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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

Computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN)

Maternal Health Risk Classification - A Comparison between A...

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2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology, ICSEIET 2023

作者： Fatmawati, Maylia Novita, Mega Saputro, Nugroho Dwi Chauhan, Alok Singh Nada, Noora Qotrun Sinha, Amit Herlambang, Bambang Agus Gupta, Shruti Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Informatics Semarang Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Semarang Indonesia School of Computing Science & Engineering Galgotias University Greater Noida India ABES Engineering College Department of Computer Science & Engineering Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

Maternal health is a critical concern, particularly for individuals who are pregnant and will shape the future generations. However, not all expectant mothers receive tailored attention and care for their unique health needs. Consequently, many mothers face high levels of health risks during pregnancy, highlighting the importance of classifying maternal health risks. Classification can help identify influential factors affecting maternal health and predict risk levels for individual mothers. In the field of data mining, various classification methods exist for analyzing complex datasets. This study focuses on two widely used algorithms: decision tree and k-Nearest Neighbor (kNN). By employing these algorithms, we aim to classify a dataset comprising 1,014 records of maternal health risk levels. Through cross-validation and T-tests, we rigorously evaluate the performance of the decision tree and kNN algorithms in this context. Our findings indicate that the kNN algorithm is more suitable for classifying maternal health risks, achieving a significantly higher accuracy of 71.50% compared to the decision tree algorithm's accuracy of 70.71%. This result establishes the superiority of the kNN algorithm in accurately classifying maternal health risks. These findings have implications for developing targeted interventions and tailored healthcare strategies to mitigate identified risks. © 2023 IEEE.

关键词： Health risks

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Developer-Centric Task Allocation: An Intelligent Approach for Enhanced Software Productivity

Developer-Centric Task Allocation: An Intelligent Approach f...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Evandro L. R. Fensterseifer Filho Joaquim V. C. Assunção Lisandra M. Fontoura Graduate Program in Computer Science Federal University of Santa Maria - UFSM Santa Maria – RS Brazil Applied Computing Department Federal University of Santa Maria - UFSM Santa Maria – RS Brazil

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Software projects are affected by technical knowledge as well as the personality of the team. Such factors can reduce or increase the software quality and development speed. For successful task allocation, it is essential to consider the skills and profile of each developer, thus maximizing their productivity. In projects with large teams, task allocation can be challenging, and the help of tools can facilitate its execution. In this work, we propose an intelligent approach for allocating software development tasks suitable to the profile of developers. From the literature, we define the appropriate skills and technical profiles for a development team, and the assessment is based on the developer completing a questionnaire. We developed a recommendation system to suggest tasks to be allocated to developers, employing text processing techniques. For validation, 495 tasks were used from an actual project developing simulator software for military training. The recommended allocations were evaluated by the project developers and used to improve the system. Validations showed that the developed approach makes consistent and coherent task recommendations to developers according to the developer profile, as participants agree with the recommendation for 76% of tasks.

关键词： Training Productivity Databases Mathematical models Classification algorithms Resource management Data mining Recommender systems Text processing Software development management

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review 10

Critical Factors of Immersive Learning in Higher Education: ...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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How a Global Elective Engineering class impacts Engineering Students' Global Efficacy

How a Global Elective Engineering class impacts Engineering ...

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2023 IEEE IFEES World Engineering Education Forum and Global Engineering Deans Council, WEEF-GEDC 2023

作者： Gurganus, Jamie R. Malschutzky, Michael M. Do Carmo Santos, Joao Carlos Zupan, Marc Dos Santos, Abel Dias Engineering & Computing Education Program & Graduate School Baltimore United States Centre for Teaching Development and Innovation Department of Management Sciences Hochschule Bonn-Rhein-Sieg Sankt Augustin Germany College of Engineering and Information Technology Department of Mechanical Engineering Baltimore United States Departamento de Engenharia Mecânica Porto Portugal

ISBN: (纸本)9798350316025

Today's pluralistic and globalized society requires a global perspective in how we think, view ourselves, and relate to others to collaborate successfully with people with different cultural backgrounds. To support the development of a global perspective, universities cultivate international co-operations to enable international mobility for students, faculty, and staff. However, in-person mobility can be inhibited due to various reasons. To support a wider pool of students gaining international experience, modern digital mediated course formats can be used to offer virtual instead of in-person mobility. This contribution evaluates a digital mediated course for mechanical engineering students (Global Engineering, GE) held in co-operation between an US and a Portuguese university, where internationally mixed student groups working on design projects in an Hyflex setting. Asides a literature driven discussion about the need for Global Engineers and a detailed description of the GE course, a longitudinal analysis was performed to assess the impact of the GE course on the students' development of a global perspective. The longitudinal analysis showed strong statistical support that the digitally mediated GE course improved the participating students' global perspective, assessed with the Global Perspective Inventory (GPI), tremendously. The observed improvements were in three of the six GPI dimensions comparable to an in-person semester abroad. Limitations of the study and future investigations are discussed. © 2023 IEEE.

关键词： Students

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Unassisted photoelectrochemical CO_(2)reduction by employingⅢ-Ⅴphotoelectrode with 15%solar-to-fuel efficiency

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Carbon Energy 2025年第3期7卷 1-10页

作者： Karthik Peramaiah Purushothaman Varadhan Vinoth Ramalingam Bilawal Khan Pradip Kumar Das Hao Huang Hui-Chun Fu Xiulin Yang Vincent Tung Kuo-Wei Huang Jr-Hau He Chemistry Program Center for Renewable Energy and Storage Technologies(CREST)and Division of Physical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia Institute of Sustainability for Chemicals Energyand Environment(ISCE2)Agency for ScienceTechnologyand Research(A*STAR)Singapore School of Computing Engineering and TechnologyRobert Gordon UniversityAberdeenUK Department of Materials Science and Engineering City University of Hong KongKowloonSARHong KongChina Guangxi Key Laboratory of Low Carbon Energy Materials School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilinChina Department of Chemical System and Engineering University of TokyoTokyoJapan

Solar-driven carbon dioxide reduction reaction(CO_(2)RR)provides an oppor tunity to produce value-added chemical feedstocks and ***,achieving efficient and stable photoelectrochemical(PEC)CO_(2)RR into selec tive products is challenging owing to the difficulties associated with the optical and the electrical configuration of PEC devices and electrocatalyst ***,we construct an efficient,concentrated sunlight-driven CO_(2)RR setup consisting of InGaP/GaAs/Ge triple-junction cell as a photoanode and oxide-derived Au(Ox-Au)as a cathode to perform the unassisted PEC CO_(2)*** one-sun illumination,a maximum operating current density of 11.5 mA cm^(-2) with an impressive Faradaic efficiency(FE)of~98%is achieved for carbon monoxide(CO)production,leading to a solar-to-fuel conversion efficiency of~15%.Under concentrated intensity of 10 sun,the photoanode records a maximum current density of~124 mAcm^(-2) and maintains~60%of FE for CO *** results demonstrate crucial advancements in usingⅢ-Ⅴbased photoanodes for concentrated PEC CO_(2)RR.

关键词： photoelectrochemical oxide derived Au concentrated sunlight selec tive products III V photoelectrode pec devices CO reduction solar fuel efficiency

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HeadSpace: Incorporating Action Failure and Character Beliefs into Narrative Planning 18

HeadSpace: Incorporating Action Failure and Character Belief...

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18th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2022

作者： Sanghrajka, Rushit Young, R. Michael Thorne, Brandon School of Computing University of Utah Salt Lake CityUT United States Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT United States Spectra Logic Salt Lake CityUT United States

ISBN: (纸本)1577358775

Previous work on story planning has lacked a knowledge representation for characters that attempt actions that fail because of the characters’ misconceptions about the world state. This work describes HEADSPACE, a state-space heuristic search planning system that generates stories that track and manipulate characters’ beliefs about the story world. The planner produces story plans with actions that are attempted but fail. We show an example story plan that contains failed-action content that cannot be generated by typical planning-based approaches to story creation, and we provide an analytical evaluation that characterizes our planner’s increased expressive range relative to other narrative planners addressing character belief and/or failed action execution. Copyright © 2022, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Knowledge representation

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Word reuse and combination support efficient communication of emerging concepts

arXiv

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arXiv 2024年

作者： Xu, Aotao Kemp, Charles Frermann, Lea Xu, Yang Department of Computer Science University of Toronto Canada School of Computing and Information Systems University of Melbourne Australia School of Psychological Sciences University of Melbourne Australia Cognitive Science Program University of Toronto Canada

A key function of the lexicon is to express novel concepts as they emerge over time through a process known as lexicalization. The most common lexicalization strategies are the reuse and combination of existing words, but they have typically been studied separately in the areas of word meaning extension and word formation. Here we offer an information-theoretic account of how both strategies are constrained by a fundamental tradeoff between competing communicative pressures: word reuse tends to preserve the average length of word forms at the cost of less precision, while word combination tends to produce more informative words at the expense of greater word length. We test our proposal against a large dataset of reuse items and compounds that appeared in English, French and Finnish over the past century. We find that these historically emerging items achieve higher levels of communicative efficiency than hypothetical ways of constructing the lexicon, and both literal reuse items and compounds tend to be more efficient than their non-literal counterparts. These results suggest that reuse and combination are both consistent with a unified account of lexicalization grounded in the theory of efficient communication. © 2024, CC BY-NC-ND.

关键词： Information theory

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RPGPref: A Planning Heuristic that Uses Playstyle Preferences to Model Player Action and Choice 18

RPGPref: A Planning Heuristic that Uses Playstyle Preference...

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18th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2022

作者： Lang, Eric W. Young, R. Michael School of Computing University of Utah 201 Presidents’ Circle Salt Lake CityUT84112 United States Entertainment Arts and Engineering Program University of Utah 201 Presidents’ Circle Salt Lake CityUT84112 United States

ISBN: (纸本)1577358775

Recent work extending planning algorithms that reason about action and change has been successful at supporting game design, player modeling, and story generation. Incorporating agent preferences over actions and propositions into a planning process allows for a more accurate prediction of what a human might do when solving a problem like playing through a game level. This paper presents the preference-based planning heuristic RPGPREF which uses relaxed plan graphs (RPGs) and preference sets to guide a planner toward a preference-conforming path to its goal. A human subjects evaluation confirms that RPGPREF successfully guides the planning process toward solution plans that recognizably match and differentiate player playstyles. Copyright © 2022, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Artificial intelligence

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ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analytics of Attack Patterns

ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analyt...

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Engineering & computing Technologies (ICECT), International Conference on

作者： Inbasat Fiza Fizza Khurshid Manahil Fatima Umara Noor Zahid Rashid Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul South Korea

ISBN: (数字)9798350349719

ISBN: (纸本)9798350349726

The ATT&CK MITRE framework serves as an expansive repository of adversary tactics, techniques, and procedures. Given the sheer volume of these intricate attack patterns, the conventional manual navigation method proves to be time-intensive and less efficient for security analysts. As a remedy, there arises a compelling necessity to present the rich content encapsulated within the ATT&CK MITRE repository through interactive visualizations. In this paper ATT&CKViz an interactive web-based cyber-attack patterns visualization tool is presented that aims to empower security analysts with the ability to effortlessly explore the repository from diverse angles, which facilitates deep insights into cyber threats. The aim is to understand cyber threat efficiently with a timely response. The empirical evaluations depict that effectiveness and user-friendliness of ATT&CKViz.

关键词： Computers Navigation Visual analytics Manuals Cyberattack

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