Search results for: cluster head

Authors: Manverpreet Kaur, Amarpreet Singh

Abstract:

The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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Authors: Naim Karasekreter, Ugur Fidan, Fatih Basciftci

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Wireless sensor networks are networks in which more than one sensor node is organized among themselves. The working principle is based on the transfer of the sensed data over the other nodes in the network to the central station. Wireless sensor networks concentrate on routing algorithms, energy efficiency and clustering algorithms. In the clustering method, the nodes in the network are divided into clusters using different parameters and the most suitable cluster head is selected from among them. The data to be sent to the center is sent per cluster, and the cluster head is transmitted to the center. With this method, the network traffic is reduced and the energy efficiency of the nodes is increased. In this study, clustering algorithms were examined in terms of clustering performances and cluster head selection characteristics to try to identify weak and strong sides. This work is supported by the Project 17.Kariyer.123 of Afyon Kocatepe University BAP Commission.

Keywords: wireless sensor networks (WSN), clustering algorithm, cluster head, clustering

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: K. Gomathi

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Mobile Ad hoc Networks (MANET) is defined as collection of routable wireless mobile nodes with no centralized administration and communicate each other using radio signals. Especially MANETs deployed in hostile environments where hackers will try to disturb the secure data transfer and drain the valuable network resources. Since MANET is battery operated network, preserving the network resource is essential one. For resource constrained computation, efficient routing and to increase the network stability, the network is divided into smaller groups called clusters. The clustering architecture consists of Cluster Head(CH), ordinary node and gateway. The CH is responsible for inter and intra cluster routing. CH election is a prominent research area and many more algorithms are developed using many different metrics. The CH with longer life sustains network lifetime, for this purpose Secondary Cluster Head(SCH) also elected and it is more economical. To nominate efficient CH, a Enhanced Distributed Weighted Clustering Algorithm (EDWCA) has been proposed. This approach considers metrics like battery power, degree difference and speed of the node for CH election. The proficiency of proposed one is evaluated and compared with existing algorithm using Network Simulator(NS-2).

Keywords: MANET, EDWCA, clustering, cluster head

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

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An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

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Authors: Ana Marie T. Acevedo

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This study was conducted to describe variations in the shapes of the elytra, head and pronotum of populations of adult Brontispa longissima (Gestro) infesting coconut farms from selected areas in the Philippines using Cluster Analysis, Relative Warp Analysis coupled with box plot and histograms and Procustean analysis. The data used in this study included shape residuals captured using the method of landmark based geometric morphometrics. Results: The results of the cluster analyses based on the average shapes of the elytra, head and pronotum shows no consistent pattern of similarity between and among five populations of B. longissima. When localized variations using Relative Warp Analysis coupled with box plot and histograms was done, the findings revealed that RWA was only successful in summarizing variations using two relative warps in the shape of the elytra where the first two warps contained 86.29% of the variations of the female and 85.48% for the males. For the head and pronotum, the first two relative warps captured less than 50% of the overall variation. Looking at the shapes of the frequency histograms, all were found to follow a unimodal distribution. The box plots reveal no consistent results. Among the three characters studied only the elytra were more robust and reliable compared to head and pronotum and then Tandag differ from the rest of the other over-lapping populations. On the other hand, Procustean Analyses revealed that elytra were more spread in the posterior region both in male and female. The coordinates in head and pronotum were evenly distributed. In the overlapping consensus configurations show that variability was exaggerated in the right side of the elytra and the posterior parts of the head and pronotum. Results also showed expansion among females while compression among males in elytra. For males, expansion are localized in the posterior part of the elytra, For the head, results showed asymmetry in the distribution of expansion areas where expansion are observed in the right postero-lateral aspect of the female head. Conclusion: The overall results may imply that they might belong to one operational taxonomic unit or ecotype or biotype. Geography might not be the factor responsible for the differentiation of the populations of B. longissima.

Keywords: cluster analysis, relative warp analysis, procrustean analysis, environmental parameters

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Authors: Ameen Jameel Alawneh

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A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.

Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets

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Authors: Mehdi Nematimoez

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Head posture is paramount to retaining gaze and balance in many activities; its control is thus important in many activities. However, little information is available about the effects of head movement restriction on other spine segment kinematics and movement patterns during lifting and lowering tasks. The aim of this study was to examine the effects of head movement restriction on relative angles and their derivatives using the stepwise segmentation approach during lifting and lowering tasks. Ten healthy men lifted and lowered a box using two styles (stoop and squat), with two loads (i.e., 10 and 20% of body weight); they performed these tasks with two instructed head postures (1. Flexing the neck to keep contact between chin and chest over the task cycle; 2. No instruction, free head posture). The spine was divided into five segments, tracked by six cluster markers (C7, T3, T6, T9, T12, and L5). Relative angles between spine segments and their derivatives (first and second) were analyzed by a stepwise segmentation approach to consider the effect of each segment on the whole spine. Accordingly, head posture significantly affected the derivatives of the relative angles and manifested latency in spine segments movement, i.e., cephalad-to-caudad or caudad-to-cephalad patterns. The relative angles for C7-T3 and T3-T6 increased over the cycle of all lifting and lowering tasks; nevertheless, in lower segments increased significantly when the spine moved into upright standing. However, these effects were clearer during lifting than lowering. Conclusively, the neck flexion can unevenly increase the flexion angles of spine segments from cervical to lumbar over lifting and lowering tasks; furthermore, stepwise segmentation reveals potential for assessing the segmental contribution in spine ROM and movement patterns.

Keywords: head movement restriction, spine kinematics, lifting, lowering, stepwise segmentation

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

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In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks（EBCAM）based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

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Authors: B. S. Bamoallem, A. J. Wodehouse, G. M. Mair

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Communication takes place not only through speech, but also by means of gestures such as facial expressions, gaze, head movements, hand movements and body posture, and though there has been rapid development, communication platforms still lack this type of behavior. We believe communication platforms need to fully achieve this verbal and non-verbal behavior in order to make interactions more engaging and more efficient. In this study we decided to focus our research on the head rather than any other body part as it is a rich source of information for speech-related movement Thus we aim to investigate the value of incorporating head movements into the use of telepresence robots as communication platforms; this will be done by investigating a system that reproduces head movement manually as closely as possible.

Keywords: engagement, nonverbal behaviours, head movements, face-to-face interaction, telepresence robot

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Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan

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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.

Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Pragya Bhawsar, Utpal Chattopadhyay

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Small and Medium Enterprises play crucial role in contributing to economic objectives of an emerging nation. To support SMEs, the idea of creation of clusters has been prevalent since past two decades. In this paper, an attempt has been done to explore the impact of being in the cluster on the competitiveness of SMEs. To meet the objective, Nasik Cluster (India) has been selected. The information was collected by means of two focus group discussions and survey of thirty SMEs. The finding generates interest revealing the fact that under the concept ‘Cluster’ a lot of ambiguity flourish. Besides the problems and opportunities of the firms in the cluster the results bring to notice that the benefits of clusterization can only reach to SMEs when the whole location can be considered/understood as a cluster, rather than many subsets (various forms of clusters) prevailing under it. Fostering such an understanding calls for harmony among the various stakeholders of the clusters. The dynamics of interaction among government, local industry associations, relevant institutions, large firms and finally SMEs which makes the most of the location based cluster, are significant in shaping the host cluster’s competitiveness and vice versa.

Keywords: SMEs, industry clusters, common facility centres, co-creation, policy

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Authors: Dongchuan Su, Hai Xie, Naibin Jiang

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Under severe accident cases, the nuclear reactor core may meltdown inside the lower head of the reactor pressure vessel (RPV). Retaining the melt pool inside the RPV is an important strategy of severe accident management. During this process, the inner wall of the lower head will be heated to high temperature of a thousand centigrade, and the outer wall is immersed in a large amount of cooling water. The material of the lower head will have serious creep damage under the high temperature and the temperature difference, and this produces a great threat to the integrity of the RPV. In this paper, the ANSYS program is employed to build the finite element method (FEM) model of the lower head, the creep phenomena is simulated under the severe accident case, the time dependent strain and stress distribution is obtained, the creep damage of the lower head is investigated, the integrity of the RPV is evaluated and the theoretical basis is provided for the optimized design and safety assessment of the RPV.

Keywords: severe accident, lower head of RPV, creep, FEM

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Authors: Mohammad Reza Shojaei, Mahdeih Mirzaeinia

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We have studied the cluster structure of even-even stable isotopes of Ge and Sr. The Schrodinger equation has been solved using the generalized parametric Nikiforov-Uvarov method with a phenomenological potential. This potential is the sum of the attractive Yukawa-like potential, a Manning-Rosen-type potential, and the repulsive Yukawa potential for interaction between the cluster and the core. We have shown that the available experimental data of the first rotational band energies can be well described by assuming a binary system of the α cluster and the core and using an analytical solution. Our results were consistent with experimental values. Hence, this model can be applied to study the other even-even isotopes

Keywords: cluser model, NU method, ge and Sr, potential central

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Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Ravi Nandu, Anmol Taploo

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As per current scenario, commercial aircrafts have been very well functioning with higher efficiency, but there is something that affects it. Every aircraft runs with the combustion produced by mixture of fuel and air. For example: A flight to travel from Mumbai to Kolkata it takes 2h: 30 min and from Kolkata to Mumbai it takes 2h: 45 min. It happens due to head and tail wind. Due to head wind air craft travels faster than its usual velocity and it takes 2h: 30 min to reach to Kolkata, while it takes 2h;45min vis versa. This lag in time is caused due to head wind that increases the drag and reduces the relative velocity of the plane. So in order to reduce this wastage of fuel there is an optimal flight altitude at which the head and tail wind action is reduced compared to the present scenario.

Keywords: drag, head wind, tail wind, aircraft

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Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Nyimas Annissa Mutiara Andini

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Every year, children develop hydrocephalus during the first year of life. If it is not treated, hydrocephalus can lead to brain damage, a loss in mental and physical abilities, and even death. To be treated, first, we have to do a proper diagnosis using some examinations especially to detect hydrocephalus earlier. One of the examination that could be done is using a head circumference measurement. Increased head circumference is a first and main sign of hydrocephalus, especially in infant (0-1 year age). Head circumference is a measurement of a child's head largest area. In this measurement, we want to get the distance from above the eyebrows and ears and around the back of the head using a measurement tape. If the head circumference of an infant is larger than normal, this infant might potentially suffer hydrocephalus. If early diagnosis and timely treatment of hydrocephalus could be done most children can recover successfully. There are some problems with early detection of hydrocephalus using regular tape for head circumference measurement. One of the problem is the infant’s comfort. We need to make the infant feel comfort along the head circumference measurement to get a proper result of the examination. For that, we can use a helpful stuff, like a hat. This paper is aimed to describe the possibility of using a head circumference measuring instrument for early detection of hydrocephalus in an infant with a mike hat, coloured-tape-in-hat. In the first life, infants’ head size is about 35 centimeters. First three months after that infants will gain 2 centimeters each month. The second three months, infant’s head circumference will increase 1 cm each month. And for the six months later, the rate is 0.5 cm per month, and end up with an average of 47 centimeters. This formula is compared to the WHO’s head circumference growth chart. The shape of this tape-in-hat is alike an upper arm measurement. This tape-in-hat diameter is about 47 centimeters. It contains twelve different colours range by age. If it is out of the normal colour, the infant potentially suffers hydrocephalus. This examination should be done monthly. If in two times of measurement there still in the same range abnormal of head circumference, or a rapid growth of the head circumference size, the infant should be referred to a pediatrician. There are the pink hat for girls and blue hat for boys. Based on this paper, we know that this measurement can be used to help early detection of hydrocephalus in an infant.

Keywords: head circumference, hydrocephalus, infant, mike hat

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Authors: Surjit Angra, Manisha Kumari, Vinod Kumar

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The objective of the Hydro Turbine Head Cover is to support the guide bearing, guide vane regulating mechanism and even in some design for generator thrust bearing support. Mechanical design of head cover deals with high static as well as fluctuating load acting on the structure. In the present work structural analysis of hydro turbine Head-cover using ANSYS software is carried out. Finite element method is used to calculate stresses on head cover. These calculations were done for the maximum possible loading under operating condition “LCI Quick Shut Down”. The results for equivalent Von-Mises stress, total deformation and directional deformation have been plotted and compared with the existing results whether the design is safe or not.

Keywords: ANSYS, head cover, hydro-turbine, structural analysis, total deformation, Von-Mises stress

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Authors: Rania Mustafa, Anfal Gadour

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Specialty area: Manchester University NHS Foundation Trust, Wythenshawe Hospital Accident and Emergency Department. About, Documentation of verbal and written head injury advice given to all adults presenting following a head injury. Our aim was to assess verbal & written head injury advice for an adult patient attending ED in Wythenshawe hospital during the period from January 2022 to May 2022, with a view to evaluating the NICE head injury guidelines concerning discharge advice and also to review the clinical notes to ensure that all adult patients presenting with a head injury are documented to have received both verbal & written head injury advice as per the NICE guidelines. Here we collected data from a random sample over a 1 month period. This data was furtherly filtered to include the adult patient >16 years and resulted in 54 patients with head injuries attending ED during this time period; then patient’s age, sex and hospital number were used to identify the discharge advice for the purpose of chart review and to assess the documentation of head injuries compliance with recommendation for NICE assessment. Data were checked between January 2022 up to May 2022 to allow more intervals for better assessment. Our finding indicates that documentation of verbal advice, 26% of patients were not recorded to have received this in January compared to only 3% in May & Written advice was not recorded in 44% of patients studied in January compared to 1% in May.

Keywords: head, injuries, advice, leaflets

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Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

Abstract:

One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Wen-Hsiang Lai

Abstract:

Except for the internal aspects of entrepreneurship (i.e. motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares the internal knowledge within industrial clusters. This study finds that when comparing to the companies which are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: entrepreneurship, industrial cluster, industrial district, economies of agglomerations, Taiwan Machinery Cluster (TMC)

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Authors: A. Akın, H. Çoban

Abstract:

This study was carried out to determine the effects of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR + Boric Acid (BA), 1/6 CTR + BA, 1/9 CTR + BA applications on yield and yield components of four years old Alphonse Lavallee grape variety (Vitis vinifera L.) grown on grafted 110 Paulsen rootstock in Konya province in Turkey in the vegetation period in 2015. According to the results, the highest maturity index 21.46 with 1/9 CTR application; the highest grape juice yields 736.67 ml with 1/3 CTR + BA application; the highest L* color value 32.07 with 1/9 CTR application; the highest a* color value 1.74 with 1/9 CTR application; the highest b* color value 3.72 with 1/9 CTR application were obtained. The effects of applications on grape fresh yield, cluster weight and berry weight were not found statistically significant.

Keywords: alphonse lavallee grape cultivar, different cluster tip reduction (1/3, 1/6, 1/9), foliar boric acid application, yield, quality

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Authors: Insiya Kapasi, Roshni Udyavar Yehuda

Abstract:

Cluster Redevelopment is a new concept in the city of Mumbai. Its regulations were laid down by the government in 2009. The concept of cluster redevelopment encompasses a group of buildings defined by a boundary as specified by the municipal authority (in this case, Mumbai), which may be dilapidated or approved for redevelopment. The study analyses the effect of cluster redevelopment in the form of renewal of old group of buildings as compared to refurbishment or restoration - on energy consumption. The methodology includes methods of assessment to determine increase or decrease in energy consumption in cluster redevelopment based on different criteria such as carpet area of the units, building envelope and its architectural elements. Results show that as the area and number of units increase the Energy consumption increases and the EPI (energy performance index) decreases as compared to the base case. The energy consumption per unit area declines by 29% in the proposed cluster redevelopment as compared to the original settlement. It is recommended that although the development is spacious and provides more light and ventilation, aspects such as glass type, traditional architectural features and consumer behavior are critical in the reduction of energy consumption.

Keywords: Cluster Redevelopment, Energy Consumption, Energy Efficiency, Typologies

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