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Editorial Engineering and technology Management: A Growing Field

IEEE Transactions on Engineering Management 2020年第3期67卷 514-515页

作者： Daim, Tugrul U Technology Management Doctoral Program Department of Engineering and Technology Management Maseeh College of Engineering and Computer Science Portland State University PortlandOR United States

As the world has struggled against a virus, technology enabled our survival in many dimensions. In many cases adoptions of technologies which would have lasted years happened in weeks if not days. For example, remote health care adoption was accelerated immensely to deal with the challenged health system. We are about to see similar technological innovations ramp up the hard hit economies through many different sectors. As always said, challenges create opportunities. Our field of Engineering and technology Management is growing. IEEE technology and Engineering Management Society (TEMS) just finished the first virtual conference: TEMSCON 2020. As a part of it we held an editors’ panel. Holding the conference on line enabled many editors of the leading journals in the field attend the event.

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COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

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computers, Materials & Continua 2021年第7期68卷 391-407页

作者： Aqib Ali Wali Khan Mashwani Samreen Naeem Muhammad Irfan Uddin Wiyada Kumam Poom Kumam Hussam Alrabaiah Farrukh Jamal Christophe Chesneau Department of Computer Science Concordia College BahawalpurBahawalpur63100Pakistan Department of Computer Science&IT Glim Institute of Modern StudiesBahawalpur63100Pakistan Institute of Numerical Sciences Kohat University of Science&TechnologyKohat26000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Program in Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiThanyaburi12110Thailand Departments of Mathematics Faculty of ScienceCenter of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research LaboratoryRoom SCL 802 Fixed Point LaboratoryScience Laboratory BuildingKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand Department of Medical Research China Medical University HospitalTaichung40402Taiwan College of Engineering Al Ain UniversityAl Ain64141United Arab Emirates Department of Mathematics Tafila Technical UniversityTafila66110Jordan Department of Statistics The Islamia University of BahawalpurBahawalpur63100Pakistan 11Department of MathematicsUniversitéde CaenLMNOCaen14032France

The purpose of this research is the segmentation of lungs computed tomography(CT)scan for the diagnosis of COVID-19 by using machine learning *** dataset contains data from patients who are prone to the *** contains three types of lungs CT images(Normal,Pneumonia,and COVID-19)collected from two different sources;the first one is the Radiology Department of Nishtar Hospital Multan and Civil Hospital Bahawalpur,Pakistan,and the second one is a publicly free available medical imaging database known as *** the preprocessing,a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest(ROIs)and acquire 52 hybrid statistical features for each ***,12 optimized statistical features are selected via the chi-square feature reduction *** the classification,five machine learning classifiers named as deep learning J4,multilayer perceptron,support vector machine,random forest,and naive Bayes are deployed to optimize the hybrid statistical features *** is observed that the deep learning J4 has promising results(sensitivity and specificity:0.987;accuracy:98.67%)among all the deployed *** a complementary study,a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

关键词： COVID-19 machine learning fuzzy c-mean deep learning J4

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Yanfi Yanfi Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy.

关键词： Support vector machines Sentiment analysis Analytical models Machine learning algorithms Food industry Companies Classification algorithms

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Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports

Dynamics of COVID-19 Misinformation: An Analysis of Conspira...

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17th International Conference on Social Computing and Social Media, SCSM 2025, held as part of the 27th HCI International Conference, HCII 2025

作者： Thakur, Nirmalya Shao, Mingchen Knieling, Victoria Su, Vanessa Bian, Andrew Jeong, Hongseok Department of Electrical Engineering and Computer Science South Dakota School of Mines and Technology Rapid CitySD57701 United States Department of Computer Science Emory University AtlantaGA30322 United States Program in Linguistics Emory University AtlantaGA30322 United States Goizueta Business School Emory University AtlantaGA30322 United States

ISBN: (纸本)9783031935350

This paper makes four scientific contributions to the area of misinformation detection and analysis on digital platforms, with a specific focus on investigating how conspiracy theories, fake remedies, and false reports emerge, propagate, and shape public perceptions in the context of COVID-19. A dataset of 5,614 posts on the internet that contained misinformation about COVID-19 was used for this study. These posts were published in 2020 on 427 online sources (such as social media platforms, news channels, and online blogs) from 193 countries and in 49 languages. First, this paper presents a structured, three-tier analytical framework that investigates how multiple motives - including fear, politics, and profit - can lead to a misleading claim. Second, it emphasizes the importance of narrative structures, systematically identifying and quantifying the thematic elements that drive conspiracy theories, fake remedies, and false reports. Third, it presents a comprehensive analysis of different sources of misinformation, highlighting the varied roles played by individuals, state-based organizations, media outlets, and other sources. Finally, it discusses multiple potential implications of these findings for public policy and health communication, illustrating how insights gained from motive, narrative, and source analyses can guide more targeted interventions in the context of misinformation detection on digital platforms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Data mining

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Strategic Information System Planning in the Industry 4.0 Era: A Systematic Literature Review

Strategic Information System Planning in the Industry 4.0 Er...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Irfan Mahendra Arief Ramadhan Agung Trisetyarso Edi Abdurachman Muhammad Zarlis Computer Science Program Bina Nusantara University Jakarta Indonesia Information Technology Faculty Nusa Mandiri University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia

Information systems and technology have an important role in building the Company's competitive advantage in facing the Industrial Era 4.0. Strategic Information System Planning (SISP) helps companies formulate reliable information systems that are aligned with business strategies. The academic world should contribute in this regard, but currently, the amount of research related to SISP is very limited. This research is a systematic literature review, which aims to find out more about SISP research trends, research motivations and backgrounds, industries that have been handled, and the methods used in developing SISP. This research is expected to be a trigger for the emergence of new research to support the successful development of SISP in companies in various industries. The results of this research show that several topics are widely researched and need to be improved in the future, namely the alignment of IS strategies with business strategies, the development of specific SISPs in various industries, and the reliability of IS strategies by considering the application of the latest information technology, such as blockchain, artificial intelligence, big data, augmented reality, Internet of Things, and cloud computing. In addition, it is also necessary to develop a SISP framework that is more accommodating to changes in the business environment that is increasingly fast, agile, and collaborative, which includes aspects of business architecture, data/information architecture, technology architecture, information system security, governance, and human resources.

关键词： Industries Systematics Bibliographies computer architecture Market research Reliability Security

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Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports

arXiv

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arXiv 2025年

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Fully rubbery synaptic transistors made out of all-organic materials for elastic neurological electronic skin

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Nano Research 2022年第2期15卷 758-764页

作者： Hyunseok Shim Seonmin Jang Jae Gyu Jang Zhoulyu Rao Jong-ln Hong Kyoseung Sim Cunjiang Yu Materials Science and Engineering Program University of HoustonHoustonTX 77204 USA Department of Chemistry Seoul National UniversitySeoul 08826Republic of Korea Department of Chemistry Ulsan National Institute of Science and Technology(UNIST)Ulsan 44919Republic of Korea Department of Mechanical Engineering University of HoustonHoustonTX 77204 USA Department of Biomedical Engineering University of HoustonHoustonTX 77204USA Department of Electrical and Computer Engineering University of HoustonHoustonTX 77204 USA Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Neurologic function implemented soft organic electronic skin holds promise for wide range of applications,such as skin prosthetics,neurorobot,bioelectronics,human-robotic interaction(HRI),***,we report the development of a fully rubbery synaptic transistor which consists of all-organic materials,which shows unique synaptic characteristics existing in biological *** synaptic characteristics retained even under mechanical stretch by 30%.We further developed a neurological electronic skin in a fully rubbery format based on two mechanoreceptors(for synaptic potentiation or depression)of pressure-sensitive rubber and an all-organic synaptic *** converting tactile signals into Morse Code,potentiation and depression of excitatory postsynaptic current(EPSC)signals allow the neurological electronic skin on a human forearm to communicate with a robotic *** collective studies on the materials,devices,and their characteristics revealed the fundamental aspects and applicability of the all-organic synaptic transistor and the neurological electronic skin.

关键词： synaptic transistor stretchable electronic skin all-organic

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Drone Application Model for Image Acquisition of Plantation Areas and Oil Palm Trees Counting 7

Drone Application Model for Image Acquisition of Plantation ...

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7th International Conference on Information Management and technology, ICIMTech 2022

作者： Sastrohartono, Hermantoro Suryotomo, Andiko Putro Saifullah, Shoffan Suparyanto, Teddy Perbangsa, Anzaludin Samsinga Pardamean, Bens Instiper Yogyakarta Faculty of Agricultural Technology Department of Agricultural Engineering Yogyakarta55281 Indonesia Universitas Pembangunan Nasional Veteran Yogyakarta Department of Informatics Yogyakarta55283 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustainable productivity. The high-performance computing technologies, Internet of Things (IoT), Big Data, Artificial Intelligence, spatial modeling, and drones are the answers to these needs. This study aims to design an application that can obtain plantation image data and analyze the calculation of the number of oil palm trees. The image of oil palm plantations is obtained from processing photo data from drones through a mosaic and composite process. This study also employed Scrum and UML as a system model development method. The image of the oil palm plantation area is used to build a tree counting model using the Viola-Jones algorithm. The oil palm tree count information generated by this system can then be used by management for fertilizing, harvesting, and monitoring the condition of oil palm trees. © 2022 IEEE.

关键词： Drones

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Protein codes promote selective subcellular compartmentalization

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science (New York, N.Y.) 2025年第6738期387卷 1095-1101页

作者： Kilgore, Henry R. Chinn, Itamar Mikhael, Peter G. Mitnikov, Ilan Van Dongen, Catherine Zylberberg, Guy Afeyan, Lena Banani, Salman F. Wilson-Hawken, Susana Lee, Tong Ihn Barzilay, Regina Young, Richard A. Whitehead Institute for Biomedical Research Cambridge MA United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology (MIT) Cambridge MA United States Abdul Latif Jameel Clinic for Machine Learning in Health MIT Cambridge MA United States Department of Biology MIT Cambridge MA United States Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA United States Computational and Systems Biology Program MIT Cambridge MA United States

Cells have evolved mechanisms to distribute ~10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must assemble. In this study, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. We developed a protein language model, ProtGPS, that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in the nucleolus. ProtGPS identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code but also a previously unrecognized code governing their distribution to diverse subcellular compartments.

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Analysis of Shoping Intention Using E-Commerce during Pandemic 8

Analysis of Shoping Intention Using E-Commerce during Pandem...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Oktavia, Tanty Gaol, Ford Lumban Hosoda, Takaaki Wijaya, Alessandro Bryan Tio, Fendy Malaysiani, Liza Azzahra Sanjaya, Sandi Martin, Yessin Rio Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665416979

This study aims to investigate people's shopping intentions using e-commerce during the pandemic in Indonesia. The method used in this research is the quantitative method in which the results of the study are used as an assumption and research discussion. Data collection was carried out by questionnaires then measure using t-test. The result can be concluded that the intention to shop using e-commerce during the COVID-19 pandemic is influenced using e-commerce features and e-commerce techniques. These results indicate that the intention to shop using e-commerce can increase if the availability of goods in e-commerce is quite complete, the quality of goods sold is very high, normal prices and technical requirement, such as speed, security, and a good e-commerce design system. © 2021 IEEE.

关键词： COVID-19

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