Where We Are With Enterprise Architecture, 2019 Embry-Riddle Aeronautical University
Where We Are With Enterprise Architecture, Leila Halawi, Richard Mccarthy, James Farah
Enterprise architecture has been continuously developing since the mid-1980s. Although there is now 35 years of research and use, there is still a lack consistent definitions and standards. This is apparent in the proliferation of so many different enterprise architecture frameworks. Despite the significant body of research, there is a need for standardization of terminology based upon a meta-analysis of the literature. Enterprise architecture programs require commitment throughout an organization to be effective and must be perceived to add value. This research offers an initial basis for researchers who need to expand and continue this research topic with an actual ...
Explore Alternatives Now! - Performance Mgmt In The Multi-Dimensional Digital World, 2019 Singapore Management University
Explore Alternatives Now! - Performance Mgmt In The Multi-Dimensional Digital World, Richard Raymond Smith
Research Collection Lee Kong Chian School Of Business
Earlier, business was not quite as dynamic, employment was intended for the long-term, and the idea of pay linked to performance was quite a dependable model. But as we examine the tradition of performance management in light of today's digital business models, there are a number of new questions that emerge.
Maximizing Multifaceted Network Influence, 2019 Singapore Management University
Maximizing Multifaceted Network Influence, Yuchen Li, Ju Fan, George V. Ovchinnikov, Panagiotis Karras
Research Collection School Of Information Systems
An information dissemination campaign is often multifaceted, involving several facets or pieces of information disseminating from different sources. The question then arises, how should we assign such pieces to eligible sources so as to achieve the best viral dissemination results? Past research has studied the problem of Influence Maximization (IM), which is to select a set of k promoters that maximizes the expected reach of a message over a network. However, in this classical IM problem, each promoter spreads out the same unitary piece of information. In this paper, we propose the Optimal Influential Pieces Assignment (OIPA) problem, which is ...
Uncertainty Theory Based Reliability-Centric Cyber-Physical System Design, 2019 Embry-Riddle Aeronautical University
Uncertainty Theory Based Reliability-Centric Cyber-Physical System Design, Houbing Song, Ya Jiang, Mingzhe Wang, Xun Jiao, Hui Kong, Rui Wang, Yongxin Liu, Jian Wang, Jiaguang Sun
Cyber-physical systems (CPSs) are built from, and depend upon, the seamless integration of software and hardware components. The most important challenge in CPS design and verification is to design CPS to be reliable in a variety of uncertainties, i.e., unanticipated and rapidly evolving environments and disturbances. The costs, delays and reliability of the designed CPS are highly dependent on software-hardware partitioning in the design. The key challenges in partitioning CPSs is that it is difficult to formalize reliability characterization in the same way as the uncertain cost and time delay.
In this paper, we propose a new CPS design ...
Forensicloud: An Architecture For Digital Forensic Analysis In The Cloud, 2019 Marshall University
Forensicloud: An Architecture For Digital Forensic Analysis In The Cloud, Cody Miller, Dae Glendowne, David Dampier, Kendall Blaylock
The amount of data that must be processed in current digital forensic examinations continues to rise. Both the volume and diversity of data are obstacles to the timely completion of forensic investigations. Additionally, some law enforcement agencies do not have the resources to handle cases of even moderate size. To address these issues we have developed an architecture for a cloud-based distributed processing platform we have named Forensicloud. This architecture is designed to reduce the time taken to process digital evidence by leveraging the power of a high performance computing platform and by adapting existing tools to operate within this ...
Exercises Integrating High School Mathematics With Robot Motion Planning, 2019 Loyola University Chicago
Exercises Integrating High School Mathematics With Robot Motion Planning, Ronald I. Greenberg, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
This paper presents progress in developing exercises for high school students incorporating level-appropriate mathematics into robotics activities. We assume mathematical foundations ranging from algebra to precalculus, whereas most prior work on integrating mathematics into robotics uses only very elementary mathematical reasoning or, at the other extreme, is comprised of technical papers or books using calculus and other advanced mathematics. The exercises suggested are relevant to any differerential-drive robot, which is an appropriate model for many different varieties of educational robots. They guide students towards comparing a variety of natural navigational strategies making use of typical movement primitives. The exercises align ...
Guest Editorial Special Issue On Toward Securing Internet Of Connected Vehicles (Iov) From Virtual Vehicle Hijacking, Yue Cao, Houbing Song, Omprakash Kaiwartya, Sinem Coleri Ergen, Jaime Lloret, Naveed Ahmad
Today’s vehicles are no longer stand-alone transportation means, due to the advancements on vehicle-tovehicle (V2V) and vehicle-to-infrastructure (V2I) communications enabled to access the Internet via recent technologies in mobile communications, including WiFi, Bluetooth, 4G, and even 5G networks. The Internet of vehicles was aimed toward sustainable developments in transportation by enhancing safety and efficiency. The sensor-enabled intelligent automation of vehicles’ mechanical operations enhances safety in on-road traveling, and cooperative traffic information sharing in vehicular networks improves traveling efficiency.
Design Of Personnel Big Data Management System Based On Blockchain, 2019 Embry-Riddle Aeronautical University
Design Of Personnel Big Data Management System Based On Blockchain, Houbing Song, Jian Chen, Zhihan Lv
With the continuous development of information technology, enterprises, universities and governments are constantly stepping up the construction of electronic personnel information management system. The information of hundreds of thousands or even millions of people’s information are collected and stored into the system. So much information provides the cornerstone for the development of big data, if such data is tampered with or leaked, it will cause irreparable serious damage. However, in recent years, electronic archives have exposed a series of problems such as information leakage, information tampering, and information loss, which has made the reform of personnel information management more ...
Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, 2019 University of Electronic Science and Technology of China
Adaboost‑Based Security Level Classifcation Of Mobile Intelligent Terminals, Feng Wang, Houbing Song, Dingde Jiang, Hong Wen
With the rapid development of Internet of Things, massive mobile intelligent terminals are ready to access edge servers for real-time data calculation and interaction. However, the risk of private data leakage follows simultaneously. As the administrator of all intelligent terminals in a region, the edge server needs to clarify the ability of the managed intelligent terminals to defend against malicious attacks. Therefore, the security level classification for mobile intelligent terminals before accessing the network is indispensable. In this paper, we firstly propose a safety assessment method to detect the weakness of mobile intelligent terminals. Secondly, we match the evaluation results ...
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, 2019 Western University
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger
Electrical and Computer Engineering Publications
Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by ...
Comparing Record Linkage Software Programs And Algorithms Using Real-World Data., 2019 RTI International
Comparing Record Linkage Software Programs And Algorithms Using Real-World Data., Alan F. Karr, Matthew T. Taylor, Suzanne L. West, Soko Setoguchi, Tzuyung D. Kou, Tobias Gerhard, Daniel B. Horton
Student Papers & Posters
Linkage of medical databases, including insurer claims and electronic health records (EHRs), is increasingly common. However, few studies have investigated the behavior and output of linkage software. To determine how linkage quality is affected by different algorithms, blocking variables, methods for string matching and weight determination, and decision rules, we compared the performance of 4 nonproprietary linkage software packages linking patient identifiers from noninteroperable inpatient and outpatient EHRs. We linked datasets using first and last name, gender, and date of birth (DOB). We evaluated DOB and year of birth (YOB) as blocking variables and used exact and inexact matching methods ...
Hybrid Superhydrophilic–Superhydrophobic Micro/ Nanostructures Fabricated By Femtosecond Laserinduced Forward Transfer For Sub-Femtomolar Raman Detection, Xiaodan Ma, Lan Jiang, Xiaowei Li, Bohong Li, Ji Huang, Jiaxing Sun, Zhi Wang, Zhijie Xu, Liangti Qu, Yongfeng Lu, Tianhong Cui
Faculty Publications from the Department of Electrical and Computer Engineering
Raman spectroscopy plays a crucial role in biochemical analysis. Recently, superhydrophobic surface-enhanced Raman scattering (SERS) substrates have enhanced detection limits by concentrating target molecules into small areas. However, due to the wet transition phenomenon, further reduction of the droplet contact area is prevented, and the detection limit is restricted. This paper proposes a simple method involving femtosecond laser-induced forward transfer for preparing a hybrid superhydrophilic–superhydrophobic SERS (HS-SERS) substrate by introducing a superhydrophilic pattern to promote the target molecules to concentrate on it for ultratrace detection. Furthermore, the HS-SERS substrate is heated to promote a smaller concentrated area. The water ...
Tech Report: Tunercar: A Superoptimization Toolchain For Autonomous Racing, 2019 University of Pennsylvania
Tech Report: Tunercar: A Superoptimization Toolchain For Autonomous Racing, Matthew O'Kelly, Hongrui Zheng, Achin Jain, Joseph Auckley, Kim Luong, Rahul Mangharam
Real-Time and Embedded Systems Lab (mLAB)
No abstract provided.
Advanced Mathematical And Numerical Methods In Control And Optimization For Smart Grids, 2019 University of Southampton
Advanced Mathematical And Numerical Methods In Control And Optimization For Smart Grids, Zhan Shu, Michael Z.Q. Chen, Qing Hui
Faculty Publications from the Department of Electrical and Computer Engineering
While renewable energy, as a part of smart-grid technologies, brings clean energy, it also brings a series of power quality problems. An increasing number of power electronic devices and new smart-grid technologies are used to ensure a safe, reliable, and high-quality operation of the power grid. However, the effectiveness of these control devices and technologies largely depends on the accuracy of the model, the advancement of control methods, and the numerical optimization of the parameters.
This special issue focuses on recent advances in modeling, numerical analysis, control, and optimization of smart grids with some special emphasis on the mathematical problems ...
Developing A Workflow To Integrate Tree Inventory Data Into Urban Energy Models, 2019 Iowa State University
Developing A Workflow To Integrate Tree Inventory Data Into Urban Energy Models, Farzad Hashemi, Breanna L. Marmur, Ulrike Passe, Janette R. Thompson
Building energy simulation is of considerable interest and benefit for architects, engineers, and urban planners. Only recently has it become possible to develop integrated energy models for clusters of buildings in urban areas. Simulating energy consumption of the built environment on a relatively large scale (e.g., such as a neighborhood) will be necessary to obtain more reliable results, since building energy parameters are influenced by characteristics of the nearby environment. Therefore, the construction of a 3-D model of urban built areas with detail of the near-building environment should enhance simulation approaches and provide more accurate results. This paper describes ...
Bibliometric Survey On Incremental Clustering Algorithms, 2019 Research Scholar, Symbiosis Institute of Technology (SIT) affiliated to Symbiosis International (Deemed University), Pune, India.
Bibliometric Survey On Incremental Clustering Algorithms, Archana Chaudhari, Rahul Raghvendra Joshi, Preeti Mulay, Ketan Kotecha, Parag Kulkarni
Library Philosophy and Practice (e-journal)
For clustering accuracy, on influx of data, the parameter-free incremental clustering research is essential. The sole purpose of this bibliometric analysis is to understand the reach and utility of incremental clustering algorithms. This paper shows incremental clustering for time series dataset was first explored in 2000 and continued thereafter till date. This Bibliometric analysis is done using Scopus, Google Scholar, Research Gate, and the tools like Gephi, Table2Net, and GPS Visualizer etc. The survey revealed that maximum publications of incremental clustering algorithms are from conference and journals, affiliated to Computer Science, Chinese lead publications followed by India then United States ...
Adaptive-Hybrid Redundancy For Radiation Hardening, 2019 Air Force Institute of Technology
Adaptive-Hybrid Redundancy For Radiation Hardening, Nicolas S. Hamilton
Theses and Dissertations
An Adaptive-Hybrid Redundancy (AHR) mitigation strategy is proposed to mitigate the effects of Single Event Upset (SEU) and Single Event Transient (SET) radiation effects. AHR is adaptive because it switches between Triple Modular Redundancy (TMR) and Temporal Software Redundancy (TSR). AHR is hybrid because it uses hardware and software redundancy. AHR is demonstrated to run faster than TSR and use less energy than TMR. Furthermore, AHR allows space vehicle designers, mission planners, and operators the flexibility to determine how much time is spent in TMR and TSR. TMR mode provides faster processing at the expense of greater energy usage. TSR ...
Research Toward A Partially-Automated, And Crime Specific Digital Triage Process Model, 2019 Marshall University
Research Toward A Partially-Automated, And Crime Specific Digital Triage Process Model, Gary Cantrell, David Dampier, Yoginder S. Dandass, Nan Niu, Chris Bogen
The digital forensic process as traditionally laid out begins with the collection, duplication, and authentication of every piece of digital media prior to examination. These first three phases of the digital forensic process are by far the most costly. However, complete forensic duplication is standard practice among digital forensic laboratories.
The time it takes to complete these stages is quickly becoming a serious problem. Digital forensic laboratories do not have the resources and time to keep up with the growing demand for digital forensic examinations with the current methodologies. One solution to this problem is the use of pre-examination techniques ...
Pipelined Parallelism In A Work-Stealing Scheduler, 2019 Washington University in St. Louis
Pipelined Parallelism In A Work-Stealing Scheduler, Thomas Kelly
All Computer Science and Engineering Research
A pipeline is a particular type of parallel program structure, often used to represent loops with cross-iteration dependencies. Pipelines cannot be expressed with the typical parallel language constructs offered by most environments. Therefore, in order to run pipelines, it is necessary to write a parallel language and scheduler with specialized support for them. Some such schedulers are written exclusively for pipelines and unable to run any other type of program, which allows for certain optimizations that take advantage of the pipeline structure. Other schedulers implement support for pipelines on top of a general-purpose scheduling algorithm. One example of such an ...
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, 2019 Singapore Management University
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham
Research Collection School Of Information Systems
Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.