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Analysis of the motivations for ISO 9001:2015 adoption in the Brazilian business context

Quality Management Journal 2021年第2期28卷 76-85页

作者： Siltori, Patricia F. S. Rampasso, Izabela Simon Martins, Vitor W. B. Anholon, Rosley Silva, Dirceu Souza Pinto, Jefferson Leal Filho, Walter School of Mechanical Engineering University of Campinas Campinas Brazil PNPD/CAPES Program Doctoral Program in Sustainable Management Systems Federal Fluminense University Niterói Brazil Department of Production Engineering State University of Pará Belém Brazil Faculty of Education University of Campinas Campinas Brazil Federal Institute of São Paulo Bragança Paulista Brazil Faculty of Life Sciences Hamburg University of Applied Sciences Hamburg Germany

This study aims to analyze the reasons that motivate Brazilian companies to implement Quality Management Systems, according to ISO 9001:2015 requirements. Based on information collected in the literature, a questionnaire was developed and answered by professionals that work with the mentioned standard in their companies. An Exploratory Factor Analysis was conducted with the collected data to group the validated variables into two constructs that present the most part of information variance. These constructs were entitled “internal improvements related motives” and “market related motives”. The findings of this research confirm and complement previous studies performed in Brazil and in other countries. © 2021 American Society for Quality.

关键词： Adoption motives ISO 9001 motivation quality management

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Carbon nitride- and graphene-based materials for the photocatalytic degradation of emerging water pollutants

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Materials Advances 2024年第7期5卷 2668-2688页

作者： Indra Jaya Budiarso Valentinus Alphano Dabur Riska Rachmantyo Hermawan Judawisastra Chechia Hu Arie Wibowo Master Program in Materials Science and Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Ganesha 10 Bandung 40132 West Java Indonesia Doctoral Program in Materials Science and Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Ganesha 10 Bandung 40132 West Java Indonesia Materials Science and Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Ganesha 10 Bandung 40132 West Java Indonesia ariewibowo@itb.ac.id Department of Chemical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R&D Center for Membrane Technology Chung Yuan Christian University Taoyuan 320 Taiwan Research Center for Nanoscience and Nanotechnology Institut Teknolgi Bandung Ganesha 10 Bandung 40132 West Java Indonesia

Photocatalytic degradation is a promising way to treat emerging pollutants in wastewater. Recently, metal-free photocatalysts such as carbon nitride- and graphene-based materials have attracted much interest in the photocatalytic degradation of emerging water pollutants owing to their visible light activity and unique electrical properties, respectively. Graphitic carbon nitride (GCN) is considered a superior visible light–active photocatalyst because of its suitable bandgap (2.7 eV). Moreover, the facile synthesis process and the high chemical and thermal stability of GCN make it one of the research hotspots in photocatalytic wastewater treatment. Besides GCN, graphene and its derivatives are utilized to support main photocatalysts by enhancing their light absorption, pollutant adsorption, and photogenerated charge separation. Furthermore, the vast modification of these materials has promoted various outstanding performances in carbon nitride- and graphene-based photocatalysts in the application of pollutant degradation. In this review, we highlight recent developments in carbon nitride- and graphene-based photocatalysts (2018–2023), focusing on the strategies to improve the activity of GCN as a visible light–active photocatalyst and the role of graphene and its derivatives as supporting materials in wastewater pollutant remediation applications.

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Improving the PBL method with Experiential Learning Theory in Software engineering Teaching

Improving the PBL method with Experiential Learning Theory i...

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Software engineering Education for the Next Generation (SEENG), International Workshop on

作者： Cleuton Almeida Cé sar Franca Professional Doctoral Program in Software Engineering Cesar School Rio Branco Acre Brazil Cesar School / Universidade Federal Rural de Pernambuco Recife Pernambuco Brazil

Context: Problem-Based Learning (PBL) and Experiential Learning Theory (ELT) are convergent active learning approaches widely known for their competent integration between theory and practice. Problem/Objective: However, the usual implementation of PBL leaves out the final active experimentation stage of the experiential learning cycle. In this article, we intend to systematically investigate the impacts of this last stage on the learning outcomes of software engineering students. Methods: A quasi-experiment was designed and applied in three software engineering courses of an undergraduate course, in Rio Branco-Acre / Brazil. Results: students who participated in two of the three treatment groups scored significantly higher on measures of motivation, experience and learning, which means that the PBL method contains gaps that can be significantly improved with the help of ELT, benefiting the learning outcomes of software engineering students.

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Development of Urban Data Sensing for Smart City Platform

Development of Urban Data Sensing for Smart City Platform

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International Conference on ICT For Smart Society (ICISS)

作者： Okyza Maherdy Prabowo Suhono Harso Supangkat Eueung Mulyana STMIK AMIK Bandung Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Smart City and Community Innovation Center School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

The idea of a “smart city” is one in which cities may effectively and efficiently manage their resources to raise the standard of living of its residents. Cities are already capable of performing sensing, understanding, and acting at a certain degree because to the existence of information technology as an enabler. Several studies have created various physical sensors for sensing in order to produce data. However, urban data is not limited to factual information on the environment and infrastructure. In order to collect data from the digital world, including social media, online news, and other digital social sensors, this research aims to create an urban data collecting system. The creation of digital urban sensor data can enhance the accuracy of the information that can help decision-makers.

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Prediction of Consumer Purchase Intention on Green Product

Prediction of Consumer Purchase Intention on Green Product

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2021 International Seminar on Application for Technology of Information and Communication, iSemantic 2021

作者： Hariyadi, Guruh Taufan Purwanto Isnanto, R Rizal Wibowo, Adi Warsito, Budi Universitas Diponegoro Doctoral Program of Information Systems Semarang Indonesia Universitas Diponegoro Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Diponegoro Faculty of Engineerig Department of Computer Engineering Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Departement of Informatics Semarang Indonesia

ISBN: (纸本)9781665428040

Education to the public on green products has been widely carried out. Consumers who buy green products can be profiled by segmenting green consumers. In green marketing, consumer education on sustainable consumption is increasingly needed in recent years due to the problem of environmental pollution which poses a serious threat to the world population. Concern for the environment is an important topic in most countries, and individuals also study environmental issues. Individuals or groups of individuals who are 'ecologically aware' are also referred to as 'green consumers.' Such consumers are considered to have more concern for the environment. This study examined the predictions on the effect of the Green Perceived Value variables consisting of functional, conditional, and social values on the purchase intention of green consumers. It also tested the comparisons with other classification models. The models used in this research were Random Forest, Decision Tree, and Neural Network.. © 2021 IEEE.

关键词： Consumer behavior

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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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Asynchronous Data Communication Architecture on Real-Time Face Recognition for Hybrid Laboratory System

Asynchronous Data Communication Architecture on Real-Time Fa...

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

作者： Nina Lestari Trisna Purnama Slamet Risnanto Budi Fitriadi Ach Maulana Habibi Yusuf Ary Setijadi Prihatmanto Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Electrical Engineering Department Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Universitas Komputer Indonesia Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

The Internet of Things (IoT) and Artificial Intelligence (AI) have reshaped educational technology, increasing the chances of developing more effective and engaging learning environments. This study proposes an architecture for asynchronous data communication with real-time face recognition, a virtual and remote labs confluence. The architecture uses IoT hardware and software to comprise critical components such as IoT cameras, message brokers, FTP servers, and AI processing servers. The aim is to optimize resource usage and maximize response time efficiency. The architecture employs message queuing to manage high volumes of face image data, facilitating immediate verification and rapid access. Our findings demonstrate that the system can achieve face recognition with 91.7% accuracy and an average system communication latency of 2.631 seconds, effectively leveraging asynchronous communication to optimize resource usage and computational efficiency. The research comprehensively measures the data communication metrics and face recognition metrics. It also explains how asynchronous data communication can be strategically deployed in a hybrid lab environment to enhance educational and operational efficacy.

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Expert System Research for Prostate Cancer : A Literature Review

Expert System Research for Prostate Cancer : A Literature Re...

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Networking, Electrical engineering, Computer Science, and Technology (IConNECT), International Conference on

作者： Rusliyawati Rusliyawati Sutyarso Sutyarso Agus Wantoro Doctoral Program of Mathematics and Natural Science Faculty University of Lampung Bandar Lampung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandar Lampung Indonesia Faculty of Mathematics and Natural Sciences University of Lampung Bandar Lampung Indonesia

In the field of computer science, expert systems have attracted many computer scientists. In recent years, expert systems have been widely used in the medical field, particularly for diagnosing and treating various diseases, especially prostate cancer. Reality has shown that expert systems hold great promise for accurate diagnosis and treatment of prostate cancer. This research summarizes several studies related to the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores potential future research. Articles and reviews on the application of expert systems in prostate cancer from 2015 to 2022 were selected from the PubMed, Embase, and Web of Science databases. Microsoft Excel 2019 and GraphPad Prism 8 were used for target variable analysis. A total of 37 articles were selected for this research. Research on artificial intelligence in prostate cancer has grown exponentially in recent years, particularly in Indonesia. Image data usage is more predominant (62%) than numerical data types in prostate cancer research. Artificial intelligence research in prostate cancer, especially in the field of treatment cases, and the use of Deep Neural Network (DNN), Human Neural Network (HNN), Fully Convolutional Network (FCN), QT Environment for C++, Artificial Neural Network (ANN) algorithms, are highly feasible for further research.

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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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Relationship between extreme rainfall and design flood-discharge of the Ciliwung river 2

Relationship between extreme rainfall and design flood-disch...

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2nd International Conference on Disaster and Management 2020, ICDM 2020

作者： Farid, M. Saputra, D. Maitsa, T.R. Kesuma, T.N.A. Kuntoro, A.A. Chrysanti, A. Water Resources Engineering Research Group Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Bandung40135 Indonesia Civil Engineering Master Program Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Bandung40135 Indonesia Civil Engineering Doctoral Program Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Bandung40135 Indonesia Center for Coastal and Marine Development Institut Teknologi Bandung Bandung40135 Indonesia Center for Water Resources Development Institut Teknologi Bandung Bandung40135 Indonesia

Flood in Jakarta is occurred almost every year due to inadequate flood control systems to the flood prediction, inadequate drainage system, and trash that clog the drainage. The increase of rainfall is also one of the causes of flooding. That changing rainfall characteristics can affect river flow. This study aims to analyze the trend of rainfall in different time frames and its effect to flood discharge. The extreme rainfall trend is analyzed for every 15 years period from rainfall data of 1985 to 2019 for several return periods. Three period is selected for trend analysis and compared to the baseline data (1985-2019). Based on the analysis, the extreme rainfall for 1995-2009 and 2005-2019 period compared to the baseline is increased for all return periods. The increasing percentage is approximately 3-10% and 5-16% respectively. Since the extreme rainfall is increased, the design discharge is also increased for all return periods. The increasing percentage for 1995-2009 and 2005-2019 period compared to the baseline is 4-12% and 7-19% respectively. However, the design rainfall and discharge for the period 1985-1999 is lower than the baseline. © Published under licence by IOP Publishing Ltd.

关键词： Rain

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