Category: Publications

Technical Paper by Nathir Rawashdeh Accepted for SAE World Congress

An SAE technical paper, co-authored by Nathir Rawashdeh, assistant professor, CMH Division, College of Computing, has been accepted for publication at the WCX SAE World Congress Experience, April 21-23, 2020, in Detroit, MI.  The title of the paper is “Mobile Robot Localization Evaluations with Visual Odometry in Varying Environments using Festo-Robotino.” 

Abstract: Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e. the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry. Moreover, it discusses the outcomes of several experiments performed utilizing the Festo-Robotino robotic platform. The experiments are designed to evaluate how changing the system’s setup will affect the overall quality and performance of an autonomous driving system. Environmental effects such as ambient light, shadows, and terrain are also investigated. Finally, possible improvements including varying camera options and programming methods are discussed.

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Nathir Rawashdeh to Present Paper at Advances in Mechanical Engineering Conference

Nathir Rawashdeh

A conference paper co-authored by Nathir Rawashdeh (CC/MERET), has been accepted for presentation and publication at the 5th International Conference on Advances in Mechanical Engineering, December 17-19, 2019, in Istanbul, Turkey.

The paper is entitled, “Effect of Camera’s Focal Plane Array Fill Factor on Digital Image Correlation Measurement Accuracy.” Co-authors are Ala L. Hijazi of German Jordanian University, and Christian J. Kähler of Universität der Bundeswehr München.

Abstract: The digital image correlation (DIC) method is one of the most widely used non-invasive full-field methods for deformation and strain measurements. It is currently being used in a very wide variety of applications including mechanical engineering, aerospace engineering, structural engineering, manufacturing engineering, material science, non-destructive testing, biomedical and life sciences. There are many factors that affect the DIC measurement accuracy where that includes; the selection of the correlation algorithm and parameters, the camera, the lens, the type and quality of the speckle pattern, the lightening conditions and surrounding environment. Several studies have addressed the different factors influencing the accuracy of DIC measurements and the sources of error. The camera’s focal plane array (FPA) fill factor is one of the parameters for digital cameras, though it is not widely known and usually not reported in specs sheets. The fill factor of an imaging sensor is defined as the ratio of a pixel’s light sensitive area to its total theoretical area. For some types of imaging sensors, the fill factor can theoretically reach 100%. However, for the types of imaging sensors typically used in most digital cameras used in DIC measurements, such as the “interline” charge coupled device CCD and the complementary metal oxide semiconductor (CMOS) imaging sensors, the fill factor is much less than 100%. It is generally believed that the lower fill factor may reduce the accuracy of photogrammetric measurements. But nevertheless, there are no studies addressing the effect of the imaging sensor’s fill factor on DIC measurement accuracy. We report on research aiming to quantify the effect of fill factor on DIC measurements accuracy in terms of displacement error and strain error. We use rigid-body-translation experiments then numerically modify the recorded images to synthesize three different types of images with 1/4 of the original resolution. Each type of the synthesized images has different value of the fill factor; namely 100%, 50% and 25%. By performing DIC analysis with the same parameters on the three different types of synthesized images, the effect of fill factor on measurement accuracy may be realized. Our results show that the FPA’s fill factor can have a significant effect on the accuracy of DIC measurements. This effect is clearly dependent on the type and characteristics of the speckle pattern. The fill factor has a clear effect on measurement error for low contrast speckle patterns and for high contrast speckle patterns (black dots on white background) with small dot size (3 pixels dot diameter). However, when the dot size is large enough (about 7 pixels dot diameter), the fill factor has very minor effect on measurement error. In addition, the results also show that the effect of the fill factor is also dependent on the magnitude of translation between images. For instance, the increase in measurement error resulting from low fill factor can be more significant for subpixel translations than large translations of several pixels.
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Mark Rouleau Is Co-author of Article in the Journal Landscape and Urban Planning

Mark Rouleau

An article by Mark Rouleau, associate professor of social sciences and member of the ICC’s Center for Data Sciences, was recently published in the journal Landscape and Urban Planning, published by Elsevier. The article, titled, “Agent-based modeling for bioenergy sustainability assessment,” is co-authored by Robert J. Zupko II.

Article Abstract: Woody biomass bioenergy is an important renewable alternative to conventional fossil fuels. However, the negative land-use change impacts of biomass harvesting necessary for bioenergy production can potentially outweigh its positive benefits if poorly managed. In this paper, we explain how Agent-Based Modeling (ABM), a form of computer simulation, can be used to conduct a comprehensive bioenergy sustainability assessment to identify possible gains and trade-offs necessary to develop bioenergy in regions with large numbers of private family forest owners or smallholders who own a significant share of available biomass. We discuss how ABM simulation can overcome the barriers of existing sustainability assessment tools and provide a demonstration of the sustainability assessment capabilities of an ABM using a hypothetical case study that explores the introduction of a bioenergy conversion facility in the Western Upper Peninsula of Michigan, United States. We conduct a series of alternative futures scenarios and compare the sustainability outcomes of three alternative policy regimes using voluntary incentive programs to encourage smallholders to harvest biomass.

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Recommended Citation: Rouleau, M., & Zupko II, R. J. (2019). Agent-based modeling for bioenergy sustainability assessment. Landscape and Urban Planning, 188, 54-63.

Zhen Liu Co-author of Publication in Cold Regions Science and Technology

Zhen Liu, associate professor of civil and environmental engineering and member of the ICC’s Center for Cyber-Physical Systems (CPS), is co-author of the article, “A multivariate freezing-thawing depth prediction model for spring load restriction,” which was published August 6, 2019, in the journal Cold Regions Science and Technology, which is published by Elsevier. Co-authors of the article are Ting Bio and John Bland.

Abstract: Road damages induced by heavily loaded truck traffic during the spring thaw are a major road distress in cold regions. To minimize these damages, Spring Load Restriction (SLR) is widely applied in the U.S., Canada, and other countries during the early thawing season by controlling the movement of freight-carrying trucks and heavy equipment travel until the thawing ends. Most SLR policies rely on the Freezing Depth (FD) and Thawing Depth (TD), especially the latter one. Therefore, accurate predictions of FD and TD are important to prevent both the extensive damage to the pavement due to the late placement or early removal of SLR and the economic loss of road users due to an unnecessarily long SLR period. Here, we propose a new multivariate model for predicting FD and TD in support of SLR decision-making. The model gives a curving surface of FD and TD in a 3-dimensional space, instead of 2-dimensional in traditional methods, by considering both the freezing and thawing indices in the entire freeze-thaw cycle. For model evaluations, yearly field data measured at five typical sites from 104 sites in Michigan were adopted. The evaluation results showed that the proposed model is accurate in predicting FD and TD for most sites. Compared to the previous TD predictions in the existing study, the TD predictions with the proposed model have been significantly improved. In addition, this study provides field data that have not been reported earlier in the literature and that can be used for validating other prediction models. The reported work is ready for practice for roadways in cold regions to support SLR decision-making.

Citation: Bao, T., Liu, Z., & Bland, J. (2019). A multivariate freezing-thawing depth prediction model for spring load restriction. Cold Regions Science and Technology, 167.

Mari Buche Is Co-author of Article in ACM SIGMIS Database

Mari Buche

Mari Buche (DataS), School of Business and Economics associate dean and professor of management information systems, is co-author of the article, “He Said, She Said: Communication Theory of Identity and the Challenges Men Face in the Information Systems Workplace,” which was published in the August 2019 issue of the newsletter ACM SIGMIS Database: the DATABASE for Advances in Information Systems.

Co-authors of the article are Cynthia K. Riemenschneider, Baylor University, and Deb Armstrong, Florida State University.

Abstract: The preponderance of the academic research focused on diversity in the IS field has emphasized the perspectives of women and racioethnic minorities. Recent research has found that following the appointment of a female CEO, white male top managers provided less help to colleagues, particularly those identified as minority-status (McDonald, Keeves, & Westphal, 2018). Additionally, Collison and Hearn (1994) assert that white men’s universal status and their occupancy of the normative standard state have rendered them invisible as objects of analysis. To develop a more holistic view of the IS workplace, we expand the academic exploration by looking at the challenges men face in the Information Systems (IS) workplace. Using a cognitive lens, we evoke the challenges men perceive they face at work and cast them into revealed causal maps. We then repeat the process evoking women’s perspectives of men’s challenges. The findings are analyzed using the Communication Theory of Identity (CTI) to determine the areas of overlap and identity gaps. This study advances our understanding of the cognitive overlap (and lack thereof) regarding the challenges facing men in the IS field, and provides another step toward developing a more inclusive IS work environment.

ACM SIGMIS Database: the DATABASE for Advances in Information Systems
Volume 50 Issue 3, August 2019
Pages 85-115
ACM New York, NY, USA

DOI: 10.1145/3353401.3353407

Ali Ebnenasir is Co-author of Article in ACM Transactions on Computational Logic

Ali EbnenasirAli Ebnenasir (SAS/CS), professor of computer science, is co-author of the article, “On the verification of livelock-freedom and self-stabilization on parameterized rings,” published in the July 2019 issue of the journal ACM Transactions on Computational Logic. The article is co-authored by Alex Klinkhamer of Google.

Abstract: This article investigates the verification of livelock-freedom and self-stabilization on parameterized rings consisting of symmetric, constant space, deterministic, and self-disabling processes. The results of this article have a significant impact on several fields, including scalable distributed systems, resilient and self-* systems, and verification of parameterized systems. First, we identify necessary and sufficient local conditions for the existence of global livelocks in parameterized unidirectional rings with unbounded (but finite) number of processes under the interleaving semantics. Using a reduction from the periodic domino problem, we show that, in general, verifying livelock-freedom of parameterized unidirectional rings is undecidable (specifically, Π10-complete) even for constant space, deterministic, and self-disabling processes. This result implies that verifying self-stabilization for parameterized rings of self-disabling processes is also undecidable. We also show that verifying livelock-freedom and self-stabilization remain undecidable under (1) synchronous execution semantics, (2) the FIFO consistency model, and (3) any scheduling policy. We then present a new scope-based method for detecting and constructing livelocks in parameterized rings. The proposed semi-algorithm behind our scope-based verification is based on a novel paradigm for the detection of livelocks that totally circumvents state space exploration. Our experimental results on an implementation of the proposed semi-algorithm are very promising as we have found livelocks in parameterized rings in a few microseconds on a regular laptop. The results of this article have significant implications for scalable distributed systems with cyclic topologies.

Citation: Klinkhamer, A., & Ebnenasir, A. (2019). On the verification of livelock-freedom and self-stabilization on parameterized rings. ACM Transactions on Computational Logic, 20(3), 16:1-16:36.

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Zhenlin Wang is Co-Author of Article in Parallel Programming Journal

Zhenlin Wang (SAS), professor of computer science, is co-author of the article, “Lightweight and accurate memory allocation in key-value cache,” published in the June 2019 issue of the International Journal of Parallel Programming, which is published by Springer.

Abstract: The use of key-value caches in modern web servers is becoming more and more ubiquitous. Representatively, Memcached as a widely used key-value cache system, originally intended for speeding up dynamic web applications by alleviating database load. One of the key factors affecting the performance of Memcached is the memory allocation among different item classes. How to obtain the most efficient partitioning scheme with low time and space consumption is a focus of attention. In this paper, we propose a lightweight and accurate memory allocation scheme in Memcached, by sampling access patterns, analyzing data locality, and reassigning the memory space. One early study on optimizing memory allocation is LAMA, which uses footprint-based MRC to optimize memory allocation in Memcached. However, LAMA does not model deletion operations in Memcached and its spatial overhead is quite large. We propose a method that consumes only 3% of LAMA space and can handle read, write and deletion operations. Moreover, evaluation results show that the average stable-state miss ratio is reduced by 15.0% and the average stable-state response time is reduced by 12.3% when comparing our method to LAMA.

Citation: Pan, C., Zhou, L., Luo, Y., Wang, X., & Wang, Z. (2019). Lightweight and accurate memory allocation in key-value cache. International Journal of Parallel Programming, 47(3), 451-466.

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