A CBIR system based on saliency driven local image features and multi orientation texture features

In Content-based Image Retrieval (CBIR), the user provides the query image in which only a selective portion of the image carries the foremost vital information known as the object region of the image. However, the human visual system also focuses on a particular salient region of an image to instinctively understand its semantic meaning. Therefore, the human visual attention technique can be well imposed in the CBIR scheme. Inspired by these facts, we initially utilized the signature saliency map-based approach to decompose the image into its respective main object region (ObR) and non-object region (NObR). ObR possesses most of the vital image information, so block-level normalized singular value decomposition (SVD) has been used to extract salient features of the ObR. In most natural images, NObR plays a significant role in understanding the actual semantic meaning of the image. Accordingly, multi-directional texture features have been extracted from NObR using Gabor filter on different wavelengths. Since the importance of ObR and NObR features are not equal, a new homogeneity-based similarity matching approach has been devised to enhance retrieval accuracy. Finally, we have demonstrated retrieval performances using both the combined and distinct ObR and NObR features on seven standard coral, texture, object, and heterogeneous datasets. The experimental outcomes show that the proposed CBIR system has a promising retrieval efficiency and outperforms various existing systems substantially.     

A mathematical model for vehicle routing problem under endogenous uncertainty

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.     

ACO–EEOLSR: enhanced energy model based link stability routing protocol in mobile ad hoc networks

A mobile ad hoc network (MANET) has abundant mobile nodes that are free to communicate independently in many locations. Many existing energy models address the inadequacy of resources based on Ad hoc On-demand Multipath Distance Vector and Optimized Link State Protocol (OLSP) routing protocols for MANET along with various parameters. The architecture of energy-efficient routing mechanisms is a challenging problem in a MANET. In this work, a novel energy-aware routing model is introduced for MANET comprising an ant colony optimization (ACO) enhanced approach to energy-efficient-optimized link state routing (named ACO–EEOLSR). Initially, the route discovery is progressed by means of neighbor estimation and also with the authentication of link stability. Parameters such as energy, distance, and hop count are employed as willingness nodes, where both the energy and distance are entrenched through the OLSP. Consequently, the hop count is applied via the ACO system that is beneficial for link stability. After the acceptance of an acknowledgement, the hop count is authorized for further performance analysis. This approach increases the Quality of Service and also uses less energy compared to other energy models. The accomplished simulation upshot depicts that the ACO–EEOLSR outperforms the EEOLSR scheme with respect to the performance metrics of energy consumption, packet delivery ratio, total remaining time, average network lifetime, and a variance of energy.     

DHT系统的安全性优化方法研究

对分布式哈希表(DHT)系统的安全脆弱性问题进行了研究,提出了多种安全性优化策略,并给出了一个原型系统。进行了真实网络实验,实验数据表明,现有DHT网络易受索引毒害和路由污染攻击,产生的错误查询结果甚至会引发更大规模的网络安全事件。通过改进一个个DHT系统的节点ID生成机制、路由表更新机制和搜索路径选择机制,从系统运行的各个阶段提升其安全场,抵御攻击者共谋。基于上述方法设计的原型系统在保证平均查询跳数增加不到1跳的情况下,在共谋攻击节点占比60%的网络中,将系统查询成功率保持在65%以上,其方法适用于各种分布式哈希表结构,具有重要的实际应用前景。     

矿井采空区无线传感器网络路由协议研究

研究和设计了一种适用于煤矿采空区的无线传感器网络路由机制。首先对LEACH协议的簇头选举机制进行了改进,在计算阀值时添加剩余能量参数,然后采用改进后的协议和多径路由机制设计了煤矿采空区无线传感器网络路由算法,最后通过NS-2仿真平台进行了实验。实验结果表明,改进后的协议与原协议相比,提高了网络中节点的能量有效性,延长了网络的生命周期。     

“主导·主体”教学模式在配置路由选择协议实验中的应用

针对多数计算机网络实验课以学生为中心的实际情况,在分析其缺点的基础上,文章提出将"主导.主体"教学模式应用于计算机网络原理实验课中,并以配置路由选择协议为实验案例,探讨"主导.主体"教学模式在其中的应用,为该教学模式在计算机网络其他实验中的应用提供借鉴意义。     

求解最小MPR集的蚁群算法与仿真

在分析利用贪心策略启发式算法求解最小MPR集的缺陷基础上,引入蚁群算法对最小MPR集进行求解.首先定义了节点及其出度和入度,并根据节点的出度和入度限制,给出了求解最小MPR集的蚁群算法.然后,对蚁群算法的3种模型Ant-Cycle、Ant-Quantity和Ant-Density加以改进,并对这3种改进模型的收敛性进行分析与实验.实验采用了圆形分布和理想均匀分布2种拓扑结构,前者实验结果表明Ant-Cycle模型的收敛速度较快,后者结果表明Ant-Cycle模型和Ant-Density模型各有优势.因此,最小MPR集的蚁群算法的模型选择需依据拓扑结构确定.最后,使用OPNET基于该算法对数据链的点对多点的点名呼叫工作方式进行模拟仿真,选择的统计量显示了节点的连通性和数据一致性,验证了该算法的合理性.     

有类路由汇总的学习和探讨

随着计算机网络技术普及和发展,计算机网络已经基本普及到各行各业,我们越来越多人在刻苦钻也计算机网络技术,我就计算机网络技术中有类路由汇总进行探讨和研究,通过有类路由与无类别域间路由的区别以及有类路由在网络设备技术中路由发布情况的研究和探讨得出总结性结论。