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Articles 31 - 60 of 978
Full-Text Articles in Engineering
Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian
Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian
Engineering Faculty Articles and Research
Hearing children of Deaf adults (CODAs) face many challenges including having difficulty learning spoken languages, experiencing social judgment, and encountering greater responsibilities at home. In this paper, we present a proposal for a smart display application called Let's Read that aims to support CODAs when learning spoken language. We conducted a qualitative analysis using online community content in English to develop the first version of the prototype. Then, we conducted a heuristic evaluation to improve the proposed prototype. As future work, we plan to use this prototype to conduct participatory design sessions with Deaf adults and CODAs to evaluate the …
Deep Learning Predicts Ebv Status In Gastric Cancer Based On Spatial Patterns Of Lymphocyte Infiltration, Baoyi Zhang, Kevin Yao, Min Xu, Jia Wu, Chao Cheng
Deep Learning Predicts Ebv Status In Gastric Cancer Based On Spatial Patterns Of Lymphocyte Infiltration, Baoyi Zhang, Kevin Yao, Min Xu, Jia Wu, Chao Cheng
Computer Vision Faculty Publications
EBV infection occurs in around 10% of gastric cancer cases and represents a distinct subtype, characterized by a unique mutation profile, hypermethylation, and overexpression of PD-L1. Moreover, EBV positive gastric cancer tends to have higher immune infiltration and a better prognosis. EBV infection status in gastric cancer is most commonly determined using PCR and in situ hybridization, but such a method requires good nucleic acid preservation. Detection of EBV status with histopathology images may complement PCR and in situ hybridization as a first step of EBV infection assessment. Here, we developed a deep learning-based algorithm to directly predict EBV infection …
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Computer Science Faculty Research
The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …
Normalization Of Simulation System Credibility Index Based On Vague Set, Yuhang Ren, Li Wei, Ma Ping, Yang Ming
Normalization Of Simulation System Credibility Index Based On Vague Set, Yuhang Ren, Li Wei, Ma Ping, Yang Ming
Journal of System Simulation
Abstract: Focus on various types of simulation system credibility indexes and the difficulty to convert the index results to credibility, a normalization method of credibility indexes based on Vague sets is proposed, which includes qualitative and quantitative conversion methods; Aiming at the problem of credibility Vague value index synthesis, the weighted arithmetic mean operator and the weighted geometric mean operator based on Vague set are given, and the applications are explained; According to the similarity principle of Vague sets, a method of transforming the credibility Vague value to the credibility single value is proposed, which improves the …
Simulation Of Pedestrian In Multifunctional Passageway Of Metro Station Area Based On Social Force Model, Wang Xi, Zhang Rui, Fei Shuo, Minghang Yang
Simulation Of Pedestrian In Multifunctional Passageway Of Metro Station Area Based On Social Force Model, Wang Xi, Zhang Rui, Fei Shuo, Minghang Yang
Journal of System Simulation
Abstract: Transitional passageway connecting subway stations and commercial facilities is generally designed as the multifunctional passageway, in which the traffic function is the main and the service function is the auxiliary. The impact of the service facilities on both sides of the passage on pedestrian traffic is difficult to be quantitatively analyzed and simulated and modeled. Through measurement, it is found that the viscous effect of service facilities on pedestrian traffic is mainly slowing down the speed or changing the trajectory direction. Through analyzing the horizontal influence range of service facilities, dividing the passage into different areas, and introducing the …
Modeling And Simulation Of Radiation Measurement System Based On Monte Carlo Method, Jinghai Cheng, Hongzhi Wang, Luoyuan Xu, Xia Tian
Modeling And Simulation Of Radiation Measurement System Based On Monte Carlo Method, Jinghai Cheng, Hongzhi Wang, Luoyuan Xu, Xia Tian
Journal of System Simulation
Abstract: A method is applied to build a virtual simulation radiometric measurement system. The mathematical and physical models of gamma ray interaction with matter, radiation sources, measurement electronics system and protective materials are constructed by using Monte Carlo method. Through numerical calculation and scene simulation of the radiation measurement system, virtual simulation acquisition and energy spectrum processing of radiation measurement data are realized. It, the system, can simulate single channel measurement and computer multi-channel measurement experiments. It can realize energy measurement, activity measurement and energy spectrum measurement of mixed, unknown or custom radiation sources in different size crystals. It can …
Kernel Block Diagonal Representation Subspace Clustering And Its Convergence Analysis, Maoshan Liu, Zhicheng Ji, Wang Yan, Jianfeng Wang
Kernel Block Diagonal Representation Subspace Clustering And Its Convergence Analysis, Maoshan Liu, Zhicheng Ji, Wang Yan, Jianfeng Wang
Journal of System Simulation
Abstract: Focus on the problems that the linear block diagonal representation subspace clustering cannot effectively handle non-linear visual data, and the regular regularizers cannot directly pursue the k-block diagonal matrix, a kernel block diagonal representation subspace clustering is proposed. In the proposed algorithm, the original input space is mapped into the kernel Hilbert space which is linearly separable, and the spectral clustering is performed in the feature space. The convergence analysis is given, and the strong convex of variables and the boundedness of function is utilized to verify the monotonically decreasing of objective function and the boundedness and convergence of …
Research On Flexible Job-Shop Dynamic Scheduling Based On Game Theory, Yichen You, Wang Yan, Zhicheng Ji
Research On Flexible Job-Shop Dynamic Scheduling Based On Game Theory, Yichen You, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To quickly and effectively respond to the machine fault disturbance events in Flexible Job-shop Scheduling Problem (FJSP), a flexible job-shop dynamic scheduling based on game theory is established. A pre-scheduling scheme is generated under Non-Dominated Sort Genetic Algorithm-Ⅱ (NSGA-Ⅱ) algorithm which introduces self-adapted crossover operators to improve the population diversity. For FJSP dynamic scheduling with machine fault, a multi-stage complete information game model is built to better balance the stability and robustness indicators and respond quickly to the machine fault, in which the stability and robustness indicators are mapped to the game players, and a hybrid Nash Equilibrium which …
System Performance Evaluation Method Based On Multi-Source Prior Data, Haozhe Liu, Li Wei, Ma Ping, Yang Ming
System Performance Evaluation Method Based On Multi-Source Prior Data, Haozhe Liu, Li Wei, Ma Ping, Yang Ming
Journal of System Simulation
Abstract: When using the Bayes method to evaluate the performance of the system with multi-source prior data, the multi-source prior data is fused, the posterior distribution is calculated by synthesizing the fused prior distribution and test data. The parameters of posterior distribution are estimated to obtain the performance evaluation results. A weighted fusion method of multi-source prior data based on Kullback-Leibler divergence is proposed, which can effectively integrate the multi-source prior data. The commonly used Markov Chain Monte Carlo method is used to estimate the parameters of Bayes posterior distribution. The influence of different proposal distributions on the sampling results …
Research On Six Degrees Of Freedom Platform Control In Special Vehicle Simulated Driving Training, Yihao Li, Zhili Zhang, Xiangyang Li, Long Yong
Research On Six Degrees Of Freedom Platform Control In Special Vehicle Simulated Driving Training, Yihao Li, Zhili Zhang, Xiangyang Li, Long Yong
Journal of System Simulation
Abstract: In order to simulate various postures of driving the special vehicles in a limited space, a set of six-degree-of-freedom motion platform for the simulation driving training system of special vehicles is developed. The mechanical structure of the six-degree-of-freedom motion platform is designed to meet the motion posture simulation requirement. The control of each degree of freedom in the motion platform is realized through the design of the embedded control system. The displacement of each electric cylinder is obtained by inverse solution algorithm, and the somatosensory simulation of acceleration and angular displacement is realized by the wash-out algorithm. It has …
Research On Moffjsp Based On Multi-Strategy Fusion Quantum Particle Swarm Optimization, Cai Min, Wang Yan, Zhicheng Ji
Research On Moffjsp Based On Multi-Strategy Fusion Quantum Particle Swarm Optimization, Cai Min, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To improve the quality of the optimal scheduling solution set, a quantum particle swarm algorithm with multi-strategy fusion is proposed for the multi-objective fuzzy flexible job shop scheduling problem with fuzzy maximum completion time, fuzzy total machine load, and fuzzy bottleneck machine load as optimization objectives. Chaotic mapping is used to improve the initial population quality, and a Lévy flight strategy is introduced to enhance the algorithm's ability to jump out of the local optimum. The neighborhood search strategy based on machine mutation is designed for local search. Cross operation is used to maintain the diversity of elite individuals, …
Simulation Of Zero-Speed Correction Algorithm For Underground Space Individual Positioning, Yijing Wang, Su Zhong, Li Qing, Li Lei
Simulation Of Zero-Speed Correction Algorithm For Underground Space Individual Positioning, Yijing Wang, Su Zhong, Li Qing, Li Lei
Journal of System Simulation
Abstract: In view of the complex and dangerous collapse environment of the tunnel, the related safety hazards of the positioning system of the tunnel rescuer are intensively analyzed, and the simulation of the inertial device worn on the chest, waist, calf, and foot surface shows that the correction on the foot surface is the best. Focus on the error accumulation of inertial devices, according to the fact that the speed is near zero when the sole of the foot fully touches the ground during walking, the algorithm of zero-speed correction for acceleration and angular velocity is compared, and a combination …
Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan
Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan
Journal of System Simulation
Abstract: In view of the complexity and low accuracy of gait recognition in the past, an intelligent gait recognition method based on plantar pressure perception is proposed. The pressure data of the gait of plantar periodic motion is collected and the obtained gait data is classified by the vector machines,the intelligent gait recognition of plantar pressure perception is realized, and the accuracy of gait feature analysis is improved. Through experiment verification, the overall classification accuracy of the classifier is more than 90%, which verifies the rationality of the feature extraction. By evaluating the real state and the results of …
Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji
Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to effectively predict the power and value fluctuation range of the short-term wind, a wind power prediction method based on clustering and kernel principal component analysis combined with random forest algorithm is proposed. The clustering analysis data processing method is used to preprocess the meteorological wind power generation data to improve the data quality, and the kernel principal component analysis method is used to reduce the dimensionality of the eight groups of characteristic data to remove the correlation of the wind power data, the random forest algorithm is used to forecast the wind power, to obtain …
Combination Forecasting Model Of Photovoltaic Power Based On Empirical Wavelet Transform, Chen Tao, Wang Yan, Zhicheng Ji
Combination Forecasting Model Of Photovoltaic Power Based On Empirical Wavelet Transform, Chen Tao, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to improve the prediction accuracy of short-term photovoltaic power, a variable weight combined prediction model based on Empirical Wavelet Transform (EWT) and PSO-optimized random forest(RF) is proposed. Gray correlation analysis is used to select similar days, EWT is used to decompose the power time series into sub-modes of different frequencies, and three modes of high, medium, and low frequency are reconstructed according to the frequency, PSO-RF and PSO-BP and PSO-LSSVM prediction models are established to dynamically calculate their respective weights for reconstruction, and error correction is performed to output the prediction results. By predicting the output power …
Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo
Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo
Journal of System Simulation
Abstract: In the unmanned cluster task execution, following the change of relative position of unmanned system, network changes in real time leads to the change of node importance of each unmanned system, and the corresponding change of data transmission and communication flow. For the better network management, the central node for controlling data communication needs to be selected. An adaptive selection method for the center node of unmanned cluster is proposed, and the mapping and feature of unmanned cluster network is expressed as graph theory. Laplacian centrality is introduced to evaluate the importance of nodes themselves. Weakening factors are …
Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong
Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong
Journal of System Simulation
Abstract: Aiming at the arbitrariness and inconsistent standards in the subjective assessment of the personnel overboard rescue training evaluation in the navigation simulator, the maneuvering process of Williamson turn rescue overboard personnel is analyzed. The evaluation index system is obtained by using the expert investigation method. The sample data of the personnel overboard rescue operation is obtained by the navigation simulator. Combining the expert investigation method, the subjective score of each sample is obtained. By using the BP neural network to train and test the samples, the intelligent evaluation model of personnel overboard rescue is obtained, and the intelligent evaluation …
Supplier Selection Based On Supplier Portrait And Markov Monte Carlo Method, Bingli Sun, Song Xiao, Guanghong Gong
Supplier Selection Based On Supplier Portrait And Markov Monte Carlo Method, Bingli Sun, Song Xiao, Guanghong Gong
Journal of System Simulation
Abstract: The supplier selection problem is a complex multi-objective decision-making problem and the key is how to establish the supplier's portrait. For the supplier selection of aerospace equipment, enterprise qualification management, business risks, and product quality are comprehensively considered. Based on Bayesian theory, the multi-parameter joint distribution derivation of portrait sample data is realized. Combined with the mathematical model derived, a Markov Monte Carlo simulation method is proposed. And combined with Gibbs sampler, the supplier ranking and selection are achieved when data is difficult to obtain or missing, which provides a new idea for supplier selection in the aerospace …
Single-Frame Image Motion Parallax Key Point Estimation Combined With Self-Supervised Learning, Zhihao Huo, Weidong Jin, Tang Peng
Single-Frame Image Motion Parallax Key Point Estimation Combined With Self-Supervised Learning, Zhihao Huo, Weidong Jin, Tang Peng
Journal of System Simulation
Abstract: The motion parallax key point FOE (Focus of Expansion) is an important parameter of railway catenary video inspection. The current method of calculating FOE requires multi-frame image matching estimation, which has high time complexity. Aiming at the single-frame image FOE estimation, a single-frame image FOE estimation algorithm fused with self-supervised learning is proposed. A full convolutional network F-VGG(Fully-Visual Geometry Group) is built as the FOE predictor, and the training label of the sample data is automatically generated through the fusion agent task, which realizes the end-to-end single-frame image FOE estimation. The experimental results show that the method has an …
Fuzzy Information Granulation And Improved Rvm For Rolling Bearing Life Prediction, Xiaoman Hu, Wang Yan, Zhicheng Ji
Fuzzy Information Granulation And Improved Rvm For Rolling Bearing Life Prediction, Xiaoman Hu, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the low accuracy in life prediction and unpredictable problems of degenerative performance trends and fluctuation ranges, etc. Of the bearing life prediction, an improved complete ensemble empirical mode decomposition with adaptive noise analysis and fuzzy information granulating method of improved relevance vector machine is proposed. Focusing on bearing data containing a lot of noise, through the improved complete ensemble empirical mode decomposition with adaptive noise analysis in combination with wavelet packet denoising, the principal component analysis is carride out by exitracing a variety of characeteristics of the signal, the effective information is extracted by granulating the fuzzy …
Midcourse Guidance Method Based On Fading Memory Filter For Intercepting Near-Space Gliding Target, Yonghua Fan, Yilun Huangfu, Xiaowen Guo, Chenlu Li, Guofei Li
Midcourse Guidance Method Based On Fading Memory Filter For Intercepting Near-Space Gliding Target, Yonghua Fan, Yilun Huangfu, Xiaowen Guo, Chenlu Li, Guofei Li
Journal of System Simulation
Abstract: Aiming at the interception of hypersonic gliding target in near space, a sliding mode guidance law based on fading memory filtering algorithm is proposed. The accurate motion parameters of the hypersonic target are obtained based on the current statistical model fading memory EKF(Extended Kalman Filter) algorithm. Based on the filtering information and sliding mode control theory, a sliding mode guidance law is designed to adjust the interception trajectory online according to the target maneuver law. The simulation results show that the proposed fading memory filtering algorithm can effectively track the gliding target with high filtering accuracy. For a …
Trajectory Tracking Control Of Planetary Entry Phase Based On Neural Network And Fractional Sliding Mode, Cunli Fan, Dai Juan, Haitao Liu, Su Zhong, Zhu Cui, Wenting Xu
Trajectory Tracking Control Of Planetary Entry Phase Based On Neural Network And Fractional Sliding Mode, Cunli Fan, Dai Juan, Haitao Liu, Su Zhong, Zhu Cui, Wenting Xu
Journal of System Simulation
Abstract: A fractional order sliding mode control method based on Radial Basis Function (RBF) neural network is proposed to solve the landing accuracy being affected by the interference during the landing process of planetary probe. Based on sliding mode control, a trajectory tracking control method for the entry phase of the probe is designed. Fractional calculus is introduced to alleviate the chattering caused by sliding mode control. RBF neural network is used to estimate and compensate the atmospheric density uncertainty. The method is applied to Mars landing scene simulation. The simulation results show that the proposed control method can accurately …
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Journal of System Simulation
Abstract: Stick-slip vibration is an important limiting factor affecting drilling speed, safety and cost. The establishment of a reliable stick-slip vibration classification model is very important for oil drilling decision-making. A new method based on Bayesian optimization and eXtreme Gradient Boosting (XGBoost) is proposed to evaluate the severity of stick-slip vibration near the bit. The classification processing of the near-bit stick-slip vibration data is carried out. The main feature vectors of the original data is extracted through time domain and frequency domain analysis. A stick-slip vibration level identification and prediction model based on XGBoost is established, and Bayesian algorithm is …
A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu
A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu
Journal of System Simulation
Abstract: A natural computing method based on spatial division search strategy is proposed. The strategy can map the high-dimensional space to the three-dimensional Cartesian coordinate system by grouping the dimensional space into a group of three dimensions. The individual after spatial segmentation is numbered into subindividual, to increases the particle number while reducing the dimension, thus the individual is distributed over wider search space to effectively increases the diversity of the population. The algorithm iterates to a certain extent and can synthesize the individual into the original individual through the numbered index. By calculating the fitness value, some poor …
Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang
Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang
Journal of System Simulation
Abstract: A Unmanned Aerial Vehicle (UAV) cluster access control mechanism based on Ethereum blockchain smart contract is proposed to solve the problems of the strategic stability and low security of UAV cluster access control mechanism. The role-based access control mechanism model is improved, and the formal definition of the access control model for UAV cluster is given. The access control architecture of UAV cluster based on blockchain technology is proposed, and the corresponding basic framework and execution process is proposed, which can effectively reduce the cost of UAV cluster operation management resources, solve the problem of incomplete state …
An Electromechanical-Electromagnetic Transient Stability Simulation System For Ac/Dc Hybrid Power System, Weijie Dong, Huang Min, Guoqing He, Bao Wei, Yilong Wang, Liu Quan
An Electromechanical-Electromagnetic Transient Stability Simulation System For Ac/Dc Hybrid Power System, Weijie Dong, Huang Min, Guoqing He, Bao Wei, Yilong Wang, Liu Quan
Journal of System Simulation
Abstract: In order to improve the hybrid simulation speed of AC/DC power grid, it is necessary to improve the simulation method of sub grid parallel. An electromechanical transient stability simulation system is presented for AC/DC hybrid power grid. The AC/DC sub network module is used to divide the large AC/DC power grid into small AC/DC sub networks, so that each sub network can be simulated in parallel. The numerical calculation method is improved for the efficiency and accuracy of simulation calculation. Taking IEEE 10-39 bus as an example, the effectiveness of the method is verified in PSCAD (Power Systems Computer …
Optizimation Of Vaccination Supply Chain Based On Scg In Nanshan District, Zhenning Dong, Shunzhou Huang, Jiajun Chen, Huiqiong Zheng
Optizimation Of Vaccination Supply Chain Based On Scg In Nanshan District, Zhenning Dong, Shunzhou Huang, Jiajun Chen, Huiqiong Zheng
Journal of System Simulation
Abstract: To optimize the vaccination network, inventory strategy and human resource allocation in Nanshan District, Supply Chain Guru's (SCG) network optimization method is used to select 50 alternative stations to decrease the fixed operating cost. SCG's inventory optimization method is used to set inventory strategy for each station, and simulation method is designed to compare total cost of all schemes. To optimize the opening days of vaccination stations, an medical personnel allocation rule is designed, which reduces some stations' opening days to 2 or 3 days and increases some stations' medical personnel. An simulation method is designed to compare the …
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter
Articles
The threat posed by misinformation and disinformation is one of the defining challenges of the 21st century. Provenance is designed to help combat this threat by warning users when the content they are looking at may be misinformation or disinformation. It is also designed to improve media literacy among its users and ultimately reduce susceptibility to the threat among vulnerable groups within society. The Provenance browser plugin checks the content that users see on the Internet and social media and provides warnings in their browser or social media feed. Unlike similar plugins, which require human experts to provide evaluations and …
Cognizant Composites: Seamless Integration Of Circuitry And Sensors Into Structural Composites, Reuben Fresquez
Cognizant Composites: Seamless Integration Of Circuitry And Sensors Into Structural Composites, Reuben Fresquez
Computer Science ETDs
This thesis describes a set of novel techniques for embedding sensors, circuitry, and electronics into structural composites. I leverage recent developments in human computer interaction to create sensors and circuitry that are seamlessly incorporated into structural composites. I fabricate bend and compression sensors, along with circuitry, from textiles, which enables me to add electronic capabilities without impacting the composite’s structural integrity. I describe the construction of these “cognizant composites” and demonstrate their functionality. I also explore techniques for embedding standard electronic components, including microcontrollers, into structural composites. Potential applications of this technology include buildings that can warn occupants if load-bearing …
Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli
Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.
Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and …