Improving Federated Learning through Abnormal Client Detection and Incentive

Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

Carbon Abatement Cost-Sharing Strategy for Electric Power Sector Based on Incentive and Subsidy Mechanisms

The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.

Stackelberg Game-Based Optimal Dispatch for PEDF Park and Power Grid Interaction under Multiple Incentive Mechanisms

The integration of photovoltaic,energy storage,direct current,and flexible load(PEDF)technologies in building power systems is an importantmeans to address the energy crisis and promote the development of green buildings.The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid.For this purpose,this work introduces a framework of multiple incentive mechanisms for a PEDF park,a building energy system that implements PEDF technologies.The incentive mechanisms proposed in this paper include both economic and noneconomic aspects,which is the most significant innovation of this paper.By modeling the relationship between a PEDF park and the power grid into a Stackelberg game,we demonstrate the effectiveness of these incentive measures in promoting the friendly interaction between the two entities.In this game model,the power grid determines on the prices of electricity trading and incentive subsidy,aiming to maximize its revenue while reducing the peak load of the PEDF park.On the other hand,the PEDF park make its dispatch plan according to the prices established by the grid,in order to reduce electricity consumption expense,improve electricity utility,and enhance the penetration rate of renewable energy.The results show that the proposed incentive mechanisms for the PEDF park can help to optimize energy consumption and promote sustainable energy practices.

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

Research on the Improvement of Incentive Mechanism for Pharmaceutical Sales Personnel - Taking Company A as an Example

Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.

Will the perceptions to incentive policies have any effect on users' willingness to participate in Mobility-as-a-Service?

With the increasing severity of urban traffic congestion and environmental pollution issues,Mobility-as-a-Service(MaaS)has garnered increasing attention as an emerging mode of transportation.Thus,how to motivate users to participate in MaaS has become an important research issue.This study first classified the incentive policies into four aspects:financial incentive policy,non-financial incentive policy,information policy,and convenience policy.Then,through online questionnaires and field interviews,456 sets of data were collected in Beijing,and the data were analyzed by the structural equation model and latent class model.The results show that the four incentive policies are positively correlated with users'participation in MaaS,among which financial incentive policy and information policy have the greatest impact,that is,they can better encourage users by increasing direct financial subsidies and broadening the information about MaaS.In addition,Latent Class Analysis was performed to class different users and it was found that the personal characteristics of users had some influence on willingness to participate in MaaS.Therefore,incentive policies should be designed to consider the needs and characteristics of different user groups to improve their willingness to participate in MaaS.The results can provide theoretical suggestions for the government to promote the widespread application of MaaS in urban transportation.

Incentive mechanism analysis of information security outsourcing based on principal-agent model

In order to solve principal-agent problems caused by interest inconformity and information asymmetry during information security outsourcing, it is necessary to design a reasonable incentive mechanism to promote client enterprises to complete outsourcing service actively. The incentive mechanism model of information security outsourcing is designed based on the principal-agent theory. Through analyzing the factors such as enterprise information assets value, invasion probability, information security environment, the agent cost coefficient and agency risk preference degree how to impact on the incentive mechanism, conclusions show that an enterprise information assets value and invasion probability have a positive influence on the fixed fee and the compensation coefficient; while information security environment, the agent cost coefficient and agency risk preference degree have a negative influence on the compensation coefficient. Therefore, the principal enterprises should reasonably design the fixed fee and the compensation coefficient to encourage information security outsourcing agency enterprises to the full extent.

Performance-based methodology for assessing seismic vulnerability and capacity of buildings

This paper presents a performance-based methodology for the assessment of seismic vulnerability and capacity of buildings. The vulnerability assessment methodology is based on the HAZUS methodology and the improved capacity- demand-diagram method. The spectral displacement (Sd) of performance points on a capacity curve is used to estimate the damage level of a building. The relationship between Sd and peak ground acceleration (PGA) is established, and then a new vulnerability function is expressed in terms of PGA. Furthermore, the expected value of the seismic capacity index (SCev) is provided to estimate the seismic capacity of buildings based on the probability distribution of damage levels and the corresponding seismic capacity index. The results indicate that the proposed vulnerability methodology is able to assess seismic damage of a large number of building stock directly and quickly following an earthquake. The SCev provides an effective index to measure the seismic capacity of buildings and illustrate the relationship between the seismic capacity of buildings and seismic action. The estimated result is compared with damage surveys of the cities of Dujiangyan and Jiangyou in the M8.0 Wenchuan earthquake, revealing that the methodology is acceptable for seismic risk assessment and decision making. The primary reasons for discrepancies between the estimated results and the damage surveys are discussed.

A Study on the Multi-Task Incentive Mechanism for the Service Provider

Both conflict and asymmetric information exist betweenthe telecom operators and the service provider,and result in illegal behaviors of the service provider.The relationship between the telecom operators andthe service provider is classical multi-task principalagentrelationship. The multi-task incentive for theservice provider is considered in the design of theprincipal-agent incentive contract, and it is necessaryto add the multi-task incentive to the serviceproviders through the analysis of the risk costs andthe agency costs of this problem.

RTRC:A Reputation-Based Incentive Game Model for Trustworthy Crowdsourcing Service

The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for these systems is how to design a proper mechanism such that the crowds spontaneously act as suppliers to contribute accurate information. Most of existing mechanisms ignore either the honesty of crowds or requesters respectively. In this paper, considering the honesty of both, we propose a game-based incentive mechanism, namely RTRC, to stimulate the crowds to contribute accurate information and to motivate the requesters to return accurate feedbacks. In addition, an evolutionary game is designed to model the dynamic of user-strategy selection. Specially, the replicator dynamic is applied to model the adaptation of strategy interactions taking into account the dynamic nature in time dependence and we also derive the evolutionarily stable strategies(ESSs) for users. Finally, empirical results over the simulations show that all the requesters and suppliers will select honest strategy to maximize their profit.

Performance-based seismic design of nonstructural building components:The next frontier of earthquake engineering

With the development and implementation of performance-based earthquake engineering,harmonization of performance levels between structural and nonstructural components becomes vital. Even if the structural components of a building achieve a continuous or immediate occupancy performance level after a seismic event,failure of architectural,mechanical or electrical components can lower the performance level of the entire building system. This reduction in performance caused by the vulnerability of nonstructural components has been observed during recent earthquakes worldwide. Moreover,nonstructural damage has limited the functionality of critical facilities,such as hospitals,following major seismic events. The investment in nonstructural components and building contents is far greater than that of structural components and framing. Therefore,it is not surprising that in many past earthquakes,losses from damage to nonstructural components have exceeded losses from structural damage. Furthermore,the failure of nonstructural components can become a safety hazard or can hamper the safe movement of occupants evacuating buildings,or of rescue workers entering buildings. In comparison to structural components and systems,there is relatively limited information on the seismic design of nonstructural components. Basic research work in this area has been sparse,and the available codes and guidelines are usually,for the most part,based on past experiences,engineering judgment and intuition,rather than on objective experimental and analytical results. Often,design engineers are forced to start almost from square one after each earthquake event: to observe what went wrong and to try to prevent repetitions. This is a consequence of the empirical nature of current seismic regulations and guidelines for nonstructural components. This review paper summarizes current knowledge on the seismic design and analysis of nonstructural building components,identifying major knowledge gaps that will need to be filled by future research. Furthermore,considering recent trends in earthquake engineering,the paper explores how performance-based seismic design might be conceived for nonstructural components,drawing on recent developments made in the field of seismic design and hinting at the specific considerations required for nonstructural components.

Incentive Scheme for Slice Cooperation Based on D2D Communication in 5G Networks

In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.

More children nutrition distribution, less labor incentive: Evidence from Chinese collective agriculture

Distribution system will affect the labor incentive that has been heatedly discussed by recent literatures.Using a unique micro dataset, this paper dem on strates that the equalitaria n distributi on system is one of the reas ons for the in sufficie nt labor incentive during the Chinese Collective Agriculture period. Specifically speaking, in the distribution of basic rations, the proportion for children (aged 1-3 and 4-7 years) was often beyond their nutrition demand, resulting the dissatisfaction of other families with more laborers and less children, thus these households will reduce their labor supply gradually. At the same time, the existence of outstanding accounts makes it a failure to use work points to buy distributions, which is the mechanism of the distribution system and insufficient labor incentive. All the results have been accepted by the robustness tests. The study will help to understand the distribution system and labor incentive, as well as the failure of the Chinese collective agriculture.

Patient attitudes about financial incentives for diabetes self-management:A survey

AIM:To study the acceptability of incentives for behavior changes in individuals with diabetes,comparing financial incentives to self-rewards and non-financial incentives.METHODS:A national online survey of United States adults with diabetes was conducted in March 2013(n = 153).This survey was designed for this study,with iterative testing and modifications in a pilot population.We measured the demographics of individuals,their interest in incentives,as well as the perceived challenge of diabetes self-management tasks,and expectations of incentives to improve diabetes self-management(financial,non-financial and self-rewards).Using an ordered logistic regression model,we assessed the association between a 32-point score of the perceived challenge of the self-management tasks and the three types of rewards.RESULTS:Ninety-six percent of individuals were interested in financial incentives,60% in non-financial incentives and 72% in self-rewards.Patients were less likely to use financial incentives when they perceived the behavior to be more challenging(odds ratio of using financial incentives of 0.82(95%CI:0.72-0.93) for each point of the behavior score).While the effectiveness of incentives may vary according to the perceived level of challenge of each behavior,participants did not expect to need large amounts to motivate them to modify their behavior.The expected average amounts needed to motivate a 5 lb weight loss in our population and to maintain this weight change for a year was $258(interquartile range of $10-100) and $713(interquartile range of $25-250) for a 15 lb weight loss.The difference in mean amount estimates for 5 lb and 15 lb weight loss was significant(P < 0.001).CONCLUSION:Individuals with diabetes are willing to consider financial incentives to improve diabetes selfmanagement.Future studies are needed to explore incentive programs and their effectiveness for diabetes.

E-Supply Chain Incentive and Coordination Based on Revenue Sharing Contract

This paper took the buyer-biased electronic market as an example, where multiple suppliers selling short-life-cycle products are bidding for an order from a powerful buyer with stochastic customer demand. It used a single period newsvendor model to analyze the decision of supplied and buyers to do or not do business online. The results suggest that lack of Incentive is the key factor of B2B electronic markets failure. At the same time, it designed a revenue sharing contract to coordinate the E-supply chain in order to prevent failure of E-market.

A case study of performance-based pavement maintenance and rehabilitation needs assessment in Pennsylvania

This paper presents the theory,method,and application of performance-based pavement needs assessment at a state level,using the Pennsylvania Interstate System as an example.First,a general framework is presented for the pavement asset management and a general optimization model is established for the pavement maintenance and rehabilitation needs assessment.Also,the bundling of pavement segments for the project implementation is discussed.Using the examples of Statewide Transportation Improvement Plan and Long Range Transportation Plan for Pennsylvania Interstate System,the application of performance-based pavement needs assessment is demonstrated.It is shown that unconstrained analysis can help decision-makers investigate the real maintenance and rehabilitation needs;financially-constrained analysis can help decision-makers select projects for implementation and examine the corresponding future pavement conditions.Trade-off analysis can help decision-makers investigate the outcomes of different investment levels on pavement maintenance and rehabilitation and make the final decision on the investment level.The proposed case study provides a good example of performance-based pavement needs assessment for developing countries.

The Flemish Performance-based Research Funding System: A Unique Variant of the Norwegian Model

The BOF-key is the performance-based research funding system that is used in Flanders, Belgium. In this paper we describe the historical background of the system, its current design and organization, as well as its effects on the Flemish higher education landscape. The BOFkey in its current form relies on three bibliometric parameters: publications in Web of Science, citations in Web of Science, and publications in a comprehensive regional database for SSH publications. Taken together, the BOF-key forms a unique variant of the Norwegian model: while the system to a large extent relies on a commercial database, it avoids the problem of inadequate coverage of the SSH. Because the bibliometric parameters of the BOF-key are reused in other funding allocation schemes, their overall importance to the Flemish universities is substantial.

Innovation Incentive of Downstream Firms in Stackelberg Duopoly Model

The licensing strategies and innovation incentives of downstream firms in a Stackelberg duopoly model were analyzed under three respective assumptions that upstream industry is monopoly, duopoly, or perfect competition. It is found that the Stackelberg firm may license his drastic innovation by a fixed royalty rate which is lower than innovalion size. The incentives of drastic innovation of Stackelberg firm facing input suppfiers with market power decrease considerably even onder royalty licensing, compared with facing perfectly competitive input market.