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4th International Conference on Applied Technologies, ICAT 2022

作者： Cárdenas-Arias, C.G. Zuza-Hernández, E. Quiroga-Méndez, J.E. Lengerke-Perez, O. Electromechanical Engineering Faculty of Natural Sciences and Engineering Unidades Tecnológicas de Santander UTS Calle de los Estudiantes No. 9-82 Bucaramanga680005 Colombia Doctoral Program in Sustainable Materials and Process Engineering Department of Sustainable Materials and Process Engineering University of the Basque Country UPV/EHU Engineer Torres Quevedo Plaza 1 Bilbao48013 Spain Energy and Materials Research Group Mechanical Engineering School Universidad Industrial de Santander Calle 9 Carrera 27 Bucaramanga Colombia

ISBN: (纸本)9783031249709

The mechanical behavior of a reinforced polylactic material with perolera pineapple fiber study is presented in order to determine its potential as an alternative industrial input material. First, the necessary information about the lactic acid production with biodegradable materials and materials reinforced with natural fibers was collected;secondly, the procedure to be followed to generate the raw material with which the composite material was developed was defined. Thirdly, the material testing experimental design reinforced with perolera pineapple fiber was made;and finally, the stress tests were carried out on the already reinforced composite material to know its mechanical properties and determine its behavior. The results obtained allow a behavior comparison of tensile resistance of PLA and PLA reinforced with pineapple fiber. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Tensile strength

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Speech Recognition for Intelligent System in Service Robots: A Review

Speech Recognition for Intelligent System in Service Robots:...

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International Conference on Electrical engineering and Computer Science (ICECOS)

作者： Ratna Atika Suci Dwijayanti Bhakti Yudho Suprapto Department of Electrical Engineering Polytechnic of Sriwijaya Doctoral Program in Engineering Science Universitas Sriwijaya Palembang Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Department of Electrical Engineering Faculty of Engineering Palembang Universitas Sriwijaya Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

Speech recognition and response system technology in service robot research continues to evolve alongside technical advances and the increasing demand for intelligent automation across industries. The development of machine learning, digital signal processing, and artificial neural networks has brought significant advancements to speech recognition systems. While speech recognition has been implemented in various systems, there is limited discussion on categorizing these systems by examining four aspects: speech recognition applications, datasets used, emotional speech recognition, and automatic speech recognition. In this study, a review of these four aspects is conducted, focusing on the algorithms and methods used, along with their advantages and disadvantages, particularly in the context of implementing them in service robots using the Indonesian language. This study involves a literature review of 100 research papers from the last five years. The review concludes that the use of the transformer method combined with other techniques and Indonesian language datasets is still very limited. Therefore, future research will focus on developing and implementing these methods in humanoid service robots.

关键词： Intelligent automation Industries Service robots Reviews Signal processing algorithms Humanoid robots Hidden Markov models Speech recognition Machine learning Transformers

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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things 11

Intrusion Detection using Deep Neural Network Algorithm on t...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Ikhwan, Syariful Wibowo, Adi Warsito, Budi School of Postgraduate Studies Diponegoro University Doctoral Program of Information System Semarang Indonesia Institut Teknologi Telkom Purwokerto D3 Telecommunication Engineering Banyumas Indonesia Diponegoro University Computer Science Informatics Department of Science and Mathematics Faculty Semarang Indonesia Diponegoro University Statistics Department of Science and Mathematics Faculty Semarang Indonesia

ISBN: (纸本)9781665460309

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small. © 2022 IEEE.

关键词： Internet of things

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Hierarchical electrospun nanofibers treated by solvent vapor annealing as air filtration mat for high-efficiency PM2.5 capture

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Science China Materials 2019年第3期62卷 423-436页

作者： Xinxin Huang Tifeng Jiao Qingqing Liu Lexin Zhang Jingxin Zhou Bingbing Li Qiuming Peng State Key Laboratory of Metastable Materials Science and Technology Yanshan UniversityQinhuangdao 066004China Hebei Key Laboratory of Applied Chemistry School of Environmental and Chemical EngineeringYanshan UniversityQinhuangdao 066004China Department of Chemistry Science of Advanced Materials Doctoral ProgramCentral Michigan UniversityMount PleasantMI 48859USA

Recently, air pollution has become more serious and started to have a dramatic effect on the health of humans in many large cities. Generally, outdoor personal protection,such as commercial masks, cannot effectively prevent the inhalation of many pollutants. Particulate matter(PM) pollutants are a particularly serious threat to human health. Here we introduce a new efficient air filtration mat that can be used for outdoor protection. The new efficient air filter’s nanocomposite materials were successfully fabricated from poly(ε-caprolactone)/polyethylene oxide(PCL/PEO) using an electrospinning technique and solvent vapor annealing(SVA).SVA treatment endows the wrinkled fiber surface and enhances the PM2.5 capture capacity of protective masks. This nanowrinkled air filtration mat can effectively filter PM2.5 with a removal efficiency of 80.01% under seriously polluted conditions(PM2.5 particle concentration above 225 mg m-3).Our field test in Qinhuangdao indicated that the air filtration mat had a high PM2.5 removal efficiency under thick *** to commercial masks, the fabricated SVA-treated PCL/PEO air filter mat demonstrated a simpler and ecofriendly preparation process with excellent degradation characteristics, showing wide potential applications with a high filtration efficiency.

关键词： electrospinning nanofiber mat solvent vapor annealing air filtration PM2.5 removal

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Deep Learning Methods for Plankton Identification: A Bibliometric Analysis and General Review 1

Deep Learning Methods for Plankton Identification: A Bibliom...

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1st International Conference on Smart Technology, Applied Informatics, and engineering, APICS 2022

作者： Ardhi, Ovide Decroly Wisnu Soeprobowati, Tri Retnaningsih Adi, Kusworo Prakasa, Esa Rachman, Arief School of Postgraduate Studies Universitas Diponegoro Doctoral of Information System Program Semarang Indonesia Vocational School Universitas Sebelas Maret Department of Informatics Engineering Surakarta Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Biology Semarang Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Physics Semarang Indonesia Bandung Indonesia Jakarta Indonesia

ISBN: (数字)9781665489850

ISBN: (纸本)9781665489850

This study investigates trends in deep learning research on microscopic images to identify and classify plankton. We performed a bibliometric analysis using VOSviewer to display the visualizations. The first step is to extract the relevant journals from the Scopus database. Extraction from relevant journals found 42 articles, including 21 journals and 21 conferences. We analyzed publication trends and analyzes of co-authorship, co-occurrence, and citations. In addition, it examines the collaborative relationship between authors by country, the emergence of co-author keywords, and the citation of journal sources. We found that the researchers performed plankton classification tasks that achieved high accuracy (>90%). The plankton identification method uses a deep learning architecture based on the Convolutional Neural Network. Among the architectures are AlexNet, GoogleNet, InceptionV3, VGGNet (16.19), ResNet (50.101), DenseNet, NasNet, MobileNetV2, ResidualNet, Shufflenet, EfficienNet, and CapsNet. Some researchers combine CNN with SparseConvNets, LMP, SVM, MorphoCluster, and Quantification Algorithm (CC, AC, PCC, PAC, Hdy). Some methods also implement transfer learning, fine-tuning, and advanced features. In addition to the CNN approach, End-to-End Object Detection with transformers is one of the new approaches in the future to identify plankton. © 2022 IEEE.

关键词： Deep learning

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Nano-flower MnO2 coated graphene composite electrodes for energy storage devices

Nano-flower MnO2 coated graphene composite electrodes for en...

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2010 MRS Fall Meeting

作者： Cheng, Qian Tang, Jie Ma, Jun Zhang, Han Shinya, Norio Qin, Lu-Chang National Institute for Materials Science 1-2-1 Sengen Tsukuba 305-0047 Japan Doctoral Program in Materials Science and Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba 305-8577 Japan Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel Hill NC 27599-3255 United States

ISBN: (纸本)9781605112800

Graphene, two-dimensional layers of sp2-bonded carbon, has many unique properties. In this paper, graphene is decorated with flower-like MnO2 nanostructures for the application in energy storage devices. The as-prepared graphene and MnO2 nano-flowers, which were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), were assembled into an asymmetric supercapacitor. The specific capacitance of the graphene electrode reached 245 F/g at a charging current of 1 mA. The MnO2 nano-flowers which consisted of tiny rods with a diameter of less than 10 nm were coated onto the graphene electrodes by electrodeposition. The specific capacitance after the MnO2 deposition is 328 F/g at the charging current of 1 mA with an energy density of 11.4 Wh/kg and power density of 25.8 kW/kg. This work suggests that our graphene-based electrodes can be a promising candidate for high-performance energy storage devices. © 2011 Materials Research Society.

关键词： Graphene

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Cellulose in natural flocculant applications: A review 4

Cellulose in natural flocculant applications: A review

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4th International Conference on Material Strength and Applied Mechanics, MSAM 2021

作者： Fauzani, D. Notodarmojo, S. Handajani, M. Helmy, Q. Kardiansyah, T. Environmental Engineering Doctoral Study Program Bandung Institute of Technology Jalan Ganesa No. 10 West Java Bandung40132 Indonesia Department of Environmental Engineering Bandung Institute of Technology Jalan Ganesa No. 10 West Java Bandung40132 Indonesia Center for Pulp and Paper The Ministry of Industry Republic of Indonesia Jalan Raya Dayeuhkolot No. 132 West Java Bandung40258 Indonesia

Natural polymeric flocculants have gained popularity in water and wastewater treatment in recent years due to their non-toxicity and biodegradability. Because of its broad availability, renewability, sustainability, and surface modification potential, cellulose is regarded as one of the foundation polymers for flocculant production and modification. The following literature review includes of an overview of coagulation-flocculation, which is the process mechanism consisting of colloid destabilization for coagulation, followed by bridging, charge neutralization, and electrostatic patch for flocculation;aspects affecting the coagulationflocculation performance;as well as the types of coagulants and flocculants that are commonly used. Furthermore, we will go over the physical and chemical properties of flocculants, as well as their usage as a coagulant-aid in the flocculation process following coagulation and as a flocculant in direct flocculation. There is also a discussion of the most recent advances in biopolymers, which are natural materials used to alter biopolymers as flocculants such as chitosan, tannins, starch, and cellulose. Whereas there is a review of the cellulose modifications that have been performed in past research to make it a natural flocculant, the use of ramie cellulose as flocculants has never been carried out to be used as a coagulant-aid and/or flocculant in drinking water and wastewater treatment. Ramie cellulose as backbone of biomaterial composites are expected to be applied as flocculants, have good flocculation performance, and can facilitate sludge handling in water treatment plants and/or wastewater treatment plants. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Cellulose

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Digital Dictionary Using Binary Search Algorithm 1

Digital Dictionary Using Binary Search Algorithm

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1st International Conference on Computer Science and Applied Mathematic, ICCSAM 2018

作者： Fitrian, Riski Muhamad Taufik, Insan Ramadhan, Muhammad Sabir Mulyani, Neni Hutahaean, Jeperson Sitio, Arjon Samuel Sihotang, Hengki Tamando Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Doctoral Program Vocational Technology Education Postgraduate Engineering Faculty Padang State University Padang West Sumatera Indonesia Sistem Informasi STMIK Royal Kisaran Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Digital Dictionary of Computer and Network engineering can be used in the learning process of computer and nerwork enginering students. Dictionaries are generally book-shaped is hard to carry because of their thick and heavy, now can be accessed anywhere by development of web technology. Digital dictionaries can be accessed through computers, laptops dan cellphones, this is make student easily in learning process. The digital dictionary can not only be used by students of computer and network engineering, but can also by general public, as long as you have an internet connection, anyone can be use this digital dictionaries. The main process in this digital dictionary is the search process. Binary search algorithm used in the search process of binary search algoritm. Binary search algoritm search is applied to word search in this digital dictionary, because this algoritm is intended for sequintal data. program language that will be used to build this digital dictionary is PHP and MySQL. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Leveraging Heart Rate Variability and Machine Learning for Daily Activity Classification in Healthy Adult Males

Leveraging Heart Rate Variability and Machine Learning for D...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Vidya Ikawati Rahadian Yusuf Ary Setijadi Prihatmanto Tatang Sudrajat Didin Saepudin Welly Surjono Doctoral Program of School of Electrical and Information Engineering Institute of Technology Bandung Bandung Indonesia Departement of Electrical and Information Engineering Institute of Technology Bandung Bandung Indonesia Universitas Sangga Buana Bandung Indonesia

ISBN: (数字)9798331527686

ISBN: (纸本)9798331527693

Advancements in machine learning techniques for analyzing heart rate variability (HRV) show great potential in accurately measuring various activities in the field of health monitoring. This work examines the feasibility of using non-invasive HRV data gathered during everyday activities to train machine learning models for accurate activity classification. In the field of personalization, the study focuses on the difficulty of adapting to individual differences in baseline HRV. It also acknowledges that HRV is influenced by stress, physical activity, and external influences, and that it is a dynamic measure. The experimental methodology consists of a pilot study using a retrospective observational cohort approach. It utilizes a waistband device to continuously record heart rate variability (HRV) during different daily activities. The study utilizes a thorough methodology that includes statistical data description, correlation analysis, variance analysis, outlier detection, and identification of cycle periods using power spectral density. The performance of various machine learning models, such as Random Forest, Naïve Bayes, Decision Tree, and Logistic Regression, was evaluated for activity classification. The Decision Tree model exhibited superior performance. The work provides useful insights into the potential of machine learning for HRV-based activity monitoring, highlighting the importance of collecting reliable data and developing tailored models to improve accuracy and practicality.

关键词： Accuracy Databases Data models Telecommunications Decision trees Reliability Heart rate variability Monitoring Stress Stress measurement

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Phase transition behavior in microcantilevers coated with M 1-phase VO2 and M2-phase VO2:Cr thin films

Phase transition behavior in microcantilevers coated with M ...

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作者： Rúa, Armando Cabrera, Rafmag Coy, Horacio Merced, Emmanuelle Sepúlveda, Nelson Fernández, Félix E. Department of Physics University of Puerto Rico Mayagüez 00681-9000 Puerto Rico Doctoral Program in Physics Graduate Center City University of New York New York 10016 United States Applied Materials Group Electrical and Computer Engineering Department Michigan State University E. Lansing MI 48824 United States

Silicon microcantilevers were coated by pulsed laser deposition with vanadium dioxide (VO2) (monoclinic M1 phase) and V 1-xCrxO2 with x near 0.024 (monoclinic M 2 phase), and their mechanical characteristics were studied as a function of temperature through the films' insulator-to-metal transition (IMT). The undoped VO2 films grew with (011)M1 planes parallel to the substrate, while Cr-doped VO2 films grew oriented with (201)M2 and (2 01)M2 planes parallel to the substrate. In both cases, the films transformed reversibly through the IMT to the tetragonal (rutile, R) phase, with film (110)R planes oriented parallel to the substrate. The fundamental resonant frequencies of the cantilevers were measured as the temperature was cycled from ambient temperature, through the IMT, and up to 100 °C. Very high resonant frequency changes were observed through the transition for both types of samples, with increases during heating of over 11 and over 15 for the cantilevers coated with pure and Cr-doped VO2, respectively. From the resonant frequencies measured at room temperature for the bare and coated cantilevers in each case, the effective Young's moduli of the films were determined. The values obtained, assuming bulk densities for the films, are 156 ± 7.5 GPa for VO2 (M1 phase) and 102 ± 3 GPa for Cr-doped VO2 (M2 phase). Strong curvature changes during the transition to the R phase were also observed for cantilevers coated with both types of films, but these were significantly higher in the case for the Cr-doped film. Curvature changes for temperature ranges outside the IMT region were small and attributed to differential thermal expansion between film and silicon substrate. From measured cantilever tip displacements in this post-transition range-for the undoped VO 2-coated microcantilevers-a rough estimate of 110 GPa was obtained for the effective Young's modulus for R-phase VO2. The substantially higher changes in resonant frequency and curvature for V1-xCr xO2-coated cant

关键词： Thin films

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