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Articles 1 - 30 of 70
Full-Text Articles in Engineering
Ai Is Here. Here’S How New Mexicans Can Prepare, Sonia Gipson Rankin, Melanie E. Moses
Ai Is Here. Here’S How New Mexicans Can Prepare, Sonia Gipson Rankin, Melanie E. Moses
Faculty Scholarship
Last December we asked the AI chatbot ChatGPT to solve a programming assignment given to computer science students at UNM. It wrote some Python code, but it generated an error. We gave the chatbot the error message and were astounded by how good its response was.
Scalable Production Of Peptides For Enhanced Struvite Formation Via Expression On The Surface Of Genetically Engineered Microbes, Jacob D. Hostert, Quincy A. Spitzer, Paola Giammattei, Julie N. Renner
Scalable Production Of Peptides For Enhanced Struvite Formation Via Expression On The Surface Of Genetically Engineered Microbes, Jacob D. Hostert, Quincy A. Spitzer, Paola Giammattei, Julie N. Renner
Faculty Scholarship
A promising method for recycling phosphate from wastewater is through precipitation of struvite (MgNH4PO4·6H2O), a slow-release fertilizer. Peptides have been shown to increase the yield of struvite formation, but producing peptides via solid phase synthesis is cost prohibitive. This work investigates the effects of peptide-expressing bacteria on struvite precipitation to provide a sustainable and cost-efficient means to enhance struvite precipitation. A peptide known for increased struvite yield was expressed on a membrane protein in Escherichia coli(E. coli), and then 5 mL precipitation reactions were performed in 50 mL culture tubes for at least 15 min. The yield of struvite crystals …
Microwave Regeneration And Thermal And Oxidative Stability Of Imidazolium Cyanopyrrolide Ionic Liquid For Direct Air Capture Of Carbon Dioxide, Yun-Yang Lee, Eda Cagli, Aidan Klemm, Ruth Dikki
Microwave Regeneration And Thermal And Oxidative Stability Of Imidazolium Cyanopyrrolide Ionic Liquid For Direct Air Capture Of Carbon Dioxide, Yun-Yang Lee, Eda Cagli, Aidan Klemm, Ruth Dikki
Faculty Scholarship
Understanding the oxidative and thermal degradation of CO2 sorbents is essential for assessing long-term sorbent stability in direct air capture (DAC). The potential degradation pathway of imidazolium cyanopyrrolide, an ionic liquid (IL) functionalized for superior CO2 capacity and selectivity, is evaluated under accelerated degradation conditions to elucidate the secondary reactions that can occur during repetitive absorption-desorption thermal-swing cycles. The combined analysis from various spectroscopic, chromatographic, and thermal gravimetric measurements indicated that radical and SN2 mechanisms in degradation are encouraged by the nucleophilicity of the anion. Thickening of the liquid and gas evolution are accompanied by 50 % reduction in CO2 …
Clickable Polymer Scaffolds Enable Ce Recovery With Peptide Ligands, Jacob D. Hostert, Maura R. Sepesy, Christine E. Duval, Julie N. Renner
Clickable Polymer Scaffolds Enable Ce Recovery With Peptide Ligands, Jacob D. Hostert, Maura R. Sepesy, Christine E. Duval, Julie N. Renner
Faculty Scholarship
Rare earth elements (REEs) are a vital part of many technologies with particular importance to the renewable energy sector and there is a pressing need for environmentally friendly and sustainable processes to recover and recycle them from waste streams. Functionalized polymer scaffolds are a promising means to recover REEs due to the ability to engineer both transport properties of the porous material and specificity for target ions. In this work, REE adsorbing polymer scaffolds were synthesized by first introducing poly(glycidyl methacrylate) (GMA) brushes onto porous polyvinylidene fluoride (PVDF) surface through activator generated electron transfer atom transfer radical polymerization (AGET ATRP). …
Statistical Analysis And Degradation Pathway Modeling Of Photovoltaic Minimodules With Varied Packaging Strategies, Sameera Nalin Venkat, Xuanji Yu, Jiqi Liu, Jakob Wegmueller, Jayvic Cristian Jimenez, Erika I. Barcelos, Hein Htet Aung, Roger H. French, Laura S. Bruckman
Statistical Analysis And Degradation Pathway Modeling Of Photovoltaic Minimodules With Varied Packaging Strategies, Sameera Nalin Venkat, Xuanji Yu, Jiqi Liu, Jakob Wegmueller, Jayvic Cristian Jimenez, Erika I. Barcelos, Hein Htet Aung, Roger H. French, Laura S. Bruckman
Faculty Scholarship
Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power …
Behavior Of Concrete Reinforced With Date Palm Fibers, Elias Ali
Behavior Of Concrete Reinforced With Date Palm Fibers, Elias Ali
Faculty Scholarship
In recent decades, researchers have begun to investigate innovative sustainable construction materials for the development of greener and more environmentally friendly infrastructures. The main purpose of this article is to investigate the possibility of employing date palm tree waste as a natural fiber alternative for conventional steel and polypropylene fibers (PPFs) in concrete. Date palm fibers are a common agricultural waste in Middle Eastern nations, particularly Saudi Arabia. As a result, this research examined the engineering properties of high‐strength concrete using date palm fibers, as well as the performance of traditional steel and PPF concrete. The concrete samples were made …
Vitrimerization Of Rigid Thermoset Polyurethane Foams: A Mechanochemical Method To Recycle And Reprocess Thermosets, Alireza Bandegi, Maya Montemayor, Ica Manas‐Zloczower
Vitrimerization Of Rigid Thermoset Polyurethane Foams: A Mechanochemical Method To Recycle And Reprocess Thermosets, Alireza Bandegi, Maya Montemayor, Ica Manas‐Zloczower
Faculty Scholarship
Polyurethane (PU) thermosets are extensively used in different applications and recycling the large amount of PU thermoset waste remains a universal challenge. Recycling the thermoset waste through vitrimerization is a feasible, cost-effective, and environmental-friendly approach. In this work, triazabicyclodecene (TBD) is used as organocatalyst in the vitrimerization process to recycle and reprocess thermoset rigid polyurethane foams. The results show that the permanent crosslinked structure of the PU thermoset foam is converted to a dynamic network upon vitrimerization. The vitrimerized network can rapidly relax the stress in 10 s at temperatures as low as 120°C. The topology rearrangement happens through the …
Numerical Investigation On Blast Response Of Cold-Formed Steel Framing Protected With Functionally Graded Composite Material, Elias Ali
Faculty Scholarship
This paper presents a numerical simulation on the blast response of cold-formed steel (CFS) structural framing system protected with a functionally graded composite material (FGM) panel. The steel frame consists of four CFS studs, which were protected by 12.5 mm thick gypsum, aluminum composite, and FGM composite materials on both sides. The numerical simulation was performed using ABAQUS on a 1.8 m × 2.4 m, overall wall panel exposed to air blast on one side. A 1.0 kg TNT explosive charge placed at four standoff distances (R) of 1.0 m, 1.5 m, 2.0 m, and 2.5 m from the framing …
Optimizing Biomedical Discoveries As An Engine Of Culture Change In An Academic Medical Center, Anne K. Dechant, Stephen Fening, Michael Haag, William Harte, Mark R. Chance
Optimizing Biomedical Discoveries As An Engine Of Culture Change In An Academic Medical Center, Anne K. Dechant, Stephen Fening, Michael Haag, William Harte, Mark R. Chance
Faculty Scholarship
Academic discovery in biomedicine is a growing enterprise with tens of billions of dollars in research funding available to universities and hospitals. Protecting and optimizing the resultant intellectual property is required in order for the discoveries to have an impact on society. To achieve that, institutions must create a multidisciplinary, collaborative system of review and support, and utilize connections to industry partners. In this study, we outline the efforts of Case Western Reserve University, coordinated through its Clinical and Translational Science Collaborative (CTSC), to promote entrepreneurial culture, and achieve goals of product development and startup formation for biomedical and population …
Continuous Operator Authentication For Teleoperated Systems Using Hidden Markov Models [Post-Print], Junjie Yan, Kevin Huang, Kyle Lindgren, Tamara Bonaci, Howard J. Chizeck
Continuous Operator Authentication For Teleoperated Systems Using Hidden Markov Models [Post-Print], Junjie Yan, Kevin Huang, Kyle Lindgren, Tamara Bonaci, Howard J. Chizeck
Faculty Scholarship
In this article, we present a novel approach for continuous operator authentication in teleoperated robotic processes based on Hidden Markov Models (HMM). While HMMs were originally developed and widely used in speech recognition, they have shown great performance in human motion and activity modeling. We make an analogy between human language and teleoperated robotic processes (i.e., words are analogous to a teleoperator's gestures, sentences are analogous to the entire teleoperated task or process) and implement HMMs to model the teleoperated task. To test the continuous authentication performance of the proposed method, we conducted two sets of analyses. We built a …
A Simplified Stress Analysis Of Functionally Graded Beams And Influence Of Material Function On Deflection, Elias Ali
Faculty Scholarship
This paper aims at providing a simplified analytical solution for functionally graded beam stress analysis and optimized material gradation on the beam deflection. The power-law (P-FGM) and exponential (E-FGM) material functions were considered for an exact solution of the normal and shear stress distributions across the beam thickness. Optimization of material function on the FGM beam deflection, which is new of its kind, was also investigated considering both simply supported and cantilever beams. It was observed that the non-dimensional normal stress and shear stress are independent of the elastic moduli values of the constituent materials but rather depends on both …
Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy
Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy
Faculty Scholarship
As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. This framework is designed to direct attention to pertinent system properties without requiring unwieldy amounts of accuracy. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of …
Death In Genetic Algorithms, Micah Burkhardt, Roman Yampolskiy
Death In Genetic Algorithms, Micah Burkhardt, Roman Yampolskiy
Faculty Scholarship
Death has long been overlooked in evolutionary algorithms. Recent research has shown that death (when applied properly) can benefit the overall fitness of a population and can outperform sub-sections of a population that are “immortal” when allowed to evolve together in an environment [1]. In this paper, we strive to experimentally determine whether death is an adapted trait and whether this adaptation can be used to enhance our implementations of conventional genetic algorithms. Using some of the most widely accepted evolutionary death and aging theories, we observed that senescent death (in various forms) can lower the total run-time of genetic …
Impossibility Results In Ai: A Survey, Mario Brcic, Roman Yampolskiy
Impossibility Results In Ai: A Survey, Mario Brcic, Roman Yampolskiy
Faculty Scholarship
An impossibility theorem demonstrates that a particular problem or set of problems cannot be solved as described in the claim. Such theorems put limits on what is possible to do concerning artificial intelligence, especially the super-intelligent one. As such, these results serve as guidelines, reminders, and warnings to AI safety, AI policy, and governance researchers. These might enable solutions to some long-standing questions in the form of formalizing theories in the framework of constraint satisfaction without committing to one option. In this paper, we have categorized impossibility theorems applicable to the domain of AI into five categories: deduction, indistinguishability, induction, …
Examining The Inertial Subrange With Nanoscale Cross-Wire Measurements Of Turbulent Pipe Flow At High Reynolds Number Near The Centreline [Post-Print], Clayton P. Byers, Marcus Hultmark, Ivan Marusic, Matt K. Fu
Examining The Inertial Subrange With Nanoscale Cross-Wire Measurements Of Turbulent Pipe Flow At High Reynolds Number Near The Centreline [Post-Print], Clayton P. Byers, Marcus Hultmark, Ivan Marusic, Matt K. Fu
Faculty Scholarship
Highly resolved, two-component velocity measurements were made near the centreline of turbulent pipe flow for Reynolds numbers in the range . These unique data were obtained with a nanoscale cross-wire probe and used to examine the inertial subrange scaling of the longitudinal and transverse velocity components. Classical dissipation rate estimates were made using both the integration of one-dimensional dissipation spectra for each velocity component and the third-order moment of the longitudinal structure function. Although the second-order moments and one-dimensional spectra for each component showed behaviour consistent with local isotropy, clear inertial range similarity and behaviour were not exhibited in the …
Designing Ai For Explainability And Verifiability: A Value Sensitive Design Approach To Avoid Artificial Stupidity In Autonomous Vehicles, Steven Umbrello, Roman V. Yampolskiy
Designing Ai For Explainability And Verifiability: A Value Sensitive Design Approach To Avoid Artificial Stupidity In Autonomous Vehicles, Steven Umbrello, Roman V. Yampolskiy
Faculty Scholarship
One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents. This paper explores how decision matrix algorithms, via the belief-desire-intention model for autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for …
Transdisciplinary Ai Observatory—Retrospective Analyses And Future-Oriented Contradistinctions, Nadisha Marie Aliman, Leon Kester, Roman Yampolskiy
Transdisciplinary Ai Observatory—Retrospective Analyses And Future-Oriented Contradistinctions, Nadisha Marie Aliman, Leon Kester, Roman Yampolskiy
Faculty Scholarship
In the last years, artificial intelligence (AI) safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently transdisciplinary AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing concrete practical examples. Distinguishing between unintentionally and intentionally triggered AI risks with diverse socio-psycho-technological impacts, we exemplify a retrospective descriptive analysis followed by a retrospective counterfactual risk analysis. Building on …
Telelocomotion—Remotely Operated Legged Robots, Kevin Huang, Divas Subedi, Rahul Mitra, Isabella Yung, Kirkland Boyd, Edwin Aldrich, Digesh Chitrakar
Telelocomotion—Remotely Operated Legged Robots, Kevin Huang, Divas Subedi, Rahul Mitra, Isabella Yung, Kirkland Boyd, Edwin Aldrich, Digesh Chitrakar
Faculty Scholarship
© 2020 by the authors. Li-censee MDPI, Basel, Switzerland. Teleoperated systems enable human control of robotic proxies and are particularly amenable to inaccessible environments unsuitable for autonomy. Examples include emergency response, underwater manipulation, and robot assisted minimally invasive surgery. However, teleoperation architectures have been predominantly employed in manipulation tasks, and are thus only useful when the robot is within reach of the task. This work introduces the idea of extending teleoperation to enable online human remote control of legged robots, or telelocomotion, to traverse challenging terrain. Traversing unpredictable terrain remains a challenge for autonomous legged locomotion, as demonstrated by robots …
Non-Invasive Measure Of Stenosis Severity Through Spectral Analysis [Post-Print], Clayton P. Byers, Alexandra Sinson, Colette Scheffers, Taikang Ning
Non-Invasive Measure Of Stenosis Severity Through Spectral Analysis [Post-Print], Clayton P. Byers, Alexandra Sinson, Colette Scheffers, Taikang Ning
Faculty Scholarship
A preliminary study on the effect of stenosis severity in a restricted flow is performed through the spectral analysis of sound signals. A model pulsatile flow that uses differing area reductions through an opening was employed, where contact microphones secured outside of the reduction measured the sound intensity in the flow. A spectral analysis shows the narrowing results in increased magnitude of frequencies in the range of 15 to 170Hz, with different narrowing cases resulting in different peak frequencies. Low frequency content up to 10 Hz remains approximately unchanged. This simplistic approach of signal processing forms a basis for enhanced …
Improving Student Preparedness For Entering The Workforce: A Hands-On Experience In Project Management For A Graduate-Level Protein Engineering Class, Nuttanit Pramounmat, Julie N. Renner
Improving Student Preparedness For Entering The Workforce: A Hands-On Experience In Project Management For A Graduate-Level Protein Engineering Class, Nuttanit Pramounmat, Julie N. Renner
Faculty Scholarship
A hands-on polypeptide engineering experience that focuses on project management was developed and incorporated in a graduate-level course. The goal was to have doctoral students in chemical engineering learn about project planning tools, and experience what it might be like to plan and execute a project in industry or business. The motivation behind this goal was to help students best-utilize their technical skills in the private sector, where 42% of doctoral recipients in science and engineering work.
Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong
Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong
Faculty Scholarship
To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Faculty Scholarship
AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. The data science community has to work on collecting and aggregating such data in a common and widely available format, so that any AI researcher can easily look up the applicable limit measurements for their latest project. AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. Data science community has to work on collecting and …
The Sounds Of Science - A Symphony For Many Instruments And Voices, Gerianne Alexander, Roland E. Allen, Anthony Atala, Warwick P. Bowen, Alan A. Coley, John B. Goodenough, Mikhail I. Katsnelson, Eugene V. Koonin, Mario Krenn, Lars S. Madsen, Martin Månsson, Nicolas P. Mauranyapin, Art I. Melvin, Ernst Rasel, Linda E. Reichl, Roman Yampolskiy, Philip B. Yasskin, Anton Zeilinger, Suzy Lidström
The Sounds Of Science - A Symphony For Many Instruments And Voices, Gerianne Alexander, Roland E. Allen, Anthony Atala, Warwick P. Bowen, Alan A. Coley, John B. Goodenough, Mikhail I. Katsnelson, Eugene V. Koonin, Mario Krenn, Lars S. Madsen, Martin Månsson, Nicolas P. Mauranyapin, Art I. Melvin, Ernst Rasel, Linda E. Reichl, Roman Yampolskiy, Philip B. Yasskin, Anton Zeilinger, Suzy Lidström
Faculty Scholarship
Sounds of Science is the first movement of a symphony for many (scientific) instruments and voices, united in celebration of the frontiers of science and intended for a general audience. John Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium-ion battery, opens the programme, reflecting on the ultimate limits of battery technology. This applied theme continues through the subsequent pieces on energy-related topics - the sodium-ion battery and artificial fuels, by Martin Månsson - and the ultimate challenge for 3D printing, the eventual production of life, by Anthony Atala. A passage by Gerianne Alexander …
Modeling And Counteracting Exposure Bias In Recommender Systems, Sami Khenissi, Olfa Nasraoui
Modeling And Counteracting Exposure Bias In Recommender Systems, Sami Khenissi, Olfa Nasraoui
Faculty Scholarship
What we discover and see online, and consequently our opinions and decisions, are becoming increasingly affected by automated machine learned predictions. Similarly, the predictive accuracy of learning machines heavily depends on the feedback data that we provide them. This mutual influence can lead to closed-loop interactions that may cause unknown biases which can be exacerbated after several iterations of machine learning predictions and user feedback. Machine-caused biases risk leading to undesirable social effects ranging from polarization to unfairness and filter bubbles. In this paper, we study the bias inherent in widely used recommendation strategies such as matrix factorization. Then we …
Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui
Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui
Faculty Scholarship
State of the art music recommender systems mainly rely on either matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction by learning from temporal sequences of user actions. Despite advances in deep learning for song recommendation, none has taken advantage of the sequential nature of songs by learning sequence models that are based on content. Aside from the importance of prediction accuracy, other significant aspects are important, such as explainability and solving the cold start problem. In this work, we propose a hybrid deep learning …
New Insights Into Anhydrobiosis Using Cellular Dielectrophoresis-Based Characterization, Mohamed Z. Rashed, Clinton J. Belott, Brett R. Janis, Michael Menze, Stuart J. Williams
New Insights Into Anhydrobiosis Using Cellular Dielectrophoresis-Based Characterization, Mohamed Z. Rashed, Clinton J. Belott, Brett R. Janis, Michael Menze, Stuart J. Williams
Faculty Scholarship
Late embryogenesis abundant (LEA) proteins are found in desiccation-tolerant species from all domains of life. Despite several decades of investigation, the molecular mechanisms by which LEA proteins confer desiccation tolerance are still unclear. In this study, dielectrophoresis (DEP) was used to determine the electrical properties of Drosophila melanogaster (Kc167) cells ectopically expressing LEA proteins from the anhydrobiotic brine shrimp, Artemia franciscana. Dielectrophoresis-based characterization data demonstrate that the expression of two different LEA proteins, AfrLEA3m and AfrLEA6, increases cytoplasmic conductivity of Kc167 cells to a similar extent above control values. The impact on cytoplasmic conductivity was surprising, given …
Evaluation Of Haptic Guidance Virtual Fixtures And 3d Visualization Methods In Telemanipulation—A User Study, Kevin Huang, Digesh Chitrakar, Fredrik Rydén, Howard Jay Chizeck
Evaluation Of Haptic Guidance Virtual Fixtures And 3d Visualization Methods In Telemanipulation—A User Study, Kevin Huang, Digesh Chitrakar, Fredrik Rydén, Howard Jay Chizeck
Faculty Scholarship
© 2019, The Author(s). This work presents a user-study evaluation of various visual and haptic feedback modes on a real telemanipulation platform. Of particular interest is the potential for haptic guidance virtual fixtures and 3D-mapping techniques to enhance efficiency and awareness in a simple teleoperated valve turn task. An RGB-Depth camera is used to gather real-time color and geometric data of the remote scene, and the operator is presented with either a monocular color video stream, a 3D-mapping voxel representation of the remote scene, or the ability to place a haptic guidance virtual fixture to help complete the telemanipulation task. …
Data-Driven I–V Feature Extraction For Photovoltaic Modules, Xuan Ma, Wei-Heng Huang, Jenny Brynjarsdottir, Jennifer L. Braid, Roger H. French
Data-Driven I–V Feature Extraction For Photovoltaic Modules, Xuan Ma, Wei-Heng Huang, Jenny Brynjarsdottir, Jennifer L. Braid, Roger H. French
Faculty Scholarship
In research on photovoltaic (PV) device degradation, current-voltage (I-V ) datasets carry a large amount of information in addition to the maximum power point. Performance parameters such as short-circuit current, open-circuit voltage, shunt resistance, series resistance, and fill factor are essential for diagnosing the performance and degradation of solar cells and modules. To enable the scaling of I-V studies to millions of I-V curves, we have developed a data-driven method to extract I-V curve parameters and distributed this method as an open-source package in R. In contrast with the traditional practice of fitting the diode equation to I-V curves individually, …
Mining Semantic Knowledge Graphs To Add Explainability To Black Box Recommender Systems, Mohammed Alshammari, Olfa Nasraoui, Scott Sanders
Mining Semantic Knowledge Graphs To Add Explainability To Black Box Recommender Systems, Mohammed Alshammari, Olfa Nasraoui, Scott Sanders
Faculty Scholarship
Recommender systems are being increasingly used to predict the preferences of users on online platforms and recommend relevant options that help them cope with information overload. In particular, modern model-based collaborative filtering algorithms, such as latent factor models, are considered state-of-the-art in recommendation systems. Unfortunately, these black box systems lack transparency, as they provide little information about the reasoning behind their predictions. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less accurate than sophisticated black box models. Recent research has demonstrated that explanations are an essential component in bringing the powerful predictions of …
Debiasing The Human-Recommender System Feedback Loop In Collaborative Filtering, Wenlong Sun, Sami Khenissi, Olfa Nasraoui, Patrick Shafto
Debiasing The Human-Recommender System Feedback Loop In Collaborative Filtering, Wenlong Sun, Sami Khenissi, Olfa Nasraoui, Patrick Shafto
Faculty Scholarship
Recommender Systems (RSs) are widely used to help online users discover products, books, news, music, movies, courses, restaurants,etc. Because a traditional recommendation strategy always shows the most relevant items (thus with highest predicted rating), traditional RS’s are expected to make popular items become even more popular and non-popular items become even less popular which in turn further divides the haves (popular) from the have-nots (un-popular). Therefore, a major problem with RSs is that they may introduce biases affecting the exposure of items, thus creating a popularity divide of items during the feedback loop that occurs with users, and this may …