Group Hybrid Coordination Control of Multi-Agent Systems With Time-Delays and Additive Noises

A new kind of group coordination control problemgroup hybrid coordination control is investigated in this paper.The group hybrid coordination control means that in a whole multi-agent system(MAS)that consists of two subgroups with communications between them,agents in the two subgroups achieve consensus and containment,respectively.For MASs with both time-delays and additive noises,two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case,respectively.By developing a new analysis idea,some sufficient conditions and necessary conditions related to the communication intensity betw een the two subgroups are obtained for the following two types of group hybrid coordination behavior:1)Agents in one subgroup and in another subgroup achieve weak consensus and containment,respectively;2)Agents in one subgroup and in another subgroup achieve strong consensus and containment,respectively.It is revealed that the decay of the communication impact betw een the two subgroups is necessary for the consensus-oriented case.Finally,the validity of the group control results is verified by several simulation examples.

Prediction and Analysis of Elevator Traffic Flow under the LSTM Neural Network

Elevators are essential components of contemporary buildings, enabling efficient vertical mobility for occupants. However, the proliferation of tall buildings has exacerbated challenges such as traffic congestion within elevator systems. Many passengers experience dissatisfaction with prolonged wait times, leading to impatience and frustration among building occupants. The widespread adoption of neural networks and deep learning technologies across various fields and industries represents a significant paradigm shift, and unlocking new avenues for innovation and advancement. These cutting-edge technologies offer unprecedented opportunities to address complex challenges and optimize processes in diverse domains. In this study, LSTM (Long Short-Term Memory) network technology is leveraged to analyze elevator traffic flow within a typical office building. By harnessing the predictive capabilities of LSTM, the research aims to contribute to advancements in elevator group control design, ultimately enhancing the functionality and efficiency of vertical transportation systems in built environments. The findings of this research have the potential to reference the development of intelligent elevator management systems, capable of dynamically adapting to fluctuating passenger demand and optimizing elevator usage in real-time. By enhancing the efficiency and functionality of vertical transportation systems, the research contributes to creating more sustainable, accessible, and user-friendly living environments for individuals across diverse demographics.

GROUP VELOCITY CONTROL SCHEME WITH LOW DISSIPATION

In order to prevent smearing the discontinuity, a modified term is added to the third order Upwind Compact Difference scheme to lower the dissipation error. Moreover, the dispersion error is controled to hold back the non physical oscillation by means of the group velocity control. The scheme is used to simulate the interactions of shock density stratified interface and the disturbed interface developing to vortex rollers. Numerical results are satisfactory.

Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm

Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algorithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance.

A Novel Sliding-mode Guidance Law Based on Lie-group Method

Although the channel-decoupling assumption is often used in design of three-dimensional guidance laws, it loses its rationality for aircrafts with strong kinematics coupling because body rotation arises. To overcome this trouble, a novel guiding method was proposed based on Lie-group. After a model of 3D guidance is formulated using vectors, the precision guidance with ending angular constraints can be transformed into a problem involving the relation between directional angles and rotational angular velocities of certain vectors. When the guidance model is imposed a SO(3)-based description, a novel 3D sliding mode guidance law with ending angular constraints can be developed via Lie-group control method and variable structure control theory. Finally, the feasibility and performance of the guidance law were shown by simulating the examples.

A Dynamic Active Multicast Group Access Control Framework Based on Trust Management System

The current multicast model provides no access control mechanism. Any host can send data directly to a multicast address or join a multicast group to become a member, which brings safety problems to multicast. In this paper, we present a new active multicast group access control mechanism that is founded on trust management. This structure can solve the problem that exists in multicast members＇ access control and distributing authorization of traditional IP multicast.

THE CONTROL OF POLYMETHACRYLATE MOLECULAR STRUCTURE BY GROUP TRANSFER POLYMERIZATION

INTRODUCTION Group transfer polymerization (GTP) is a method for controlling the structure of acrylic polymers in which reactive chain ends are covalentiy bound to a trimethylsilyl group. In the presence of a catalyst, monomer inserts into these chain ends between the silyl group and the last monomer unit. The process is illustrated by equation (1) for methyl methacrylate. GTP is a living polymerization, i. e., there is little or no chain termination and no chain transfer. A significant advantage of GTP is that it

Some Group Runs Based Multivariate Control Charts for Monitoring the Process Mean Vector

In this article, we propose two control charts namely, the “Multivariate Group Runs’ (MV-GR-M)” and the “Multivariate Modified Group Runs’ (MV-MGR-M)” control charts, based on the multivariate normal processes, for monitoring the process mean vector. Methods to obtain the design parameters and operations of these control charts are discussed. Performances of the proposed charts are compared with some existing control charts. It is verified that, the proposed charts give a significant reduction in the out-of-control “Average Time to Signal” (ATS) in the zero state, as well in the steady state compared to the Hotelling’s T2 and the synthetic T2 control charts.

Group control for procedural rules:parameterized complexity and consecutive domains

We consider GROUP CONTROL BY ADDING INDIVIDUALS(GCAI)in the setting of group identification for two procedural rules-the consensus-start-respecting rule and the liberal-start-respecting rule.It is known that GCAI for both rules are NP-hard,but whether they are fixed-parameter tractable with respect to the number of distinguished individuals remained open.We resolve both open problems in the affirmative.In addition,we strengthen the NP-hardness of GCAI by showing that,with respect to the natural parameter the number of added individuals,GCAI for both rules are W[2]-hard.Notably,the W[2]-hardness for the liberal-startrespecting rule holds even when restricted to a very special case where the qualifications of individuals satisfy the so-called consecutive ones property.However,for the consensus-startrespecting rule,the problem becomes polynomial-time solvable in this special case.We also study a dual restriction where the disqualifications of individuals fulfill the consecutive ones property,and show that under this restriction GCAI for both rules turn out to be polynomial-time solvable.Our reductions for showing W[2]-hardness also imply several algorithmic lowerbounds.

APPLICATION OF INTELLIGENCE FORECASTING METHOD IN TRAFFIC ANALYSIS OF EGCS

Traffic flow forecasting is an important part of elevator group control system (EGCS).This paper applies time series prediction theories based on neural networks(NN) to EGCSs traffic analysis,and establishes a time series NN traffic flow forecasting model.Simulation results show its validity.

Psychological effects of colorectal cancer screening: Participants vs individuals not invited

AIM To investigate the possible long-term psychological harm of participating in colorectal cancer(CRC)screening in Norway.METHODS In a prospective, randomized trial, 14294 participants(aged 50-74 years) were invited to either flexible sigmoidoscopy(FS) screening, or a faecal immunochemical test(FIT)(1:1). In total, 4422 screening participants(32%) completed the questionnaire, which consisted of the Hospital Anxiety and Depression Scale and the SF-12, a generic health-related quality of life(HRQOL) measurement, when invited to screening and one year after the invitation. A control group of 7650 individuals was invited to complete the questionnaire only, at baseline and one year after, and 1911(25%) completed the questionnaires.RESULTS Receiving a positive or negative screening result and participating in the two different screening modalities did not cause clinically relevant mean changes in anxiety, depression or HRQOL after one year. FS screening, but not FIT, was associated with an increased probability of being an anxiety case(score ≥ 8) at the one-year follow-up(5.6% of FS participants transitioned from being not anxious to anxious, while 3.0% experienced the reverse). This increase was moderately significantly different from the changes in the control group(in which the corresponding numbers were 4.8% and 4.5%, respectively), P = 0.06. CONCLUSION Most individuals do not experience psychological effects of CRC screening participation after one year, while FS participation is associated with increased anxiety for a smaller group.

Fourth order accurate compact scheme with group velocity control (GVC)

For solving complex flow field with multi-scale structure higher order accurate schemes are preferred. Among high order schemes the compact schemes have higher resolving efficiency. When the compact and upwind compact schemes are used to solve aerodynamic problems there are numerical oscillations near the shocks. The reason of oscillation production is because of non-uniform group velocity of wave packets in numerical solutions. For improvement of resolution of the shock a parameter function is introduced in compact scheme to control the group velocity. The newly developed method is simple. It has higher accuracy and less stencil of grid points.

Optimization of group control strategy and analysis of energy saving in refrigeration plant

This study proposes a group control system optimization strategy coupled with a refrigeration plant model for a primary pump variable flow system,in order to improve the automation level of the refrigeration plant and maximize the energy saving potential.First,the control variables,optimization objectives,and operational con-straints of the entire system were analyzed.Then,by collecting the operational data for each component and combining these data with theoretical analysis,the sub models were designed and the input parameters,output parameters,and optimization variables of each sub-model were defined.Next,the sub-models were coupled and the control variables of the operational combination,leading to the lowest overall system energy consumption,were obtained using a particle swarm optimization algorithm.Finally,considering a medical building in North China as an example,the application effectiveness of the optimal control strategy of the refrigeration plant was analyzed.The results showed that the energy-savings of the group control system after the optimization of the re-frigerator,chilled water pump,cooling water pump,and cooling tower could reach 9.42,8.04,5.67,and 14.64%,respectively.This is a remarkable energy-savings benefit.The research described in this study also provides some reference for the design of group control systems in refrigeration plants.

Attitude maneuvers avoiding forbidden directions

Many space missions require the execution of large-angle attitude slews during which stringent pointing constraints must be satisfied.For example,the pointing direction of a space telescope must be kept away from directions to bright objects,maintaining a prescribed safety margin.In this paper we propose an open-loop attitude control algorithm which determines a rest-to-rest maneuver between prescribed attitudes while ensuring that any of an arbitrary number of body-fixed directions of light-sensitive instruments stays clear of any of an arbitrary number of space-fixed directions.The approach is based on an application of a version of Pontryagin’s Maximum Principle tailor-made for optimal control problems on Lie groups,and the pointing constraints are ensured by a judicious choice of the cost functional.The existence of up to three first integrals of the resulting system equations is established,depending on the number of light-sensitive and forbidden directions.These first integrals can be exploited in the numerical implementation of the attitude control algorithm,as is shown in the case of one light-sensitive and several forbidden directions.The results of the test cases presented confirm the applicability of the proposed algorithm.

The Use and Non-use Values of Ecosystem Services for Hechuan Wetland

Hechuan wetland is located in the mid-Yellow River and at the intersection of Shaanxi, Shanxi and Henan provinces in China. It is the largest hot spring lake wetland in the Yellow River basin and the birthplace of Guanju, a famous poem in theBook of Songs. Based on field investigations and questionnaires, we valued Hechuan Wetland ecosystem services, considering use values and non-use values. The annual use value of Hechuan Wetland ecosystem services is 79.236 bilion CNY. The contingent valuation method was applied to value the annual non-use value, which is 6.27 bilion CNY. We examined how the historical and cultural value of theBook of Songs affected respondents’ willingness to pay by establishing a control group. Results suggest that historical and cultural value does have a strong inlfuence on wilingness to pay.

Nonlinear spectral-like schemes for hybrid schemes

In spectral-like resolution-WENO hybrid schemes,if the switch function takes more grid points as discontinuity points,the WENO scheme is often turned on,and the numerical solutions may be too dissipative.Conversely,if the switch function takes less grid points as discontinuity points,the hybrid schemes usually are found to produce oscillatory solutions or just to be unstable.Even if the switch function takes less grid points as discontinuity points,the final hybrid scheme is inclined to be more stable,provided the spectral-like resolution scheme in the hybrid scheme has moderate shock-capturing capability.Following this idea,we propose nonlinear spectral-like schemes named weighted group velocity control(WGVC)schemes.These schemes show not only high-resolution for short waves but also moderate shock capturing capability.Then a new class of hybrid schemes is designed in which the WGVC scheme is used in smooth regions and the WENO scheme is used to capture discontinuities.These hybrid schemes show good resolution for small-scales structures and fine shock-capturing capabilities while the switch function takes less grid points as discontinuity points.The seven-order WGVC-WENO scheme has also been applied successfully to the direct numerical simulation of oblique shock wave-turbulent boundary layer interaction.

Evaluating the implementation of rapid diagnostic tests in a malaria elimination setting

Background It was recommended that malaria rapid diagnostic tests(RDTs)should be available in all epidemiological situations.But evidence was limited on the implementation of RDTs and its effectiveness in malaria elimination settings.This study examined the implementation of RDTs and how it affected the diagnosis of imported malaria patients in Jiangsu Province,China.Methods To scale up RDTs,this study developed an intervention package with four major elements covering the supply of RDT test,the training on RDTs,the monitoring and management of RDT use,and the advocacy of RDTs.By using a pretest-posttest control group design,we implemented the interventions in 4 cities in Jiangsu Province with the rest nine cities as controlled areas,from January 2017 to January 2018.Difference-in-Difference approach was used to evaluate the impact of the scale-up of RDTs on the identification of malaria cases.Three binary outcome measures were included to indicate delayed malaria diagnosis,malaria cases with confirmed malaria diagnosis at township-level institutions,and severe malaria cases,respectively.Linear probability regression was performed with time and group fixed effects and the interaction term between time and group.Results Intervention areas received sufficient RDT test supply,regular professional training programs,monthly tracking and management of RDT supply and use,and health education to targeted population.The implementation of interventions was associated with 10.8%(P=0.021)fewer patients with delayed diagnosis.But intervention areas did not see a higher likelihood of having confirmed diagnosis from township-level institutions(coefficient=-0.038,P=0.185)or reduced severe malaria cases(coef.=0.040,P=0.592).Conclusions The comprehensive package of RDT implementation in this study is promising in scaling up RDT use and improving access to care among malaria patients,especially in malaria elimination settings.

An applied multi-agent system within the framework of a player-centered probabilistic computer game

The probabilistic model to represent the behavior of an applied multi-agent system that introduces the interaction between a set of agents and Player has been developed within the framework of player-centered probabilistic computer games.The approach features are given with the aid of a game developed for testing cognitive abilities.The agent’s behavior is nondeterministic and therefore unpredictable from Player viewpoint.The system allows both coordinated and autonomous agent’s behavior that depends on availability of information about the presence and position of workable agents for each other.Agent’s behavior is determined with the aid of the algorithm that includes identification of the probabilistic model parameters using maximized objective functions representing individual and group probabilities for Player defeating.Both the model and algorithm ensure the behavior control for relevant applied multi-agent systems.