Getting grip in changing environments: the effect of friction anisotropy inversion on robot locomotion

Legged locomotion of robots can be greatly improved by bioinspired tribological structures and by applying the principles of computational morphology to achieve fast and energy-efficient walking. In a previous research, we mounted shark skin on the belly of a hexapod robot to show that the passive anisotropic friction properties of this structure enhance locomotion efficiency, resulting in a stronger grip on varying walking surfaces. This study builds upon these results by using a previously investigated sawtooth structure as a model surface on a legged robot to systematically examine the influences of different material and surface properties on the resulting friction coefficients and the walking behavior of the robot. By employing different surfaces and by varying the stiffness and orientation of the anisotropic structures, we conclude that with having prior knowledge about the walking environment in combination with the tribological properties of these structures, we can greatly improve the robot’s locomotion efficiency.

Hydrothermal polymerization of porous aromatic polyimide networks and machine learning-assisted computational morphology evolution interpretation

We report on the hydrothermal polymerization (HTP) of porous polyimide (PI) networks using the medium H2O and the comonomers 1,3,5-tris(4-aminophenyl)benzene (TAPB) and pyromellitic acid (PMA).

Manipuri Morphological Analysis

Morphological analysis is the basic foundation in Natural Language Processing applications including Syntax Parsing, Machine Translation (MT), Information Retrieval (IR) and Automatic Indexing. Morphological Analysis can provide valuable information for computer based linguistics task such as Lemmatization and studies of internal structure of the words or the feature values of the word. Computational Morphology is the application of morphological rules in the field of Computational Linguistics, and it is the emerging area in AI, which studies the structure of words, which are formed by combining smaller units of linguistics information, called morphemes: the building blocks of words. It provides about Semantic and Syntactic role in a sentence. It can analyze the Manipuri word forms and produces grammatical information, which is associated with the lexicon. Morphological Analyzer for Manipuri language has been tested on 4500 Manipuri lexicons in Shakti Standard Format (SSF) using Meitei Mayek Unicode as source; thereby an accuracy of 84% has been obtained on a manual check.

Computer-Based Tools for Word and Paradigm Computational Morphology

The Word and Paradigm approach to morphology associates lexemes with tables of surface forms for different morphosyntactic property sets. Researchers express their realizational theories, which show how to derive these surface forms, using formalisms such as Network Morphology and Paradigm Function Morphology. The tables of surface forms also lend themselves to a study of the implicative theories, which infer the realizations in some cells of the inflectional system from the realizations of other cells. There is an art to building realizational theories. First, the theories should be correct, that is, they should generate the right surface forms. Second, they should be elegant, which is much harder to capture, but includes the desiderata of simplicity and expressiveness. Without software to test a realizational theory, it is easy to sacrifice correctness for elegance. Therefore, software that takes a realizational theory and generates surface forms is an essential part of any theorist’s toolbox. Discovering implicative rules that connect the cells in an inflectional system is often quite difficult. Some rules are immediately apparent, but others can be subtle. Software that automatically analyzes an entire table of surface forms for many lexemes can help automate the discovery process. Researchers can use Web-based computerized tools to test their realizational theories and to discover implicative rules.

LatMor: A Latin Finite-State Morphology Encoding Vowel Quantity

We present the first large-coverage finite-state open-source morphology for Latin (called LatMor) which parses as well as generates vowel quantity information. LatMor is based on the Berlin Latin Lexicon comprising about 70,000 lemmata of classical Latin compiled by the group of Dietmar Najock in theirwork on concordances of Latin authors (see Rapsch and Najock, 1991) which was recently updated by us. Compared to the well-known Morpheus system of Crane (1991, 1998), which is written in the C programming language, based on 50,000 lemmata of Lewis and Short (1907), not well documented and therefore not easily extended, our new morphology has a larger vocabulary, is about 60 to 1200 times faster and is built in the form of finite-state transducers which can analyze as well as generate wordforms and represent the state-of-the-art implementation method in computational morphology. The current coverage of LatMor is evaluated against Morpheus and other existing systems (some of which are not openly accessible), and is shown to rank first among all systems together with the Pisa LEMLAT morphology (not yet openly accessible). Recall has been analyzed taking the Latin Dependency Treebank¹ as gold data and the remaining defect classes have been identified. LatMor is available under an open source licence to allow its wide usage by all interested parties.