysis ofthisstudy focused on the main encryption criteria,namely,nonlinearity,the bit independence criterion(BIC),strictavalanche criterion(SAC),differential probability(DP),and maximum expected linear probability(MELP).Thesecriteria ensure that the S-boxes provide robust security against various cryptanalytic attacks.The ML-F algorithmconsistently surpassed the FA and other optimization algorithms in generating S-boxes with higher nonlinearityand better overall cryptographic properties.In case of ML-F-based S-boxes,the results indicated a better averagenonlinear score and more resistance against several cryptographic attacks for quite a number of criteria.Therefore,they were considered more reliable while dealing with secured encryption.The values generated by the ML-FS-boxes are near ideal in both SAC and BIC,indicating better diffusion properties and consequently,enhancedsecurity.The DP analysisfurthershowed that the ML-F-generated S-boxes are highly resistant to differential attacks,which is a crucial requirement for secure encryption systems.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
The research advances of the technology of landscape impact assessment in China and other countries are introduced at first.And then aiming at the characters of the environmental regulation project,the assessment prin...The research advances of the technology of landscape impact assessment in China and other countries are introduced at first.And then aiming at the characters of the environmental regulation project,the assessment principles and research methods are proposed.Two typical viewpoints and a representative protection area in the project area are selected to respectively make a landscape impact assessment.Meanwhile,this research describes in details how to apply Map Overlays,Compared Evaluation and Visual Factors Evaluation in the process.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
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
An important problem in wireless communication networks (WCNs) is that they have a minimum number of resources, which leads to high-security threats. An approach to find and detect the attacks is the intrusion detecti...An important problem in wireless communication networks (WCNs) is that they have a minimum number of resources, which leads to high-security threats. An approach to find and detect the attacks is the intrusion detection system (IDS). In this paper, the fuzzy lion Bayes system (FLBS) is proposed for intrusion detection mechanism. Initially, the data set is grouped into a number of clusters by the fuzzy clustering algorithm. Here, the Naive Bayes classifier is integrated with the lion optimization algorithm and the new lion naive Bayes (LNB) is created for optimally generating the probability measures. Then, the LNB model is applied to each data group, and the aggregated data is generated. After generating the aggregated data, the LNB model is applied to the aggregated data, and the abnormal nodes are identified based on the posterior probability function. The performance of the proposed FLBS system is evaluated using the KDD Cup 99 data and the comparative analysis is performed by the existing methods for the evaluation metrics accuracy and false acceptance rate (FAR). From the experimental results, it can be shown that the proposed system has the maximum performance, which shows the effectiveness of the proposed system in the intrusion detection.展开更多
The influence of social upbringing on the activity pattern of lion Panthera leo cubs was investigated at three sites. In this study, stimulus objects such as sticks, grass, fresh dung （elephant Loxondota africana, ze...The influence of social upbringing on the activity pattern of lion Panthera leo cubs was investigated at three sites. In this study, stimulus objects such as sticks, grass, fresh dung （elephant Loxondota africana, zebra Equus quagga, impala Aepyceros melampus, duiker Sylvicapra grimmia, kudu Tragelaphus strepsiceros, giraffe Giraffa camelopardalis and wildebeest Connochaetes taurinus） and cardboard boxes, were utilized in an enrichment program aimed at encouraging active behaviors of captive lion cubs at Antelope Park and Masuwe. Lion cubs at Chipangali were not behaviorally enriched. Activity patterns were recorded for 10 days at each site. We recorded moving, resting, playing, grooming, visual exploration and display of hunting instincts. We found that behavioral enrichment enhanced the active behaviors of captive lion cubs. Orphan-raised cubs spent more time moving, playing and displaying hunting instincts than mother-raised cubs, but the time spent grooming was similar across areas and suggests that grooming is not influenced by enrichment. Mother-raised cubs spent more time engaged in visual exploration than orphan-raised cubs and this could be a behavior acquired from mothers or a result of confidence to explore because of their presence. Activity patterns were different among time treatments across our three study sites. Based on these findings, we suggest that lion cubs raised in captivity could benefit from behavioral enrichment to encourage active behaviors essential for eventual reintroduction into the wild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
Understanding the factors that facilitate the emergence of cooperation among organisms is central to the study of social evolution. Spotted hyenas Crocuta crocuta frequently cooperate to mob lions Panthera leo, approa...Understanding the factors that facilitate the emergence of cooperation among organisms is central to the study of social evolution. Spotted hyenas Crocuta crocuta frequently cooperate to mob lions Panthera leo, approaching the lions as a tightknit group while vocalizing loudly in an attempt to overwhelm them and drive them away. Whereas cooperative mobbing behavior has been well documented in birds and some mammals, to our knowledge it has never been described during interactions between 2 apex predators. Using a 27-year dataset, we characterize lion-hyena encoun- ters, assess rates of mobbing behavior observed during these interactions, and inquire whether mobbing results in successful acquisition of food. Lions and hyenas interacted most often at fresh kills, especially as prey size and the number of hyenas present increased. Possession of food at the beginning of an interaction positively affected retention of that food by each predator species. The presence of male lions increased the probability of an interspecific interaction but decreased the likelihood of hyenas obtaining or retaining possession of the food. Hyena mobbing rates were highest at fresh kills, but lower when adult male lions were present. The occurrence of mobbing was predicted by an increase in the number of hyenas present. Whether or not mobbing resulted in acquisition of food from lions was predicted by an increase in the number of mobs formed by the hyenas present, suggesting that cooperation among hyenas enhances their fitness.展开更多
Camivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up con- trol in ecosystems throughout the world, yet, little is known about how fire affects short-term carni...Camivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up con- trol in ecosystems throughout the world, yet, little is known about how fire affects short-term carnivore distributions across the landscape. Through the use of a long-term data set we investigated the distribution of lions, during the daytime, in relation to burned areas in Serengeti National Park, Tanzania. We found that lions avoid burned areas despite the fact that herbivores, their prey, are attracted to burned areas. Prey attraction, however, likely results from the reduction in cover caused by burning, that may thereby decrease lion hunting success. Lions also do not preferentially utilize the edges of burned areas over unburned areas de- spite the possibility that edges would combine the benefit of cover with proximity to abundant prey. Despite the fact that lions avoid burned areas, lion territory size and reproductive success were not affected by the proportion of the territory burned each year. Therefore, burning does not seem to reduce lion fitness perhaps because of the heterogeneity of burned areas across the landscape or because it is possible that when hunting at night lions visit burned areas despite their daytime avoidance of these ar- eas .展开更多
文摘LION(evoLedv sIng mOmeNumt)是Google公司通过启发式程序搜索的方式发现的优化器,是一种独特的基于学习的优化算法。LION算法通过在上步动量和本步梯度之间维持两个不同的插值,并有效结合了解耦的权重衰减技术,实现了超越传统符号梯度下降类算法的性能。LION算法在许多大规模深度学习问题中展现了较强的优势,得到了广泛的应用。然而,尽管已有工作已经证明了LION的收敛性,但尚未有研究给出一个全面的收敛速度分析。已有研究证明,LION能够解决一类特定的盒约束优化问题,本文着重证明了,在?1范数度量下,LION收敛到这类问题的Karush-Kuhn-Tucker(KKT)点的速度为(Q√dK^(-1/4)),其中d为问题维度,K为算法的迭代步数。更进一步,我们移除了约束条件,证明LION在一般无约束问题上以相同的速度收敛至目标函数的驻点。与已有研究工作相比,本文证明的收敛速度达到了关于问题维度d的最优依赖关系;关于迭代步数K,这一速度还达到了非凸优化问题中随机梯度类算法能实现的最优理论下界。此外,这一理论下界以梯度的?2范数度量,而LION所属的符号梯度下降类算法通常度量的是更大的?1范数。由于在不同的梯度范数度量下关于问题维度d得到的收敛速度结果会有所差异,为了验证本文证明的收敛速度关于维度d同样是最优的,我们在多种深度学习任务上设计了全面的实验,不仅证明了LION与同样匹配理论下界的随机梯度下降法相比具有更低的训练损失和更强的性能,而且还验证了LION算法在迭代过程中梯度的ℓ_(1)/ℓ_(2)范数比始终处于Q(√d)的量级,从而在经验上说明了本文证明的收敛速度同样匹配关于d的最优下界。
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Substitution boxes(S-boxes)are key components of symmetrical cryptosystems,acting as nonlinear substitutionfunctions that hide the relationship between the encrypted text and input key.This confusion mechanism is vitalfor cryptographic security because it prevents attackers from intercepting the secret key by analyzing the encryptedtext.Therefore,the S-box design is essential for the robustness of cryptographic systems,especially for the dataencryption standard(DES)and advanced encryption standard(AES).This study focuses on the application of theffreffy algorithm(FA)and metaheuristic lion optimization algorithm(LOA),thereby proposing a hybrid approachcalled the metaheuristic lion ffreffy(ML-F)algorithm.FA,inspired by the blinking behavior of ffreffies,is a relativelynew calculation technique that is effective for various optimization problems.However,FA offen experiences earlyconvergence,limiting the ability to determine the global optimal solution in complex search areas.To address thisproblem,the ML-F algorithm was developed by combining the strengths of FA and LOA.This study identiffesa research gap in enhancing S-box nonlinearity and resistance to differential attacks,which the proposed ML-Faims to address.The main contributions of this paper are the enhanced cryptographic robustness of the S-boxesdeveloped with ML-F,consistently outperforming those generated by FA and other methodsregarding nonlinearityand overall cryptographic properties.The LOA,inspired by the social hunting behavior of lions,uses the collectiveintelligence of a pride of lions to explore and exploit the search space more effectively.The experimental analysis ofthisstudy focused on the main encryption criteria,namely,nonlinearity,the bit independence criterion(BIC),strictavalanche criterion(SAC),differential probability(DP),and maximum expected linear probability(MELP).Thesecriteria ensure that the S-boxes provide robust security against various cryptanalytic attacks.The ML-F algorithmconsistently surpassed the FA and other optimization algorithms in generating S-boxes with higher nonlinearityand better overall cryptographic properties.In case of ML-F-based S-boxes,the results indicated a better averagenonlinear score and more resistance against several cryptographic attacks for quite a number of criteria.Therefore,they were considered more reliable while dealing with secured encryption.The values generated by the ML-FS-boxes are near ideal in both SAC and BIC,indicating better diffusion properties and consequently,enhancedsecurity.The DP analysisfurthershowed that the ML-F-generated S-boxes are highly resistant to differential attacks,which is a crucial requirement for secure encryption systems.
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The research advances of the technology of landscape impact assessment in China and other countries are introduced at first.And then aiming at the characters of the environmental regulation project,the assessment principles and research methods are proposed.Two typical viewpoints and a representative protection area in the project area are selected to respectively make a landscape impact assessment.Meanwhile,this research describes in details how to apply Map Overlays,Compared Evaluation and Visual Factors Evaluation in the process.
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.
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.
文摘An important problem in wireless communication networks (WCNs) is that they have a minimum number of resources, which leads to high-security threats. An approach to find and detect the attacks is the intrusion detection system (IDS). In this paper, the fuzzy lion Bayes system (FLBS) is proposed for intrusion detection mechanism. Initially, the data set is grouped into a number of clusters by the fuzzy clustering algorithm. Here, the Naive Bayes classifier is integrated with the lion optimization algorithm and the new lion naive Bayes (LNB) is created for optimally generating the probability measures. Then, the LNB model is applied to each data group, and the aggregated data is generated. After generating the aggregated data, the LNB model is applied to the aggregated data, and the abnormal nodes are identified based on the posterior probability function. The performance of the proposed FLBS system is evaluated using the KDD Cup 99 data and the comparative analysis is performed by the existing methods for the evaluation metrics accuracy and false acceptance rate (FAR). From the experimental results, it can be shown that the proposed system has the maximum performance, which shows the effectiveness of the proposed system in the intrusion detection.
文摘The influence of social upbringing on the activity pattern of lion Panthera leo cubs was investigated at three sites. In this study, stimulus objects such as sticks, grass, fresh dung （elephant Loxondota africana, zebra Equus quagga, impala Aepyceros melampus, duiker Sylvicapra grimmia, kudu Tragelaphus strepsiceros, giraffe Giraffa camelopardalis and wildebeest Connochaetes taurinus） and cardboard boxes, were utilized in an enrichment program aimed at encouraging active behaviors of captive lion cubs at Antelope Park and Masuwe. Lion cubs at Chipangali were not behaviorally enriched. Activity patterns were recorded for 10 days at each site. We recorded moving, resting, playing, grooming, visual exploration and display of hunting instincts. We found that behavioral enrichment enhanced the active behaviors of captive lion cubs. Orphan-raised cubs spent more time moving, playing and displaying hunting instincts than mother-raised cubs, but the time spent grooming was similar across areas and suggests that grooming is not influenced by enrichment. Mother-raised cubs spent more time engaged in visual exploration than orphan-raised cubs and this could be a behavior acquired from mothers or a result of confidence to explore because of their presence. Activity patterns were different among time treatments across our three study sites. Based on these findings, we suggest that lion cubs raised in captivity could benefit from behavioral enrichment to encourage active behaviors essential for eventual reintroduction into the wild
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Understanding the factors that facilitate the emergence of cooperation among organisms is central to the study of social evolution. Spotted hyenas Crocuta crocuta frequently cooperate to mob lions Panthera leo, approaching the lions as a tightknit group while vocalizing loudly in an attempt to overwhelm them and drive them away. Whereas cooperative mobbing behavior has been well documented in birds and some mammals, to our knowledge it has never been described during interactions between 2 apex predators. Using a 27-year dataset, we characterize lion-hyena encoun- ters, assess rates of mobbing behavior observed during these interactions, and inquire whether mobbing results in successful acquisition of food. Lions and hyenas interacted most often at fresh kills, especially as prey size and the number of hyenas present increased. Possession of food at the beginning of an interaction positively affected retention of that food by each predator species. The presence of male lions increased the probability of an interspecific interaction but decreased the likelihood of hyenas obtaining or retaining possession of the food. Hyena mobbing rates were highest at fresh kills, but lower when adult male lions were present. The occurrence of mobbing was predicted by an increase in the number of hyenas present. Whether or not mobbing resulted in acquisition of food from lions was predicted by an increase in the number of mobs formed by the hyenas present, suggesting that cooperation among hyenas enhances their fitness.
基金We thank the Tanzania Wildlife Re- search Institute, Tanzania National Parks and Tanzania Com- mission for Science and Technology for permission to conduct research in the Serengeti. This work was supported by Na-tional Science Foundation grants DEB 0308486 to C.E and M.R., 9903416 and 0343960 to C.P., and 0543398, and 0842230 to M.R.
文摘Camivores play a central role in ecosystem processes by exerting top-down control, while fire exerts bottom-up con- trol in ecosystems throughout the world, yet, little is known about how fire affects short-term carnivore distributions across the landscape. Through the use of a long-term data set we investigated the distribution of lions, during the daytime, in relation to burned areas in Serengeti National Park, Tanzania. We found that lions avoid burned areas despite the fact that herbivores, their prey, are attracted to burned areas. Prey attraction, however, likely results from the reduction in cover caused by burning, that may thereby decrease lion hunting success. Lions also do not preferentially utilize the edges of burned areas over unburned areas de- spite the possibility that edges would combine the benefit of cover with proximity to abundant prey. Despite the fact that lions avoid burned areas, lion territory size and reproductive success were not affected by the proportion of the territory burned each year. Therefore, burning does not seem to reduce lion fitness perhaps because of the heterogeneity of burned areas across the landscape or because it is possible that when hunting at night lions visit burned areas despite their daytime avoidance of these ar- eas .
