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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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Deep Multi-Scale Residual Learning-based Blocking Artifacts Reduction for Compressed Images

Deep Multi-Scale Residual Learning-based Blocking Artifacts ...

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IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)

作者： Min-Hui Lin Chia-Hung Yeh Chu-Han Lin Chih-Hsiang Huang Li-Wei Kang Department of Electrical Engineering National Sun Yat-sen University Kaohsiung Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781538678855

Blocking artifact, characterized by visually noticeable changes in pixel values along block boundaries, is a general problem in block-based image/video compression systems. Various post-processing techniques have been proposed to reduce blocking artifacts, but most of them usually introduce excessive blurring or ringing effects. This paper presents a deep learning-based compression artifacts reduction (or deblocking) framework relying on multi-scale residual learning. Recent popular approaches usually train deep models using a per-pixel loss function with explicit image priors for directly producing deblocked images. Instead, we formulate the problem as learning the residuals (or the artifacts) between original and the corresponding compressed images. In our deep model, each input image is down-scaled first with blocking artifacts naturally reduced. Then, the learned SR (super-resolution) convolutional neural network (CNN) will be used to up-sample the down-scaled version. Finally, the up-scaled version (with less artifacts) and the original input are fed into the learned artifact prediction CNN to obtain the estimated blocking artifacts. As a result, the blocking artifacts can be successfully removed by subtracting the predicted artifacts from the input image while preserving most original visual details.

关键词： Image coding Transform coding Image restoration Discrete cosine transforms Artificial intelligence Image resolution Convolutional neural networks

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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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Thermal runaway evaluation of α-methylstyrene and trans-β-methylstyrene with benzaldehyde

Thermal runaway evaluation of α-methylstyrene and trans-β-...

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作者： Lin, S.-Y. Tseng, J.-M. Lee, M.-K. Wu, T.-C. Shu, C.-M. Doctoral Program Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology 123 University Rd. Douliou Yunlin 64002 Taiwan Department of Occupational Safety and Health Chia-Nan University of Pharmacy and Science 60 Er-Jen Rd. Jen-Te Tainan 71710 Taiwan Department of Safety Health and Environmental Engineering HungKuang University 34 Chung-Chie Rd. ShaLu Taichung 43302 Taiwan

Styrene is an important chemical in the petrochemical industry. In recent years, there have been sporadic releases, runaway reactions, fires, and thermal explosion accidents incurred by styrene and its derivatives worldwide. The purpose of this study was to estimate the impact of styrene and its derivatives of α-methylstyrene (AMS) and trans-β-methylstyrene (TBMS) contacting with benzaldehyde. Experiments were carried out to evaluate the thermokinetic parameters estimated by differential scanning calorimetry (DSC) and thermal activity monitor III (TAM III). TAM III was used to determine the fundamental thermokinetics under various isothermal temperatures, 80, 90 and 100C. This autocatalytic reaction was demonstrated in thermal curves. After styrene was contacted with benzaldehyde, the exothermic onset temperature (T 0) and the total heat of reaction (Q total) were altered by DSC tests. When benzaldehyde is mixed with AMS and TBMS, the reaction time will be shorter but the enthalpy reduced, as revealed by TAM III tests. As AMS and TBMS, respectively, were contacted with benzaldehyde, both exothermic phenomena were changed during the reaction excursion. According to the results of this research, an operator should dictate the oxygen concentration in order to avoid any potential hazards during handling and transportation. © 2009 Akadémiai Kiadó, Budapest.

关键词： Differential scanning calorimetry

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Integration of Local Traditions Bugis-Makassarese: Learning Strategies to Improve Mathematical Communication Skills 2

Integration of Local Traditions Bugis-Makassarese: Learning ...

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2nd Annual engineering and Vocational Education Conference, AEVEC 2020

作者： Asfar, A.M.I.T. Asfar, A.M.I.A. Nurannisa, A. Department of Mathematics Education STKIP Muhammadiyah Bone Dg. Pasolong Street No. 62 Watampone Indonesia Doctoral Program in Science Education Universitas Negeri Makassar Bonto Langkasa street Makassar Indonesia Department of Chemical Engineering of State Polytechnic of Ujung Pandang Tamalanrea Makassar Indonesia

Communication skill is of local Bugis-Makasar one of skill needed in mathematical learning in order that the students can solve the problem in social life particularly economic mathematic. Integration of local tradition sipakatau, sipakainge and sipakalebbi consists of philosophy which can increase students' communication skill. The purpose of this study is to find out the improvement of students' communication skill of STKIP Muhammadiyah Bone in using learning strategy of 3S. Design of this study was experimental research Quasi Experimental Design using Nonequivalent Control Group Design. Based on the results of this study can be concluded that the earning strategy of 3S is effective in improving student's communication skill in economic mathematics in STKIP Muhammadiyah Bone not only on students' cognitive side but also affective and psychomotor side. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Multi-tenant Cloud SaaS Application for a meeting to task transition via deep learning models

Multi-tenant Cloud SaaS Application for a meeting to task tr...

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Artificial Intelligence and Internet of Things (GCAIoT), IEEE Global Conference

作者： Viktor Walter-Tscharf Department of Information Engineering and Computer Science Doctoral Program Industrial Innovation Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology

ISBN: (纸本)9798350309850

Thought digitalisation and the post pandemic period online meetings increase by 12.9% and number of attendees by 13.5%. According to Zoom, Google Meets, and MS Teams they collectively increased there amount of active users from March 2020 until june 2021 by 253%. Additionally virtual meetings are becoming inefficient, unproductive and unstructured, where results are not documented correctly. The intention is to shift those statistics by revolutionising the way online meeting are held. The paper outlines the technical requirements for a user-friendly web application that allows to reproduce a virtual meeting including agreements, its participants interactions and highlighting relevant sequences, is outlined. The developed AI meeting wizard autonomously documents the discussed content in the form of notes, to-dos tasks and integrates them directly into task management, mail or calendar tools. Reinforcing the focus on the discussion by increased interaction and productivity instead of task management and note taking.

关键词： Technical requirements Productivity Pandemics Software as a service Speech recognition Internet of Things Task analysis

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Simulation studies on dynamic and distributed domain-based mobile IPv6 mobility management

Simulation studies on dynamic and distributed domain-based m...

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IEEE International Conference on Networks

作者： Chang Woo Pyo Jie Li H. Kameda Doctoral Program System & Information Engineering University of Tsukuba Tsukuba Science City Ibaraki Japan Institute of Information Science & Elelctronics University of Tsukuba Tsukuba Science City Ibaraki Japan

ISBN: (纸本)0780377885

We address mobility management for the Internet protocol version 6 in mobile networks, namely mobile IPv6 (MIPv6). To correctly transfer IPv6 packets to a mobile node (MN), the MN has to update its binding to the home network while roaming away from its home network. Mobile IP networks suffer high binding update traffic from high rates of handoffs and the long packet delivery delay from the large distance to the home network. In this paper, we introduce a dynamic and distributed mobility management protocol for MIPv 6 to reduce the binding update and packet delivery delay and traffic. We describe the basic protocol operations, and examine the performance improvement of our mobility management against the previous mobile IP mobility management methods. We show that the dynamic and distributed mobility management method outperforms other previous methods, and the dynamic approach provides the optimal mobility solution for MIPv6 and the distributed approach can decentralize the network load.

关键词： Mobile radio mobility management Home automation Cities and towns Telecommunication traffic Protocols Systems engineering and theory Information science IP networks Mobile communication Internet

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A Systematic Integrated Literature Review of Clinical Data Management Platforms of HL7 FHIR

A Systematic Integrated Literature Review of Clinical Data M...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Franz Frederik Walter Viktor Walter-Tscharf Department of Information Engineering and Computer Science Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology Doctoral Program Industrial Innovation

This study is dedicated to a critical investigation of the existing approaches toward a data visualization management platform based on Fast Health Interoperability Resources (FHIR). Despite the growing popularity of FHIR, the available evidence provides a compelling reason to believe that its use is still accompanied by a significant number of technical challenges. Therefore, the development of tools to ensure its convenient visualization remains a pressing need for a variety of stakeholders operating in the healthcare industry. Results of the systematic literature review that included 26 studies provide valuable information about the most popular instruments in this area, such as the OpenEHR CKM approach. The review offers a critical discussion of the most important advantages and disadvantages of different approaches. It provides valuable recommendations for further research as well as practical recommendations concerning the best ways to utilize data visualization platforms based on FHIR. It defines the tradeoff of functionality versus the ease of dissemination as one of the most important problems facing most platforms and suggests avenues for developing additional tooling support for visualizing FHIR. The results of the research could be useful both for scientists and practitioners.

关键词： Industries Systematics Bibliographies Instruments Data visualization Pressing Medical services

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Parallel Computing Approach for Preprocessing AIS Data in Transshipment Feature Extraction

Parallel Computing Approach for Preprocessing AIS Data in Tr...

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International Conference on Smart Green Technology in Electrical and Information Systems (ICSGTEIS)

作者： Widyadi Setiawan Linawati Linawati I Made Oka Widyantara Dewa Made Wiharta Putu Arya Mertasana Sri Andriati Asri Doctoral Program of Engineering Science Udayana University Denpasar Indonesia Electrical Engineering Departement Udayana University Denpasar Indonesia Electrical Engineering Departement Politeknik Negeri Bali Denpasar Indonesia

AIS (Automatic Identification System) data is an important data source in the shipping and logistics industry to track and monitor ships in real-time. Extraction of transshipment features from AIS data is essential in understanding the pattern and characteristics of transshipment activity at a particular port or place. This study discusses an efficient AIS data preprocessing framework to prepare the transshipment feature extraction. The preprocessing steps include data collection, data cleansing, trajectory extraction, trajectory cleaning, and overlapping trajectory extraction. One of the crucial approaches used in this study is the application of parallel computing. Parallel computing allows us to execute independent data processing tasks at the same time simultaneously. In AIS data preprocessing, the parallel approach allows us to clean, populate, and process data from many vessels in less time. To test the applicability, we created a final comparison for different types of ships based on its AIS data for Indonesia from November 2022 to April 2023. Using parallel computing to process AIS data makes data processing more efficient, especially for large and complex AIS data. This efficiency accelerates data preparation before transshipment feature extraction. The results show that the framework can accelerate runtime and improve trajectory quality.

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Rice Variety Identification Using Edge Feature Extraction and Texture-Based Segmentation

Rice Variety Identification Using Edge Feature Extraction an...

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

作者： Setiawan, Aji Adi, Kusworo Widodo, Catur Edi Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Faculty of Engineering Darma Persada University Department of Information Technology Jakarta Indonesia Diponegoro University School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia

ISBN: (纸本)9798350339215

This research proposes a methodology for identifying the optimal feature combination using Support Vector Machine (SVM) based on edge and texture features. Canny, Sobel, and Prewitt for edge detection and GLCM, Gabor, and LBP for texture analysis are popular feature extraction techniques widely employed in various cases. The approach combines edge and texture features with SVM to classify rice types into five categories: Ipsala, Jasmine, Karacadag, Arborio, and Basmati. Experimental results demonstrate that SVM using Canny, Sobel, and Prewitt combined Gabor texture features outperforms the comparative methods. A comparative analysis based on accuracy scores using confusion matrices is conducted. Combining all feature edge methods, Canny, Sobel, and Prewitt with Gabor on SVM classification is the best model for rice object classification, achieving an accuracy of 96%. © 2023 IEEE.

关键词： Support vector machines

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