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Full-Text Articles in Engineering

Solar Thermal Dish Storage System Project: A Novel Receiver Experiment Model, Forrest Osborn Jan 2021

Solar Thermal Dish Storage System Project: A Novel Receiver Experiment Model, Forrest Osborn

Undergraduate Research Posters 2021

Solar energy utilizes sunlight to generate electricity but inefficiencies in energy storage limits this technology. Transferring sunlight into thermal energy can contribute to solve this problem. The goal of this study was to determine feasibility of a heat exchanger to be used with an existing solar parabolic dish. For this purpose, a heat gun was used to measure the thermal properties of a novel receiver design. This system was used to analyze different receiver configurations for a copper tube containing water as a heat transfer fluid. The inlet and outlet water temperatures and the effect of HTF flow rate were …

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Nickel-Iron Alloy Nanoparticle Characteristics Pre- And Post-Reaction With Orange G, Shelby L. Foster, Prashant Acharya, Mojtaba Abolhassani, Skylar Watson, Sheldon Shinn, Lauren F. Greenlee Jan 2021

Nickel-Iron Alloy Nanoparticle Characteristics Pre- And Post-Reaction With Orange G, Shelby L. Foster, Prashant Acharya, Mojtaba Abolhassani, Skylar Watson, Sheldon Shinn, Lauren F. Greenlee

Chemical Engineering Faculty Publications and Presentations

Bimetallic nanoparticles comprised of iron and nickel were synthesized, characterized, and evaluated to optimize the ideal metal ratio for azo dye removal from water systems. Results show that changing the molar ratio of nickel to iron caused different removal rates, as well as the extent of overall elimination of azo dye from water. Lower molar ratios, from Ni1Fe10 to Ni2.5Fe10, exhibited a higher removal efficiency of 80–99%. Higher concentrations of Ni in the catalyst, from Ni3Fe10 to Ni5Fe10 , resulted in 70–90% removal. The lower molar ratios …

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Society Of Women Engineers: Central Illinois Award, Joyce Li '22 Jan 2021

Society Of Women Engineers: Central Illinois Award, Joyce Li '22

Distinguished Student Work

A healthy nation is a wealthy nation. The well-being of the citizens of the United States lies in the hands of, frankly, themselves. The activists who promote progress and prosperity. The engineers who create that which have never been. And lastly, the medical professionals that allocate years of their life to study, treat, and improve the physical well-being of their populations. Yet as America progresses with time, our healthcare system is failing the very people it was meant to serve: the public. More than 82 million people in this country have inadequate or no health insurance. As this number rises …

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Design, Development And Temporal Evaluation Of An Mri-Compatible In-Vitro Circulation Model Using A Compliant Aaa Phantom, Mirunalini Thirugnanasambandam, Tejas Canchi, Senol Piskin, Christof Karmonik, Ethan Kung, Prahlad Menon, Stephanie Avril, Ender A. Finol Jan 2021

Design, Development And Temporal Evaluation Of An Mri-Compatible In-Vitro Circulation Model Using A Compliant Aaa Phantom, Mirunalini Thirugnanasambandam, Tejas Canchi, Senol Piskin, Christof Karmonik, Ethan Kung, Prahlad Menon, Stephanie Avril, Ender A. Finol

Publications

Biomechanical characterization of abdominal aortic aneurysms (AAA) has become commonplace in rupture risk assessment studies. However, its translation to the clinic has been greatly limited due to the complexity associated with its tools and their implementation. The unattainability of patient-specific tissue properties leads to the use of generalized population-averaged material models in finite element analyses, which adds a degree of uncertainty to the wall mechanics quantification. In addition, computational fluid dynamics modeling of AAA typically lacks the patient-specific inflow and outflow boundary conditions that should be obtained by non-standard of care clinical imaging. An alternative approach for analyzing AAA flow …

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Computational Modeling For Decision-Making Under Climate Change Uncertainty: Reservoir Simulation Game, Julianne Quinn Jan 2021

Computational Modeling For Decision-Making Under Climate Change Uncertainty: Reservoir Simulation Game, Julianne Quinn

All ECSTATIC Materials

Almost every decision you make is under uncertainty. Will I need a rain jacket in the afternoon? Will they say yes if I ask them out? Is 1 hour enough time to finish this assignment? Oftentimes, we can use computational modeling to simulate different scenarios of what might happen in the future to inform what decisions are best on average, or what decisions minimize the worst case outcome. For example, you could decide what player to draft for your Fantasy Football team by simulating player performance. In this activity, we will simulate how much water to release from a dam …

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Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza Jan 2021

Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza

Browse all Theses and Dissertations

With the growing number of Unmanned Aircraft Systems, current network-centric architectures present limitations in meeting real-time and time-critical requirements. Current methods utilizing centralized off-platform processing have inherent energy inefficiencies, scalability challenges, performance concerns, and cyber vulnerabilities. In this dissertation, an adaptive, two-stage, energy-efficient, edge-centric architecture is proposed to address these limitations. A novel, edge-centric Sense-and-Avoidance architecture framework is presented, and a corresponding prototype is developed using commercial hardware to validate the proposed architecture. Instead of a network-centric approach, processing is distributed at the logical edge of the sensors, and organized as Detection and Classification Subsystems. Classical machine vision algorithms are …

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Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan Jan 2021

Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan

Browse all Theses and Dissertations

Renewable and clean energy has been the driving force behind the booming storage industry. The need for producing energy from clean and quickly replenishable energy sources has never been as high as it is now. However, renewable energy only supplies a little over a quarter of the world’s electricity needs and much less of the world’s total energy requirements. One reason is the intermittent nature of renewable energy. Inexpensive and convenient storage technologies are required to solve this issue. It is believed that batteries offer the most viable solution to conquer the problem of renewable energy intermittency. To aid the …

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Bridge Damage Identification Using Deep Learning-Based Convolutional Neural Networks (Cnns), Sandeep Sony Jan 2021

Bridge Damage Identification Using Deep Learning-Based Convolutional Neural Networks (Cnns), Sandeep Sony

Civil and Environmental Engineering Publications

In this paper, a novel method is proposed based on a windowed-one-dimensional convolutional neural network for multiclass damage detection using acceleration responses. The data is pre-processed and augmented by extracting samples of windows of the original acceleration time series. 1D CNN is developed to classify the signals in multiple classes. The damage is detected if the predicted classification is one of the indicated damage levels. The damage is quantified using the predicted class probabilities. Various signals from the accelerometers are provided as input to the 1D CNN model, and the resulting class probabilities are used to identify the location of …

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Characterization & Calibration Of Foresight Ice, Hareem Nisar, Terry M Peters, Elvis C.S. Chen Jan 2021

Characterization & Calibration Of Foresight Ice, Hareem Nisar, Terry M Peters, Elvis C.S. Chen

Robarts Imaging Publications

No abstract provided.

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Real-Time Voluntary Motion Prediction And Parkinson's Tremor Reduction Using Deep Neural Networks, Anas Ibrahim, Yue Zhou, Mary E. Jenkins, Ana Luisa Trejos, Michael D. Naish Jan 2021

Real-Time Voluntary Motion Prediction And Parkinson's Tremor Reduction Using Deep Neural Networks, Anas Ibrahim, Yue Zhou, Mary E. Jenkins, Ana Luisa Trejos, Michael D. Naish

Mechanical and Materials Engineering Publications

Wearable tremor suppression devices (WTSD) have been considered as a viable solution to manage parkinsonian tremor. WTSDs showed their ability to improve the quality of life of individuals suffering from parkinsonian tremor, by helping them to perform activities of daily living (ADL). Since parkinsonian tremor has been shown to be nonstationary, nonlinear, and stochastic in nature, the performance of the tremor models used by WTSDs is affected by their inability to adapt to the nonlinear behaviour of tremor. Another drawback that the models have is their limitation to estimate or predict one step ahead, which introduces delay when used in …

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A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz Jan 2021

A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz

Electrical and Computer Engineering Publications

With recent advances in non-contact sensing technology such as cameras, unmanned aerial and ground vehicles, the structural health monitoring (SHM) community has witnessed a prominent growth in deep learning-based condition assessment techniques of structural systems. These deep learning methods rely primarily on convolutional neural networks (CNNs). The CNN networks are trained using a large number of datasets for various types of damage and anomaly detection and post-disaster reconnaissance. The trained networks are then utilized to analyze newer data to detect the type and severity of the damage, enhancing the capabilities of non-contact sensors in developing autonomous SHM systems. In recent …

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Transfer Learning By Similarity Centred Architecture Evolution For Multiple Residential Load Forecasting, Santiago Gomez-Rosero, Miriam A M Capretz, Syed Mir Jan 2021

Transfer Learning By Similarity Centred Architecture Evolution For Multiple Residential Load Forecasting, Santiago Gomez-Rosero, Miriam A M Capretz, Syed Mir

Electrical and Computer Engineering Publications

The development from traditional low voltage grids to smart systems has become extensive and adopted worldwide. Expanding the demand response program to cover the residential sector raises a wide range of challenges. Short term load forecasting for residential consumers in a neighbourhood could lead to a better understanding of low voltage consumption behaviour. Nevertheless, users with similar characteristics can present diversity in consumption patterns. Consequently, transfer learning methods have become a useful tool to tackle differences among residential time series. This paper proposes a method combining evolutionary algorithms for neural architecture search with transfer learning to perform short term load …

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Deep Learning For High-Impedance Fault Detection: Convolutional Autoencoders, Khushwant Rai, Firouz Badrkhani Ajaei, Farnam Hojatpanah, Katarina Grolinger Jan 2021

Deep Learning For High-Impedance Fault Detection: Convolutional Autoencoders, Khushwant Rai, Firouz Badrkhani Ajaei, Farnam Hojatpanah, Katarina Grolinger

Electrical and Computer Engineering Publications

High-impedance faults (HIF) are difficult to detect because of their low current amplitude and highly diverse characteristics. In recent years, machine learning (ML) has been gaining popularity in HIF detection because ML techniques learn patterns from data and successfully detect HIFs. However, as these methods are based on supervised learning, they fail to reliably detect any scenario, fault or non-fault, not present in the training data. Consequently, this paper takes advantage of unsupervised learning and proposes a convolutional autoencoder framework for HIF detection (CAE-HIFD). Contrary to the conventional autoencoders that learn from normal behavior, the convolutional autoencoder (CAE) in CAE-HIFD …

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‘Digits’ App - Smartphone Augmented Reality For Hand Telerehabilitation, Hongdao Dong, Edward Ho, Herbert Shin, Tania Banerjee, Geoffrey Masschelein, Jacob Davidson, Sandrine De Ribaupierre, Roy Eagleson, Caitlin Symonette Jan 2021

‘Digits’ App - Smartphone Augmented Reality For Hand Telerehabilitation, Hongdao Dong, Edward Ho, Herbert Shin, Tania Banerjee, Geoffrey Masschelein, Jacob Davidson, Sandrine De Ribaupierre, Roy Eagleson, Caitlin Symonette

Electrical and Computer Engineering Publications

Hand telerehabilitation currently has limitations for accurate and remote assessment of range of motion (ROM) in small finger joints. ‘DIGITS’ application utilises the front smartphone camera to measure finger ROM in a reliable and rapid assessment protocol. Our initial beta-phase testing examined the consistency of our software measurements to in-person goniometry. 6 to 9 degrees of difference existed between the smartphone application recorded data versus the in-person measurements. This range is within acceptable 7 to 9 degree tolerance for interrater goniometry measurements. The effect of environmental factors such as hand distance, lightings and hand orientation was evaluated. The intraclass correlation …

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Micro-Ct Of The Human Ossicular Chain: Statistical Shape Modeling And Implications For Otologic Surgery, Western University, London Health Sciences Centre Jan 2021

Micro-Ct Of The Human Ossicular Chain: Statistical Shape Modeling And Implications For Otologic Surgery, Western University, London Health Sciences Centre

Electrical and Computer Engineering Publications

The ossicular chain is a middle ear structure consisting of the small incus, malleus and stapes bones, which transmit tympanic membrane vibrations caused by sound to the inner ear. Despite being shown to be highly variable in shape, there are very few morphological studies of the ossicles. The objective of this study was to use a large sample of cadaveric ossicles to create a set of three-dimensional models and study their statistical variance. Thirty-three cadaveric temporal bone samples were scanned using micro-computed tomography (μCT) and segmented. Statistical shape models (SSMs) were then made for each ossicle to demonstrate the divergence …

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Characterization, Analysis, And Application Of Wbg Power Devices For Future Power Conversion Systems, Ali Mahmoud Salman Al-Bayati Jan 2021

Characterization, Analysis, And Application Of Wbg Power Devices For Future Power Conversion Systems, Ali Mahmoud Salman Al-Bayati

Electronic Theses and Dissertations

Semiconductor power devices are the most momentous constituents of any power converter system. Fast switching, compactness, high performance and efficiency, and high temperature operation are the exacting challenges experienced by conventional silicon (Si) power device based power converters in many applications. In this dissertation, the wide bandgap (WBG) power devices are studied and used to transcend the limitations imposed by the Si power devices. It mainly focuses on characterization and analysis of the behavior of WBG power devices as well as design and development of efficient, high performance, and reliable dc–dc power converters based on WBG technology. First, using computer …

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Inventions Of Scientists, Engineers And Specialists From Different Countries In The Area Of Nanotechnologies. Part I, Leonid A. Ivanov, Li Da Xu, Elena Bokova, Aleksandr D. Ishkov, Svetlana Muminova Jan 2021

Inventions Of Scientists, Engineers And Specialists From Different Countries In The Area Of Nanotechnologies. Part I, Leonid A. Ivanov, Li Da Xu, Elena Bokova, Aleksandr D. Ishkov, Svetlana Muminova

Information Technology & Decision Sciences Faculty Publications

The article provides an abstract review of patents. The results of creative activity of scientists, engineers and specialists, including inventions in the field of nanotechnology and nanomaterials, being implemented, allow achieving a significant effect in construction, housing and community services, and related sectors of the economy. For example, the invention (A method to produce graphene-containing suspensions by means of graphite exfoliation and a device to perform it) refers to chemical and construction industries and can be used in modification of plastic lubricant, epoxy resins and concretes. The technical task of the invention is to increase efficiency of graphite exfoliation, to …

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Inventions Of Scientists, Engineers And Specialists From Different Countries In The Area Of Nanotechnologies. Part Ii, Leonid A. Ivanov, Li Da Xu, Zhanna V. Pisarenko, Qiang Wang, Petr S. Prokopiev Jan 2021

Inventions Of Scientists, Engineers And Specialists From Different Countries In The Area Of Nanotechnologies. Part Ii, Leonid A. Ivanov, Li Da Xu, Zhanna V. Pisarenko, Qiang Wang, Petr S. Prokopiev

Information Technology & Decision Sciences Faculty Publications

The article provides an abstract review of patents. The results of creative activity of scientists, engineers and specialists, including inventions in the field of nanotechnology and nanomaterials, being implemented, allow achieving a significant effect in construction, housing and community services, and related sectors of the economy. For example, the invention «Method for liquidphase synthesis of nanostructured ceramic material in the CeO2–Sm2O3 system to create a solid oxide fuel cell» can contribute to the active development of alternative, hydrogen energy. Fuel cells have a wide range of applications – from batteries in portable electronic devices to large-scale power generation and autonomous …

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Spacecraft Informatics, K. L. Yung, Lida Xu, Chris Zhang Jan 2021

Spacecraft Informatics, K. L. Yung, Lida Xu, Chris Zhang

Information Technology & Decision Sciences Faculty Publications

No abstract provided.

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2020-2021 Annual Security And Fire Report - Weatherford Campus, Southwestern Oklahoma State University Jan 2021

2020-2021 Annual Security And Fire Report - Weatherford Campus, Southwestern Oklahoma State University

ANNUAL SECURITY & FIRE REPORTS

This is the 2020-2021 Annual Security and Fire Report of the Sayre Campus by Southwestern Oklahoma State University.

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Implementation Of Microfluidic Mixers For The Optimization Of Polymeric, Gold, And Perovskite Nanomaterials Synthesis, Alexa Roberts Jan 2021

Implementation Of Microfluidic Mixers For The Optimization Of Polymeric, Gold, And Perovskite Nanomaterials Synthesis, Alexa Roberts

ETD Archive

I would like to thank Dr. Chandra Kothapalli for the opportunity to participate in this research project and the continuous guidance he has given me in all aspects of the lab work. I would like to acknowledge the entire Chemical and Biomedical Engineering Department for their assistance throughout the program, for partially supporting my tuition and stipend through teaching assistantships, and the opportunities to present and discuss my research project with other interested students and faculty. I would like to acknowledge Dr. Petru Fodor and Dr. Geyou Ao for their support as members of my defense committee. Additionally, I would …

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Calvin Engineering Lab Development, Christopher Hartemink Jan 2021

Calvin Engineering Lab Development, Christopher Hartemink

Summer Research

The project was selected was a robotic hand that has a variety of unique and interesting inputs. These demonstrations would follow and in class project of small groups designing a simple artificial hand from basic crafting materials such as cardboard, strings, straws, and glue. These interesting inputs included a mechanical measurement, muscle signals measurement, and neurological signal measurement. Effort was primarily focused on the neurological measurement in the form of electroencephalogram (EEG). The selected design was based on simple electrical components and an Arduino. This was done to show students the applications of components experienced throughout their classes at Calvin.

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Use Of Energy Consumption During Milling To Fill A Measurement Gap In Hybrid Additive Manufacturing, K. L. M. Avegnon, P. Noll, M. R. Uddin, G. Madireddy, R. Williams, A. Achuthan, M. P. Sealy Jan 2021

Use Of Energy Consumption During Milling To Fill A Measurement Gap In Hybrid Additive Manufacturing, K. L. M. Avegnon, P. Noll, M. R. Uddin, G. Madireddy, R. Williams, A. Achuthan, M. P. Sealy

Department of Mechanical and Materials Engineering: Faculty Publications

Coupling additive manufacturing (AM) with interlayer peening introduces bulk anisotropic properties within a build across several centimeters. Current methods to map high resolution anisotropy and heterogeneity are either destructive or have a limited penetration depth using a nondestructive method. An alternative pseudo-nondestructive method to map high-resolution anisotropy and heterogeneity is through energy consumption during milling. Previous research has shown energy consumption during milling correlates with surface integrity. Since surface milling of additively manufactured parts is often required for post-processing to improve dimensional accuracy, an opportunity is available to use surface milling as an alternative method to measure mechanical properties and …

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A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali Jan 2021

A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali

Department of Anthropology: Faculty Publications

Airborne light detection and ranging (LIDAR) systems allow archaeologists to capture 3D data of anthropogenic landscapes with a level of precision that permits the identification of archaeological sites in difficult to reach and inaccessible regions. These benefits have come with a deluge of LIDAR data that requires significant and costly manual labor to interpret and analyze. In order to address this challenge, researchers have explored the use of state-of-the-art automated object recognition algorithms from the field of deep learning with success. This previous research, however, has been limited to the exploration of deep learning processes that work with only 2D …

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High Mobility N-Type Field Effect Transistors Enabled By Wse2/Pdse2 Heterojunctions, Arthur Bowman Iii Jan 2021

High Mobility N-Type Field Effect Transistors Enabled By Wse2/Pdse2 Heterojunctions, Arthur Bowman Iii

Wayne State University Dissertations

Two-dimensional (2D) semiconductors such as transition metal dichalcogenides (TMDs) have emerged as a promising candidate for post-silicon electronics. Few-layer tungsten diselenide (WSe2), a well-studied TMD, has sown high hole mobility and ON/OFF ratio in field effect transistor (FET) devices. But the n-type performance of WSe2 is still quite limited by the presence of a substantial Schottky Barrier. Palladium diselenide, (PdSe2) is a newly discovered TMD that is of interest because of its high electron mobility, and moderate ON/OFF ratios. However, despite its relatively small bandgap, the n-type performance of few-layer PdSe2 FETs has also been limited by a Schottky barrier, …

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Flexure And Punching Shear Behavior Of Uhpc Elements Post-Tensioned With Unbonded Tendons, Mehmet Dogu Jan 2021

Flexure And Punching Shear Behavior Of Uhpc Elements Post-Tensioned With Unbonded Tendons, Mehmet Dogu

Wayne State University Dissertations

ABSTRACTFLEXURE AND PUNCHING SHEAR BEHAVIOR OF UHPC ELEMENTS POST-TENSIONED WITH UNBONDED TENDONS by Mehmet Dogu August 2021 Advisor: Dr. Fatmir Menkulasi Major: Civil and Environmental Engineering (Structural Engineering) Degree: Doctor of Philosophy Procedures for predicting the flexural strength, moment-curvature-deformation response, and punching shear capacity of PT UHPC elements are presented. The prediction method for flexural strength is based on a mechanics based phenomenological model. A set of equations is provided to predict strand stress at the ultimate limit state as a function of plastic hinge length. The procedure for obtaining the moment-curvature-deformation response does not rely on empiricism other than …

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Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas Jan 2021

Methods To Integrate Domain Expert User Knowledge Into Process Discovery, Jasim Alnahas

Wayne State University Dissertations

Process Mining (PM) is a new era in business development management that reinforces business process sustainability. Process Mining uses various techniques to discover the process model and identify the root cause analysis of process delays based on the event log. There are three main types of process models: procedural models, declarative models, and hybrid models. Procedural models tend to discover the main pattern of the activity flows in the process. In contrast, declarative models analyze the process behavior and express this behavior as a compact set of rules between pair of two activities. Hybrid models are a combination of procedural …

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Experimental Methods To Capture Curing Induced Effects In Adhesive Bonded Joints, Akshat Agha, Fadi Abu-Farha Jan 2021

Experimental Methods To Capture Curing Induced Effects In Adhesive Bonded Joints, Akshat Agha, Fadi Abu-Farha

Publications

The rapidly increasing use of structural adhesives, especially in the joining of automotive body structures has motivated various investigations of the effects of adhesive curing process on joints. The automotive-grade structural adhesives require heat curing, which, in the meantime, performs thermal loading on the substrates and causes undesirable effects in the joint. For example, the curing process results in complex residual stresses in the adhesive bond which are detrimental to the performance of the adhesive bond and thereby the automobile body structure, particularly the crashworthiness. To thoroughly evaluate such effects, this paper consists of two parts. The first part presents …

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An Analysis Of C/C++ Datasets For Machine Learning-Assisted Software Vulnerability Detection, Daniel Grahn, Junjie Zhang Jan 2021

An Analysis Of C/C++ Datasets For Machine Learning-Assisted Software Vulnerability Detection, Daniel Grahn, Junjie Zhang

Computer Science and Engineering Faculty Publications

As machine learning-assisted vulnerability detection research matures, it is critical to understand the datasets being used by existing papers. In this paper, we explore 7 C/C++ datasets and evaluate their suitability for machine learning-assisted vulnerability detection. We also present a new dataset, named Wild C, containing over 10.3 million individual opensource C/C++ files – a sufficiently large sample to be reasonably considered representative of typical C/C++ code. To facilitate comparison, we tokenize all of the datasets and perform the analysis at this level. We make three primary contributions. First, while all the datasets differ from our Wild C dataset, some …

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Recommending Collaborations Using Link Prediction, Nikhil Chennupati Jan 2021

Recommending Collaborations Using Link Prediction, Nikhil Chennupati

Browse all Theses and Dissertations

Link prediction in the domain of scientific collaborative networks refers to exploring and determining whether a connection between two entities in an academic network may emerge in the future. This study aims to analyze the relevance of academic collaborations and identify the factors that drive co-author relationships in a heterogeneous bibliographic network. Using topological, semantic, and graph representation learning techniques, we measure the authors' similarities w.r.t their structural and publication data to identify the reasons that promote co-authorships. Experimental results show that the proposed approach successfully infer the co-author links by identifying authors with similar research interests. Such a system …

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