Siddiq Babaker

Applied Science University

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Ahmed Alkhayyat

Iraqi University

Kun Zhang

Xavier University of Louisiana

Ming Su

Hebei University

Anas Ratib Alsoud

Al-Ahliyya Amman University

Jayant Jagtap

NIMS University

Jie Gao

Affiliated Hospital of Nantong University

Jie Xiong

Jiangxi University of Technology

Dingfa Liu

Wen's Food Group (China)

Jaspreet Kaur

Punjab Engineering College

Ali Khatibi

Management and Science University

Cooperative Institutions

Uttaranchal University

Chongqing University

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation

Al-Ahliyya Amman University

Management and Science University

Graduate School USA

Jiangxi University of Technology

Iraqi University

University of Babylon

Islamic University

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Label big data compression in Internet of things based on piecewise linear regression

Applied Mathematics and Nonlinear Sciences (2022)

Ming Su Kun Zhang Jianwei Zhao Siddiq Babaker

Abstract In order to solve the key problem that most of the energy of wireless sensor network nodes is consumed in wireless data modulation, which is an extremely important and limited resource. The energy efficiency evaluation scheme of data compression algorithm based on the separation of hardware factor and algorithm factor is proposed; In order to improve the running efficiency of the compression algorithm and reduce the energy consumption of the algorithm itself, a program level energy-saving optimization method for the data compression algorithm is proposed; In order to keep the energy-saving benefits of the data compression algorithm when the wireless transmission power is adjusted, an adjustment mechanism of the compression algorithm which can adapt to the change of transmission power is proposed. The experiment shows that when the wireless transmission power is - 7dBm and below (k < 178.4), the data should be compressed by S-LZW algorithm, and when the wireless transmission power is - 5dBm and above (k > 178.4), the b ~ RLE algorithm should be used for compression. The validity of the method is verified.

Data compression ratio

10.2478/amns.2022.2.0136

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Improving Reliability and Data Management in Internet of Things Based Wireless Sensor Networks

Internet Technology Letters (2025)

Siddiq Babaker Ali Khatibi Anas Ratib Alsoud Jaspreet Kaur Jayant Jagtap

ABSTRACT With the rapid growth of the Internet of Things (IoT), wireless sensor networks (WSNs) are becoming increasingly vital in advancing information and communication technologies. These networks are widely integrated with the Internet across numerous applications. In WSN‐assisted IoT, ensuring energy efficiency and security is critical for Quality of Service (QoS), but remains challenging due to the networks' open and resource‐constrained nature. This paper introduces a novel solution: a secure entropy‐based Jaccard similarity integrated with a fuzzy C‐means (EJS‐FCM) clustering approach for dynamic WSN‐IoT networks. Cluster heads (CHs) are selected using a boosted grasshopper optimization (BGO) algorithm, and an Adler‐32 hashing‐based scheme authenticates each sensor node. Secure hash elliptical curve cryptography (SHECC) then encrypts data collected from the CHs, enhancing IoT data security through hashing functions in both encryption and decryption. The proposed approach significantly improves security, QoS, and energy efficiency, as evidenced by enhanced network lifetime, throughput, packet delivery ratio, delay, and encryption time.

10.1002/itl2.646

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Retrieval and Characteristic Analysis of Multimedia Tester Based on Bragg Equation

Applied Mathematics and Nonlinear Sciences (2022)

Jie Gao Siddiq Babaker

Abstract In order to solve the problem of Bragg equation, a research on retrieval and feature of multimedia testing machine is proposed. Firstly, this paper investigates the various stages of multimedia retrieval system and some mainstream multimedia retrieval algorithms, in order to cover all aspects of relevant algorithms. Secondly, on the basis of investigation, eight representative algorithms are selected. These algorithms cover three stages of multimedia retrieval system, including feature extraction stage, feature matching stage and geometric verification stage. Based on the above observed characteristics, finally, some relevant suggestions on architecture design and system optimization are put forward, including the design of single node processor, the design in parallel environment and the suggestions for simulation and evaluation using this test set.

Feature (linguistics)

10.2478/amns.2022.2.0135

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Uniqueness of system integration scheme of artificial intelligence technology in fractional differential mathematical equation

Applied Mathematics and Nonlinear Sciences (2022)

Dingfa Liu Jie Xiong Siddiq Babaker

Abstract At present, various branches of mathematics have developed very mature, but they still lack an internal structural correlation. They are like “islands” in the universe. If we can find the universal conversion relationship of the three basic mathematical structures of geometry, arithmetic and logic, it will greatly expand the field of mathematics. The ultimate goal of mathematics in the past is to pursue its preciseness, while the ultimate goal of mathematics in the future is to pursue its unity. Fractional differential equation is a generalization of integer order calculus. It discusses the theory of any non integer order differential and integral equation. The rise of artificial intelligence technology just provides the most powerful laboratory for the unity of mathematics. To explore the mystery of the brain and achieve the ultimate goal of artificial intelligence technology, the key is to make a major breakthrough in basic mathematical research and find a basic theoretical system describing the mutual mapping and transformation of different mathematical paradigms. The unity of mathematics will undoubtedly become the forefront of the development of mathematics in the future, which will be the core of the research on the new generation of intelligent computer and artificial intelligence technology.

10.2478/amns.2022.2.0103

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