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This document proposes a control scheme for delayed bilateral teleoperation of a mobile robot, which it is sought to achieve a coordination of the master device position with the slave mobile robot velocity, and at the same time synchronize the force exerted by the operator with force applied by the environment over the mobile robot. This approach allows the operator to improve the sensitive perception of the remote environment in which the robot navigates while he generates commands to control the mobile robot motion. In this paper, variable and asymmetrical communication time delays are taken into account, as well as a non-passive model of the human operator, for which a novel model is proposed that has a more general structure than the typical ones used to date in the teleoperation field. Furthermore, based on the theoretical analysis presented, the state of convergence in the stationary response is obtained. In addition, an experimental performance evaluation is carried out, where the position–velocity error, force error and the time to complete the task are evaluated. In the tests, a human operator commands a remote mobile robot to push objects of different weight while he perceives the weight of each object through the force feedback system. As an outcome, the theoretical and practical results obtained allow concluding that a satisfactory trade-off between stability and transparency is reached.
In the present modern age, a robot works like human and is controlled in such a manner that its movements should not create hindrance in human activities. This characteristic involves gesture feat and gesture recognition. This article is aimed to describe the developments in algorithms devised for obstacle avoidance in robot navigation which can open a new horizon for advancement in businesses. For this purpose, our study is focused on gesture recognition to mean socio-technological implication. Literature review on this issue reveals that movement of robots can be made efficient by introducing gesture-based collision avoidance techniques. Experimental results illustrated a high level of robustness and usability of the Gesture recognition (GR) system. The overall error rate is almost 10%. In our subjective judgment, we assume that GR system is very well-suited to instruct a mobile service robot to change its path on the instruction of human.
Designing the boundary layer thickness and switching gain in the nonlinear part of sliding mode controller (SMC) is one of the main subjects in SMC design that needs human experience, knowledge on the amplitude of disturbances, and information about the bounds of system uncertainties. In this paper, to reduce the trial-and-error effort by the designer(s) two different fitness functions in the horizontal and vertical planes are presented and a heuristic method is used for their optimization. The optimal switching gain in the proposed approach properly compensates the unmodeled dynamics, model uncertainty, and external disturbances. Chattering phenomenon in control signals and noise measurement effect are reduced by the optimal selection of boundary layer thickness. This proposed method is applied to an autonomous underwater vehicle (AUV) and evaluated through the real-time and cost-effective manner. The execution code is implemented on a single-board computer (SBC) through the xPC Target and is evaluated by the processor-in-the-loop (PIL) test. The results of the PIL test in the two different test cases indicate that the chattering phenomenon and amplitude of control signal applied to the actuators are reduced in comparison with the three conventional approaches in the AUV motion control.
What is the lexicon, what does it contain, and how is it structured? What principles determine the functioning of the lexicon as a component of natural language grammar? What role does lexical information play in linguistic theory? This accessible introduction aims to answer these questions, and explores the relation of the lexicon to grammar as a whole. It includes a critical overview of major theoretical frameworks, and puts forward a unified treatment of lexical structure and design. The text can be used for introductory and advanced courses, and for courses that touch upon different aspects of the lexicon, such as lexical semantics, lexicography, syntax, general linguistics, computational lexicology and ontology design. The book provides students with a set of tools which will enable them to work with lexical data for all kinds of purposes, including an abundance of exercises and in-class activities designed to ensure that students are actively engaged with the content and effectively acquire the necessary knowledge and skills they need.
Manufacturing knowledge is maintained primarily in the unstructured text in industry. To facilitate the reuse of the knowledge, previous efforts have utilized Natural Language Processing (NLP) to classify manufacturing documents or to extract structured knowledge (e.g. ontology) from manufacturing text. On the other hand, extracting more complex knowledge, such as manufacturing rule, has not been feasible in a practical scenario, as standard NLP techniques cannot address the input text that needs validation. Specifically, if the input text contains the information irrelevant to the rule-definition or semantically invalid expression, standard NLP techniques cannot selectively derive precise information for the extraction of the desired formal manufacturing rule. To address the gap, we developed the feedback generation method based on Constraint-based Modeling (CBM) coupled with NLP and domain ontology, designed to support formal manufacturing rule extraction. Specifically, the developed method identifies the necessity of input text validation based on the predefined constraints and provides the relevant feedback to help the user modify the input text, so that the desired rule can be extracted. We proved the feasibility of the method by extending the previously implemented formal rule extraction framework. The effectiveness of the method is demonstrated by enabling the extraction of correct manufacturing rules from all the cases that need input text validation, about 30% of the dataset, after modifying the input text based on the feedback. We expect the feedback generation method will contribute to the adoption of semantics-based technology in the manufacturing field, by facilitating precise knowledge acquisition from manufacturing-related documents in a practical scenario.
With the increasing public interest in artificial intelligence (AI), there is also increasing interest in learning about the benefits that AI can deliver to society. This book focuses on research advances in AI that benefit the conservation of wildlife, forests, coral reefs, rivers, and other natural resources. It presents how the joint efforts of researchers in computer science, ecology, economics, and psychology help address the goals of the United Nations' 2030 Agenda for Sustainable Development. Written at a level accessible to conservation professionals and AI researchers, the book offers both an overview of the field and an in-depth view of how AI is being used to understand patterns in wildlife poaching and enhance patrol efforts in response, covering research advances, field tests and real-world deployments. The book also features efforts in other major conservation directions, including protecting natural resources, ecosystem monitoring, and bio-invasion management through the use of game theory, machine learning, and optimization.
The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.
Travelers interact with a large number and variety of products and services during their journeys. The quality of a travel experience depends on a whole urban mobility system considered in space and time. This paper outlines the relevant concepts to be considered in designing urban mobility. The goal is to provide a language and insights for the early stages of a design process. A literature review sheds light on the complexity of urban mobility from technical, sociotechnical, and user experience perspectives. Observations of experiences in urban areas provide data for describing and understanding travel experience patterns and issues. The paper proposes a conceptual model to describe and analyze different facets of traveler experience and categorizes problems that travelers face when they interact with an urban mobility system. A case study is reported illustrating the use of the conceptual model in identifying travel problems for a demand-responsive transport service.
This paper deals with the control of an active ankle foot orthosis (AAFO) for paretic patients. State of the art methods using an AAFO try to track a predefined trajectory of the ankle joint while guaranteeing the wearer’s safety in the presence of a large tracking error. Combining the wearer’s safety and tracking accuracy is generally difficult to achieve at the same time, hence a trade-off should be found. Proxy-based sliding mode control (PSMC) offers great performances in both position tracking and safety guarantee. However, its tracking performance is subject to the influences of parameter uncertainties and external disturbances that generally occur during walking. This paper introduces an adaptation interaction method to the basic PSMC with an online adaptation of the proportional, integral and derivative parameters. At the same time, a gait phase-based ankle reference generation algorithm was proposed to adjust the joint reference trajectory in real time. The experiments using the AAFO show better tracking results with respect to basic PSMC while guaranteeing the safety.
Recently, valuable knowledge that can be retrieved from a huge volume of datasets (called Big Data) set in motion the development of frameworks to process data based on parallel and distributed computing, including Apache Hadoop, Facebook Corona, and Microsoft Dryad. Apache Hadoop is an open source implementation of Google MapReduce that attracted strong attention from the research community both in academia and industry. Hadoop MapReduce scheduling algorithms play a critical role in the management of large commodity clusters, controlling QoS requirements by supervising users, jobs, and tasks execution. Hadoop MapReduce comprises three schedulers: FIFO, Fair, and Capacity. However, the research community has developed new optimizations to consider advances and dynamic changes in hardware and operating environments. Numerous efforts have been made in the literature to address issues of network congestion, straggling, data locality, heterogeneity, resource under-utilization, and skew mitigation in Hadoop scheduling. Recently, the volume of research published in journals and conferences about Hadoop scheduling has consistently increased, which makes it difficult for researchers to grasp the overall view of research and areas that require further investigation. A scientific literature review has been conducted in this study to assess preceding research contributions to the Apache Hadoop scheduling mechanism. We classify and quantify the main issues addressed in the literature based on their jargon and areas addressed. Moreover, we explain and discuss the various challenges and open issue aspects in Hadoop scheduling optimizations.
The strong chromatic number χs(G) of a graph G on n vertices is the least number r with the following property: after adding $r\lceil n/r\rceil-n$ isolated vertices to G and taking the union with any collection of spanning disjoint copies of Kr in the same vertex set, the resulting graph has a proper vertex colouring with r colours. We show that for every c > 0 and every graph G on n vertices with Δ(G) ≥ cn, χs(G) ≤ (2+o(1))Δ(G), which is asymptotically best possible.
Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning, and those wanting to learn about the next stage of the cybersecurity arms race.
In Balaji and Mahmoud [1], the authors introduced a distance-based Gini index for rooted trees. In this paper, we introduce a degree-based Gini index (or just simply degree Gini index) for graphs. The latter index is a topological measure on a graph capturing the proximity to regular graphs. When applied across the random members of a class of graphs, we can identify an average measure of regularity for the class. Whence, we can compare the classes of graphs from the vantage point of closeness to regularity.
We develop a simplified computational formula for the degree Gini index and study its extreme values. We show that the degree Gini index falls in the interval [0, 1). The main focus in our study is the degree Gini index for the class of binary trees. Via a left-packing transformation, we show that, for an arbitrary sequence of binary trees, the Gini index has inferior and superior limits in the interval [0, 1/4]. We also show, via the degree Gini index, that uniform rooted binary trees are more regular than binary search trees grown from random permutations.
Speech- and gesture-based interfaces for computer-aided design (CAD) modeling must employ vocabulary suitable for target professional groups. We conducted an experiment with 40 participants from architecture and engineering backgrounds to elicit their speech preferences for four CAD manipulation tasks: Scale, Rotate, Copy, and Move. We compiled speech command terms used by participants and analyzed verbalizations based on three analytic themes: the exactness of descriptions, the granularity of descriptions, and the use of CAD legacy terms. We found that participants from both groups used precise and vague expressions in their verbalizations and used a median of three parameters in their verbalizations. Architects used CAD legacy terms more than Engineers in the tasks Scale and Rotate. Based on these findings, we give recommendations for the design of speech- and gesture-based interface for conceptual CAD modeling.
Increasingly, products are designed for global markets, yet studies of design practices primarily investigate designers from high-income countries. Specifically, the use of prototypes during design is likely affected by the background of the designer and the environment in which they are designing. To broaden our understanding of the extent to which prototyping best practices are used beyond Western designers, in this study, we conducted interviews with novice designers from Ghana, a middle-income country (MIC), to examine how Ghanaian novice designers (upper-level undergraduate students) used prototypes throughout their design courses. We compared the reported use of prototypes to best practice behaviors and analyzed the types of prototypes used. We found evidence that these Ghanaian novice designers used some critical prototyping best practice behaviors, while other behaviors were underutilized, specifically during the front-end phases of design and for the purpose of engaging with stakeholders. Additionally, virtual models dominated their prototyping choices. We discuss likely reasons for these trends based on participants’ design experiences and design contexts.
We prove the following 30 year-old conjecture of Győri and Tuza: the edges of every n-vertex graph G can be decomposed into complete graphs C1,. . .,Cℓ of orders two and three such that |C1|+···+|Cℓ| ≤ (1/2+o(1))n2. This result implies the asymptotic version of the old result of Erdős, Goodman and Pósa that asserts the existence of such a decomposition with ℓ ≤ n2/4.
An abelian processor is an automaton whose output is independent of the order of its inputs. Bond and Levine have proved that a network of abelian processors performs the same computation regardless of processing order (subject only to a halting condition). We prove that any finite abelian processor can be emulated by a network of certain very simple abelian processors, which we call gates. The most fundamental gate is a toppler, which absorbs input particles until their number exceeds some given threshold, at which point it topples, emitting one particle and returning to its initial state. With the exception of an adder gate, which simply combines two streams of particles, each of our gates has only one input wire, which sends letters (‘particles’) from a unary alphabet. Our results can be reformulated in terms of the functions computed by processors, and one consequence is that any increasing function from ℕk to ℕℓ that is the sum of a linear function and a periodic function can be expressed in terms of (possibly nested) sums of floors of quotients by integers.
We add Most X are Y to the syllogistic logic of All X are Y and Some X are Y. We prove soundness, completeness, and decidability in polynomial time. Our logic has infinitely many rules, and we prove that this is unavoidable.