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Artificial Intelligence Based Solar Radiation Predictive Model Using Weather Forecasts

computers, Materials & Continua 2022年第4期71卷 109-124页

作者： Sathish Babu Pandu A.Sagai Francis Britto Pudi Sekhar P.Vijayarajan Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Mesfer Al Duhayyim Department of Electrical and Electronics Engineering University College of EngineeringPanruti607106India Department of Mechanical Engineering Rohini College of Engineering&TechnologyPalkulam629401India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyAndra Pradesh530046India Department of Electrical and Electronics Engineering University College of EngineeringBIT CampusTiruchirappalli620024India Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Solar energy has gained attention in the past two decades,since it is an effective renewable energy source that causes no harm to the *** Irradiation Prediction(SIP)is essential to plan,schedule,and manage photovoltaic power plants and grid-based power generation *** models have been proposed for SIP in the literature while such studies demand huge volumes of weather data about the target location for a lengthy period of *** this scenario,commonly available Artificial Intelligence(AI)technique can be trained over past values of irradiance as well as weatherrelated parameters such as temperature,humidity,wind speed,pressure,and ***,in current study,the authors aimed at developing a solar irradiance prediction model by integrating big data analytics with AI models(BDAAI-SIP)using weather forecasting *** order to perform long-term collection of weather data,Hadoop MapReduce tool is *** proposed solar irradiance prediction model operates on different ***,data preprocessing take place using various sub processes such as data conversion,missing value replacement,and data ***,Elman Neural Network(ENN),a type of feedforward neural network is also applied for predictive *** is divided into input layer,hidden layer,loadbearing layer,and output *** overcome the insufficiency of ENN in choosing the value of weights and hidden layer neuron count,Mayfly Optimization(MFO)algorithm is *** order to validate the performance of the proposed model,a series of experiments was *** experimental values infer that the proposed model outperformed other methods used for comparison.

关键词： Solar irradiation prediction weather forecast artificial intelligence Elman neural network mayfly optimization

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A Qest to Engage computer Science Students: Using Dungeons and Dragons for Developing Sof Skills 10

A Qest to Engage Computer Science Students: Using Dungeons a...

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10th computer Science Education Research Conference, CSERC 2021

作者： Veldthuis, Marcella Koning, Mathijs Stikkolorum, Dave Leiden Institute Of Advanced Computer Science Leiden University Netherlands The Hague University Of Applied Sciences Netherlands

ISBN: (纸本)9781450385763

For several years the learning of soft skills has been underappreciated in computer science education. At the same time industry articulates the growing need for well skilled professionals that are technically equipped on one hand and good communicators and collaborators on the other hand. World wide, educational institutions adopted the suggestions from 21st century skills advise reports and started to include soft skills related topics in their curricula. This paper explains our didactic approach for engaging students into active learning for developing soft skills and to make them aware of the importance of this topic in relation to their professional future. The track 'Storytelling' in our Game Development and Simulation program is perfectly suited for applying a didactic approach in which soft skills are naturally integrated in lectures and examination. We so do by utilising the tabletop role-playing game Dungeons & Dragons. The game involves grouping students together to solve several story-driven challenges. The students have to collaborate and apply their creativity to solve these presented problems and overcome obstacles. Based on surveys from two academic semesters, we conclude that using the tabletop role-playing game Dungeons & Dragons as a didactic instrument contributes to the development of students' soft skills by offering them an engaging way of learning. © 2021 Owner/Author.

关键词： Students

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A Review of Algorithms's Complexities on Different Valued Sorted and Unsorted Data

A Review of Algorithms's Complexities on Different Valued So...

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2023 International Conference on IT and Industrial Technologies, ICIT 2023

作者： Shabbir, Attia Majeed, Asad Iftikhar, Mahnoor Ali, Raja Hashim Arshad, Usama Shabbir, Muhammad Zeeshan Zeeshan Ijaz, Ali Ali, Nisar Aftab, Ali Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Sorting and searching are critical processes for effecttive data analysis. In this paper, we evaluate the performance of various sorting and searching algorithms and compare their time and space complexities on both sorted and unsorted data. The algorithms we analyzed include six common sorting algorithms (insertion, radix, bucket, merge, bubble, and quick sort) and three search algorithms (linear, binary, and jump search). The results of our study provide insights into the best algorithms to use for different input sizes and types of data. It was found that for small input sizes, all algorithms perform similarly, but for larger input sizes, insertion and radix sorts are better for time complexity while bubble sort is better for space complexity. Additionally, jump search outperformed linear and binary search algorithms in both time and space complexity. Besides, difference between time and space complexity of sorted and unsorted data was significant. © 2023 IEEE.

关键词： Computational complexity

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Intrusion Detection Systems Based on Machine Learning Approaches: A Systematic Review

Intrusion Detection Systems Based on Machine Learning Approa...

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2023 International Conference on Science, Engineering and Business for Sustainable Development Goals, SEB-SDG 2023

作者： Ogundokun, Roseline Oluwaseun Basil, Ugochukwu Babatunde, Akinbowale Nathaniel Abdulahi, Abdul Rahman Tosho Adenike, Ajiboye Raimot Adebiyi, Ayodele Ariyo Kaunas University of Technology Department of Multimedia Engineering Lithuania Landmark University Sdg 11. Sustainable Cities and Communities Omu Aran Nigeria Landmark University Department of Computer Science Omu Aran Nigeria Kwara State University Department of Computer Science Malete Nigeria Institute of Information and Communication Technology Department of Computer Science Kwara State Polytechnic Nigeria Institute of Applied Sciences Department of Statistics Kwara State Polytechnic Nigeria Landmark University Omu-Aran Department of Computer Science Omu Aran Nigeria Landmark University Omu Aran Sdg 3. Good Health and Wellbeing Nigeria

ISBN: (纸本)9798350324785

The proliferation of Internet use poses certain security problems for networks. Intrusion detection (ID) in cybersecurity technology is to recognize unexpected entry to or assaults on secured networked computers. In the research, many machine learning (ML) and deep learning (DL) algorithms have been used to tackle intrusion detection systems (IDS). Nevertheless, few publications examine and explain the present state of employing ML approaches to tackle ID issues. This systematic review (SR) analyzes 11 papers published between 2016 and 2021 that focused on developing single, hybrid, and ensemble classifiers. Similar research is evaluated based on their classifier designs, the datasets they used, and their conceptual frameworks. Recent accomplishments and limits in developing IDS systems using ML are presented and analyzed. In addition, many prospective study possibilities are offered. © 2023 IEEE.

关键词： Intrusion detection

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Artificial Intelligence Adoption for Cybersecurity in Africa

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Journal of Information Security 2024年第2期15卷 134-147页

作者： Nadine Nibigira Vincent Havyarimana Zhu Xiao School of Engineering Sciences University of Burundi Doctoral School Bujumbura Burundi Department of Applied Sciences Burundi Higher Institute of Education (ENS) Bujumbura Burundi College of Computer Science and Electronic Engineering Hunan University Yongzhou Hunan

Legacy-based threat detection systems have not been able to keep up with the exponential growth in scope, frequency, and effect of cybersecurity threats. Artificial intelligence is being used as a result to help with the issue. This paper’s primary goal is to examine how African nations are utilizing artificial intelligence to defend their infrastructure against cyberattacks. Artificial intelligence (AI) systems will make decisions that impact Africa’s future. The lack of technical expertise, the labor pool, financial resources, data limitations, uncertainty, lack of structured data, absence of government policies, ethics, user attitudes, insufficient investment in research and development, and the requirement for more adaptable and dynamic regulatory systems all pose obstacles to the adoption of AI technologies in Africa. The paper discusses how African countries are adopting artificial intelligence solutions for cybersecurity. And it shows the impact of AI to identify shadow data, monitor for abnormalities in data access and alert cyber security professionals about potential threats by anyone accessing the data or sensitive information saving valuable time in detecting and remediating issues in real-time. The study finds that 69.16% of African companies are implementing information security strategies and of these, 45% said they use technologies based on AI algorithms. This study finds that a large number of African businesses use tools that can track and analyze user behaviour in designated areas and spot anomalies, such as new users, strange IP addresses and login activity, changes to permissions on files, folders, and other resources, and the copying or erasure of massive amounts of data. Thus, we discover that just 18.18% of the target has no national cybersecurity strategy or policy. The study proposes using big data security analytics to integrate AI. Adopting it would be beneficial for all African nations, as it provides a range of cyberattack defense techn

关键词： Artificial Intelligence (AI) Cybersecurity Cyberattacks Cybercriminals

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Leveraging Multimodal Ensemble Fusion-Based Deep Learning for COVID-19 on Chest Radiographs

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computer Systems Science & Engineering 2023年第10期47卷 873-889页

作者： Mohamed Yacin Sikkandar K.Hemalatha M.Subashree S.Srinivasan Seifedine Kadry Jungeun Kim Keejun Han Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Biomedical Engineering Bannari Amman Institute of TechnologySathyamangalam638401India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Institute of Biomedical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea Division of Computer Engineering Hansung UniversitySeoul02876Korea

Recently,COVID-19 has posed a challenging threat to researchers,scientists,healthcare professionals,and administrations over the globe,from its diagnosis to its *** researchers are making persistent efforts to derive probable solutions formanaging the pandemic in their *** of the widespread and effective ways to detect COVID-19 is to utilize radiological images comprising X-rays and computed tomography(CT)*** the same time,the recent advances in machine learning(ML)and deep learning(DL)models show promising results in medical ***,the convolutional neural network(CNN)model can be applied to identifying abnormalities on chest *** the epidemic of COVID-19,much research is led on processing the data compared with DL techniques,particularly *** study develops an improved fruit fly optimization with a deep learning-enabled fusion(IFFO-DLEF)model for COVID-19 detection and *** major intention of the IFFO-DLEF model is to investigate the presence or absence of *** do so,the presented IFFODLEF model applies image pre-processing at the initial *** addition,the ensemble of three DL models such as DenseNet169,EfficientNet,and ResNet50,are used for feature ***,the IFFO algorithm with a multilayer perceptron(MLP)classification model is utilized to identify and classify *** parameter optimization of the MLP approach utilizing the IFFO technique helps in accomplishing enhanced classification *** experimental result analysis of the IFFO-DLEF model carried out on the CXR image database portrayed the better performance of the presented IFFO-DLEF model over recent approaches.

关键词： COVID-19 computer vision deep learning image classification fusion model

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Synchronizing innovation: unveiling the synergy of need-based and curiosity-based experimentation in AI technology adoption for libraries

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Library Hi Tech News 2023年第9期40卷 15-17页

作者： Gupta, Varun Gupta, Chetna Multidisciplinary Research Centre for Innovations in SMEs (MrciS) Gisma University of Applied Sciences GmbH Potsdam Germany Department of Computer Science Engineering Jaypee Institute of Information Technology Noida India Department of Economics and Business Administration University of Alcala Alcalá de Henares Spain

Purpose: In the context of libraries adopting artificial intelligence (AI) technology, this paper aims to demonstrate the synergy between two different yet complimentary frameworks, need-based experimentation (NBE) and curiosity-based experimentation (CBE). It looks at how these frameworks interact and operate together to promote technological innovation and innovation in libraries. Design/methodology/approach: The authors’ extensive professional experience in the AI adoption and innovation of libraries is drew upon in this paper. The methodology encompasses empirical observations of various libraries engaging in digital innovations through experimentations with AI technology adoption practices. Using the frameworks of NBE and CB), these observations are examined to find patterns, relationships and mutual reinforcement between the two methods. The analysis of this study is built on the authors’ observations and real-world case studies. Findings: The research reveals that NBE and CBE work together to provide libraries with all-encompassing adoption methods for AI technology. This study indicates a dynamic interaction between NBE and CBE that boosts libraries’ methods for adopting AI technology. NBE acts as a catalyst for CBE by raising awareness of specific library needs, prompting librarians to explore AI technologies aligned with those needs. This synergy empowers librarians to creatively experiment with technology solutions that directly address pressing library challenges. Conversely, CBE fuels NBE by promoting group learning among diverse team members and fostering individual motivation to tackle library needs collaboratively. As they explore AI technology out of personal curiosity, librarians make important contributions that enhance NBE. Originality/value: The novel aspect of this study is the recognition of the complementarity between NBE and CBE frameworks, which suggests that libraries should view them as intertwined rather than two separate approaches. Foc

关键词： Artificial intelligence Curiosity-based experimentation (CBE) framework Experimentations Libraries Need-based experimentation (NBE) framework Technology adoption

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Predicting Survival HIV/AIDS Patients Using Machine Learning Methods: Artificial Neural Network and Decision Tree Models

Predicting Survival HIV/AIDS Patients Using Machine Learning...

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2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Ndabarushimana, Ladislas Ngom, Papa Ndekou Tandong, Paul Python Diongue, Abdou Ka Banzubaze, Emmanuel University Cheikh Anta Diop of Dakar Department of Mathematics and Computer Science Dakar Senegal University Gaston Berger of Saint Louis Department of Applied Mathematics Saint Louis Senegal National Institute of Public Health Department of Paraclinical Sciences Bujumbura Burundi

ISBN: (纸本)9798350327816

In Burundi, Anti Retroviral Therapy(ART) helps to control infected people living with Immunodeficiency Virus/Acquired Immune Deficiency Syndrome(HIV/AIDS), but the rate of deaths is still high. This paper presents a model for predicting the survival of HIV/AIDS patients treated in health institution' Association Nationale de Soutien aux Seropositifs et Malades du SIDA' (ANSS) in Burundi. Algorithms of Artificial Neural Network(ANN) and Decision Tree(DT) were used for predicting the survival of People Living With HIV(PLWHIV) under the ANSS health care departments. The results show that the average probability of survival of patients at ANSS institution was 90.2% for an average follow-up period of 5 years. The developed model will help ANSS institution and the Ministry of Health to define effective management strategies for these HIV/AIDS patients. © 2023 IEEE.

关键词： ANSS Artificial Neural Network Burundi Decision Tree HIV/AIDS survival prediction

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A news image captioning approach based on multimodal pointer-generator network

A news image captioning approach based on multimodal pointer...

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作者： Chen, Jingqiang Zhuge, Hai School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Network Engineering Guangzhou University Guangzhou China Department of Computer Science School of Engineering and Applied Science Aston University Birmingham United Kingdom Key Laboratory of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing China

News image captioning aims to generate captions or descriptions for news images automatically, serving as draft captions for creating news image captions manually. News image captions are different from generic captions as news image captions contain more detailed information such as entity names and events. Therefore, both images on news and the accompanying text are the source of generating caption of news image. Pointer-generator network is a neural method defined for text summarization. This article proposes the Multimodal pointer-generation network by incorporating visual information into the original network for news image captioning. The multimodal attention mechanism is proposed by splitting attention into visual attention paid to the image and textual attention paid to the text. The multimodal pointer mechanism is proposed by using both textual attention and visual attention to compute pointer distributions, where visual attention is first transformed into textual attention via the word-image relationships. The multimodal coverage mechanism is defined to reduce repetitions of attentions or repetitions of pointer distributions. Experiments on the DailyMail test dataset and the out-of-domain BBC test dataset show that the proposed model outperforms the original pointer-generator network, the generic image captioning method, the extractive news image captioning method, and the LDA-based method according BLEU, METEOR, and ROUGL-L evaluations. Experiments also show that the proposed multimodal coverage mechanisms can improve the model, and that transforming visual attention to pointer distributions can improve the model. © 2020 John Wiley & Sons, Ltd.

关键词： Statistical tests

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A computer-Controlled FPGA-Based Pulser/Receiver System for Ultrasound Instrumentation

A Computer-Controlled FPGA-Based Pulser/Receiver System for ...

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Ultrasonics Symposium (LAUS), IEEE UFFC Latin America

作者： Amauri Amorin Assef Ednilson de Souza Contieri Gilson Maekawa Kanashiro Michel Andrey Freitas Kohler Joaquim Miguel Maia Eduardo Tavares Costa Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELT Federal University of Technology– Paraná (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) Federal University of Technology– Paraná (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) Federal University of Technology– Paraná (UTFPR) Federal Institute of Paraná (IFPR) Paranavaí Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELN Federal University of Technology–Paraná (UTFPR) Curitiba Brazil DEEB-FEEC & CEB State University of Campinas (UNICAMP) Campinas Brazil

ISBN: (数字)9798350349085

ISBN: (纸本)9798350349092

Developing novel ultrasound methods for biomedical investigations typically requires costly instruments, which are not always available in research laboratories. This paper describes the implementation of a flexible computer-controlled FPGA-based pulser/receiver (P/R) system for ultrasound research. The system's main features are limited dimensions, the capability to generate complex waveforms using the Pulse Width Modulation (PWM) technique, and direct access to raw data. The proposed system was characterized in the first evaluation by measuring the central frequency and bandwidth of the output waveforms generated using a 5 MHz transducer. A 3-cycle 5 MHz sinusoidal excitation pulse with the Hanning window and a 5 µs chirp pulse from 3 to 7 MHz with the Tukey window were applied. Next, phantom experiments were performed using a 1.6 MHz transducer to measure the resolution of 15 targets with 1 mm diameter and 10 mm apart in the axial direction using the FWHM method. The results demonstrate that the P/R system can be used for medical ultrasound research and instrumentation, including piezoelectric transducer driver, high-intensity focused ultrasound (HIFU), non-destructive testing (NDT), and pulse waveform generator.

关键词： Ultrasonic imaging Ultrasonic variables measurement Chirp Instruments Piezoelectric transducers Pulse width modulation Biomedical measurement

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