Computer and Information Science

Foreword
Contents
Contributors
symKrypt: A Lightweight Symmetric-Key Cryptography for Diverse Applications
	1 Introduction
	2 Proposed Systems
		2.1 Preliminary
		2.2 Description
		2.3 Encryption Process
		2.4 Decryption Process
		2.5 Sequence of Messages\' Blocks
		2.6 Encryption of the Entire Message as a Single Block
		2.7 True-Random Number Generator
		2.8 Pseudo-random Number Generator
	3 Analysis
		3.1 Time Complexity
		3.2 Correctness of SymKrypt
		3.3 Brute-Force Attacks
		3.4 Birthday Attacks
		3.5 Cryptanalysis Attacks
		3.6 Attacks Analysis
		3.7 Dictionary Attacks
		3.8 Attacks Analysis
	4 Experimental Results
		4.1 Cryptography Testing
		4.2 Randomness Testing
		4.3 Pseudo-random Number Generator
	5 Discussion
	6 Conclusion
	References
PK-BERT: Knowledge Enhanced Pre-trained Models with Prompt for Few-Shot Learning
	1 Introduction
	2 Related Work
		2.1 Pre-trained Language Model for Few-Shot Learning
		2.2 Pre-trained Language Model with Prompt
		2.3 Knowledge Enhanced Pre-trained Language Model
	3 Methodology
		3.1 Notation
		3.2 Dataset and Benchmark
		3.3 Prompt
		3.4 Representation
		3.5 Masked Language Modelling for Few-Shot Learning
	4 Experiments
		4.1 Experimental Principle
		4.2 Experimental Parameters
		4.3 Experimental Result
		4.4 Confusion Matrix
		4.5 Sample Setting and Baseline Models
		4.6 Comparison of Results
	5 Discussion
	6 Conclusions
	References
Typhoon Track Prediction Based on TimeForce CNN-LSTM Hybrid Model
	1 Introduction
	2 TF-CNN-LSTM Model
		2.1 CNN Model
		2.2 TimeForce Module
		2.3 LSTM Model
	3 Experiment
		3.1 Experimental Data
		3.2 Accuracy Evaluation Index
		3.3 Analysis of Experimental Results
		3.4 Case Verification
	4 Discussion
	5 Conclusion
	References
The Novel Characterizing Method of Collective Behavior Pattern in PSO
	1 Introduction
	2 Related Work
		2.1 The Original PSO Algorithm
		2.2 Swarm State Division Based on the Evolutionary Factor
		2.3 Swarm State Division Based on Order Parameter
	3 Our Work
		3.1 Visualization of Swarm Behavior Pattern
		3.2 Swarm Trend Factor of PSO
	4 Experimental Results
		4.1 Description of Algorithm Performance by Swarm Trend Factor
		4.2 Comparison with Evolutionary Factor
	5 Conclusions
	References
Research on Box Office Prediction of Commercial Films Based on Internet Search Index and Multilayer Perceptron
	1 Introduction
	2 Data Collection and Forecasting Methods
		2.1 Baidu Index and Google Trends
		2.2 Data Collection
		2.3 Forecasting Methods
	3 Results and Findings
		3.1 Results
		3.2 Findings
	4 Conclusion
	References
A DCRC Model for Text Classification
	1 Introduction
	2 Related Work
		2.1 CNN Model
		2.2 BiLSTM Model
		2.3 BiGRU Model
	3 Problem Definition and Proposed Work
		3.1 BiGRU-CNN Based Text Feature Acquisition and Context Dependent Learning
		3.2 Mitigation of Feature Loss Problems Based on BiLSTM
		3.3 Overview of the DCRC Model
	4 Experiments
		4.1 Datasets
		4.2 Evaluation
		4.3 Experiment Results
	5 Conclusion
	References
Hierarchical Medical Classification Based on DLCF
	1 Introduction
	2 Background and Related Work
		2.1 CNN Model
		2.2 LSTM
		2.3 Random Forest
	3 Problem Definition and Proposed Work
		3.1 Introduction to the DLC Layer
		3.2 Introduction to R Layer
		3.3 Overview of DLCR Model
	4 Experiments
		4.1 Datasets
		4.2 Baselines and Evaluation
	5 Conclusion and Future Work
	References
Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks
	1 Introduction
	2 Related Work
	3 Materials and Methods
		3.1 Dataset and Pre-processing
		3.2 1D CNN Design
	4 Experimental Results
	5 Conclusion
	References
Based on the Analysis of Interrelation Between Parallel Distributed Computer System and Network
	1 Introduction
	2 Combined with the Interconnection of Network Resources, the Time-Sharing System of Computer Is Analyzed
	3 Analyze the Processor Inside the Computer, Extending to Distributed Network Analysis
		3.1 Analysis of Distributed Treatment
		3.2 Peripheral Multi-machine System
		3.3 Relationship Between Distribution Processing and Network
	4 Analysis of Computer System Parallelism, Extending to Distributed Network Systems
		4.1 Analysis of Computer Space Structure
		4.2 Computer Structure Combined with the Role of Processor Implementation
		4.3 Structure Analysis of Distributed Computer System
		4.4 The Role of Computer Systems in the Form of Network Distribution
	5 Conclusion
	References
Improvement of DGA Long Tail Problem Based on Transfer Learning
	1 Introduction
	2 Related Work
		2.1 Long Tail
		2.2 DGA Detection
	3 Methodology
		3.1 Long Tail
		3.2 Data Pre-processing
		3.3 Transfer Learning
		3.4 Data Balanced Review
	4 Experiments
		4.1 Dataset
		4.2 Experimental Setup
	5 Experimental Results
	6 Conclusions
	References
A Phonetics and Semantics-Based Chinese Short Text Fusion Algorithm
	1 Introduction
	2 Method
		2.1 Background
		2.2 Feature Construction
		2.3 Training
		2.4 Similarity Calculation and Features Fusion
	3 Experiments and Result
		3.1 Evaluation Setting
		3.2 Comparison Result
		3.3 Component Analysis
	4 Conclusion
	References
Feature Extension for Chinese Short Text Based on Tongyici Cilin
	1 Introduction
	2 Method
		2.1 Compute Surface Similarity
		2.2 Segment Words and Extract Major Differences in Sentenses
		2.3 Similarity Calculation of Major Difference Components
		2.4 Similarity Calculation of Major Difference Components
	3 Experiment and Analysis
		3.1 Dataset
		3.2 Evaluation Setting
		3.3 Criteria
		3.4 Comparison Result
	4 Conclusion
	References
Task-Level Consistency Semi-supervised Based Domain Adaptation for Lung Nodules Segmentation
	1 Introduction
	2 Related Work
		2.1 nnU-Net
		2.2 Dual-Task Consistency (DTC)
	3 Method
		3.1 Dataset
		3.2 DTC Semi-supervised Based Domain Adaptation
		3.3 Dual-Task Deep Supervision
	4 Evaluation Metrics
		4.1 Dice Similarity Coefficient
		4.2 Precision and Recall
	5 Experiments and Results
		5.1 Experimental Platform
		5.2 Applying nnU-Net
		5.3 Result
	6 Conclusion
	References
Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures
	1 Introduction
	2 Literature Review
	3 Materials and Methods
		3.1 Convolutional Neural Networks
		3.2 Generative Adversarial Networks
		3.3 The Dataset
		3.4 Proposed Method
	4 Results and Discussion
		4.1 DCGAN Results
		4.2 Hyper Parameters Tuning
	5 Conclusion
	References
Author Index