Article
Computer Science, Information Systems
Md Atiqur Rahman, Mohamed Hamada
Summary: This paper proposes a lossless image compression method by reducing image dimensions and using prediction techniques, which demonstrates an improvement compared to existing techniques.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Biochemical Research Methods
Felix Hanau, Hannes Rost, Idoia Ochoa
Summary: The study introduces a new compression algorithm, mspack, for mass spectrometry data, which exploits additional redundancy to achieve higher compression ratios, supporting both lossless and lossy compression for mzML and mzXML formats. In experiments, mspack achieved an average reduction of 76% in file sizes for lossless compression and 94% for lossy compression compared to the original files. Additionally, mspack outperforms existing algorithms in compression efficiency and runtime performance.
Article
Engineering, Multidisciplinary
Saad Merrouche, Boban Bondzulic, Milenko Andric, Dimitrije Bujakovic
Summary: This paper analyzes the lossless and lossy compression of disparity images with low range resolution. The WebP image format is found suitable for lossless compression with an average compression ratio of 20. The HEIC algorithm achieves much higher compression ratios with acceptable reduction of disparity map accuracy.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Computer Science, Information Systems
Tonny Hidayat, Mohd Hafiz Zakaria, Ahmad Naim Che Pee
Summary: Compression is a crucial process in digitizing data, especially in the era of Big Data. Lossless compression reduces data size without losing any information, making it ideal for archiving files. Huffman's algorithm is an effective method for 8-bit data compression.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Merve Varol Arisoy
Summary: With the advancement of digitalization, the use of Internet for transmitting text documents instead of human transmission has grown. This has led to the idea that text documents can serve as a secure means of storing information. Researchers have found that deep learning models are more resistant to steganalysis compared to traditional methods such as word-line shifting and synonym replacement. In this study, text generation techniques were employed to hide information both at the word and character level, using methods such as arithmetic coding and Huffman coding. The proposed method outperformed existing techniques in terms of information embedding efficiency and resistance to steganalysis.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Chemistry, Analytical
Aniol Marti, Jordi Portell, Jaume Riba, Orestes Mas
Summary: We propose an algorithm based on linear prediction for lossless and near-lossless compression of RF signals. Two signal detection methods are used: spectrum sensing and error computation in the Levinson-Durbin algorithm. These algorithms are integrated into FAPEC, a data compressor for space missions. Testing on different datasets shows that our approach achieves better compression ratios than gzip and is comparable to FLAC, but with higher speeds. Performance of our signal detectors is also assessed, demonstrating high compression ratios through lossy compression of irrelevant signal segments.
Article
Computer Science, Interdisciplinary Applications
Diego Rossinelli, Gilles Fourestey, Felix Schmidt, Bjoern Busse, Vartan Kurtcuoglu
Summary: The rapid increase in medical and biomedical image acquisition rates has created new opportunities and challenges for image analysis. Development of data compression schemes has become an important step in addressing the high I/O bandwidth demand caused by high acquisition rates.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Chemistry, Analytical
Tomasz Krokosz, Jarogniew Rykowski, Malgorzata Zajecka, Robert Brzoza-Woch, Leszek Rutkowski
Summary: Modern cryptosystems often require the length of the encrypted data to be approximately the same as or longer than the encryption key. However, in resource-constrained wireless sensor nodes, the data payload can be very short while the key length is much longer. This article proposes using a combination of two data compression algorithms as a standard-length encryption key algorithm to enhance the security of short data sequences.
Article
Engineering, Electrical & Electronic
Erdal Erdal
Summary: Efficient encoding algorithms are introduced in the study, utilizing frequency modulation and Huffman encoding in compression algorithms. Testing on 30 images from three different datasets showed excellent performance of the algorithms.
JOURNAL OF ELECTRONIC IMAGING
(2021)
Article
Computer Science, Information Systems
Xiaoxiao Liu, Ping An, Yilei Chen, Xinpeng Huang
Summary: An improved lossless image compression algorithm is proposed in this study, which achieves higher compression ratios by combining linear prediction, integer wavelet transform, and Huffman coding. Experimental results demonstrate that the algorithm outperforms state-of-the-art algorithms, especially on images with complex textures and higher resolutions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Tassnim Dardouri, Mounir Kaaniche, Amel Benazza-Benyahia, Jean-Christophe Pesquet
Summary: This paper proposes a compression scheme based on neural network learning of lifting operators, and improves the dynamic fully connected neural network model for better consideration of input images. The experimental results demonstrate the advantages of this method in lossy and lossless image compression.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Steffy Maria Joseph, P. S. Sathidevi
Summary: This paper proposes two algorithms to improve the lossless compression efficiency for high spatial resolution microarray images using general entropy codecs. By utilizing Huffman and arithmetic coders and JPEG 2000, the algorithms aim to ensure the availability of decoders for future applications of the images.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
Mohammed Otair, Laith Abualigah, Mohammed K. Qawaqzeh
Summary: This paper proposes a new method for digital image compression by dividing the image into blocks and utilizing Huffman coding technique, aiming to improve compression rates and maintain image quality.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Hardware & Architecture
Albin Eldstal-Ahrens, Angelos Arelakis, Ioannis Sourdis
Summary: This article introduces a hybrid lossy/lossless compression scheme (LC)-C-2, which is applicable to both the memory subsystem and I/O traffic of a processor chip. By combining general-purpose lossless compression with state-of-the-art lossy compression, (LC)-C-2 achieves high compression ratios and improves the utilization of chip's bandwidth resources, resulting in improved system performance and energy efficiency.
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
(2022)
Article
Mathematics, Applied
Aharon Fruchtman, Yoav Gross, Shmuel T. Klein, Dana Shapira
Summary: A new dynamic Huffman encoding is proposed, which utilizes future information instead of past information. This study extends the idea to bidirectional adaptive compression and shows that it performs at least as well as static Huffman and improves on the future-only based variant. The technique is further extended to arithmetic coding with theoretical and empirical results supporting the enhancement of the new compression algorithm.
DISCRETE APPLIED MATHEMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Mohammed Hassan, Mohamed Hamada
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2018)
Article
Multidisciplinary Sciences
Md Atiqur Rahman, Mohamed Hamada
Article
Computer Science, Information Systems
Jesse Jeremiah Tanimu, Mohamed Hamada, Mohammed Hassan, Habeebah Kakudi, John Oladunjoye Abiodun
Summary: This study developed a predictive model for cervical cancer outcome using a decision tree algorithm and feature selection techniques. SMOTETomek was employed to handle missing values and imbalanced data for improved performance. The decision tree classifier with selected features exhibited high accuracy and sensitivity in addressing feature reduction and class imbalance issues.
Review
Chemistry, Multidisciplinary
Latifat Salau, Mohamed Hamada, Rajesh Prasad, Mohammed Hassan, Anand Mahendran, Yutaka Watanobe
Summary: Recommender systems (RSs) are intelligent software that predict users' opinions on specific items. This survey examines literature on RSs in e-learning, providing classification and statistics. The survey reveals the trends in traditional and nontraditional recommendation techniques, offering different recommendations for future e-learning.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Anand Mahendran, Kumar Kannan, Mohamed Hamada, Manuel Mazzara
Summary: This paper explores the insertion operation in DNA computing and the evolutionary computation model based on it. By analyzing the trade-off between different complexity measures and levels of ambiguity, the application of these measures in natural language and bio-molecular structure modeling is examined.
Article
Engineering, Electrical & Electronic
Aminu Musa, Mohammed Hassan, Mohamed Hamada, Farouq Aliyu
Summary: Recent advances in computing have made it possible to automate hydroponic systems for real-time plant disease detection. However, existing deep learning models are not suitable for embedded systems and cannot be deployed on resource-constrained IoT devices. Therefore, this paper proposes a low-power deep learning model using knowledge distillation techniques for plant disease detection.
JOURNAL OF LOW POWER ELECTRONICS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Md. Atiqur Rahman, Mohamed Hamada
Summary: This article introduces a method for selecting the optimal lossless data compression technique and provides an analysis based on experimental results to demonstrate its effectiveness. The model recommends the best algorithm for each type of data based on application requirements.
Article
Operations Research & Management Science
Sarika Jain, Sumit Sharma, Jorrit Milan Natterbrede, Mohamed Hamada
INTERNATIONAL JOURNAL OF KNOWLEDGE AND SYSTEMS SCIENCE
(2020)
Article
Computer Science, Theory & Methods
Mohammed Hassan, Mohamed Hamada, Saratu Yusuf Ilu
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2020)
Proceedings Paper
Computer Science, Hardware & Architecture
Md. Atiqur Rahman, Mohamed Hamada
2019 IEEE 13TH INTERNATIONAL SYMPOSIUM ON EMBEDDED MULTICORE/MANY-CORE SYSTEMS-ON-CHIP (MCSOC 2019)
(2019)
Article
Computer Science, Interdisciplinary Applications
Mohamed Hamada, Mohammed Hassan
Article
Education & Educational Research
Mohamed Hamada, Mohamed Hassan
EURASIA JOURNAL OF MATHEMATICS SCIENCE AND TECHNOLOGY EDUCATION
(2017)
Article
Education & Educational Research
Mohamed Hamada, Mohammed Hassan
EURASIA JOURNAL OF MATHEMATICS SCIENCE AND TECHNOLOGY EDUCATION
(2017)
Proceedings Paper
Computer Science, Hardware & Architecture
Mohammed Hassan, Mohamed Hamada
2017 IEEE 11TH INTERNATIONAL SYMPOSIUM ON EMBEDDED MULTICORE/MANY-CORE SYSTEMS-ON-CHIP (MCSOC 2017)
(2017)