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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Kadam Rangrao, Shrikant Patil Abhijit, Seema Sharma, Lakshay Rani, D Shobha Ukirade, Chaitali Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Computer Science Engineering Karad India Jaywant College of Management Karad India Indraprastha Institute of Information Technology Delhi India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Obstetrics and Gynecology Karad India

ISBN: (纸本)9798350360707

The Internet of Things (IoT) has brought smart healthcare systems to the medical industry. These systems are typically made up of a network, a remote server, and sensors with smart capabilities. The primary goals of this system are to offer multidimensional feature monitoring and fundamental therapy recommendations. The primary goals of Internet of Things (IoT)-based healthcare services are to enhance quality of life and offer a great user experience at an affordable price. The primary purpose of IoT is to give elderly patients with chronic illnesses access to trustworthy, efficient, and intelligent healthcare services as well as connectivity to the medical resources that are readily available. Thus, many studies are developed on the different applications which worked on the IoT for the healthcare which includes wearable as well as non-wearable devices or machines. Thus, it makes the users to obtain the data from anywhere and wherever required for the study or analysis of the patients. In the meantime, the Internet of Things is expanding to include even the tiniest sensors and the fundamentals of automation and machine-to-machine communication. © 2024 IEEE.

关键词： healthcare internet of things (IoT) network service

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Identification of coexistence of biological and non-biological aerosol particles with DAPI (4′,6-diamidino-2-phenylindole) stain

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Particuology 2023年第1期72卷 49-57页

作者： Ting Liu Jiaquan Zhang Junji Cao Han Zheng Changlin Zhan Hongxia Liu Lili Zhang Kai Xiao Shan Liu Dong Xiang Daizhou Zhang School of Environmental Science and Engineering Hubei Polytechnic UniversityHubei Key Laboratory of Mine Environmental Pollution Control and RemediationHuangshi 435003China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430063China Faculty of Environmental and Symbiotic Sciences Prefectural University of KumamotoKumamoto 862-8502Japan

The fluorescent dye 4′,6-diamidino-2-phenylindole (DAPI) has been widely used to stain microorganisms in various environment media. We applied DAPI fluorescence enumeration to airborne microorganisms and found that non-biological particles, including organic compounds, minerals, and soot, were also visible upon exposure to UV excitation under fluorescence microscope. Using laboratory-prepared biological particles as the control, we investigated the feasibility of identifying both biological and non-biological particles in the same sample with DAPI staining. We prepared biological (bacterial, fungi, and plant detritus) and non-biological (biochar, soot, mineral, metal, fly ash, salt) particles in the laboratory and enumerated the particles and their mixture with DAPI. We found that mineral particles were transparent, and biochar, soot, metals and fly ash particles were black under a filter set at excitation 350/50 nm and emission 460/50 nm bandpass (DAPI-BP), while biological particles were blue, as expected. Particles of the water-soluble salts NaCl and (NH_(4))_(2)SO_(4) were yellow under a filter set at excitation 340–380 nm and emission 425 nm long pass (DAPI-LP). Case studies with samples of dustfall, atmospheric aerosols and surface soils could allow for the quantification of the relative number of different types of particles and particles with organic matter or salt coating as well. Fluorescence enumeration with DAPI stain is thus able to identify the co-existence of biological and non-biological particles in the air, at least to the extent of those examined in this study.

关键词： 4',6-diamidino-2-phenylindole(DAPI) Biological particles Nonbiological particles Atmospheric aerosols

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Improving Recommendation Systems with a Combination of Similarity Measures on the Example of Radio Service Data 12th

Improving Recommendation Systems with a Combination of Simil...

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12th International Workshop of Advanced Manufacturing and Automation, IWAMA 2022

作者： Morozov, Jurij Saradgishvili, Sergei Tumanyan, Polina Voinov, Nikita Drobintsev, Pavel Wu, Jian Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg195251 Russia College of Mechanical and Electrical Engineering Changshu Institute of Technology Changshu215500 China

ISBN: (纸本)9789811993374

In this paper, we will experiment with a music content recommendation system using a collaborative filtering approach. The experiment will be carried out using a combination of formulas that allow you to calculate similarities when developing collaborative filtering. The Otai Coefficient and Euclidean distance were chosen as metrics, as a result of their combination, a recommendation system is obtained that gives a positive result. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Recommender systems

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ML-Based Edge Application for Detection of Forced Oscillations in Power Grids

ML-Based Edge Application for Detection of Forced Oscillatio...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Dorado-Rojas, Sergio A. Xu, Shunyao Vanfretti, Luigi Ayachi, M. Ilies I. Ahmed, Shehab Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States King Abdullah University of Science and Technology Electrical and Computer Engineering Thuwal Saudi Arabia

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

This paper presents a Machine Learning (ML) solution deployed in an Internet-of-Things (IoT) edge device for detecting forced oscillations in power grids. We base our proposal on a one-dimensional (1D) and two-dimensional (2D) Convolutional Neural Network (CNN) architecture, trained offline and deployed on an Nvidia Jetson TX2. Our work also shows the advantages of optimizing the CNNs models, after training, using TensorRT, a library for accelerating deep learning inference in real-time. Both real-world and synthetic measurement signals are employed to validate the applicability of the proposed approach. © 2022 IEEE.

关键词： Convolutional neural networks

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Soft-Prompting with Graph-of-Thought for Multi-modal Representation Learning 30

Soft-Prompting with Graph-of-Thought for Multi-modal Represe...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Yang, Juncheng Li, Zuchao Xie, Shuai Yu, Wei Li, Shijun Du, Bo School of Computer Science Wuhan University Hubei Wuhan China National Engineering Research Center for Multimedia Software Hubei Wuhan China School of Electronic Information Engineering Henan Polytechnic Institute Henan Nanyang China JD Explore Academy Beijing China

ISBN: (纸本)9782493814104

The chain-of-thought technique has been received well in multi-modal tasks. It is a step-by-step linear reasoning process that adjusts the length of the chain to improve the performance of generated prompts. However, human thought processes are predominantly non-linear, as they encompass multiple aspects simultaneously and employ dynamic adjustment and updating mechanisms. Therefore, we propose a novel Aggregation-Graph-of-Thought (AGoT) mechanism for soft-prompt tuning in multi-modal representation learning. The proposed AGoT models the human thought process not only as a chain but also models each step as a reasoning aggregation graph to cope with the overlooked multiple aspects of thinking in single-step reasoning. This turns the entire reasoning process into prompt aggregation and prompt flow operations. Experiments show that our multi-modal model enhanced with AGoT soft-prompting achieves good results in several tasks such as text-image retrieval, visual question answering, and image recognition. In addition, we demonstrate that it has good domain generalization performance due to better reasoning. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Image enhancement

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Self-excitation of Terahertz Plasmons in Graphene FETs Enabled by Transit-time Negative Dynamic Conductance 2

Self-excitation of Terahertz Plasmons in Graphene FETs Enabl...

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2nd International Conference for Advancement in Technology, ICONAT 2023

作者： Ryzhii, Maxim Ryzhii, Victor Otsuji, Taiichi Mitin, Vladimir Shur, Michael S. University of Aizu Department of Computer Science and Engineering Aizu-Wakamatsu Japan Research Institute of Electrical Communication Tohoku University Sendai Japan University at Buffalo Department of Electrical Engineering SUNY BuffaloNY United States Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9781665475174

The interband Zener-Klein interband tunneling in the field-effect transistors (FETs) with the graphene channels consisting of the reverse-biased p-i-n junctions enables the negative dynamic conductance associated with the electrons and hole propagation delays. This can lead to the self-excitation of plasmons in the gated p- and n-regions. For the submicrometer gate lengths, the frequency of these plasmons is in the terahertz (THz) range. The plasmon self-excitation in this regime can be used for the generation of THz radiation. © 2023 IEEE.

关键词： Plasmons

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Multimodal Hate Speech Event Detection - Shared Task 4, CASE 2023 6

Multimodal Hate Speech Event Detection - Shared Task 4, CASE...

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6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, CASE 2023

作者： Thapa, Surendrabikram Jafri, Farhan Ahmad Hürriyetoğlu, Ali Vargas, Francielle Lee, Roy Ka-Wei Naseem, Usman Department of Computer Science Virginia Polytechnic Institute State University United States Department of Computer Science Jamia Millia Islamia India KNAW Humanities Cluster DHLab Netherlands Institute of Mathematical and Computer Sciences University of São Paulo Brazil Singapore University of Technology and Design Singapore Singapore College of Science and Engineering James Cook University Australia

ISBN: (纸本)9789544520892

Ensuring the moderation of hate speech and its targets emerges as a critical imperative within contemporary digital discourse. To facilitate this imperative, the shared task Multimodal Hate Speech Event Detection was organized in the sixth CASE workshop co-located at RANLP 2023. The shared task has two subtasks. The sub-task A required participants to pose hate speech detection as a binary problem i.e. they had to detect if the given text-embedded image had hate or not. Similarly, sub-task B required participants to identify the targets of the hate speech namely individual, community, and organization targets in text-embedded images. For both sub-tasks, the participants were ranked on the basis of the F1-score. The best F1-score in sub-task A and sub-task B were 85.65 and 76.34 respectively. This paper provides a comprehensive overview of the performance of 13 teams that submitted the results in Subtask A and 10 teams in Subtask B. © CASE 2023 - Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-Political Events from Text, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023.

关键词： Speech recognition

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FDM Printing: A Fabrication Method for Fluidic Soft Circuits?

FDM Printing: A Fabrication Method for Fluidic Soft Circuits...

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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Savita V. Kendre Lehong Wang Ethan Wilke Nicholas Pacheco Loris Fichera Markus P. Nemitz Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Computer Science Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Mechanical and Materials Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D-printed fluidic logic gates, fabricating a valve from thermoplastic polyurethane. We investigate the 3D printing of tubing and introduce a novel extrusion nozzle for tubing production. Our approach significantly reduces the production time for soft fluidic valves from 27 hours using replica molding to 3 hours with FDM printing. We apply our 3D-printed valve to develop optimized XOR gates and D-latch circuits, presenting a rapid and cost-effective fabrication method for fluidic logic gates that aims to make fluidic circuitry more accessible to the soft robotics community.

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Automating life science labs at the single-cell level through precise ultrasonic liquid sample ejection:PULSE

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Microsystems & Nanoengineering 2024年第6期10卷 173-188页

作者： Peiran Zhang Zhenhua Tian Ke Jin Kaichun Yang Wesley Collyer Joseph Rufo Neil Upreti Xianjun Dong Luke P.Lee Tony Jun Huang Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Department of Mechanical Engineering Virginia Polytechnic Institute and State UniversityBlacksburgVA 24061USA Genomics and Bioinformatics Hub Department of NeurologyBrigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA Department of Medicine Brigham and Women’s HospitalHarvard Medical SchoolBostonMAUSA Department of Bioengineering Department of Electrical Engineering and Computer ScienceUniversity of California at BerkeleyBerkeleyCAUSA Institute of Quantum Biophysics Department of BiophysicsSungkyunkwan UniversitySuwonKorea Department of Chemistry&Nanoscience Ewha Womans UniversitySeoulKorea

Laboratory automation technologies have revolutionized biomedical ***,the availability of automation solutions at the single-cell level remains scarce,primarily owing to the inherent challenges of handling cells with such small dimensions in a precise,biocompatible ***,we present a single-cell-level laboratory automation solution that configures various experiments onto standardized,microscale test-tube matrices via our precise ultrasonic liquid sample ejection technology,known as *** enables the transformation of titer plates into microdroplet arrays by printing nanodrops and single cells acoustically in a programmable,scalable,and biocompatible *** pipetting robots,PULSE enables researchers to conduct biological experiments using single cells as anchoring points(e.g.,1 cell vs.1000 cells per“tube”),achieving higher resolution and potentially more relevant data for modeling and downstream *** demonstrate the ability of PULSE to perform biofabrication,precision gating,and deterministic array barcoding via preallocated droplet-addressable *** cells can be gently printed at a speed range of 5–20 cell⋅s−1 with an accuracy of 90.5–97.7%,which can then adhere to the substrate and grow for up to 72 h while preserving cell *** the deterministic barcoding experiment,95.6%barcoding accuracy and 2.7%barcode hopping were observed by comparing the phenotypic data with known genotypic data from two types of single *** PULSE platform allows for precise and dynamic analyses by automating experiments at the single-cell level,offering researchers a powerful tool in biomedical research.

关键词： precise liquid offering

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Physics of Graphene Dirac Plasmons and their Terahertz Device Applications 24

Physics of Graphene Dirac Plasmons and their Terahertz Devic...

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24th International Conference on Applied Electromagnetics and Communications, ICECOM 2023

作者： Otsuji, Taiichi Satou, Akira Ryzhii, Victor Ryzhii, Maxim Mitin, Vladimir Shur, Michael S. Tohoku University Research Institute of Electrical Communication Sendai Japan University of Aizu Department of Computer Science and Engineering Aizuwakamatsu Japan University at Buffalo SUNY Department of Electrial and Electronic Engineering BuffaloNY United States Computer and Electronic Engineering Rensellaer Polytechnic Institute Department of Electrial TroyNY United States

ISBN: (纸本)9798350313017

关键词： Graphene

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