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IEEE International Symposium on Biomedical Imaging

作者： Yih-Choung Yu Haki Shyntassov Padmanabh Kaushik Lisa Gabel Department of Electrical and Computer Engineering Lafayette College Easton PA USA Department of Psychology and the Neuroscience Program Lafayette College Easton PA USA

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Dyslexia (aka reading disability) is the most common cause of learning disabilities. It affects children across language orthographies, despite adequate intelligence and educational opportunity. Studies have shown that identifying children with dyslexia at young age is crucial to provide effective intervention to improve learning outcomes. Recently we demonstrated that children with reading disability exhibit impaired performance on a virtual maze learning task across language orthographies. Using a machine learning algorithm, we have achieved a classification accuracy up to 80%. This paper presents an algorithm, including image segmentation, synchronization of image and text data, saccade detection, and event alignment, using the eye-gazing data recorded from an eye tracker during maze-solving tasks. The saccadic events detected by this algorithm showed good correlation with the incorrect decisions participants made during maze-solving, which could be an additional variable to be used in the machine learning algorithm to enhance the accuracy for dyslexia classification.

关键词： Image segmentation Machine learning algorithms Correlation Accuracy Signal processing algorithms Predictive models Dyslexia

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A real-world data collection framework for a fused dataset creation for joint human and remotely operated vehicle monitoring and anomalous command detection

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 432-445页

作者： Rafaella Elia George Plastiras Eva Pettemeridou Antonis Savva Theocharis Theocharides Department of Electrical and Computer Engineering University of CyprusNicosiaCyprus KIOS Research and Innovation Center of Excellence University of CyprusNicosiaCyprus Center for Applied Neuroscience(CAN) University of CyprusNicosiaCyprus

Unmanned Remotely Operated Vehicles(ROVs)are widely used in safety-critical missions,spanning across monitoring,surveillance,and search and rescue *** most cases,the human operator controls the ROV under stressful conditions and in harsh *** physical and mental states of the operator are vital as they may cause involuntary movements,issuing unintentional commands due to fatigue or ***,a joint monitoring mechanism that will assess the operator's commands can be beneficial in preventing potentially catastrophic events,such as *** this end,in this study,we propose a data collection framework for creating a fused dataset,consisting of data obtained from both the human operator and the ROV,and we integrate stress induction to stimulate stress and fatigue that may affect operators during *** optimise the dataset,which includes the operator's physiological signals and inertial measurement unit(IMU)sensor data from the ROV,using data fusion approaches and feature *** evaluate the dataset through the statistical analysis,illustrating a statistical difference between data characterising normal and involuntary ***,we evaluate the optimised and original datasets over a variety of classifiers,demonstrating an accuracy of 94%and 95%,respectively.

关键词： operator fused operators

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Representations of fricatives in subcortical model responses: Comparisons with human consonant perceptiona)

Representations of fricatives in subcortical model responses...

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作者： Hamza, Yasmeen Farhadi, Afagh Schwarz, Douglas M. McDonough, Joyce M. Carney, Laurel H. Department of Biomedical Engineering University of Rochester RochesterNY14627 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Depts. of Neuroscience and Biomedical Engineering University of Rochester RochesterNY14627 United States Department of Linguistics University of Rochester RochesterNY14627 United States Depts. of Biomedical Engineering Neuroscience and Electrical and Computer Engineering University of Rochester RochesterNY14627 United States

Fricatives are obstruent sound contrasts made by airflow constrictions in the vocal tract that produce turbulence across the constriction or at a site downstream from the constriction. Fricatives exhibit significant intra/intersubject and contextual variability. Yet, fricatives are perceived with high accuracy. The current study investigated modeled neural responses to fricatives in the auditory nerve (AN) and inferior colliculus (IC) with the hypothesis that response profiles across populations of neurons provide robust correlates to consonant perception. Stimuli were 270 intervocalic fricatives (10 speakers × 9 fricatives × 3 utterances). Computational model response profiles had characteristic frequencies that were log-spaced from 125 Hz to 8 or 20 kHz to explore the impact of high-frequency responses. Confusion matrices generated by k-nearest-neighbor subspace classifiers were based on the profiles of average rates across characteristic frequencies as feature vectors. Model confusion matrices were compared with published behavioral data. The modeled AN and IC neural responses provided better predictions of behavioral accuracy than the stimulus spectra, and IC showed better accuracy than AN. Behavioral fricative accuracy was explained by modeled neural response profiles, whereas confusions were only partially explained. Extended frequencies improved accuracy based on the model IC, corroborating the importance of extended high frequencies in speech perception. © 2023 Acoustical Society of America.

关键词： Frequency response

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Efficient pumping of atomic frequency combs in a Tm3+:YAG crystal for broadband quantum optical storage

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Physical Review Applied 2025年第5期23卷 054076-054076页

作者： Yisheng Lei Zongfeng Li Mahdi Hosseini Department of Electrical and Computer Engineering and Applied Physics Program Northwestern University Evanston Illinois 60208 USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47907 USA

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Here, we report a storage efficiency greater than 28% in a Tm3+:YAG crystal (where YAG is yttrium aluminum garnet) at elevated temperatures, achieving this milestone without relying on optical cavities and without compromising memory bandwidth. We introduce different pumping techniques for Tm-based memories that enable multifrequency-window storage and high memory bandwidth reaching 630 MHz, significantly surpassing previous Tm-based memory demonstrations, considering the operating temperature of 3.5 K. Furthermore, we propose a general method for large-bandwidth atomic frequency memory using non-Kramers rare-earth ions (REIs) in solids, paving the way for storage efficiencies and bandwidths approaching fundamental limits. The compatibility of Tm memories with neutral-atom quantum processors and their seamless integration with scalable photonic platforms, such as lithium niobate on insulator, underscore their potential for distributed quantum computing, hybrid quantum networks, and space-based quantum communication. Our study represents a significant advancement toward practical high-performance quantum memories based on REI-doped crystals, where we predict that gigahertz bandwidth and storage efficiencies exceeding 30% are achievable at lower temperatures.

关键词： Qubits

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Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

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Light(Science & Applications) 2022年第11期11卷 2817-2831页

作者： Yueming Li Ying Jiang Lu Lan Xiaowei Ge Ran Cheng Yuewei Zhan Guo Chen Linli Shi Runyu Wang Nan Zheng Chen Yang Ji-Xin Cheng Department of Mechanical Engineering Boston UniversityBostonMA 02215USA Graduate Program for Neuroscience Boston UniversityBostonMA 02215USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Chemistry Boston UniversitBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Division of Materials Science and Engineering Boston UniversityBostonMA 02215USA Department of Biological Engineering Massachusetts Institute of TechnologyCambridgeMA 02142USA

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological *** non-invasive neuromodulation methods offer limited precision at the milimeter ***,we report opticallygenerated focused ultrasound(OFUS)for non-invasive brain stimulation with ultrahigh *** is generated by a soft optoacoustic pad(SOAP)fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane *** generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83μm,which is two orders of magnitude smaller than that of conventional transcranial-focused ultrasound(tFUS).Here,we show effective OFUS neurostimulation in vitro with a single ultrasound *** demonstrate submillimeter transcranial stimulation of the mouse motor cortex in *** acoustic energy of 0.6 mJ/cm?,four orders of magnitude less than that of tFUS,is suffcient for successful OFUS *** offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision noninvasively.

关键词： SOAP stimulation precision

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Multi-robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees

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SN computer Science 2024年第1期5卷 31页

作者： Mukhopadhyay, Shayok Umari, Hassan Koirala, Koshish Electrical & Computer Engineering and Computer Science Department University of New Haven 300 Boston Post Rd West Haven 06516 CT United States Department of Electrical Engineering American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates Mechatronics Engineering graduate program American University of Sharjah Sharjah P.O. Box 26666 United Arab Emirates

A map is necessary for tasks such as path planning or localization, which are common to mobile robot navigation. However, a map may be unavailable if the environment in which a robot navigates is unknown. Creating a map requires an exploration algorithm. Such algorithms guide robots to boundaries that separate known portions of a map from the unknown portions. Such boundaries are known as frontiers. There are image processing-based algorithms that detect frontiers. The authors’ previous work uses two, i.e., local and global, rapidly exploring random trees (RRTs) for two-dimensional exploration using a single robot. The present work applies the above to a multiagent system with three robots. A market-based strategy is used to allocate exploration tasks to the robots. Results show that the developed exploration strategy successfully explores a map in a reasonable amount of time compared to image processing-based approaches, and also reduces the map exploration cost. This strategy is readily usable for three-dimensional exploration with drones. It is also shown that the usage of a local frontier detector along with a global frontier detector helps reduce exploration time compared to simply using a global frontier detector alone. As an outline to future work, the paper also shows an extension of the proposed approach towards three-dimensional mapping using a single robot. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Exploration Mapping Multi-agent Navigation ROS RRT

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Enhancement of Antenna Gain With M&W Slot Model on EBG Reflector Structure Utilizing Reflection Phase Diagram Analysis 13

Enhancement of Antenna Gain With M&W Slot Model on EBG Refle...

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13th International electrical engineering Congress, iEECON 2025

作者： Chakunna, Payu Phusam, Nopphadon Mahatthanajatuphat, Pisit Lee, Wilaiporn Suangun, Thanakarn University of Phayao School of Engineering Phayao Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

This research demonstrates the improvement in antenna gain by utilizing an EBG reflector. The EBG reflector includes a unit cell with grooves shaped like the letters M and W to mitigate surface waves at a frequency of 2.45 GHz. The suggested EBG reflector is constructed on an FR-4 substrate exhibiting a uniform dielectric constant of 4.3, a loss tangent of 0.025, and a thickness of 1.6 mm. Furthermore, the impact of boosting the antenna gain can be analyzed by the reflection phase diagram, which exhibits values ranging from +90° to -90° at the resonant frequency of the reflector. The proposed EBG reflector comprises 5x5 unit cells. The testing results of the reflector's performance, when integrated with a general dipole antenna, indicate that it can effectively respond to the resonant frequency of 2.45 GHz, with a |S11| level below -10 dB within the frequency range of 2.2 GHz to 2.6 GHz, thereby adequately covering the IEEE 802.11 b/g/n band. The suggested EBG reflector exhibits a gain of around 6.5 dBi at 2.45 GHz, indicating its efficacy in enhancing gain relative to the standard PEC reflector. Moreover, the radiation pattern is also directional. © 2025 IEEE.

关键词： Antenna reflectors

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Temperature-Dependent Hydrogen Modulations of Ultra-Scaled a-IGZO Thin Film Transistor Under Gate Bias Stress

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2024年 5卷 9-16页

作者： Aslam, Muhammad Chang, Shu-Wei Chuang, Min-Hui Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan701401 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Recently, a-IGZO has advanced toward the next-generation electronics system because of its compatibility with complementary metal oxide semiconductor (CMOS) and back-end-of-line (BOEL) based systems. A systematic electrical characterization of a-IGZO TFT related to reliability issues, such as positive bias temperature stress (PBTS) and negative bias temperature stress (NBTS), would entitle its integration into novel electronics systems. Unexpectedly, PBTS is characterized by the transition of positive Vth shift to negative Vth shift (ΔVth, the positive shift followed by the stress and temperature activated negative shift). This transition is attributed to charge trapping/trap-site generations and hydrogen migration to the active layer. The ΔVth shift mechanism depends on the temperature and voltage stress. On the other hand, a negative ΔVth shift has been observed during the NBTS operation and could be attributed to the hole trapping at the interface of GI/IGZO. An effective suppression of the gate leakage current has also been observed during reliability tests. Simulation results reveal a pronounced potential at the edges of source and drain regions, and considered the origin of hydrogen migration into the IGZO layer. Thermal image results also reveal the strong temperature/potential distribution at the edges of the source/drain regions, indorsing the simulation results. © 2020 IEEE.

关键词： Oxide semiconductors

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Inflationary flows: calibrated Bayesian inference with diffusion-based models 24

Inflationary flows: calibrated Bayesian inference with diffu...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Daniela de Albuquerque John Pearson Department of Electrical & Computer Engineering School of Medicine Duke University Durham NC Department of Neurobiology Department of Electrical & Computer Engineering Center for Cognitive Neuroscience Duke University Durham NC

ISBN: (纸本)9798331314385

Beyond estimating parameters of interest from data, one of the key goals of statistical inference is to properly quantify uncertainty in these estimates. In Bayesian inference, this uncertainty is provided by the posterior distribution, the computation of which typically involves an intractable high-dimensional integral. Among available approximation methods, sampling-based approaches come with strong theoretical guarantees but scale poorly to large problems, while variational approaches scale well but offer few theoretical guarantees. In particular, variational methods are known to produce overconfident estimates of posterior uncertainty and are typically non-identifiable, with many latent variable configurations generating equivalent predictions. Here, we address these challenges by showing how diffusion-based models (DBMs), which have recently produced state-of-the-art performance in generative modeling tasks, can be repurposed for performing calibrated, identifiable Bayesian inference. By exploiting a previously established connection between the stochastic and probability flow ordinary differential equations (pfODEs) underlying DBMs, we derive a class of models, inflationary flows, that uniquely and deterministically map high-dimensional data to a lower-dimensional Gaussian distribution via ODE integration. This map is both invertible and neighborhood-preserving, with controllable numerical error, with the result that uncertainties in the data are correctly propagated to the latent space. We demonstrate how such maps can be learned via standard DBM training using a novel noise schedule and are effective at both preserving and reducing intrinsic data dimensionality. The result is a class of highly expressive generative models, uniquely defined on a low-dimensional latent space, that afford principled Bayesian inference.

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device 8

Objective Sleep Quality Measurement based on Fuzzy Logic and...

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8th International Conference on computer Science and Computational Intelligence, ICCSCI 2023

作者： Wijaya, Jason A. Andersen, Pauw D. Surantha, Nico Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method. © 2023 The Authors. Published by Elsevier B.V.

关键词： actigraphy artificial intelligences fuzzy logic sleep sleep quality

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