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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2024年第4期86卷 81-94页

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Okumus, Ibrahim Taner Tapus, Nicolae Faculty of Automatic Control and Computer Science University of Science and Technology POLITEHNICA Bucharest Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey Dept. of Computer Science University of Science and Technology POLITEHNICA Bucharest Romania

The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study presents a comparative performance evaluation of traditional networking paradigms and Software-Defined Networking (SDN)-based architectures within WSN. Utilizing the Floodlight SDN controller and Mininet-WiFi emulator, we conducted a series of experiments across three different network topologies, varying the number of hosts and access points. The performance metrics focused on are average latency, packet loss percentage, and throughput. The results demonstrate a considerable improvement in all measured parameters under the SDN-based environment compared to the traditional setup. Specifically, SDN environments consistently showcased lower latency, minimal packet loss, and higher throughput, with the most notable difference observed in smaller network configurations. The findings suggest that SDN, with its centralized control plane, can significantly enhance the performance of WSNs, particularly in scenarios demanding rapid scalability and dynamic traffic management. This study underscores the potential of SDN architectures in optimizing WSN operations and lays the groundwork for future research in this domain. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Floodlighting

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Distributed Event-Triggered Adaptive Cooperative Circumnavigation control of Networked Unmanned Aerial Vehicles 20

Distributed Event-Triggered Adaptive Cooperative Circumnavig...

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20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Ghommam, Jawhar Fareh, Raouf Al Naimi, Ibrahim Sultan Qaboos University College of Engineering Department of Electrical and Computer Engineering Oman Laboratory of Control Energy Management ENIS Tunisia University of Sharjah Electrical Engineering Dept. United Arab Emirates

ISBN: (纸本)9798350332568

In this paper, the objective for a group of unmanned aerial vehicle agents (UAVs) to achieve three dimensional circumnavigation around a moving target which information is made available to all agents in the group. The cooperative circumnavigation is to drive the UAVs to orbit around the target according to a given elliptical desired spatial formation. Due to the thrust limitation needed to fly the drone, existing cyclic pursuit algorithms cannot be extended directly to achieve this objective. Thus the proposed algorithm is worked out to take into account this constraint in order to achieve such objective. The drones are subject to unknown external disturbance, also the masses of those agent drones are assumed to be unknown. Furthermore, the communication cost can be decreased and the Zeno behavior is shown to be excluded. The proposed controller guarantees the bounded control effort irrespective of the external disturbance and model uncertainties of the drone. Numerical simulations are conducted to illustrate the efficacy of the approach. © 2023 IEEE.

关键词： Drones

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A Systematic Study on Ransomware Attack: Types, Phases and Recent Variants 5

A Systematic Study on Ransomware Attack: Types, Phases and R...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Krishna Prasad, D.S. Prasanna Kumar, H.R. Dept. of Computer & Communication Engineering. Karnataka574110 India Visvesvaraya Technological University Belagavi590018 India Pes Institute of Technology and Management Dept. of Information Science and Engineering Shivamogga India

ISBN: (纸本)9798350385649

The rise of ransomware attacks presents a major cybersecurity threat, leading to considerable financial losses and disrupting crucial operations across diverse sectors. In-dept. research on the field of ransomware assaults is presented in this study, with particular attention to the various kinds and variations that have appeared throughout time. This research includes a thorough examination of the strategies, processes, and methods that ransomware perpetrators use to carry out their operations. The study outlines the many stages in the lifecycle of ransomware attacks, including the introduction of infection vectors, the use of encryption tools, and the last step of extortion. The research also explores the terrain of ransomware variations, recognizing the evolution and diversity of these threats throughout time. With a taxonomy that categorizes variations depending on their dissemination methods, encryption algorithms, and evasion approaches. © 2024 IEEE.

关键词： Cybersecurity

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Exploratory Data Analysis of Titanic Survival Prediction using Machine Learning Techniques 2

Exploratory Data Analysis of Titanic Survival Prediction usi...

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2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Gupta, Anshika Arora, Deepak Tiwari, Shivam Aset Lucknow Amity University Dept. of Computer Science & Engineering Uttar Pradesh India Gl Bajaj Institute Technology & Management Dept. of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9781665456302

It is very important to find out the root causes of human tragedies in the past so that future crises can be avoided. The incident of 15 April 1912 is an example of a human tragedy in which around 1500 passengers and working staff lost their lives. Continuous research in today's time shows that if the proper statistical assessment was done then it would probably be possible that human devastation could be reduced. In today's era, many new and powerful technologies are available, with the help of which accurate statistical calculations can be done. In this research study, Titanic survivals have been studied based on machine learning techniques. In the study, out of the total entities, 891 entities have been used for training and 418 entities have been used for the test set and the comparative study of different machine learning algorithms gives importance to this research study. © 2023 IEEE.

关键词： Machine learning

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A hierarchical and modular agent-oriented framework for power systems co-simulations

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Energy Informatics 2022年第4期5卷 48页

作者： De Vizia, Claudia Macii, Alberto Patti, Edoardo Bottaccioli, Lorenzo Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Interuniversity Dept. of Regional and Urban Studies Politecnico di Torino Turin Italy

During the last decades, numerous simulation tools have been proposed to faithfully reproduce the different entities of the grid together with the inclusion of new elements that make the grid "smart". Often, these domain-specific simulators have been then coupled with co-simulation platforms to test new scenarios. In parallel, agent-oriented approaches have been introduced to test distributed control strategies and include social and behavioural aspects typical of the consumer side. Rarely, simulators of the physical systems have been coupled with these innovative techniques, especially when social and psychological aspects have been considered. In order to ease the re-usability of these simulators, avoiding re-coding everything from scratch, we propose a hierarchical and modular agent-oriented framework to test new residential strategies in the energy context. If needed, the presented work enables the user to select the desired level of details of the agent-based framework to match the corresponding physical system without effort to test very different scenarios. Moreover, it allows adding on top of the physical data, behavioural aspects. To this end, the characteristics of the framework are first introduced and then different scenarios are described to demonstrate the flexibility of the proposed work: (i) a first stand-alone scenario with two hierarchy levels, (ii) a second co-simulation scenario with a photovoltaic panel simulator and (iii) a third stand-alone scenario with three hierarchy levels. Results demonstrate the flexibility and ease of use of the framework, allowing us to compare several scenarios and couple new simulators to build a more and more complex environment. The framework is in the early stages of its development. However, thanks to its properties in the future it could be extended to include new actors, such as industries, to get the full picture. © 2022, The Author(s).

关键词： Smart power grids

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SDN-based Mobile Edge Computing with Vacation of Virtual Machines 3

SDN-based Mobile Edge Computing with Vacation of Virtual Mac...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Rout, Suchismita Jaiswal, Ankita Bagade, Monika Keshao Patra, Sudhansu Shekhar Kiit Deemed to Be University School of Computer Engineering Bhubaneswar India Shri Ramdeobaba College of Engineering and Management Dept. of Computer Sc. & Engineering Nagpur India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9798350381931

A vast array of IoT devices have been implemented worldwide as cloud computing and virtualization have become more and more commonplace. Because of this, processing of computationally demanding tasks is moved from the edge to the centralised cloud, increasing energy consumption in cloud data centres and causing a noticeable delay for vital applications. The paradigm for cloud computing has shifted in recent years from centralised to mobile edge computing (MEC), where computational workloads are delegated to edge servers close to user equipment (UE). This epitome results in minimal latency for UE, effective resource utilisation at the edge, and decreased energy consumption in cloud data centres. Given this, developing optimal energy-saving solutions for resource allocation and computing job offloading in MEC networks has become a challenging challenge due to the rapidly growing size and complexity of these networks. The vacation policy is a suggested power-saving traffic management strategy for edge servers. Software-defined network (SDN) architecture allows virtual machines (VMs) to take vacations. The goal of QoS optimisation is to decrease the active servers serving the tasks while maintaining QoS criteria. Numerous performance metrics of the system are calculated, including average system size, sojourn duration, percentage of client requests fulfilled, and frequency of desertion. Lastly, many numerical results are given to demonstrate the influence of certain particular factors on the MEC performance metrics. © 2024 IEEE.

关键词： Mobile edge computing

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FERVENCY: A Squashy Intrigue to Ascertain Emotions using Textual Categorization 4

FERVENCY: A Squashy Intrigue to Ascertain Emotions using Tex...

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4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Datta, Suseta Mitra, Poojarini Kundu, Pritam University of Engineering & Management Kolkata Dept. of Computer Science and Engineering Kolkata India University of Engineering & Management Kolkata Dept. of Computer Applications Kolkata India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Emotion Detection (ED) is a type of sentimental analysis that uses text data to generate and assess emotions. This is a relatively new field in Natural Language Processing, computer Linguistics, and Text Analysis. The fundamental goal is to recognize emotions in a variety of contexts, including language, facial expressions, gestures, and noises. This study provides an effective and accurate method by searching for essential phrases in a specified database. By categorizing enormous quantities of text, an automated communication system was also constructed and tested to anticipate moods. This article discusses three different types of machine learning classifiers that may be used to categorize text patterns and discern emotions. The Light Gradient Boost Machine (LightGBM) Classifier has given 93.2% mean accuracy based on repetition of 10 objects in 3 times. LightGBM has performed marginally better than other two classifiers (Extreme Gradient Boosting and Category Boosting). The suggestions detail the primary contributions, as well as the methodology utilized, databases used, conclusions gained, and strengths and shortcomings. Finally, the goal of this research is to better emotional categorization and the relationship between dispersion and different types of emotions. © 2022 IEEE.

关键词： Natural language processing systems

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Radiomics-based classification in imbalanced datasets: complexity or interpretability

Radiomics-based classification in imbalanced datasets: compl...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Simone Boesso Lorenzo Farina Manuela Petti Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Radiomics represents a specialized branch of medical imaging where quantitative features are extracted from images. Performing a classification using radiomics means solving two common problems: the imbalanced setting, and the large number of features that would increase the risk of overfitting. Moreover, since its main application and impact are in clinical field, there is the need of interpretable models for explaining their results. The aim of this study is to compare two modelling approaches: one based on a logistic regression model, known for its simplicity and interpretability, and RUSBoost, an ensemble method designed to handle class imbalance with potentially higher complexity, in order to answer the question whether higher complexity and lower interpretability are justified when dealing with radiomics data. Additionally, due to the large literature suggesting it, we analyze the impact of a feature selection step applied to these two classifiers. Test performances measured across 20 repeated splits on two datasets show how the RUSBoost approach is able to capture more detailed patterns of the data but this is highly dependent on the dataset at hand.

关键词： Logistic regression Analytical models Feature extraction Oncology Data models Complexity theory Mutual information Radiomics Overfitting Tumors

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Challenges in Integrating Data Analytics in Small Businesses 1

Challenges in Integrating Data Analytics in Small Businesses

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, Priyanka Mahalakshmi, S. Singh, Sangeeta Agrawal, Ankur Kumar Nazli, Sadaf Sneha, G. Chandigarh University Dept. of Computer Sci. Engineering Chandigarh India Madhav University Dept. of CSE Pindwara India Management and Commerce Dept. of Buss Aligarh India J.S. University Dept. Of Management Shikohabad India Dhanalakshmi Srinivasan College Dept. of Business Administration Coimbatore India

ISBN: (纸本)9798350356816

For small businesses, the integration of data analytics is fraught with a variety of obstacles that prevent these organizations from capitalizing on decision making support tools powered by their data. In this abstract, this will examine the major challenges these small enterprises face: limited financial resources and a lack of technical knowledge or scalable tools suited for their scale. Initial Costs: As an SMB, the worst thing that you can do is spend your entire tech budget on analytics software because oftentimes even when you think like a giant but act like small business Analytics Software companies have prohibitively high costs. Furthermore, the integration itself may be impeded by legacy technology infrastructure and staff entrenched in traditional modes of working who are unwilling to embrace new methods. In contrast, overcoming these obstacles by adopting data analytics has sizable revenue and competitive capabilities Solving these problems with budget solutions, adequate training and clear strategies will allow small businesses to exploit the potential of data analytics. This paper aims to establish a ground comprehension on these issues and necessitates the need for agile, mobile analytics solutions in small enterprises. © 2024 IEEE.

关键词： Cluster Data analytics Small business analytics

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GANs for Synthetic Environmental Data Generation (Air Quality) for Low-Resource Regions 2

GANs for Synthetic Environmental Data Generation (Air Qualit...

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2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Verma, Seema Jain, Neha Mahapatra, Madhumita Setia, Sonia Sachdeva, Vrinda Kumar, Manoj Dept. of Computer Science & Engineering Delhi Technical campus Uttar Pradesh Greater Noida India Dept. of Computer Science & Engineering Sharda University Uttar Pradesh Greater Noida India Dept. of Computer Science & Engineering G.L Bajaj Institute of Technology and Management Uttar Pradesh Greater Noida India Uttar Pradesh Ghaziabad India

ISBN: (纸本)9798331541217

Due to the significant expenses and logistical difficulties involved in deploying monitoring equipment, many areas, especially those in developing nations, lack adequate environmental data. This work presents a novel approach that uses Generative Adversarial Networks (GANs) for creating artificial environmental data. The model of GAN is trained for generating synthetic data for under-monitored or unmonitored areas by utilizing high-resolution environmental data from well-monitored regions. The paper discusses the generation of synthetic data and its comparison with real data based on statistical properties. The analysis reveals that the characteristics of the created data closely align with the actual data. With the help of this synthetic data, researchers and policymakers will be able to make more informed decisions by having precise estimations of important environmental indicators like air quality. © 2024 IEEE.

关键词： Generative adversarial networks

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