Search results for: transportation networks
3727 Hybrid Algorithm for Frequency Channel Selection in Wi-Fi Networks
Authors: Cesar Hernández, Diego Giral, Ingrid Páez
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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks
Procedia PDF Downloads 5103726 Pre-Shared Key Distribution Algorithms' Attacks for Body Area Networks: A Survey
Authors: Priti Kumari, Tricha Anjali
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Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys
Procedia PDF Downloads 3373725 Social Media Marketing in Russia
Authors: J. A. Ageeva, Z. S. Zavyalova
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The article considers social media as a tool for business promotion. We analyze and compare the SMM experience in the western countries and Russia. A short review of Russian social networks are given including their peculiar features, and the main problems and perspectives of Russian SMM are described.Keywords: social media, social networks, marketing, SMM
Procedia PDF Downloads 5243724 The Load Balancing Algorithm for the Star Interconnection Network
Authors: Ahmad M. Awwad, Jehad Al-Sadi
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The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.Keywords: load balancing, star network, interconnection networks, algorithm
Procedia PDF Downloads 2923723 Epistemic Uncertainty Analysis of Queue with Vacations
Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine
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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion
Procedia PDF Downloads 4013722 Neural Networks for Distinguishing the Performance of Two Hip Joint Implants on the Basis of Hip Implant Side and Ground Reaction Force
Authors: L. Parisi
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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.Keywords: kinemic gait data, neural networks, hip joint implant, hip arthroplasty, rehabilitation engineering
Procedia PDF Downloads 3293721 Toward an Understanding of the Neurofunctional Dissociation between Animal and Tool Concepts: A Graph Theoretical Analysis
Authors: Skiker Kaoutar, Mounir Maouene
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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from Mc Rae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.Keywords: animals, tools, network, semantics, small-world, resilience to damage
Procedia PDF Downloads 5103720 Anti-Phase Synchronization of Complex Delayed Networks with Output Coupling via Pinning Control
Authors: Chanyuan Gu, Shouming Zhong
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Synchronization is a fundamental phenomenon that enables coherent behavior in networks as a result of interactions. The purpose of this research had been to investigate the problem of anti-phase synchronization for complex delayed dynamical networks with output coupling. The coupling configuration is general, with the coupling matrix not assumed to be symmetric or irreducible. The amount of the coupling variables between two connected nodes is flexible, the nodes in the drive and response systems need not to be identical and there is not any extra constraint on the coupling matrix. Some pinning controllers are designed to make the drive-response system achieve the anti-phase synchronization. For the convenience of description, we applied the matrix Kronecker product. Some new criteria are proposed based on the Lyapunov stability theory, linear matrix inequalities (LMI) and Schur complement. Lastly, some simulation examples are provided to illustrate the effectiveness of our proposed conditions.Keywords: anti-phase synchronization, complex networks, output coupling, pinning control
Procedia PDF Downloads 3683719 Effective Planning of Public Transportation Systems: A Decision Support Application
Authors: Ferdi Sönmez, Nihal Yorulmaz
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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.Keywords: operator cost, bi-level optimization model, user cost, urban transportation
Procedia PDF Downloads 2153718 Performance and Emission Prediction in a Biodiesel Engine Fuelled with Honge Methyl Ester Using RBF Neural Networks
Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.
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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means
Procedia PDF Downloads 5313717 Performance Analysis of Heterogeneous Cellular Networks with Multiple Connectivity
Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon
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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry
Procedia PDF Downloads 3003716 Phone Number Spoofing Attack in VoLTE 4G
Authors: Joo-Hyung Oh
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The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.Keywords: LTE, 4G, VoLTE, phone number spoofing
Procedia PDF Downloads 4083715 Long Short-Time Memory Neural Networks for Human Driving Behavior Modelling
Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou
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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change
Procedia PDF Downloads 2213714 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks
Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos
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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.Keywords: metaphor detection, deep learning, representation learning, embeddings
Procedia PDF Downloads 1223713 Traffic Congestions Modeling and Predictions by Social Networks
Authors: Bojan Najdenov, Danco Davcev
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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android
Procedia PDF Downloads 4543712 Natural Emergence of a Core Structure in Networks via Clique Percolation
Authors: A. Melka, N. Slater, A. Mualem, Y. Louzoun
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Networks are often presented as containing a “core” and a “periphery.” The existence of a core suggests that some vertices are central and form the skeleton of the network, to which all other vertices are connected. An alternative view of graphs is through communities. Multiple measures have been proposed for dense communities in graphs, the most classical being k-cliques, k-cores, and k-plexes, all presenting groups of tightly connected vertices. We here show that the edge number thresholds for such communities to emerge and for their percolation into a single dense connectivity component are very close, in all networks studied. These percolating cliques produce a natural core and periphery structure. This result is generic and is tested in configuration models and in real-world networks. This is also true for k-cores and k-plexes. Thus, the emergence of this connectedness among communities leading to a core is not dependent on some specific mechanism but a direct result of the natural percolation of dense communities.Keywords: cliques, core structure, percolation, phase transition
Procedia PDF Downloads 1393711 Gender Effects in EEG-Based Functional Brain Networks
Authors: Mahdi Jalili
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Functional connectivity in the human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks – whose nodes are brain regions and edges correspond to functional links between them – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using correlation analysis and were further binarized to obtain binary functional networks. Global and local efficiency measures – as graph theory metrics– were computed for the extracted networks. We found that male brains have a significantly greater global efficiency (i.e., global communicability of the network) across all frequency bands for a wide range of cost values in both hemispheres. Furthermore, for a range of cost values, female brains showed significantly greater right-hemispheric local efficiency (i.e., local connectivity) than male brains.Keywords: EEG, brain, functional networks, network science, graph theory
Procedia PDF Downloads 4223710 Use of Integrated Knowledge Networks to Increase Innovation in Nanotechnology Research and Development
Authors: R. Byler
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Innovation, particularly in technology development, is a crucial aspect of nanotechnology R&D and, although several approaches to effective innovation management exist, organizational structures that promote knowledge exchange have been found to be most effect in supporting new and emerging technologies. This paper discusses Integrated Knowledge Networks (IKNs) and evaluates its use within nanotechnology R&D to increase technology innovation. Specifically, this paper reviews the role of IKNs in bolstering national and international nanotechnology development and in enhancing nanotechnology innovation. Both physical and virtual IKNs, particularly IT-based network platforms for community-based innovation, offer strategies for enhanced technology innovation, interdisciplinary cooperation, and enterprise development. Effectively creating and managing technology R&D networks can facilitate successful knowledge exchange, enhanced innovation, commercialization, and technology transfer. As such, IKNs are crucial to technology development processes and, thus, in increasing the quality and access to new, innovative nanoscience and technologies worldwide.Keywords: community-based innovation, integrated knowledge networks, nanotechnology, technology innovation
Procedia PDF Downloads 3803709 Improving Axial-Attention Network via Cross-Channel Weight Sharing
Authors: Nazmul Shahadat, Anthony S. Maida
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In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks
Procedia PDF Downloads 503708 2023 Targets of the Republic of Turkey State Railways
Authors: Hicran Açıkel, Hüseyin Arak, D. Ali Açıkel
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Train or high-speed train is a land transportation vehicle, which is safe and offers passengers flight-like comfort while it is preferred for busy lines with respect to passengers. In this study, TCDD’s (Turkish State Railroads Company) targets for the year of 2023, the planned high-speed train lines, improvements, which are considered for the existing lines, and achievability of these targets are examined.Keywords: train, high-speed train, TCDD, transportation
Procedia PDF Downloads 2193707 Trends of Public-Private Partnership Infrastructure in Thailand
Authors: Wasaporn Techapeeraparnich
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Bringing private investor involving in providing public infrastructure have been increasingly used worldwide, and there is no exception for developing countries like Thailand. Recently, there is a huge investment opportunity for public-private partnership (PPP) in Thailand, especially in the transportation sector. This paper analyses the development of the PPP since the early beginning of PPP in different service sectors. It also summarizes the development of PPP and its application in terms of usage, opportunities and trends particularly in the transport sector. The results are aimed to draw some lessons learned for future development.Keywords: case study, public-private partnership, transportation, Thailand
Procedia PDF Downloads 4093706 The Role of Social Networking in Activating the Participation of Youth in the Community
Authors: Raya Hamed Hial Al Maamari
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The gulf societies have been undergoing radical changes because of the technology transfer. It altered the humanities attitudes. Especially, youth habits so they become a fond of using social networking. This study aimed to find out the ratio of social networking in Directing youth to participate with government institutions in decision-making and improving their societies. The study considered a descriptive study, social survey method was used on a sample of 100 young men from different gulf countries, using an electronic questionnaire, with some interviews with famous leaders of youth groups. Finally, the researchers suggested many effective views to activate youth efforts using social networks as an effective manner to plan for the development policy and Implemented accurately in the community. The findings illustrated that social networks play a vital role in encouraging youth to participate Enthusiastically in providing the service. As it notices these networks contain large numbers of youth. Therefore, the influences become widely and feasible. Moreover, the study indicated the fact that most of youth teamwork started in these social networks. Then, it has been growing to the real society.Keywords: social work, volunteering, youth, community
Procedia PDF Downloads 3163705 Efficient Broadcasting in Wireless Sensor Networks
Authors: Min Kyung An, Hyuk Cho
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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 3193704 Location Management in Wireless Sensor Networks with Mobility
Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar
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Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.Keywords: mobility management, motes, multihop, wireless sensor networks
Procedia PDF Downloads 3823703 NR/PEO Block Copolymer: A Chelating Exchanger for Metal Ions
Authors: M. S. Mrudula, M. R. Gopinathan Nair
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In order to utilize the natural rubber for developing new green polymeric materials for specialty applications, we have prepared natural rubber and polyethylene oxide based polymeric networks by two shot method. The polymeric networks thus formed have been used as chelating exchanger for metal ion binding. Chelating exchangers are, in general, coordinating copolymers containing one or more electron donor atoms such as N, S, O, and P that can form coordinate bonds with metals. Hydrogels are water- swollen network of hydrophilic homopolymer or copolymers. They acquire a great interest due to the facility of the incorporation of different chelating groups into the polymeric networks. Such polymeric hydrogels are promising materials in the field of hydrometallurgical applications and water purification due to their chemical stability. The current study discusses the swelling response of the polymeric networks as a function of time, temperature, pH and [NaCl] and sorption studies. Equilibrium swelling has been observed to depend on both structural aspects of the polymers and environmental factors. Metal ion sorption shows that these polymeric networks can be used for removal, separation, and enrichment of metal ions from aqueous solutions and can play an important role for environmental remediation of municipal and industrial wastewater.Keywords: block copolymer, adsorption, chelating exchanger, swelling study, polymer, metal complexes
Procedia PDF Downloads 3153702 Comparative Analysis of Canal Centering Ratio, Apical Transportation, and Remaining Dentin Thickness between Single File System Using Cone Beam Computed Tomography: An in vitro Study
Authors: Aditi Jain
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Aim: To compare the canal transportation, centering ability and remaining dentin thickness of OneShape and WaveOne system using CBCT. Objective: To identify rotary system which respects original canal anatomy. Materials and Methods: Forty extracted human single-rooted premolars were used in the present study. Pre-instrumentation scans of all teeth were taken, canal curvatures were calculated, and the samples were randomly divided into two groups with twenty samples in each group, where Group 1 included WaveOne system and Group 2 Protaper rotary system. Post-instrumentation scans were performed, and the two scans were compared to determine canal transportation, centering ability and remaining dentin thickness at 1, 3, and 5 mm from the root apex. Results: Using Student’s unpaired t test results were as follows; for canal transportation Group 1 showed statistical significant difference at 3mm, 6mm and non-significant difference was obtained at 9mm but for Group 2 non-statistical significant difference was obtained at 3mm, 6mm, and 9mm. For centering ability and remaining dentin thickness Group 1 showed non-statistical significant difference at 3mm and 9mm, while statistical significant difference at 6mm was obtained. When comparison of remaining dentin thickness was done at three levels using two groups WaveOne and ProTaper. There was non-statistical significant difference between two groups. Conclusion: WaveOne single reciprocation file respects original canal anatomy better than ProTaper. WaveOne depicted the best centering ability.Keywords: ShapeOne, WaveOne, transportation, centering ability, dentin thickness, CBCT (Cone Beam Computed Tomography)
Procedia PDF Downloads 1753701 Adaptive Routing Protocol for Dynamic Wireless Sensor Networks
Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali
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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
Procedia PDF Downloads 5103700 Energy Consumption Optimization of Electric Vehicle by Using Machine Learning: A Comparative Literature Review and Lessons Learned
Authors: Sholeh Motaghian, Pekka Toivanen, Keiji Haataja
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The swift expansion of the transportation industry and its associated emissions have captured the focus of policymakers who are dedicated to upholding ecological sustainability. As a result, understanding the key contributors to transportation emissions is of utmost significance. Amidst the escalating transportation emissions, the significance of electric vehicles cannot be overstated. Electric vehicles play a critical role in steering us towards a low-carbon economy and a sustainable ecological setting. The effective integration of electric vehicles hinges on the development of energy consumption models capable of accurately and efficiently predicting energy usage. Enhancing the energy efficiency of electric vehicles will play a pivotal role in reducing driver concerns and establishing a vital framework for the efficient operation, planning, and management of charging infrastructure. In this article, the works done in this field are reviewed, and the advantages and disadvantages of each are stated.Keywords: deep learning, electrical vehicle, energy consumption, machine learning, smart grid
Procedia PDF Downloads 353699 Enhancing Throughput for Wireless Multihop Networks
Authors: K. Kalaiarasan, B. Pandeeswari, A. Arockia John Francis
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Wireless, Multi-hop networks consist of one or more intermediate nodes along the path that receive and forward packets via wireless links. The backpressure algorithm provides throughput optimal routing and scheduling decisions for multi-hop networks with dynamic traffic. Xpress, a cross-layer backpressure architecture was designed to reach the capacity of wireless multi-hop networks and it provides well coordination between layers of network by turning a mesh network into a wireless switch. Transmission over the network is scheduled using a throughput-optimal backpressure algorithm. But this architecture operates much below their capacity due to out-of-order packet delivery and variable packet size. In this paper, we present Xpress-T, a throughput optimal backpressure architecture with TCP support designed to reach maximum throughput of wireless multi-hop networks. Xpress-T operates at the IP layer, and therefore any transport protocol, including TCP, can run on top of Xpress-T. The proposed design not only avoids bottlenecks but also handles out-of-order packet delivery and variable packet size, optimally load-balances traffic across them when needed, improving fairness among competing flows. Our simulation results shows that Xpress-T gives 65% more throughput than Xpress.Keywords: backpressure scheduling and routing, TCP, congestion control, wireless multihop network
Procedia PDF Downloads 4983698 Interactive Solutions for the Multi-Objective Capacitated Transportation Problem with Mixed Constraints under Fuzziness
Authors: Aquil Ahmed, Srikant Gupta, Irfan Ali
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In this paper, we study a multi-objective capacitated transportation problem (MOCTP) with mixed constraints. This paper is comprised of the modelling and optimisation of an MOCTP in a fuzzy environment in which some goals are fractional and some are linear. In real life application of the fuzzy goal programming (FGP) problem with multiple objectives, it is difficult for the decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise or uncertain. Also, we developed the concept of linearization of fractional goal for solving the MOCTP. In this paper, imprecision of the parameter is handled by the concept of fuzzy set theory by considering these parameters as a trapezoidal fuzzy number. α-cut approach is used to get the crisp value of the parameters. Numerical examples are used to illustrate the method for solving MOCTP.Keywords: capacitated transportation problem, multi objective linear programming, multi-objective fractional programming, fuzzy goal programming, fuzzy sets, trapezoidal fuzzy number
Procedia PDF Downloads 407