Electrical and Computer Engineering Faculty Research and Publications

Permanent URI for this collectionhttps://hdl.handle.net/2097/4254

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Open Access
Understanding the survival of Zika virus in a vector interconnected sexual contact network
(2019-05-10) Ferdousi, Tanvir; Cohnstaedt, Lee W.; McVey, D. Scott; Scoglio, Caterina M.
The recent outbreaks of the insect-vectored Zika virus have demonstrated its potential to be sexually transmitted, which complicates modeling and our understanding of disease dynamics. Autochthonous outbreaks in the US mainland may be a consequence of both modes of transmission, which affect the outbreak size, duration, and virus persistence. We propose a novel individual-based interconnected network model that incorporates both insect-vectored and sexual transmission of this pathogen. This model interconnects a homogeneous mosquito vector population with a heterogeneous human host contact network. The model incorporates the seasonal variation of mosquito abundance and characterizes host dynamics based on age group and gender in order to produce realistic projections. We use a sexual contact network which is generated on the basis of real world sexual behavior data. Our findings suggest that for a high relative transmissibility of asymptomatic hosts, Zika virus shows a high probability of sustaining in the human population for up to 3 months without the presence of mosquito vectors. Zika outbreaks are strongly affected by the large proportion of asymptomatic individuals and their relative transmissibility. The outbreak size is also affected by the time of the year when the pathogen is introduced. Although sexual transmission has a relatively low contribution in determining the epidemic size, it plays a role in sustaining the epidemic and creating potential endemic scenarios.
Open Access
A spatio-temporal individual-based network framework for West Nile virus in the USA: Spreading pattern of West Nile virus
(2019-03-13) Moon, Sifat A.; Cohnstaedt, Lee W.; McVey, D. Scott; Scoglio, Caterina M.
West Nile virus (WNV)—a mosquito-borne arbovirus—entered the USA through New York City in 1999 and spread to the contiguous USA within three years while transitioning from epidemic outbreaks to endemic transmission. The virus is transmitted by vector competent mosquitoes and maintained in the avian populations. WNV spatial distribution is mainly determined by the movement of residential and migratory avian populations. We developed an individual-level heterogeneous network framework across the USA with the goal of understanding the long-range spatial distribution of WNV. To this end, we proposed three distance dispersal kernels model: 1) exponential—short-range dispersal, 2) power-law—long-range dispersal in all directions, and 3) power-law biased by flyway direction —long-range dispersal only along established migratory routes. To select the appropriate dispersal kernel we used the human case data and adopted a model selection framework based on approximate Bayesian computation with sequential Monte Carlo sampling (ABC-SMC). From estimated parameters, we find that the power-law biased by flyway direction kernel is the best kernel to fit WNV human case data, supporting the hypothesis of long-range WNV transmission is mainly along the migratory bird flyways. Through extensive simulation from 2014 to 2016, we proposed and tested hypothetical mitigation strategies and found that mosquito population reduction in the infected states and neighboring states is potentially cost-effective.
Open Access
Estimation of swine movement network at farm level in the US from the Census of Agriculture data
(2019-04-17) Moon, Sifat A.; Ferdousi, Tanvir; Self, Adrian; Scoglio, Caterina M.
Swine movement networks among farms/operations are an important source of information to understand and prevent the spread of diseases, nearly nonexistent in the United States. An understanding of the movement networks can help the policymakers in planning effective disease control measures. The objectives of this work are: (1) estimate swine movement probabilities at the county level from comprehensive anonymous inventory and sales data published by the United States Department of Agriculture - National Agriculture Statistics Service database, (2) develop a network based on those estimated probabilities, and (3) analyze that network using network science metrics. First, we use a probabilistic approach based on the maximum information entropy method to estimate the movement probabilities among different swine populations. Then, we create a swine movement network using the estimated probabilities for the counties of the central agricultural district of Iowa. The analysis of this network has found evidence of the small-world phenomenon. Our study suggests that the US swine industry may be vulnerable to infectious disease outbreaks because of the small-world structure of its movement network. Our system is easily adaptable to estimate movement networks for other sets of data, farm animal production systems, and geographic regions.
Open Access
Performance Comparison for Ballistocardiogram Peak Detection Methods
(2019) Suliman, Ahmad; Carlson, Charles; Ade, Carl J.; Warren, Steve; Thompson, David E.
A number of research groups have proposed methods for ballistocardiogram (BCG) peak detection toward the identification of individual cardiac cycles. However, objective comparisons of these proposed methods are lacking. This paper, therefore, conducts a systematic and objective performance evaluation and comparison of several of these approaches. Five peak-detection methods (three replicated from the literature and two adapted from code provided by the methods' authors) are compared using data from 30 volunteers. A basic cross-correlation approach was also included as a sixth method. Two high-performing methods were identified: the method proposed by Sadek et al. and the method proposed by Brüser et al. The first achieved the highest average peak-detection rate of 94%, the lowest average false alarm rate of 0.0552 false alarms per second, and a relatively small mean absolute error between the real and detected peaks: 0.0175 seconds. The second method achieved the lowest mean absolute error of 0.0088 seconds between the real and detected peaks, an average peak-detection success rate of 89%, and 0.0766 false alarms per second. All metrics are averaged across participants.
Open Access
Understanding the role of sexual transmission in the spread of ZIKA virus using an individual-based interconnected population model
Ferdousi, Tanvir; Cohnstaedt, Lee W.; McVey, D. S.; Scoglio, Caterina M.; tanvirf; caterina; Ferdousi, Tanvir; Scoglio, Caterina
Zika virus has affected the world as a long-term threat. Modeling its transmission is important in order to facilitate forecasts and control measures. We propose a novel node-based interconnected population model to simulate both vectored and sexual transmission of Zika virus. Using a sexual contact network, we incorporate heterogeneous mixing in the host population with stochastic transmission for realistic predictions. We also incorporate climatic variations in our model, which affect the mosquito vector population and consequently the arbovirus transmission. We perform extensive simulations to understand the effects of sexual transmission rate and network topology on the spreading of infections. Sexual transmission contributes to the epidemic spread and under certain conditions, can sustain it up to several months without vectors. This can potentially lead to recurrences once the mosquitoes overwinter. We also find that sexual transmission can have a stronger effect when vectored transmission is relatively weaker due to climatic conditions. Our results show that vectored and sexual transmission affect the disease dynamics differently.
Open Access
Double-Sided Energy Auction in Microgrid: Equilibrium under Price Anticipation
Faqiry, M. Nazif; Das, Sanjoy; sdas; Das, Sanjoy
This paper investigates the problem of proportionally fair double-sided energy auction involving buying and selling agents. The grid is assumed to be operating under islanded mode. A distributed auction algorithm that can be implemented by an aggregator, as well as a possible approach by which the agents may approximate price anticipation is considered. Equilibrium conditions arising due to price anticipation is analyzed. A modified auction to mitigate the resulting loss in efficiency due to such behavior is suggested. This modified auction allows the aggregate social welfare of the agents to be arbitrarily close to that attainable with price taking agents. Next, equilibrium conditions when the aggregator collects a surcharge price per unit of energy traded is examined. A bi-objective optimization problem is identified that takes into account both the agents' social welfare as well as the aggregator's revenue from the surcharge. The results of extensive simulations, which corroborate the theoretical analysis, are reported. © 2013 IEEE.
Open Access
Network clustering and community detection using modulus of families of loops
(2017-01-17) Shakeri, Heman; Poggi-Corradini, Pietro; Albin, Nathan; Scoglio, Caterina; caterina; pietro; albin; Scoglio, Caterina; Poggi-Corradini, Pietro; Albin, Nathan
We study the structure of loops in networks using the notion of modulus of loop families. We introduce an alternate measure of network clustering by quantifying the richness of families of (simple) loops. Modulus tries to minimize the expected overlap among loops by spreading the expected link usage optimally. We propose weighting networks using these expected link usages to improve classical community detection algorithms. We show that the proposed method enhances the performance of certain algorithms, such as spectral partitioning and modularity maximization heuristics, on standard benchmarks.
Open Access
A Multiband OFDMA Heterogeneous Network for Millimeter Wave 5G Wireless Applications
(2016-09-22) Niknam, S.; Nasir, A. A.; Mehrpouyan, H.; Natarajan, Balasubramaniam; bala; Natarajan, Balasubramaniam
Emerging fifth generation (5G) wireless networks require massive bandwidth in higher frequency bands, extreme network densities, and flexibility of supporting multiple wireless technologies in order to provide higher data rates and seamless coverage. It is expected that the utilization of the large bandwidth in the millimeter-wave (mmWave) band and deployment of heterogeneous networks (HetNets) will help address the data rate requirements of 5G networks. However, high pathloss and shadowing in the mmWave frequency band, strong interference in the HetNets due to massive network densification, and coordination of various air interfaces are challenges that must be addressed. In this paper, we consider a relay based multiband orthogonal frequency division multiple access HetNet in which mmWave small cells are deployed within the service area of macro cells. In particular, we attempt to exploit the distinct propagation characteristics of mmWave bands (i.e., 60 GHz-the V-band and 70-80 GHz the E-band) and the long term evolution band to maximize overall data rate of the network via efficient resource allocation. The problem is solved using a modified dual decomposition approach and then a low complexity greedy solution based on the iterative activity selection algorithm is presented. Simulation results show that the proposed approach outperforms conventional schemes.
Open Access
Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies
(2016-09-23) Scoglio, Caterina M.; Bosca, C.; Riad, M. H.; Sahneh, Faryad D.; Britch, S. C.; Cohnstaedt, L. W.; Linthicum, K. J.; caterina; faryad; Scoglio, Caterina; Sahneh, Faryad D.
Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States.
Open Access
Student proposals for design projects to aid children with severe disabilities
(2016-06-26) Warren, Steven; swarren; Warren, Steven
Children with severe disabilities have unique individual needs. Technology-based designs intended to quantify the well-being of these children or assist them with learning or activities of daily living are often by nature "one of" designs tightly matched to these needs. For children with severe autism, such designs must be incorporated into their environments in unobtrusive ways to avoid upsetting or distracting these children. This design space and its affiliated challenges offer a rich environment for engineering students to exercise their design creativity. This paper presents an end-of-semester exercise for a Kansas State University Introduction to Biomedical Engineering class, where students propose senior-design projects geared toward children with severe disabilities. The goal of the exercise is to integrate concepts related to biomedical devices, design factors, care delivery environments, and assistive technology into a proposed design with clear practical benefit that can be implemented in prototype form by a senior design team over the span of about two semesters. The deliverable for the design exercise is a four-page paper in two-column IEEE format that adheres to a pre-specified structure. To focus these design-project ideas, students are asked to offer their thoughts within the framework of needs specified by clinical staff at Heartspring in Wichita, KS, a facility that serves severely disabled children, where nearly all of the full-time residents are autistic, and most are nonverbal. In addition to the educational benefits offered by this experience, the author's intent is to help spur ideas for new senior design projects that can be supported with resources from existing NSF-funded grants which provide equipment and materials for such endeavors. Six semesters worth of design ideas are presented here, along with the results of assessment rubrics applied to the final papers. The class is populated by students from various departments within the Kansas State University College of Engineering, so design proposals are varied and incorporate low-level to system-level solutions. Some of these design ideas have been adopted by design teams, whereas others await attention. © American Society for Engineering Education, 2016.
Open Access
Maximizing algebraic connectivity in interconnected networks
(2016-03-21) Shakeri, Heman; Albin, Nathan; Sahneh, Faryad D.; Poggi-Corradini, Pietro; Scoglio, Caterina; faryad; albin; pietro; caterina
Algebraic connectivity, the second eigenvalue of the Laplacian matrix, is a measure of node and link connectivity on networks. When studying interconnected networks it is useful to consider a multiplex model, where the component networks operate together with interlayer links among them. In order to have a well-connected multilayer structure, it is necessary to optimally design these interlayer links considering realistic constraints. In this work, we solve the problem of finding an optimal weight distribution for one-to-one interlayer links under budget constraint. We show that for the special multiplex configurations with identical layers, the uniform weight distribution is always optimal. On the other hand, when the two layers are arbitrary, increasing the budget reveals the existence of two different regimes. Up to a certain threshold budget, the second eigenvalue of the supra-Laplacian is simple, the optimal weight distribution is uniform, and the Fiedler vector is constant on each layer. Increasing the budget past the threshold, the optimal weight distribution can be nonuniform. The interesting consequence of this result is that there is no need to solve the optimization problem when the available budget is less than the threshold, which can be easily found analytically.
Open Access
Exact coupling threshold for structural transition reveals diversified behaviors in interconnected networks
(2015-10-05) Sahneh, Faryad D.; Scoglio, Caterina; Van Mieghem, P.; faryad; caterina
Open Access
Ultralow Power Energy Harvesting Body Area Network Design: A Case Study
(2015-10-27) Zheng, C. Y.; Kuhn, William B.; Natarajan, Balasubramaniam; wkuhn; bala
Open Access
Robustness surfaces of complex networks
(2014-11-25) Manzano, Marc; Sahneh, Faryad D.; Scoglio, Caterina M.; Calle, Eusebi; Marzo Lazaro, Jose Luis; faryad; caterina; jlmarzol
Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.
Open Access
Performance measurement for brain-computer or brain-machine interfaces: a tutorial
(2014-05-19) Thompson, David E.; Quitadamo, Lucia R.; Mainardi, Luca; Laghari, Khalil ur Rehman; Gao, Shangkai; Kindermans, Pieter-Jan; Simeral, John D.; Fazel-Rezai, Reza; Matteucci, Matteo; Falk, Tiago H.; Bianchi, Luigi; Chestek, Cynthia A.; Huggins, Jane E.; davet
Objective. Brain–computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. Approach. A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop. Main results. Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories. Significance. Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.
Open Access
Using GENI for experimental evaluation of Software Defined Networking in smart grids
(2014-07-22) Sydney, Ali; Ochs, David S.; Scoglio, Caterina M.; Gruenbacher, Don M.; Miller, Ruth D.; caterina; grue; rdmiller
The North American Electric Reliability Corporation (NERC) envisions a smart grid that aggressively explores advance communication network solutions to facilitate real-time monitoring and dynamic control of the bulk electric power system. At the distribution level, the smart grid integrates renewable generation and energy storage mechanisms to improve the reliability of the grid. Furthermore, dynamic pricing and demand management provide customers an avenue to interact with the power system to determine the electricity usage that best satisfies their lifestyle. At the transmission level, efficient communication and a highly automated architecture provide visibility in the power system and as a result, faults are mitigated faster than they can propagate. However, such higher levels of reliability and efficiency rest on the supporting communication infrastructure. To date, utility companies are moving towards Multiprotocol Label Switching (MPLS) because it supports traffic engineering and virtual private networks (VPNs). Furthermore, it provides Quality of Service (QoS) guarantees and fail-over mechanisms in addition to meeting the requirement of non-routability as stipulated by NERC. However, these benefits come at a cost for the infrastructure that supports the fullMPLS specification. With this realization and given a two week implementation and deployment window in GENI, we explore the modularity and flexibility provided by the low cost OpenFlow Software Defined Networking (SDN) solution. In particular, we use OpenFlow to provide 1.) automatic fail-over mechanisms, 2.) a load balancing, and 3.) Quality of Service guarantees: all essential mechanisms for smart grid networks.
Open Access
ADABOOST+: an ensemble learning approach for estimating weather-related outages in distribution systems
(2013-09-24) Kankanala, Padmavathy; Das, Sanjoy; Pahwa, Anil; sdas; pahwa
Environmental factors, such as weather, trees, and animals, are major causes of power outages in electric utility distribution systems. Of these factors, wind and lightning have the most significant impacts. The objective of this paper is to investigate models to estimate wind and lighting related outages. Such estimation models hold the potential for lowering operational costs and reducing customer downtime. This paper proposes an ensemble learning approach based on a boosting algorithm, AdaBoost+, for estimation of weather-caused power outages. Effectiveness of the model is evaluated using actual data, which comprised of weather data and recorded outages for four cities of different sizes in Kansas. The proposed ensemble model is compared with previously presented regression, neural network, and mixture of experts models. The results clearly show that AdaBoost+ estimates outages with greater accuracy than the other models for all four data sets.
Open Access
Abruptness of cascade failures in power grids
(2014-01-15) Pahwa, Sakshi; Scoglio, Caterina M.; Scala, Antonio; sakship; caterina
Electric power-systems are one of the most important critical infrastructures. In recent years, they have been exposed to extreme stress due to the increasing demand, the introduction of distributed renewable energy sources, and the development of extensive interconnections. We investigate the phenomenon of abrupt breakdown of an electric power-system under two scenarios: load growth (mimicking the ever-increasing customer demand) and power fluctuations (mimicking the effects of renewable sources). Our results on real, realistic and synthetic networks indicate that increasing the system size causes breakdowns to become more abrupt; in fact, mapping the system to a solvable statistical-physics model indicates the occurrence of a first order transition in the large size limit. Such an enhancement for the systemic risk failures (black-outs) with increasing network size is an effect that should be considered in the current projects aiming to integrate national power-grids into “super-grids”.
Open Access
A novel single-phase inverter with D-STATCOM capability for wind applications
(2013-08-20) Sotoodeh, Pedram; Miller, Ruth Douglas; rdmiller
The modular multilevel converter (MMC) is an attractive topology for HVDC/FACTS systems. In this paper a new single-phase MMC-based D-STATCOM inverter for grid connection is proposed. The proposed inverter is designed for grid-connected wind turbines in the small- to mid-sized (10kW-20kW) range using the most advanced multi-level inverter topology. The proposed MMC D-STATCOM inverter controls the DC link voltage as well as the active and reactive power transferred between the renewable energy source, specifically wind turbine, and the grid in order to regulate the power factor (PF) of the grid regardless of the input active power from wind turbine. The goal of this paper is to present a new inverter with FACTS capability in a single unit without any additional cost. The 5-level D-STATCOM inverter is simulated and the results are presented to verify the operation of the proposed system. The simulation studies are carried out in the MATLAB/Simulink environment. To validate the simulation results, an experimental configuration of a 5-Level MMC D-STATCOM inverter has been built and tested.
Open Access
Optimal intentional islanding to enhance the robustness of power grid networks
(2013-09-01) Pahwa, Sakshi; Youssef, M.; Schumm, Phillip R. B.; Scoglio, Caterina M.; Schulz, Noel N.; caterina; noels; sakship
Intentional islanding of a power system can be an emergency response for isolating failures that might propagate and lead to major disturbances. Some of the islanding techniques suggested previously do not consider the power flow model; others are designed to minimize load shedding only within the islands. Often these techniques are computationally expensive. We aim to find approaches to partition power grids into islands to minimize the load shedding not only in the region where the failures start, but also in the topological complement of the region. We propose a new constraint programming formulation for optimal islanding in power grid networks. This technique works efficiently for small networks but becomes expensive as size increases. To address the scalability problem, we propose two grid partitioning methods based on modularity, properly modified to take into account the power flow model. They are modifications of the Fast Greedy algorithm and the Bloom algorithm, and are polynomial in running time. We tested these methods on the available IEEE test systems. The Bloom type method is faster than the Fast Greedy type, and can potentially provide results in networks with thousands of nodes. Our methods provide solutions which retain at least 40–50% of the system load. Overall, our methods efficiently balance load shedding and scalability.