Trust-based co-operative routing for secure communication in mobile ad hoc networks

The working of a Mobile Ad hoc NETwork(MANET)relies on the supportive cooperation among the network nodes.But due to its intrinsic features,a misbehaving node can easily lead to a routing disorder.This paper presents two trust-based routing schemes,namely Trust-based Self-Detection Routing(TSDR)and Trust-based Cooperative Routing(TCOR)designed with an Ad hoc On-demand Distance Vector(AODV)protocol.The proposed work covers a wide range of security challenges,including malicious node identification and prevention,accurate trust quantification,secure trust data sharing,and trusted route maintenance.This brings a prominent solution for mitigating misbehaving nodes and establishing efficient communication in MANET.It is empirically validated based on a performance comparison with the current Evolutionary Self-Cooperative Trust(ESCT)scheme,Generalized Trust Model(GTM),and the conventional AODV protocol.The extensive simulations are conducted against three different varying network scenarios.The results affirm the improved values of eight popular performance metrics overcoming the existing routing schemes.Among the two proposed works,TCOR is more suitable for highly scalable networks;TSDR suits,however,the MANET application better with its small size.This work thus makes a significant contribution to the research community,in contrast to many previous works focusing solely on specific security aspects,and results in a trade-off in the expected values of evaluation parameters and asserts their efficiency.

Adaptive multicascade attribute reduction based on quantum-inspired mixed co-evolution

Due to the fact that conventional heuristic attribute reduction algorithms are poor in running efficiency and difficult in accomplishing the co-evolutionary reduction mechanism in the decision table, an adaptive multicascade attribute reduction algorithm based on quantum-inspired mixed co-evolution is proposed. First, a novel and efficient self- adaptive quantum rotation angle strategy is designed to direct the participating populations to mutual adaptive evolution and to accelerate convergence speed. Then, a multicascade model of cooperative and competitive mixed co-evolution is adopted to decompose the evolutionary attribute species into subpopulations according to their historical performance records, which can increase the diversity of subpopulations and select some elitist individuals so as to strengthen the sharing ability of their searching experience. So the global optimization reduction set can be obtained quickly. The experimental results show that, compared with the existing algorithms, the proposed algorithm can achieve a higher performance for attribute reduction, and it can be considered as a more competitive heuristic algorithm on the efficiency and accuracy of minimum attribute reduction.

加拿大“Co-operative Education”教育模式研究

通过分析加拿大百年理工学院的"Co-operative Education"实习教育模式,了解了"CO-OP"项目的具体运作方式。加拿大高职实习教育重视政府职能的参与,强调学校、企业和学生的三方合作,通过"COOP"项目实现三方共赢,其模式值得我们借鉴。

滑铁卢大学Co-Operative教育计划概况与启示

在本科毕业生就业日趋严峻的形势下,工作经验成为困惑毕业生求职和用人单位纳才的一个突出问题。如何完善高等教育模式,使大学生的课堂教学和工作经验有机结合是所有高等教育工作者需要思考的一个问题。加拿大滑铁卢大学先进办学理念中的Co-Operative教育计划,将课堂教学和实际工作结合在一起,对我国高校实践教学改革具有借鉴意义。

Applying the Teaching Strategy of Co-operative Learning to ELT

This article focuses on a brief introduction of the teaching strategies of Co-operative Learning(CL). Some of the strategies are chosen to make certain changes in ELT field. It is proved that the Teaching Strategy of CL can be applied in ELT, which makes the classroom teaching more efficient and arose learners’ interests. The Teaching Strategy of CL can help students improve their ability of learning and problem solving. It is a new breakthrough to the traditional teaching model.

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Cooperative co-evolution based distributed path planning of multiple mobile robots

This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution,which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2Dpath planning problems.

Exploration of New Financing Mode of Farmers' Co-operatives——A Case of Guangxi Zhuang Autonomous Region,China

Based on the overview of the role played by farmers' co-operatives in developing rural economy and existing problems,the thesis has introduced the factors which influence the development of farmers' co-operatives including five aspects,namely conditions of scale economy,popularization and application of agricultural production technology,comparative advantage,market expectancy and government support.By analyzing typical cases of three co-operatives in Guangxi(Heng County Dadi Growing Co-operatives,talents-leading share-holding co-operatives;Long'an County Guixiniu Co-operatives,co-operatives led by leading-enterprise;Nanning City Tanluo Town Jinguang Fruits and Potatoes Co-operatives,co-operatives led by leading-enterprise),the way to develop farmers' co-operatives by dint of the external capital has been discussed.The results demonstrate that conditions of scale economy,popularization and application of agricultural production technology,comparative advantage,excellent market expectancy and government support,are conducive to absorbing external capital.Under China's existing economic conditions,the government should normalize the use and allocation procedure of program fund.

Harmony search algorithm with differential evolution based control parameter co-evolution and its application in chemical process dynamic optimization

A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.

Employing Two ‘Sandwich Delay’ Mechanisms to Enhance Predictability of Embedded Systems Which Use Time-Triggered Co-Operative Architectures

In many real-time resource-constrained embedded systems, highly-predictable system behavior is a key design requirement. The “time-triggered co-operative” (TTC) scheduling algorithm provides a good match for a wide range of low-cost embedded applications. As a consequence of the resource, timing, and power constraints, the implementation of such algorithm is often far from trivial. Thus, basic implementation of TTC algorithm can result in excessive levels of task jitter which may jeopardize the predictability of many time-critical applications using this algorithm. This paper discusses the main sources of jitter in earlier TTC implementations and develops two alternative implementations – based on the employment of “sandwich delay” (SD) mechanisms – to reduce task jitter in TTC system significantly. In addition to jitter levels at task release times, we also assess the CPU, memory and power requirements involved in practical implementations of the proposed schedulers. The paper concludes that the TTC scheduler implementation using “multiple timer interrupt” (MTI) technique achieves better performance in terms of timing behavior and resource utilization as opposed to the other implementation which is based on a simple SD mechanism. Use of MTI technique is also found to provide a simple solution to “task overrun” problem which may degrade the performance of many TTC systems.

The Study of Chatting Program in Terms of Co-operative Principle

Nowadays,chatting programs have become very popular among TV audience,because they are well integrated with information,entertainment and leisure.They can bring a lot of laughter as well as elicitation to the audience.However,with the sharp increase of chatting programs on television,some programs which are not well designed emerge at an amazing rate.Our au dience always have a bad feeling to these programs and even mislead by them.My paper analyzes some chatting programs from the perspective of Grice's co-operative principles,and gives some suggestion for how to make chatting program go more smoothly.

Pathogenetic Consequences of Cytomegalovirus-Host Co-evolution

Co-evolution has been shown to result in an adaptive reciprocal modification in the respective behaviors of interacting populations over time. In the case of host-parasite co-evolution,the adaptive behavior is most evident from the reciprocal change in fitness of host and parasite-manifested in terms of pathogen survival versus host resistance. Cytomegaloviruses and their hosts represent a pairing of populations that has co-evolved over hundreds of years. This review explores the pathogenetic consequences emerging from the behavioral changes caused by co-evolutionary forces on the virus and its host.

Comparative study on membership legislation in Canadian and Chinese agricultural co-operative laws

For centuries, groups of people desiring to supply themselves with goods, to market their products, or to obtain services of various kinds on a co-operative basis, have made increasing use of co-operative associations to achieve these purposes. Duringthe period, legislation designed especially for the incorporation and conduct of such associations has been enacted by different counties. Since a co-operative is established and carried on by and for the use of its members, this essay makes a comparison between Canadian and Chinese co-operative laws in terms of membership in the aspects of qualifications, rights and obligations and withdrawal of membership, so as to probe the function of co-operative legislation and find some enlightment from it.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

A cooperative Co-evolutional immune algorithm

A co-evolutional immune algorithm for the optimization of a function with real parameters is de-scribed.It uses a cooperative co-evolution of two populations,one is a population of antibodies and theother is a population of successful mutation vectors.These two population evolve together to improve thediversity of the antibodies.The algorithm described is then tested on a suite of optimization problems.The results show that on most of test functions,this algorithm can converge to the global optimum atquicker rate in a given range,the performance of optimization is improved effetely.

Adaptive Co-evolution Model for Multi-agent System

It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.

A Co-Evolution Model for Dynamic Social Network and Behavior

Individual behaviors, such as drinking, smoking, screen time, and physical activity, can be strongly influenced by the behavior of friends. At the same time, the choice of friends can be influenced by shared behavioral preferences. The actor-based stochastic models (ABSM) are developed to study the interdependence of social networks and behavior. These methods are efficient and useful for analysis of discrete behaviors, such as drinking and smoking;however, since the behavior evolution function is in an exponential format, the ABSM can generate inconsistent and unrealistic results when the behavior variable is continuous or has a large range, such as hours of television watched or body mass index. To more realistically model continuous behavior variables, we propose a co-evolution process based on a linear model which is consistent over time and has an intuitive interpretation. In the simulation study, we applied the expectation maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to find the maximum likelihood estimate (MLE) of parameter values. Additionally, we show that our assumptions are reasonable using data from the National Longitudinal Study of Adolescent Health (Add Health).

Time-Optimal Control Problem for <i>n</i>×<i>n</i>Co-Operative Parabolic Systems with Control in Initial Conditions

In this paper, time-optimal control problem for a liner n× n co-operative parabolic system involving Laplace operator is considered. This problem is, steering an initial state y(0)=u?, with control u?so that an observation y(t) hitting a given target set in minimum time. First, the existence and uniqueness of solutions of such system under conditions on the coefficients are proved. Afterwards necessary and sufficient conditions of optimality are obtained. Finally a scaler case is given.

Constraints Hindering the Adoption of Scientific Dairy Farming Practices by Members and Non-members of Dairy Co-operative Societies （DCS）/Milk Producer Institutions （MPI）

The present study was conducted in four districts of Telangana State of India with 120 respondents in which 60 were members and other 60 were non-members of DCSs （Dairy Co-operative Societies）/MPIs （Milk Producer Institutions）. Constraints perceived in dairy farming and suggestions elicited by members and non-members were noted, tabulated and analyzed. The major constraints perceived by half or more than half of members were scarcity of water （91.67%）, lack of green fodder （88.33%）, preferring NS （natural service） than AI （Artificial Insemination） （83.33%）, negligence in feeding pregnant and dry animals （81.37%）, insufficient loan amount （78.33%）, tendency to feed only grass and brans （71.67%）, lack of availability of sufficient labour （70.00%）, lack of remunerative price for milk （66.67%）, high cost of feed （61.67%）, lack of fodder conservation （55.00%） and high cost of animals （50.00%）. Whereas major constraints perceived by non-members were scarcity of water （96.67%）, lack of green fodder （93.33%）, preferring NS than AI （88.33%）, lack of availability of sufficient labour （85.00%）, negligence in feeding pregnant and dry animals （83.33%）, tendency to feed only grass and brans （78.33%）, high cost of animals （75.00%）, complex procedure for obtaining loans （71.67%） and high cost of feed （66.67%）. Suggestions elicited by members majorly were providing subsidy for purchase of animals/providing loans on par with the cost of animal （81.67%）, enhancing the procurement price （70.00%）, providing more incentives （60.00%）, encouraging calf rearing （58.33%） and conducting frequent animal health camps （50.00%）. In case of non-members major suggestions elicited were conducting frequent animal health camps （68.33%） and providing subsidy on purchase of animals/providing loans on par with the cost of animal （58.33%）. Considering the above constraints perceived and suggestions elicited by dairy farmers a proper linkage strategy should be developed among private and public sectors in providing need based services to the dairy farmers.

Hybrid Support Vector Regression with Parallel Co-Evolution Algorithm Based on GA and PSO for Forecasting Monthly Rainfall

Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.