Road traffic has been an open challenge in a highly-populated area in the world. India is one of them where traffic management is a crucial problem to solve. Road traffic congestion, traffic rule violation, road accid...
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In recent times, drastic climate changes have caused a substantial increase in the growth of crop diseases. This causes large-scale demolition of crops, decreases cultivation, and eventually leads to the financial los...
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In this paper,the authors revisit decentralized control of linear quadratic(LQ)*** of imposing an assumption that the process and observation noises are Gaussian,the authors assume that the controllers are restricted ...
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In this paper,the authors revisit decentralized control of linear quadratic(LQ)*** of imposing an assumption that the process and observation noises are Gaussian,the authors assume that the controllers are restricted to be *** authors show that the multiple decentralized control models,the form of the best linear controllers is identical to the optimal controllers obtained under the Gaussian noise *** main contribution of the paper is the solution ***,optimal controllers for decentralized LQ systems are identified using dynamic programming,maximum principle,or spectral *** authors present an alternative approach which is based by combining elementary building blocks from linear systems,namely,completion of squares,state splitting,static reduction,orthogonal projection,(conditional)independence of state processes,and decentralized estimation.
Power load forecasting is essential for optimizing power generation and distribution efficiency. This paper proposes a novel method for daily average load forecasting, referred to as LARSI-TPE-XGB, which integrates th...
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Model-to-model transformations involve converting one type of the model into another. This can be used in many ways for various reasons, considering model performance with particular deployment platforms. This paper i...
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In this paper, we introduce the Maximum Distance Sublattice Problem (MDSP). We observed that the problem of solving an instance of the Closest Vector Problem (CVP) in a lattice L is the same as solving an instance of ...
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Offensive messages on social media,have recently been frequently used to harass and criticize *** recent studies,many promising algorithms have been developed to identify offensive *** algorithms analyze text in a uni...
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Offensive messages on social media,have recently been frequently used to harass and criticize *** recent studies,many promising algorithms have been developed to identify offensive *** algorithms analyze text in a unidirectional manner,where a bidirectional method can maximize performance results and capture semantic and contextual information in *** addition,there are many separate models for identifying offensive texts based on monolin-gual and multilingual,but there are a few models that can detect both monolingual and multilingual-based offensive *** this study,a detection system has been developed for both monolingual and multilingual offensive texts by combining deep convolutional neural network and bidirectional encoder representations from transformers(Deep-BERT)to identify offensive posts on social media that are used to harass *** paper explores a variety of ways to deal with multilin-gualism,including collaborative multilingual and translation-based ***,the Deep-BERT is tested on the Bengali and English datasets,including the different bidirectional encoder representations from transformers(BERT)pre-trained word-embedding techniques,and found that the proposed Deep-BERT’s efficacy outperformed all existing offensive text classification algorithms reaching an accuracy of 91.83%.The proposed model is a state-of-the-art model that can classify both monolingual-based and multilingual-based offensive texts.
Social media users articulate their opinions on a broad spectrum of subjects and share their experiences through posts comprising multiple modes of expression, leading to a notable surge in such multimodal content on ...
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Cloud computing has drastically changed the delivery and consumption of live streaming *** designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technic...
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Cloud computing has drastically changed the delivery and consumption of live streaming *** designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technical and business issues surrounding cloudbased live streaming is provided,including the benefits of cloud computing,the various live streaming architectures,and the challenges that live streaming service providers face in delivering high‐quality,real‐time *** different techniques used to improve the performance of video streaming,such as adaptive bit‐rate streaming,multicast distribution,and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is *** such as improving user experience and live streaming service performance using cutting‐edge technology,like artificial intelligence and machine learning are *** addition,the legal and regulatory implications of cloud‐based live streaming,including issues with network neutrality,data privacy,and content moderation are *** future of cloud computing for live streaming is examined in the section that follows,and it looks at the most likely new developments in terms of trends and *** technology vendors,live streaming service providers,and regulators,the findings have major policy‐relevant *** on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector,as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.
The art of hiding secret text within an innocuous cover medium is steganography. Steganalysis is the counterpart of steganography which focuses on the detection and extraction of the secret text from the medium. Featu...
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ISBN:
(数字)9783031612985
ISBN:
(纸本)9783031612978
The art of hiding secret text within an innocuous cover medium is steganography. Steganalysis is the counterpart of steganography which focuses on the detection and extraction of the secret text from the medium. Feature engineering is the crucial field in Stegware Analysis which intends to identify more specific features, focusing on the accuracy and efficiency. Feature engineering is a process in Machine learning where the features of any dataset are selected and extracted for further use. Feature engineering is the process of extracting, transforming and selecting the most relevant features form the data that aids in discriminating between the stego and cover image. This is because, most of the time, the data will be in a raw format. Any ML model needs the data to be pre-processed and kept ready to train the model. Thus, from the pool of raw data, the required data needs to be selected and can be used in training the model. Further, the data at point needs to be extracted to get the precise data. The scope of the work is to identify the various feature engineering techniques available in practice and efficiently use them to achieve high accuracy and precision in the system. The survey focuses on the several feature selection and extraction techniques like filter method, wrapper method and embedded methods. Correlation being one of the feature selection methods is focused;while statistical moments computes the mean, variance and skewness of the feature. The extraction method holds the Computation of Invariants and other such. Comparative study is made on both the methods to understand the concepts with ease. The work starts by taking a sample from the dataset and few feature extraction techniques are applied on the same. Then the original image is compared with the extracted images with the view of histogram. The paper gives valuable insights into the effectiveness of different feature engineering techniques using the dataset and underscores the importance of featu
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