Cloud-RAN is a recent architecture for mobile networks where the processing units are located indistant data centers while, until now, they were attached to antennas. The main challenge, to fulfillprotocol constraints, is to guarantee low latency for the periodic messages sent from each antenna...

The lattice reduction algorithm (LRA) takes as inputs a basis of lattice and outputs a relatively short vector up to Hermite factor multiplication. The worst case of Hermite factor of known LRAs has an exponential size to the rank of the given lattice. In this paper, we present a sublattice...

Generating r-combinations of the set N={1, 2, …, n} in lexicographical order has been an interest for researchers in the field of computer science and combinatorial optimization. This study provides three new algorithms for generating these r-combinations in lexicographical order for the given...

Prediction of nonlinear dynamic process remains a challenging and active research topic. In this paper, adaptive nonlinear prediction based on a Hammerstein-modeling approach is investigated. Motivated by the desire to represent the best fit to the nonlinear dynamical plant with the Hammerstein...

Generalized eigenvalue problem (GEP) plays a significant role in signal processing and machine learning. This paper proposes a consensus-based distributed algorithm for GEP in multi-agent systems, where data samples are distributively stored across agents. The distributed GEP is reformulated as...

District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. However, not only the correlation between multiple optimization objectives, but also the time-varying energy demand is ignored when establishing and solving the...

AbstractSoil moisture (SM) of maize has an extremely important impact on the growth and development of maize. Therefore, predicting the SM of maize will become extremely important, guiding the management of agricultural irrigation and water resources. This paper, therefore, proposes a new hybrid...

This research proposed an optimization method using a solution technique based on two well-known techniques, differential evolution and particle swarm optimization, to tackle a multi-visit and multi-period workforce scheduling and routing problem in field service operation of a sugarcane mill...

While deep learning algorithms demonstrate a great potential in scientific computing, its application to multi-scale problems remains to be a big challenge. This is manifested by the ``frequency principle" that neural networks tend to learn low frequency components first. Novel architectures...

Wearable sensor based human activity recognition (HAR) has a broad range of applications in healthcare, fitness, smart home, and surveillance. In spite of the substantial amount of computational research on HAR, the open challenges in multi-sensor based activity recognition including complex...