Search results for: small-world networks
1762 Springback Prediction for Sheet Metal Cold Stamping Using Convolutional Neural Networks
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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.Keywords: springback, cold stamping, convolutional neural networks, machine learning
Procedia PDF Downloads 1351761 Theoretical Modeling of Self-Healing Polymers Crosslinked by Dynamic Bonds
Authors: Qiming Wang
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Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds
Procedia PDF Downloads 1771760 Relay-Augmented Bottleneck Throughput Maximization for Correlated Data Routing: A Game Theoretic Perspective
Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli
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In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks
Procedia PDF Downloads 631759 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals
Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty
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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction
Procedia PDF Downloads 1001758 Message Authentication Scheme for Vehicular Ad-Hoc Networks under Sparse RSUs Environment
Authors: Wen Shyong Hsieh, Chih Hsueh Lin
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In this paper, we combine the concepts of chameleon hash function (CHF) and identification based cryptography (IBC) to build a message authentication environment for VANET under sparse RSUs. Based on the CHF, TA keeps two common secrets that will be embedded to all identities to be as the evidence of mutual trusting. TA will issue one original identity to every RSU and vehicle. An identity contains one public ID and one private key. The public ID, includes three components: pseudonym, random key, and public key, is used to present one entity and can be verified to be a legal one. The private key is used to claim the ownership of the public ID. Based on the concept of IBC, without any negotiating process, a CHF pairing key multiplied by one private key and other’s public key will be used for mutually trusting and to be utilized as the session key of secure communicating between RSUs and vehicles. To help the vehicles to do message authenticating, the RSUs are assigned to response the vehicle’s temple identity request using two short time secretes that are broadcasted by TA. To light the loading of request information, one day is divided into M time slots. At every time slot, TA will broadcast two short time secretes to all valid RSUs for that time slot. Any RSU can response the temple identity request from legal vehicles. With the collected announcement of public IDs from the neighbor vehicles, a vehicle can set up its neighboring set, which includes the information about the neighbor vehicle’s temple public ID and temple CHF pairing key that can be derived by the private key and neighbor’s public key and will be used to do message authenticating or secure communicating without the help of RSU.Keywords: Internet of Vehicles (IOV), Vehicular Ad-hoc Networks (VANETs), Chameleon Hash Function (CHF), message authentication
Procedia PDF Downloads 3811757 Design and Performance Improvement of Three-Dimensional Optical Code Division Multiple Access Networks with NAND Detection Technique
Authors: Satyasen Panda, Urmila Bhanja
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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.Keywords: Cross Correlation (CC), Three dimensional Optical Code Division Multiple Access (3-D OCDMA), Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA), Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN), Three Dimensional Modified Quadratic Congruence/Modified Prime (3-D MQC/MP) code
Procedia PDF Downloads 4041756 Managerial Advice-Seeking and Supply Chain Resilience: A Social Capital Perspective
Authors: Ethan Nikookar, Yalda Boroushaki, Larissa Statsenko, Jorge Ochoa Paniagua
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Given the serious impact that supply chain disruptions can have on a firm's bottom-line performance, both industry and academia are interested in supply chain resilience, a capability of the supply chain that enables it to cope with disruptions. To date, much of the research has focused on the antecedents of supply chain resilience. This line of research has suggested various firm-level capabilities that are associated with greater supply chain resilience. A consensus has emerged among researchers that supply chain flexibility holds the greatest potential to create resilience. Supply chain flexibility achieves resilience by creating readiness to respond to disruptions with little cost and time by means of reconfiguring supply chain resources to mitigate the impacts of the disruption. Decisions related to supply chain disruptions are made by supply chain managers; however, the role played by supply chain managers' reference networks has been overlooked in the supply chain resilience literature. This study aims to understand the impact of supply chain managers on their firms' supply chain resilience. Drawing on social capital theory and social network theory, this paper proposes a conceptual model to explore the role of supply chain managers in developing the resilience of supply chains. Our model posits that higher level of supply chain managers' embeddedness in their reference network is associated with increased resilience of their firms' supply chain. A reference network includes individuals from whom supply chain managers seek advice on supply chain related matters. The relationships between supply chain managers' embeddedness in reference network and supply chain resilience are mediated by supply chain flexibility.Keywords: supply chain resilience, embeddedness, reference networks, social capitals
Procedia PDF Downloads 2191755 Simulation of Climatic Change Effects on the Potential Fishing Zones of Dorado Fish (Coryphaena hippurus L.) in the Colombian Pacific under Scenarios RCP Using CMIP5 Model
Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo
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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.Keywords: climatic change, artificial neural networks, dorado fish, CPUE
Procedia PDF Downloads 2351754 Artificial Neural Network Approach for Modeling Very Short-Term Wind Speed Prediction
Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite
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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination
Procedia PDF Downloads 1081753 Internet of Things Networks: Denial of Service Detection in Constrained Application Protocol Using Machine Learning Algorithm
Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio
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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.Keywords: algorithm, CoAP, DoS, IoT, machine learning
Procedia PDF Downloads 631752 A Molecular Dynamics Study on Intermittent Plasticity and Dislocation Avalanche Emissions in FCC and BCC Crystals
Authors: Javier Varillas, Jorge Alcalá
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We investigate dislocation avalanche phenomena in face-centered cubic (FCC) and body-centered cubic (BCC) crystals using massive, large-scale molecular dynamics (MD) simulations. The analysis is focused on the intermittent development of dense dislocation arrangements subjected to uniaxial tensile straining under displacement control. We employ a novel computational scheme that allows us to inject an entangled dislocation structure in periodic MD domains. We assess the emission of plastic bursts (or dislocation avalanches) in terms of the sharp stress drops detected in the stress-strain curve. The plastic activity corresponds to the sporadic operation of specific dislocation glide processes exhibiting quiescent periods between successive avalanche events. We find that the plastic intermittences in our simulations do not overlap in time under sufficiently low strain rates as dissipation operates faster than driving, where the dense dislocation networks evolve through the emission of dislocation avalanche events whose carried slip adheres to self-organized power-law distributions. These findings enable the extension of the slip distributions obtained from strict displacement-controlled micropillar compression experiments towards smaller values of slip size. Our results furnish further understanding upon the development of entangled dislocation networks in metal plasticity, including specific mechanisms of dislocation propagation and annihilation, along with the evolution of specific dislocation populations through dislocation density analyses.Keywords: dislocations, intermittent plasticity, molecular dynamics, slip distributions
Procedia PDF Downloads 1331751 Processing and Modeling of High-Resolution Geophysical Data for Archaeological Prospection, Nuri Area, Northern Sudan
Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali
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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid
Procedia PDF Downloads 4741750 Preparation of Wireless Networks and Security; Challenges in Efficient Accession of Encrypted Data in Healthcare
Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar
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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.Keywords: aggregation, cipher, homomorphic stream, encryption
Procedia PDF Downloads 2491749 Preparation and Properties of Self-Healing Polyurethanes Utilizing the Host-Guest Interaction between Cyclodextrin and Adamantane Moieties
Authors: Kaito Sugane, Mitsuhiro Shibata
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Self-healing polymers have attracted attention because their physical damage and cracks can be effectively repaired, thereby extending the lifetime of the materials. Self-healing polymers using host-guest interaction have the advantage that they are quickly repaired under mild temperature conditions when compared with self-healing polymer using dynamic covalent bonds such as Diels-Alder (DA)/retro-DA and disulfide metathesis reactions. Especially, it is known that hydrogels utilizing the host-guest interaction between cyclodextrin and various guest molecules are repeatedly self-repaired at room temperature. However, most of the works deal with hydrogels, and little attention has been paid for thermosetting resins as polyurethane, epoxy and unsaturated polyester resins. In this study, polyetherurethane networks (PUN-CD-Ads) incorporating cyclodextrin and adamantane moieties were prepared by the crosslinking reactions of β-cyclodextrin (CD), 1-adamantanol (AdOH), glycerol ethoxylate (GCE) and hexamethylene diisocyanate (HDI), and thermal, mechanical and self-healing properties of the polymer network films were investigated. Our attention was focused on the influences of molar ratio of CD/AdOH, GCE/CD and OH/NCO on the properties. The FT-IR, and gel fraction analysis revealed that the urethanization reaction smoothly progress to form polyurethane networks. When two cut pieces of the films were contacted at the cross-section at room temperature for 30 seconds, the two pieces adhered to produce a self-healed film. Especially, the PUN-CD-Ad prepared at GCE/CD = 5/1, CD/AdOH = 1/1, and OH/NCO = 1/1 film exhibited the highest healing efficiency for tensile strength. Most of the PUN-CD-Ads were successfully self-healed at room temperature.Keywords: host-guest interaction, network polymer, polyurethane, self-healing
Procedia PDF Downloads 1751748 Work-Life Balance: A Landscape Mapping of Two Decades of Scholarly Research
Authors: Gertrude I Hewapathirana, Mohamed M. Moustafa, Michel G. Zaitouni
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The purposes of this research are: (a) to provide an epistemological and ontological understanding of the WLB theory, practice, and research to illuminate how the WLB evolved between 2000 to 2020 and (b) to analyze peer-reviewed research to identify the gaps, hotspots, underlying dynamics, theoretical and thematic trends, influential authors, research collaborations, geographic networks, and the multidisciplinary nature of the WLB theory to guide future researchers. The research used four-step bibliometric network analysis to explore five research questions. Using keywords such as WLB and associated variants, 1190 peer-reviewed articles were extracted from the Scopus database and transformed to a plain text format for filtering. The analysis was conducted using the R version 4.1 software (R Development Core Team, 2021) and several libraries such as bibliometrics, word cloud, and ggplot2. We used the VOSviewer software (van Eck & Waltman, 2019) for network visualization. The WLB theory has grown into a multifaceted, multidisciplinary field of research. There is a paucity of research between 2000 to 2005 and an exponential growth from 2006 to 2015. The rapid increase of WLB research in the USA, UK, and Australia reflects the increasing workplace stresses due to hyper competitive workplaces, inflexible work systems, and increasing diversity and the emergence of WLB support mechanisms, legal and constitutional mandates to enhance employee and family wellbeing at multilevel social systems. A severe knowledge gap exists due to inadequate publications disseminating the "core" WLB research. "Locally-centralized-globally-discrete" collaboration among researchers indicates a "North-South" divide between developed and developing nations. A shortage in WLB research in developing nations and a lack of research collaboration hinder a global understanding of the WLB as a universal phenomenon. Policymakers and practitioners can use the findings to initiate supporting policies, and innovative work systems. The boundary expansion of the WLB concepts, categories, relations, and properties would facilitate researchers/theoreticians to test a variety of new dimensions. This is the most comprehensive WLB landscape analysis that reveals emerging trends, concepts, networks, underlying dynamics, gaps, and growing theoretical and disciplinary boundaries. It portrays the WLB as a universal theory.Keywords: work-life balance, co-citation networks; keyword co-occurrence network, bibliometric analysis
Procedia PDF Downloads 1901747 Yawning Computing Using Bayesian Networks
Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube
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Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms
Procedia PDF Downloads 4501746 Data Augmentation for Early-Stage Lung Nodules Using Deep Image Prior and Pix2pix
Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung
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Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.Keywords: medical technology, artificial intelligence, radiology, lung cancer
Procedia PDF Downloads 601745 Pilot-free Image Transmission System of Joint Source Channel Based on Multi-Level Semantic Information
Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu
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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness
Procedia PDF Downloads 1071744 A Review on Cloud Computing and Internet of Things
Authors: Sahar S. Tabrizi, Dogan Ibrahim
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Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.Keywords: cloud computing, cloud systems, cloud services, IaaS, PaaS, SaaS
Procedia PDF Downloads 2261743 Collaboration versus Cooperation: Grassroots Activism in Divided Cities and Communication Networks
Authors: R. Barbour
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Peace-building organisations act as a network of information for communities. Through fieldwork, it was highlighted that grassroots organisations and activists may cooperate with each other in their actions of peace-building; however, they would not collaborate. Within two divided societies; Nicosia in Cyprus and Jerusalem in Israel, there is a distinction made by organisations and activists with regards to activities being more ‘co-operative’ than ‘collaborative’. This theme became apparent when having informal conversations and semi-structured interviews with various members of the activist communities. This idea needs further exploration as these distinctions could impact upon the efficiency of peacebuilding activities within divided societies. Civil societies within divided landscapes, both physically and socially, play an important role in conflict resolution. How organisations and activists interact with each other has the possibility to be very influential with regards to peacebuilding activities. Working together sets a positive example for divided communities. Cooperation may be considered a primary level of interaction between CSOs. Therefore, at the beginning of a working relationship, organisations cooperate over basic agendas, parallel power structures and focus, which led to the same objective. Over time, in some instances, due to varying factors such as funding, more trust and understanding within the relationship, it could be seen that processes progressed to more collaborative ways. It is evident to see that NGOs and activist groups are highly independent and focus on their own agendas before coming together over shared issues. At this time, there appears to be more collaboration in Nicosia among CSOs and activists than Jerusalem. The aims and objectives of agendas also influence how organisations work together. In recent years, Nicosia, and Cyprus in general, have perhaps changed their focus from peace-building initiatives to more environmental issues which have become new-age reconciliation topics. Civil society does not automatically indicate like-minded organisations however solidarity within social groups can create ties that bring people and resources together. In unequal societies, such as those in Nicosia and Jerusalem, it is these ties that cut across groups and are essential for social cohesion. Societies are a collection of social groups; individuals who have come together over common beliefs. These groups in turn shape the identities and determine the values and structures within societies. At many different levels and stages, social groups work together through cooperation and collaboration. These structures in turn have the capabilities to open up networks to less powerful or excluded groups, with the aim to produce social cohesion which may contribute social stability and economic welfare over any extended period.Keywords: collaboration, cooperation, grassroots activism, networks of communication
Procedia PDF Downloads 1481742 Learning Dynamic Representations of Nodes in Temporally Variant Graphs
Authors: Sandra Mitrovic, Gaurav Singh
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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.Keywords: churn prediction, dynamic networks, node2vec, auto-encoders
Procedia PDF Downloads 3051741 Making Social Accountability Initiatives Work in the Performance of Local Self-Governing Institutions: District-Level Analysis in Rural Assam, India
Authors: Pankaj Kumar Kalita
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Ineffectiveness of formal institutional mechanisms such as official audit to improve public service delivery has been a serious concern to scholars working on governance reforms in developing countries. Scholars argue that public service delivery in local self-governing institutions can be improved through application of informal mechanisms such as social accountability. Social accountability has been reinforced with the engagement of citizens and civic organizations in the process of service delivery to reduce the governance gap in developing countries. However, there are challenges that may impede the scope of establishing social accountability initiatives in the performance of local self-governing institutions. This study makes an attempt to investigate the factors that may impede the scope of establishing social accountability, particularly in culturally heterogeneous societies like India. While analyzing the implementation of two rural development schemes by Panchayats, the local self-governing institutions functioning in rural Assam in India, this study argues that the scope of establishing social accountability in the performance of local self-governing institutions, particularly in culturally heterogeneous societies in developing countries will be impeded by the absence of inter-caste and inter-religion networks. Data has been collected from five selected districts of Assam using in-depth interview method and survey method. The study further contributes to the debates on 'good governance' and citizen-centric approaches in developing countries.Keywords: citizen engagement, local self-governing institutions, networks, social accountability
Procedia PDF Downloads 3101740 An Intelligent Transportation System for Safety and Integrated Management of Railway Crossings
Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti
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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety
Procedia PDF Downloads 4911739 Internet Protocol Television: A Research Study of Undergraduate Students Analyze the Effects
Authors: Sabri Serkan Gulluoglu
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The study is aimed at examining the effects of internet marketing with IPTV on human beings. Internet marketing with IPTV is emerging as an integral part of business strategies in today’s technologically advanced world and the business activities all over the world are influences with the emergence of this modern marketing tool. As the population of the Internet and on-line users’ increases, new research issues have arisen concerning the demographics and psychographics of the on-line user and the opportunities for a product or service. In recent years, we have seen a tendency of various services converging to the ubiquitous Internet Protocol based networks. Besides traditional Internet applications such as web browsing, email, file transferring, and so forth, new applications have been developed to replace old communication networks. IPTV is one of the solutions. In the future, we expect a single network, the IP network, to provide services that have been carried by different networks today. For finding some important effects of a video based technology market web site on internet, we determine to apply a questionnaire on university students. Recently some researches shows that in Turkey the age of people 20 to 24 use internet when they buy some electronic devices such as cell phones, computers, etc. In questionnaire there are ten categorized questions to evaluate the effects of IPTV when shopping. There were selected 30 students who are filling the question form after watching an IPTV channel video for 10 minutes. This sample IPTV channel is “buy.com”, it look like an e-commerce site with an integrated IPTV channel on. The questionnaire for the survey is constructed by using the Likert scale that is a bipolar scaling method used to measure either positive or negative response to a statement (Likert, R) it is a common system that is used is the surveys. By following the Likert Scale “the respondents are asked to indicate their degree of agreement with the statement or any kind of subjective or objective evaluation of the statement. Traditionally a five-point scale is used under this methodology”. For this study also the five point scale system is used and the respondents were asked to express their opinions about the given statement by picking the answer from the given 5 options: “Strongly disagree, Disagree, Neither agree Nor disagree, Agree and Strongly agree”. These points were also rates from 1-5 (Strongly disagree, Disagree, Neither disagree Nor agree, Agree, Strongly agree). On the basis of the data gathered from the questionnaire some results are drawn in order to get the figures and graphical representation of the study results that can demonstrate the outcomes of the research clearly.Keywords: IPTV, internet marketing, online, e-commerce, video based technology
Procedia PDF Downloads 2321738 Contact Zones and Fashion Hubs: From Circular Economy to Circular Neighbourhoods
Authors: Tiziana Ferrero-Regis, Marissa Lindquist
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Circular Economy (CE) is increasingly seen as the reorganisation of production and consumption, and cities are acknowledged as the sources of many ecological and social problems; at the same time, they can be re-imagined through an ecologically and socially resilient future. The concept of the CE has received pointed critiques for its techno-deterministic orientation, focus on science and transformation by the policy. At the heart of our local re-imagining of the CE into circularity through contact zones there is the acknowledgment of collective, spontaneous and shared imaginations of alternative and sustainable futures through the creation of networks of community initiatives that are transformative, creating opportunities that simultaneously make cities rich and enrich humans. This paper presents a mapping project of the fashion and textile ecosystem in Brisbane, Queensland, Australia. Brisbane is currently the most aspirational city in Australia, as its population growth rate is the highest in the country. Yet, Brisbane is considered the least “fashion city” in the country. In contrast, the project revealed a greatly enhanced picture of distinct fashion and textile clusters across greater Brisbane and the adjacency of key services that may act to consolidate CE community contact zones. Clusters to the north of Brisbane and several locales to the south are zones of a greater mix between public/social amenities, walkable zones and local transport networks with educational precincts, community hubs, concentration of small enterprises, designers, artisans and waste recovery centers that will help to establish knowledge of key infrastructure networks that will support enmeshing these zones together. The paper presents two case studies of independent designers who work on new and re-designed clothing through recovering pre-consumer textiles and that operate from within creative precincts. The first case is designer Nelson Molloy, who recently returned to the inner city suburb of West End with their Chasing Zero Design project. The area was known in the 1980s and 1990s for its alternative lifestyle with creative independent production, thrifty clothing shops, alternative fashion and a socialist agenda. After 30 years of progressive gentrification of the suburb, which has dislocated many of the artists, designers and artisans, West End is seeing the return and amplification of clusters of artisans, artists, designers and architects. The other case study is Practice Studio, located in a new zone of creative growth, Bowen Hills, north of the CBD. Practice Studio combines retail with a workroom, offers repair and remaking services, becoming a point of reference for young and emerging Australian designers and artists. The paper demonstrates the spatial politics of the CE and the way in which new cultural capital is produced thanks to cultural specificities and resources. It argues for the recognition of contact zones that are created by local actors, communities and knowledge networks, whose grass-roots agency is fundamental for the co-production of CE’s systems of local governance.Keywords: contact zones, circular citities, fashion and textiles, circular neighbourhoods, australia
Procedia PDF Downloads 891737 How Virtualization, Decentralization, and Network-Building Change the Manufacturing Landscape: An Industry 4.0 Perspective
Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg
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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.Keywords: Industry 4.0., mass customization, production networks, virtual process-chain
Procedia PDF Downloads 2671736 Analysis of Storm Flood in Typical Sewer Networks in High Mountain Watersheds of Colombia Based on SWMM
Authors: J. C. Hoyos, J. Zambrano Nájera
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Increasing urbanization has led to changes in the natural dynamics of watersheds, causing problems such as increases in volumes of runoff, peak flow rates, and flow rates so that the risk of storm flooding increases. Sewerage networks designed 30 – 40 years ago don’t account for these increases in flow volumes and velocities. Besides, Andean cities with high slopes worsen the problem because velocities are even higher not allowing sewerage network work and causing cities less resilient to landscape changes and climatic change. In Latin America, especially Colombia, this is a major problem because urban population at late XX century was more than 70% is in urban areas increasing approximately in 790% in 1940-1990 period. Thus, it becomes very important to study how changes in hydrological behavior affect hydraulic capacity of sewerage networks in Andean Urban Watersheds. This research aims to determine the impact of urbanization in high-sloped urban watersheds in its hydrology. To this end it will be used as study area experimental urban watershed named Palogrande-San Luis watershed, located in the city of Manizales, Colombia. Manizales is a city in central western Colombia, located in Colombian Central Mountain Range (part of Los Andes Mountains) with an abrupt topography (average altitude is 2.153 m). The climate in Manizales is quite uniform, but due to its high altitude it presents high precipitations (1.545 mm/year average) with high humidity (83% average). Behavior of the current sewerage network will be reviewed by the hydraulic model SWMM (Storm Water Management Model). Based on SWMM the hydrological response of urban watershed selected will be evaluated under the design storm with different frequencies in the region, such as drainage effect and water-logging, overland flow on roads, etc. Cartographic information was obtained from a Geographic Information System (GIS) thematic maps of the Institute of Environmental Studies of the Universidad Nacional de Colombia and the utility Aguas de Manizales S.A. Rainfall and streamflow data is obtained from 4 rain gages and 1 stream gages. This information will allow determining critical issues on drainage systems design in urban watershed with very high slopes, and which practices will be discarded o recommended.Keywords: land cover changes, storm sewer system, urban hydrology, urban planning
Procedia PDF Downloads 2471735 Visual Simulation for the Relationship of Urban Fabric
Authors: Ting-Yu Lin, Han-Liang Lin
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This article is about the urban form of visualization by Cityengine. City is composed of different domains, and each domain has its own fabric because of arrangement. For example, a neighborhood unit contains fabrics such as schools, street networks, residential and commercial spaces. Therefore, studying urban morphology can help us understand the urban form in planning process. Streets, plots, and buildings seem as urban fabrics, and they configure urban form. Traditionally, urban morphology usually discussed single parameter, which is building type, ignoring other parameters such as streets and plots. However, urban space is three-dimensional, instead of two-dimensional. People perceive urban space by their visualization. Therefore, using visualization can fill the gap between two dimensions and three dimensions. Hence, the study of urban morphology will strengthen the understanding of whole appearance of a city. Cityengine is a software which can edit, analyze and monitor the data and visualize the result for GIS, a common tool to analyze data and display the map for urban plan and urban design. Cityengine can parameterize the data of streets, plots and building types and visualize the result in three-dimensional way. The research will reappear the real urban form by visualizing. We can know whether the urban form can be parameterized and the parameterized result can match the real urban form. Then, visualizing the result by software in three dimension to analyze the rule of urban form. There will be three stages of the research. It will start with a field survey of Tainan East District in Taiwan to conclude the relationships between urban fabrics of street networks, plots and building types. Second, to visualize the relationship, it will turn the relationship into codes which Cityengine can read. Last, Cityengine will automatically display the result by visualizing.Keywords: Cityengine, urban fabric, urban morphology, visual simulation
Procedia PDF Downloads 2851734 The Impact of Quality Cost on Revenue Sharing in Supply Chain Management
Authors: Fayza M. Obied-Allah
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Customer’ needs, quality, and value creation while reducing costs through supply chain management provides challenges and opportunities for companies and researchers. In the light of these challenges, modern ideas must contribute to counter these challenges and exploit opportunities. Perhaps this paper will be one of these contributions. This paper discusses the impact of the quality cost on revenue sharing as a most important incentive to configure business networks. No doubt that the costs directly affect the size of income generated by a business network, so this paper investigates the impact of quality costs on business networks revenue, and their impact on the decision to participate the revenue among the companies in the supply chain. This paper develops the quality cost approach to align with the modern era, the developed model includes five categories besides the well-known four categories (namely prevention costs, appraisal costs, internal failure costs, and external failure costs), a new category has been developed in this research as a new vision of the relationship between quality costs and innovations of industry. This new category is Recycle Cost. This paper is organized into six sections, Section I shows quality costs overview in the supply chain. Section II discusses revenue sharing between the parties in supply chain. Section III investigates the impact of quality costs in revenue sharing decision between partners in supply chain. The fourth section includes survey study and presents statistical results. Section V discusses the results and shows future opportunities for research. Finally, Section VI summarizes the theoretical and practical results of this paper.Keywords: quality cost, recycle cost, revenue sharing, supply chain management
Procedia PDF Downloads 4311733 Social Network Roles in Organizations: Influencers, Bridges, and Soloists
Authors: Sofia Dokuka, Liz Lockhart, Alex Furman
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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.Keywords: organizational network analysis, social roles, influencer, bridge, soloist
Procedia PDF Downloads 93