Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells

This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

Community Perceptions and Socio-Demographic Influence on Trophy Hunting in Rungwa Game Reserve, Tanzania

The trophy hunting industry in Tanzania plays a significant role in wildlife conservation as well as economic and community development. Trophy hunting has been conducted in Rungwa Game Reserve (RGR) for several decades;however, the trophy hunting opinions from the local communities living adjacent to the reserve are not well documented. This study aimed to assess the awareness and attitudes of local communities living adjacent to Rungwa Game Reserves toward trophy hunting. Furthermore, the study assessed factors that influenced the opinions of participants by using structural equation modeling. We used semi-structured interviews and key informant interviews in the three villages adjacent to RGR. The local communities are aware of existing hunting operations around the game reserves. The study found positive attitudes among local communities toward trophy hunting, only if local people accrue benefits from hunting operations. The community’s attitudes towards trophy hunting varied across household size and occupation. Education and household position had an indirect influence on the community’s attitude. Our findings suggest that socio-demographic variables are important to consider when assessing awareness and attitudes toward trophy hunting. Local communities are willing to support trophy hunting operations if the benefits obtained from hunting are significant and it can improve wildlife conservation and their livelihood. In conclusion, trophy hunting is important to local communities living adjacent to protected areas, and banning them may have a significant impact on their livelihood and wildlife conservation. Therefore, it is recommended that conservation policies and interventions consider the dual significance of trophy hunting, fostering strategies that balance socio-economic benefits for communities and wildlife conservation.

Research on hunting stability and bifurcation characteristics of nonlinear stochastic wheelset system

A stochastic wheelset model with a nonlinear wheel-rail contact relationship is established to investigate the stochastic stability and stochastic bifurcation of the wheelset system with the consideration of the stochastic parametric excitations of equivalent conicity and suspension stiffness.The wheelset is systematized into a onedimensional(1D)diffusion process by using the stochastic average method,the behavior of the singular boundary is analyzed to determine the hunting stability condition of the wheelset system,and the critical speed of stochastic bifurcation is obtained.The stationary probability density and joint probability density are derived theoretically.Based on the topological structure change of the probability density function,the stochastic Hopf bifurcation form and bifurcation condition of the wheelset system are determined.The effects of stochastic factors on the hunting stability and bifurcation characteristics are analyzed,and the simulation results verify the correctness of the theoretical analysis.The results reveal that the boundary behavior of the diffusion process determines the hunting stability of the stochastic wheelset system,and the left boundary characteristic value cL=1 is the critical state of hunting stability.Besides,stochastic D-bifurcation and P-bifurcation will appear in the wheelset system,and the critical speeds of the two kinds of stochastic bifurcation decrease with the increase in the stochastic parametric excitation intensity.

Cooperative multi-target hunting by unmanned surface vehicles based on multi-agent reinforcement learning

To solve the problem of multi-target hunting by an unmanned surface vehicle(USV)fleet,a hunting algorithm based on multi-agent reinforcement learning is proposed.Firstly,the hunting environment and kinematic model without boundary constraints are built,and the criteria for successful target capture are given.Then,the cooperative hunting problem of a USV fleet is modeled as a decentralized partially observable Markov decision process(Dec-POMDP),and a distributed partially observable multitarget hunting Proximal Policy Optimization(DPOMH-PPO)algorithm applicable to USVs is proposed.In addition,an observation model,a reward function and the action space applicable to multi-target hunting tasks are designed.To deal with the dynamic change of observational feature dimension input by partially observable systems,a feature embedding block is proposed.By combining the two feature compression methods of column-wise max pooling(CMP)and column-wise average-pooling(CAP),observational feature encoding is established.Finally,the centralized training and decentralized execution framework is adopted to complete the training of hunting strategy.Each USV in the fleet shares the same policy and perform actions independently.Simulation experiments have verified the effectiveness of the DPOMH-PPO algorithm in the test scenarios with different numbers of USVs.Moreover,the advantages of the proposed model are comprehensively analyzed from the aspects of algorithm performance,migration effect in task scenarios and self-organization capability after being damaged,the potential deployment and application of DPOMH-PPO in the real environment is verified.

Accurate threat hunting in industrial internet of things edge devices

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and processing.Any kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire IIoT.Moreover,they can allow malicious software installed on end nodes to penetrate the network.This paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge devices.The proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the Multi-class AdaBoost and majority voting.Experimental evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.

Arabic Sign Language Gesture Classification Using Deer Hunting Optimization with Machine Learning Model

Sign language includes the motion of the arms and hands to communicate with people with hearing disabilities.Several models have been available in the literature for sign language detection and classification for enhanced outcomes.But the latest advancements in computer vision enable us to perform signs/gesture recognition using deep neural networks.This paper introduces an Arabic Sign Language Gesture Classification using Deer Hunting Optimization with Machine Learning(ASLGC-DHOML)model.The presented ASLGC-DHOML technique mainly concentrates on recognising and classifying sign language gestures.The presented ASLGC-DHOML model primarily pre-processes the input gesture images and generates feature vectors using the densely connected network(DenseNet169)model.For gesture recognition and classification,a multilayer perceptron(MLP)classifier is exploited to recognize and classify the existence of sign language gestures.Lastly,the DHO algorithm is utilized for parameter optimization of the MLP model.The experimental results of the ASLGC-DHOML model are tested and the outcomes are inspected under distinct aspects.The comparison analysis highlighted that the ASLGC-DHOML method has resulted in enhanced gesture classification results than other techniques with maximum accuracy of 92.88%.

Deer Hunting Optimization with Deep Learning Enabled Emotion Classification on English Twitter Data

Currently,individuals use online social media,namely Facebook or Twitter,for sharing their thoughts and emotions.Detection of emotions on social networking sites’finds useful in several applications in social welfare,commerce,public health,and so on.Emotion is expressed in several means,like facial and speech expressions,gestures,and written text.Emotion recognition in a text document is a content-based classification problem that includes notions from deep learning(DL)and natural language processing(NLP)domains.This article proposes a Deer HuntingOptimizationwithDeep Belief Network Enabled Emotion Classification(DHODBN-EC)on English Twitter Data in this study.The presented DHODBN-EC model aims to examine the existence of distinct emotion classes in tweets.At the introductory level,the DHODBN-EC technique pre-processes the tweets at different levels.Besides,the word2vec feature extraction process is applied to generate the word embedding process.For emotion classification,the DHODBN-EC model utilizes the DBN model,which helps to determine distinct emotion class labels.Lastly,the DHO algorithm is leveraged for optimal hyperparameter adjustment of the DBN technique.An extensive range of experimental analyses can be executed to demonstrate the enhanced performance of the DHODBN-EC approach.A comprehensive comparison study exhibited the improvements of the DHODBN-EC model over other approaches with increased accuracy of 96.67%.

Flight Behavioural Responses for African Ungulates across Species and Vegetation Covers in a Trophy Hunting Ecosystem: A Case Study from Selous Game Reserve, Tanzania

Trophy hunting has severe consequences on wild animals’ behaviors, which in return has implications for affecting wildlife populations. The Selous Game Reserve is a protected area in Tanzania that has been subjected to commercial trophy hunting for decades, and information about the effects of trophy hunting on animals’ welfare is still scarce. The Flight Initiating Distance (FID) can be a good measure to evaluate the welfare of animals and the level of risk perception towards anthropogenic disturbances, including trophy hunting. The study used linear mixed models to assess the flight responses of twelve commonly hunted species in the Selous game reserve (S.G.R.). The study compared animal vigilance between species, vegetation types, and group size. The FID varied between species, with which more vigilance was observed in zebras, elands, wildebeests, and sable antelopes. The study found a significant influence of vegetation cover on individual species’ FID. Further, the study found a significant influence of group size on animals’ vigilance (L. M. M., 95% CI = 0.590 - 4.762), in which there was a decrease in FID with an increase in group size for wildebeests. At the same time, other species, such as buffaloes, eland, hartebeests, and zebras, had their FIDs increasing with the increase in group size. We conclude that the impact of trophy hunting on savannah ungulates varies between species, vegetation covers, and group size of individual species. Regulatory authorities should consider minimum approach distances by trophy hunters in different vegetation cover to reduce animal biological disturbances.

Economic Valuation of Auctioned Tourist Hunting Blocks in Tanzania

Economic valuation of ecosystems is increasingly being recognized as an important exercise to inform sustainable utilization and conservation of natural assets. It helps in planning and establishing fair profit margins that accrue either directly or indirectly from the consumptive and non-consumptive uses of ecosystem goods and services. This paper is based on a study which estimated the economic values of tourist hunting blocks (HBs) in Tanzania using the Analytic Multicriteria Valuation Method (AMUVAM). The study used a sample size of 12 out of 24 vacant hunting blocks which were to be auctioned to potential hunting companies in December 2022. The economic values of HBs were estimated using the time horizon of 10 years (the mean tenure for winning company). The results show that the economic values ranged from USD 6,215,588 to USD 653,470,695 per hunting block and the Existence Value (EV) constituted about 19% of the Total Economic Value (TEV). EV ranged from USD 632,210 to USD 125,147,285. The study underscores the need for decisions to allocate ecosystems, such as HBs, to both direct and indirect uses, to be guided by a though understanding of their values. We further recommend building the capacity of staff charged with the role of managing and allocating uses of these ecosystems to enable them undertake economic valuation of ecosystems using both simple and more robust analytical tools, such as the GIS, relational databases, and worldwide websites based tools, like InVEST (Integrated Valuation of Environmental Services and Tradeoffs), ARIES (Artificial Intelligence for Ecosystem Services), and Co$ting Nature.

Cool Hunting研究在产品创新设计中的应用

在市场竞争白热化的当下,用户体验日趋重要,如何让产品/服务更具前瞻性和创新性,更好地满足用户需求,我们引入了Cool Hunting研究,结合家电领域的特点,进行酷故事的收集与整理,并通过分析与酷创新,发现家电领域的产品/服务的创新机会,以期更好地满足市场和用户需求。

FOX Hunting System——一种新的功能基因筛选技术

FOX hunting system是近几年发展起来的又一新型分子生物学研究工具。在2006年,FOX hunting system作为一种植物功能获得性基因筛选技术首次被提出,可用于系统性阐明植物基因的功能。FOX hunting system可以在转基因植株中过量表达单个或有限数量的全长cDNA,这些异常表达的全长cDNA可能会导致显著的突变表型。根据研究目的对表型等方面发生改变的功能获得性突变植株进行筛选和解析,可以推断出转基因突变植株中所携带外源基因的功能。本文将就FOX hunting system的开发、流程、应用和发展等方面内容进行详细的阐述。

Influence of Vehicle Parameters on Critical Hunting Speed Based on Ruzicka Model

While introducing foreign advanced technology and cooperating with Chinese famous research institutes,the high-speed vehicles are designed and take the major task of passenger transport in China.In high-speed vehicle,the characteristic of shock absorber is an important parameter which determines overall behavior of the vehicle.The most existing researches neglect the influence of the series stiffness of the shock absorber on the vehicle dynamic behavior and have one-sided views on the equivalent conicity of wheel tread.In this paper,a high speed passenger vehicle in China is modeled to investigate the effect of the parameters taking series hydraulic shock absorber stiffness into consideration on Ruzicka model.Using the vehicle dynamic model,the effect of main suspension parameters on critical speed is studied.In order to verify the reasonableness of shock absorber parameter settings,vibration isolation characteristics are calculated and the relationship between suspension parameters and the vehicle critical hunting speed is studied.To study the influence of equivalent conicity on vehicle dynamic behavior,a series of wheel treads with different conicities are set and the vehicle critical hunting speeds with different wheel treads are calculated.The discipline between the equivalent conicity of wheel tread and critical speed are obtained in vehicle nonlinear system.The research results show that the critical speed of vehicle much depends on wheelset positioning stiffness and anti-hunting motion damper,and the series stiffness produces notable effect on the vehicle dynamic behavior.The critical speed has a peak value with the equivalent conicity increasing,which is different from the traditional opinion in which the critical speed will decrease with the conicity increasing.The relationship between critical speed and conicity of wheel tread is effected by the suspension parameters of the vehicle.The study results obtained offer a method and useful data to designing the parameters of the high speed vehicle and simulation study.

Influences of aerodynamic loads on hunting stability of high-speed railway vehicles and parameter studies

The influences of steady aerodynamic loads on hunting stability of high-speed railway vehicles were investigated in this study.A mechanism is suggested to explain the change of hunting behavior due to actions of aerodynamic loads：the aerodynamic loads can change the position of vehicle system（consequently the contact relations）,the wheel/rail normal contact forces,the gravitational restoring forces/moments and the creep forces/moments.A mathematical model for hunting stability incorporating such influences was developed.A computer program capable of incorporating the effects of aerodynamic loads based on the model was written,and the critical speeds were calculated using this program.The dependences of linear and nonlinear critical speeds on suspension parameters considering aerodynamic loads were analyzed by using the orthogonal test method,the results were also compared with the situations without aerodynamic loads.It is shown that the most dominant factors a ff ecting linear and nonlinear critical speeds are different whether the aerodynamic loads considered or not.The damping of yaw damper is the most dominant influencing factor for linear critical speeds,while the damping of lateral damper is most dominant for nonlinear ones.When the influences of aerodynamic loads are considered,the linear critical speeds decrease with the rise of cross wind velocity,whereas it is not the case for the nonlinear critical speeds.The variation trends of critical speeds with suspension parameters can be significantly changed by aerodynamic loads.Combined actions of aerodynamic loads and suspension parameters also a ff ect the critical speeds.The effects of such joint action are more obvious for nonlinear critical speeds.

Self-organized search-attack mission planning for UAV swarm based on wolf pack hunting behavior

Cooperative search-attack is an important application of unmanned aerial vehicle(UAV)swarm in military field.The coupling between path planning and task allocation,the heterogeneity of UAVs,and the dynamic nature of task environment greatly increase the complexity and difficulty of the UAV swarm cooperative search-attack mission planning problem.Inspired by the collaborative hunting behavior of wolf pack,a distributed selforganizing method for UAV swarm search-attack mission planning is proposed.First,to solve the multi-target search problem in unknown environments,a wolf scouting behavior-inspired cooperative search algorithm for UAV swarm is designed.Second,a distributed self-organizing task allocation algorithm for UAV swarm cooperative attacking of targets is proposed by analyzing the flexible labor division behavior of wolves.By abstracting the UAV as a simple artificial wolf agent,the flexible motion planning and group task coordinating for UAV swarm can be realized by self-organizing.The effectiveness of the proposed method is verified by a set of simulation experiments,the stability and scalability are evaluated,and the integrated solution for the coupled path planning and task allocation problems for the UAV swarm cooperative search-attack task can be well performed.

An Exploration of the Relation between Hunting and Aggressiveness: Using Inmates Networks at Prison Secondary School as an Illustration

Aim of this research is to explore the relation of hunting with aggressiveness. For this purpose, two samples of prison inmates (who were students of the prison secondary school) were collected (class A = 23, class B = 12). The network indicators for superficial, idiosyncratic and strategic behavior (particularly, aggressiveness), applied in Bekiari and Hasanagas (2016), which were based on the primary network variables (outdegree, indegree, Katz status, pagerank, authority) were used. Non-network variables were also used for the criminal profile of the inmates. The data were sampled with questionnaire. Spearman test was conducted for detecting correlation between aggressiveness and hunting and Principal Component Analysis was used for formulating a typology. The following results were produced: The criminal profile seems hardly to be related with hunting experience or attitude. The relation of hunting experience and attitude with the superficial, idiosyncratic and strategic aggressiveness was examined. These three occasions of aggressiveness are expected to describe the incidental reaction, impulsive and adaptive reaction, respectively. The hunting is quite irrelevant to the incidental reaction. The impulsiveness seems to be more strongly correlated with hunting. In case of adaptiveness, there are many similarities with impulsiveness. The typology which is based on the existence (or not) of hunting experience seems to be more insightful, as it reveals a gradual involvement of aggressiveness dimensions, from incidentality to impulsiveness and further to adaptiveness. The following behavioral patterns of gradually enhanced aggressiveness appear: incidentally just provoking, impulsively being aggressive but without harming, and adaptively being aggressive and harming.

Multi-robot hunting strategy based on FIS and artificial immune algorithm

data is gathered to describe the relative location and relative motion state of the robots, which in turn forms the beginning stage of the fuzzy rule. The artificial immune algorithm optimizes and generates the rule data base and adaptive design considers factors in measuring the hunting efficiency. The optimized rules are applied to the hunting task and the results show that the algorithm can effectively actualize hunting of multiple mobile robots.

Hunting problems of multi-quadrotor systems via bearing-based hybrid protocols with hierarchical network

Bearing-based hunting protocols commonly adopt a leaderless consensus method,which requests an entire state of the target for each agent and ignores the necessity of collision avoidance.We investigate a hunting problem of multi-quadrotor systems with hybrid bearing protocols,where the quadrotor systems are divided into master and slave groups for reducing the onboard loads and collision avoidance.The masters obtain the entire state of the target,whose hybrid protocols are based on the displacement and bearing constraints to maintain formation and to avoid the collision in the hunting process.However,the slaves’protocols merely depend on the part state of the masters to reduce loads of data transmission.We also investigate the feasibility of receiving the bearing state from machine vision.The simulation results are given to illustrate the effectiveness of the proposed hybrid bearing protocols.

Status of Wetland in Dhorpatan Hunting Reserve, Nepal

Wetland means the surface of the earth that is permanently or seasonally or partially covered with water. Wetlands are most productive areas for biodiversity and local livelihood support. Nepal ratified Ramsar convention in 1987 and started to include the wetland in Ramsar site and till now nine wetland sites are included in Ramsar site. There are still lacking systematic research and conservation approach for these wetlands;therefore, our study attempted to assess the status of wetlands in the Dhorpatan Hunting Reserve, Nepal;and explored threats and conservation challenges. We prepared list of streams and lakes and collected detail information regarding area, district, block, elevation and cultural as well as ecological importance of lakes. We recorded total 11 lakes with total 304477 m2 areas. The Sundaha lake is largest lake of the reserve having significant religious importance. We also recorded 7 streams in the reserve. Wetlands of the reserve were facing problem of sedimentation, pollution, and change in climate has also effects on these wetland ecosystem and their importance.

Tree stand falls: A persistent cause of neurological injury in hunting

AIM: To characterize and compare our current series of patients to prior reports in order to identify any changes in the incidence of neurological injury related to hunting accidents in Rochester, New York.METHODS: All tree stand-related injuries referred to our regional trauma center from September 2003 through November 2011 were reviewed. Information was obtained from the hospital's trauma registry and medical records were retrospectively reviewed for data pertaining to the injuries.RESULTS: Fifty-four patients were identified. Ninetysix percent of patients were male with a mean age of 47.9 years(range 15-69). The mean Injury Severity Score was 12.53 ± 1.17(range 2-34). The average height of fall was 18.2 feet(range 4-40 feet). All patients fell to the ground with the exception of one who landed on rocks, and many hit the tree or branches on the way down. A reason for the fall was documented in only 13 patients, and included tree stand construction(3), loss of balance(3), falling asleep(3), structural failure(2), safety harness breakage(3) or lightheadedness(1). The most common injuries were spinal fractures(54%), most commonly in the cervical spine(69%), followed by the thoracic(38%) and lumbar(21%) spine. Eight patients required operative repair. Head injuries occurred in 22%. Other systemic injuries include rib/clavicular fractures(47%), pelvic fractures(11%), solid organ injury(23%), and pneumothorax or hemothorax(19%). No patient deaths were reported. The average hospital length of stay was 6.56 ± 1.07 d. Most patients were discharged home without(72%) or with(11%) services and 17% required rehabilitation. CONCLUSION: Falls from hunting tree stands are still common, with a high rate of neurological injury. Compared to a decade ago we have made no progress in preventing these neurological injuries, despite an increase in safety advances. Neurosurgeons must continue to advocate for increased safety awareness and participate in leadership roles to improve outcomes for hunters.

DYNAMIC HUNTING EXTREMUM CONTROL METHOD BASED ON MEASURE AND ESTIMATION

Objective To propose a dynamic hunting extremum control method based on comparison of the estimated value and measured value. Methods The output linear group of the system is approximately expressed as an nth order system with large time constant or with time delay. Moreover, the relation between input drive reversal of the logic circuit and dynamic output of the system is analyzed in detail. The calculating formulae for the drive reversal are given for different extremum control systems. Based on principles above, a controller using a micrprocessor and a testing laboratory plant were designed and implemented. Results With this new method, the controller achieves fast optimum point hunting process, good performance in extremum control systems for high order processes, and robust result under sudden change or drift of the extremum characteristics. Conclusion The new control owns the merits of rapid optimizing dynamics, robusticity, and wide applicability.