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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Chaves, Ramon Motta, Claudia Correia, Antonio Paredes, Hugo Caetano, Barbara De Souza, Jano Moreira Schneider, Daniel Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Federal University of Rio de Janeiro Brazil Inesc Tec University of Tr s-os-Montes e Alto Douro Utad Quinta de Prados Apartado 1013 Vila Real Portugal Systems Engineering and Computer Science Program PESC/COPPE/UFRJ Rio de Janeiro Brazil

ISBN: (纸本)9781665405270

In recent years, digital technologies have been used to support discussions about the city and also to involve citizens in participatory public processes. However, despite the widespread use of social media platforms, old issues related to engagement and participation still persist in digital initiatives. The main goal of this study is to carry out an empirical evaluation of a collective intelligence model that combines crowdsourcing and social storytelling to support discussions about the city from a bottom-up perspective. Within a design science research approach we designed a participatory action study that was carried out through a workshop with students and professionals from different areas, such as architecture, urban design and information technology. As a result, we were able to assess whether the collective intelligence model was acceptable to the participants by investigating whether the behavioral assumptions were valid and thus outlining some contributions to the field of urban informatics. © 2022 IEEE.

关键词： Crowdsourcing

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A Study on Medicinal Plant Leaf Recognition Using Artificial Intelligence 3

A Study on Medicinal Plant Leaf Recognition Using Artificial...

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3rd International Conference on informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021

作者： Ayumi, Vina Ermatita, Ermatita Abdiansah, Abdiansah Noprisson, Handrie Purba, Mariana Utami, Marissa Universitas Sriwijaya Doctoral Program in Engineering Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang Indonesia Universitas Mercu Buana Faculty of Computer Science Jakarta Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Muhammadiyah University of Bengkulu Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665427333

Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce these resources, some researchers propose to implement artificial intelligence technology. This paper aims are to conduct a systematic literature review of medicinal plant leaf recognition published in the last two years (2019-2020) from IEEE, Springer and Science Direct. We obtained 15 studies in the field of medicinal plant leaf recognition using artificial intelligence. The dataset used for medicinal plant leaf recognition is mostly used private dataset, however, there are public dataset named Leaf, Flavia, Swedish dataset. We also found robust method that can be used for medicinal plant leaf recognition is Multichannel Modified Local Gradient Pattern (MCMLGP) and Gray Level Co-Occurrence Matrix (GLCM) as feature extraction;and Convolutional Neural Network (CNN), Multi-Layer Perceptron trained with Backpropagation algorithm (MLP-BP), Support Vector Machine (SVM), and Transfer Learning (VGG19) as classifier. © 2021 IEEE.

关键词： Image processing

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Contrast Enhancement and Exposure Correction Using a Structure Aware Distribution Fitting

SSRN

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SSRN 2023年

作者： Barbosa, Matheus Rocha Scharcanski, Jacob Electrical Engineering Graduate Program Federal University of Rio Grande do Sul Porto Alegre Brazil Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Brazil

This paper proposes a method for contrast enhancement and exposure correction in images. The method fits regionally to the image a parametric model of probability distribution, respecting the image structure and edges between regions. This is done using regional versions of the classical expressions for estimating the parameters of the distribution, obtained by replacing the sample mean present in the original expressions by an edge preserving smoothing filter. After the fitting, the cumulative distribution function (CDF) of the adjusted model and the inverse of the CDF of the desired distribution are applied. A structure aware heuristic that detects smooth regions is proposed and used to attenuate the transformations in flat regions. The method was named Structure Aware Distribution Stretch (SADS). SADS was compared with other methods from the literature using objective no-reference and full-reference image quality assessment (IQA) metrics in the tasks of simultaneous contrast enhancement and exposure correction and in the task of defogging/dehazing. The experiments indicated a superior overall performance of SADS with respect to the compared methods for the image sets used, according to the IQA metrics adopted. © 2023, The Authors. All rights reserved.

关键词： Distribution functions

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Digital Nomads during the COVID-19 Pandemic: Evidence from Narratives on Reddit discussions 25

Digital Nomads during the COVID-19 Pandemic: Evidence from N...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： De Almeida, Marcos Antonio Correia, Antonio De Souza, Jano Moreira Schneider, Daniel Systems Engineering and Computer Science Program PESC/COPPE/UFRJ Rio de Janeiro Brazil Inesc Tec University of Trás-os-Montes e Alto Douro Vila Real Portugal Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

ISBN: (纸本)9781665405270

In this paper, we report on new findings about the results of an empirical study which aims to investigate how the COVID-19 pandemic has been shaping nomadic work practices and also challenging the lifestyles of digital nomads (DN). To do this, we collected textual data from posts in a Reddit community. We argue that, in order to understand how to design technical solutions for the so-called 'new normal' working conditions, one way to approach this is to understand how digital nomads are being impacted in their work practices and routines, and also how they are seeing the future of their technology-mediated work-life space. Finally, we show how evidence collected from DNs about their experiences and difficulties perceived during the pandemic period can inform CSCW researchers worldwide about future design-oriented strands. © 2022 IEEE.

关键词： COVID-19

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Drought propagation in an Andean basin in South America: a spatio-temporal analysis approach with monitoring indices

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Arabian Journal of Geosciences 2025年第3期18卷 1-21页

作者： Ocampo-Marulanda, Camilo Mera-Franco, Julián David Lizcano, Víctor Augusto Carvajal-Escobar, Yesid Canchala, Teresita Zorrilla-Millan, Daniel Felipe Caicedo-Bravo, Eduardo Water Resources Engineering and Soil Research Group (IREHISA) School of Natural Resources and Environmental Engineering Universidad del Valle Cali Colombia Graduate Program in Biometrics and Applied Statistics Department of Statistics and Informatics Federal Rural University of Pernambuco Recife Brazil School of Exact Sciences and Engineering Universidad Sergio Arboleda Bogotá Colombia Programa de Ingeniería Ambiental Facultad de Ingeniería Universidad Mariana Pasto Colombia School of Electrical and Electronic Engineering Universidad del Valle Cali Colombia

Drought is a climatic phenomenon that has increased in severity over time. This study analyzed drought spread in the Alto Patía basin (13,047 km2) in South America, applying the Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), and Streamflow Drought Index (SDI) to assess meteorological, agricultural, and hydrological drought, respectively. Synchronous and asynchronous correlations were estimated, and Wavelet analysis was conducted to verify relationships among drought types. Results show that the lag between drought types varies based on the intensity, temporal continuity, and spatial extent of meteorological drought. A lag of zero months (1–2 months) was observed between meteorological and hydrological drought when moderate (severe) meteorological drought partially (fully) covers the basin. Agricultural drought, however, does not always correspond to meteorological drought during isolated rainfall events. As the first study in Colombia to systematically connect these drought types, this research addresses a gap in understanding how drought impacts progress across systems in regions with complex rainfall patterns. These findings offer critical insights into the interdependencies among drought types, supporting enhanced drought monitoring and early warning systems in similar climatic regions. By identifying specific lags between meteorological and hydrological droughts, this study provides practical guidance for land management, water conservation, and crop planning, offering a foundation for future research on drought resilience strategies.

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Identifying New Persons in the Context of the Robocup@Home Competition Using KNN

Identifying New Persons in the Context of the Robocup@Home C...

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IEEE Latin American Robotics Symposium, LARS

作者： David Segalle Gustavo Fardo Armênio Gustavo Fontes Lewin Everson De Souza Silva João Alberto Fabro Computer Engineering Course UTFPR-Federal University of Technology - Paraná Curitiba PR Brazil Computer Engineering Course - UTFPR Curitiba PR Brazil Eletronic Engineering Course - UTFPR Curitiba PR Brazil PPGCA-Graduate Program on Applied Informatics-UTFPR Curitiba PR Brazil

Robocup@Home proposes a challenge related to Person Recognition: after presented, a new ‘operator’ should become ‘immediately’ recognizable by the robot. The presentation procedure may require the operator to correctly interact with the robot, following a certain procedure, as instructed by the robot itself (for example, staying in front of the robot, so that the robot can take pictures of this person). In this paper, we propose the use of the KNN (K-Nearest Neighbor) supervised machine learning algorithm to include a new ‘operator’ in a database of persons recognizable by the robot. This algorithm uses information taken from an image segmentation of the face of the operator. The experiment evaluates how long it takes to include a new operator if the robot has from 1 to 12 current operators, evaluating also how long it takes to include this operator based on 1, 2 or more images of the new operator, taken from slightly different points of view. The results confirm that KNN can be used to ‘present to the robot’ up to 13 new operators, with up to 15 images for each operator, in less than 60 seconds.

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Observing Generator Performance by Finite Element Analysis Considering Coil Numbers

Observing Generator Performance by Finite Element Analysis C...

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Technology and Policy in Energy and Electric Power (ICT-PEP), International Conference on

作者： Muhammad Afnan Habibi Mochamad Farhan Ali Irfani Langlang Gumilar Arya Kusumawardana Aripriharta Angger Baskoro Study Program of Power Plant Engineering Technology Universitas Negeri Malang Malang Indonesia Department of Electrical Engineering and Informatics Universitas Negeri Malang Malang Indonesia Dept. Electrical Engineering and Computer Sciences National Yang Ming Chiao Tung University Hsinchu Taiwan

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies.

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Improvement of E-Nose Sensor Signal Using MVA, FFT, DWT Methods on Pineapple Fruit Maturity

Improvement of E-Nose Sensor Signal Using MVA, FFT, DWT Meth...

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International Conference on Information Technology, Information Systems and Electrical engineering (ICITISEE)

作者： Mhd Arief Hasan Riyanarto Sarno M. Syauqi Hanif Ardani Informatics Department Intitut Teknologi Sepuluh Nopember Surabaya Indonesia Informatic Engineering Study Program Universitas Lancang Kuning Pekanbaru Indonesia

In this study, we built an Electronic Nose to detect pineapple ripeness. We designed a prototype E-Nose using a wooden crate. Inside the box, we built the E-Nose using 9 MQ sensor circuits connected to the Arduino Microcontroller. In the crate, we put an object, namely a pineapple with three levels of ripeness (ripe, half ripe, and unripe), each weighing 1kg placed in three different positions (5cm, 20cm, and 35cm) from the position of the sensor array (E-nose). We converted the signal output results into ppm units. We compared the value of each fruit signal based on the level of ripeness and distance using E-Nose. We used several signal processing methods (wavelets) for signal processing. Then, we improved the signal generated using wavelet. The wavelet methods used are Moving Average, Fast Fourier Transform (FFT), and Discrete Wavelet Transform (DWT). The contribution of this research is to see the influence of the signal valuegenerated from the sensor (MQ Sensor) to the position (distance) of the object (fruit) and its influence on the level of maturity (fruit). Then signalgenerated from the sensor we make improvements with the mva, fft, and dwt methods.

关键词： Electrical engineering Microcontrollers Fast Fourier transforms Array signal processing Prototypes Electronic noses Discrete wavelet transforms

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Forecasting system using single exponential smoothing with golden section optimization 2

Forecasting system using single exponential smoothing with g...

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2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Widitriani, N.P.S. Parwita, W.G.S. Meinarni, N.P.S. Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali80225 Indonesia

Puri Wira Mahkota Ltd is a distributor company in the automotive parts industry. Puri Wira Mahkota has an obstacles in preparing weekly order on stock to the primary production unit. They predict total sales of product in the coming period just by using an expectation from stock administration staff then it will be compared with sales data in the previous period without any calculations using a definitive formula. Forecasting calculation could support Puri Wira Mahkota to predict the quantity of product. The purpose of this research is to apply the calculation process that can predict the quantity of product should be produced by the primary production unit every month and also to prevent over stock and out of stock. The method used in the forecasting calculation is Single Exponential Smoothing. To optimize Single Exponential Smoothing we used the Golden Section. The principle of the Golden Section is to reduce the alpha area boundary so it will produce an ideal forecast value with the minimum MAPE (Mean Absolute Percentage Error) level. This research shows the results that the Golden Section finds the optimal forecasting value with a level of MAPE (Mean Absolute Percentage Error) of 43.39%. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Sales

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On the Dominant Local Metric Dimension of Corona Product Graphs

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IAENG International Journal of Applied Mathematics 2022年第4期52卷 1页

作者： Umilasari, Reni Susilowati, Liliek Slamin Prabhu, Savari Mathematics Department Airlangga University Indonesia Study Program of Informatics Jember University Indonesia Mathematics Department Rajalakshmi Engineering College Tamil Nadu Chennai602105 India

A nontrivial connected graph T which one of the vertex is v, v is said to distinguish two vertex u;t if the distance between v and u is different from v to t, where u,t (Formula Presented) V (T). Metric dimension is one topic in graph theory that uses the concept of distance. Combining the definition of the local metric dimension and dominating set, there is a new term, we called it dominant local metric dimension and symbolized as Ddiml(T). An ordered subset Wl = {w1,w2,…,wn}(Formula Presented)V (T) is called a dominant local resolving set of T if Wl is a local resolving set as well as a dominating set of T. The goal of this paper’s research is to determine precise values of dominant local metric dimension for the corona product graphs. n copies of the graphs P1,P2,…,Pn of P are made to constructed the corona of any two graph T and P. After that, we link the i-th vertex of T to the vertices of Pi, where n is an order of graph T. T corona P is symbolized by T(Formula Presented)P. © 2022,IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Graph theory

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