Overview and Graph Theory of the Immune System of Crustacean

In this paper,different kinds of enzymes,immune factors and regulatory factors of the immune system of crustaceans are summarized and then combed systematically and thoroughly. According to the mutual influence and effects of these factors,different symbolic forms are introduced to express the effects,and ultimately the whole node graph of the system is obtained. The graph theory can be used for further researches on the immune system of crustacean.

Modelling of a WDM Network Using Graph Theory and Dijkstra Algorithm for Traffic Redirection

Optical transport networks are now the basic infrastructure of modern communications systems, including the SDH and WDM backbone network of local network operators, in the case of Cameroon. Given the colossal investments required to deploy these networks, particularly related to the cost of equipment (optical fibers, transponders and multiplexers), the optimization of bandwidth and dynamic allocation of resources is essential to control operating costs and ensure continuity of service. Automatic switching technology for optical networks brings intelligence to the control plane to fully facilitate bandwidth utilization, traffic redirection, and automatic configuration of end-to-end services. This paper considers a local network operator’s WDM network without the implementation of the automatic switching technology, develops a network modeling software platform called Graphic Networks and using graph theory integrates a particularity of the automatic switching technology, which is the automatic rerouting of traffic in case of incident in the network. The incidents considered here are those links or route failures and node failures.

Game Theory Algorithm of Reconfiguration for Shipboard Power System

船舶电力系统故障重构通过改变系统供电路径来恢复重要负载的供电，对增强系统的存活性有着重要意义。在多智能体（agent）架构的基础上，构建船舶电力系统博弈重构模型并提出求解方法。该模型以船舶电力系统中不同区域的agent作为博弈参与者，将船舶电力系统的重构问题转化为各agent之间的合作一竞争问题，从而保证重要负载的恢复供电。论文进一步提出该模型的求解算法，该算法首先判断博弈模式的合作与非合作属性，之后通过agent或agent联盟之间的博弈过程，计算各agent所属的负载／发电机的投切及转移策略。仿真算例表明，该算法能够快速有效地求解船舶电力系统重构问题，最大程度保证系统的存活性。

Fault Diagnosis Based on Graph Theory and Linear Discriminant Principle in Electric Power Network

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.

Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using Game Theory (GT) and Neural Networks (NN). Also, due to the stochastic behavior of power markets and generators’ forced outages, Monte Carlo Simulation (MCS) is used for reliability evaluation. Generation reliability focuses merely on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using GT, two outcomes are considered: cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. Loss of Load Expectation (LOLE) is used as the reliability index and the results show generation reliability in cooperation market is better than non-cooperation outcome.

Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

Security Risk Assessment of Cyber Physical Power System Based on Rough Set and Gene Expression Programming

Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality. © 2014 Chinese Association of Automation.

Reliability and sensitivity analysis of loop-designed security and stability control system in interconnected power systems

Security and stability control system(SSCS)in power systems involves collecting information and sending the decision from/to control stations at different layers;the tree structure of the SSCS requires more levels.Failure of a station or channel can cause all the execution stations(EXs)to be out of control.The randomness of the controllable capacity of the EXs increases the difficulty of the reliability evaluation of the SSCS.In this study,the loop designed SSCS and reliability analysis are examined for the interconnected systems.The uncertainty analysis of the controllable capacity based on the evidence theory for the SSCS is proposed.The bidirectional and loop channels are introduced to reduce the layers and stations of the existing SSCS with tree configuration.The reliability evaluation and sensitivity analysis are proposed to quantify the controllability and vulnerable components for the SSCS in different configurations.By aiming at the randomness of the controllable capacity of the EXs,the uncertainty analysis of the controllable capacity of the SSCS based on the evidence theory is proposed to quantify the probability of the SSCS for balancing the active power deficiency of the grid.

Identifying multiple influential spreaders in complex networks based on spectral graph theory

One of the hot research topics in propagation dynamics is identifying a set of critical nodes that can influence maximization in a complex network.The importance and dispersion of critical nodes among them are both vital factors that can influence maximization.We therefore propose a multiple influential spreaders identification algorithm based on spectral graph theory.This algorithm first quantifies the role played by the local structure of nodes in the propagation process,then classifies the nodes based on the eigenvectors of the Laplace matrix,and finally selects a set of critical nodes by the constraint that nodes in the same class are not adjacent to each other while different classes of nodes can be adjacent to each other.Experimental results on real and synthetic networks show that our algorithm outperforms the state-of-the-art and classical algorithms in the SIR model.

Channel Assignment Method Using Parallel Tabu Search Based on Graph Theory in Wireless Sensor Networks

Wireless sensor networks are suffering from serious frequency interference.In this paper,we propose a channel assignment algorithm based on graph theory in wireless sensor networks.We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks.The channel assignment problem is equivalent to the generalized graph-coloring problem which is a NP-complete problem.We further present a meta-heuristic Wireless Sensor Network Parallel Tabu Search(WSN-PTS) algorithm,which can optimize global networks with small numbers of iterations.The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.

A Computational Synthesis Approach of Mechanical Conceptual Design Based on Graph Theory and Polynomial Operation

The design synthesis is the key issue in the mechanical conceptual design to generate the design candidates that meet the design requirements.This paper devotes to propose a novel and computable synthesis approach of mechanisms based on graph theory and polynomial operation.The graph framework of the synthesis approach is built firstly,and it involves:(1)the kinematic function units extracted from mechanisms;(2)the kinematic link graph that transforms the synthesis problem from mechanical domain into graph domain;(3)two graph representations,i.e.,walk representation and path representation,of design candidates;(4)a weighted matrix theorem that transforms the synthesis process into polynomial operation.Then,the formulas and algorithm to the polynomial operation are presented.Based on them,the computational flowchart to the synthesis approach is summarized.A design example is used to validate and illustrate the synthesis approach in detail.The proposed synthesis approach is not only supportive to enumerate the design candidates to the conceptual design of a mechanical system exhaustively and automatically,but also helpful to make that enumeration process computable.

Multi-Body Dynamics Modeling and Simulation Analysis of a Vehicle Suspension Based on Graph Theory

Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test.Then,it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results.The results show that the model has high precision and can predict the performance of the vehicle.It also provides a new solution for the vehicle dynamic modeling.

Applications of Graph Theory to Gross Error Detection for GPS Geodetic Control Networks

This paper describes a broad perspective of the application of graph theory to establishment of GPS control networks whereby the GPS network is considered as a connected and directed graph with three components.In this algorithm the gross error detection is undertaken through loops of different spanning trees using the "Loop Law" in which the individual components Δ X, Δ Y and Δ Z sum up to zero.If the sum of the respective vector components ∑X,∑Y and ∑Z in a loop is not zero and if the error is beyond the tolerable limit (ε>w),it indicates the existence of gross errors in one of the baselines in the loop and therefore the baseline must be removed or re_observed.After successful screening of errors by graph theory,network adjustment can be carried out.In this paper,the GPS data from the control network established as reference system for the HP Dam at Baishan county in Liaoning province is presented to illustrate the algorithm.

Effect of graph generation on slope stability analysis based on graph theory

Limit equilibrium method （LEM） and strength reduction method （SRM） are the most widely used methods for slope stability analysis. However, it can be noted that they both have some limitations in practical application. In the LEM, the constitutive model cannot be considered and many assumptions are needed between slices of soil/rock. The SRM requires iterative calculations and does not give the slip surface directly. A method for slope stability analysis based on the graph theory is recently developed to directly calculate the minimum safety factor and potential critical slip surface according to the stress results of numerical simulation. The method is based on current stress state and can overcome the disadvantages mentioned above in the two traditional methods. The influences of edge generation and mesh geometry on the position of slip surface and the safety factor of slope are studied, in which a new method for edge generation is proposed, and reasonable mesh size is suggested. The results of benchmark examples and a rock slope show good accuracy and efficiency of the presented method.

INTERFERENCE COORDINATION METHOD BASED ON GRAPH THEORY IN TWO-TIER CELLULAR NETWORKS

This paper studies an interference coordination method by means of spectrum allocation in Long-Term Evolution (LTE) multi-cell scenario that comprises of macrocells and femtocells. The purpose is to maximize the total throughput of femtocells while ensuring the Signal-to-Interference plus Noise Ratio (SINR) of the edge macro mobile stations (mMSs) and the edge femtocell Mobile Stations (fMSs). A new spectrum allocation algorithm based on graph theory is proposed to reduce the interference. Firstly, the ratio of Resource Blocks (RBs) that mMSs occupy is obtained by genetic algorithm. Then, after considering the impact of the macro Base Stations (mBSs) and small scale fading to the fMS on different RBs, multi-interference graphs are established and the spectrum is allocated dynamically. The simulation results show that the proposed algorithm can meet the Quality of Service (QoS) requirements of the mMSs. It can strike a balance between the edge fMSs' throughput and the whole fMSs' throughput.

Model and Algorithm for the Optimal Controlled Partitioning of Power Systems

解列是电力系统在故障时结构完整性得不到保证的情况下分裂为2个或多个孤立稳定运行子系统的过程或操作。及时恰当的主动解列操作将能有效地避免因保护连锁动作使得电力系统被动解列而崩溃所造成的巨额经济损失。结合图论中的相关概念和输电网最优解列的物理过程，建立电力系统最优主动解列断面选择问题的完整数学模型，并基于含连通图约束的背包问题（connected graph constrained knapsack problem，CGKP）及其求解算法提出“搜索＋调整”的2阶段求解方法。为降低问题的复杂性，将完整数学模型分解成图的最优平衡分割问题和基于优化潮流的调节问题，并分2个阶段分别求解。其中，图的最优平衡分割问题又被分解成多个CGKP，利用基于含CGKP的图分割方法进行求解。所提出的主动解列策略具有较强理论基础，计算复杂度低，算例的计算结果证明了该模型及算法的正确性和有效性。

Alterations of Cerebral Functional Connectivity in Patients with Frontal Lobe Epilepsy:A Graph Theory Study

The aim of the present study is to investigate the brain functional network changes of patients with frontal lobe epilepsy(FLE)by resting-state functional magnetic resonance imaging(rsfMRI)and graph theoretical analysis.rsfMRI is performed in 46 adult patients with FLE and 46 age matched healthy controls(HCs).A functional network is built from these subjects,and the topological properties of such network are analyzed quantitatively using graph theoretical methods.According to the results,both FLE patients and HCs exhibit prominent small world features.Compared with HCs,FLE shows a decrease in local efficiency(Eloc),clustering coefficient,nodal efficiency as well as nodal degree.Furthermore,FLE(seven)has fewer hubs than HCs(ten).The functional abnormalities in the network organization suggest functional disturbances in patients with FLE.This study helps to gain new insights into the functional disorder in patients with FLE.The networks built here can also be a set of potential biomarkers for the diagnosis,monitoring and the treatment of FLE.

Regional differences in gully network connectivity based on graph theory:a case study on the Loess Plateau,China

Material exchange frequently occurs in gullies,and thus the relationship between a gullynetwork structure and sediment transport potential has attracted considerable interest.However,previous researches ignored the difficulty of material transport from sources to sinks,and did not quantify the connectivity of a network structure.In this study,we used a graph model structure to model gully networks of six typical sample areas in the Loess Plateau of China and quantified gully network connectivity using four indexes:average node strength,accessibility from sources to sinks,potential flow,and network structural connectivity index.Results show that:(1)Reflected by different quantitative indexes,the trends of gully network connectivity in different regions are similar.From north to south,the connectivity of a sample area first increases and then decreases.(2)The more mature gullies have stronger network connectivity.Small resistance is conducive to material transport in the gullies.(3)The node connectivity index of the gully network shows a significant aggregation distribution in space,and node connectivity on the main channel is often stronger than that on the branch trench.These results not only deepen the understanding of the process and mechanism of loess gully geomorphic development and evolution but also provide a reference for geomorphic studies.

FastCluster: a graph theory based algorithm for removing redundant sequences

In many cases, biological sequence databases contain redundant sequences that make it difficult to achieve reliable statistical analysis. Removing the redundant sequences to find all the real protein families and their representatives from a large sequences dataset is quite important in bioinformatics. The problem of removing redundant protein sequences can be modeled as finding the maximum independent set from a graph, which is a NP problem in Mathematics. This paper presents a novel program named FastCluster on the basis of mathematical graph theory. The algorithm makes an improvement to Hobohm and Sander’s algorithm to generate non-redundant protein sequence sets. FastCluster uses BLAST to determine the similarity between two sequences in order to get better sequence similarity. The algorithm’s performance is compared with Hobohm and Sander’s algorithm and it shows that Fast- Cluster can produce a reasonable non-redundant pro- tein set and have a similarity cut-off from 0.0 to 1.0. The proposed algorithm shows its superiority in generating a larger maximal non-redundant (independent) protein set which is closer to the real result (the maximum independent set of a graph) that means all the protein families are clustered. This makes Fast- Cluster a valuable tool for removing redundant protein sequences.

A graph theory model using human nature structure

A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure( HNS) embodies the most basic movement characteristics of the body. The human body can be divided into basic units like head,torso,and limbs. Using these basic units,a graph theory model for the HNS can be constructed. GMH provides a basic model for human posture processing,and the outline in the perspective projection plane is the body contour of an image. In addition,the GMH can be applied to articulated motion and deformable objects,e. g.,in the design and analysis of body posture,by modifying mapping parameters of the GMH.