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IEEE MIT Undergraduate Research Technology Conference (URTC)

作者： Nilgun Duman Alper Y. Ozbey Isil Isiksalan Ulkuhan Guler Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798331531003

ISBN: (纸本)9798331531010

This study explores the body sites for measuring transcutaneous carbon dioxide (CO 2 ) noninvasively using a miniaturized monitor that employs a technique known as timedomain dual lifetime referencing. Accurate measurement of CO 2 levels is crucial for patients with respiratory distress who need monitoring in both clinical and home care settings. We tested this novel monitor by calculating ratio values of luminescence light, indicative of CO 2 levels, at five d ifferent b ody locations: cheek, forearm, forehead, wrist, and fingertip, on f our subjects. We also conducted a repeatability analysis: we tested the sensor on one subject at the fingertip each day for three consecutive days. Our findings show that while all t ested s ites presented reliable data, the forehead and cheek yielded faster settling times, and the forearm, forehead, and wrist produced less variation in readings. The results highlight the significance of c hoosing e ffective sites for accurate transcutaneous CO 2 monitoring.

关键词： Wrist Forehead Accuracy Carbon dioxide Luminescence Sensors Reliability Biomedical monitoring Wearable devices Monitoring

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Parasitic Circus: On the Feasibility of Golden-Free PCB Verification

Parasitic Circus: On the Feasibility of Golden-Free PCB Veri...

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International Symposium on Physical & Failure Analysis of Integrated Circuits

作者： Maryam Saadat Safa Patrick Schaumont Shahin Tajik Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350360608

ISBN: (纸本)9798350360615

Printed circuit boards (PCBs) are an integral part of electronic systems. Hence, verifying their physical integrity in the presence of supply chain attacks (e.g., tampering and counterfeiting) is of utmost importance. Recently, tamper detection techniques grounded in impedance characterization of PCB's Power Delivery Network (PDN) have gained prominence due to their global detection coverage, non-invasive, and low-cost nature. Similar to other physical verification methods, these techniques rely on the existence of a physical golden sample for signature comparisons. However, having access to a physical golden sample for golden signature extraction is not feasible in many real-world scenarios. In this work, we assess the feasibility of eliminating a physical golden sample and replacing it with a simulated golden signature obtained by the PCB design files. By performing extensive simulation and measurements on an in-house designed PCB, we demonstrate how the parasitic impedance of the PCB components plays a major role in reaching a successful verification. Based on the obtained results and using statistical metrics, we show that we can mitigate the discrepancy between collected signatures from simulation and measurements.

关键词： Measurement Integrated circuits Machine learning algorithms Impedance measurement Printed circuits Supply chains Impedance

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Feasibility of Pointcloud-based Ultrasound-CT Registration towards Automated, Robot-Assisted Image-Guidance in Spine Surgery*

Feasibility of Pointcloud-based Ultrasound-CT Registration t...

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International Symposium on Medical Robotics (ISMR)

作者： Xihan Ma Xiao Zhang Yang Wang Christopher Nycz Arno Sungarian Songbai Ji Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA University of Massachusetts Memorial Medical Center Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering and the Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350377118

ISBN: (纸本)9798350377125

Image-guidance has been shown to improve spine surgical accuracy and patient outcome. Such image guidance can be achieved by registering low-cost, realtime, and radiation-free intraoperative ultrasound (US) with preoperative computed tomography (CT). Employing robotic US system (RUSS) allows automated acquisition of a wide 3D volume, facilitating efficient and accurate registration with CT. However, the registration between CT and robotic 3D US remains an open problem mainly due to (i) the lack of relevant testbed and dataset, and (ii) the modality discrepancy between CT and US. To address these challenges, we present a custom-built lumbar spine phantom for multimodal imaging with rigidly attached fiducials. The phantom is scanned by CT and in-house RUSS. A novel pointcloud-based registration pipeline is presented to register CT and robotic 3D US data of the spine phantom. Preliminary experiments demonstrate efficient (0.53 ± 0.02 seconds) registration of the lumbar spine with an accuracy of 3.57 mm in terms of fiducial registration error (FRE), which is robust to varying initial alignment of the pointclouds. These results show initial feasibility of adopting the proposed registration pipeline in robotic US guided spine surgery. Future work includes further evaluation of registration performance in ex vivo spine samples with denser US acquisitions to further improve registration accuracy.

关键词： Accuracy Three-dimensional displays Ultrasonic imaging Medical robotics Computed tomography Spine Pipelines

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Career-Based Explainable Course Recommendation 18th

Career-Based Explainable Course Recommendation

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18th International Conference on Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, iConference 2023

作者： Striebel, Jacob Myers, Rebecca Liu, Xiaozhong Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States

ISBN: (纸本)9783031280313

The type and quality of education that a student receives can have a profound impact on their career. In contrast to education that is not intentionally organized to help students achieve specific career objectives, career-based education seeks to provide students with the skills that are required to achieve specific career goals. In this work, we propose a course recommendation framework that is designed to recommend courses based directly on their ability to teach skills relevant to a user-specified career goal. Within our framework, course recommendations are generated in a transparent manner, using skills to bridge between jobs and courses in a knowledge-based inference procedure. Due to the procedure’s transparency, our system is able to provide faithful template-based explanations detailing why each recommended course was chosen for recommendation. Our framework contrasts with other course recommendation systems in the literature that lack the ability to explain their choices and therefore may lack trustworthiness from the perspective of a user. The proposed framework has several applications, including assisting students with course planning, as well as aiding with curriculum evaluation and development by providing insight into the usefulness of specific courses to specific careers. We conduct a preliminary evaluation of our system, and its performance is competitive against two baselines. We provide all the resources needed to reproduce our results. (http://***/striebel/cbecr ) © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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Thermal Ablation Therapy Control with Tissue Necrosis-driven Temperature Feedback Enabled by Neural State Space Model with Extended Kalman Filter

Thermal Ablation Therapy Control with Tissue Necrosis-driven...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ryo Murakami Satoshi Mori Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA The United States Department of Biomedical Engineering Robotics Engineering and Computer Science Engineering Worcester Polytechnic Institute Worcester MA The United States

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Thermal ablation therapy is a major minimally invasive treatment. One of the challenges is that the targeted region and therapeutic progression are often invisible to clinicians, requiring feedback provided in numerical information or imaging. Several emerging imaging modalities offer visualization of the ablation-induced necrosis formation; however, relying solely on necrosis monitoring can result in tissue overheating and endangering patients. Some of the necrosis monitoring modalities are known for their capabilities in temperature sensing, but the principles on which they are based have several limitations, such as sensitivity to the tissue motion and their environment. In this study, we propose a necrosis progression-based temperature estimation technique as an added safety feature for avoiding overheating. This model-based method does not require additional sensing hardware. It is designed to work as an independent estimator or a complimentary estimation component with other thermometers for improved robustness. For this objective, the Neural State Space model is used to approximate the ablation therapy, whose theoretical models involve nonlinear partial differential equations. Then, the Extended Kalman Filter is designed based on the model. The simulation study shows the estimation module robustly estimates the tissue temperature under several types of noise. The maximum estimation error observed before terminating ablation was around 1 °C, and the desired safety feature was successfully demonstrated. The estimator is expected to be used in a variety of necrosis monitoring modalities to guarantee more precise and safer treatment. More ambitiously, the architecture with the Neural State Space model and Extended Kalman Filter is generalizable to other medical/biological procedures involving nonlinear and patient/environment-specific physics and even to procedures having no reliable theoretical models.

关键词： Thermometers Estimation Medical treatment Mathematical models Robustness Sensors Safety Temperature control Kalman filters Monitoring

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Adaptive Inverter Control for Resilient Grid

Adaptive Inverter Control for Resilient Grid

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IEEE General Meeting Power& Energy Society

作者： Tan Zhang John Andrew Orr EDF Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

This study extends the previous adaptive inverter control work and introduces an alternative adaptive voltage regulation control strategy that accounts the voltage regulation delays and power priority switch that could have profound positive impacts on the autonomous operations of the inverter-based resources and hence the real-time hosted grid dynamics. This work evaluates the expandability of the overall proposed adaptive inverter frequency and voltage control methodologies under an unbalanced meshed microgrid with fault-induced feeder switching and multiple contingencies in addition to random power output from renewable generators. The extensive favorable simulation results demonstrate that a phase-locked loop based "current-mode controlled" inverter with properly designed controllers can effectively enhance its hosted utility grid strength, improve power system resiliency under dynamic changing operational environments.

关键词： Islanding Adaptive systems Power system dynamics Switches Microgrids Power system stability Control systems Inverters Voltage control Transient analysis

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Parasitic Circus: On the Feasibility of Golden-free PCB Verification

arXiv

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arXiv 2024年

作者： Safa, Maryam Saadat Schaumont, Patrick Tajik, Shahin Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA United States

Printed circuit boards (PCBs) are an integral part of electronic systems. Hence, verifying their physical integrity in the presence of supply chain attacks (e.g., tampering and counterfeiting) is of utmost importance. Recently, tamper detection techniques grounded in impedance characterization of PCB’s Power Delivery Network (PDN) have gained prominence due to their global detection coverage, non-invasive, and low-cost nature. Similar to other physical verification methods, these techniques rely on the existence of a physical golden sample for signature comparisons. However, having access to a physical golden sample for golden signature extraction is not feasible in many real-world scenarios. In this work, we assess the feasibility of eliminating a physical golden sample and replacing it with a simulated golden signature obtained by the PCB design files. By performing extensive simulation and measurements on an in-house designed PCB, we demonstrate how the parasitic impedance of the PCB components plays a major role in reaching a successful verification. Based on the obtained results and using statistical metrics, we show that we can mitigate the discrepancy between collected signatures from simulation and measurements. © 2024, CC BY.

关键词： Printed circuit boards

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Robot-Assisted Wide-Area Photoacoustic System

Robot-Assisted Wide-Area Photoacoustic System

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IEEE Symposium (IUS) Ultrasonics

作者： Shang Gao Xihan Ma Haichong K. Zhang Department of Robotics Engineering Worcester Polytechnic Institute Worcester USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester USA Department of Computer Science Worcester Polytechnic Institute Worcester USA

Liver ischemia and reperfusion injury (IRI) is a vascular complication that can lead to hepatic functional impairment. IRI is relevant in liver transplantation and during liver surgery performed with intermittent vascular inflow occlusion. Detecting intraoperative liver oxygenation impairment and ischemia could help prevent IRI, which is challenging partially due to the multiple hepatic vascular inflows. We propose a robot-assisted wide-area photoacoustic (PA) imaging system to monitor the liver oxygenation level intraoperatively. PA imaging has been widely used for oxygenation detection in preclinical research. We used a robotic arm to actuate the 2D PA probe and scan across the liver surface. An accurate volumetric tomography can be reconstructed via registering 2D images to the recorded robot trajectory. An ex vivo porcine liver sample was scanned using the proposed system. The result suggested that the robot-assisted wide-area PA tomography has the potential to be incorporated into clinical practice to evaluate liver SO2 intraoperatively.

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Silicon Echoes: Non-Invasive Trojan and Tamper Detection using Frequency-Selective Impedance Analysis

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2023年第4期2023卷 238-261页

作者： Mosavirik, Tahoura Monfared, Saleh Khalaj Safa, Maryam Saadat Tajik, Shahin Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA United States

The threat of chip-level tampering and its detection has been widely researched. Hardware Trojan insertions are prominent examples of such tamper events. Altering the placement and routing of a design or removing a part of a circuit for side-channel leakage/fault sensitivity amplification are other instances of such attacks. While semi-and fully-invasive physical verification methods can confidently detect such stealthy tamper events, they are costly, time-consuming, and destructive. On the other hand, virtually all proposed non-invasive side-channel methods suffer from noise and, therefore, have low confidence. Moreover, they require activating the tampered part of the circuit (e.g., the Trojan trigger) to compare and detect the modifications. In this work, we introduce a non-invasive post-silicon tamper detection technique applicable to different classes of tamper events at the chip level without requiring the activation of the malicious circuit. Our method relies on the fact that physical modifications (regardless of their physical, activation, or action characteristics) alter the impedance of the chip. Hence, characterizing the impedance can lead to the detection of the tamper events. To sense the changes in the impedance, we deploy known RF tools, namely, scattering parameters, in which we inject sine wave signals with high frequencies to the power distribution network (PDN) of the system and measure the "echo" of the signal. The reflected signals in various frequency bands reveal different tamper events based on their impact size on the die. To validate our claims, we performed measurements on several proof-ofconcept tampered hardware implementations realized on FPGAs manufactured with a 28 nm technology. We further show that deploying the Dynamic Time Warping (DTW) distance can distinguish between tamper events and noise resulting from manufacturing process variation of different chips/boards. Based on the acquired results, we demonstrate that stealthy hardwa

关键词： Scattering parameters

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An Attention-based Self-Supervised Approach to Monocular Depth Estimation from UAV captured Video Sequences

An Attention-based Self-Supervised Approach to Monocular Dep...

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Pattern Recognition and Artificial Intelligence (PRAI), International Conference on

作者： Yasmina Benkhoui Tahar El-Korchi Reinhold Ludwig Electrical and Computer Engineering Department Worcester Polytechnic Institute Civil and Environmental Engineering Department Worcester Polytechnic Institute

UAV-based inspections represent a promising solution to contactless civil infrastructure condition assessment, especially bridges. In this context, depth estimation is crucial as it helps predict the distance to objects, plan flight trajectories, and avoid obstacles. Recently, learning-based methods made significant progress in monocular depth estimation. However, supervised approaches require a large amount of annotated depth data which remains challenging to collect. As an alternative, researchers have been investigating self-supervised learning, where the depth estimation network is trained by projecting a view to nearby views and minimizing the re-projection photometric loss. However, current methods lack accuracy and robustness since they do not exploit structural information, leading to inaccurate spatial representations and surface discontinuities. In addition, monocular depth estimation suffers from scale ambiguity, and external or prior information is needed for scale recovery. This work sought to overcome these issues by adapting the standard joint network of estimating depth and pose based on a self-learned depth prediction network from monocular videos. The proposed method introduces a soft attention mechanism and a recurrent block. The attention mechanism guides the neural network’s attention to the global structures and local attributes and recovers the spatial relationship of visual features, whereas the recurrent block leverages sequence frames to capture temporal information in addition to spatial information. Our experiments and ablation study on AeroBridge dataset demonstrate that these modifications efficiently capture spatio-temporal information and generate competitive qualitative and quantitative results compared to state-of-the-art methods confirming the practical applicability of our design in inspection tasks.

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