Journal of Electronic & Information Systems

Abstract: Traditional collaborative signature schemes face significant challenges in resisting quantum computing attacks, securing private keys in distributed architectures, and balancing operational efficiency, which are critical requirements for modern electronic and information systems like IoT, blockchain, and federated learning. This paper proposes P-CSNKS, a novel post-quotum collaborative signature scheme featuring a non-linear private key splitting technique.... More

Abstract: A simulation-based and deterministic approach was employed to assess the health-related fitness of upper primary school students through a Fuzzy Inference System (FIS) implemented in MATLAB. Standardized physical assessments were used to gather fitness data, which were then systematically categorized by gender and grade. While statistical metrics such as mean and standard deviation were extracted,... More

Abstract: An advanced low-power True Single Phase Clock (TSPC) flip-flop design leveraging a synergistic integration of three power-saving techniques: auto-gated clock gating, power gating, and redundant-transition suppression. The proposed architecture targets both dynamic and leakage power reduction in sequential circuits without sacrificing speed or timing integrity. Auto-gated clock gating dynamically disables the clock signal when input... More

Abstract: Magnetometers are widely used spacecraft attitude sensors due to their numerous advantages. Typically, fully observing a spacecraft’s attitude requires the use of at least two distinct sensor types. Thus, relying exclusively on a magnetometer introduces major challenges for estimation algorithms. The problem of spacecraft attitude estimation based on magnetometer measurements is generally nonlinear. Cubature Kalman... More

Abstract: In this work, we introduce m-FDPC, a mass-based variant of the Fast Density Peak Clustering (FDPC) algorithm, aimed at improving both performance and ease of use in unsupervised learning tasks. Traditional FDPC relies on Euclidean distance and requires careful parameter tuning and data normalization, which can significantly affect clustering outcomes—especially for heterogeneous or high-dimensional datasets.... More