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computer Vision and Machine Intelligence (CVMI), International Conference on

作者： Kaisei Matsumoto Takao Toma Shiho Oshiro Tomohisa Wada Computer Science and Intelligent Systems Program University of the Ryukyus Okinawa Japan Magna Design Net Inc Okinawa Japan Information Technology Center University of the Ryukyus Okinawa Japan Dept. of Engineering Area of Computer Science and Intelligent Systems University of the Ryukyus Okinawa Japan

This paper discusses intelligent constellation generation based on autoencoder communication system. In previous studies, the amplitude was set to fluctuate between r=0.0 and 1.0. However, when checking the generated constellation, distortion was confirmed instead of the conventional symbol arrangement. Therefore, in this paper, it compares the case where the amplitude is constant, the case where the average amplitude within a Minibatch is 1, and the case where the average amplitude is 1 for Interval time. The communication standard used in this research is IEEE 802.11a, assuming wireless Local Area Network (LAN) specifications. The IEEE 802.11a standard has an Fast Fourier Transform (FFT) length of 64, a subcarrier number of 52, and Quadrature Phase Shift Keying (QPSK) and 16 Quadrature Amplitude Modulation (QAM), modulation methods. A guard interval of 800 ns is added and the symbol length is 4000 ns. First, a simulation was performed under the condition that the amplitude was kept constant. QPSK with 4 symbols, constant amplitude model is rounded more than previous research result. 16QAM with 16 symbols is arranged regularly like lined up on a line. Second, the simulation was performed under the condition that the average amplitude within the minibatch was set to 1. QPSK with 4 symbols, appears to rotate clockwise. 16QAM with 16 symbols has a more uniform symbol placement than previous research result. Third, a simulation was performed under the condition that the average amplitude within Interval time was set to 1. QPSK with 4 symbols, is the closest to square among QPSK output results so far. The direction is slightly tilted, but if it can be rotated a little more, it may be possible to reproduce the same symbol arrangement as before. 16QAM with 16 symbols, the symbol arrangement is biased as a whole. However, it can be seen that are arranged in line on the line, perhaps due to regularity. As future work, in addition to the conditions set this time, it will exa

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An Image-Guided Robotic System for Transcranial Magnetic Stimulation: System Development and Experimental Evaluation

arXiv

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arXiv 2024年

作者： Liu, Yihao Zhang, Jiaming Ai, Letian Tian, Jing Sefati, Shahriar Liu, Huan Martin-Gomez, Alejandro Kheradmand, Amir Armand, Mehran Dept. of Computer Science JHU BaltimoreMD United States Dept. of Neurology JH Medicine BaltimoreMD United States Dept. of Mechanical Eng. JHU BaltimoreMD United States Sch. of Autom. China U. of Geosci. Hubei Wuhan China I3R U of Arkansas FayettevilleAK United States Dept. of EECS U of Arkansas FayettevilleAK United States Dept. of Neuroscience JH Medicine BaltimoreMD United States

Transcranial magnetic stimulation (TMS) is a noninvasive medical procedure that can modulate brain activity, and it is widely used in neuroscience and neurology research. Compared to manual operators, robots may improve the outcome of TMS due to their superior accuracy and repeatability. However, there has not been a widely accepted standard protocol for performing robotic TMS using fine-segmented brain images, resulting in arbitrary planned angles with respect to the true boundaries of the modulated cortex. Given that the recent study in TMS simulation suggests a noticeable difference in outcomes when using different anatomical details, cortical shape should play a more significant role in deciding the optimal TMS coil pose. In this work, we introduce an image-guided robotic system for TMS that focuses on (1) establishing standardized planning methods and heuristics to define a reference (true zero) for the coil poses and (2) solving the issue that the manual coil placement requires expert hand-eye coordination which often leading to low repeatability of the experiments. To validate the design of our robotic system, a phantom study and a preliminary human subject study were performed. Our results show that the robotic method can half the positional error and improve the rotational accuracy by up to two orders of magnitude. The accuracy is proven to be repeatable because the standard deviation of multiple trials is lowered by an order of magnitude. The improved actuation accuracy successfully translates to the TMS application, with a higher and more stable induced voltage in magnetic field sensors. © 2024, CC BY-NC-ND.

关键词： Noninvasive medical procedures

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Identification of Cancer Biomarkers for Multi-class Diagnostics through Network Analysis of RNAseq Data of Tumor-Educated Platelets

Identification of Cancer Biomarkers for Multi-class Diagnost...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ali Toccacieli Manuela Petti MSc Program in Engineering in Computer Science Sapienza University of Rome Rome Italy dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Tumor-educated platelets (TEPs) are circulating blood cells with a distinct tumor-driven phenotype and act as carriers and protectors of metastases. To date, some studies have shown that the TEPs transcriptome can be used for cancer diagnostics. The objective of this study is to propose a procedure based on differential gene expression and differential gene co-expression analyses to identify a set of key genes for multi-class cancer diagnostics. To reach this aim, we analyzed RNA-seq data (57736 genes) of 130 subjects, of whom 40 patients with glioblastoma multiforme (GBM), 35 patients with pancreatic adenocarcinoma (PAAD), and 55 healthy donors (HC). We focused our analysis on the subset of differentially expressed genes (DEGs), and we used these genes to build and analyze the differential co-expression networks, identifying the hub genes. With this procedure, we obtained a restricted set of DEGs that maximize the accuracy in classifying patients according to their conditions (GBM, PAAD, or HC). Indeed, we validated our results by comparing the achieved classification accuracy with that resulting from random selections of DEGs and we obtained that genes selected by differential co-expression (DCE) network analysis have greater predictive power than any other set of differentially expressed genes, including using all of them.

关键词： Measurement Blood platelets Network analyzers Cells (biology) Biomarkers Object recognition Gene expression

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Topic Relation Graph Construction to Identify Challenges in Introducing programming in Indonesian K-12 Education

Topic Relation Graph Construction to Identify Challenges in ...

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Smart Technology (ICE-SMARTec), IEEE International Conference on

作者： Mewati Ayub Oscar Karnalim Hapnes Toba Maresha Caroline Wijanto Hans Dulimarta Williyandie Saputra Tabitha Emanuella Kotambunan Master Program of Computer Science Maranatha Christian University Bandung Indonesia Dept. of Computer Science and Engineering Ewha Womans University Seoul South Korea School of Computing Grand Valley State University Michigan USA Informatics Engineering Maranatha Christian University Bandung Indonesia

programming can help K-12 students to develop their 21st-century core skills. Despite the benefits, programming is not common to be delivered in Indonesian K-12 education. There is a need to understand potential challenges in introducing programming to K-12 students. We developed a questionnaire survey covering four identified dimensions of challenges: administrative, facilities, teachers, and students. We also asked about common programming assessments and their preferred software features for teaching programming. Forty K-12 teachers were invited to complete the survey. The responses were analyzed with thematic analysis using a bigram-based Latent Dirichlet Allocation topic modeling and descriptive statistics. Our study shows that the challenges include limited learning modules, an insufficient number of computers, limited programming skills, and limited computational thinking skills. Scratch was the most common programming language used and many programming assessments were about debugging a program or writing a small program. Visualization and animation can be helpful in teaching programming.

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Improved Transform Algorithm of Direct Computation of Discrete Cosine for Mel-scale Frequency Cepstral Coefficient

Improved Transform Algorithm of Direct Computation of Discre...

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2021 IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2021

作者： Lai, Shin-Chi Hung, Ying-Hsiu Zhu, Yi-Chang Wang, Szu-Ting Sheu, Ming-Hwa Juang, Wen-Ho National Formosa University Dept. of Automation Engineering Yunlin Taiwan National Yunlin University of Science and Technology Dept. of Electronic Engineering Yunlin Taiwan National Formosa University Doctor's Program of Smart Industry Technology Research and Design Yunlin Taiwan Nanhua University Dept. of Computer Science and Information Engineering Chiayi County Taiwan

ISBN: (纸本)9781665437554

In this work, we proposed a direct computation of the DCT algorithm that is improved by utilizing the coefficients of cosine and sine to calculate the DCT bins for Mel-scale frequency cepstral coefficients (MFCC). Instead of computing directly, the cosine coefficient is sharply declined more than 85% at the expense of the amount of additions and multiplications. According to the PSNR comparison results, and the proposed method is similar to Jo et al.'s algorithm. which uses approximate computation, so that the PSNR value is closed to 52 dB. Although the proposed algorithm must pay for some accuracy and extra complexity in computation, it still can greatly reduce more sizes of ROM. Based on the point of interest of simple control and straightforward structure, the algorithm is a selectable design for applications to the design of MFCC. © 2021 IEEE.

关键词： Discrete cosine transforms

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Surasachai Doungtap Jirayu Petchhan Varinya Phanichraksaphong Jenq-Haur Wang International Graduate Program of Electrical Engineering and Computer Science Dept. of Electrical Engineering National Taiwan University of Science & Technology Taiwan R. O. C. Department of Computer Science and Information Engineering National Taipei University of Technology Taiwan R. O. C.

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-dept. utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle.

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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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Electricity Consumption Prediction using Generative Models

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Transactions of the Korean Institute of Electrical Engineers 2022年第1期71卷 218-224页

作者： Kim, Heesang Im, Hyeonseung Moon, Yang-Sae Dept. of Computer Science and Engineering Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Korea Republic of Interdisciplinary Graduate Program in Medical Bigdata Convergence Kangwon National University Korea Republic of

Recently, advanced metering infrastructure (AMI) has been deployed for power demand distribution and energy saving, and correspondingly traditional watt-hour meters installed in apartments and industrial sites are also being replaced with AMIs. Accordingly, power demand prediction using AMIs will become increasingly important to save electrical energy consumption. In this paper, we develop various deep learning-based electricity consumption prediction models using simple neural networks, convolutional neural networks, recurrent neural networks, and encoder-decoder-based generative models. To build prediction models, we use average power demand data collected from various home smart meters. Experimental results show that the generative model outperforms other deep learning-based models in terms of mean squared error, and we roughly explain why the generative model is better than other models by examining the activation layer output distributions. © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Watt hour meters

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SYNAPTIC WEIGHT DISTRIBUTIONS DEPEND ON THE GEOMETRY OF PLASTICITY

arXiv

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arXiv 2023年

作者： Pogodin, Roman Cornford, Jonathan Ghosh, Arna Gidel, Gauthier Lajoie, Guillaume Richards, Blake Aaron Mila McGill Canada Dept. CS and OR. Université de Montréal Mila Canada Dept. Maths and Stats Université de Montréal Mila Canada Dept. of Neurology & Neurosurgery School of Computer Science Montreal Neurological Institute McGill Canada Learning in Machines and Brains Program Mila CIFAR Canada

A growing literature in computational neuroscience leverages gradient descent and learning algorithms that approximate it to study synaptic plasticity in the brain. However, the vast majority of this work ignores a critical underlying assumption: the choice of distance for synaptic changes – i.e. the geometry of synaptic plasticity. Gradient descent assumes that the distance is Euclidean, but many other distances are possible, and there is no reason that biology necessarily uses Euclidean geometry. Here, using the theoretical tools provided by mirror descent, we show that the distribution of synaptic weights will depend on the geometry of synaptic plasticity. We use these results to show that experimentally-observed log-normal weight distributions found in several brain areas are not consistent with standard gradient descent (i.e. a Euclidean geometry), but rather with non-Euclidean distances. Finally, we show that it should be possible to experimentally test for different synaptic geometries by comparing synaptic weight distributions before and after learning. Overall, our work shows that the current paradigm in theoretical work on synaptic plasticity that assumes Euclidean synaptic geometry may be misguided and that it should be possible to experimentally determine the true geometry of synaptic plasticity in the brain. Copyright © 2023, The Authors. All rights reserved.

关键词： Geometry

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Electronic-photonic quantum systems on-chip

Electronic-photonic quantum systems on-chip

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Quantum 2.0, QUANTUM 2022

作者： Wang, Imbert Ramesh, Anirudh Kramnik, Danielius Fargas Cabanillas, Josep M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We present progress towards realizing electronic-photonic quantum systems on-chip;particularly, entangled photon-pair sources, placing them in the context of previous work, and outlining our vision for mass-producible... 详细信息

ISBN: (纸本)9781957171111

关键词： Quantum entanglement

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