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  • International Journal Advanced Network Monitoring Controls

 

Article

An Efficient Density-Based Clustering Algorithm for the Capacitated Vehicle Routing Problem

The capacitated vehicle routing problem (CVRP) is one of the most challenging problems in the optimization of distribution. Most approaches can solve case studies involving less than 100 nodes to optimality, but time-consuming. To overcome the limitation, this paper presents a novel two-phase heuristic approach for the capacitated vehicle routing problem. Phase I aims to identifying sets of cost-effective feasible clusters through an improved density-based clustering algorithm. Phase II assigns

Jiashan Zhang

International Journal of Advanced Network, Monitoring and Controls , ISSUE 4, 161–165

Article

Research on Balanced Energy Consumption of Wireless Sensor Network Nodes Based on Clustering Algorithm

Jie Huang

International Journal of Advanced Network, Monitoring and Controls , ISSUE 4, 15–19

Research paper

POSTERIOR BELIEF CLUSTERING ALGORITHM FOR ENERGY-EFFICIENT TRACKING IN WIRELESS SENSOR NETWORKS

Bo Wu, Yanpeng Feng, Hongyan Zheng

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 628–641

Article

A NEW UNEQUAL CLUSTERING ALGORITHM USING ENERGY-BALANCED AREA PARTITIONING FOR WIRELESS SENSOR NETWORKS

this paper, we propose a new unequal clustering algorithm based on the partitioned circles network model, having better accuracy in the energy consumption analysis than the rectangular one. The superiority of the algorithm we propose is cluster parameters, by which the region width and cluster-head probability, are obtained with a complete energy consumption analysis. Through the simulation evaluation, the algorithm brings the better performance than the equal clustering.

Amin Suharjono, Wirawan, Gamantyo Hendrantoro

International Journal on Smart Sensing and Intelligent Systems , ISSUE 5, 1808–1829

Article

Detection of Blink State Based on Fatigued Driving

or inaccurate positioning[7]. Therefore, this paper chooses Dlib open source library to detect human eye features. Firstly, the 68 face feature points provided by the Dlib open source library are used to accurately calibrate the position of the face and the human eye, and then the aspect ratio between the length and the width of the human eye is measured. Finally, the Kmeans clustering algorithm is used to analyze the collected ratio. The threshold of blinking. Figure 1 below, a is the 68 face

Lei Chao, Wang Changyuan, Li Guang, Shi Lu

International Journal of Advanced Network, Monitoring and Controls , ISSUE 4, 24–29

Research Article

AN ARTIFICIAL IMMUNE NETWORK CLUSTERING ALGORITHM FOR MANGROVES REMOTE SENSING IMAGE

Yanmin LUO, Peizhong LIU, Minghong LIAO

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 116–134

Article

FACE RECOGNITION BASED ON IMPROVED SUPPORT VECTOR CLUSTERING

Traditional methods for face recognition do not scale well with the number of training sample, which limits the wide applications of related techniques. We propose an improved Support Vector Clustering algorithm to handle the large-scale biometric feature data effectively. We prove theoretically that the proposed algorithm converges to the optimum within any given precision quickly. Compared to related state-of-the-art Support Vector Clustering algorithms, it has the competitive performances on

Yongqing Wang, Xiling Liu

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1807–1829

Article

COMPUTER VISION-BASED COLOR IMAGE SEGMENTATION WITH IMPROVED KERNEL CLUSTERING

Color image segmentation has been widely applied to diverse fields in the past decades for containing more information than gray ones, whose essence is a process of clustering according to the color of pixels. However, traditional clustering methods do not scale well with the number of data, which limits the ability of handling massive data effectively. We developed an improved kernel clustering algorithm for computing the different clusters of given color images in kernel-induced space for

Yongqing Wang, Chunxiang Wang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1706–1729

Research Article

CFM: A FITNESS-MODEL-BASED TOPOLOGY CONTROL ALGORITHM FOR WIRELESS SENSOR NETWORKS

topology can be achieved by fitness model, so we designed an approximate clustering algorithm based on fitness model, which is distributed. CFM is composed of three phases: links generation phase, heads selection phase and cluster division phase. The performance of CFM algorithm was analyzed through simulation experiments, which indicated a well-constructed topology and effectively prolonged network lifetime.

Linfeng Liu, Jiagao Wu, Fu Xiao, Ruchuan Wang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 58–76

Article

SPECTRAL CLUSTERING WITH SPATIAL COHERENCE PROPERTY JOINTING TO ACTIVE CONTOUR MODEL FOR IMAGE LOCAL SE GMENTATION

spectral clustering algorithm is used to extract initial contour of the local region of an image. Then, the NBACM (narrow band active contour model) is combined with the priori information of initial contour to evolve contour curve to get the segmentation result. At last, the local segmentation experiment is realized on synthetic images and medical images. The experimental results show that the method proposed can extract contour accurately and can improve the effectiveness and robust for image local

Guang Hu, Shengzhi Yuan

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1731–1749

Article

Design and Implementation of Music Recommendation System Based on Hadoop

, database and ETL operation, which can calculate a set of complete recommendation system from user operation end to server and data calculation. In order to improve the accuracy of the recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation algorithm based on user-based collaborative filtering.The experimental results show that the accuracy of the proposed algorithm has been significantly improved after the introduction of k-means.

Zhao Yufeng, Li Xinwei

International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 126–132

Article

Improved Faster R-CNN Algorithm for Sea Object Detection Under Complex Sea Conditions

detection accuracy of the above method is not high. In this paper, the Faster R-CNN[11-13] object detection algorithm is improved. The K-Means clustering algorithm[14] is introduced to perform cluster analysis on the size of the object in the image, and the clustering results are directly input into the area recommendation network to achieve the improvement of the area recommendation network. Using Soft -The NMS algorithm replaces the NMS algorithm to reduce the miss detection probability of small

Liu Yabin, Yu Jun, Hu Zhiyi

International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 76–82

Research Article

COOPERATIVE MULTI TARGET TRACKING USING MULTI SENSOR NETWORK

tracking system using multiple mobile sensors. For the purposes of surveillance and security, trackers use an Extended Kohonen neural network to track the moving targets in their environments. The proposed tracking algorithm can be used for single and multiple target tracking. A clustering algorithm is used in order to minimize the number of active trackers over time and hence save energy. An auction based algorithm is used for the purpose of optimizing the cooperation between trackers. Quantitative

Ahmed M. Elmogy, Fakhreddine O. Karray

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 716–734

Article

UNSUPERVISED GROUPING OF MOVING OBJECTS BASED ON AGGLOMERATIVE HIERARCHICAL CLUSTERING

In this article, we present a method to identify a grouping of sensor nodes that show similar movement patterns in an ad-hoc manner. The motivation behind the ad-hoc grouping is to allow a system to monitor complex and concrete situations of people and/or devices such as “who is/are utilizing what object(s)” and “what objects are carried together” without any supervision of human before and at the time of interaction. An agglomerative hierarchical clustering algorithm was applied to a data

Kaori Fujinami

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 2276–2296

Article

SEFP: A NEW ROUTING APPROACH USING FUZZY LOGIC FOR CLUSTERED HETEROGENEOUS WIRELESS SENSOR NETWORKS

Wireless sensor networks (WSNs) are composed of set sensor nodes communicating through wireless channels with limited resources. Therefore, several routing protocols and approaches about energy efficient operation of WSNs have been proposed. Clustering algorithm based routing protocols are well used for efficient management of sensing sensor node energy resources. However, many researches were focused on optimization of well-known hierarchical routing approaches of WSNs using fuzzy logic system

hassan EL ALAMI, Abdellah NAJID

International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 2286–2306

Article

A Disparateness-Aware Scheduling using K-Centroids Clustering and PSO Techniques in Hadoop Cluster

cluster environment. In this research work we represent K-centroids clustering in big data mechanism for Hadoop cluster. This approach is mainly focused on the energy consumption in The Hadoop cluster, which helps to increase the system reliability. The Hadoop cluster consists of resources which are categorized for minimizing the scheduling delay in the Hadoop cluster using the K-Centroids clustering algorithm. A novel provisioning mechanism is introduced along with the consideration of load, energy

E. Laxmi Lydia, M.Ben Swarup

International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 34–46

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