Search results for: number of networks per unit volume of elastomer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15837

Search results for: number of networks per unit volume of elastomer

15747 Developing Artificial Neural Networks (ANN) for Falls Detection

Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

Abstract:

The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

Procedia PDF Downloads 468
15746 Low Back Pain and Patients Lifting Behaviors among Nurses Working in Al Sadairy Hospital, Aljouf

Authors: Fatma Abdel Moneim Al Tawil

Abstract:

Low back pain (LBP) among nurses has been the subject of research studies worldwide. However, evidence of the influence of patients lifting behaviors and LBP among nurses in Saudi Arabia remains scarce. The purpose of this study was to investigate the relationship between LBP and nurses lifting behaviors. LBP questionnaire was distributed to 100 nurses working in Alsadairy Hospital distributed as Emergency unit(9),Coronary Care unit (9), Intensive Care Unit (7), Dialysis unit (30), Burn unit (5), surgical unit (11), Medical (14) and, X-ray unit (15). The questionnaire included demographic data, attitude scale, Team work scale, Back pain history and Knowledge scale. Regarding to emergency unit, there is appositive significant relation between teamwork scale and Knowledge as r = (0.807) and P =0.05. Regarding to ICU unit, there is a positive significant relation between teamwork scale and attitude scale as r= (0.781) and P =0.05. Regarding to Dialysis unit, there is a positive significant relation between attitude scale and teamwork scale as r=(0.443) and P =0.05. The findings suggest enhanced awareness of occupational safety with safe patient handling practices among nursing students must be emphasized and integrated into their educational curriculum. Moreover, back pain prevention program should incorporate the promotion of an active lifestyle and fitness training the implementation of institutional patient handling policies.

Keywords: low back pain, lifting behaviors, nurses, team work

Procedia PDF Downloads 390
15745 Use of a Relief Mobile Unit in the Humanitarian Cause

Authors: Stephani Ferreira da Silva Manso, Regina M. M. Dias Chiquetano

Abstract:

This article aims to present a research on one of the main aspects of response in humanitarian causes: agility of operations. Brazil is among the 10 countries with the highest number of people affected by disasters.The main types of disasters in Brazil include floods and mass movements. Focusing on a nongovernmental organization that began in the conflicts of First and Second World Wars, arriving in Brazil in 1984. In 2017, the organization has activated their emergency response mobile unit to reach families following flooding that affected around 9,000 people. In partnership with Truckvan, the mobile unit, has 45 m² of floor space and is divided into three compartments each designed to meet the main needs of the population: the first will be used to prepare hot meals, the second to washing and drying of clothes, and the third for the accomplishment of psychological support. This option will be available for situations where there are more than one thousand victims who are sheltered, even temporarily, and demand immediate care, which will be identified through the National Emergency Plan. In this way, the actions that were already done as donation of blankets, clothes, hygiene kits, among others, will be enhanced. Studies show that one of the biggest difficulties in responding to the disaster is in the first few hours after the disaster. This study aimed to show the organization's innovative results and to propose improvement actions in transportation focused on humanitarian aid as the concepts developed in the manufacture and adaptation of the mobile unit to the rescue environment. Thus, the principles of this humanitarian aid bus are very effective.

Keywords: disasters, humanitarian cause, relief, unit mobile

Procedia PDF Downloads 157
15744 Overview of Standard Unit System of Shenzhen Land Spatial Planning and Case Analysis

Authors: Ziwei Huang

Abstract:

The standard unit of Shenzhen land spatial planning has the characteristics of vertical conduction, horizontal evaluation, internal balance and supervision of implementation. It mainly assumes the role of geospatial unit, assists in promoting the complex development of the business in Shenzhen and undertakes the management and transmission of upper and lower levels of planning as well as the Urban management functions such as gap analysis of public facilities, planning evaluation and dynamic monitoring of planning information. Combining with the application examples of the analysis of gaps in public facilities in Longgang District, it can be found that the standard unit of land spatial planning in Shenzhen as a small-scale geographic basic unit, has a stronger urban spatial coupling effect. However, the universality of the application of the system is still lacking and it is necessary to propose more scientific and powerful standard unit delineation standards and planning function evaluation indicators to guide the implementation of the system's popularization and application.

Keywords: Shenzhen city, land spatial planning, standard unit system, urban delicacy management

Procedia PDF Downloads 95
15743 Numerical Simulations of Fire in Typical Air Conditioned Railway Coach

Authors: Manoj Sarda, Abhishek Agarwal, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

Abstract:

Railways in India remain primary mode of transport having one of the largest networks in the world and catering to billions of transits yearly. Catastrophic economic damage and loss to life is encountered over the past few decades due to fire to locomotives. Study of fire dynamics and fire propagation plays an important role in evacuation planning and reducing losses. Simulation based study of propagation of fire and soot inside an air conditioned coach of Indian locomotive is done in this paper. Finite difference based solver, Fire Dynamic Simulator (FDS) version 6 has been used for analysis. A single air conditioned 3 tier coupe closed to ambient surroundings by glass windows having occupancy for 8 people is the basic unit of the domain. A system of three such coupes combined is taken to be fundamental unit for the entire study to resemble effect to an entire coach. Analysis of flame and soot contours and concentrations is done corresponding to variations in heat release rate per unit volume (HRRPUA) of fire source, variations in conditioned air velocity being circulated inside coupes by vents and an alternate fire initiation and propagation mechanism via ducts. Quantitative results of fractional area in top and front view of the three coupes under fire and smoke are obtained using MATLAB (IMT). Present simulations and its findings will be useful for organizations like Commission of Railway Safety and others in designing and implementing safety and evacuation measures.

Keywords: air conditioned coaches, fire propagation, flame contour, soot flow, train fire

Procedia PDF Downloads 255
15742 Remaining Useful Life Estimation of Bearings Based on Nonlinear Dimensional Reduction Combined with Timing Signals

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

Abstract:

In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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15741 Allocation of Mobile Units in an Urban Emergency Service System

Authors: Dimitra Alexiou

Abstract:

In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

Procedia PDF Downloads 459
15740 On the Performance Analysis of Coexistence between IEEE 802.11g and IEEE 802.15.4 Networks

Authors: Chompunut Jantarasorn, Chutima Prommak

Abstract:

This paper presents an intensive measurement studying of the network performance analysis when IEEE 802.11g Wireless Local Area Networks (WLAN) coexisting with IEEE 802.15.4 Wireless Personal Area Network (WPAN). The measurement results show that the coexistence between both networks could increase the Frame Error Rate (FER) of the IEEE 802.15.4 networks up to 60% and it could decrease the throughputs of the IEEE 802.11g networks up to 55%.

Keywords: wireless performance analysis, coexistence analysis, IEEE 802.11g, IEEE 802.15.4

Procedia PDF Downloads 518
15739 Conceptual Knowledge Structure Updates after Instructor Provided Structural Feedback: An Exploratory Study Applied with Undergraduate Architectural Engineering Students

Authors: Roy B. Clariana, Ryan L. Solnosky

Abstract:

Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

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15738 A Robust Stretchable Bio Micro-Electromechanical Systems Technology for High-Strain in vitro Cellular Studies

Authors: Tiffany Baetens, Sophie Halliez, Luc Buée, Emiliano Pallecchi, Vincent Thomy, Steve Arscott

Abstract:

We demonstrate here a viable stretchable bio-microelectromechanical systems (BioMEMS) technology for use with biological studies concerned with the effect of high mechanical strains on living cells. An example of this is traumatic brain injury (TBI) where neurons are damaged with physical force to the brain during, e.g., accidents and sports. Robust, miniaturized integrated systems are needed by biologists to be able to study the effect of TBI on neuron cells in vitro. The major challenges in this area are (i) to develop micro, and nanofabrication processes which are based on stretchable substrates and to (ii) create systems which are robust and performant at very high mechanical strain values—sometimes as high as 100%. At the time of writing, such processes and systems were rapidly evolving subject of research and development. The BioMEMS which we present here is composed of an elastomer substrate (low Young’s modulus ~1 MPa) onto which is patterned robust electrodes and insulators. The patterning of the thin films is achieved using standard photolithography techniques directly on the elastomer substrate—thus making the process generic and applicable to many materials’ in based systems. The chosen elastomer used is commercial ‘Sylgard 184’ polydimethylsiloxane (PDMS). It is spin-coated onto a silicon wafer. Multistep ultra-violet based photolithography involving commercial photoresists are then used to pattern robust thin film metallic electrodes (chromium/gold) and insulating layers (parylene) on the top of the PDMS substrate. The thin film metals are deposited using thermal evaporation and shaped using lift-off techniques The BioMEMS has been characterized mechanically using an in-house strain-applicator tool. The system is composed of 12 electrodes with one reference electrode transversally-orientated to the uniaxial longitudinal straining of the system. The electrical resistance of the electrodes is observed to remain very stable with applied strain—with a resistivity approaching that of evaporated gold—up to an interline strain of ~50%. The mechanical characterization revealed some interesting original properties of such stretchable BioMEMS. For example, a Poisson effect induced electrical ‘self-healing’ of cracking was identified. Biocompatibility of the commercial photoresist has been studied and is conclusive. We will present the results of the BioMEMS, which has also characterized living cells with a commercial Multi Electrode Array (MEA) characterization tool (Multi Channel Systems, USA). The BioMEMS enables the cells to be strained up to 50% and then characterized electrically and optically.

Keywords: BioMEMS, elastomer, electrical impedance measurements of living cells, high mechanical strain, microfabrication, stretchable systems, thin films, traumatic brain injury

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15737 Function Approximation with Radial Basis Function Neural Networks via FIR Filter

Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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15736 A Review of Security Attacks and Intrusion Detection Schemes in Wireless Sensor Networks: A Survey

Authors: Maleh Yassine, Ezzati Abdellah

Abstract:

Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs.

Keywords: wireless sensor networks, security attack, denial of service, IDS, cluster-based model, signature based IDS, hybrid IDS

Procedia PDF Downloads 345
15735 Optimal Maintenance Policy for a Partially Observable Two-Unit System

Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

Abstract:

In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

Procedia PDF Downloads 436
15734 Efficient Broadcasting in Wireless Sensor Networks

Authors: Min Kyung An, Hyuk Cho

Abstract:

In this paper, we study the Minimum Latency Broadcast Scheduling (MLBS) problem in wireless sensor networks (WSNs). The main issue of the MLBS problem is to compute schedules with the minimum number of timeslots such that a base station can broadcast data to all other sensor nodes with no collisions. Unlike existing works that utilize the traditional omni-directional WSNs, we target the directional WSNs where nodes can collaboratively determine and orientate their antenna directions. We first develop a 7-approximation algorithm, adopting directional WSNs. Our ratio is currently the best, to the best of our knowledge. We then validate the performance of the proposed algorithm through simulation.

Keywords: broadcast, collision-free, directional antenna, approximation, wireless sensor networks

Procedia PDF Downloads 317
15733 Influence Maximization in Dynamic Social Networks and Graphs

Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

Abstract:

Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

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15732 Is Electricity Consumption Stationary in Turkey?

Authors: Eyup Dogan

Abstract:

The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.

Keywords: unit root, electricity consumption, sectoral data, subnational data

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15731 Adaptive Routing Protocol for Dynamic Wireless Sensor Networks

Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

Abstract:

The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

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15730 Analyzing the Impact of DCF and PCF on WLAN Network Standards 802.11a, 802.11b, and 802.11g

Authors: Amandeep Singh Dhaliwal

Abstract:

Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

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15729 Factorization of Computations in Bayesian Networks: Interpretation of Factors

Authors: Linda Smail, Zineb Azouz

Abstract:

Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution P(S) where S is a subset of I. The general idea is to write the expression of P(S) in the form of a product of factors where each factor is easy to compute. More importantly, it will be very useful to give an interpretation of each of the factors in terms of conditional probabilities. This paper considers a semantic interpretation of the factors involved in computing marginal probabilities in Bayesian networks. Establishing such a semantic interpretations is indeed interesting and relevant in the case of large Bayesian networks.

Keywords: Bayesian networks, D-Separation, level two Bayesian networks, factorization of computation

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15728 Neural Network Approach to Classifying Truck Traffic

Authors: Ren Moses

Abstract:

The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

Procedia PDF Downloads 275
15727 Bandwidth Efficient Cluster Based Collision Avoidance Multicasting Protocol in VANETs

Authors: Navneet Kaur, Amarpreet Singh

Abstract:

In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

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15726 Experimental Study of Hyperparameter Tuning a Deep Learning Convolutional Recurrent Network for Text Classification

Authors: Bharatendra Rai

Abstract:

The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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15725 VANETs Geographic Routing Protocols: A survey

Authors: Ramin Karimi

Abstract:

One of common highly mobile wireless ad hoc networks is Vehicular Ad Hoc Networks. Hence routing in vehicular ad hoc network (VANET) has attracted much attention during the last few years. VANET is characterized by its high mobility of nodes and specific topology patterns. Moreover these networks encounter a significant loss rate and a very short duration of communication. In vehicular ad hoc networks, one of challenging is routing of data due to high speed mobility and changing topology of vehicles. Geographic routing protocols are becoming popular due to advancement and availability of GPS devices. Delay Tolerant Networks (DTNs) are a class of networks that enable communication where connectivity issues like sparse connectivity, intermittent connectivity; high latency, long delay, high error rates, asymmetric data rate, and even no end-to-end connectivity exist. In this paper, we review the existing Geographic Routing Protocols for VANETs and also provide a qualitative comparison of them.

Keywords: vehicular ad hoc networks, mobility, geographic routing, delay tolerant networks

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15724 Worst-Case Load Shedding in Electric Power Networks

Authors: Fu Lin

Abstract:

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

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15723 Design and Simulation of All Optical Fiber to the Home Network

Authors: Rahul Malhotra

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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15722 Study of the Vertical Handoff in Heterogeneous Networks and Implement Based on Opnet

Authors: Wafa Benaatou, Adnane Latif

Abstract:

In this document we studied more in detail the Performances of the vertical handover in the networks WLAN, WiMAX, UMTS before studying of it the Procedure of Handoff Vertical, the whole buckled by simulations putting forward the performances of the handover in the heterogeneous networks. The goal of Vertical Handover is to carry out several accesses in real-time in the heterogeneous networks. This makes it possible a user to use several networks (such as WLAN UMTS and WiMAX) in parallel, and the system to commutate automatically at another basic station, without disconnecting itself, as if there were no cut and with little loss of data as possible.

Keywords: vertical handoff, WLAN, UMTS, WIMAX, heterogeneous

Procedia PDF Downloads 358
15721 Security Threats on Wireless Sensor Network Protocols

Authors: H. Gorine, M. Ramadan Elmezughi

Abstract:

In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: wireless sensor networks, network security, light weight encryption, threats

Procedia PDF Downloads 487
15720 Daylight Performance of a Single Unit in Distinct Arrangements

Authors: Rifat Tabassoom

Abstract:

Recently multistoried housing projects are accelerating in the capital of Bangladesh- Dhaka, to house its massive population. Insufficient background research leads to a building design trend where a single unit is designed and then multiplied all through the buildings. Therefore, although having identical designs, all the units cannot perform evenly considering daylight, which also alters their household activities. This paper aims to understand if a single unit can be an optimum solution regarding daylight for a selected housing project.

Keywords: daylight, orientation, performance, simulations

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15719 Tumor Detection Using Convolutional Neural Networks (CNN) Based Neural Network

Authors: Vinai K. Singh

Abstract:

In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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15718 Reliable Multicast Communication in Next Generation Networks

Authors: Muazzam Ali Khan Khattak

Abstract:

Next Generation Network is combination of different networks having different technologies. Due to mobile nature of nodes the movement of nodes occurs from one network to another network. Multicasting in such networks is still a hot issue of research because the user in today's world wants reliable communication wherever it lies. Due to heterogeneity of NGN it is very difficult to handle reliable multicast communication. In this paper we proposed an improved scheme for reliable multicast communication in next generation networks. Because multicast communication is very important to deliver same data packets to multiple receivers and minimize the network traffic. This new scheme will make the multicast communication in NGN more reliable and efficient.

Keywords: next generation networks, route request, IPT, NACK, ARQ, DTN

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