Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

Energy-dependent relative charge transfer cross sections of Cs+ + Rb(5s, 5p)

Magneto optical trap recoil ion momentum spectroscopy is used to measure energy-dependent charge exchange cross sections in the Cs+ + Rb(5s, 5p) system over a range of projectile energies from 3.2 to 6.4 keV. The measurements are kinematically complete and yield cross sections that are differential in collision energy, scattering angle, and initial and final states

The brezis-ekeland-nayroles minimization principle with mixed finite element method for elastoplastic dynamic problems

We propose a modification of the Hamiltonian formalism which can be used for dissipative systems, the Brezis-Ekeland-Nayroles principle. The formalism is specialized to the standard plasticity in small strains and dynamics. We apply it to solve the classical problem of a thin tube in plane strain subjected to an internal pressure. The continuum is discretized with mixed finite elements

Resolution in Linguistic Propositional Logic based on Linear Symmetrical Hedge Algebra

The paper introduces a propositional linguistic logic that serves as the basis for automated uncertain reasoning with linguistic information. First, we build a linguistic logic system with truth value domain based on a linear symmetrical hedge algebra. Then, we consider G\"{o}del's t-norm and t-conorm to define the logical connectives for our logic. Next, we present a resolution inference rule, in which two clauses having contradictory linguistic truth values can be resolved. We also give the concept of reliability in order to capture the approximative nature of the resolution inference rule. Finally, we propose a resolution procedure with the maximal reliability.Comment: KSE 2013 conferenc

Negative Magnetoresistance in the Nearest-neighbor Hopping Conduction

We propose a size effect which leads to the negative magnetoresistance in granular metal-insulator materials in which the hopping between two nearest neighbor clusters is the main transport mechanism. We show that the hopping probability increases with magnetic field. This is originated from the level crossing in a few-electron cluster. Thus, the overlap of electronic states of two neighboring clusters increases, and the negative magnetoresistance is resulted.Comment: Latex file, no figur

Serially concatenated unity-rate codes improve quantum codes without coding-rate reduction

Inspired by the astounding performance of the unity rate code (URC) aided classical coding and detection schemes, we conceive a quantum URC (QURC) for assisting the design of concatenated quantum codes. Unfortunately, a QURC cannot be simultaneously recursive as well as non-catastrophic. However, we demonstrate that, despite being non-recursive, our proposed QURC yields efficient concatenated codes, which exhibit a low error rate and a beneficial interleaver gain, provided that the coding scheme is carefully designed with the aid of EXtrinsic Information Transfer (EXIT) charts

Quantum-aided multi-user transmission in non-orthogonal multiple access systems

With the research on implementing a universal quantum computer being under the technological spotlight, new possibilities appear for their employment in wireless communications systems for reducing their complexity and improving their performance. In this treatise, we consider the downlink of a rank-deficient, multi-user system and we propose the discrete-valued and continuous-valued Quantum-assisted Particle Swarm Optimization (QPSO) algorithms for performing Vector Perturbation (VP) precoding, as well as for lowering the required transmission power at the Base Station (BS), while minimizing the expected average Bit Error Ratio (BER) at the mobile terminals. We use the Minimum BER (MBER) criterion. We show that the novel quantum-assisted precoding methodology results in an enhanced BER performance, when compared to that of a classical methodology employing the PSO algorithm, while requiring the same computational complexity in the challenging rank-deficient scenarios, where the number of transmit antenna elements at the BS is lower than the number of users. Moreover, when there is limited Channel State Information (CSI) feedback from the users to the BS, due to the necessary quantization of the channel states, the proposed quantum-assisted precoder outperforms the classical precoder