Metaheuristics with Vector Quantization Enabled Codebook Compression Model for Secure Industrial Embedded Environment

Article Computer Science, Information Systems

An Implementation of Modified Blowfish Technique with Honey Bee Behavior Optimization for Load Balancing in Cloud System Environment

Preeti Rani et al.

Summary: Cloud computing allows data to be stored on virtual servers, with load balancing being a critical challenge. Various solutions have been proposed, with the Modified-HBB-LB technique outperforming existing strategies and reducing the number of migration tasks by 30%, 25%, and 20% compared to other techniques. Additionally, the proposed technique maintains 3-5% higher performance levels on makespan, completion, and response time compared to existing comparative techniques.

WIRELESS COMMUNICATIONS & MOBILE COMPUTING (2022)

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Article Mathematical & Computational Biology

Manta Ray Foraging Optimization with Vector Quantization Based Microarray Image Compression Technique

Nora A. Alkhaldi et al.

Summary: DNA microarray technologies are important for studying genetic function, regulation, and interaction. This paper presents a microarray image compression technique using the MRFO algorithm and LBG model, which achieved superior compression efficacy compared to existing models through optimized codebooks and Deflate-based index table compression.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

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Article Engineering, Electrical & Electronic

Communication-Efficient Federated Learning Over MIMO Multiple Access Channels

Yo-Seb Jeon et al.

Summary: This paper proposes a communication-efficient strategy for federated learning over multiple-input multiple-output multiple access channels (MACs). The strategy involves compressing high dimensional local gradients to lower-dimensional gradient vectors using block sparsification and performing joint MIMO detection and sparse local-gradient recovery. Simulation results demonstrate that the proposed method significantly reduces communication cost while achieving identical classification accuracy.

IEEE TRANSACTIONS ON COMMUNICATIONS (2022)

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Article Engineering, Electrical & Electronic

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

Mingzhe Chen et al.

Summary: This paper provides a comprehensive study on efficiently deploying distributed learning over wireless edge networks, presenting several emerging paradigms including federated learning, federated distillation, distributed inference, and multi-agent reinforcement learning. It addresses challenges such as uncertain wireless environment, limited resources, and hardware constraints, offering guidelines and future research opportunities.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2021)

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Article Mathematical & Computational Biology

Sequence Fusion Algorithm of Tumor Gene Sequencing and Alignment Based on Machine Learning

Chao Tang et al.

Summary: With the advancement of DNA high-throughput technology, the correlation between DNA sequence variation and human diseases has become a major focus. Research is focused on detecting DNA sequence variation and establishing a DNA sequence sparse matrix. The study proposes new SNP and InDel detection methods and achieves good experimental results in intelligent reasoning research.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2021)

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Article Computer Science, Information Systems

Metaheuristic-based vector quantization approach: a new paradigm for neural network-based video compression

Saad M. Darwish et al.

Summary: Video compression plays a significant role in motion picture communication by eliminating redundancies in both temporal and spatial domains. Current research focuses on enhancing neural network-based video codecs for better predictions and adaptive compression techniques.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

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Review Computer Science, Information Systems

A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications

Uthayakumar Jayasankar et al.

Summary: The explosive growth of data in the digital world has led to the development of efficient data compression techniques to minimize storage and transmission requirements. Various approaches have been developed, and a detailed survey has been conducted to address current data quality needs, coding schemes, data types, and applications. Comparative analysis has been performed, and future research directions have been highlighted.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2021)

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Article Computer Science, Information Systems