例谈解题心理过程——从与导数有关问题说起

对于解题者来说,记忆已有问题情境称为＂源＂,当前问题情境称为＂靶＂,在利用＂源＂问题解决＂靶＂问题的过程中,就是建立方法和结构的对应关系.

Research Progress on Resource Utilization of Livestock and Poultry Manure

Although mass livestock and poultry breeding brought magnificent econom-ic benefits to the society, it made great harm to the environment. By reviewing the current status of environmental pol ution caused by livestock and poultry manure in China, harm-free treatment technology for livestock and poultry manure including fer-tilization technology, feed processing technology and energy technology were elabo-rated so as to address the existing issues in this regard and provide references for resource utilization and eliminating environmental pol ution through modified technical system and environment laws.

Problems and Countermeasures of the Bio-energy Development in China

The current development and utilization status of bio-energy at home and abroad was summarized, and a multi-angle in-depth analysis and reflection was given to the problems encountered in the development of bio-energy. Furthermore, some suggestions were put forward to accelerate the further development of bio-en-ergy industry in China.

Separation method for multi-source blended seismic data

Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.

Virtual Machine Scheduling for Improving Energy Efficiency in laaS Cloud

In IaaS Cloud,different mapping relationships between virtual machines(VMs) and physical machines(PMs) cause different resource utilization,so how to place VMs on PMs to reduce energy consumption is becoming one of the major concerns for cloud providers.The existing VM scheduling schemes propose optimize PMs or network resources utilization,but few of them attempt to improve the energy efficiency of these two kinds of resources simultaneously.This paper proposes a VM scheduling scheme meeting multiple resource constraints,such as the physical server size(CPU,memory,storage,bandwidth,etc.) and network link capacity to reduce both the numbers of active PMs and network elements so as to finally reduce energy consumption.Since VM scheduling problem is abstracted as a combination of bin packing problem and quadratic assignment problem,which is also known as a classic combinatorial optimization and NP-hard problem.Accordingly,we design a twostage heuristic algorithm to solve the issue,and the simulations show that our solution outperforms the existing PM- or network-only optimization solutions.

Study on Development Process and Mechanism of Ecological Compensation in Beijing and Hebei Province

The problem of water resources has become a bottleneck for the sustainable development of Beijing and Hebei Province (the two regions together are called "Jingji Region" for short).It is imperative to establish an effective and equitable water resources ecological compensation (eco-compensation) mechanism.The three stages of water resources eco-compensation are expatiated here namely the eco-compensation missing stage,ecocompensation start stage and the eco-compensation development stage.Through the establishment of eco-compensation game model based on the game theory,the reasons of the formation for the three stages were analyzed,as well as the conversion conditions from non-cooperative game to cooperative game among the related stakeholders including the central government,the water recipient government and the water source government.Furthermore,this study pointed out that the water resources eco-compensation in Jingji Region was not established based on the institution,but formed and developed in coping with the challenges of water crisis.However,institution construction is quite essential in game process for the water recipient government and the water source government.Finally recommendations in four areas including legalization of eco-compensation mechanism,setting up compensation standards,leading industrial upgrading and developing related incentives and constraints were concluded.

How People Use Earthquake Information and Its Influence on Household Preparedness in New Zealand

Forty-eight interviews were undertaken with residents in Timaru, Wanganui and Napier, New Zealand, in 2008 to explore how people understand and use information about earthquake hazards and preparedness, and how this process affects actual preparedness. Three main types of information were identified as being utilized by people： passive information （e.g., newspapers, brochures, TV, radio, websites）, interactive information （e.g., community activities, school activities~ and workplace activities）, and experiential information （e.g., experiencing a hazardous event, responding to an event, and working in an organization that deals with hazards）. People tended to either contextualize hazard and preparedness information around any prevailing beliefs they had or form new beliefs on exposure to information. A number of core beliefs were identified as crucial for helping people consider that preparing is important and motivating actual adjustment adoption. Society also has an influence on how people interpret information and form intentions to prepare. People are often influenced by the opinions of others, and as preparing for disasters is not seen as a societal norm, this can cause people not to prepare. Feeling a responsibility for others （e.g., children） appears to be a major driver of preparedness. Other societal factors such as trust, leadership and sense of community also influence interpretation, dissemination and use of hazards and preparedness information. Finally, a number of resource issues can help or hinder preparedness.

Balanced energy-efficient relay selection scheme in wireless mobile relay networks

In order to resolve the relay selection problem in wireless mobile relay networks （WMRNs）, a novel balanced energy-efficient mobile relay selection scheme is proposed in this paper. Compared with traditional counter-based algorithm, distance and energy consumption are considered from network respect to provide a better network lifetime performance in the proposed scheme. Also, it performs well when nodes move freely at high speed. A random assessment delay （RAD） mechanism is added to avoid collisions and improve transmission efficiency. Simulation results reveal that, the proposed scheme has advantages in prolonging network lifetime, balancing energy compared with existing counter-based scheme. consumption and reducing the total energy consumption

Optimal joint relay selection and resource allocation with QoS constraints in multiuser OFDM-based cellular networks

This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.

Cooperative Game Approach for Scheduling in Two-Virtual-Antenna Cellular Networks with Relay Stations Fairness Consideration

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.

Try and error-based scheduling algorithm for cluster tools of wafer fabrications with residency time constraints

To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an objective of minimizing Makespan for the wafer jobs in cluster tools.Firstly,mathematical formulations of scheduling problems were presented by using assumptions and definitions of a scheduling domain.Resource conflicts were analyzed in the built scheduling model,and policies to solve resource conflicts were built.A scheduling algorithm was developed.Finally,the performances of the proposed algorithm were evaluated and compared with those of other methods by simulations.Experiment results indicate that the proposed algorithm is effective and practical in solving the scheduling problem of the cluster tools.

Joint subcarrier and power allocation with threshold in cooperative multiuser networks

In this paper, we investigate a resource allocation issue in OFDMA-based decode-and-forward cooperative multiuser networks and propose joint subcarrier and power allocation schemes. The optimal solution of this combinable allocation shows high computational complexity, so we allocate subcarriers and power separately. At firstly, we distribute subcarriers to relays and users under the assumption of equal power distribution. Here, we propose an equal capacity increment （ECI） allocation strategy to achieve tradeoff between total throughput and fairness. To further improve the system performance, we introduce threshold into ECI strategy, named ECI strategy with threshold （ECI-T）, where subcarriers with bad performance are prevented from transmitting. Subsequently, a water-filling method is adopted to distribute the power to cooperative links in order to fully utilize the limited power. Simulation results show that system performance of the proposed schemes is significantly enhanced compared with an existing resource allocation scheme. Besides, the resource allocation schemes with the water- filling method notably outperform schemes with equal power allocation.

Noisy Chaotic Neural Network for Resource Allocation in High-Speed Train OFDMA System

High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.

Climate-induced Changes in Spring Maize Water Requirement in Xiliaohe River Watershed

Xiliaohe River watershed plays an important role in regional and national grain security.With the development of society and economy,water consumption that increased dramatically causes water shortages.Crop water requirement can provide quantitative basis for making regional irrigation scheme.In this study,spring maize water requirement is calculated by using PenmanMonteith formula and spring maize coefficient from May to September at 10 meteorological stations in Xiliaohe River watershed from 1951 to 2005.The variation trend of the spring maize water requirement during the whole growing stage,water requirement in every month,and meteorological influencing factors are obtained by using Mann-Kendall method,and the degree of grey incidence between the water requirement and meteorological influencing factors are shown.The results are the spring maize water requirement during the whole growing stages increases at half of the stations in Xiliaohe River watershed,and are remarkably affected by the water requirement in May.The monthly mean,maximum and minimum air temperature form May to September show an increasing trend in Xiliaohe River watershed in recent 55 years.The monthly mean and minimum air temperature increases notably.The relative humidity,precipitation,wind speed and sunshine show a decreasing trend with variety for different months.The monthly maximum air temperature,wind speed,sunshine and monthly mean air temperature have the highest correlation degree with spring maize water requirement from May to September.

A novel dynamic call admission control policy for wireless network

To address the issue of resource scarcity in wireless communication, a novel dynamic call admission control scheme for wireless mobile network was proposed. The scheme established a reward computing model of call admission of wireless cell based on Markov decision process, dynamically optimized call admission process according to the principle of maximizing the average system rewards. Extensive simulations were conducted to examine the performance of the model by comparing with other policies in terms of new call blocking probability, handoff call dropping probability and resource utilization rate. Experimental results show that the proposed scheme can achieve better adaptability to changes in traffic conditions than existing protocols. Under high call traffic load, handoff call dropping probability and new call blocking probability can be reduced by about 8%, and resource utilization rate can be improved by 2%-6%. The proposed scheme can achieve high source utilization rate of about 85%.

Indoor measurement method of smoke screen disturbance efficiency based on Gaussian diffusion model

Because of ground clutter wave interf e rence,it is difficult to measure smoke screen disturbance in the field.In this pape r,a kind of indoor measurement method of smoke screen disturbance efficiency ba sed on Gaussian diffusion model is put forward.As a characteristic,the measur ement result of smoke screen area density proves that the indoor measurement met hod of smoke screen disturbance efficiency based on Gaussian diffusion model is fea sible.

Recovery of metals and other beneficial products from coal fly ash： a sustainable approach for fly ash management

Increasing production and disposal of coal fly ash （CFA） is a matter of serious environment concern. However, CFA contains various beneficial metals and mineral matters whose demand is increasing in the industrialized world, while natural supplies are diminishing. Therefore, recovery of these potential resources from CFA can be an alternative way to save mineral resources, as well as to reduce the environmental burden of CFA disposal. There are numerous methods developed for the recovery of beneficial products from CFA. Based on the US patents and journal literatures, the present review describes the recovery status and technologies of major elements such as Al, Si, Fe and Ti, and trace elements such as V, Ga, Ge, Se, Li, Mo, U, Au, Ag, Pt groups and rare earth elements （REEs） and other beneficial products such as magnetic materials, cenospheres, and unburned carbon from CFA. It also highlights the recovery efficiency and drawbacks for their extraction, and suggests future research to develop satisfactory results in terms of selective recovery and purification.

Progress and Challenges of Shale Gas Exploration and Development in China

China is abandant in shale gas resources. Encouraged by the successful development of shale gas resources in the U. S., China began its shale gas research and exploration activity about 10 years ago. This paper briefed the history, state quo and future of shale gas development in the country. Factors that constrain the shale gas industry there include technology limitations, attitude of the government, environmental concerns and etc. The future of the shale gas industry in China depends heavily on how well these issues are dealt.

A New Algorithm for Resource Constraint Project Scheduling Problem Based on Multi-Agent Systems

The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocation decision involved in RCPSP has also been developed. And this algorithm can be used in the multi-project scheduling field as well.Finally, an illustration is given.

Underdetermined Blind Source Separation of Adjacent Satellite Interference Based on Sparseness

The problem of underdetermined blind source separation of adjacent satellite interference is proposed in this paper. Density Clustering algorithm(DC-algorithm) presented in this article is different from traditional methods. Sparseness representation has been applied in underdetermined blind signal source separation. However, some difficulties have not been considered, such as the number of sources is unknown or the mixed matrix is ill-conditioned. In order to find out the number of the mixed signals, Short Time Fourier Transform(STFT) is employed to segment received mixtures. Then, we formulate the blind source signal as cluster problem. Furthermore, we construct Cost Function Pair and Decision Coordinate System by using density clustering. At the end of this paper, we discuss the performance of the proposed method and verify the novel method based on several simulations. We verify the proposed method on numerical experiments with real signal transmission, which demonstrates the validity of the proposed method.