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A position-enhanced sequential feature encoding model for lung infections and lymphoma classification on CT images
PurposeDifferentiating pulmonary lymphoma from lung infections using CT images is challenging. Existing deep neural network-based lung CT...
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Procedure-Aware Action Quality Assessment: Datasets and Performance Evaluation
In this paper, we investigate the problem of procedure-aware action quality assessment, which analyzes the action quality by delving into the...
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DNA codes over \(GR(2^{3},d)[X]/\langle X^{2},2X \rangle\)
The main results of this paper are in two directions. First, the family of finite local rings of length 4 whose annihilator of their maximal ideals...
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Representation, arbitrariness, and the emergence of speech
This paper discusses three related claims. The first claim is that the expressive limitations of iconic and indexical communication and cognition are...
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Needle tracking in low-resolution ultrasound volumes using deep learning
PurposeClinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-time navigation, faces the challenge of precise...
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Beyond Cognition and Affect: An Analysis of Anorexia Nervosa within the Framework of Addiction
Anorexia Nervosa is widely recognized as having both cognitive and affective dimensions. Current accounts typically explain the perplexing behaviors...
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A network intrusion detection system based on deep learning in the IoT
As industrial and everyday devices become increasingly interconnected, the data volume within the Internet of Things (IoT) has experienced a...
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Parameters optimization and precision enhancement of Takagi–Sugeno fuzzy neural network
Takagi–Sugeno fuzzy neural network (TSFNN) has been widely used in intelligent prediction. The prediction accuracy of TSFNN is impacted by its model...
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A novel fusion feature imageization with improved extreme learning machine for network anomaly detection
As the complexity and quantity of network data continue to increase, accurate and efficient anomaly detection methods become critical. Deep...
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MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods
In recent years, some classical graph contrastive learning(GCL) frameworks have been proposed to address the problem of sparse labeling of graph data...
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Mindfulness in Orthopedic Rehabilitation: Can the Use of a Mindfulness Diary Positively Influence the Therapeutic Outcome of Orthopedic Rehabilitation?
ObjectivesMindfulness is a proven therapeutic practice for reducing anxiety, depression, and chronic pain, which are factors that influence the...
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Distributed neuro-fuzzy routing for energy-efficient IoT smart city applications in WSN
Wireless sensor networks (WSNs) enable seamless data gathering and communication, facilitating efficient and real-time decision-making in IoT...
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Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans
The use of algorithms and automated systems, especially those leveraging artificial intelligence (AI), has been exploding in the public sector, but...
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Fake and propaganda images detection using automated adaptive gaining sharing knowledge algorithm with DenseNet121
An additional tool for swaying public opinion on social media is to present recent developments in the creation of natural language. The term “Deep...
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Detection of pulmonary nodules in chest radiographs: novel cost function for effective network training with purely synthesized datasets
PurposeMany large radiographic datasets of lung nodules are available, but the small and hard-to-detect nodules are rarely validated by computed...
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Analyzing processing time and load factor: 5-node mix network with ElGamal encryption and XOR shuffling
To provide anonymous communication, this paper proposes the implementation of a 5-node mix network using ElGamal encryption and XOR Shuffling. An...
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When is it acceptable to break the rules? Knowledge representation of moral judgements based on empirical data
Constraining the actions of AI systems is one promising way to ensure that these systems behave in a way that is morally acceptable to humans. But...
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VLSI realization of hybrid fast fourier transform using reconfigurable booth multiplier
A discrete fourier transform (DFT) of a series of samples may be quickly and efficiently computed with the use of a mathematical procedure known as...
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Subgraph generation applied in GraphSAGE deal with imbalanced node classification
In graph neural network applications, GraphSAGE applies inductive learning and has been widely applied in important research topics such as node...
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A Review of Anonymization Algorithms and Methods in Big Data
In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of...