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EADTC: An Approach to Interpretable and Accurate Crime Prediction

EADTC: An Approach to Interpretable and Accurate Crime Predi...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Ma, Yujunrong Nakamura, Kiminori Lee, Eung-Joo Bhattacharyya, Shuvra S. University of Maryland Dept. of Electrical and Computer Engineering United States University of Maryland Dept. of Criminology and Criminal Justice United States Mgh and Harvard Medical School Camca Dept. of Radiology United States Institute for Advanced Computer Studies Maryland Crime Research and Innovation Center University of Maryland Dept. of Electrical and Computer Engineering United States

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Machine learning applications related to high-stakes decisions are often surrounded by significant amounts of controversy. This has led to increasing interest in interpretable machine learning models. A well-known class of interpretable models is that of decision trees (DTs), which mirror a common strategy used by humans to arrive at solutions through a series of well-defined decisions. However, much of previous research on DTs for criminal justice predictions has focused primarily on collections (ensembles) of DTs whose results are aggregated together. Such DT ensembles are used to help improve accuracy;however, their increased complexity and deviation from human decision-making processes makes them much less interpretable compared to single-DT approaches. In this paper, we present a new DT model for criminal recidivism prediction that is designed with high interpretability, accuracy, and fairness as core objectives. The interpretability of the model stems from its formulation in terms of a single DT structure, while accuracy is achieved through an intensive optimization process of DT parameters that is carried out using a novel evolutionary algorithm. Through extensive experiments, we analyze the performance of our proposed EADTC (Evolutionary Algorithm Decision Tree for Crime prediction) method on relevant datasets. Our experiments show that the EADTC approach achieves competitive accuracy and fairness with respect to state-of-the-art ensemble DT models, while achieving higher interpretability due to the simpler, single-DT structure. © 2022 IEEE.

关键词： Decision trees

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Analysis of Short and Aging Faults in TSVs at the Physical Level with Parametric Variation 26

Analysis of Short and Aging Faults in TSVs at the Physical L...

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26th International Symposium on Quality Electronic Design, ISQED 2025

作者： Kirtonia, Prosen Williams, Shelby Kawatkar, Prasanna Khalil, Kasem Bayoumi, Magdy Univ. of Mississippi Department of Electrical and Computer Engineering Oxford 38677 MS United States University of Louisiana at Lafayette Dept. of Electrical and Computer Engr. Lafayette 70504 LA United States Univ. of Louisiana at Lafayette Center for Advanced Computer Studies Lafayette 70504 LA United States

ISBN: (纸本)9798331509422

The importance of using chiplets and 3D ICs is growing rapidly, driven by the slowing of Moore's Law and the benefits they offer. advanced packaging of chiplets, and interconnects in 3D ICs are crucial for enhancing computing performance and power efficiency. Hence, Through-Silicon Vias (TSVs) serve as prominent vertical conduits to ensure efficient chip-to-chip communication. The primary objective of this work is to model TSV faults at the material level to observe transmission performance deviations alongside other parametric analyses. We employ Ansys High-Frequency Structure Simulator (HFSS) to design the TSV at the physical level. The reflection coefficient is measured over a 0.1-30 GHz frequency band to observe -15 dB bandwidth for a wide range of lengths (30-200 μ m), radius (4-50 μ m), and insulator thickness (0.2-1.5 μ m), considering distinct densities. Furthermore, a crack of 5-15 μ m is introduced in the dielectric layer to implement a short fault, and copper conductance is reduced by 5-30% for different stages of aging faults to evaluate anomalies. Finally, multiple TSVs are incorporated into the design to assess near-end and far-end cross-talk at 15 and 30 μ m pitch. Therefore, before developing an equivalent R-L-C circuit for fault detection, it is essential to investigate functionality and faults at the physical level for a more comprehensive understanding. © 2025 IEEE.

关键词： 3D IC Aging Fault Chiplet Cross-talk HFSS Moore's Law Short Fault Through-Silicon Vias TSV

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Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV) 14

Integrating AI-Driven Robust Control Algorithm with 3D Hand ...

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14th IEEE International Conference on Control System, Computing and engineering, ICCSCE 2024

作者： Al-Shayeb, Ibrahim Emad Abro, Ghulam E Mustafa Khan, Fawad Salam Boudville, Rozan Abdallah, Ayman M. King Fahd University of Petroleum and Minerals-KFUPM Control and Instrumentation Engineering Dept. Dhahran Saudi Arabia King Fahd University of Petroleum and Minerals-KFUPM Interdisciplinary Research Center for Aviation and Space Exploration Dhahran Saudi Arabia Air University Department of Creative Technologioes Islamabad Pakistan Universiti Teknologi MARA Electrical Engineering Studies College of Electrical Engineering Permatang Pauh Pulau Pinang13500 Malaysia King Fahd University of Petroleum and Minerals-KFUPM Aerospace Engineering Dept. Dhahran Saudi Arabia

ISBN: (纸本)9798350364507

The aviation sector has seen several modifications, most of which are connected to autopilot systems. In the current era of artificial intelligence (AI), robust control algorithms can be tuned for optimal accuracy by utilizing AI's power. To adjust the control system for controlling the drone, this publication suggests combining the Reinforcement Learning algorithm with the ability to recognize 3D hand gestures as input. This study uses Deep Deterministic Policy Gradient (DDPG) in conjunction with 3D hand gesture recognition to determine the optimal reward and transfer the processed input to proportional integral derivative (PID) control. This method demonstrated how an AI-powered control algorithm can enhance an underactuated quadrotor unmanned aerial vehicle's (UAV) ability to fly and hover. In addition to simulation data, the study includes hardware results that were verified with a DJI Tello Drone. When compared to a typical PID flight controller, the examination of the findings shows that the new design framework provides better accuracy and computing time. Six reward functions normalized between 0 and -4000, have been estimated for training episodes of 2500, 5000, 7500, and 10,000. The greatest observation, wherein the rewards are computed for maximum value, has been recorded on 2500 episodes. © 2024 IEEE.

关键词： Drones

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Accuracy Enhancing Time Limited Model Reduction Framework: Computational Efficiency in Power Systems

Accuracy Enhancing Time Limited Model Reduction Framework: C...

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International Bhurban Conference on Applied Sciences & Technology, IBCAST

作者： Muhammad Latif Hira Ambreen Muhammad Imran Samra Zafar Sajid Bashir Department of Electrical Engineering Military College of Signals (MCS) National University of Sciences & Technology (NUST) Islamabad Pakistan Department of Electrical Engineering Sir Syed Center for Advanced Studies in Engineering Institute of Technology (SS-CASE-IT) Islamabad Pakistan Henan University School of Computer and Information Engineering Kaifeng China College of Electrical & Mechanical Engineering NUST Islamabad Pakistan

ISBN: (数字)9798331516680

ISBN: (纸本)9798331516697

The analytical and modelling precision required to build modern wind turbines makes them stable, controlled, and observable. This article presents a state-of-the-art method for lowering the model order of a wind turbine driven by a double-fed induction generator, where the rotational speed varies over time. The suggested approach uses state-space representations to set up a comprehensive and systematic framework for analysing wind turbine performance and checking for compliance with grid standards. A time-constrained Gramians-based novel balanced realization approach is employed to reduce the dimensionality of the large-scale wind turbine model. Stability and reduced approximation error are two benefits of the lower-order system. The proposed method also gives researchers an a priori formula for the error-bound, making computations faster and more efficient. Using substantial simulation data, we show that our method improves upon previous methods in optimising models that include wind turbines with changing rotational speeds, taking into account both stability and error computation. To enhance the efficacy and accuracy of their modeling procedures, academics and researchers analyzing wind turbines should incorporate this new methodology.

关键词： Analytical models Accuracy Uncertainty Computational modeling Stability criteria Velocity control Power system stability Approximation error Wind turbines Computational efficiency

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Jitter-Based True Random Number Generator with Dynamic Selection Bit Reconfiguration

Jitter-Based True Random Number Generator with Dynamic Selec...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Prosen Kirtonia Shelby Williams Magdy Bayoumi Dept. of Electrical and Computer Engineering Univ. of Louisiana at Lafayette Lafayette LA USA Center for Advanced Computer Studies University of Louisiana at Lafayette Lafayette LA USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

A compact, lightweight jitter-based True Random Number Generator (TRNG) is proposed in this paper. The key idea behind this design is to use a combination of high-entropy noise sources to select those same noise sources to operate at a time. This is achieved through cross-coupled connections and dynamic selection bit reconfiguration, reducing hardware consumption without compromising the quality of the generated bits. In cryptography and security, a TRNG plays a vital role in developing unique keys for encryption, thereby ensuring the integrity and protection of the system. The design utilizes various combinations of odd numbers of inverters to introduce jitter as a noise source to create Running Oscillators (RO). Moreover, the design employs multiplexers and a single XNOR logic gate for dynamic noise source selection. Finally, the area, speed, power, and energy of the proposed TRNG are measured using Synopsys Design Compiler (SDC) for 14nm, 32nm, and 45nm technology nodes. The randomness of this design is tested and validated using NIST SP800-22 tests. All 16 statistical tests for randomness outlined in the NIST test suite are passed without requiring post-processing circuitry. Hence, this TRNG design presents significant advancements in secure data risk management, offering an ultra-compact and efficient solution for generating secure keys.

关键词： Ring oscillators Power measurement Noise Area measurement Energy measurement Switches NIST

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Lightweight, High-Entropy TRNG Using Quad Cross-Coupled Feedback Architecture

Lightweight, High-Entropy TRNG Using Quad Cross-Coupled Feed...

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IEEE Southeastcon

作者： Shelby Williams Prosen Kirtonia Sonia Akter Kasem Khalil Magdy Bayoumi Center for Advanced Computer Studies Univ. of Louisiana at Lafayette Lafayette LA USA Dept. of Electrical and Computer Engineering Univ. of Louisiana at Lafayette Lafayette LA USA Department of Electrical and Computer Engineering Univ. of Mississippi Oxford MS USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This paper presents a lightweight, high-entropy true random number generator architecture featuring an innovative quad cross-coupled feedback mechanism to enhance randomness. The primary goal is to develop an efficient and secure true random number generator that addresses the growing demand for reliable random number generation in cryptographic and security-critical applications. The motivation stems from the need to improve entropy, reduce resource utilization, and ensure robustness across varying technologies. With the intention of achieving near-perfect randomness, the Quad-Input Oscillating Circuit module integrates self-coupled, jitter-inducing ring oscillators with cross-coupled feedback loops to induce metastability. Comprehensive evaluations confirm a Shannon entropy of 0.999818, a minimum entropy of 0.977257, and a collision entropy of 0.999636. The design was synthesized using Synopsys Design Compiler at 45 nm, 32 nm, and 14 nm, achieving a maximum frequency of 6.7 GHz, power consumption as low as 72 µW, and area utilization of 24 µ m 2 at 14 nm. Rigorous validation through multiple statistical test suites, including the AIS-31, Autocorrelation, Deviation, Diehard, the National Institute of Standards and Technologies SP800-22 and SP800-90B, and TestU01, confirms its efficiency and reliability. Real random bits were implemented as oscilloscope-viewable signals on the Cyclone V Field Programmable Gate Array developed by Altera, representing a significant advancement in secure random number generation technologies.

关键词： Ring oscillators Scalability NIST Logic gates Entropy Generators Robustness Resource management Random number generation Field programmable gate arrays

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EpiCare: A Reinforcement Learning Benchmark for Dynamic Treatment Regimes 38

EpiCare: A Reinforcement Learning Benchmark for Dynamic Trea...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Hargrave, Mason Spaeth, Alex Grosenick, Logan Center for Studies in Physics and Biology The Rockefeller University New YorkNY United States Dept. of Electrical and Computer Engineering University of California Santa Cruz Santa CruzCA United States Dept. of Psychiatry and BMRI Weill Cornell Medicine Cornell University New YorkNY United States

Healthcare applications pose significant challenges to existing reinforcement learning (RL) methods due to implementation risks, limited data availability, short treatment episodes, sparse rewards, partial observations, and heterogeneous treatment effects. Despite significant interest in using RL to generate dynamic treatment regimes for longitudinal patient care scenarios, no standardized benchmark has yet been developed. To fill this need we introduce Episodes of Care (EpiCare), a benchmark designed to mimic the challenges associated with applying RL to longitudinal healthcare settings. We leverage this benchmark to test five state-of-the-art offline RL models as well as five common off-policy evaluation (OPE) techniques. Our results suggest that while offline RL may be capable of improving upon existing standards of care given sufficient data, its applicability does not appear to extend to the moderate to low data regimes typical of current healthcare settings. Additionally, we demonstrate that several OPE techniques standard in the the medical RL literature fail to perform adequately on our benchmark. These results suggest that the performance of RL models in dynamic treatment regimes may be difficult to meaningfully evaluate using current OPE methods, indicating that RL for this application domain may still be in its early stages. We hope that these results along with the benchmark will facilitate better comparison of existing methods and inspire further research into techniques that increase the practical applicability of medical RL. © 2024 Neural information processing systems foundation. All rights reserved.

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Vector proportional integral controller in series connected custom power device for voltage quality enhancement

Vector proportional integral controller in series connected ...

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2021 International Conference on Emerging Power Technologies, ICEPT 2021

作者： Majeed, Hatif Bin Abdul Khan, Aqib Iqbal, Wasim Khalid, Hassan Abdullah Engineering Air University Department of Electrical and Computer Islamabad Pakistan U.S. Pakistan Center for Advanced Studies in Energy NUST Islamabad Pakistan

ISBN: (纸本)9781665412933

Dynamic Voltage Restorer (DVR) is one of the most efficient and economical series connected custom power device having a major application in Power Quality Enhancement at consumer and distribution level. In the control structure, the DVR usually utilizes rotating reference frame, which comes with certain downsides. Main purpose of this study is to execute a performance analysis on both rotating and stationary reference frame based DVR's. Cascaded controllers with an outer voltage controller and an inner current controller have been used as control strategy. As current controllers, both Proportional Integral (PI) and Vector Proportional Integral (VPI) controllers are used separately to compare their performance using MATLAB/Simulink. This comparative analysis has been carried out by considering settling time, overshoot and error signals for linear as well as non-linear loads while taking the computational time delays into account. © 2021 IEEE.

关键词： Controllers

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Automatic quality control in computed tomography volumes segmentation using a small set of XCAT as reference images

Automatic quality control in computed tomography volumes seg...

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Medical Imaging 2023: Physics of Medical Imaging

作者： Dahal, Lavsen Wang, Yuqi Tushar, Fakrul Islam Montero, Isabel Lafata, Kyle Abadi, Ehsan Samei, Ehsan Segars, William P. Lo, Joseph Y. Center for Virtual Imaging Trials United States Carl E. Ravin Advanced Imaging Laboratories United States Dept. of Radiology Duke University School of Medicine United States Medical Physics Duke University United States Dept. of Electrical and Computer Engineering Pratt School of Engineering Duke University United States

ISBN: (纸本)9781510660311

Deep learning methods have performed superiorly to segment organs of interest from Computed Tomography images than traditional methods. However, the trained models do not generalize well at the inference phase, and manual validation and correction are not feasible for large-scale studies. Therefore, automatic methods to detect segmentation failure are crucial for computer Aided Diagnosis systems. In this work, we present an automatic quality control method that can be used to reject poor segmentation. We register new test cases against a set of XCATreference or training images. This "reverse classification accuracy"approach uses similarity of image registration to estimate segmentation quality. We validated this approach on two large public CT datasets, CT-ORG and ABDOMEN-1K with multiple organs. We show empirical cutoffs for predicted similarity coefficient for organs of interest in public datasets that can be used for datasets where ground truth is not available. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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Image Pre-processing for Differential Diagnosis of Multiple Sclerosis using Brain MRI 2

Image Pre-processing for Differential Diagnosis of Multiple ...

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2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Memon, Khuhed Yahya, Norashikin Yusoff, Mohd Zuki Hashim, Hilwati Ali, Syed Saad Azhar Siddiqui, Shahabuddin Universiti Teknologi PETRONAS Dept. of Electrical & Electronic Engineering Perak Seri Iskandar Malaysia Universiti Teknologi PETRONAS HiCoE-CISIR Dept. of Electrical & Electronic Engineering Perak Seri Iskandar Malaysia Universiti Teknologi MARA Faculty of Medicine Department of Radiology Selangor Sungai Buloh Malaysia Center for Smart Mobility & Logistics King Fahd University of Petroleum & Minerals Aerospace Engineering Dept. Dhahran Saudi Arabia Pakistan Institute of Medical Sciences Advanced International Hospital Department of Radiology Islamabad Pakistan

ISBN: (纸本)9798350347982

Multiple sclerosis (MS) is a type of auto-immune disease affecting the human brain. One of the challenges in clinical diagnosis of MS lies in its close similarity to another type of brain auto-immune disease known as neuromyelitis optica (MNO). Hence, various researchers are looking into the development of computer-aided differential diagnosis (CADD) of MS vs. MNO. Generally, the development of the CADD, involves image pre-processing, feature extraction, statistical analysis and training and testing of the classification model. The focus of this paper is on the 2 critical pre-processing steps prior to classification of MS vs. MNO, namely skull stripping and lesion segmentation. In particular, both skull stripping and brain lesion segmentation are tested with a popular semantic segmentation technique, DeepLabV3. For comparison, a recently published technique, SynthStrip from FreeSurfer [1], developed by Harvard University is also tested for brain extraction / skull removal. Similarly for segmentation of brain lesions, Lesion Segmentation Tool in SPM Toolbox is tested and compared. The results from this study provides insight on what are the appropriate pre-processing techniques for the development of an reliable automatic differential diagnosis tool for multiple sclerosis conditions. © 2023 IEEE.

关键词： computer aided diagnosis

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