Let p be a prime and Fq be the finite field of order q = pm. In this paper, we study FqR-skew cyclic codes where R = Fq + uFq with u2 = u. To characterize FqR-skew cyclic codes, we first establish their algebraic stru...
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Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease that is often caused by abnormal genes in the heart muscle. The identification of HCM-related genes is one of the crucial tasks to prevent and treat the pa...
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ISBN:
(纸本)9781665462730
Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease that is often caused by abnormal genes in the heart muscle. The identification of HCM-related genes is one of the crucial tasks to prevent and treat the patient. Gene expression analysis is a direct approach to screen for a gene with a higher or lower expression level in the HCM cell than in the normal cell. Microarray and RNA-Seq technology are used for measuring transcription levels. Both techniques have different advantages to obtain gene expression data. The integration of microarray and RNA-Seq data has already been effectively used to identify disease biomarkers. The ranking method is an interesting technique and is mostly used for ranking players or teams in sports. Each method has different strengths and can be appropriately applied to integrate various data and used to prioritize the importance genes. In this work, six ranking techniques to integrate microarray and RNA-Seq data were applied to prioritize the HCM-related genes. The performance reveals that the ranking method is also a well-suited technique in this task, and it turns out that the PageRank technique yields the best performance.
Energy production from solar photovoltaic (PV) plants is unpredictable, mainly due to the stochastic formation and movement of clouds or aerosol - dust particles which scatter or disperse solar radiation. Accurate for...
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A large number of objects participating in the voting can be an advantage as well as a disadvantage. In the case of decentralized federated learning, adding the model to the aggregation is preceded by a vote. The choi...
A large number of objects participating in the voting can be an advantage as well as a disadvantage. In the case of decentralized federated learning, adding the model to the aggregation is preceded by a vote. The choice of voters and their results can be falsified through various attacks such as dataset poisoning. In this paper, we propose a fuzzy consensus analyzing the results of individual voters regarding the aggregation of a given model. The consensus is based on a fuzzy controller that selects the most reliable models for aggregation. For this reason, it uses image-modifying heuristics and quick evaluations of incoming results. If a decision is made that a selected client is unreliable several times, it is blocked to reduce the number of performed operations. The proposed system was tested on selected tasks related to image classification. The results were discussed and compared to evaluate the proposed system.
Conformal prediction is a statistical framework that generates prediction sets containing ground-truth labels with a desired coverage guarantee. The predicted probabilities produced by machine learning models are gene...
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The symmetrized tropical semiring is an extension of the tropical semifield, initially introduced to solve tropical linear systems using Cramer’s rule. It is equivalent to the signed tropical hyperfield which has bee...
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With several deep learning approaches, the domain of automatic speech recognition (ASR) has seen notable advancements in recent times. The domains of intelligent human- computer interaction and machine translation gre...
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ISBN:
(数字)9798350372120
ISBN:
(纸本)9798350372137
With several deep learning approaches, the domain of automatic speech recognition (ASR) has seen notable advancements in recent times. The domains of intelligent human- computer interaction and machine translation greatly benefited from accurate speech recognition. The present study introduces a hybrid architecture amalgamating a convolutional neural network (CNN) and bidirectional long short-term memory (BLSTM) for speech recognition. For aligning speech input sequences with corresponding text output sequences, it uses the connectionist temporal classification (CTC) technique. The experiments were done on the LJ speech dataset, and the results showed with an increased number of training samples, the performance of the speech recognition algorithm tended to be increased but the time taken for training gradually increased over time. Moreover, a trained speech recognition algorithm exhibits a longer training time when the recognition accuracy is lower. In this study, we implemented a hybrid deep learning model CNN-BLSTM, in conjunction with the CTC loss function, which attains a word error rate (WER) of 36.97% on the testing dataset.
We consider coloring problems inspired by the theory of anti-Ramsey / rainbow colorings that we generalize to a far extent. Let F be a hereditary family of graphs;i.e., if H ∈ F and H′ ⊂ H then also H′ ⊂ F. For a g...
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In this paper, we address problems related to parameters concerning edge mappings of graphs. Inspired by Ramsey’s Theorem, the quantity m(G, H) is defined to be the minimum number n such that for every f: E(Kn) → E(...
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As the capacity of communications systems is currently being outpaced by the increasing demand for access to audio-visual services, the versatile video coding (VVC) standard has emerged. It shows around 40% bit rate s...
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ISBN:
(数字)9798350379037
ISBN:
(纸本)9798350379044
As the capacity of communications systems is currently being outpaced by the increasing demand for access to audio-visual services, the versatile video coding (VVC) standard has emerged. It shows around 40% bit rate savings over the predecessor codec, the high efficiency video coding (HEVC) standard. However, this coding gain is obtained with a significant increase in the computational complexity associated with VVC. The cuboidal partitioning algorithm has shown capabilities in modeling both the global and local commonality of a video frame and discovers a set of non-overlapping rectangular regions, known as cuboids, over the current frame. Since cuboids are highly homogeneous and are computationally efficient, in this paper, it is proposed to employ their intrinsic homogeneity information in predicting the coding tree unit (CTU) structure of VVC. Experimental results show that up to 10.5% complexity reduction for intra coded 4K resolution video sequences, with an increase in bit rate by 1.4%.
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