Original Grammar Research Articles

MultiGreen: A multiplexing architecture for GreenGate cloning.

Genetic modification of plants fundamentally relies upon customized vector designs. The ever-increasing complexity of transgenic constructs has led to increased adoption of modular cloning systems for their ease of use, cost effectiveness, and rapid prototyping. GreenGate is a modular cloning system catered specifically to designing bespoke, single transcriptional unit vectors for plant transformation-which is also its greatest flaw. MultiGreen seeks to address GreenGate's limitations while maintaining the syntax of the original GreenGate kit. The primary limitations MultiGreen addresses are 1) multiplexing in series, 2) multiplexing in parallel, and 3) repeated cycling of transcriptional unit assembly through binary intermediates. MultiGreen efficiently concatenates bespoke transcriptional units using an additional suite of level 1acceptor vectors which serve as an assembly point for individual transcriptional units prior to final, level 2, condensation of multiple transcriptional units. Assembly with MultiGreen level 1 vectors scales at a maximal rate of 2*⌈log6n⌉+3 days per assembly, where n represents the number of transcriptional units. Further, MultiGreen level 1 acceptor vectors are binary vectors and can be used directly for plant transformation to further maximize prototyping speed. MultiGreen is a 1:1 expansion of the original GreenGate architecture's grammar and has been demonstrated to efficiently assemble plasmids with multiple transcriptional units. MultiGreen has been validated by using a truncated violacein operon from Chromobacterium violaceum in bacteria and by deconstructing the RUBY reporter for in planta functional validation. MultiGreen currently supports many of our in-house multi transcriptional unit assemblies and will be a valuable strategy for more complex cloning projects.

Sign Language Recognition and Interpretation System

Sign language is a visual language that individuals with speech and hearing difficulties use to communicate in their daily conversations. Through its original grammar, it is totallyan optical communication language, as opposed to vocal languages. This study report proposed an effective strategy to accomplishing the translation of 24 static sign language alphabets and numerals of American Sign Language into humanoid. Researchers are now focusing their efforts on building commercially viable Sign Language Recognition systems. Researchers use a range of techniques to perform their research. It all starts with the methods of data acquisition. The data collection method varies depending on the cost of a suitable device, however for the Sign Language Recognition System to be commercialized, a low-cost strategy is required. The methods used by researchers to develop Sign Language Recognition varied as well. Each approach has its own advantages over others, and researchers are continually experimenting with various methods to produce their own Sign Language Recognition. Each approach has its own set of limitations when compared to others. The purpose of this study is to examine several ways to sign language recognitionand choose the optimal method. Keywords — Feature Extraction and Representation, Artificial Neural Networks, Convolution Neural Network, TensorFlow, Keras, OpenCV.

Natural Language Processing and Computational Linguistics

Natural Language Processing and Computational Linguistics

Knowledge extraction from the learning of sequences in a long short term memory (LSTM) architecture

Transparency and trust in machine learning algorithms have been deemed to be fundamental and yet, from a practical point of view, they remain difficult to implement. Particularly, explainability and interpretability are certainly among the most difficult capabilities to be addressed and imply to be able to understand a decision in terms of simple cues and rules. In this article, we address this specific problem in the context of sequence learning by recurrent neuronal models (and more specifically Long Short Term Memory model). We introduce a general method to extract knowledge from the latent space based on the clustering of the internal states. From these hidden states, we explain how to build and validate an automaton that corresponds to the underlying (unknown) grammar, and allows to predict if a given sequence is valid or not. Finally, we show that it is possible for such complex recurrent model, to extract the knowledge that is implicitly encoded in the sequences and we report a high rate of recognition of the sequences extracted from the original grammar. This method is illustrated on artificial grammars (Reber grammar variants) as well as on a real use-case in the electrical domain, whose underlying grammar is unknown.

Essence of grammar according to modern linguistics and Afghan linguists’ perspectives

The paper explored views in modern linguistic theories and Afghan linguist perspectives about essence of grammar, its original source, its function in language use and the relationship between mental rules and their description in grammar books. The data were collected from theoretical linguistics, grammar books and 10 Afghan professors who teach linguistics and Persian-Dari grammar in Kabul University via a questionnaire. MS excel was used to analyze the data. The results show the term Grammar refers to a set of constructional rules of a language located in speakers’ minds. It is unconscious knowledge which enables speakers of a language to produce and understand its utterances. These mental rules govern composition of phonemes, morphemes, words, phrases, clauses and sentences. Grammar books are like maps of original grammar which has mental essence and describe it. Children learn their native language from elders and their coeval speakers. Second language learners, can learn a foreign language through social interaction and grammar books. Compiling grammatical rules of a language introduces word formation techniques to expand its lexicon, help speakers to know more about their language capacities and possibilities. Grammar books aim to facilitate learning formal language, description of constructional rules, language learning for foreigners and provide correct writing guidelines. The research prescribes grammar teachers to use grammar as means of enrichment of formal language, as it can better function to do its scientific mission.

Biblical Hebrew: An Introductory Grammar

This is a revision of Page H. Kelley’s Biblical Hebrew: An Introductory Grammar (Grand Rapids: Eerdmans, 1992). This second edition retains the original approach and lesson plan of Kelley’s volume, while providing extensive corrections, updates, format improvements, summaries, indexes, and new figures and tables. The revision includes a separate handbook that provides an answer key to the exercises found at the end of each lesson in the grammar book. The expressed intent of this revision is to enable colleges and seminaries to continue to use Kelley’s volume for their Hebrew classes.The revised grammar is advertised as providing “easy-to-understand explanations.” Furthermore, the preface states, “students should be expected to study the lesson carefully, but without attempting to memorize rules” (p. xv). The instructor and student will have to decide whether or not these statements hold up. Following older approaches to teaching biblical Hebrew, Kelley’s grammar is filled with highly technical explanations, long lists of rules, a multitude of tables, and a complex approach to explaining Hebrew verbs. None of these issues were corrected in the new edition. For example, a long list of rules is provided for interrogatives (pp. 119–22). These types of lists demand memorization, which for the beginning student will seem tedious and disconnected from the main task of learning the Hebrew language. It would be better to provide a few basic ideas for interrogatives and then refer the student to a reference section for more details.While the grammar employs the usual sequence of building from the alphabet to nouns and then to verbs, Kelley’s approach to explain verbs is not straightforward. Verbs are taught from the premise of learning all the stems at once. This is true for the strong and weak verb. Furthermore, the second edition has kept the weak-verb designations, using the older pe-ayin-lamed paradigm as compared to identifying weak letters by their numbered position in a verb (pp. 104–5). This terminology provides more layers of complexity for the student. Having learned Hebrew from the original Kelley grammar, I can attest to the mountains of rules and details that need to be memorized as a result of this approach. It seems that a far better method, as employed by most grammar books, is to teach the qal strong verb first, then explain each stem in its strong and weak verb conjugations.As in the original Kelley grammar, the book tends to use terms that are not defined or well-defined. For example, the term diacritical marks (p. 37) is stated without definition. The term shortening (p. 59), in regard to vowels in monosyllabic adjectives, is employed without explanation or reference to a previous section. Furthermore, the book retains explanations that are questionable. For example, the grammar states in regard to inserting of between construct nouns: “Since Hebrew lacked such an all-purpose preposition, the construct relationship helped to fill the gap” (p. 75). It is likely that the grammar is offered in black-and-white to reduce cost; however, color coding would be more effective. For example, the synopsis of the perfect verb for each stem (§14.56, p. 148) is difficult to understand given its use of numbers for Hebrew consonants and light/heavy shading to reflect stem characteristics.The challenge with Hebrew grammar books is to try to find the right balance between being a teaching tool and a reference grammar. Until recently, most grammar books, like Kelley’s, have leaned heavily toward being a reference grammar. The result is an emphasis on majoring on the minors, which may appeal to analytical students but confuses and frustrates students with different learning styles. New-generation grammars seek to overcome this obstacle by making learning fun and interesting, covering the basic elements of the language, and providing reference sections or footnotes for more detailed explanations of Hebrew grammar and syntax. Furthermore, these new grammars use second-language learning approaches, including memory tools, interesting visual illustrations, interactive dialogue, simple-to-more-complex explanations, and immediate engagement in reading and interpreting the Hebrew Scriptures. While the revised Kelley grammar provides the building blocks for this type of instruction, it will require a highly skilled and inventive instructor to ensure that all students, with different learning styles, are able to learn Biblical Hebrew.

Modularity and compositionality: The case of temporal modifiers

This paper concerns the possibility of building Montague grammars in a modular and incremental way. As an illustration, we investigate the following question. Given an atemporal Montague grammar, on the one hand, and a temporal ontology, on the other hand, is it possible to combine them into a new grammar such that it would: (i) conservatively extend the original grammar, and (ii) allow temporal modifiers to be accommodated.

On translating Lambek grammars with one division into context-free grammars

We describe a method of translating a Lambek grammar with one division into an equivalent context-free grammar whose size is bounded by a polynomial in the size of the original grammar. Earlier constructions by Buszkowski and Pentus lead to exponential growth of the grammar size.

Localizing Ashkenazic Jews to Primeval Villages in the Ancient Iranian Lands of Ashkenaz.

The Yiddish language is over 1,000 years old and incorporates German, Slavic, and Hebrew elements. The prevalent view claims Yiddish has a German origin, whereas the opposing view posits a Slavic origin with strong Iranian and weak Turkic substrata. One of the major difficulties in deciding between these hypotheses is the unknown geographical origin of Yiddish speaking Ashkenazic Jews (AJs). An analysis of 393 Ashkenazic, Iranian, and mountain Jews and over 600 non-Jewish genomes demonstrated that Greeks, Romans, Iranians, and Turks exhibit the highest genetic similarity with AJs. The Geographic Population Structure analysis localized most AJs along major primeval trade routes in northeastern Turkey adjacent to primeval villages with names that may be derived from “Ashkenaz.” Iranian and mountain Jews were localized along trade routes on the Turkey’s eastern border. Loss of maternal haplogroups was evident in non-Yiddish speaking AJs. Our results suggest that AJs originated from a Slavo-Iranian confederation, which the Jews call “Ashkenazic” (i.e., “Scythian”), though these Jews probably spoke Persian and/or Ossete. This is compatible with linguistic evidence suggesting that Yiddish is a Slavic language created by Irano-Turko-Slavic Jewish merchants along the Silk Roads as a cryptic trade language, spoken only by its originators to gain an advantage in trade. Later, in the 9th century, Yiddish underwent relexification by adopting a new vocabulary that consists of a minority of German and Hebrew and a majority of newly coined Germanoid and Hebroid elements that replaced most of the original Eastern Slavic and Sorbian vocabularies, while keeping the original grammars intact.

Interactive design of probability density functions for shape grammars

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (pdf) over such a shape space and to sample models according to the designed pdf. First, we propose a user interface that enables a user to quickly provide preference scores for selected shapes and suggest sampling strategies to decide which models to present to the user to evaluate. Second, we propose a novel kernel function to encode the similarity between two procedural models. Third, we propose a framework to interpolate user preference scores by combining multiple techniques: function factorization, Gaussian process regression, autorelevance detection, and l 1 regularization. Fourth, we modify the original grammars to generate models with a pdf proportional to the user preference scores. Finally, we provide evaluations of our user interface and framework parameters and a comparison to other exploratory modeling techniques using modeling tasks in five example shape spaces: furniture, low-rise buildings, skyscrapers, airplanes, and vegetation.

Techniques for automated testing of Lola industrial robot language Parser

The accuracy of parsing execution directly affects the accuracy of semantic analysis, optimization and object code generation. Therefore, parser testing represents the basis of compiler testing. It should include tests for correct and expected, but also for unexpected and invalid cases. Techniques for testing the parser, as well as algorithms and tools for test sentences generation, are discussed in this paper. The methodology for initial testing of a newly developed compiler is proposed. Generation of negative test sentences by modifying the original language grammar is described. Positive and negative test cases generated by Grow, Purdom's algorithm with and without length control, CDRC-P algorithm and CDRC-P algorithm with length control are applied to the testing of L-IRL robot programming language. For this purpose two different tools for generation of test sentences are used. Based on the presented analysis of possible solutions, the appropriate method can be chosen for testing the parser for smaller grammars with many recursive rules.

BPEL 규칙 모델링을 위한 규칙 기반 BPEL 시스템 설계와 구현

BPEL is a standard executable language for specifying actions within business processes with Web services. BPEL workflow requires rule engine to describe application process in BPEL, as the requirements increase. It is needed to develop new BPEL`s engine or modify BPEL`s engine in order to add the functionality of rules to BPEL engines, but this method is not easy to implement and it requires very high cost. In this paper, we present an R4BPEL document, which uses the original BPEL grammar and includes a rule document. With this method, it is possible to build rule-based BPEL environment easily by adding web services with rules and R4BPEL document analyzer to the general-purpose Web services. In this paper, we campared a BPEL`s document in proposed system with a BPEL`s document in the existing system. And we demonstrated the simplicity of the rule-based system.

A New Palladian Shape Grammar

The following paper describes a shape grammar that recreates Palladian villas. A Palladian grammar was originally proposed by Stiny and Mitchell. However, this alternative grammar uses different parametric shape rules and methodology to test the hypothesis that different grammars can generate the same corpus of designs. The formalism is then implemented using a computerised design tool. The grammar includes subdivision rules that allow for a more economical formulation. A new corpus of solutions is explored and the derivation is compared with the original Palladian grammar. The project is part of wider research aimed at formulating a generic housing grammar.

An environment for supporting active learning in courses on language processing

PAG ( Prototyping with Attribute Grammars ) is an environment that promotes active learning in courses on language processing (e.g. compiler construction and computational linguistics). In PAG, learners can specify the syntax and the semantics of their languages with attribute grammars. Then, the environment generates prototypes of processors for the languages specified which learners can test with different inputs. For each valid input the prototypes produce one or more decorated syntax trees, which learners can navigate using the semantic equations in the original grammar. In this paper we describe the environment and we report its educational uses.

Inferring Graph Grammars by Detecting Overlap in Frequent Subgraphs

Inferring Graph Grammars by Detecting Overlap in Frequent SubgraphsIn this paper we study the inference of node and edge replacement graph grammars. We search for frequent subgraphs and then check for an overlap among the instances of the subgraphs in the input graph. If the subgraphs overlap by one node, we propose a node replacement graph grammar production. If the subgraphs overlap by two nodes or two nodes and an edge, we propose an edge replacement graph grammar production. We can also infer a hierarchy of productions by compressing portions of a graph described by a production and then inferring new productions on the compressed graph. We validate the approach in experiments where we generate graphs from known grammars and measure how well the approach infers the original grammar from the generated graph. We show graph grammars found in biological molecules, biological networks, and analyze learning curves of the algorithm.

From UBGs to CFGs A practical corpus-driven approach

AbstractWe present a simple and intuitive unsound corpus-driven approximation method for turning unification-based grammars, such as HPSG, CLE, or PATR-II into context-free grammars (CFGs). Our research is motivated by the idea that we can exploit (large-scale), hand-written unification grammars not only for the purpose of describing natural language and obtaining a syntactic structure (and perhaps a semantic form), but also to address several other very practical topics. Firstly, to speed up deep parsing by having a cheap recognition pre-flter (the approximated CFG). Secondly, to obtain an indirect stochastic parsing model for the unification grammar through a trained PCFG, obtained from the approximated CFG. This gives us an efficient disambiguation model for the unification-based grammar. Thirdly, to generate domain-specific subgrammars for application areas such as information extraction or question answering. And finally, to compile context-free language models which assist the acoustic model of a speech recognizer. The approximation method is unsound in that it does not generate a CFG whose language is a true superset of the language accepted by the original unification-based grammar. It is a corpus-driven method in that it relies on a corpus of parsed sentences and generates broader CFGs when given more input samples. Our open approach can be fine-tuned in different directions, allowing us to monotonically come close to the original parse trees by shifting more information into the context-free symbols. The approach has been fully implemented inJAVA.

Urdu in a parallel grammar development environment

In this paper, we report on the role of the Urdu grammar in the Parallel Grammar (ParGram) project (Butt, M., King, T. H., Niño, M.-E., & Segond, F. (1999). A grammar writer’s cookbook. CSLI Publications; Butt, M., Dyvik, H., King, T. H., Masuichi, H., & Rohrer, C. (2002). ‘The parallel grammar project’. In: Proceedings of COLING 2002, Workshop on grammar engineering and evaluation, pp. 1–7). The Urdu grammar was able to take advantage of standards in analyses set by the original grammars in order to speed development. However, novel constructions, such as correlatives and extensive complex predicates, resulted in expansions of the analysis feature space as well as extensions to the underlying parsing platform. These improvements are now available to all the project grammars.

Inference of node replacement graph grammars

Graph grammars combine the relational aspect of graphs with the iterative and recursive aspects of string grammars, and thus represent an important next step in our ability to discover knowledge from data. In this paper we describe an approach to learning node replacement graph grammars. This approach is based on previous research in frequent isomorphic subgraphs discovery. We extend the search for frequent subgraphs by checking for overlap among the instances of the subgraphs in the input graph. If subgraphs overlap by one node we propose a node replacement grammar production. We also can infer a hierarchy of productions by compressing portions of a graph described by a production and then infer new productions on the compressed graph. We validate this approach in experiments where we generate graphs from known grammars and measure how well our system infers the original grammar from the generated graph. We also describe results on several real-world tasks from chemical mining to XML schema induction. We briefly discuss other grammar inference systems indicating that our study extends classes of learnable graph grammars.

Genetic programming incorporating biased mutation for evolution and adaptation of Snakebot

In this work we propose an approach for incorporating learning probabilistic context-sensitive grammar (LPCSG) in genetic programming (GP), employed for evolution and adaptation of locomotion gaits of a simulated snake-like robot (Snakebot). Our approach is derived from the original context-free grammar which usually expresses the syntax of genetic programs in canonical GP. Empirically obtained results verify that employing LPCSG contributes to the improvement of computational effort of both (i) the evolution of the fastest possible locomotion gaits for various fitness conditions and (ii) adaptation of these locomotion gaits to challenging environment and degraded mechanical abilities of the Snakebot.

Extending a scripting language for visual basic forms

A prototype scripting language was introduced in 2002 to assist the blind in creating forms for Visual Basic programs in a much simpler fashion; currently, creating these forms are particularly difficult for the blind and visually impaired. The language is expanded to include the Visual Basic objects that were omitted from the original grammar for the scripting language. A second prototype of the compiler for the scripting language is now available online. An example and a formal grammar are included.