bluuebunny/crossref_metadata_2025 huggingface dataset:
Competing for Resources: Estimating Adversary Strategy for Effective Plan Generation
Authors: Chrpa Lukáš , Rytíř Pavel , Horčík Rostislav , Edelkamp Stefan
Published: July 2022

Effective decision making while competing for limited resources in adversarial environments is important for many real-world applications (e.g. two Taxi companies competing for customers). Decision-making techniques such as Automated planning have to take into account possible actions of adversary (or competing) agents. That said, the agent should know what the competitor will likely do and then generate its plan accordingly. In this paper we propose a novel approach for estimating strategies of the adversary (or the competitor), sampling its actions that might hinder agent's goals by interfering with the agent's actions. The estimated competitor strategies are used in plan generation such that agent's actions have to be applied prior to the ones of the competitor, whose estimated times dictate the deadlines. We empirically evaluate our approach leveraging sampling of competitor's actions by comparing it to the naive approach optimising the make-span (not taking the competing agent into account at all) and to Nash Equilibrium (mixed) strategies.
Inconsistent Planning: When in Doubt, Toss a Coin!
Authors: Dementiev Yuriy , Fomin Fedor , Ignatiev Artur
Published: July 2022

One of the most widespread human behavioral biases is the present bias -- the tendency to overestimate current costs by a bias factor. Kleinberg and Oren (2014) introduced an elegant graph-theoretical model of inconsistent planning capturing the behavior of a present-biased agent accomplishing a set of actions. The essential measure of the system introduced by Kleinberg and Oren is the cost of irrationality -- the ratio of the total cost of the actions performed by the present-biased agent to the optimal cost. This measure is vital for a task designer to estimate the aftermaths of human behavior related to time-inconsistent planning, including procrastination and abandonment.
As we prove in this paper, the cost of irrationality is highly susceptible to the agent's choices when faced with a few possible actions of equal estimated costs. To address this issue, we propose a modification of Kleinberg-Oren's model of inconsistent planning. In our model, when an agent selects from several options of minimum prescribed cost, he uses a randomized procedure. We explore the algorithmic complexity of computing and estimating the cost of irrationality in the new model.
Robustification of Online Graph Exploration Methods
Authors: Eberle Franziska , Lindermayr Alexander , Megow Nicole , Nölke Lukas , Schlöter Jens
Published: July 2022

Exploring unknown environments is a fundamental task in many domains, e.g., robot navigation, network security, and internet search. We initiate the study of a learning-augmented variant of the classical, notoriously hard online graph exploration problem by adding access to machine-learned predictions. We propose an algorithm that naturally integrates predictions into the well-known Nearest Neighbor (NN) algorithm and significantly outperforms any known online algorithm if the prediction is of high accuracy while maintaining good guarantees when the prediction is of poor quality. We provide theoretical worst-case bounds that gracefully degrade with the prediction error, and we complement them by computational experiments that confirm our results. Further, we extend our concept to a general framework to robustify algorithms. By interpolating carefully between a given algorithm and NN, we prove new performance bounds that leverage the individual good performance on particular inputs while establishing robustness to arbitrary inputs.
Homomorphisms of Lifted Planning Tasks: The Case for Delete-Free Relaxation Heuristics
Authors: Horčík Rostislav , Fišer Daniel , Torralba Álvaro
Published: July 2022

Classical planning tasks are modelled in PDDL which is a schematic language based on first-order logic. Most of the current planners turn this lifted representation into a propositional one via a grounding process. However, grounding may cause an exponential blowup. Therefore it is important to investigate methods for searching for plans on the lifted level. To build a lifted state-based planner, it is necessary to invent lifted heuristics. We introduce maps between PDDL tasks preserving plans allowing to transform a PDDL task into a smaller one. We propose a novel method for computing lifted (admissible) delete-free relaxed heuristics via grounding of the smaller task and computing the (admissible) delete-free relaxed heuristics there. This allows us to transfer the knowledge about relaxed heuristics from the grounded level to the lifted level.
Bounding Quality in Diverse Planning
Authors: Katz Michael , Sohrabi Shirin , Udrea Octavian
Published: July 2022

Diverse planning is an important problem in automated planning with many real world applications. Recently, diverse planning has seen renewed interest, with work that defines a taxonomy of computational problems with respect to both plan quality and solution diversity. However, despite the recent advances in diverse planning, the variety of approaches and the number of available planners are still quite limited, even nonexistent for several computational problems. In this work, we aim to extend the portfolio of planners for various computational problems in diverse planning. To that end, we introduce a novel approach to finding solutions for three computational problems within diverse planning and present planners for these three problems. For one of these problems, our approach is the first one that is able to provide solutions to the problem. For another, we show that top-k and top quality planners can provide, albeit naive, solutions to the problem and we extend these planners to improve the diversity of the solution. Finally, for the third problem, we show that some existing diverse planners already provide solutions to that problem. We suggest another approach and empirically show it to compare favorably with these existing planners.
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability Using Tree Search and Graph Neural Networks
Authors: Osanlou Kevin , Frank Jeremy , Bursuc Andrei , Cazenave Tristan , Jacopin Eric , Guettier Christophe , Benton J.
Published: July 2022

Scheduling under uncertainty is an area of interest in artificial intelligence. We study the problem of Dynamic Controllability (DC) of Disjunctive Temporal Networks with Uncertainty (DTNU), which seeks a reactive scheduling strategy to satisfy temporal constraints in response to uncontrollable action durations. We introduce new semantics for reactive scheduling: Time-based Dynamic Controllability (TDC) and a restricted subset of TDC, R-TDC. We present a tree search approach to determine whether or not a DTNU is R-TDC. Moreover, we leverage the learning capability of a Graph Neural Network (GNN) as a heuristic for tree search guidance. Finally, we conduct experiments on a known benchmark on which we show R-TDC to retain significant completeness with regard to DC, while being faster to prove. This results in the tree search processing fifty percent more DTNU problems in R-TDC than the state-of-the-art DC solver does in DC with the same time budget. We also observe that GNN tree search guidance leads to substantial performance gains on benchmarks of more complex DTNUs, with up to eleven times more problems solved than the baseline tree search.
Deciding Unsolvability in Temporal Planning under Action Non-Self-Overlapping
Authors: Panjkovic Stefan , Micheli Andrea , Cimatti Alessandro
Published: July 2022

The field of Temporal Planning (TP) is receiving increasing interest for its many real-world applications. Most of the literature focuses on the TP problem of finding a plan, with algorithms that are not guaranteed to terminate when the problem admits no solution. In this paper, we present sound and complete decision procedures that address the dual problem of proving that no plan exists, which has important applications in oversubscription, model validation and optimization. We focus on the expressive and practically relevant semantics of action non-self-overlapping, recently proved to be PSPACE-complete. For this subclass, we propose two approaches: a reduction of the planning problem to model-checking of Timed Transition Systems, and a heuristic-search algorithm where temporal constraints are represented by Difference Bound Matrices. We implemented the approaches, and carried out an experimental evaluation against other state-of-the-art TP tools. On benchmarks that admit no plans, both approaches dramatically outperform the other planners, while the heuristic-search algorithm remains competitive on solvable benchmarks.
A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs
Authors: Patton Noah , Jeong Jihwan , Gimelfarb Mike , Sanner Scott
Published: July 2022

Recent advances in efficient planning in deterministic or stochastic high-dimensional domains with continuous action spaces leverage backpropagation through a model of the environment to directly optimize action sequences. However, existing methods typically do not take risk into account when optimizing in stochastic domains, which can be incorporated efficiently in MDPs by optimizing a nonlinear utility function of the return distribution. We bridge this gap by introducing Risk-Aware Planning using PyTorch (RAPTOR), a novel unified framework for risk-sensitive planning through end-to-end optimization of commonly-studied risk-sensitive utility functions such as entropic utility, mean-variance optimization and CVaR. A key technical difficulty of our approach is that direct optimization of general risk-sensitive utility functions by backpropagation is impossible due to the presence of environment stochasticity. The novelty of RAPTOR lies in leveraging reparameterization of the state distribution, leading to a unique distributional perspective of end-to-end planning where the return distribution is utilized for sampling as well as optimizing risk-aware objectives by backpropagation in a unified framework. We evaluate and compare RAPTOR on three highly stochastic MDPs, including nonlinear navigation, HVAC control, and linear reservoir control, demonstrating the ability of RAPTOR to manage risk in complex continuous domains according to different notions of risk-sensitive utility.
Classical Planning with Avoid Conditions
Authors: Steinmetz Marcel , Hoffmann Jörg , Kovtunova Alisa , Borgwardt Stefan
Published: July 2022

It is often natural in planning to specify conditions that should be avoided, characterizing dangerous or highly undesirable behavior. PDDL3 supports this with temporal-logic state trajectory constraints. Here we focus on the simpler case where the constraint is a non-temporal formula ? - the avoid condition - that must be false throughout the plan. We design techniques tackling such avoid conditions effectively. We show how to learn from search experience which states necessarily lead into ?, and we show how to tailor abstractions to recognize that avoiding ? will not be possible starting from a given state. We run a large-scale experiment, comparing our techniques against compilation methods and against simple state pruning using ?. The results show that our techniques are often superior.
MAPDP: Cooperative Multi-Agent Reinforcement Learning to Solve Pickup and Delivery Problems
Authors: Zong Zefang , Zheng Meng , Li Yong , Jin Depeng
Published: July 2022

Cooperative Pickup and Delivery Problem (PDP), as a variant of the typical Vehicle Routing Problems (VRP), is an important formulation in many real-world applications, such as on-demand delivery, industrial warehousing, etc. It is of great importance to efficiently provide high-quality solutions of cooperative PDP. However, it is not trivial to provide effective solutions directly due to two major challenges: 1) the structural dependency between pickup and delivery pairs require explicit modeling and representation. 2) the cooperation between different vehicles is highly related to the solution exploration and difficult to model. In this paper, we propose a novel multi-agent reinforcement learning based framework to solve the cooperative PDP (MAPDP). First, we design a paired context embedding to well measure the dependency of different nodes considering their structural limits. Second, we utilize cooperative multi-agent decoders to leverage the decision dependence among different vehicle agents based on a special communication embedding. Third, we design a novel cooperative A2C algorithm to train the integrated model. We conduct extensive experiments on a randomly generated dataset and a real-world dataset. Experiments result shown that the proposed MAPDP outperform all other baselines by at least 1.64\% in all settings, and shows significant computation speed during solution inference.
Entropy Estimation via Normalizing Flow
Authors: Ao Ziqiao , Li Jinglai
Published: July 2022

Entropy estimation is an important problem in information theory and statistical science. Many popular entropy estimators suffer from fast growing estimation bias with respect to dimensionality, rendering them unsuitable for high dimensional problems. In this work we propose a transformbased method for high dimensional entropy estimation, which consists of the following two main ingredients. First by modifying the k-NN based entropy estimator, we propose a new estimator which enjoys small estimation bias for samples that are close to a uniform distribution. Second we design a normalizing flow based mapping that pushes samples toward a uniform distribution, and the relation between the entropy of the original samples and the transformed ones is also derived. As a result the entropy of a given set of samples is estimated by first transforming them toward a uniform distribution and then applying the proposed estimator to the transformed samples. Numerical experiments demonstrate the effectiveness of the method for high dimensional entropy estimation problems.
Inference and Learning with Model Uncertainty in Probabilistic Logic Programs
Authors: Verreet Victor , Derkinderen Vincent , Martires Pedro Zuidberg Dos , Raedt Luc De
Published: July 2022

An issue that has so far received only limited attention in probabilistic logic programming (PLP) is the modelling of so-called epistemic uncertainty, the uncertainty about the model itself. Accurately quantifying this model uncertainty is paramount to robust inference, learning and ultimately decision making. We introduce BetaProbLog, a PLP language that can model epistemic uncertainty. BetaProbLog has sound semantics, an effective inference algorithm that combines Monte Carlo techniques with knowledge compilation, and a parameter learning algorithm. We empirically outperform state-of-the-art methods on probabilistic inference tasks in second-order Bayesian networks, digit classification and discriminative learning in the presence of epistemic uncertainty.
Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions
Authors: Wang Yuanhong , Bremen Timothy van , Wang Yuyi , Kuželka Ondřej
Published: July 2022

Given a first-order sentence ? and a domain size n, how can one sample a model of ? on the domain {1, . . . , n} efficiently as n scales? We consider two variants of this problem: the uniform sampling regime, in which the goal is to sample a model uniformly at random, and the symmetric weighted sampling regime, in which models are weighted according to the number of groundings of each predicate appearing in them. Solutions to this problem have applications to the scalable generation of combinatorial structures, as well as sampling in several statistical-relational models such as Markov logic networks and probabilistic logic programs. In this paper, we identify certain classes of sentences that are domain-liftable under sampling, in the sense that they admit a sampling algorithm that runs in time polynomial in n. In particular, we prove that every sentence of the form ∀x∀y: ?(x, y) for some quantifier-free formula ?(x,y) is domain-liftable under sampling. We then further show that this result continues to hold in the presence of one or more cardinality constraints as well as a single tree axiom constraint.
NukCP: An Improved Local Search Algorithm for Maximum k-Club Problem
Authors: Chen Jiejiang , Wang Yiyuan , Cai Shaowei , Yin Minghao , Zhou Yupeng , Wu Jieyu
Published: July 2022

The maximum k-club problem (MkCP) is an important clique relaxation problem with wide applications. Previous MkCP algorithms only work on small-scale instances and are not applicable for large-scale instances. For solving instances with different scales, this paper develops an efficient local search algorithm named NukCP for the MkCP which mainly includes two novel ideas. First, we propose a dynamic reduction strategy, which makes a good balance between the time efficiency and the precision effectiveness of the upper bound calculation. Second, a stratified threshold configuration checking strategy is designed by giving different priorities for the neighborhood in the different levels. Experiments on a broad range of different scale instances show that NukCP significantly outperforms the state-of-the-art MkCP algorithms on most instances.
New Results in Bounded-Suboptimal Search
Authors: Fickert Maximilian , Gu Tianyi , Ruml Wheeler
Published: July 2022

In bounded-suboptimal heuristic search, one attempts to find a solution that costs no more than a prespecified factor of optimal as quickly as possible. This is an important setting, as it admits faster-than-optimal solving while retaining some control over solution cost. In this paper, we investigate several new algorithms for bounded-suboptimal search, including novel variants of EES and DPS, the two most prominent previous proposals, and methods inspired by recent work in bounded-cost search that leverages uncertainty estimates of the heuristic. We perform what is, to our knowledge, the most comprehensive empirical comparison of bounded-suboptimal search algorithms to date, including both search and planning benchmarks, and we find that one of the new algorithms, a simple alternating queue scheme, significantly outperforms previous work.
PRISM: A Rich Class of Parameterized Submodular Information Measures for Guided Data Subset Selection
Authors: Kothawade Suraj , Kaushal Vishal , Ramakrishnan Ganesh , Bilmes Jeff , Iyer Rishabh
Published: July 2022

With ever-increasing dataset sizes, subset selection techniques are becoming increasingly important for a plethora of tasks. It is often necessary to guide the subset selection to achieve certain desiderata, which includes focusing or targeting certain data points, while avoiding others. Examples of such problems include: i)targeted learning, where the goal is to find subsets with rare classes or rare attributes on which the model is under performing, and ii)guided summarization, where data (e.g., image collection, text, document or video) is summarized for quicker human consumption with specific additional user intent. Motivated by such applications, we present PRISM, a rich class of PaRameterIzed Submodular information Measures. Through novel functions and their parameterizations, PRISM offers a variety of modeling capabilities that enable a trade-off between desired qualities of a subset like diversity or representation and similarity/dissimilarity with a set of data points. We demonstrate how PRISM can be applied to the two real-world problems mentioned above, which require guided subset selection. In doing so, we show that PRISM interestingly generalizes some past work, therein reinforcing its broad utility. Through extensive experiments on diverse datasets, we demonstrate the superiority of PRISM over the state-of-the-art in targeted learning and in guided image-collection summarization. PRISM is available as a part of the SUBMODLIB (https://github.com/decile-team/submodlib) and TRUST (https://github.com/decile-team/trust) toolkits.
Search Strategies for Topological Network Optimization
Authors: Moffitt Michael D.
Published: July 2022

We consider an application of combinatorial search to the optimization of topologies in series-parallel networks. We propose a recursive search over the space of decomposition trees, in which partial solutions are obtained by exploring k-way partitionings of expandable nodes. We present two complementary pruning techniques that bound the value of intermediate solutions from above and below, applying monotonic operations to the contents of unresolved leaves. We also develop a means to exploit the convexity of our objective function, so as to prevent the redundant recomputation of subcircuit configurations. Finally, we evaluate our approach on a parameterized benchmark suite of electrical circuits, demonstrating over an order of magnitude improvement in performance as compared to a baseline implementation.
Subset Approximation of Pareto Regions with Bi-objective A*
Authors: Rivera Nicolás , Baier Jorge A. , Hernández Carlos
Published: July 2022

In bi-objective search, we are given a graph in which each directed arc is associated with a pair of non-negative weights, and the objective is to find the Pareto-optimal solution set. Unfortunately, in many practical settings, this set is too large, and therefore its computation is very time-consuming. In addition, even though bi-objective search algorithms generate the Pareto set incrementally, they do so exhaustively. This means that early during search the solution set covers is not diverse, being concentrated in a small region of the solution set. To address this issue, we present a new approach to subset approximation of the solution set, that can be used as the basis for an anytime bi-objective search algorithm. Our approach transforms the given task into a target bi-objective search task using two real parameters. For each particular parameter setting, the solutions to the target task is a subset of the solution set of the original task. Depending on the parameters used, the solution set of the target task may be computed very quickly. This
allows us to obtain, in challenging road map benchmarks, a rich variety of solutions in times that may be orders of magnitude smaller than the time needed to compute the solution set. We show that by running the algorithm with an appropriate sequence of parameters, we obtain a growing sequence of solutions that converges to the full solution set. We prove that our approach is correct and that Bi-Objective A* prunes at least as many nodes when run over the target task.
Optimize What You Evaluate With: Search Result Diversification Based on Metric Optimization
Authors: Yu Hai-Tao
Published: July 2022

Most of the existing methods for search result diversification (SRD) appeal to the greedy strategy for generating diversified results, which is formulated as a sequential process of selecting documents one-by-one, and the locally optimal choice is made at each round. Unfortunately, this strategy suffers from the following shortcomings: (1) Such a one-by-one selection process is rather time-consuming for both training and inference. (2) It works well on the premise that the preceding choices are optimal or close to the optimal solution. (3) The mismatch between the objective function used in training and the final evaluation measure used in testing has not been taken into account. We propose a novel framework through direct metric optimization for SRD (referred to as MO4SRD) based on the score-and-sort strategy. Specifically, we represent the diversity score of each document that determines its rank position based on a probability distribution. These distributions over scores naturally give rise to expectations over rank positions. Armed with this advantage, we can get the differentiable variants of the widely used diversity metrics. Thanks to this, we are able to directly optimize the evaluation measure used in testing. Moreover, we have devised a novel probabilistic neural scoring function. It jointly scores candidate documents by taking into account both cross-document interaction and permutation equivariance, which makes it possible to generate a diversified ranking via a simple sorting. The experimental results on benchmark collections show that the proposed method achieves significantly improved performance over the state-of-the-art results.
Effects of phase-change material on performance of cement mortar at varying temperatures
Authors: Palampalli P. , Raj A. , Mini K. M.
Published: July 2022

Recent thermal effect reports have shown a widespread increase in temperature associated with global warming. The need to preserve building interiors at a steady, comfortable temperature has become a major task for engineers. This has resulted in the development of phase-change materials (PCMs), which can be positioned in the interior of building components to absorb heat from the surroundings. The main aim of this study was to examine the physical, mechanical and thermal properties of cement mortar incorporating encapsulated PCMs at different temperature phases. The materials required for the PCMs and encapsulation were selected based on economy, availability and temperature tolerance. The results were compared with a control specimen and improved behaviour in thermal resistance was noted. The compressive strength was reduced with an increased percentage of PCM; the reduction in strength could be compensated with the addition of micro-silica. Temperature phases did not have much influence on the strength and durability properties. Based on thermal resistance and strength properties, 5% PCM incorporation showed the best performance. An analytical model was developed using Comsol Multiphysics software to assess the thermal comfort in a building made of PCM-incorporated mortar block walls in comparison with conventional brick walls.
Modelling of a Heterogeneous Corpus: The Example of Chapbook Literature
Authors: Leblanc Elina
Published: July 2022

This article proposes an analysis of Spanish chapbook literature from the digital perspective. It provides a systematic study of the metadata and services selected by seventeen digital libraries to model their collections.In the first part, we propose an overview of those libraries. Their great variety reflects the heterogeneity of this popular literature, which is at the margin of studies on printed productions, and escapes the classifications traditionally used for books. In the second part, we describe four different strategies used by digital libraries to model this type of content, focusing either 1) on the document as an archive to be preserved, 2) on the document as the result of an editorial process, 3) on the text, or 4) on the illustrations. Our objective is thus to outline a digital model for these types of documents and to help future projects in defining their own offer of services.This article is part of the research project "Untangling the cordel / Démêler le cordel / Desenrollando el cordel (2020-2023)" financed by the Philanthropic Sandoz-Monique de Meuron Family Foundation and directed by the professor Constance Carta (University of Geneva).Cet article propose une analyse de la littérature de colportage espagnole au prisme du numérique, en étudiant de manière systématique les métadonnées et les services sélectionnés par dix-sept bibliothèques numériques pour modéliser leurs collections.Dans un premier temps, nous proposons un panorama de ces bibliothèques, dont la grande variété reflète celle de cette littérature populaire, à la marge des études sur les productions imprimées et qui échappe aux classifications traditionnellement employées pour le livre. Dans un second temps, nous décrivons quatre stratégies différentes employées par les bibliothèques numériques pour modéliser ce type de contenus, en mettant l’accent soit sur le document en tant qu’archives à conserver, soit sur le document en tant que résultat d’un processus éditorial, soit sur le texte, soit sur l’illustration. Notre objectif est ainsi d’esquisser les contours d’un modèle numérique pour ce type de documents et d’aider de futurs projets dans la définition de leur propre offre de services.Cet article s’inscrit dans le cadre du projet de recherche « Démêler le cordel / Desenrollando el cordel / Untangling the cordel (2020-2023) » financé par la Fondation philanthropique Famille Sandoz-Monique de Meuron et dirigé par la professeure Constance Carta (Université de Genève).
Resource efficiency of metallurgical production
Authors: Chernikova O. P. , Zlatitskaya Yu. A.
Published: July 2022

The balanced development of the world community in the next decade implies achievement of sustainable development goals by increasing the efficiency of resources utilization in the economic, social and environmental spheres of human activity. Within the framework of globalization processes, which inevitably affect the national economic, social and environmental agenda, the last two spheres are becoming increasingly important. The main measures of the state national policy of the Russian Federation are aimed at solving social and economic problems that ensure realization of the right of every person to a favorable environment. Timely solution of the problems of social and environmental well-being, as indicators of the life quality of population, is a priority task of the state authorities of the regions together with the top management of city-forming enterprises that bear major social and environmental burden. Increase in the resources utilization efficiency is of particular importance in regions with a dominant location of metallurgical production. Atmosphere and water pollution, a high level of occupational morbidity and injuries caused by equipment wear and safety violations at production facilities, the prevalence of mortality over births, an intensive migration outflow of the population, depreciation of engineering infrastructure with simultaneously growing industrial output reflect the imbalance in situation of the metallurgical region, delay its sustainable development. The conducted scientific research made it possible to develop a system of indicators for assessing the resource efficiency of metallurgical production with their grouping by development components. It makes possible for the management to evaluate the contribution of each set of components to the resulting value, propose measures and guidelines for optimizing coefficients, identify business competitiveness growth factors, determine investment targets, and also demonstrate to the world community the transformation of production and economic activities of companies in accordance with global trends in resource conservation and sustainability.
Analysis of the drawing mill drive operation
Authors: Nikitin A. G. , Bazhenov I. A. , Gerasimov S. P.
Published: July 2022

For enterprises of the metallurgical industry, the task of increasing the operational life of drawing mills is urgent. The reasons for a significant decrease in the resource and an increase in the number of equipment downtime are related to the operational problems. Downtime due to emergency equipment failures account for up to 45 % of the mill’s operating time per month. The paper considers the drive scheme of the drawing mill and analyzes the loss of time to restore its working condition. It is shown that the replacement of a cylindrical gearbox with a gearshift mechanism and a  bevel gear with a planetary gear motor equipped with a frequency converter will increase the productivity of the drawing mill by reducing emergency equipment downtime.
Development of an imitation model of a two-mass technological vibratory unit with electromagnetic excitation
Authors:   Novosibirsk State Technical University, Russian Federation, Neyman Lyudmila A. , Neyman Vladimir Yu. ,   Novosibirsk State Technical University, Russian Federation, Markov Aleksey V. ,   Novosibirsk State Technical University, Russian Federation, Lappi Sergey Yu. ,   Novosibirsk State Technical University, Russian Federation
Published: July 2022

The research performed is actual because it is necessary to improve methods of calculations of rapid dynamic processes in electrical units. The object of research is the construction of a two-mass technological vibration unit with electromagnetic excitation. The subject of research is the method of calculation based on the created simulation model of the vibration unit dynamic cha-racteristics in transient and stationary modes with respect to a form and frequency of the source voltage. The mathematical model is based on non-linear differential equations of the electrical and mechanical balance. The main objective of research is the development of a simulation model of a two-mass technological vibration unit with electromagnetic excitation using modern methods of computer simulation. The example of the numerical implementation of the mathematical model by structural modeling methods in the Matlab Simulink is considered and the computer model of the electromagnetic vibration unit is created. The examples of the calculation of dynamical cha-racteristics of electromagnetic vibration unit for the analysis of electromechanical processes in transient and stationary modes are presented. Some of calculated values of integral indicators describing conversion processes of electric energy consumed from a power supply are given. The proposed simulation model of a technological vibration unit can be used to calculate rapid dyna-mic processes in different modes to provide a rational choice of vibration unit parameters when it is designed. The model is also useful for the analysis and synthesis of automatic systems to control the supplied voltage amplitude, frequency and form. The results of the research can be of particular interest to specialists in the area of machine strength dynamics and vibration protection.
Stepless control of the modulation index of a three-phase drive inverter in the flat-top’ mode
Authors:   Linde Material Handling GmbH, Novosibirsk, Russian Federation, Kromm Andrey A. , Simakov Gennady M. ,   Novosibirsk State Technical University, Russian Federation, Gusev Andrey E. ,   Novosibirsk State Technical University, Russian Federation
Published: July 2022

The article discusses one of the ways of stepless overmodulation in a semiconductor three-phase voltage inverter implemented according to the B6 scheme. In the review part of the article, the features of the PWM and overmodulation (“flat-top”) modes are briefly considered. The formation of the maximum possible values of the output voltage of the converter is possible due to the maximum values of the modulation index and the voltage inverter coefficient. It is shown that a variable-modulation index in the "flat-top" mode has a number of significant advantages over a fixed one, formed, for example, by "mixing" the PWM reference signal with additional harmonic signals. The geometric interpretation of the positions of the inverter output voltage vectors on the plane and their connection with the PWM reference signal made it possible to synthesize a high-precision (basic) non-linear characteristic in the inverter reference voltage path and to form a linear stepless control law for the inverter output voltage when the “flat-top” of the specified voltage coefficient is activated. The results of comparison of the basic variant of converter output voltage control with a simpler one obtained by approximating the basic equations using numerical methods of mathematics and computer simulation are presented. The absolute error of the modulation index in the case of approximation is no more than one percent in the entire "flat-top" range. The hodographs of the output voltage of the inverter in the X-Y axes are given for three different coefficients of the converter during the transition from PWM to "flat-top". The advantages of the method include the simplicity of its implementation in a new or existing space-vector PWM, the implementation of which is carried out exclusively by a software product. This aspect makes this method particularly attractive in low budget drives.
Sobre lo sublime en la España del siglo XVIII: lecturas y escritos de Gaspar M. de Jovellanos
Authors: Lorenzo Álvarez Elena de
Published: July 2022

La presencia de la estética de lo sublime en la literatura española de finales del siglo xviii es una constante que ha sido especialmente atendida en el caso de lo sublime cósmico en la poesía filosófica de Juan Meléndez Valdés y parcialmente en el de la obra literaria de Gaspar M. de Jovellanos. Aquí volvemos al ilustrado de referencia del siglo xviii español para perfilar la presencia de lo sublime en su obra completa y reconstruir el mapa de fuentes sobre lo sublime en que Jovellanos pudo forjar su conocimiento y gusto sobre lo sublime, para contextualizarlo en el marco estético, filosófico y religioso del sublime europeo, y para contribuir al trazado de la conformación de la estética de lo sublime en España.
Comunicación no verbal y somatismos fraseológicos de base emocional
Authors: Penas Ibáñez María Azucena
Published: July 2022

El estudio versa sobre la comunicación no verbal y los somatismos fraseológicos de base emocional. Se analizan, a partir del Glosario de somatismos del español de Saracho Arnáiz, 61 ítems vinculados a la emoción vehiculizada por las partes del cuerpo, en un total de 281 casos. Los somatismos fraseológicos cubren todas las emociones básicas de Plutchik y todas las emociones sociales de Etxebarria, salvo los celos, así como dos tipos de metáforas conceptuales. En la investigación realizada se observa que, de los cuatro somatismos faciales, el más importante es el ojo. Esto corrobora la primacía del ojo en la fraseología, a diferencia de la comunicación no verbal donde se prima la boca.
Locura y pensamiento periférico en la poesía de Leopoldo María Panero
Authors: Antúnez Arce Rafael
Published: July 2022

Como defiende Foucault, no se puede establecer una evolución coherente en la historia del pensamiento ni en la de ninguna disciplina científica. Esto hace que la literatura, como cualquier otra disciplina científica se vea abocada a un análisis al margen de periodos históricos y cánones establecidos. Por otra parte, Foucault considera que la literatura es lenguaje alejándose lo más posible de sí mismo. Algo palpable en particular en autores que se entregan a la violencia del grito, y donde el pensamiento es expresión del deseo y desgarramiento del sujeto. Como sucede en Artaud o Blanchot, en Leopoldo María Panero nos hallamos ante una escritura del afuera, del sujeto escindido en sus devenires rizomáticos, empleando la terminología de Deleuze y Guattari, en la que el significante se halla desterritorializado y descodificado, para lo que emplea procedimientos logofágicos como el óstracon, el hápax o el criptograma.
Kordons Berlin: Bilder und Emotionen der deutschen Hauptstadt im 20. Jahrhundert
Authors: Heinecke Leonie
Published: July 2022

Klaus Kordon ist ein Autor deutscher Kinder- und Jugendliteratur. Der Schauplatz eines Großteils seiner Romane zur deutschen Geschichte im 20. Jahrhundert ist Berlin: In der Trilogie der Wendepunkte, bestehend aus den Romanen Die Roten Matrosen oder Ein vergessener Winter (1998), Mit dem Rücken zur Wand (1999) und Der erste Frühling (1999),  zeichnet Kordon ein literarisches Bild der Hauptstadt durch ein Jahrhundert, welches von sozialpolitischen Umbrüchen geprägt ist, die für stetige Veränderungen sorgen: Ende des Deutschen Kaiserreiches, Dreißigerjahre, Zweiter Weltkrieg und Beginn der Nachkriegszeit. Nachdem ausgewählte theoretische Fundamente zur Raumanalyse vorgestellt werden, untersucht der Artikel den Raum und die mit ihm untrennbar verbundene Raumerfahrung in den drei Romanen. Daiel ist, die Konstruktion des Berlinbildes Kordons für den Leser nachvollziehbar zu machen und dabei besonders die emotionale Bedeutung hervorzuheben, die der Raum für und durch die Protagonisten durch das Jahrhundert hinweg erlangt.
Utopía y metafísica del tiempo en «Tlön, Uqbar, Orbis Tertius» de Jorge Luis Borges
Authors: Amado Cano José David
Published: July 2022

El artículo estudia la relación del cuento «Tlön, Uqbar, Orbis Tertius» de Jorge Luis Borges con la tradición occidental de textos utópicos. Se hace hincapié en la configuración del tiempo narrado, que se analiza a través de la filosofía de Agustín de Hipona y de Paul Ricoeur. El estudio de las teorías metafísicas del tiempo de Tlön y cómo este es percibido y experimentado por sus habitantes permite considerar el mundo imaginario de Borges como una metáfora viva del nuestro.
[RETRACTED] Pure Calm CBD Gummies v1
Authors: not provided JaditMays
Published: July 2022

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[RETRACTED] Big Update:-Twin Elements CBD Oil Evaluation - Must Read!!! v1
Authors: not provided frankdula
Published: July 2022

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People's normal actions result in a wholesome lifestyle. Function, diet, and pleased instances are typical contained in this. Some aspects may intervene with this specific balanced practise and end in wellness issues. Era represents part in some. The others may derive from not known inner and additional influences. Strain is really a cerebral issue although suffering is really a significant physical issue. It's difficult to remove them because many people might not understand how to take action normally or may possibly resort to harmful medicines, which may trigger different issues.
[RETRACTED] Via Keto Apple Gummies Canada Reviews- 3 Ways Create Better VIA KETO APPLE GUMMIES CANADA With The Help Of Your Dog v1
Authors: Keto Apple Gummies Canada Reviews Via
Published: July 2022

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[RETRACTED] GoKeto Gummies Reviews: Does Go Keto Gummy Bears Works? v1
Authors: not provided goketogummiesreviewsasdf
Published: July 2022

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GoKeto Gummies Reviews: Does Go Keto Gummy Bears Works?
[RETRACTED] Kerassentials Reviews (#1 Formula) On The Marketplace For Managing Nail Fungus And Skin Health! v1
Authors: not provided kerassentialsnews
Published: July 2022

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Check The Availability Of Kerassentials On the Official Website
[RETRACTED] Vitality HQ Keto Gummies Reviews 2022 Updated | Scam Or Legit ? v1
Authors: not provided JamesBlocker
Published: July 2022

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One should involveVitality HQ Keto Gummiesitems several times each day for improved results. It stays in a sticky structure,..
[RETRACTED] Bellisima Bites Collagen Gummies:-Does Collagen Skin Gummies Supplement Work? What to Know Before Buying! v1
Authors: not provided bellisimabitescollagen
Published: July 2022

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Collagen Skins' edibles were developed and introduced to the public with the necessary tools to restore every method your parchedness, sun tanning, frightful kinks, unwanted flaws, fine lines, and dark circles offer that take place on your sensitive skins in a top standard and the proper method, in a long-term and reliable method.
[RETRACTED] https://www.facebook.com/ViaKetoAppleGummiesAu/ v1
Authors: keto gummies australia via
Published: July 2022

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[RETRACTED] The ACV Secret Moisturizer Reviews | Best Natural Products For Normal Skin v1
Authors: not provided uskoparnalim
Published: July 2022

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[RETRACTED] Golden Revive Plus Reviews: [Scam Exposed 2022] Read Ingredients, Side Effects Price & Where To Buy? v1
Authors: not provided G
Published: July 2022

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Golden Reviews Plus Reviews
The Kyrgyz Republic: Concept, Strategies, and Practices for the Preservation of the National Cultural Heritage
Authors: Oktyabrskaya I. V. , Alymkulova S. K. , Nazarov I. I. , Samushkina E. V.
Published: July 2022

This study deals with the concept of «cultural heritage» in the Kyrgyz Republic, including both material culture and traditional ideology. We describe their codification, and strategies for their preservation and popularization. We draw on a large database, which includes findings of original fieldwork. We outline the elaboration of the concept of cultural heritage and its content, presenting a systematic description of institutional aspect and meaning, and we analyze the practices of its implementation. The historical and cultural heritage is viewed as a multifactorial space. The realities of modern Kyrgyzstan suggest that the nation implements integration strategies in foreign policy. While using the notions of cultural heritage and traditional values, the republic strengthens its ties with other members of the CIS, raising the level of its integration into the Central Asian community and maintaining its status as part of the world civilization. Cultural heritage is a key resource of social change and the economic stabilization of local communities. Its preservation at the level of everyday culture, academic, and educational practices, museums, festivals, etc. is a condition of national consolidation.
Vantagens econômicas e sustentáveis da logística ferroviária brasileira
Authors: De Almeida Barboza Lucas , Regina de Oliveira Lorena
Published: July 2022

Desde a primeira revolução industrial, as ferrovias se destacaram em relação ao transporte de passageiros e de cargas a longas distâncias, além de serem mais rápidas que os animais utilizados até então para o transporte. Durante os séculos, as ferrovias passaram por várias inovações e com elas surgiram questionamentos relativos ao uso e suas vantagens e desvantagens, gerando a impressão de que as ferrovias são apenas vantajosas no que se refere a seus custos e não abordando as diversas outras vantagens. Considerado o mais lento entre os modais, o uso das ferrovias se destaca pelo baixo custo nas manutenções durante a vida útil que ocorrem entre cinco a dez anos. No que se refere ao uso de combustível, ela se mostra competitiva e sustentável, tanto na possibilidade de diferentes usos (diesel e eletricidade), quanto na quantidade de emissão de carbono na atmosfera. O uso da malha ferroviária brasileira se restringe a algumas regiões, gerando um gargalo logístico ao modal ferroviário, impactando nos altos custos de permanência deste modal, bem como pouco investimento em manutenção e expansão ferroviária. Contudo, o presente artigo tem como objetivo principal apontar a importância econômica e os benefícios do modal ferroviário para a logística brasileira, que vai além dos baixos custos envolvidos. Para o desenvolvimento dessa pesquisa, utilizou como metodologia o método qualitativo e revisão de literatura, por meio de pesquisas que apontaram como resultado o auxílio do crescimento nas regiões Centro-Sul brasileiras e a redução na emissão dos gases de efeito estufa.
Ransomware Detection in Cyber Security Domain
Authors: ASLAN Ömer
Published: July 2022

In recent years, ransomware has become highly profitable cyber attacks. This is because, everyday there are several new devices attending to computer networks before testing their security strength. In addition, it is easy to launch ransomware attacks by using Ransomware-as-a-Service. This paper proposed a new method that creates the ransomware specific features by using ransomware behaviors which are performed on file, registry, and network resources. The weights are assigned to the behaviors based upon where the actions are performed. The most feasible features are selected based on the assigned weights as well as Information Gain. The selected features are classified by using ML classifiers including J48 (C4.5), RF (Random Forest), AdaBoost (Adaptive Boosting), SLR (Simple Logistic Regression), KNN (K-Nearest Neighbors), BN (Bayesian Network), and SMO (Sequential Minimal Optimization). The experiments are performed on several ransomware variants as well as benign samples. The test results show that our proposed method is feasible and effective. The DR, FPR, f-measure, and accuracy are measured as 100%, 1.4%, 99.4%, 99.38%, respectively.