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A fault-tolerant scheduling strategy through proactive and clustering techniques for scientific workflows in cloud computing

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Soft Computing 2025年第2期29卷 755-781页

作者： Farhood, Suha Mubdir Khorsand, Reihaneh Hussein, Nashwan Jasim Ramezanpour, Mohammadreza Branch Islamic Azad University Isfahan Iran Department of Programming Collage of Information Technology University of Babylon Hillah Iraq Department of Computer Engineering Mobarakeh Branch Islamic Azad University Mobarakeh Isfahan Iran

Cloud computing offers solutions for various scientific and business applications. Large-scale scientific applications, which are organized as scientific workflows, are carried out using cloud computing. However, the higher failure rates in cloud computing can be attributed to the numerous servers and components dealing with intense workloads. This study presents a fault-tolerant scheduling approach using proactive and clustering methods for scientific workflows in cloud computing. Initially, the task clustering issue is addressed by consolidating multiple short-duration tasks into a single job to improve the runtime performance of workflow executions. Subsequently, an automated workflow scheduling strategy is outlined with four key stages: monitoring, analysis, planning, and execution. During monitoring, clustered jobs and the capacities of available cloud resources are observed. In the analysis phase, the accuracy of failure prediction is enhanced by employing the Group Method of Data Handling (GMDH) neural network prior to any faults or failures. The planning stage introduces a novel hybrid multi-objective algorithm, MOPSO-aSA, based on MOPSO and adaptive simulated annealing (SA), to streamline workflow scheduling in error-prone execution environments. Moreover, the reliability of application execution is maintained through re-clustering and migration techniques following any faults or failures. Finally, based on the experimental findings, it is evident that the proposed strategy surpasses other methods in terms of makespan, total cost, energy consumption, and failure rate. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Simulated annealing

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Renal Tumor Classification and Detection Based on Artificial Intelligence 3

Renal Tumor Classification and Detection Based on Artificial...

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3rd International Conference on Communications, information System, and Data Science, CISDS 2024

作者： Al-Taie, Raflaa Hilmi Hussein, Nashwan J. Physiology and Organ Functions Department College of Medicine University of Babylon Iraq Department of Electrical Power Engineering AL-Hussain University College Department of Programming Collage of Information Technology University of Babylon Iraq

ISBN: (数字)9781510688322

ISBN: (纸本)9781510688315

The kidney is a crucial organ in the human body, co-operating billions of pipelines to cleanse the body's water. Kidney failure, renal tumor happens when cells divide uncontrollably and form an aberrant collection of cells surrounding or within the kidney. This cell type has the ability to disrupt regular kidney activity and destroy healthy cells. The prompt diagnosis of renal tumor is critical since they can be fatal if left untreated. Because it is dependent on the skill of the person analyzing the images, the traditional approach of manually checking the MR image may not be very accurate. The study concentrated on the diagnosis of normal and normal renal tumor. To enhance accuracy and expedite diagnosis, using publicly accessible individual records, the present research used methodologies for machine learning, involving support vector machine learning (SVM), adaptive optimization (AO), as well as gradient enhancement (GE). It uses an approach for making the dataset reduced multidimensional. Image feature extraction is a data preprocessing method that minimizes the time required to train the proposed algorithm. The accuracy rates of the algorithms for diagnosing normal and up normal are reported to be 88.8 % for GB, 83.8 % for ADA, 86.1 % for SVM and 93.3% for KNN and for up normal diagnosis tumor are reported to be 55.3 % for GB, 55.4 % for SVM, 55.3 % for ADA and 51.0% for KNN. © 2025 SPIE.

关键词： Image enhancement

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Educational Research Trends of the Use of Gaze Learning Data Through Topic Modeling and Scientometric Analysis 1st

Educational Research Trends of the Use of Gaze Learning D...

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1st International workshop on AI for Research, AI4Research 2024 and 4th International workshop on Democracy and AI, DemocrAI 2024, held in conjunction with 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024

作者： Lee, Jungmin Shin, Huigon Yoo, YoungJoon Choi, Jongwon Kim, Mi Song Department of Advanced Imaging GSAIM Chung-Ang University Seoul Korea Republic of Computer Programming and Analysis School of Information Technology Fanshawe College London Canada Department of Artificial Intelligence Chung-Ang University Seoul Korea Republic of Curriculum Studies Western University London Canada

ISBN: (纸本)9789819795352

Multimodal learning analytics have become increasingly important in enabling a deeper understanding of teaching and learning in educational research. However, in comparison to other multimodal learning data, there is a limited understanding of the trends within gaze learning data. To address this challenge, this study aims to identify latent topics in gaze learning data through topic modeling and scientometric analysis. We analyzed the abstracts of 573 peer-reviewed and conference proceeding papers that used gaze learning data, written in English, and published between 2008 and February 2024. The findings are as follows. First, three main topics were identified through topic modeling analysis: (learning analytics, multimodal learning, and inclusive learning). Second, the scientometric analysis revealed the structure in which diverse clusters in cited references and institutions are connected around the emerging topics. Based on these findings, the study would provide insights into research directions in both educational research and applications using gaze learning data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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A blockchain-oriented covert communication technology with controlled security level based on addressing confusion ciphertext

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Frontiers of Computer Science 2025年第2期19卷 133-135页

作者： Lejun ZHANG Bo ZHANG Ran GUO Zhujun WANG Guopeng WANG Jing QIU Shen SU Yuan LIU Guangxia XU Zhihong TIAN Sergey GATAULLIN Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China Research and Development Center for E-Learning Ministry of EducationBeijing 100039China College of Information Engineering Yangzhou UniversityYangzhou 225009China School Math and Computer Science Quanzhou Normal UniversityQuanzhou 362000China Pazhou Lab Guangzhou 510330China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of SciencesMoscow 117418Russia Industrial Programming Department MIREA-Russian Technological UniversityMoscow 119454Russia

1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods also exist,such as peer-to-peer networks and distributed hash *** technology,which is decentralized,anonymous,non-tamperable and anti-attack,can be applied to covert communication to solve the problems of traditional methods and improve the quality of communication.

关键词： communication tables networks

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The use of Cryptography in Network Security

The use of Cryptography in Network Security

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9th International Conference on Application of information and Communication Technologies, AICT 2015

作者： Jafarov, Zafar Information Technology and Programming' Department Azerbaijan Technical University Baku Azerbaijan

ISBN: (纸本)9781467368551

Network Security is the most vital component in information security because it is responsible for securing all information passed through networked computers. Network Security refers to all hardware and software functions, characteristics, features, operational procedures, accountability, measures, access control, and administrative and management policy required to provide an acceptable level of protection for Hardware and Software, and information in a network. Only one particular element underlies many of the security mechanisms in use: Cryptographic techniques; hence our focus is on this area Cryptography. Cryptography is an emerging technology, which is important for network security. Research on cryptography is still in its developing stages and a considerable research effort is still required for secured communication. © 2015 IEEE.

关键词： Network security

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Text classification experiments on Mongolian language

Text classification experiments on Mongolian language

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8th International Forum on Strategic technology, IFOST 2013

作者： Damiran, Zolboo Altangerel, Khuder MUST-CSMS/Department of Information System Ulaanbaatar Mongolia MUST-CSMS/Department of Programming Technology Ulaanbaatar Mongolia

ISBN: (纸本)9781479909315

Text classification is an important task of assigning objects from a universe to two or more classes, especially classification is to classify the topic or the theme of a document. In this research, we have analyzed the result of an experiment on a text classification using Naive Bayesian method approaches for Mongolian language. We have training set of documents, each labeled with one of 10 classes. Since it is the first work in this field for Mongolian language no previous work results were available for comparison. © 2013 IEEE.

关键词： Classification (of information)

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A succinct canonical register automaton model for data domains with binary relations

A succinct canonical register automaton model for data domai...

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10th International Symposium on Automated technology for Verification and Analysis, ATVA 2012

作者： Cassel, Sofia Jonsson, Bengt Howar, Falk Steffen, Bernhard Dept. of Information Technology Uppsala University Sweden Department of Programming Systems Technical University Dortmund Germany

ISBN: (纸本)9783642333859

We present a novel canonical automaton model for languages over infinite data domains, that is suitable for specifying the behavior of services, protocol components, interfaces, etc. The model is based on register automata. A major contribution is a construction of succinct canonical register automata, which is parameterized on the set of relations by which elements in the data domain can be compared. We also present a Myhill Nerode-like theorem, from which minimal canonical automata can be constructed. This canonical form is as expressive as general deterministic register automata, but much better suited for modeling in practice since we lift many of the restrictions on the way variables can be accesed and stored: this allows our automata to be significantly more succinct than previously proposed canonical forms. Key to the canonical form is a symbolic treatment of data languages, which allows us to construct minimal representations whenever the set of relations can be equipped with a so-called branching framework. © 2012 Springer-Verlag.

关键词： Automata theory

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A New Method for Research of Grown-In Microdefects in Dislocation-Free Silicon Single Crystals

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Journal of Crystallization Process and technology 2011年第2期1卷 13-17页

作者： V.I Talanin I.E Talanin N.Ph Ustimenko Department of Programming & Information Technology Classic Private University

As a virtual experimental device for analysis and calculation of grown-in microdefects formation in undoped silicon dislocation-free single crystals the software is proposed. The software is built on the basis on diffusion model of formation, growth and coalescence of grown-in microdefects. Diffusion model describes kinetics of defect structure changes during cooling after growth on crystallization temperature to room temperature. The software allows the use of personal computer to investigate the defect structure of dislocation-free silicon single crystals with a diameter on 30 mm to 400 mm grown by floating-zone and Czochralski methods.

关键词： Silicon Grown-In Microdefects Precipitate Vacancy Microvoid Interstitial Dislocation Loop

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Visual Language Plans - Formalization of a pedagogical learnflow modeling language

Visual Language Plans - Formalization of a pedagogical learn...

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International Workshop on Petri Nets and Software Engineering, PNSE 2014

作者： Irgang, Kerstin Irgang, Thomas Human-Centered Information Systems Clausthal University of Technology Germany Department of Software Engineering and Theory of Programming Fernuniversität Hagen Germany

In this paper we present an approach to support selfregulated learn-flows in the collaborative environment Metafora. In this environment students construct Visual Language Plans. Those plans model workflows of learning activities, which the students execute to solve complex learning scenarios across different tools. Visual Language plans were already used in the context of different pedagogical studies but have no formal syntax or semantics, yet. In this paper, we present the syntax of Visual Language Plans and develop a mapping from Visual Language Plans to Petri net defining semantics. With the help of this semantics, the environment can support the students executing their learnflows. If students execute activities given in a Visual Language Plan which are not enabled in the corresponding Petri net, feedback messages occur guiding the students. Students can refine their Visual Language Plan during execution. If a plan changes the corresponding Petri net model also changes. Analyzing the newly generated Petri net model can help to uncover faulty states of the learnflow model.

关键词： Visual languages

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Promoter recognition with machine learning algorithms keREM, RULSE-3 and ANN

Promoter recognition with machine learning algorithms keREM,...

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International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012

作者： Karli, Günay Nayir, Ahmet Faculty of Engineering and Information Technology International Burch Universiy Sarajevo Bosnia and Herzegovina Department of Computer Programming Fatih University Istanbul Turkey

ISBN: (纸本)9781467314466

Data mining has become an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering interesting and previously unknown knowledge from very large real world database. These databases contain potential gold mine of valuable information, but it is beyond human ability to analyze massive amount of data and elicit meaningful patterns by using conventional techniques. In this study, DNA sequence was analyzed to locate promoter which is a regulatory region of DNA located upstream of a gene, providing a control point for regulated gene transcription. In this study, some supervised learning algorithms such as artificial neural network (ANN), RULES-3 and newly developed keREM rule induction algorithm were used to analyse to DNA sequence. In the experiments different option of keREM, RULES-3 and ANN were used, and according to the empirical comparisons, the algorithms appeared to be comparable to well-known algorithms in terms of the accuracy of the extracted rule in classifying unseen data. © 2012 IEEE.

关键词： Supervised learning

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