This study scrutinizes five years of Sarajevo's Air Quality Index (AQI) data using diverse machine learning models - Fourier autoregressive integrated moving average (Fourier ARIMA), Prophet, and Long short-term m...
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Recently,the Internet of Things(IoT)has been used in various applications such as manufacturing,transportation,agriculture,and healthcare that can enhance efficiency and productivity via an intelligent management cons...
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Recently,the Internet of Things(IoT)has been used in various applications such as manufacturing,transportation,agriculture,and healthcare that can enhance efficiency and productivity via an intelligent management console *** the increased use of Industrial IoT(IIoT)applications,the risk of brutal cyber-attacks also *** leads researchers worldwide to work on developing effective Intrusion Detection systems(IDS)for IoT infrastructure against any malicious ***,this paper provides effective IDS to detect and classify unpredicted and unpredictable severe attacks in contradiction to the IoT infrastructure.A comprehensive evaluation examined on a new available benchmark TON_IoT dataset is *** data-driven IoT/IIoT dataset incorporates a label feature indicating classes of normal and attack-targeting IoT/IIoT ***,this data involves IoT/IIoT services-based telemetry data that involves operating systems logs and IoT-based traffic networks collected from a realistic medium-scale IoT *** is to classify and recognize the intrusion activity and provide the intrusion detection objectives in IoT environments in an efficient ***,several machine learning algorithms such as Logistic Regression(LR),Linear Discriminant Analysis(LDA),K-Nearest Neighbors(KNN),Gaussian Naive Bayes(NB),Classification and Regression Tree(CART),Random Forest(RF),and AdaBoost(AB)are used for the detection intent on thirteen different intrusion *** performance metrics like accuracy,precision,recall,and F1-score are used to estimate the proposed *** experimental results show that the CART surpasses the other algorithms with the highest accuracy values like 0.97,1.00,0.99,0.99,1.00,1.00,and 1.00 for effectively detecting the intrusion activities on the IoT/IIoT infrastructure on most of the employed *** addition,the proposed work accomplishes high performance compared to other recent rela
The extreme learning machine is a fast neural network with outstanding performance. However, the selection of an appropriate number of hidden nodes is time-consuming, because training must be run for several values, a...
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This paper reports on ongoing and innovative research in the area of eXplainable Artificial Intelligence (XAI). A classical XAI task is considered as finding an explanation of the model generated via Machine Learning ...
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Microgrids (MGs) serve as central interfaces for distributed generation, predominantly employing voltage source inverters (VSIs). These MGs operate in either autonomous or grid-connected modes, facilitating local powe...
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The utilization of binary representation of the embeddings over real valued features represents a promising avenue, in terms of memory savings and faster operations for various machine learning models. In this researc...
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Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly *** this,with its distributed and dynamic nature and shortcomings in virtualization deployme...
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Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly *** this,with its distributed and dynamic nature and shortcomings in virtualization deployment,the cloud environment is exposed to a wide variety of cyber-attacks and security *** Intrusion Detection System(IDS)is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various *** attacks are becoming more frequent and powerful,and their attack pathways are continually changing,which requiring the development of new detection *** the purpose of the study is to improve detection *** Selection(FS)is *** the same time,the IDS’s computational problem is limited by focusing on the most relevant elements,and its performance and accuracy *** this research work,the suggested Adaptive butterfly optimization algorithm(ABOA)framework is used to assess the effectiveness of a reduced feature subset during the feature selection phase,that was motivated by this motive *** classification is not compromised by using an ABOA *** design of Deep Neural Networks(DNN)has simplified the categorization of network traffic into normal and DDoS threat ***’s parameters can be finetuned to detect DDoS attacks better using specially built *** reconstruction error,no exploding or vanishing gradients,and reduced network are all benefits of the changes outlined in this *** it comes to performance criteria like accuracy,precision,recall,and F1-Score are the performance measures that show the suggested architecture outperforms the other existing *** the proposed ABOA+DNN is an excellent method for obtaining accurate predictions,with an improved accuracy rate of 99.05%compared to other existing approaches.
Cardiovascular diseases (CVDs) persist as a primary cause of mortality on a global scale, necessitating effective prediction methods. This study presents a novel modelling approach utilizing the Self-Organizing Map (S...
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We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we ...
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Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret in...
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Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information *** enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover *** this paper,a novel encrypted communication scheme for image SWE is *** reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer *** employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be *** receiver can restore the secretmessage fromthe received image using only the list header position *** scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover *** boasts high concealment and security,along with a complete message restoration rate,making it resistant to ***,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of *** validate the proposed framework,practical tests and comparisons are conducted using multiple *** results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.
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