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Full-Text Articles in Engineering

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney Oct 2021

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney

Articles

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and ...


Did George Orwell’S Newspeak Have A Point?: Linguistic Relativity And Its Implications For Copyright, Christopher S. Yoo Aug 2021

Did George Orwell’S Newspeak Have A Point?: Linguistic Relativity And Its Implications For Copyright, Christopher S. Yoo

Faculty Scholarship at Penn Law

To date, copyright scholarship has almost completely overlooked the linguistics and cognitive psychology literature exploring the connection between language and thought. An exploration of the two major strains of this literature, known as universal grammar (associated with Noam Chomsky) and linguistic relativity (centered around the Sapir-Whorf hypothesis), offers insights into the copyrightability of constructed languages and of the type of software packages at issue in Google v. Oracle recently decided by the Supreme Court. It turns to modularity theory as the key idea unifying the analysis of both languages and software in ways that suggest that the information filtering associated ...


Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney Aug 2021

Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney

Articles

For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no ...


Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty Aug 2021

Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty

REU Final Reports

Forest Park, one of the largest public parks in the United States with over 40 trails to pick from when planning a hiking trip. One of the main problems this park has is that there are too many trails, and a lot of the trails extend over 3 miles. Due to these circumstances’ trails are not checked frequently and hikers are forced to hike trails in the area with no warnings of potential hazards they can encounter. In this paper I researched how Forest Park currently monitors its trails and then set up a goal to solve the problem. We ...


Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee Aug 2021

Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee

REU Final Reports

The inclusion of technology on the trail can lead to better experiences for everyone involved in the hobby. Hikers can play a more prominent role in the maintenance of the trails by being able to provide better reports of obstructions while directly on the trail. This paper goes into the project of revamping the obstruction report system applied at Forest Park in Portland, Oregon. Most of my contributions to the project focus on mobile app development with some research into path planning algorithms related to the continuations of this project.


Forensic Artifact Finder (Forensicaf): An Approach & Tool For Leveraging Crowd-Sourced Curated Forensic Artifacts, Tyler Balon, Krikor Herlopian, Ibrahim Baggili, Cinthya Grajeda-Mendez Aug 2021

Forensic Artifact Finder (Forensicaf): An Approach & Tool For Leveraging Crowd-Sourced Curated Forensic Artifacts, Tyler Balon, Krikor Herlopian, Ibrahim Baggili, Cinthya Grajeda-Mendez

Electrical & Computer Engineering and Computer Science Faculty Publications

Current methods for artifact analysis and understanding depend on investigator expertise. Experienced and technically savvy examiners spend a lot of time reverse engineering applications while attempting to find crumbs they leave behind on systems. This takes away valuable time from the investigative process, and slows down forensic examination. Furthermore, when specific artifact knowledge is gained, it stays within the respective forensic units. To combat these challenges, we present ForensicAF, an approach for leveraging curated, crowd-sourced artifacts from the Artifact Genome Project (AGP). The approach has the overarching goal of uncovering forensically relevant artifacts from storage media. We explain our approach ...


Forensicast: A Non-Intrusive Approach & Tool For Logical Forensic Acquisition & Analysis Of The Google Chromecast Tv, Alex Sitterer, Nicholas Dubois, Ibrahim Baggili Aug 2021

Forensicast: A Non-Intrusive Approach & Tool For Logical Forensic Acquisition & Analysis Of The Google Chromecast Tv, Alex Sitterer, Nicholas Dubois, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The era of traditional cable Television (TV) is swiftly coming to an end. People today subscribe to a multitude of streaming services. Smart TVs have enabled a new generation of entertainment, not only limited to constant on-demand streaming as they now offer other features such as web browsing, communication, gaming etc. These functions have recently been embedded into a small IoT device that can connect to any TV with High Definition Multimedia Interface (HDMI) input known as Google Chromecast TV. Its wide adoption makes it a treasure trove for potential digital evidence. Our work is the primary source on forensically ...


Another Brick In The Wall: An Exploratory Analysis Of Digital Forensics Programs In The United States, Syria Mccullough, Stella Abudu, Ebere Onwubuariri, Ibrahim Baggili Aug 2021

Another Brick In The Wall: An Exploratory Analysis Of Digital Forensics Programs In The United States, Syria Mccullough, Stella Abudu, Ebere Onwubuariri, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

We present a comprehensive review of digital forensics programs offered by universities across the United States (U.S.). While numerous studies on digital forensics standards and curriculum exist, few, if any, have examined digital forensics courses offered across the nation. Since digital forensics courses vary from university to university, online course catalogs for academic institutions were evaluated to curate a dataset. Universities were selected based on online searches, similar to those that would be made by prospective students. Ninety-seven (n = 97) degree programs in the U.S. were evaluated. Overall, results showed that advanced technical courses are missing from curricula ...


Duck Hunt: Memory Forensics Of Usb Attack Platforms, Tyler Thomas, Mathew Piscitelli, Bhavik Ashok Nahar, Ibrahim Baggili Aug 2021

Duck Hunt: Memory Forensics Of Usb Attack Platforms, Tyler Thomas, Mathew Piscitelli, Bhavik Ashok Nahar, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

To explore the memory forensic artifacts generated by USB-based attack platforms, we analyzed two of the most popular commercially available devices, Hak5's USB Rubber Ducky and Bash Bunny. We present two open source Volatility plugins, usbhunt and dhcphunt, which extract artifacts generated by these USB attacks from Windows 10 system memory images. Such artifacts include driver-related diagnostic events, unique device identifiers, and DHCP client logs. Our tools are capable of extracting metadata-rich Windows diagnostic events generated by any USB device. The device identifiers presented in this work may also be used to definitively detect device usage. Likewise, the DHCP ...


Power-Over-Tether Unmanned Aerial System Leveraged For Trajectory Influenced Atmospheric Sensing, Daniel Rico Aug 2021

Power-Over-Tether Unmanned Aerial System Leveraged For Trajectory Influenced Atmospheric Sensing, Daniel Rico

Computer Science and Engineering: Theses, Dissertations, and Student Research

The use of unmanned aerial systems (UASs) in agriculture has risen in the past decade and is helping to modernize agriculture. UASs collect and elucidate data previously difficult to obtain and are used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this thesis, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS configured for long-term, high throughput atmospheric monitoring with an array of ...


Aerial Flight Paths For Communication, Alisha Bevins Aug 2021

Aerial Flight Paths For Communication, Alisha Bevins

Computer Science and Engineering: Theses, Dissertations, and Student Research

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be ...


Using Contextual Bandits To Improve Traffic Performance In Edge Network, Aziza Al Zadjali Aug 2021

Using Contextual Bandits To Improve Traffic Performance In Edge Network, Aziza Al Zadjali

Computer Science and Engineering: Theses, Dissertations, and Student Research

Edge computing network is a great candidate to reduce latency and enhance performance of the Internet. The flexibility afforded by Edge computing to handle data creates exciting range of possibilities. However, Edge servers have some limitations since Edge computing process and analyze partial sets of information. It is challenging to allocate computing and network resources rationally to satisfy the requirement of mobile devices under uncertain wireless network, and meet the constraints of datacenter servers too. To combat these issues, this dissertation proposes smart multi armed bandit algorithms that decide the appropriate connection setup for multiple network access technologies on the ...


A Real-World, Hybrid Event Sequence Generation Framework For Android Apps, Jun Sun Aug 2021

A Real-World, Hybrid Event Sequence Generation Framework For Android Apps, Jun Sun

Computer Science and Engineering: Theses, Dissertations, and Student Research

Generating meaningful inputs for Android apps is still a challenging issue that needs more research. Past research efforts have shown that random test generation is still an effective means to exercise User-Interface (UI) events to achieve high code coverage. At the same time, heuristic search approaches can effectively reach specified code targets. Our investigation shows that these approaches alone are insufficient to generate inputs that can exercise specific code locations in complex Android applications.

This thesis introduces a hybrid approach that combines two different input generation techniques--heuristic search based on genetic algorithm and random instigation of UI events, to reach ...


Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau Aug 2021

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective ...


Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part I: The Drug Development Process, Heather R. Campbell, Robert A. Lodder Aug 2021

Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part I: The Drug Development Process, Heather R. Campbell, Robert A. Lodder

Pharmaceutical Sciences Faculty Publications

Computational methods have provided pharmaceutical scientists and engineers a means to go beyond what's possible with experimental testing alone. Providing a means to study active pharmaceutical ingredients (API), excipients, and drug interactions at or near-atomic levels. This paper provides a review of this and other innovative computational methods used for solving pharmaceutical problems throughout the drug development process. Part one of two this paper will emphasize the role of computational methods and game theory in solving pharmaceutical challenges.


Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part Ii: Serious Gaming, Heather R. Campbell, Robert A. Lodder Aug 2021

Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part Ii: Serious Gaming, Heather R. Campbell, Robert A. Lodder

Pharmaceutical Sciences Faculty Publications

Serious gaming has begun to take a foothold in pharmaceutical problem-solving. Companies such as Akili's Interactive are seeing success in the form of positive clinical trial results and FDA approval of digital therapeutics. Academic researchers have begun exploring novel uses for serious gaming in the way of protein design and more with promising results. This paper provides a review of such topics in addition to topics of game repurposing- repurposing a game originally intended for entertainment into a serious game-such as Minecraft and America's Army. Reviewing these topics this paper shows the utility of serious gaming as a ...


Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick Jul 2021

Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick

Systems Science Faculty Publications and Presentations

Reconstructability Analysis (RA) and Bayesian Networks (BN) are both probabilistic graphical modeling methodologies used in machine learning and artificial intelligence. There are RA models that are statistically equivalent to BN models and there are also models unique to RA and models unique to BN. The primary goal of this paper is to unify these two methodologies via a lattice of structures that offers an expanded set of models to represent complex systems more accurately or more simply. The conceptualization of this lattice also offers a framework for additional innovations beyond what is presented here. Specifically, this paper integrates RA and ...


Using Machine Learning To Develop A Fully Automated Soybean Nodule Acquisition Pipeline (Snap), Talukder Zaki Jubery, Clayton N. Carley, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian, Asheesh K. Singh Jul 2021

Using Machine Learning To Develop A Fully Automated Soybean Nodule Acquisition Pipeline (Snap), Talukder Zaki Jubery, Clayton N. Carley, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian, Asheesh K. Singh

Mechanical Engineering Publications

Nodules form on plant roots through the symbiotic relationship between soybean (Glycine max L. Merr.) roots and bacteria (Bradyrhizobium japonicum) and are an important structure where atmospheric nitrogen (N2) is fixed into bioavailable ammonia (NH3) for plant growth and development. Nodule quantification on soybean roots is a laborious and tedious task; therefore, assessment is frequently done on a numerical scale that allows for rapid phenotyping, but is less informative and suffers from subjectivity. We report the Soybean Nodule Acquisition Pipeline (SNAP) for nodule quantification that combines RetinaNet and UNet deep learning architectures for object (i.e., nodule) detection and segmentation ...


Detection Of Message Injection Attacks Onto The Can Bus Using Similarities Of Successive Messages-Sequence Graphs, Mubark Jedh, Lotfi Ben Othmane, Noor Ahmed, Bharat Bhargava Jul 2021

Detection Of Message Injection Attacks Onto The Can Bus Using Similarities Of Successive Messages-Sequence Graphs, Mubark Jedh, Lotfi Ben Othmane, Noor Ahmed, Bharat Bhargava

Electrical and Computer Engineering Publications

The smart features of modern cars are enabled by a number of Electronic Control Units (ECUs) components that communicate through an in-vehicle network, known as Controller Area Network (CAN) bus. The fundamental challenge is the security of the communication link where an attacker can inject messages (e.g., increase the speed) that may impact the safety of the driver. Most of existing practical IDS solutions rely on the knowledge of the identity of the ECUs, which is proprietary information. This paper proposes a message injection attack detection solution that is independent of the IDs of the ECUs. First, we represent ...


Reconfiguring Non-Convex Holes In Pivoting Modular Cube Robots, Daniel Adam Feshbach, Cynthia Sung Jul 2021

Reconfiguring Non-Convex Holes In Pivoting Modular Cube Robots, Daniel Adam Feshbach, Cynthia Sung

Lab Papers (GRASP)

We present an algorithm for self-reconfiguration of admissible 3D configurations of pivoting modular cube robots with holes of arbitrary shape and number. Cube modules move across the surface of configurations by pivoting about shared edges, enabling configurations to reshape themselves. Previous work provides a reconfiguration algorithm for admissible 3D configurations containing no non-convex holes; we improve upon this by handling arbitrary admissible 3D configurations. The key insight specifies a point in the deconstruction of layers enclosing non-convex holes at which we can pause and move inner modules out of the hole. We prove this happens early enough to maintain connectivity ...


Reshaping The Landscape Of The Future: Software-Defined Manufacturing, Lei Xu, Lin Chen, Zhimin Gao, Hiram Moya, Weidong Shi Jul 2021

Reshaping The Landscape Of The Future: Software-Defined Manufacturing, Lei Xu, Lin Chen, Zhimin Gao, Hiram Moya, Weidong Shi

Computer Science Faculty Publications and Presentations

We describe the concept of software-defined manufacturing, which divides the manufacturing ecosystem into software definition and physical manufacturing layers. Software-defined manufacturing allows better resource sharing and collaboration, and it has the potential to transform the existing manufacturing sector.


The Multi-Vehicle Cycle Inventory Routing Problem: Formulation And A Metaheuristic Approach, Vincent F. Yu, Audrey Tedja Widjaja, Aldy Gunawan, Pieter Vansteenwegen Jul 2021

The Multi-Vehicle Cycle Inventory Routing Problem: Formulation And A Metaheuristic Approach, Vincent F. Yu, Audrey Tedja Widjaja, Aldy Gunawan, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper presents a new variant of the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) which aims to determine a subset of customers to be visited, the appropriate number of vehicles used, and the corresponding cycle time and route sequence, such that the total cost (e.g. transportation, inventory, and rewards) is minimized. The MV-CIRP is formulated as a mixed-integer nonlinear programming model. We propose a Simulated Annealing (SA) based algorithm to solve the problem. SA is first tested on the available benchmark Single-Vehicle CIRP (SV-CIRP) instances and compared to the state-of-the-art algorithms. SA is then tested on the benchmark MV-CIRP ...


Deep Multiview Image Fusion For Soybean Yield Estimation In Breeding Applications, Luis G. Riera, Matthew E. Carroll, Zhisheng Zhang, Johnathon M. Shook, Sambuddha Ghosal, Tianshuang Gao, Arti Singh, Sourabh Bhattacharya, Baskar Ganapathysubramanian, Asheesh K. Singh, Soumik Sarkar Jun 2021

Deep Multiview Image Fusion For Soybean Yield Estimation In Breeding Applications, Luis G. Riera, Matthew E. Carroll, Zhisheng Zhang, Johnathon M. Shook, Sambuddha Ghosal, Tianshuang Gao, Arti Singh, Sourabh Bhattacharya, Baskar Ganapathysubramanian, Asheesh K. Singh, Soumik Sarkar

Mechanical Engineering Publications

Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop a machine learning (ML) approach adept at soybean (Glycine max L. (Merr.)) pod counting to enable genotype seed yield rank prediction from in-field video data collected by a ground robot. To meet this goal, we developed a multiview image-based yield estimation framework utilizing deep learning architectures. Plant images captured from different angles were fused to estimate the yield and subsequently to rank soybean genotypes for application in breeding decisions. We used data ...


Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski Jun 2021

Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski

Systems Science Faculty Publications and Presentations

Paper presents a concept that is new to robotics education and social robotics. It is based on theatrical games, in motions for social robots and animatronic robots. Presented here motion model is based on Drift Differential Model from biology and Fokker-Planck equations. This model is used in various areas of science to describe many types of motion. The model was successfully verified on various simulated mobile robots and a motion game of three robots called "Mouse and Cheese."


Toward An Intelligent Driving Behavior Adjustment Based On Legal Personalized Policies Within The Context Of Connected Vehicles, Fatma Outay, Nafaa Jabeur, Hedi Haddad, Zied Bouyahia, Hana Gharrad Jun 2021

Toward An Intelligent Driving Behavior Adjustment Based On Legal Personalized Policies Within The Context Of Connected Vehicles, Fatma Outay, Nafaa Jabeur, Hedi Haddad, Zied Bouyahia, Hana Gharrad

All Works

The advent of Connected Vehicles (CVs) is creating new opportunities within the transportation sector. It is, indeed, expected to improve road traffic safety, enhance mobility, reduce fuel consumption and gas emissions, as well as foster economic growth via investments and jobs. However, to motivate the deployment of CVs and maximize their related benefits, policymakers must create appropriate neutral legal frameworks. These frameworks should promote the innovation of current road infrastructures, support cooperation and interoperability between transportation systems, and encourage fair competition between companies while upholding consumer privacy as well as data protection. We argue that policymakers should also support innovative ...


A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead Jun 2021

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global ...


Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger Jun 2021

Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger

Michigan Tech Publications

Soil strength characterization is essential for any problem that deals with geomechanics, including terramechanics/terrain mobility. Presently, the primary method of collecting soil strength parameters through in situ measurements but sending a team of people out to a site to collect data this has significant cost implications and accessing the location with the necessary equipment can be difficult. Remote sensing provides an alternate approach to in situ measurements. In this lab study, we compare the use of Apparent Thermal Inertia (ATI) against a GeoGauge for the direct testing of soil stiffness. ATI correlates with stiffness, so it allows one to ...


Robust Learning Via Persistency Of Excitation, Kaustubh Sridhar, Oleg Sokolsky, Insup Lee, James Weimer Jun 2021

Robust Learning Via Persistency Of Excitation, Kaustubh Sridhar, Oleg Sokolsky, Insup Lee, James Weimer

Departmental Papers (CIS)

Improving adversarial robustness of neural networks remains a major challenge. Fundamentally, training a network is a parameter estimation problem. In adaptive control theory, maintaining persistency of excitation (PoE) is integral to ensuring convergence of parameter estimates in dynamical systems to their robust optima. In this work, we show that network training using gradient descent is equivalent to a dynamical system parameter estimation problem. Leveraging this relationship, we prove a sufficient condition for PoE of gradient descent is achieved when the learning rate is less than the inverse of the Lipschitz constant of the gradient of loss function. We provide an ...


Communication Objectives Model (Com): A Taxonomy Of Face-To-Face Communication Objectives To Inform Tele-Presence Technology Adoption, Rachel E. Dianiska, Peggy Wu, Charles J. Peasley, Kaitlyn M. Ouverson, Jacklin H. Stonewall, Emily Oldham, Brett Israelsen, Stephen B. Gilbert, James H. Oliver Jun 2021

Communication Objectives Model (Com): A Taxonomy Of Face-To-Face Communication Objectives To Inform Tele-Presence Technology Adoption, Rachel E. Dianiska, Peggy Wu, Charles J. Peasley, Kaitlyn M. Ouverson, Jacklin H. Stonewall, Emily Oldham, Brett Israelsen, Stephen B. Gilbert, James H. Oliver

Industrial and Manufacturing Systems Engineering Publications

Computer-mediated communication (CMC) has become the new normal in the era of pandemic-induced physical distancing. CMC has dramatically reduced business travel and daily commuting for knowledge workers able to work from home, which in turn reduces carbon emissions and energy expenditure. CMC offers a different communication experience compared to in-person interactions, and its impact on the success of communication is complex. Here, we report the Communication Objectives Model (COM), a framework developed to: a) understand differences in the performance of communication objectives between CMC and face-to-face interactions, and b) guide future research on measurement of such communication objectives. Given that ...


Establishing Suitable Metrics To Encourage Broader Use Of Atomic Requirements, William L. Honig Jun 2021

Establishing Suitable Metrics To Encourage Broader Use Of Atomic Requirements, William L. Honig

Computer Science: Faculty Publications and Other Works

Despite the apparent benefits of singular, individual, or atomic requirements, their use remains limited, and teaching their creation is difficult. The acceptance of a set of requirements metrics specifically designed to evaluate atomic requirements may lead to their better utilization and improved requirements engineering. Twelve metrics designed to measure atomic requirements are presented here: six used on individual requirements statements and six applied to a requirements document or set of requirement statements. Example metrics for individual requirements are Requirement Completeness and Requirement Atomicity; examples to measure multiple requirements include Requirements Traceablity and Requirements Purity. These metrics are designed to work ...