Symbolic Generation Research Articles

An Automated Semi–symbolic State Equation Generation Method for Simulation of Power Electronic Systems

Computer-aided analysis is playing an important role in the design and control of power electronic systems. A discrete-state event-driven (DSED) framework with state-space modeling has been proposed recently for accurate and efficient off-line simulation. Nevertheless, automated equation formulation for arbitrary circuits is also required to develop the DSED framework toward general simulation software. However, the traditional state equation generation method is very time-consuming, especially for large-scale systems due to the variable topologies brought by switching events. In this article, an automated semi-symbolic state equation generation method is proposed. Based on the switching function modeling of basic switching legs, an explicit function from switching states to state equation matrices is given, which reduces the computational cost without sacrificing any accuracy. The operating and topological characteristics of power electronics systems are utilized for further optimization. The proposed method greatly increases the simulation efficiency of power electronic systems, especially for large-scale systems. Two cases of the 2 MW 4-port solid-state transformers with different system scales are simulated with the proposed method under the DSED framework. About 700-fold and 1200-fold acceleration is achieved compared with one fast-speed commercial software, where the proposed method contributes 50-fold and 110-fold acceleration in the two cases, respectively.

Learning Adversarial Transformer for Symbolic Music Generation.

Symbolic music generation is still an unsettled problem facing several challenges. The complete music score is a quite long note sequence, which consists of multiple tracks with recurring elements and their variants at various levels. The transformer model, benefiting from its self-attention has shown advantages in modeling long sequences. There have been some attempts at applying the transformer-based model to music generation. However, previous works train the model using the same strategy as the text generation task, despite the obvious differences between the pattern of texts and musics. These models cannot consistently produce music samples of high quality. In this article, we propose a novel adversarial transformer to generate transformer to generate music pieces with high musicality. The generative adversarial learning and the self-attention networks are combined creatively. The generation of long sequence is guided by the adversarial objectives, which provides a strong regularization to enforce the transformer to focus on learning of the global and local structures. Instead of adopting the time-consuming Monte Carlo (MC) search method that is commonly used in the existing sequence generative models, we propose an effective and convenient method to compute the reward for each generated step (REGS) for the long sequence. The discriminator is trained to optimize the elaborately designed global and local loss objective functions simultaneously, which enables the discriminator to give reliable REGS for the generator. The adversarial objective combined with the teacher forcing objective is used to guide the training of the generator. The proposed model can be used to generate single-track or multitrack music pieces. Experiments show that our model can generate long music pieces with the improved quality compared with the original music transformers.

Prospects of using the UFMC technology in 5G / IMT-2020 networks

<p>Subject of investigation. The article considers the technology of frequency multiplexing with universal filtering UFMC, planned to be introduced in the fifth generation of mobile communication networks, which allows maximizing the rate of decay of the side lobes of the multi frequency signal spectrum that cause out-of-band emissions. Method. As a method of investigation, a computational experiment was chosen. Main results. The parameters of the OFDM and UFMC signals were compared to determine the gain of the UFMC technology in the occupied bandwidth of the signal spectrum, as well as the number of arithmetic operations, required to generate a data symbol compared to the OFDM technology, on the basis of which, conclusions were made about the practical application of UFMC technology in networks mobile communication of the fifth generation. Practical significance. The conducted analysis can help to select the optimal number of sub-channels in groups in order to minimize the amount of computations during the UFMC symbol generation process.</p>

Quantum Spatial Modulation of Optical Channels: Quantum Boosting in Spectral Efficiency

Spatial modulation (SM) improves spectral efficiency (SE) by creating the constellation of active optical antenna indices. However, quantum properties of light are not exploited to improve the SE. In this letter, multi-plane diffraction (MPD) set-up creating exponentially increasing number of propagation paths for classical sources is exploited to introduce quantum spatial modulation (QSM). Exponential number of paths and quantum superposition-based classical symbol generation for transmitting simultaneous multiple classical symbols are exploited for linear and exponential quantum boosting of SM, respectively. It is theoretically modeled, numerically analyzed, and the challenges of joint design of source-channel coding and QSM are discussed.

Prospects of using the UFMC technology In 5g / Imt-2020 networks

<p><span>The article considers the technology of frequency multiplexing with universal filtering UFMC, planned to be introduced in the fifth generation of mobile communication networks, which allows maximizing the rate of decay of the side lobes of the multifrequency signal spectrum that cause out-of-band emissions. As a method of investigation, a computational experiment was chosen. The parameters of the OFDM and UFMC signals were compared to determine the gain of the UFMC technology in the occupied bandwidth of the signal spectrum, as well as the number of arithmetic operations, required to generate a data symbol compared to the OFDM technology, on the basis of which, conclusions were made about the practical application of UFMC technology in networks mobile communication of the fifth generation. The conducted analysis can help to select the optimal number of sub-channels in groups in order to minimize the amount of computations during the UFMC symbol generation process.</span></p>

Rethinking Architecture and Urban Form in the Context of Power Discourse: Case Study Nicosia, North Cyprus

This study investigates the symbolic attributes of power relations within the built environment of the walled city of Nicosia and contributes to the interpretation of generated meaning. The fundamental aim of this study is to provide a comprehensive explanation and description of how power as a socially constructed phenomenon aids in defining the language of the city and architecture. Studies of the built environment in relation to power discourse are a continuous process, and due to the subjectivity of interpretations, this study adopted the epistemological stance of constructivism. Based on deductive reasoning, this study hypothesises that power aids in defining the language and imageability of the city, and the results have verified the propositions. The case study of this research was diachronically analysed and focused on the socially-constructed symbolic meaning generation, within the framework of interpretivism. In order to analyse the city, a conceptual approach was developed. Two main approaches that support the research hypothesis were established: the language of the city; and imageability of the city. The imageability of the city was based on the five elements of the city, published in 1960. However, due to the context of this research, three of the elements that fully supported the research aim and objectives were selected, namely, landmark, district and path. The two main conceptual approaches were tied to power relations within the built environment based on the theoretical frameworks of: Markus; Dovey; and Njoh. In conclusion, the walled city of Nicosia exhibits symbols of ‘power over’ such as segregation, seduction, manipulation, and authority. The results have verified the proposition that power aids in defining the language and imageability of a city, thereby transforming the city and its inhabitants.

Massively Parallel Simulations of Binary Black Hole Intermediate-Mass-Ratio Inspirals

We present a highly-scalable framework that targets problems of interest to the numerical relativity and broader astrophysics communities. This framework combines a parallel octree-refined adaptive mesh with a wavelet adaptive multiresolution and a physics module to solve the Einstein equations of general relativity in the BSSN formulation. The goal of this work is to perform advanced, massively parallel numerical simulations of Intermediate Mass Ratio Inspirals (IMRIs) of binary black holes with mass ratios on the order of 100:1. These studies will be used to generate waveforms as used in LIGO data analysis and to calibrate semi-analytical approximate methods. Our framework consists of a distributed memory octree-based adaptive meshing framework in conjunction with a node-local code generator. The code generator makes our code portable across different architectures. The equations corresponding to the target application are written in symbolic notation and generators for different architectures can be added independent of the application. Additionally, this symbolic interface also makes our code extensible, and as such has been designed to easily accommodate many existing algorithms in astrophysics for plasma dynamics and radiation hydrodynamics. Our adaptive meshing algorithms and data-structures have been optimized for modern architectures with deep memory hierarchies. This enables our framework to have achieve excellent performance and scalability on modern leadership architectures. We demonstrate excellent weak scalability up to 131K cores on ORNL's Titan for binary mergers for mass ratios up to 100.

Teamwork management in Creative industries: factors influencing productivity

The 'experience' economy, characterizes by the growing needs for cultural identity and social empowerment, and aided by technologies of knowledge generation, information processing and communication of symbols, further reinforce this. The creative industries involve the concretization of an image, through whatever medium for some form of economic return. However, the nature of experience goods makes demand pattern unpredictable and production process difficult to control. The uncertainty of demand for the creative product, pose managerial and organizational challenges. The structure and staffing of creative projects are often temporary, as are capital investment. Success is dependent on the composition of projects teams with individuals and groups working in a highly interactive and adaptive fashioning of the product: Despite this fact, a great deal of research conducted in the area of group dynamics suggests that groups are often much less creative and productive than they are usually assumed. The important question of how to manage creative teams to achieve a high productivity with limited resources and time arises in innovation management both from the theoretical and practical points of view. There is still no clarity which factors affecting productivity of teamwork are more important than others. The study was aimed at the identification most important factors for the productivity of teamwork. The survey of 113 student creative teams in 8 counties (Lithuania, Poland, Canada, China, France, Italy, Russia, and Denmark) was performed. Based of the findings the hierarchy of the significance of the factors influencing the productivity of teamwork is established and described in the article.

An end-to-end framework for safe software development

It is largely recognized that the architectures of embedded systems are becoming more and more complex both at hardware and software levels. Despite the significant advances in the development tools, developing the software of such systems while ensuring their safety is still a difficult task. In this paper, we propose an end-to-end programming framework to ease the development of safe software systems. The programming framework, supported by a proper methodology and workflow, make it possible to design safe/secure software that implements functional requirements while respecting multiple non-functional requirements and mastering architectural complexity, time-to-market and cost. The programming framework is based on five concepts: (1) model-based system engineering: MBSE, (2) design-by-contract approach, (3) formal analysis of models based on symbolic execution, (4) code generation, and (5) static and dynamic code analysis. The effectiveness of the methodology has been demonstrated through multiple use-cases. The framework is realized using CEA LIST (http://www-list.cea.fr/en/) open-source development platforms: Papyrus, Frama-C, and UNISIM-VP. These platforms are results of many research and industrial projects such as FP7-SafeAdapt11SafeAdapt project was funded by the European Commission within the 7th Framework Program under the grant number “608945”., FUI-EQUITAS22EQUITAS project was funded by Bpifrance under call FUI-AAP16 with a contract number “F1312031-Q”., FP7-STANCE33STANCE project was also funded by the European Commission under the ICT theme of the 7th Framework Program with the grant agreement number “317753”., CATRENE-OpenES44OpenES project was funded under the CATRENE Program with the agreement number “CA703–2013”., FSN-SESAM Grids55SESAM Grids is a “Programme d'Investissement d'Avenir” project funded by “FSN-Briques Génériques du Logiciel Embarqué N°3” with contract number “O14830-67155”., and H2020-VESSEDIA66VESSEDIA project is funded by the European Commission under the SEC theme of the H2020 Framework Program with the grant agreement number “731453”..

Automated reasoning for attributed graph properties

Graphs are ubiquitous in computer science. Moreover, in various application fields, graphs are equipped with attributes to express additional information such as names of entities or weights of relationships. Due to the pervasiveness of attributed graphs, it is highly important to have the means to express properties on attributed graphs to strengthen modeling capabilities and to enable analysis. Firstly, we introduce a new logic of attributed graph properties, where the graph part and attribution part are neatly separated. The graph part is equivalent to first-order logic on graphs as introduced by Courcelle. It employs graph morphisms to allow the specification of complex graph patterns. The attribution part is added to this graph part by reverting to the symbolic approach to graph attribution, where attributes are represented symbolically by variables whose possible values are specified by a set of constraints making use of algebraic specifications. Secondly, we extend our refutationally complete tableau-based reasoning method as well as our symbolic model generation approach for graph properties to attributed graph properties. Due to the new logic mentioned above, neatly separating the graph and attribution parts, and the categorical constructions employed only on a more abstract level, we can leave the graph part of the algorithms seemingly unchanged. For the integration of the attribution part into the algorithms, we use an oracle, allowing for flexible adoption of different available SMT solvers in the actual implementation. Finally, our automated reasoning approach for attributed graph properties is implemented in the tool AutoGraph integrating in particular the SMT solver Z3 for the attribute part of the properties. We motivate and illustrate our work with a particular application scenario on graph database query validation.

MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment

Generating music has a few notable differences from generating images and videos. First, music is an art of time, necessitating a temporal model. Second, music is usually composed of multiple instruments/tracks with their own temporal dynamics, but collectively they unfold over time interdependently. Lastly, musical notes are often grouped into chords, arpeggios or melodies in polyphonic music, and thereby introducing a chronological ordering of notes is not naturally suitable. In this paper, we propose three models for symbolic multi-track music generation under the framework of generative adversarial networks (GANs). The three models, which differ in the underlying assumptions and accordingly the network architectures, are referred to as the jamming model, the composer model and the hybrid model. We trained the proposed models on a dataset of over one hundred thousand bars of rock music and applied them to generate piano-rolls of five tracks: bass, drums, guitar, piano and strings. A few intra-track and inter-track objective metrics are also proposed to evaluate the generative results, in addition to a subjective user study. We show that our models can generate coherent music of four bars right from scratch (i.e. without human inputs). We also extend our models to human-AI cooperative music generation: given a specific track composed by human, we can generate four additional tracks to accompany it. All code, the dataset and the rendered audio samples are available at https://salu133445.github.io/musegan/.

How to differentiate collective variables in free energy codes: Computer-algebra code generation and automatic differentiation

The proper choice of collective variables (CVs) is central to biased-sampling free energy reconstruction methods in molecular dynamics simulations. The PLUMED 2 library, for instance, provides several sophisticated CV choices, implemented in a C++ framework; however, developing new CVs is still time consuming due to the need to provide code for the analytical derivatives of all functions with respect to atomic coordinates. We present two solutions to this problem, namely (a) symbolic differentiation and code generation, and (b) automatic code differentiation, in both cases leveraging open-source libraries (SymPy and Stan Math, respectively). The two approaches are demonstrated and discussed in detail implementing a realistic example CV, the local radius of curvature of a polymer. Users may use the code as a template to streamline the implementation of their own CVs using high-level constructs and automatic gradient computation. Program summaryProgram Title: Practical approaches to the differentiation of collective variables in free energy codes: computer-algebra code generation and automatic differentiationProgram Files doi:http://dx.doi.org/10.17632/r4r67bvkdn.1Licensing provisions: GNU Lesser General Public License Version 3 (LGPL-3)Programming languages: C++, PythonNature of problem: The C++ implementation of collective variables (CVs, functions of atomic coordinates to be used in biased sampling applications) in biasing libraries for atomistic simulations, such as PLUMED [1], requires computation of both the variable and its gradient with respect to the atomic coordinates; coding and testing the analytical derivatives complicate the implementation of new CVs.Solution method: The paper shows two approaches to automate the computation of CV gradients, namely, symbolic differentiation with code generation and automatic code differentiation, demonstrating their implementation entirely with open-source software (respectively, SymPy and the Stan Math Library).Additional comments: The paper’s accompanying code serves as an example and template for the methods described in the paper; it is distributed as the two modules curvature_codegen and curvature_autodiff integrated in PLUMED 2’s source tree; the latest version is available at https://github.com/tonigi/plumed2-automatic-gradients .[1] Tribello GA, Bonomi M, Branduardi D, Camilloni C, Bussi G. PLUMED 2: New feathers for an old bird. Computer Physics Communications. 2014 Feb;185(2):604-13.

Symbolic consumption and Generation Y consumers: evidence from Thailand

PurposeThe purpose of this paper is to investigate Generation Y consumers’ symbolic consumption on brand attitude and purchase intention toward global brands.Design/methodology/approachA conceptual model has been developed to illustrate the proposed relationships among the related variables. Data from a total of 300 usable surveys were collected from Thai Generation Y consumers. The proposed hypotheses were tested using structural equation modeling analyses.FindingsThe study found that Generation Y consumers’ symbolic consumption has a significant and positive effect on brand attitude and purchase intention.Research limitations/implicationsTime and resources limitation did not allow to study the larger sample. Future research should include more product categories and more global brands. Sample can be extended to consumers in ASEAN countries to provide more comprehensive insights into consumer perceptions and brand behaviors toward global brands.Practical implicationsThe findings suggest that symbolic consumption is a key motivation to increase purchase intention when developing marketing strategies for the Generation Y consumer.Originality/valueThis study has contributions to symbolic consumption and Generation Y literature combining several important dimensions into a structural model, and examines the relationships among these dimensions.

Ultra-Wideband Joint Spatial Coding for Secure Communication and High-Resolution Imaging

This paper introduces new techniques for ultra-wideband (UWB) joint spatial coding in order to establish a secure line-of-sight wireless communication link, performing precision localization of point objects, and generating high-resolution images from complex scenes. For the proposed technique, symbol generation and coding are jointly performed by multiple widely spaced transmitters. This method enables the transmission of directionally modulated signals that can only be decoded at a desired angle, resulting in a secure communication link. It is also shown that joint spatial coding by multiple transmitters that are synchronized with each other enables the precise localization of multiple point objects and allows high-resolution 3-D imaging of distributed objects. The technique is demonstrated experimentally in the frequency range 3–10 GHz by generating and detecting UWB pulses.

Symbolic Generation of Painlevé Equations

A symbolic generation of Painleve equations is developed on the basis of the antiquantization of deformed Heun-class equations. The corresponding CAS Maple package is presented, along with examples of its use. The particular cases of reduced confluent Heun equations are discussed.

Antiquantization of deformed Heun class equations as a tool for symbolic generation of Painlevé equations

We have used antiquantization of deformed Heun class equations for programming the generation of Painlevé equations with the CAS Maple.

Fractal generator for efficient production of random planar patterns and symbols in digital mapping

In digital cartography, the automatic generation of random planar patterns and symbols is still an ongoing challenge. Those patterns and symbols of randomness have randomly variated configurations and boundaries, and their generating algorithms are constrained by the shape features, cartographic standards and many other conditions. The fractal geometry offers favorable solutions to simulate random boundaries and patterns. In the work presented in this paper, we used both fractal theory and random Iterated Function Systems (IFS) to develop a method for the automatic generation of random planar patterns and symbols. The marshland and the trough cross-bedding patterns were used as two case studies for the implementation of the method. We first analyzed the morphological characteristics of those two planar patterns. Then we designed algorithms and implementation schemes addressing the features of each pattern. Finally, we ran the algorithms to generate the patterns and symbols, and compared them with the requirements of a few digital cartographic standards. The method presented in this paper has already been deployed in a digital mapping system for practical uses. The flexibility of the method also allows it to be reused and/or adapted in various software platforms for digital mapping.

Symbolic Arrays in Symbolic PathFinder

Symbolic Execution is a program analysis technique used to increase software reliability. Modern software often manipulate complex data structures, many of which being similar to arrays. We present a novel approach and implementation in Symbolic PathFinder for handling symbolic arrays in Java. It enables analyzing a broader class of programs that manipulates arrays. We also extend the Symbolic Pathfinder testcase generation to support numeric arrays.

PACE: Redundancy Engineering in RLNC for Low-Latency Communication

Random linear network coding (RLNC) is attractive for data transfer as well as data storage and retrieval in complex and unreliable settings. The existing systematic RLNC approach first sends all source symbols in a generation without encoding followed by the coded redundant packets at the tail of the generation. This systematic tail RLNC achieves low delay when packet drops are rare; however, recovery of any dropped source symbol requires to wait for the coded packets at the end of the generation. We propose and evaluate a novel PACE RLNC approach that paces the transmissions of coded redundant packets throughout the generation of source symbols. The paced coded packets enable the recovery of dropped source symbols without waiting for the tail end of the generation. More specifically, we propose PACE-Uniform, which uniformly intersperses individual coded packets throughout the generation, and PACE-Burst, which intersperses bursts of code packets. Our extensive simulation evaluations indicate that PACE-Uniform significantly reduces the mean source symbol delay compared to tail RLNC, while achieving nearly the same loss probability. We also demonstrate that PACE-Burst generalizes the concept of pacing the redundant packet transmissions and can be flexibly tuned between PACE-Uniform and the conventional tail RLNC by controlling the number of coded packets in a burst.

A Study on Overvoltage Distribution Across the High Voltage Winding of an Electric Power Transformer

The main objective of this paper is to represent effects of overvoltage on a transformer winding by analysis and modelling with special attention given to the voltage distribution across the winding. The authors have considered both approaches in modelling the winding: windings with distributed electrical parameters, and secondly disk coils with concentrated parameters. All known models are assembled in a general model based upon distributed parameters, while the excitation voltages display sinusoidal variation in time (commutation) or step. Both induced and commutation voltages, applied across the transformer winding, will generate free oscillations which are analyzed further on. According to the model, the transformer’s windings are divided in several disk coils with concentrated known parameters. This results in a complete electrical network used for simulations. All simulations have been performed using the software package SYSEG (SYmbolic State Equation Generation). Using SYSEG package, from the state equations assembled in terms of the disk coils voltages, one can obtain the overvoltage across the transformer winding as function of time. If the frequency of the commutation voltage and the frequency of the free oscillations are in close range, then the voltage across the disk coils shows a non-uniform distribution. An important aspect of this paper is accounting for asymmetry of the transformer by modelling the reinforced insulation of the first turns of the disk coils of the transformer’s high voltage winding. This affects the value of the inter-turn capacitance of these coils, and is an aspect which is treated in our simulations.