Motions of a homopolar motor inside a conducting tube

We analyze the physics of a type of homopolar motor comprising an AA battery with two cylindrical neodymium magnets on each end that roll inside a metal cylindrical tube. The motion of the motor results from the interaction between the magnetic field of the magnets and the magnetic field created by the current inside the magnets. We develop a model to describe the dynamics of the system, including the calculation of the terminal velocity of the motor due to eddy currents.Comment: 4 pages, 1 figur

DNN-based Detectors for Massive MIMO Systems with Low-Resolution ADCs

Low-resolution analog-to-digital converters (ADCs) have been considered as a practical and promising solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. Unfortunately, low-resolution ADCs significantly distort the received signals, and thus make data detection much more challenging. In this paper, we develop a new deep neural network (DNN) framework for efficient and low-complexity data detection in low-resolution massive MIMO systems. Based on reformulated maximum likelihood detection problems, we propose two model-driven DNN-based detectors, namely OBMNet and FBMNet, for one-bit and few-bit massive MIMO systems, respectively. The proposed OBMNet and FBMNet detectors have unique and simple structures designed for low-resolution MIMO receivers and thus can be efficiently trained and implemented. Numerical results also show that OBMNet and FBMNet significantly outperform existing detection methods.Comment: 6 pages, 8 figures, submitted for publication. arXiv admin note: text overlap with arXiv:2008.0375

Linear and Deep Neural Network-based Receivers for Massive MIMO Systems with One-Bit ADCs

The use of one-bit analog-to-digital converters (ADCs) is a practical solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. However, the distortion caused by one-bit ADCs makes the data detection task much more challenging. In this paper, we propose a two-stage detection method for massive MIMO systems with one-bit ADCs. In the first stage, we propose several linear receivers based on the Bussgang decomposition, that show significant performance gain over existing linear receivers. Next, we reformulate the maximum-likelihood (ML) detection problem to address its non-robustness. Based on the reformulated ML detection problem, we propose a model-driven deep neural network-based (DNN-based) receiver, whose performance is comparable with an existing support vector machine-based receiver, albeit with a much lower computational complexity. A nearest-neighbor search method is then proposed for the second stage to refine the first stage solution. Unlike existing search methods that typically perform the search over a large candidate set, the proposed search method generates a limited number of most likely candidates and thus limits the search complexity. Numerical results confirm the low complexity, efficiency, and robustness of the proposed two-stage detection method.Comment: 12 pages, 10 figure

Optical Hall response of bilayer graphene: the manifestation of chiral hybridised states in broken mirror symmetry lattices

Understanding the mechanisms governing the optical activity of layered-stacked materials is crucial to the design of devices aimed at manipulating light at the nanoscale. Here, we show that both twisted and slid bilayer graphene are chiral systems that can deflect the polarization of linear polarized light. However, only twisted bilayer graphene supports circular dichroism. Our calculation scheme, which is based on the time-dependent Schr\"odinger equation, is particularly efficient for calculating the optical-conductivity tensor. Specifically, it allows us to show the chirality of hybridized states as the handedness-dependent bending of the trajectory of kicked Gaussian wave packets in bilayer lattices. We show that nonzero Hall conductivity is the result of the noncanceling manifestation of hybridized states in chiral lattices. We also demonstrate the continuous dependence of the conductivity tensor on the twist angle and the sliding vector.Comment: 24 pages, 6 figure

Context modeling of agile software and a contextbased approach to support virtual enterprises

In the practice of software development contexts have been only implicitly modeled and transformed in fixed part of software. The information about context is dispersed in objects across the application. Each context change leads to modification or new development of the software. The context modeling helps developer to separate context objects from contextdependent objects. It allows better reuse of analysis, design and implementation models, if the context of certain objects is changed. The context modeling is interesting and necessary, when the software should be agile - i.e. when the environment and the condition of the software could be changed permanently, e.g. in case of platform for virtual enterprises. The paper introduces a novel approach to support processes within generic platforms for virtual enterprises: the context-based approach. The main advantage of the approach lies in its generic capacity, which allows the users to define processes flexibly to support their own enterprises. In this paper, we discuss further the phenomenon of extra-context logic, its modeling and its application case. The information of extra-context logic provides not only the better understanding of application domain, but also can be used by a wizard to support the interaction of users working with multiple systems

ARtVista: Gateway To Empower Anyone Into Artist

Drawing is an art that enables people to express their imagination and emotions. However, individuals usually face challenges in drawing, especially when translating conceptual ideas into visually coherent representations and bridging the gap between mental visualization and practical execution. In response, we propose ARtVista - a novel system integrating AR and generative AI technologies. ARtVista not only recommends reference images aligned with users' abstract ideas and generates sketches for users to draw but also goes beyond, crafting vibrant paintings in various painting styles. ARtVista also offers users an alternative approach to create striking paintings by simulating the paint-by-number concept on reference images, empowering users to create visually stunning artwork devoid of the necessity for advanced drawing skills. We perform a pilot study and reveal positive feedback on its usability, emphasizing its effectiveness in visualizing user ideas and aiding the painting process to achieve stunning pictures without requiring advanced drawing skills. The source code will be available at https://github.com/htrvu/ARtVista.Comment: CHI 202

Первое сообщение об Auerbachia chakravartyi (Myxosporea: Bilvavulida) из желчного пузыря Megalaspis cordyla во Вьетнаме

В 2017 г. в Тонкинском заливе было исследовано 20 экз. Megalaspis cordyla. Морфологическими и молекулярно-биологическими методами было установлено наличие в желчном пузыре 7 из 20 рыб (35 %) спор Auerbachia chakravartyi Narasimhamurti, Kalavati, Anuradha, Padma, 1990. Это первая находка представителей рода Auerbachia в морских рыбах Вьетнама