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Artificial visual perception neural system using a solution-processable MoS_(2)-based in-memory light sensor

Light(Science & Applications) 2023年第8期12卷 1583-1594页

作者： Dayanand Kumar Lana Joharji Hanrui Li Ayman Rezk Ammar Nayfeh Nazek El-Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer Engineering ProgramComputer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science Khalifa UniversityAbu Dhabi 127788United Arab Emirates

Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.

关键词： visual neural process

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Norepinephrine changes behavioral state through astroglial purinergic signaling

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Science (New York, N.Y.) 2025年第6748期388卷 769-775页

作者： Chen, Alex B. Duque, Marc Rymbek, Altyn Dhanasekar, Mahalakshmi Wang, Vickie M. Mi, Xuelong Tocquer, Loeva Narayan, Sujatha Legorreta, Emmanuel Marquez Eddison, Mark Yu, Guoqiang Wyart, Claire Prober, David A. Engert, Florian Ahrens, Misha B. Howard Hughes Medical Institute Janelia Research Campus Ashburn VA United States Department of Molecular and Cellular Biology Harvard University Cambridge MA United States Graduate Program in Neuroscience Harvard Medical School Boston MA United States Tianqiao and Chrissy Chen Institute for Neuroscience Division of Biology and Biological Engineering California Institute of Technology Pasadena CA United States Sorbonne Université Paris Brain Institute (Institut du Cerveau Institut National de la Santé et de la Recherche Médicale U1127 Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225 Assistance Publique-Hôpitaux de Paris Campus Hospitalier Pitié-Salpêtrière Paris France Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA United States Present address: Allen Institute for Brain Science Seattle WA United States Department of Automation Tsinghua University Beijing China

Both neurons and glia communicate through diffusible neuromodulators;however, how neuron-glial interactions in such neuromodulatory networks influence circuit computation and behavior is unclear. During futility-induced behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine (NE) drives fast excitation and delayed inhibition of behavior and circuit activity. We found that astroglial purinergic signaling implements the inhibitory arm of this motif. In larval zebrafish, NE triggers astroglial release of adenosine triphosphate (ATP), extracellular conversion of ATP into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. Our results suggest a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in NE-mediated behavioral and brain state transitions and position astroglia as important effectors in neuromodulatory signaling.

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Etching-free pixel definition in InGaN green micro-LEDs

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Light(Science & Applications) 2024年第8期13卷 1655-1665页

作者： Zhiyuan Liu Yi Lu Haicheng Cao Glen Isaac Maciel Garcia Tingang Liu Xiao Tang Na Xiao Raul Aguileta Vazquez Mingtao Nong Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering ProgramCEMSE DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The traditional plasma etching process for defining micro-LED pixels could lead to significant sidewall *** near sidewall regions act as non-radiative recombination centers and paths for current leakage,significantly deteriorating device *** this study,we demonstrated a novel selective thermal oxidation(STO)method that allowed pixel definition without undergoing plasma damage and subsequent dielectric *** annealing in ambient air oxidized and reshaped the LED structure,such as p-layers and InGaN/GaN multiple quantum ***,the pixel areas beneath the pre-deposited SiO_(2)layer were selectively and effectively *** was demonstrated that prolonged thermal annealing time enhanced the insulating properties of the oxide,significantly reducing LED leakage ***,applying a thicker SiO_(2)protective layer minimized device resistance and boosted device efficiency *** the STO method,InGaN green micro-LED arrays with 50-,30-,and 10-μm pixel sizes were manufactured and *** results indicated that after 4 h of air annealing and with a 3.5-μm SiO_(2)protective layer,the 10-μm pixel array exhibited leakage currents density 1.2×10^(-6)A/cm^(2)at-10 V voltage and a peak on-wafer external quantum efficiency of~6.48%.This work suggests that the STO method could become an effective approach for future micro-LED manufacturing to mitigate adverse LED efficiency size effects due to the plasma etching and improve device ***-LEDs fabricated through the STO method can be applied to micro-displays,visible light communication,and optical interconnect-based *** planar pixel geometry will provide more possibilities for the monolithic integration of driving circuits with ***,the STO method is not limited to micro-LED fabrication and can be extended to design other III-nitride devices,such as photodetectors,laser diodes,high-electron-mobility transistors

关键词： annealing protective quantum

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Bi_2Se_3/C Nanocomposite as a New Sodium-Ion Battery Anode Material

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Nano-Micro Letters 2018年第3期10卷 135-143页

作者： Lixin Xie Ze Yang Jingying Sun Haiqing Zhou Xiaowei Chi Hailong Chen ANDy X.Li Yan Yao Shuo Chen Department of Physics and TcSUH University of Houston Department of Electrical and Computer Engineering and Materials Science and Engineering Program University of Houston The Woodruff School of Mechanical Engineering Georgia Institute of Technology Clements High School

Bi_2Se_3 was studied as a novel sodium-ion battery anode material because of its high theoretical capacity and high intrinsic conductivity. Integrated with carbon,Bi_2Se_3/C composite shows excellent cyclic performance and rate capability. For instance, the Bi_2Se_3/C anode delivers an initial capacity of 527 mAh g^(-10) at 0.1 A g^(-1) and maintains 89% of this capacity over 100 cycles. The phase change and sodium storage mechanism are also carefully investigated.

关键词： Bi2Se3 Sodium-ion battery High-energy ball milling Sodium storage mechanism

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A review of the numerical methods for solving the binary Allen–Cahn equation

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Physica A: Statistical Mechanics and its Applications 2025年 670卷

作者： Lee, Hyun Geun Li, Yibao Yang, Junxiang Kwak, Soobin Hwang, Youngjin Ham, Seokjun Kim, Hyundong Jyoti Nam, Yunjae Kim, Junseok Department of Mathematics Dongguk University Seoul04620 Korea Republic of School of Mathematics and Statistics Xi'an Jiaotong University Xi'an710049 China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China Department of Mathematics Korea University Seoul02841 Korea Republic of Department of Mathematics and Physics Gangneung-Wonju National University Gangneung25457 Korea Republic of Smart infrastructure Gangneung-Wonju National University Gangneung25457 Korea Republic of The Institute of Basic Science Korea University Seoul02841 Korea Republic of Program in Actuarial Science and Financial Engineering Korea University Seoul02841 Korea Republic of

In this review, we present an overview of numerical methods to solve the binary Allen–Cahn (AC) equation, which is extensively used to model phase separation processes in materials science. It describes the time-dependent evolution of interfaces between two phases and accounts for both local reaction kinetics and diffusion effects. This equation plays a critical role in understanding the behavior of interfaces. The AC equation has various applications across fields such as materials science, physics, and biology, where it helps to analyze and predict phenomena such as phase transitions, grain boundary motion, and pattern formation in complex systems. Its importance lies in its ability to model the dynamics of interfaces and help the study of pattern formation and phase transitions in diverse environments. We discuss various computational methodologies developed for this important mathematical model and describe their strengths, limitations, and applications in diverse scientific domains. © 2025 Elsevier B.V.

关键词： Rate constants

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Survival Analysis of Kasturi Tobacco Plants in Jember District using the Stratified Cox and Extended Cox Models

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MethodsX 2025年

作者： Angga Iryanto Pratama Dwi Rantini Ratih Ardiati Ningrum Arip Ramadan Fazidah Othman Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Research Group of Data-Driven Decision Support System Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia

In 2022, tobacco was the top export commodity, generating $106.3 million in sales. East Java Province contributes significantly to Indonesia's tobacco production, with an annual output of 188.6 thousand tons. Jember Regency is the area in East Java Province which is a Kasturi tobacco cultivation area. The productivity of Kasturi tobacco continues to decrease due to several factors that can affect the survival of the tobacco. This study aims to analyze the survival of Kasturi tobacco by creating stratified Cox and extended Cox models in order to handle factors that cannot fulfill the proportional hazard assumption. Based on the results of the analysis, the stratified Cox model is the best model with AIC and BIC values of 798.108 and 805.5748 respectively, while the extended Cox has AIC and BIC values of 840.2186 and 850.1732 respectively. Variables that can significantly affect the survival of Kasturi tobacco are the variable concentration of ZA fertilizer, pesticide concentration. The addition of ZA fertilizer must be appropriate, because if excessive it can cause poisoning of tobacco plants. Likewise with pesticides, if excessive it will cause damage to the leaves. This policy can increase the productivity of Kasturi tobacco. Then, Jember Regency contributes greater export capacity. • This paper aims to determine the factors that affect the survival of Kasturi tobacco plants in Jember • By using the extended Cox model, the best one is obtained using the Heaviside function with AIC and BIC values of 840.2186 and 850.1732, respectively • The stratified Cox model is better than the extended Cox model, which has AIC and BIC values of 798.108 and 805.5748, respectively

关键词： Productive Agriculture Cox Proportional Hazard Stratified Cox Extended Cox Kasturi Tobacco

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An automated entrepreneurial team selection tool 123

An automated entrepreneurial team selection tool

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123rd ASEE Annual Conference and Exposition

作者： Sassenfeld, Rolfe J. Nogales, Luke Gamillo, Barbara Andrea New Mexico State University Program Coordinator of the Electronics and Computer Engineering Program Engineering Technology Department United States

This is a Work in Progress paper and will focus on the development and implementation of a software tool for engineering entrepreneurship team selection. Students working in teams is an integral part of today's engineering learning experience. Selection of students for team placement is often done manually or in some other ad hoc fashion. We present an automated software tool we call "TeamBuilder" for forming teams in the classroom, as well as for supporting forming entrepreneurial teams. Our tool incorporates factors such as the student's personality, experience, major, and gender. TeamBuilder uses the Teamology approach, which utilizes Carl Jung's personality formula, similar to the Myers-Briggs type indicator, to classify a student's primary cognitive mode. The TeamBuilder program also incorporates a student's demographic information, enabling users to better specify the team makeup. Instructors can select and prioritize the criteria for group composition and TeamBuilder automatically builds the teams. This tool allows any instructor to quickly form teams that have diversity or similarities with respect to personality type, primary cognitive modes, academic major, specific experience or expertise, and gender. With TeamBuilder, instructors can prioritize which factors are most important for the particular team exercise. TeamBuilder also offers the ability to create completely randomized student teams. This tool can support and facilitate researchers studying the effect of team composition on student learning. Instructors can even use TeamBuilder to create randomized control teams to use as comparison to teams with specific compositions. In this paper we discuss the evolution of the TeamBuilder software and its use in the entrepreneurship team formation. We provide illustrative examples of TeamBuilder in use within courses to study the effect on students' team formation preferences. Initial data is used to directionally assess the performance of teams formed ad hoc

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A Classifiers Experimentation with Quantum Machine Learning

A Classifiers Experimentation with Quantum Machine Learning

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2023 International Electrical engineering Congress, iEECON 2023

作者： Khemapatapan, Chaiyaporn Thepsena, Thammanoon Jeamaon, Aomduan College of Innovative Technology and Engineering Dhurakij Pundit University Computer Engineering Program Bangkok Thailand

ISBN: (纸本)9798350332360

Quantum Computing is a new way to create a different type of computer system from Quantum Mechanics. Quantum machine learning is one of the applications took the benefit from qauntum computers. In this experiment, we use the IBM Qiskit library to study how well a quantum machine learning classifier works. We made two different colored dots to represent the two-class dataset. The quantum circuit can be collected from the Qiskit library. The 1st and 2nd order feature map schemes operated by oracle quantum oracle functions are applied before making a classification. Finally, we can call the quantum support vector machine or QSVM function to classify data. Kernel matrix from the studied qauntum model shows that quantum computing can be used to clearly classify classes of the dataset with 100 percent accuracy. © 2023 IEEE.

关键词： Support vector machines

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Meteorological Prediction Using Cloud's Images 12

Meteorological Prediction Using Cloud's Images

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12th International Electrical engineering Congress, iEECON 2024

作者： Ongkittikul, Surachai Jundang, Nattapong Panyokaew, Thanayut Department Of Computer Engineering Mahanakorn Institute Of Innovation Faculty Of Engineering And Technology Mahanakorn University Of Technology Bangkok Thailand Mahanakorn University Of Technology Engineering Program In Computer Engineering And Artificial Intelligence Faculty Of Engineering And Technology Bangkok Thailand

ISBN: (纸本)9798350383591

This paper uses YOLO deep learning to create a predict system for Meteorological Service for Air Navigation with a total of 5 types of forecast results: BKN, CAVOK, FEW, OVER and SCT. Indicative information for evaluating the image is observing the nature of the clouds arranged together and comparing them to quantities in the sky using the unit of measurement 'okta', which is divided into 8 parts of the image. Therefore, the nature of using deep learning in the article is to teach deep learning to recognize various image characteristics both during the day and at night in order to use the results of the forecast to inform the weather conditions in the sky. The process in this article consists of 3 steps: The first step is to train the data with images with different characteristics from the 5 data types. The next step is to test the accuracy of the weights generated from the training and training steps. The final step is to use water values to create a decision-making system for users. From the experiment, private dataset in this paper, more than 2500 images were used to participate in the experiment. The results of the experiment found that the average results of precision, recall, mAP50, and mAP50-95 could be measured at 84.7%, 92.1%, 95.7%, and 95.3%, respectively. © 2024 IEEE.

关键词： Air navigation

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Developing a rubric to assess critical thinking in assignments with an onen-ended component

Developing a rubric to assess critical thinking in assignmen...

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2009 ASEE Annual Conference and Exposition

作者： Alfrey, Karen Cooney, Elaine Undergraduate Program in Biomedical Engineering IUPUI Electrical and Computer Engineering Technology IUPUI United States

The ability to think critically is vital to success in engineering and technology practice. Employers in these fields, however, consistently identify critical thinking as one of the skills that is not sufficiently developed in new college graduates, and call upon engineering and technology educators to address this obvious need. Unfortunately, critical thinking is a developmental skill that cannot be taught simply by the usual methods - step-by-step instruction followed by repetitive drills - used for other technical skills. Critical thinking must instead be nurtured through practical experience solving problems with appropriate guidance and reinforcement. One very effective context for developing such skills is in open-ended assignments with no single "right" answer, to which students must apply not only their technical knowledge, but also an element of critical judgment, to determine which approach among many possible will yield the most reasonable and applicable results. For educators, a key component of nurturing critical thinking is learning to recognize and reinforce it when it happens, or nudge students toward such behaviors when it is not happening but should be. Toward that end, we have developed a rubric to assess critical thinking during several phases (initial design or set-up;testing of method;evaluation of results) of open-ended assignments in engineering and technology. The rubric is designed to be generally applicable to open-ended assignments at every level (freshman through senior) in engineering and technology, allowing users to track the development of critical thinking skills as students progress through the curriculum. We present the rubric and preliminary results from applying it to two different open-ended assignments. © American Society for engineering Education, 2009.

关键词： Students

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