International Journal of Computational Thinking and Data Science

Enhancing Quantum Information Processing – SU(2) Operator Model Development for Three-Qubit Quantum Systems Entanglement Classification

Amirul Asyraf Zhahir — 2024-09-15

The study introduces the development of the operator model within the Local Unitary (LU) protocol for entanglement classification, specifically of the pure three-qubit quantum systems. Addressing the challenge of accurately distinguishing different classes of entanglement, this research aims to enhance the understanding and utilization of entangled quantum states in quantum information processing. A systematic approach was employed in the development of the model, designed to effectively distinguish different classes of entanglement. This study contributes significantly to quantum information processing, by providing valuable insights into the nature of entangled quantum states and enabling researchers to gain a better understanding, utilizing them effectively in various quantum applications. The developed operator model holds significant potential for the advancements in entanglement classification and broaderscope of quantum information processing. The model marks a notable achievement in enabling a more precise and efficient entanglement of entangled quantum systems, which is crucial for advancing various quantum technologies. Future research should extends this model to a higher-qubit and higher-dimensional quantum systems and explore its integration with several other entanglement classification protocols and Lie groups to further advance the field.

Approximation of Interval Type-2 Neutrosophic Bézier Surface Model for Uncertainty Data

Siti Nur Idara Rosli — 2024-09-15

Some data will be wasted during the data collection process due to uncertain criteria or noise information. In the context of the interval type-2 neutrosophic set (IT2NS) theory's ability to handle uncertain data, this study will use geometric models to illustrate how all data will be processed. IT2NS is a generalization of the type-1 neutrosophic set, interval type-2 fuzzy set, and intuitionistic fuzzy set. This study will show how to use the approximation approach to visualize the interval type-2 neutrosophic Bézier surface (IT2NBS) model. However, the existence of truth, indeterminacy, and falsity membership functions in neutrosophic features makes the model challenging to visualize. Apart from that, the attributes of IT2NS have an upper and lower bound, which makes it difficult. Using the IT2NS theory, this study will first introduce an interval type-2 neutrosophic control net (IT2NCN) to build the model. The IT2NBS models will be represented by blending the IT2NCN and the Bernstein basis function. Afterward, the truth, indeterminacy, and falsity memberships of the IT2NBSs are approximated for the mean, upper and lower bounds of the IT2NCN. A review of the algorithm used to create the IT2NBS approximation models will wrap up the study. Fortunately, the results of this study will yield a predictive model that is used in some medical applications or bathymetry data collection that involves the uncertainty data problem in the data collection.

Performance Analysis of Light Detection and Ranging (LIDAR) in Augmented Reality (AR)

Muhammad Iskandar Sa’at Sa’at — 2024-09-15

Augmented reality (AR) has existed for decades, dating back from roughly 50 years ago when the renowned ‘father of computer graphics’ Ivan Sutherland first invented an AR head-mounted display system. Ever since, various organizations strive to improve the technology but while the AR technology definitely evolved significantly since its advent, the technology progress is relatively stagnant these past few years whereby we see little to no usage at least from common end user perspective. This may be due to various limitations of technologies currently utilized in AR. However, things may change since in 2020, the tech giant, Apple Inc. has made an unprecedented breakthrough by including the light detection and ranging (LiDAR) scanner on consumers’ smartphones which could potentially revolutionize the AR industry. This research primarily revolves around analyzing the performance of utilization of LiDAR technology in AR mainly in mobile devices available for the mass. The methodology and concept for this research is fairly straight-forward, the AR experience boosted by the newly introduced LiDAR technology will be compared with the widely used technology which primarily consist of the implementation of Simultaneous Localization and Mapping (SLAM) and RGB camera with the exclusion of LiDAR and assessing the potential of LiDAR to further improvise AR experience and implementation in various fields. Testing results has shown significant improvement from various important aspects in AR whereby occlusion is possible in object rendering, the estimations based on live visual stimuli accuracy at roughly 99% in comparison to the true values as well as the ability to accurately perceive the geometry of objects in the real world environment through advanced depth and space perception.

3D Lightweight Cryptosystem Design for IoT Applications Based on Composite S-Box

Tasnuva Ali — 2024-09-15

The security of the Internet of Things (IoT) depends on strong cryptographic functions that require extensive computation and resources. The security of Internet of Things (IoT) relies on the use of strong cryptographic functions that demand extensive computation and resources. Therefore, the selection of a cryptographic system is influenced by the computational and communicational capabilities of IoT devices, including their energy requirements, memory constraints, and execution time. This paper aims to develop a lightweight and secure encryption algorithm for IoT applications, focusing on advancing cryptanalysis techniques. We propose a new lightweight algorithm named enhanced 3D RECTANGLE, designed to deliver robust security for IoT applications and optimized for cell phones with minimal memory usage, low power consumption, and efficient performance. The RECTANGLE block cipher was chosen for this research due to its high efficiency and speed relative to other lightweight algorithms, despite some security issues. The proposed enhanced 3D RECTANGLE algorithm improves confusion and diffusion properties through a new 3D array block rotation method for 4x4 plaintext, based on a 128-bit key and 16 rounds. Additionally, we designed a 4x4 composite S-Box with a Galois field pipelining structure, offering a more advanced solution compared to the Look-Up Table method. The cryptanalysis, avalanche effect, and bit error rate tests were conducted to verify the security strength of the proposed algorithm. The proposed algorithm was evaluated against two existing algorithms, RECTANGLE and Extended 3D RECTANGLE. The enhanced 3D RECTANGLE algorithm provides better cryptanalysis, demonstrating a 40% avalanche effect and achieving a bit error rate (BER) of 31%, indicating its greater effectiveness compared to the other two lightweight algorithms.