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Articles 3361 - 3390 of 63093
Full-Text Articles in Entire DC Network
A Longitudinal Analysis Of Morphological Shape Variation Of Spleen In Patients With Fontan Surgery, Varatharajan Nainamalai, Håvard Bjørke Jenssen, Mostafa Rezaeitaleshmahalleh, Djinaud Prophete, Jordan Gosnell, Sarah Khan, Marcus Haw, Jingfeng Jiang, Joseph Vettukattil
A Longitudinal Analysis Of Morphological Shape Variation Of Spleen In Patients With Fontan Surgery, Varatharajan Nainamalai, Håvard Bjørke Jenssen, Mostafa Rezaeitaleshmahalleh, Djinaud Prophete, Jordan Gosnell, Sarah Khan, Marcus Haw, Jingfeng Jiang, Joseph Vettukattil
Michigan Tech Publications
Background: Splenic size serves as a surrogate biomarker for predicting portal vein hyper-tension and liver abnormalities in subjects with Fontan Associated Liver Disease (FALD). We analyze the long-term shape variation of the spleen in FALD subjects using morphological shape features of radiomic features. Methods: We used 154 (84 from computed tomography and 70 from magnetic resonance) image volumes obtained from 36 individuals who underwent stage 3 Fontan procedure and 145 computed tomography images from controls to assess splenomegaly. To understand the splenomegaly, thirteen shape features of the spleen over three 10-year intervals, and variations between controls and FALD subjects were …
Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha
Towards Sustainable Community-Designed Ai Systems In The Public Sector, Victoria Chui, Kelly Mcconvey, Erina Seh-Young Moon, Maya Ghai, Shion Guha
Health Services and Informatics Research
Advancements in data-driven modeling and artificial intelligence applications in public sector settings can lead to increased ten sions between stakeholder needs and tangible model capabilities from developers. Engaging multiple stakeholder groups in model development through the gleaning of sociotechnical, theoretical in sights using qualitative methods can contribute to more impactful, beneficial model solutions. Qualitative methods can complement quantitative model development, emphasizing stakeholder priori ties, informing model design choices, and promoting sustainable connections and model longevity. We are excited to discuss human centered qualitative methods, sustainable modeling practices, and community engagement in this workshop, engaging with scholars on system-level modeling strategies.
A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz
A Comprehensive Deep Learning System With Mgrf Modeling For Predicting Breast Cancer Response To Neoadjuvant Chemotherapy, Ahmed Sharafeldeen, Fatma Taher, Norah Saleh Alghamdi, Eman Alnaghy, Reham Alghandour, Khadiga M. Ali, Sameh Shamaa, Abdelrahman Gamal, Mohammed Ghazal, Sohail Contractor, Ayman El-Baz
All Works
Accurate prediction of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) is critical for tailoring treatment strategies and improving patient outcomes. This study introduces a novel deep learning-based framework that integrates multi-parametric magnetic resonance imaging (MRI) (i.e., T1, T2, STIR, and DWI), along with clinical and molecular subtype markers, to classify tumor response into pathological complete response (pCR), partial response (PR), and stable disease (SD). First, tumor regions are delineated across MRI modalities and then modeled using a translation-invariant Markov-Gibbs random field (MGRF) with analytical parameter estimation to capture modality-specific spatial appearance patterns correlated with NAC response. Subsequently, diffusion-weighted MRI …
Zeus: Zero-Shot Llm Instruction For Union Segmentation In Multimodal Medical Imaging, Siyuan Dai, Kai Ye, Guodong Liu, Haoteng Tang, Liang Zhan
Zeus: Zero-Shot Llm Instruction For Union Segmentation In Multimodal Medical Imaging, Siyuan Dai, Kai Ye, Guodong Liu, Haoteng Tang, Liang Zhan
Computer Science Faculty Publications
Medical image segmentation has achieved remarkable success through the continuous advancement of UNet-based and Transformer-based foundation backbones. However, clinical diagnosis in the real world often requires integrating domain knowledge, especially textual information. Conducting multimodal learning involves visual and text modalities shown as a solution, but collecting paired vision-language datasets is expensive and time-consuming, posing significant challenges. Inspired by the superior ability in numerous cross-modal tasks for Large Language Models (LLMs), we proposed a novel Vision-LLM union framework to address the issues. Specifically, we introduce frozen LLMs for zero-shot instruction generation based on corresponding medical images, imitating the radiology scanning and …
Strengthening Scientific Integrity: Digital Forensics For Biomedical Research Imaging, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha
Strengthening Scientific Integrity: Digital Forensics For Biomedical Research Imaging, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha
Computer Science: Faculty Publications and Other Works
To fight against the increasing misconduct cases in science, this Ph. D. research confronted the challenge of scientific integrity with a pioneering investigation into digital forensic analysis specifically tailored for biomedical images. This work conducted extensive research into key manipulation types–copy-move forgery, image reuse, and AI-generated content–developing novel, fully explainable, and auditable computational detection methods for each. In a commitment to transparency and to promote research to the area, these techniques are provided as open-source resources. Besides the isolated techniques for each type of image forged, a central contribution is the development of an end-to-end system, created through collaboration with …
Research On Policy Representation In Deep Reinforcement Learning, Zhen Chen, Zhuoyi Wu, Lin Zhang
Research On Policy Representation In Deep Reinforcement Learning, Zhen Chen, Zhuoyi Wu, Lin Zhang
Journal of System Simulation
Abstract: Deep reinforcement learning (DRL) has achieved remarkable success in various domains. Nevertheless, existing policy networks in DRL still face significant challenges in areas such as generalizability, multi-task adaptability, and sample efficiency. Policy representation, as a crucial research direction for enhancing DRL capabilities, aims to improve an agent's adaptability to environmental changes and novel tasks by constructing more efficient and generalizable forms of policy expression. This paper provided a concise overview of key research advances in the field of policy representation. It introduced diverse policy architectures, ranging from traditional multi-layer perceptron (MLP) -based policies to those based on pointer networks, …
A Web Application For Generating Argument Maps For Essays Using Llms, Alexis R. Chalmers
A Web Application For Generating Argument Maps For Essays Using Llms, Alexis R. Chalmers
Theses
Argumentative writing is a critical skill that strengthens students’ reasoning, communication, and analytical abilities. However, maintaining a clear and organized argument structure while writing can be challenging. Argument maps — visual diagrams which explicitly show an argument’s structure — have been shown to improve students’ writing, but are rarely used outside of the planning stage of an essay due to the time and effort required to create them. Automatically generating argument maps from student essays helps students to evaluate the structure of their argument as they write and makes identifying unsupported claims visible. To evaluate whether large language models (LLMs) …
Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang
Thinking On Simulation Science And Engineering In The Era Of Artificial Intelligence, Wenhui Fan, Yuan Jiang
Journal of System Simulation
Abstract: With the rapid advancement of artificial intelligence and computing technologies, simulation technologies have leapfrogged, propelling the discipline of simulation toward greater maturity. Research progress in computer simulation technologies both in China and abroad was reviewed, and the definition and connotation of simulation were clarified. It was proposed that the Chinese terms "仿真" "仿效"and " 模拟" be unified under a single term " 仿真" with corresponding "Simulation" "Emulation" and "Analog" in English translated uniformly as "Simulation". Simulation science and engineering discipline was delineated, which was grounded in three core theoretical foundations: analogical theory,computational theory, and model validation theory. The first-level …
Research Review Of Intelligent Navigation Simulation Technology And Its Applications, Tao Liu, Hanxi Li, Yong Yin, Jialun Liu
Research Review Of Intelligent Navigation Simulation Technology And Its Applications, Tao Liu, Hanxi Li, Yong Yin, Jialun Liu
Journal of System Simulation
Abstract:Navigation simulation develops models of ship navigation environments and behavior to simulate ship responses under various scenarios, enabling the prediction of ship behavior under complex and disturbing conditions. With the development of computer graphics, virtual reality, and artificial intelligence technologies in recent years, especially the development of unmanned ship technology, new research topics and applications have emerged in navigation simulation technology. This paper introduced the current research status and development trends of navigation simulation technology and reviewed it from three aspects: typical scenarios, key technologies, and development trends. The development trends and key points of multi-dimensional electronic navigation charts, …
Current Situation Of Simulation Course Offerings In Colleges And Universities In China And Abroad, Xiaogang Qiu, Zhengqiu Zhu, Kai Xu, Guanghong Gong
Current Situation Of Simulation Course Offerings In Colleges And Universities In China And Abroad, Xiaogang Qiu, Zhengqiu Zhu, Kai Xu, Guanghong Gong
Journal of System Simulation
Abstract: As fundamental teaching units, courses serve as vital carriers of disciplinary knowledge transmission and critical bridges for converting research outcomes into educational content. The construction of simulation courses plays a pivotal role in developing the simulation discipline. The inaugural "Intelligence+ " symposium on simulation discipline and specialty construction focused on exploring the current state of simulation courses and pedagogy in China while examining future development directions. This report presented the key findings and discussions from the symposium regarding simulation courses and pedagogy. The analysis covered four parts: first, an overview of simulation course offerings and characteristics at European and …
Research On Requirements And Methods For Intelligent Assessment Of Simulation Credibility, Bingheng Wang, Tingrui Liu, Fan Yang, Huan Zhang, Wei Li, Ping Ma, Ming Yang
Research On Requirements And Methods For Intelligent Assessment Of Simulation Credibility, Bingheng Wang, Tingrui Liu, Fan Yang, Huan Zhang, Wei Li, Ping Ma, Ming Yang
Journal of System Simulation
Abstract: The accuracy of simulations in representing real-world systems is a critical concern for users. Simulation credibility assessment ensures trustworthiness by evaluating the correctness and effectiveness of simulations to meet application requirements. As simulation technologies are widely adopted, and new simulation paradigms emerge, traditional assessment methods are increasingly showing limitations in their dependence on experts, data processing capabilities, and assessment efficiency. This paper systematically reviewed the research demands, current progress, new technologies, and future trends of intelligent simulation credibility assessment. Based on the simulation credibility assessment process and problem analysis, the requirements for intelligent credibility assessment were discussed. Intelligent technologies …
Optimization And Simulation Of Adaptive Production Scheduling Based On Hybrid Decision-Making Mechanism, Zhicheng Ji, Zhen Quan, Yan Wang
Optimization And Simulation Of Adaptive Production Scheduling Based On Hybrid Decision-Making Mechanism, Zhicheng Ji, Zhen Quan, Yan Wang
Journal of System Simulation
Abstract: To optimize flexible production scheduling with the objectives of the longest makespan, mean tardiness, and bottleneck machine processing load rate, a hybrid decision-making mechanism scheduling algorithm was proposed based on the decision complexity and constraint characteristics of machine assignment and task sequencing. The algorithm adopted a two-dimensional chromosome to encode machine assignment and a heuristic rule to evaluate task sequencing priority, enhancing the adaptability of the method to decision-making optimization. In order to further improve the performance of the proposed scheduling method, an adaptive rule strategy was designed based on the distribution of processing time required for waiting scheduling …
Research On Simulation Training Technology For Special Vehicle Command Based On Gesture Behavior Cognition Interaction, Xiangyang Li, Zhili Zhang, Rui Wang, Xiao Wang, Cheng Chi
Research On Simulation Training Technology For Special Vehicle Command Based On Gesture Behavior Cognition Interaction, Xiangyang Li, Zhili Zhang, Rui Wang, Xiao Wang, Cheng Chi
Journal of System Simulation
Abstract: To overcome the practical shortcomings in the driving command training of special vehicles, a simulation training technology framework based on gesture behavior cognition and command interaction was proposed. A somatosensory interactive motion capture device and human skeleton model were used to conduct the real-time dynamic recognition and spatial coordinate transformation of the gesture actions of the command training personnel. The median filtering method was applied to eliminate the abrupt data and random noise. The spatial coordinates were processed consistently by using the human skeleton centralization and normalization method. Based on the command gesture action behavior model library and the …
Dynamic Data Driven Simulation Based On Macro-Microscopic Hierarchical Simulation Models, Xu Xie, Yuqing Ma
Dynamic Data Driven Simulation Based On Macro-Microscopic Hierarchical Simulation Models, Xu Xie, Yuqing Ma
Journal of System Simulation
Abstract:This paper proposed a dynamic data driven simulation approach based on macro-microscopic hierarchical simulation models. This approach enabled the measurement data from the real system to affect the macroscopic simulation and microscopic simulation in sequence and made the two simulations evolve together so that it could provide decision makers with the state evolution prediction of the real system at the macroscopic level to assist decision making and provide a microscopic testbed similar to the real system, on which decision makers could deduce and evaluate their strategies. This paper established a formal description of the approach and designed a data …
Research On High-Performance Optimization Methods For Fastdds In Heterogeneous Real-Time Simulation, Congping Liu, Wei Song, Jian Fang, Fei Liu
Research On High-Performance Optimization Methods For Fastdds In Heterogeneous Real-Time Simulation, Congping Liu, Wei Song, Jian Fang, Fei Liu
Journal of System Simulation
Abstract:FastDDS faces limitations under high-frequency data streams, such as lock contention, performance overhead from frequent context switching, and configuration complexity of multiple nodes under strict real-time constraints, which affect the experimental efficiency. This paper proposed a performance optimization method based on a batch-scalable circular queue (BSCQ). The approach replaced the traditional mutex mechanism with a lock-free algorithm to reduce lock contention and avoid deadlocks, while batch processing improved data locality, cache hit rates, and memory utilization, effectively reducing data transmission delay and improving system throughput. Hazard pointers were introduced to ensure safe memory management during batch processing and eliminate …
Reflections On Innovative Approaches To Autonomous Simulation Software, Feng Tian
Reflections On Innovative Approaches To Autonomous Simulation Software, Feng Tian
Journal of System Simulation
Abstract: Given China's weak foundation in simulation software, simply replicating the development paths of these global leading companies offers limited potential for leapfrog development. Based on an analysis of pitfalls in the independent innovation of domestic simulation software, this paper proposed and elaborated on six strategic approaches: avoiding established paths, aligning with national realities, pursuing extreme performance, leveraging special needs to advance technology, building new systems from the ground up, and embracing artificial intelligence (AI)-native architectures. These strategies aim to provide new perspectives for the independent innovation and development of domestic simulation software.
Reliability Simulation Testing And Verification Technologies For Intelligent Systems: Frontiers, Progress, And Challenges, Zili Wang, Yuntian Gao, Dezhen Yang, Yeyang Liu, Yi Ren
Reliability Simulation Testing And Verification Technologies For Intelligent Systems: Frontiers, Progress, And Challenges, Zili Wang, Yuntian Gao, Dezhen Yang, Yeyang Liu, Yi Ren
Journal of System Simulation
Abstract: Intelligent systems are extensively deployed in domains such as transportation, energy and water resources, smart healthcare, and aerospace, where their reliability is directly linked to public safety and social stability, thus requiring thorough and scientifically rigorous verification. This article conducted an in-depth exploration of the current state of reliability simulation and verification techniques for intelligent systems. It defined the concept of reliability specific to intelligent systems and identified key challenges they face in areas including mission scenario modeling, characteristic modeling and simulation, evaluation and verification, and simulation platforms. Future development requirements were proposed to guide research toward more trustworthy, …
Modeling And Simulation Of Complex Systems Based On Graph Neural Networks, Jinhu Lü, Hongyi Jiang, Deyuan Liu, Shaolin Tan
Modeling And Simulation Of Complex Systems Based On Graph Neural Networks, Jinhu Lü, Hongyi Jiang, Deyuan Liu, Shaolin Tan
Journal of System Simulation
Abstract: Modeling and simulation of complex systems are critical issues for understanding their structural and functional properties. The ability of graph neural networks (GNNs) to learn and represent the internal correlations within data provides a new approach for modeling and simulating complex systems. Currently, there are various types of GNN models involving frequency-domain, spatial-domain, generative, heterogeneous, and spatio-temporal models. These models are widely applied in complex system modeling and simulation research in multiple fields such as industrial internet, social networks, and supply chains based on specific tasks and scenarios. Starting from three representative tasks: network topology representation, dynamic evolution modeling, …
Intelligent Transition Of Automotive Industry Driven By Autonomous Driving Simulation Testing Technology, Jianping Wu, Guanzhou Li, Shuai Zhao, Ling Huang
Intelligent Transition Of Automotive Industry Driven By Autonomous Driving Simulation Testing Technology, Jianping Wu, Guanzhou Li, Shuai Zhao, Ling Huang
Journal of System Simulation
Abstract: As a pivotal approach supporting the safety verification and commercial implementation of intelligent driving systems, autonomous driving simulation testing has achieved remarkable progress in technical methodologies and application scenarios. Conventional real-world road testing faces critical limitations including prohibitive costs, inadequate coverage of corner case scenarios, and efficiency bottlenecks, rendering it insufficient for safety validation of high-level autonomous driving systems (L4 and above). To address these challenges, simulation testing frameworks have evolved into a multi-layered verification system encompassing mathematical modeling, virtual scenarios, hardware-in-the-loop (HIL), mixed reality, and cloud-based simulation clusters. Specifically, mathematical modeling accelerates algorithm development; virtual scenario simulation enhances …
A Review Of Intelligent Generation Of Combat Simulation Scenarios, Zhiming Dong, Zhongqi Hu, Zhaoyang Liu, Heyang Zhou
A Review Of Intelligent Generation Of Combat Simulation Scenarios, Zhiming Dong, Zhongqi Hu, Zhaoyang Liu, Heyang Zhou
Journal of System Simulation
Abstract: In order to improve the efficiency of combat simulation, this paper provided a theoretical reference for the research on the intelligent generation of combat simulation scenarios. It systematically reviewed the intelligent generation methods of combat simulation scenarios based on large language models (LLMs). It began by introducing the basic content of combat simulation scenarios, analyzed the shortcomings of current mainstream scenario generation methods, and discussed how to leverage LLMs to address these issues. Next, it outlined the application paradigms and key supporting technologies for the intelligent generation of combat simulation scenarios based on LLMs. Finally, it pointed out the …
Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, And Case Study, Yongkui Liu, Kang Yang, Benben Tuo, Yaduo Pan, Xinyu Wang, Yihan Wang, Yongqian Gong, Lin Zhang, Lihui Wang, Tingyu Lin, Bin Zi, Yuan Li, Wei You, Xun Xu
Digital Twinned Industrial Robot: Conceptual Framework, Key Technologies, And Case Study, Yongkui Liu, Kang Yang, Benben Tuo, Yaduo Pan, Xinyu Wang, Yihan Wang, Yongqian Gong, Lin Zhang, Lihui Wang, Tingyu Lin, Bin Zi, Yuan Li, Wei You, Xun Xu
Journal of System Simulation
Abstract: To effectively enhance the value and full life cycle management level of industrial robots, this paper integrated deeply digital twin with industrial robots and discussed a new concept, namely digital twinned industrial robot (DTIR). It defined the concept, composition, and typical characteristics of DTIRs and proposed their system architecture. From the perspective of the full life cycle of "design, manufacturing, operation and maintenance, and decommissioning", the key technologies of DTIRs were systematically sorted out. Furthermore, the validity of the proposed conceptual framework was verified through a case study. Finally, the paper summarized the findings and discussed the future development …
Large-Scale Social Simulator: Frontiers And Perspectives, Jinghua Piao, Chen Gao, Fang Zhang, Jun Su, Yong Li
Large-Scale Social Simulator: Frontiers And Perspectives, Jinghua Piao, Chen Gao, Fang Zhang, Jun Su, Yong Li
Journal of System Simulation
Abstract: Social experiments, as a typical research method in social sciences, aim to study specific social phenomena or the impacts of policies by observing the behaviors of individuals, organizations, or social groups in real or simulated environments. However, traditional social experiment methods often face challenges such as random bias, high costs, and ethical risks, making them inadequate to address increasingly complex research demands. Against this backdrop, computational social experiments have emerged, enabling researchers to conduct social experiments within computational simulation environments that are free from random bias, cost-efficient, and ethically manageable. Meanwhile, China is currently undergoing a critical period of …
Combat-Oriented Comprehensive Simulation And Verification Technology For Equipment System Rms, Yue Zhang, Wenliang Zhang, Qiang Feng, Xing Guo, Yi Ren, Zili Wang
Combat-Oriented Comprehensive Simulation And Verification Technology For Equipment System Rms, Yue Zhang, Wenliang Zhang, Qiang Feng, Xing Guo, Yi Ren, Zili Wang
Journal of System Simulation
Abstract:Existing reliability maintainability supportability (RMS) simulation and verification methods for equipment systems are typically conducted under standard conditions and suffer from weak combat environments and task modeling capabilities. To address this limitation, a multi-agent RMS simulation and verification framework was proposed. Key breakthroughs included agent modeling techniques for complex environments and variable tasks, interaction mechanisms among environmental agents, task agents, equipment, and support systems, and a simulation-based comprehensive RMS evaluation method. Case studies demonstrate that the proposed method effectively models complex environments and variable tasks, supports combat-oriented simulation and verification and design scheme evaluation, and meets combat-ready development requirements.
Multi-Scenario Multi-Satellite Mission Planning Method Based On Adaptive Large Neighborhood Search, Xiutian Li, Ling Wang, Yingwu Chen, Lining Xing, Yingguo Chen
Multi-Scenario Multi-Satellite Mission Planning Method Based On Adaptive Large Neighborhood Search, Xiutian Li, Ling Wang, Yingwu Chen, Lining Xing, Yingguo Chen
Journal of System Simulation
Abstract: To further improve the execution efficiency of remote sensing satellites, an integrated optimization framework combining adaptive large neighborhood search (ALNS) and a constraint programming-boolean satisfiability problem (CP-SAT) solver monitor was proposed, addressing the challenges of complex constraints, dynamic scale, and resource heterogeneity in multi-scenario multi-satellite mission planning. A unified multi-objective mixed-integer programming model was established, coupling heterogeneous constraints of point targets and area tasks. A time-domain rolling mechanism dynamically decomposed the problem scale, and a priority screening strategy enhanced the search efficiency of ALNS. Solution feasibility was verified in real time through the CP-SAT monitor. Results show that compared …
What Drives Weight Status Among Female University Students? A Machine Learning Analysis Of Sociodemographic, Dietary, And Lifestyle Determinants, Radwan Qasrawi, Abir Ajab, Leila Cheikh Ismail, Ayesha Al Dhaheri, Sharifa Alblooshi, Razan Abu Ghoush, Stephanny Vicuna Polo, Malak Amro, Suliman Thwib, Ghada Issa, Haleama Al Sabbah
What Drives Weight Status Among Female University Students? A Machine Learning Analysis Of Sociodemographic, Dietary, And Lifestyle Determinants, Radwan Qasrawi, Abir Ajab, Leila Cheikh Ismail, Ayesha Al Dhaheri, Sharifa Alblooshi, Razan Abu Ghoush, Stephanny Vicuna Polo, Malak Amro, Suliman Thwib, Ghada Issa, Haleama Al Sabbah
All Works
Background: Obesity and underweight are increasingly common among young adult women, often resulting from complex interactions between diet, lifestyle, and socioeconomic factors. This study addresses that gap by applying machine learning to a wide range of behavioral, dietary, and demographic data. The main research question asks: What are the key factors influencing weight status among female university students, and how accurately can machine learning models identify them? We hypothesize that different factors are significantly associated with underweight, overweight, and obesity, and that machine learning can reliably detect these patterns. The aim is to identify the strongest predictors and support more …
Ai Project Facilitation Guidance For Research Computing And Data (Rcd) Professionals, Anna Alber, Laura Briggs, Paul Brunk, Manasvita Joshi, Atish P. Kamble, Amira Kefi, Timothy Middelkoop, Semir Sarajlic, Ana Maria Sokovic, Jeffrey N. Valdez, Ying Zhang
Ai Project Facilitation Guidance For Research Computing And Data (Rcd) Professionals, Anna Alber, Laura Briggs, Paul Brunk, Manasvita Joshi, Atish P. Kamble, Amira Kefi, Timothy Middelkoop, Semir Sarajlic, Ana Maria Sokovic, Jeffrey N. Valdez, Ying Zhang
Administration and Staff Articles and Research
The role of Artificial Intelligence (AI) in research and education continues to rapidly grow, resulting in increased collaboration between researchers in AI and Research Computing and Data (RCD) professionals to meet the research and teaching demands. RCD professionals bridge the gap between research and technology by guiding and collaborating with researchers and educators through the process of selecting the hardware, software, and services best suited for executing their AI projects. This includes ensuring compliance with funding and regulatory requirements across the entire lifecycle of the project. In this paper, we present an overview of the AI project lifecycle and how …
Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai
Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai
Pepperdine Dispute Resolution Law Journal
Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …
Detecting Android Malware Based On Static Analysis Using Classification And Modified Clustering Techniques, Abdullah Allawi Al-Sraratee, Ahmed Habeeb Al-Azawei
Detecting Android Malware Based On Static Analysis Using Classification And Modified Clustering Techniques, Abdullah Allawi Al-Sraratee, Ahmed Habeeb Al-Azawei
Journal of Intelligent Informatics, Networking, and Cybersecurity
Because Android malware harms internet security, prior research proposes several different approaches to detect it accurately. However, such proposed models depend on numerous number of features to attain high accuracy. This could lead to high computation cost and potential overfitting. Furthermore, manual data labeling is labor-intensive, requiring significant human effort and skills. This research aims to: 1) extend previous literature on Android malware detection, 2) improve the accuracy of Android malware detection based on a low number of features, and 3) modify a clustering technique to group data into two different clusters to address the issue of unlabeled data. To …
Identifying The Desired Word Suggestion In Simultaneous Audio, Dylan Gaines, Keith Vertanen
Identifying The Desired Word Suggestion In Simultaneous Audio, Dylan Gaines, Keith Vertanen
Michigan Tech Publications
We explore a method for presenting word suggestions for non-visual text input using simultaneous voices. We conduct two perceptual studies and investigate the impact of different presentations of voices on a user's ability to detect which voice, if any, spoke their desired word. Our sets of words simulated the word suggestions of a predictive keyboard during real-world text input. We find that when voices are simultaneous, user accuracy decreases significantly with each added word suggestion. However, adding a slight 0.15 s delay between the start of each subsequent word allows two simultaneous words to be presented with no significant decrease …
Perceptions Of Blind Adults On Non-Visual Mobile Text Entry, Dylan Gaines, Keith Vertanen
Perceptions Of Blind Adults On Non-Visual Mobile Text Entry, Dylan Gaines, Keith Vertanen
Michigan Tech Publications
Text input on mobile devices without physical keys can be challenging for people who are blind or low-vision. We interview 12 blind adults about their experiences with current mobile text input to provide insights into what sorts of interface improvements may be the most beneficial. We identify three primary themes that were experiences or opinions shared by participants: the poor accuracy of dictation, difficulty entering text in noisy environments, and difficulty correcting errors in entered text. We also discuss an experimental non-visual text input method with each participant to solicit opinions on the method and probe their willingness to learn …