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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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Electrochemical measurement of serotonin by Au-CNT electrodes fabricated on microporous cell culture membranes

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Microsystems & Nanoengineering 2020年第1期6卷 494-506页

作者： Ashley A.Chapin Pradeep R.Rajasekaran David N.Quan Liangbing Hu Jens Herberholz William E.Bentley Reza Ghodssi Fischell Department of Bioengineering College ParkMD 20742USA Institute for Systems Research College ParkMD 20740USA Department of Materials Science and Engineering College ParkMD 20740USA Department of Psychology and Neuroscience and Cognitive Science Program College ParkMD 20740USA Institute for Bioscience and Biotechnology Research RockvilleMD 20850USA Robert E.Fischell Institute for Biomedical Devices RockvilleMD 20850USA Department of Electrical and Computer Engineering College ParkMD 20742USA

Gut–brain axis(GBA)communication relies on serotonin(5-HT)signaling between the gut epithelium and the peripheral nervous system,where 5-HT release patterns from the basolateral(i.e.,bottom)side of the epithelium activate nerve *** have been few quantitative studies of this gut-neuron signaling due to a lack of real-time measurement tools that can access the basolateral gut *** vitro platforms allow quantitative studies of cultured gut tissue,but they mainly employ offline and endpoint assays that cannot resolve dynamic molecular-release ***,we present the modification of a microporous cell culture membrane with carbon nanotube-coated gold(Au-CNT)electrodes capable of continuous,label-free,and direct detection of 5-HT at physiological *** characterization of single-walled carbon nanotube(SWCNT)-coated Au electrodes shows increased electroactive surface area,5-HT specificity,sensitivity,and saturation time,which are correlated with the CNT film drop-cast *** microliters of CNT films,with a 10-min saturation time,0.6μA/μM 5-HT sensitivity,and reliable detection within a linear range of 500 nM–10μM 5-HT,can be targeted for high-concentration,high-time-resolution 5-HT *** films(12.5μL)with a 2-h saturation time,4.5μA/μM 5-HT sensitivity,and quantitative detection in the linear range of 100 nM–1μM can target low concentrations with low time *** electrodes achieved continuous detection of dynamic diffusion across the porous membrane,mimicking basolateral 5-HT release from cells,and detection of cell-released 5-HT from separately cultured RIN14B cell ***-integrated cell culture systems such as this can improve in vitro molecular detection mechanisms and aid in quantitative GBA signaling studies.

关键词： release saturation dynamic

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Detecting defects of railway tracks by using computer vision methodology

Detecting defects of railway tracks by using computer vision...

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IISE Annual Conference and Expo 2021

作者： Ravishankar, Premkumar Tokgoz, Berna Eren Zhang, Xulong Zhang, Jing Hwang, Seokyon Department of Industrial and Systems Engineering Lamar University BeaumontTX United States Department of Computer Science Lamar University BeaumontTX United States Construction Management Program Lamar University BeaumontTX United States

ISBN: (纸本)9781713838470

Maintaining railway tracks in healthy conditions is critical to ensuring the safe operation of railroad transportation. According to the Federal Railroad Administration (FRA), nearly 23% of train accidents that occurred between 2015 to 2020 were due to the defects of the tracks. In an effort to prevent such accidents, railway companies regularly inspect tracks to detect and fix defects of track systems. This research proposes an innovative method for conducting railroad track inspection to enhance the maintenance operation. The proposed approach aims to overcome the existing inspection practices based on human observation that is costly, time-consuming, and error prone. To this end, the proposed method utilizes computer vision methodologies to achieve high-level automation and accuracy of defect detection through the analysis of digital images. The outcome of this study is envisioned to help railway companies perform predictive maintenance more effectively and, thereby, reduce the risk of train accidents and increase the resiliency of their assets. © 2021 IISE Annual Conference and Expo 2021. All rights reserved.

关键词： Railroad tracks

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Uncertainty Quantification Using Subsampling for Assembly-Free Estimates of Genomic Distance and Phylogenetic Relationships 26th

Uncertainty Quantification Using Subsampling for Assembly-F...

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26th International Conference on Research in Computational Molecular Biology, RECOMB 2022

作者： Rachtman, Eleonora Sarmashghi, Shahab Bafna, Vineet Mirarab, Siavash Bioinformatics and Systems Biology Graduate Program UC San Diego La JollaCA United States Department of Electrical and Computer Engineering UC San Diego La JollaCA United States Department of Computer Science and Engineering UC San Diego La JollaCA United States

Computing the distance between two genomes, often without using alignments or even access to assembled sequences, is fundamental to many downstream analyses. © 2022, The Author(s), under exclusive license to Spri... 详细信息

ISBN: (纸本)9783031047480

关键词： Uncertainty analysis

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Glucose Sensing Utilizing Complex-Valued Neural Networks 23

Glucose Sensing Utilizing Complex-Valued Neural Networks

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Lv, Yiqi Meng, Xiang Luo, Yong Pei, Yan The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University China and Jt. International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai China Doctoral Program Grad. Sch. of Comp. Science and Engineering Graduate Department of Computer and Information Systems University of Aizu Aizuwakamatsu Japan Computer Science Division University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9798400700705

This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter of glucose with the concentration range of 0-300mg/dL in the 60-80 GHz frequency band by High Frequency Structure Simulator (HFSS) simulations. Then we combine the sensing model with a neural network to detect and predict the glucose concentration relying on the learning ability of the neural network. In the prediction of the concentration of unknown samples, the absolute error between the predicted value and the true value is within 5mg/dL, which confirms the ability of the proposed CVNN model. © 2023 ACM.

关键词： Millimeter waves

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Controller Design via Adaptive Critic and Model Reference Methods

Controller Design via Adaptive Critic and Model Reference Me...

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International Joint Conference on Neural Networks 2003

作者： Lendaris, G.George Santiago, Roberta McCarthy, Jay Carroll, Michael Systems Science Ph.D. Program Electrical and Computer Engineering Portland State University Portland OR 97201 United States Systems Science Ph.D. Program Portland State University Portland OR 97201 United States Electrical Engineering Department Portland State University Portland OR 97201 United States Computational Neuroscience University of Chicago Chicago IL United States

Dynamic programming (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adaptive Critics (AC) provide computationally feasible means for performing approximate Dynamic programming (ADP). The term 'adaptive ' in A C refers to the critic 's improved estimations of the Value Function used by DP. To apply DP, the user must craft a Utility function that embodies all the problem-specific design specifications/criteria. Model Reference Adaptive Control methods have been successfully used in the control community to effect on-line redesign of a controller in response to variations in plant parameters, with the idea that the resulting closed loop system dynamics will mimic those of a Reference Model. The work reported here 1) uses a reference model in ADP as the key information input to the Utility function, and 2) uses ADP off-line to design the desired controller. Future work will extend this to on-line application. This method is demonstrated for a hypersonic shaped airplane called LoFL YTE®;its handling characteristics are natively a little "hotter" than a pilot would desire. A control augmentation subsystem is designed using ADP to make the plane "feel like " a better behaved one, as specified by a Reference Model. The number of inputs to the successfully designed controller are among the largest seen in the literature to date.

关键词： Adaptive control systems

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Reversible JPEG Data Hiding Based on EMD

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通讯和计算机（中英文版） 2012年第10期9卷 1135-1141页

作者： Wen-Chung Kuo Shao-Hung Kuo Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Yunlin 672 Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Yunlin 640 Taiwan

As the rapid growth of smart phone technology, people have a lot of digital image information such as digital photos or videos. Both data hiding and data compression are very important technologies in image processing field. On the overview, it seems that there is no relationship between data hiding and data compression because data hiding mechanisms focus on information security and data compression mechanisms emphasize the compression ratio. However, the more secret data is embedded, the more capacity the stego image increases. Actually, they are closely related. Until now, there are many literatures to discuss the secret data how to be embedded into the media image and keeps the original capacity as soon as possible. In this paper, a reversible data hiding scheme based on EMD data hiding and JPEG (Joint Picture Experts Group) compression technology will be proposed. According to experimental results, the authors can prove that our proposed scheme maintains high embedding capacity, security and good compression ratio.

关键词：数据隐藏 JPEG EMD 可逆数字图像信息数据嵌入压缩技术数据压缩

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Prediction of porosity in casting junctions using a mathematical model developed through design of experiments

Prediction of porosity in casting junctions using a mathemat...

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39th Annual North American Manufacturing Research Conference, NAMRC39

作者： Mane, Abhay Awad, Mahmoud Orady, Elsayed Knight, James College of Engineering and Computer Science AENG Program University of Michigan-Dearborn Dearborn MI United States Department of Industrial Engineering ALHOSN University Abu Dhabi United Arab Emirates Department of Industrial and Manufacturing Systems Engineering University of Michigan-Dearborn Dearborn MI United States

ISBN: (纸本)9781618390578

Proper design of castings is essential to avoid casting defects that cannot be eliminated by design of tooling and process parameters. Shrinkage porosity is one of the defects which usually occur at casting junctions and cannot be easily eliminated. Currently, designers use rules that were established based on experience and intuition and are not supported by proper experimentation. In this paper an approach to design and optimize design of casting junctions using a database of mathematical models is presented. The mathematical models give relationships between porosity and the junctions' dimensional features. To illustrate this approach, a mathematical model for a V-junction has been developed using Design of Experiments (DoE) and regression analysis techniques. The experimental runs for the study are established using a D-optimality criterion and conducted using MAGMASoft, comprehensive software for casting simulation, for measuring porosity in casting junctions. The simulations carried out in MAGMASoft are validated by comparing its results with experimental results from previous studies. The mathematical model is then developed by applying regression analysis. The results of the model have been validated and found to agree with both the experimental and the validation simulation experiments.

关键词： Regression analysis

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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A robotic and virtual testing platform highlighting the promise of soft wearable actuators for wrist tremor suppression

Device

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Device 2025年

作者： Alona Shagan Shomron Christina Chase-Markopoulou Johannes R. Walter Johanna Sellhorn-Timm Yitian Shao Tobias Nadler Audrey Benson Isabell Wochner Ellen H. Rumley Isabel Wurster Philipp Klocke Daniel Weiss Syn Schmitt Christoph Keplinger Daniel F.B. Haeufle Robotic Materials Department Max Planck Institute for Intelligent Systems Stuttgart Germany Institute for Modelling and Simulation of Biomechanical Systems University of Stuttgart Stuttgart Germany Stuttgart Center for Simulation Science (SimTech) University of Stuttgart Stuttgart Germany Hertie Institute for Clinical Brain Research University of Tübingen Tübingen Germany Haptic Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart Germany Institute for Computer Engineering (ZITI) University of Heidelberg Heidelberg Germany Paul M. Rady Department of Mechanical Engineering University of Colorado Boulder CO USA Center for Neurology Department of Neurodegenerative Diseases University of Tübingen Tübingen Germany Center for Bionic Intelligence (BITS) Tübingen and Stuttgart Germany Material Science and Engineering Program University of Colorado Boulder CO USA Werner Reichardt Center for Integrative Neuroscience University of Tübingen Tübingen Germany

Nearly 80 million people in the world deal with medical conditions that cause involuntary periodic movements known as tremors. Wearable soft robotic devices offer a potential solution for actively suppressing these tremors. However, existing prototypes face limitations in actuation performance and complex testing procedures. We present a comprehensive approach for the rapid evaluation of emerging wearable tremor-suppression technologies. This method combines reproducing patient-recorded tremor episodes and measuring tremor suppression in a robotic platform, termed a “mechanical patient”, with validation of the achieved suppression performance of soft actuators via biomechanical modeling, thereby avoiding time-consuming clinical testing in the early stages of development. Using this approach, we highlight that an antagonistic pair of slim and lightweight electrohydraulic actuators can effectively suppress clinically relevant tremors between 2 and 8 Hz. The biomechanical model confirms that the pair of actuators generates adequate suppression forces for all tested tremors.

关键词： tremor suppression mechanical patient soft actuators wearable devices biomechanical simulation DTI-4: Validate

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