• International Journal of Concrete Structures and Materials
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• v.9 no.1
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• pp.119-132
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• 2015

Electrical resistivity is an important physical property of portland cement concrete which is directly related to chloride induced corrosion process. This study examined the electrical surface resistivity (SR) and bulk electrical resistivity (BR) of concrete cylinders for various binary and ternary based high-performance concrete (HPC) mixtures from 7 to 161 days. Two different types of instruments were utilized for this investigation and they were 4 point Wenner probe meter for SR and Merlin conductivity tester for bulk resistivity measurements. Chronological development of electrical resistivity as well as correlation between two types of resistivity on several days was established for all concrete mixtures. The ratio of experimental surface resistance to bulk resistance and corresponding resistivity was computed and compared with theoretical values. Results depicted that bulk and SR are well correlated for different groups of HPC mixtures and these mixtures have attained higher range of electrical resistivity for both types of measurements. In addition, this study presents distribution of surface and bulk resistivity in different permeability classes as proposed by Florida Department of Transportation (FDOT) specification from 7 to 161 days. Furthermore, electrical resistivity data for several HPC mixtures and testing procedure provide multiple promising options for long lasting bridge decks against chloride induced corrosion due to its ease of implementation, repeatability, non-destructive nature, and low cost.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.567-579
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• 2016

Several energy saving techniques in cellular wireless networks such as active base station (BS) selection, transmit power budget adaptation and user association have been studied independently or only part of these aspects have been considered together in literature. In this paper, we jointly tackle these three problems and propose an integrated framework, called dynamic cell reconfiguration (DCR). It manages three techniques operating on different time scales for ultimate energy conservation while guaranteeing the quality of service (QoS) level of users. Extensive simulations under various configurations, including the real dataset of BS topology and utilization, demonstrate that the proposed DCR can achieve the performance close to an optimal exhaustive search. Compared to the conventional static scheme where all BSs are always turned on with their maximum transmit powers, DCR can significantly reduce energy consumption, e.g., more than 30% and 50% savings in uniform and non-uniform traffic distribution, respectively.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.33-39
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• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.74-82
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• 2022

Improving long-term performance in highway projects is an imperative goal for public administrations. Project delivery and procurement methods might provide an opportunity to align design and construction processes with this goal. Previous studies have explored whether project delivery methods impact the long-term performance of highway projects. However, these studies did not focus specifically on how core elements within the procurement might relate to long-term performance. Thus, this research aims to fill this gap by exploring to what extent and how long-term evaluation criteria are considered in design-build best-value procurement of highway projects. To this end, content analysis was conducted on 100 projects procured between 2009 and 2019 by 19 DOTs across the U.S. The analysis of 365 evaluation criteria found that (1) roughly 11% of them related to long-term performance. (2) The weight given to these criteria in the overall technical proposal was lower than 30%. (3) Sixty-five percent (65%) of long-term evaluation criteria focused on design while 15% related to materials and technology, respectively. The results of this study are a first steppingstone to initiate a deep exploration of the relationship between procurement practices and actual project performance. Currently, with sustainability and life cycle assessments being top concerns in infrastructure projects, this line of research might be of particular interest to DOTs and highway agencies across the U.S. and worldwide.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.74-83
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• 2011

This paper recognized a need in the architecture, engineering, and construction industry for new programs and methods of producing reliable energy simulations using BIM (Building Information Modeling) technology. Current methods and programs for running energy simulations are not very timely, difficult to understand, and lack high interoperability between the BIM software and energy simulation software. It is necessary to improve on these drawbacks as design decision are often made without the aid of energy modeling leading to the design and construction of non-optimized buildings with respect to energy efficiency. The goal of this research project is to develop a new methodology to produce energy estimates from a BIM model in a more timely fashion and to improve interoperability between the simulation engine and BIM software. In the proposed methodology, the extracted information from a BIM model is compiled into an INP file and run in a popular energy simulation program, DOE-2, on an hourly basis for a desired time period. Case study showed that the application of this methodology could be used to expediently provide energy simulations while at the same time reproducing the BIM in a more readably three dimensional modeling program. With the aid of an easy to run and easily understood energy simulation methodology, designers will be able to make more energy conscious decisions during the design phase and as changes in design requirements arise.

• Steel and Composite Structures
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• v.52 no.5
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• pp.543-555
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• 2024

This study examines the seismic vulnerability of vertically irregular reinforced concrete (RC) frame buildings, focusing on the effectiveness of retrofitting techniques such as rocking walls (RWs) in mitigating soft story mechanisms. Utilizing a seven-story residential apartment as a prototype in a high-seismicity urban area, this research performs detailed nonlinear simulations to evaluate both regular and irregular structures, both before and after retrofitting. Pushover and nonlinear time history analyses were conducted using OpenSees software, with a suite of nine ground motion records to capture diverse seismic scenarios. The findings indicate that retrofitting with RWs significantly improves seismic performance: for instance, roof displacements at the Collapse Prevention (CP) level decreased by up to 23% in the irregular structure with retrofitting compared to its non-retrofitted counterpart. Additionally, interstory drift ratios were more uniform post-retrofit, with Drift Concentration Factor (DCF) values approaching 1.0 across all performance levels, reflecting reduced variability in seismic response. The global ductility of the retrofitted buildings improved, with displacement ductility ratios increasing by up to 29%. These results underscore the effectiveness of RWs in enhancing global ductility, mitigating soft story failures, and providing a more predictable deformation pattern during seismic events. The study thus provides valuable insights into the robustness and cost-effectiveness of using rocking walls for retrofitting irregular RC buildings.

• Journal of Smart Tourism
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• v.4 no.2
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• pp.25-33
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• 2024

This study examines the factors influencing the use of mobile food ordering applications and their impact on consumption behavior amidst recent societal changes. It re-evaluates the relevance of factors from the UTAUT2 theory in predicting customers' behavioral intentions. Additionally, the study explores the moderating effect of confidence in food safety measures (CFSM). Quantitative research methods are employed. A structured questionnaire that measures the psychological factors, behavioral intention, and actual usage of mobile food ordering applications was used to collect customer data. Regression and moderation analyses are conducted to test the hypotheses and examine the moderating role of CFSM. The findings reveal that performance expectation, effort expectation, and habit significantly predict customers' intention to use mobile food ordering applications. Moreover, for customers with high CFSM, social influence, facilitating conditions, and hedonic motivation add additional contributions to their behavioral intention. This study extends the UTAUT2 theory by applying it to mobile food ordering applications and examining the influence of CFSM. It identifies the specific factors that drive customers' intention to use these applications and highlights the importance of CFSM as a moderating factor. The findings offer theoretical insights and practical implications for researchers and practitioners in the mobile food ordering industry.

• Electrical & Electronic Materials
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• v.16 no.9
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• pp.61.1-61
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• 2003

Stoichiometric, uniform, amorphous ZrO$_2$ films with an equivalent oxide thickness of ∼1.5nm and a dielectric constant of ∼18 were deposited by an atomic layer controlled deposition process on silicon for potential application in meta-oxide-semiconductor(MOS) devices. The conduction mechanism is identified as Schottky emission at low electric fields and as Poole-Frenkel emission at high electric fields. the MOS devices showed low leakage current, small hysteresis(〈50mV), and low interface state density(∼2*10e11/cm2eV). Microdiffraction and high-resolution transmission electron microscopy showed a localized monoclinic phase of ${\alpha}$-ZrO$_2$ and an amorphous interfacial ZrSi$\_$x/O$\_$y/ layer which has a correspondign dielectric constant of 11

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.56.1-56.1
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• 2016

A low-mass star-forming region, L1251B, is an excellent example of a small and nearby group of protostellar objects. L1251B has been mapped spectroscopically with the Infrared Spectrograph (IRS) onboard the Spitzer Space Telescope. IRS has provided mid-IR emission lines (e.g., [Fe II], [Ne II], and ro-vibrational H2) and absorption features of CO2 and H2O ice in studying the physical state of the ionized gas and the material residing in the circumstellar environments. We will present the distribution of outflows and ice components in L1251B.

• Earthquakes and Structures
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• v.9 no.6
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• pp.1153-1179
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• 2015

This paper focuses on presenting modeling considerations and insight into the performance of typical straight, curved, and skewed box-girder bridges in California which form the bulk of the bridge inventory in the state. Three case study bridges are chosen: Meloland Road Overpass, Northwest Connector of Interstate 10/215 Interchange, and Painter Street Overpass, having straight, curved, and skewed superstructures, respectively. The efficacy of nonlinear dynamic analysis is established by comparing the response from analytical models to the recorded strong motion data. Finally insights are provided on the component behavioral characteristics and shift in vulnerability for each of the bridge types considered.