Cluster Leader Research Articles

Ensemble Neural Network in Classifying Handwritten Arabic Numerals

A method has been proposed to classify handwritten Arabic numerals in its compressed form using partitioning approach, Leader algorithm and Neural network. Handwritten numerals are represented in a matrix form. Compressing the matrix representation by merging adjacent pair of rows using logical OR operation reduces its size in half. Considering each row as a partitioned portion, clusters are formed for same partition of same digit separately. Leaders of clusters of partitions are used to recognize the patterns by Divide and Conquer approach using proposed ensemble neural network. Experimental results show that the proposed method recognize the patterns accurately.

Intrusion detection in Mobile Ad-hoc Networks: Bayesian game formulation

Present Intrusion Detection Systems (IDSs) for MANETs require continuous monitoring which leads to rapid depletion of a node's battery life. To address this issue, we propose a new IDS scheme comprising a novel cluster leader election process and a hybrid IDS. The cluster leader election process uses the Vickrey–Clarke–Groves mechanism to elect the cluster leader which provides the intrusion detection service. The hybrid IDS comprises a threshold based lightweight module and a powerful anomaly based heavyweight module. Initially, only the lightweight module is activated. The decision to activate the heavyweight module is taken by modeling the intrusion detection process as an incomplete information non-cooperative game between the elected leader node and the potential malicious node. Simulation results show that the proposed scheme significantly reduces the IDS traffic and overall power consumption in addition to maintaining a high detection rate and accuracy.

An Optimized Multicast Backbone Routing for Increasing Residual Energy in MANET

Background/Objectives: Due to the presence of mobility, the nodes may move out of the coverage region. Mobility of nodes causes network partition. This will lead to heavy overhead and less packet forwarding ratio. Methods/Statistical Analysis: In this research work, Residual Energy based Reliable Multicast Routing (RERMR) is proposed to increase the packet forwarding rate based on optimized multicast backbone construction. It consists of following phases. In first phase, the multicast backbone is constructed based on trustable loop and trust factors. The backbone is maintained by means of cluster group members. If the cluster head is not responding to cluster members or other cluster head, the secondary cluster leader checks whether it attains the latency threshold and announces that as a cluster head. Reliable path is calculated based on stability of links and residual energy is saved based on signal strength and distance. Results: For simulation, the network simulator tool (NS 2.34) is used. The QoS parameters and the proposed parameters are taken for analysis for performance of existing and proposed work. Based on the simulation results, the proposed work achieves better performance than previous protocols in terms of path reliability rate, network stability rate, end to end delay, end to end transmission and communication overhead.

Biological responses to nanoscale particles.

Biological responses to nanoscale particles.

Analysis of Elementary Cellular Automata Chaotic Rules Behavior

We present detailed and in depth analysis of Elementary Cellular Automata (ECA) with periodic cylindrical configuration. The focus is to determine whether Cellular Automata (CA) is suitable for the generation of pseudo random number sequences (PRNs) of cryptographic strength. Additionally, we identify the rules that are most suitable for such applications. It is found that only two sub-clusters of the chaotic rule space are actually capable of producing viable PRNs. Furthermore, these two sub-clusters consist of two majorly non-linear rules. Each sub-cluster of rules is derived from a cluster leader rule by reflection or negation or the combined two transformations. It is shown that the members of each subcluster share the same dynamical behavior. Results of testing the ECA running under these rules for comprehensively large number of lattice lengths using the Diehard Test suite have shown that apart from some anomaly, the whole output sequence can be potentially utilized for cryptographic strength pseudo random sequence generation with sufficiently large number of p-values pass rates.

LEADERSHIP PERCEPTIONS IN COLLABORATIVE MARKETING GROUPS: CASES FROM THE SOUTHERN PHILIPPINES

Numerous smallholder vegetable farmers in the Southern Philippines have been organized into clusters or collaborative marketing groups. The purpose of these clusters is to gain production, marketing and capacity building support, consolidate produce for higher value markets, deliver in bulk to save on transport and transaction costs, and to increase household income. One of the factors influencing the ability of the clusters to achieve these goals is leadership. Using the case study method, this study looks at the leadership traits of cluster leaders in Bukidnon, South Cotabato and Davao City. A total of 35 smallholder farmers from the three areas were interviewed using a structured questionnaire. The research showed that the clusters have trusted leaders. The members have high regard towards their leaders. Their definition of an ideal leader fits the description of their current leaders. The members also trust their leaders to represent them in transactions and meetings.

New York City's Children First Networks: turning accountability on its head

PurposeThe purpose of this paper is to report findings from an exploratory study of New York's Children First Networks (CFNs); to examine what is known about the CFNs thus far, drawing on new empirical research, as well as document review and analysis of secondary sources.Design/methodology/approachOrganizational learning theory guided this qualitative study. As such, in‐depth interviews conducted with central office staff, network leadership teams, cluster leaders, and principals focused on the flow and management of information within the networks; the ways in which stakeholders developed shared meanings; how collective intelligence was built and transmitted; and organizational responses to the early experience of the CFNs.FindingsFindings highlight the tools and processes the NYC Department of Education (DOE) has put into place to operationalize the CFNs. Respondents identified as critical the replacement of supervisory leadership from the district with customization of services provided by the network teams to promote principal‐led reforms. Increased efficiency was noted by interviewees, but a number of challenges in the reform’s implementation also surfaced that point to the limitations of the CFNs as a capacity‐building mechanism.Research limitations/implicationsAs an exploratory study, this research is intended to inform larger‐scale, mixed‐methods investigations of school networks, especially those implementing reforms aimed at improving teaching and learning in schools. Research is needed into the resource exchanges between individuals and groups in networks, what differentiates high‐performing from lower‐performing networks, and how data are used to inform the evolution of network structures and practices.Originality/valueThis study is the first peer‐reviewed article on the evolution of New York City's Children First Networks.

Collaborative target tracking in WSNs using the combination of maximum likelihood estimation and Kalman filtering

Target tracking using wireless sensor networks requires efficient collaboration among sensors to tradeoff between energy consumption and tracking accuracy. This paper presents a collaborative target tracking approach in wireless sensor networks using the combination of maximum likelihood estimation and the Kalman filter. The cluster leader converts the received nonlinear distance measurements into linear observation model and approximates the covariance of the converted measurement noise using maximum likelihood estimation, then applies Kalman filter to recursively update the target state estimate using the converted measurements. Finally, a measure based on the Fisher information matrix of maximum likelihood estimation is used by the leader to select the most informative sensors as a new tracking cluster for further tracking. The advantages of the proposed collaborative tracking approach are demonstrated via simulation results.

A Biologically Inspired Sensor Wakeup Control Method for Wireless Sensor Networks

This paper presents an artificial ant colony approach to distributed sensor wakeup control (SWC) in wireless sensor networks (WSN) to accomplish the joint task of surveillance and target tracking. Each sensor node is modeled as an ant, and the problem of target detection is modeled as the food locating by ants. Once the food is found, the ant will release pheromone. The communication, invalidation, and fusion of target information are modeled as the processes of pheromone diffusion, loss, and accumulation. Since the accumulated pheromone can measure the existence of a target, it is used to determine the probability of ant-searching activity in the next round. To the best of our knowledge, this is the first biologically inspired SWC method in the WSN. Such a biologically inspired method has multiple desirable advantages. First, it is distributive and does not require a centralized control or cluster leaders. Therefore, it is free of the problems caused by leader failures and can save the communication cost for leader selection. Second, it is robust to false alarms because the pheromone is accumulated temporally and spatially and thus is more reliable for wakeup control. Third, the proposed method does not need the knowledge of node position. Two theorems are presented to analytically determine the key parameters in the method: the minimum and maximum pheromone. Simulations are carried out to evaluate the performance of the proposed method in comparison with representative methods.

Lay Leadership in Sparsely Populated Rural Australia: Uniting Churches in South Australia

South Australia is sparsely populated agricultural country. Small towns, many with Uniting Churches, serve the communities. Only a few of these churches have their own ordained minister. Most ministers serve a cluster of three or more churches, often assisted by lay teams which take some services. Many churches are led by teams of lay people. Surveys and case-studies showed that the vitality of the lay-led churches was no different from churches led by ordained ministers. In many lay-led churches there is a strong sense of ownership by the lay people, and those involved in leadership often reported that they had grown in faith through their responsibilities. The preferred pattern of leadership in rural churches adopted by the Synod of the Uniting Church in South Australia is that of local lay leadership. ‘Resourcing ministers’ are being appointed to mentor and resource the lay leaders of clusters of between six and 12 congregations.

Cluster-Based Distributed Face Tracking in Camera Networks

In this paper, we present a distributed multicamera face tracking system suitable for large wired camera networks. Unlike previous multicamera face tracking systems, our system does not require a central server to coordinate the entire tracking effort. Instead, an efficient camera clustering protocol is used to dynamically form groups of cameras for in-network tracking of individual faces. The clustering protocol includes cluster propagation mechanisms that allow the computational load of face tracking to be transferred to different cameras as the target objects move. Furthermore, the dynamic election of cluster leaders provides robustness against system failures. Our experimental results show that our cluster-based distributed face tracker is capable of accurately tracking multiple faces in real-time. The overall performance of the distributed system is comparable to that of a centralized face tracker, while presenting the advantages of scalability and robustness.

Tracking Fast Moving Targets in Wireless Sensor Networks

We propose a dynamic distributed algorithm for tracking objects that move fast in a sensor network. In the earlier efforts in tracking moving targets, the current leader node at time t predicts the location only for time t + 1 and if the target moves in high speed, it can pass by a group of nodes very fast without being detected. Therefore, as the target increases its speed, the probability of missing that target also increases. In this study, we propose a target tracking system that predicts future k locations of the target and awakens the corresponding leader nodes so that the nodes along the trajectory self organize to form the clusters to collect data related to the target in advance and thus reduce the target misses. The algorithm first provides detection of the target and forms a cluster with the neighboring nodes around it. After the selection of the cluster leader, the coordinates of the target is estimated using localization methods and cooperation between the cluster nodes under the control of the leader node. The coordinates and the speed of the target are then used to estimate its trajectory. This information in turn provides the location of the nodes along the estimated trajectory which can be awaken, hence providing tracking of the moving object. We describe the algorithm, analyze its efficiency and show by simulations that it performs well to track very fast moving objects with speeds much higher than reported in literature.

An Efficient Data Aggregation Algorithm for Cluster-based Sensor Network

Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energyefficiency of sensor nodes. One node, called the cluster leader, collects data from surrounding nodes and then sends the summarized information to upstream nodes. In this paper, we propose an algorithm to select a cluster leader that will perform data aggregation in a partially connected sensor network. The algorithm reduces the traffic flow inside the network by adaptively selecting the shortest route for packet routing to the cluster leader. We also describe a simulation framework for functional analysis of WSN applications taking our proposed algorithm as an example.

Design and Evaluation of a Distributed Clustering Algorithm for Mobile ad hoc Networks

This paper proposes a new clustering algorithm for global positioning system (GPS)-based mobile ad hoc networks that takes into consideration the direction of the overall traffic flow in the network. The proposed cluster leader logic algorithm is motivated by the GPS quorum hybrid routing algorithm, where clusterheads are positioned on the terrain upon a conceptual cellular grid. The proposed distributed clustering algorithm chooses the clusterheads based on the traffic flow patterns, i.e. the nodes best suited to forward and route network traffic are selected. Our approach allows a clusterhead which is overwhelmed with sending packets to identify an additional clusterhead from nodes available in its cell to share its load. Likewise, clusterheads with low load will try to relinquish their role as a clusterhead. We propose a new concept called cell fanning that allows collocated clusterheads in one cell to share routing responsibilities by declaring which cells they are responsible for routing packets to. We conducted extensive simulation experiments with enforced directional traffic patterns. Two important results are presented: power consumption per clusterhead and average queuing delay for each clusterhead. Results in terms of message overheads, number of clusterheads, power consumption, and queuing delay reveal that system performance is enhanced when clusterheads are chosen considering the direction of the traffic flow.

Application driven cluster based group key management with identifier in wireless sensor networks

This paper proposes and analyzes a scalable and an efficient cluster based group key management protocol by introducing identity based infrastructure for secure communication in mobile wireless sensor networks. To ensure scalability and dynamic re-configurability, the system employs a cluster based approach by which group members are separated into clusters and the leaders of clusters securely communicate with each other to agree on a group key in response to changes in membership and member movements. Through analysis we have demonstrated that our protocol has a high probability of being resilient for secure communication among mobile nodes. Finally, it is established that the proposed scheme is efficient for secure positioning in wireless sensor networks.

MANET Routing with Provably Low Complexity Through Constant Density Clustering and Route Request Broadcast

As mobile ad hoc networks (MANETs) are emerging as important components in critical and large-scale applications, it is crucial to develop MANET routing mechanisms with provably low complexity. In this paper, we give a tutorial overview of the efficient use of elementary node clustering and route request broadcast mechanisms for low-complexity MANET routing. We explain these mechanisms with illustrative examples and discuss their theoretical performance characteristics. We demonstrate that node clustering with constant density and route request broadcasting with a doubling radius technique over the network of cluster leaders can be employed for MANET routing with theoretically proven low complexity. Moreover, we contrast these efficient elementary clustering and route request broadcast mechanisms with clustering and route information accumulation mechanisms in the widely studied AODV and DSR routing protocols and discuss the implications of these various mechanisms for scalable MANET routing.

Application of chemometric tools for automatic classification and profile extraction of DNA samples in forensic tasks

In this paper a method for the automatic DNA spots classification and extraction of profiles associated in DNA polyacrilamide gel electrophoresis is presented and it integrates the use of image processing techniques and chemometrics tools. A software which implements this method was developed; for feature extraction a combination of a PCA analysis and a C4.5 decision tree were used. To obtain good results in the profile extraction only DNA spots are useful; therefore, it was necessary to solve a two-class classification problem among DNA spots and no-DNA spots. In order to perform the classification process with high velocity, effectiveness and robustness, comparative classification studies among support vector machine (SVM), K-NN and PLS-DA classifiers were made. The best results obtained with the SVM classifier demonstrated the advantages attributed to it in the literature as a two-class classifier. A Sequential Cluster Leader Algorithm and another one developed for the restoration of pattern missing spots were needed to conclude the profiles extraction step. The experimental results show that this method has a very effective computational behavior and effectiveness, and provide a very useful tool to decrease the time and increase the quality of the specialist responses.

The psi-cube: a bus-based cube-type clustering network for high-performance on-chip systems

This paper proposes a bus-based cube-type network, called psi-cube, that alleviates the two problems, long wires and a limited number of I/O pins, against the on-chip systems through a small diameter and dynamic clusters, respectively. The 2 n -node psi-cube is organized on the sets of node-partitions produced with an extended n-bit Hamming code ψ( n, k) [M. Takesue, Ψ-Cubes: recursive bused fat-hypercubes for multilevel snoopy caches, in: Proceedings of the International Symposium on Parallel Architectures, Algorithms, and Networks, IEEE CS Press, 1999, pp. 62–67] if we connect the nodes in each partition to the bus owned by the leader of the partition. Owing to the routing between the leaders separated by the distance of 1–3, the diameter equals ⌊ n/2⌋ if n≠2 p − 1 or ⌈ n/2⌉ otherwise. The maximum bus length is O(2 p−1 ) or O(2 k−1 ) when the psi-cube is mapped onto an array. We dynamically produce separate sets of clusters for different off-chip targets such as memory blocks, so the traffic to the leaders of clusters is much smaller than in static clusters fixed in hardware. From simulation results, the psi-cube outperforms over the mesh if the bus delay is less than 4 times the mesh link’s, and the dynamic clusters increase the psi-cube bandwidth by over 60%.

Cluster overlay broadcast (COB): MANET routing with complexity polynomial in source-destination distance

Routing algorithms with time and message complexities that are provably low and independent of the total number of nodes in the network are essential for the design and operation of very large scale wireless mobile ad hoc networks (MANETs). In this paper, we develop and analyze Cluster Overlay Broadcast (COB), a low-complexity routing algorithm for MANETs. COB runs on top of a one-hop cluster cover of the network, which can be created and maintained using, for instance, the Least Cluster Change (LCC) algorithm. We formally prove that the LCC algorithm maintains a cluster cover with a constant density of cluster leaders with minimal update cost. COB discovers routes by flooding (broadcasting) route requests through the network of cluster leaders with a doubling radius technique. Building on the constant density property of the network of cluster leaders, we formally prove that, if there exists a route from a source to a destination node with a minimum hop count of A, then COB discovers a route with at most O(/spl Delta/) hops from the source to the destination node in at most O(/spl Delta/) time and by sending at Most O(/spl Delta//sup 2/) messages. We prove this result for arbitrary node distributions and mobility patterns and also show that COB adapts asymptotically optimally to the mobility of the nodes. In our simulation experiments, we examine the network layer performance of COB, compare it with Dynamic Source Routing, and investigate the impact of the MAC layer on COB routing.

Should structural interventions be evaluated using RCTs? The case of HIV prevention

Structural interventions addressing macro-social determinants of risk have been suggested as potentially important adjuncts to biomedical and behavioural interventions for the prevention of HIV and other diseases. A few interventions of this type have been evaluated using randomised controlled trials (RCTs), the most rigorous design to evaluate the effects of biomedical and behavioural interventions. The appropriateness of applying RCTs to structural interventions is however debated. This paper considers whether issues of ethics, feasibility and utility preclude the use of RCTs in evaluations of structural interventions for HIV prevention. We conclude there is nothing particular to this category of interventions prohibiting use of RCTs. However, we suggest that RCTs may prove unacceptable, unfeasible or not useful in certain circumstances, such as where an intervention brings important benefits other than HIV prevention (such as increased income); where leaders of clusters do not allow decisions about macro-social policies to be determined randomly; where the unit of social organization addressed by an intervention is so large that recruitment of adequate numbers of clusters is impossible; and where the period required to trial interventions extends beyond practical decision-making time-scales. In such cases, alternative evaluative designs must be assessed for their ability to provide evidence of intervention effectiveness.