A semi-automatic alignment method for math educational standards using the MP (materialization pattern) model

Automatic Speech Recognition (ASR) is reaching further and further into everyday life with Apple’s Siri, Google voice search, automated telephone information systems, dictation devices, closed captioning, and other applications. Along with such advances in speech technology, sociolinguists have been considering new methods for alignment and vowel formant extraction, including techniques like the Penn Aligner (Yuan and Liberman 2008) and the FAVE automated vowel extraction program (Evanini et al. 2009; Rosenfelder et al. 2011). With humans transcribing audio recordings into sentences, these semi-automated methods can produce effective vowel formant measurements (Labov et al. 2013). But as the quality of ASR improves, sociolinguistics may be on the brink of another transformative technology: large-scale, completely automated vowel extraction without any need for human transcription. It would then be possible to quickly extract vowels from virtually limitless hours of recordings, such as YouTube, publicly available audio/video archives, and large-scale personal interviews or streaming video. How far away is this transformative moment? In this article, we introduce a fully automated program called DARLA (short for “Dartmouth Linguistic Automation,”http://darla.dartmouth.edu), which automatically generates transcriptions with ASR and extracts vowels using FAVE. Users simply upload an audio recording of speech, and DARLA produces vowel plots, a table of vowel formants, and probabilities of the phonetic environments for each token. In this paper, we describe DARLA and explore its sociolinguistic applications. We test the system on a dataset of the US Southern Shift and compare the results with semi-automated methods.

Introduction. Qualitative changes in the perception of fiction by schoolchildren of different ages pose the task of methodologists to define the concept of "literary development" and its criteria, which to a large extent should determine the direction and methods of studying artistic works. The methods. Definition of the concept of "literary development" and its criteria, which to a large extent should determine the direction and methods of studying artistic works. Results. Need form validation that would test both knowledge and skills, and yet would contain clear criteria for assessing knowledge and skills of students with different level of training, would be consistent with the concept of school literary education and educational standards in the literature, including "Requirements to level of preparation of students". The main school should form an understanding of the specific laws of literature and the nature of its impact on the reader. In grades 5–9, there is a "systematic accumulation of information and ideas related to the generic, genre and stylistic specifics of literature". A graduate of a basic school should become a reader capable of "artistic perception, their own reflections, experiences, associations". The level of literary development of schoolchildren is closely related to their philological abilities, age and individual characteristics, and the effectiveness of educational activities. The most important quality of the reader – the need to Express a feeling, idea, thought in the word, "germination" words in visual, auditory, and other associations, emotional sensitivity to the word, intonation and style of speech, a holistic attitude to the literary work, a General look at its architecture, the conceptual perception of the composition. Originality. The content of literary education of high school students in accordance with these criteria allows us to speak about their readiness for independent re- search work in literature lessons. Conclusion. The level of literary development of schoolchildren is closely related to their philological abili- ties, age and individual characteristics, and the effectiveness of educational activities. The most important quality of the reader – the need to Express a feeling, idea, thought in the word, "germination" words in visual, auditory, and other associations, emotional sensitivity to the word, intonation and style of speech, a holistic attitude to the literary work, a General look at its architecture, the con- ceptual perception of the composition.

Intelligent hybrid system for dark spot detection using SAR data

The geospatial community is moving toward distributed databases and Web services by following the general developments in information and communication technology. The sharing of resources across multiple information communities raises the need of new technologies that support resource discovery and information retrieval. This paper investigates if a common ontology is desirable and feasible for information retrieval in a European spatial data infrastructure. It does so by reviewing relevant literature and proposes an approach for the automatic updating of existing ontologies, designed to facilitate access to multilingual descriptors of geospatial resources. We demonstrate by means of a prototype of an experimental system that the proposed approach is feasible. The experimental system is unique because it integrates a gazetteer, the EuroVoc multilingual vocabulary, the GEMET multilingual thesaurus, an automatic concept space generator, and graph matching into one system. Based on our study, we conclude that it will be impractical to rely only on one common ontology for resource discovery. We also conclude that the approach of using human-created ontologies in combination with automatic concept space generation and associative retrieval is a powerful means to the discovery of geospatial resources. In the absence of a consistent use of semantic Web technologies, a centralized approach to indexing of metadata is required, which has consequences for architectural choices

The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research

The key task of the current stage of the education system development is the task of transition to new methods of organization and support of the educational process, allowing providing high-quality training of graduates with practical knowledge and skills in demand in the labor market. To solve this task is possible only with the use of innovative methods and tools for the creation of information-educational environment in the formation and processing of learning objects and software services distributed in the educational network and allowing the flexible implementation of the processes of educational and methodological support of educational activities. The aim of the research is to determine the possibilities of using the ontological approach to the construction of innovative automated education management systems, including the construction of individual learning trajectories. In this regard, the problem of modeling and algorithmization of the formation of educational programs as a chain of interrelated training modules and objects, taking into account the implementation of a competence-based model of learning in a distributed educational environment of the University, seems to be interesting. The modern education system is to be aimed primarily at adaptive generation of educational content, taking into account the needs of students and in accordance with constantly changing conditions and needs of the labor market. At present, research in this area mainly concerns issues such as the use of multimedia technologies and simulation programs, knowledge testing technologies based on the competency model, methods for measuring the degree of satisfaction with the quality of training, and management methods based on the portfolio of students. These issues and problems are considered with varying degrees of detail, for example, in [1, 2, 3, 4] and other works. The developed methodology for the formation of educational programs is based on the research results of these authors and is developing towards the use of ontologies that can integrate various concepts of professional and educational standards and create on their basis fundamentally new educational modules and objects. In our opinion, it corresponds to world trends in the development of science in this field of knowledge. It is propose d to use the methods and methodologies of knowledge engineering as engineering methods: ontological engineering methods used for semantic modeling of the information and educational environment, allowing to represent the subject area in the form of a set of interconnected ontologies; methods for constructing and visualizing ontologies; methodologies for building databases and knowledge bases and forming complex queries to databases and knowledge bases; methods for semantic analysis of metadata; graph theory. As a result of the analysis of the objects of the information and educational environment, the requirements for the meta-description of educational objects and services are identified, and a description of the concepts of basic ontologies of the informational and educational environment is presented. The article also discusses the possibilities of using modern software for the formation of an intellectual repository of ontologies. Thus, the proposed toolkit for generating educational programs, in our opinion, will allow us to formalize, simplify, and significantly accelerate the process offlexible development of materials necessary for organizing and supporting the educational process. Application of the described approach makes it possible to improve the quality of training of specialists due to the prompt creation of organizational, managerial and educational materials adapted to the requirements of the labor market, taking into account the peculiarities of forms and methods of training.

All features visible in the aerial photographs can be collected by traditional photogrammetric methods; however, such techniques require high operator skills and are very time-consuming. The decision which photogrammetric method uses in mapping is primarily economic, also workload, project deadline requirements and accurate data have to be considered. Up-to-date developed automatic or semi-automatic systems are highly effective for 3D features extraction in urban areas. The investigation objective is the comparison of analytical and digital semi-automatic photogrammetric mapping methods for 3D building models extraction from aerial images analysing in time-consuming and in collected data accuracy consideration.

Among the more recent applications for natural language processing algorithms has been the analysis of spoken language data for diagnostic and remedial purposes, fueled by the demand for simple, objective, and unobtrusive screening tools for neurological disorders such as dementia. The automated analysis of narrative retellings in particular shows potential as a component of such a screening tool since the ability to produce accurate and meaningful narratives is noticeably impaired in individuals with dementia and its frequent precursor, mild cognitive impairment, as well as other neurodegenerative and neurodevelopmental disorders. In this article, we present a method for extracting narrative recall scores automatically and highly accurately from a word-level alignment between a retelling and the source narrative. We propose improvements to existing machine translation-based systems for word alignment, including a novel method of word alignment relying on random walks on a graph that achieves alignment accuracy superior to that of standard expectation maximization-based techniques for word alignment in a fraction of the time required for expectation maximization. In addition, the narrative recall score features extracted from these high-quality word alignments yield diagnostic classification accuracy comparable to that achieved using manually assigned scores and significantly higher than that achieved with summary-level text similarity metrics used in other areas of NLP. These methods can be trivially adapted to spontaneous language samples elicited with non-linguistic stimuli, thereby demonstrating the flexibility and generalizability of these methods.

In order to be able to match correctly the track elements produced by a muon in the Tracker and the Muon System of the CMS experiment [1] the mutual alignment precision between the Tracker and the Barrel Muon System must be no worse than 100-400 micrometers depending on the radial distance of the muon chambers from the Tracker. To fulfill this requirement an alignment system had to be designed. This system contains subsystems for determining the positions of the barrel and endcap chambers while a third one connects these two to the Tracker. Since the Barrel muon chambers are embedded into the magnet yoke of the experiment a nonconventional alignment method had to be developed. In this paper we restrict ourselves to the Barrel Alignment System and the calibration methods of its components.

S-BPM promoters claim a stakeholder perspective for modeling processes and organizational development. By moving actors or active system components to the center of interest, functions and business objects are specified in the context of subjects and their behavior. Although the correspondence to natural language sentence semantics is evident, stakeholders in their routine tasks need to be trained to express their business processes in a subject-oriented way, in particular taking into account task-relevant communication with other stakeholders. Moreover, function-oriented developers need learning support, as S-BPM represents a novel BPM paradigm. Findings from language learning facilitate not only structuring information according to standard sentence semantics, but also designing learning environments through principled S-BPM learning support.

We propose and demonstrate a method of automatic alignment for multiple optical components using a genetic algorithm. The connection between two optical components requires extremely precise alignment in the order of sub-micron-meters. It, therefore, typically takes an experienced technician around 30 to 60 minutes to manually align optical components. Although automatic fiber alignment systems are being developed, they are not practical for use when the degrees of freedom in the alignment of multiple optical components are large. To overcome this difficulty, we have devised a method of automatic alignment for multiple optical components using a genetic algorithm. In a conducted experiment, we successfully connected three optical components within a short span of time (3 minutes) through simultaneous alignment

Engineering education has increasingly become an area of interest at the P-12 level, yet attempts to align engineering knowledge, skills, and habits to existing elementary and secondary educational programming have been parochial in nature (e.g., for a specific context, grade, or initiative). Consequently, a need exists to establish a coherent P-12 content framework for engineering teaching and learning, which would serve as both an epistemological foundation for the subject and a guide for the design of developmentally appropriate educational standards, performance expectations, learning progressions, and assessments. A comprehensive framework for P-12 engineering education would include a compelling rationale and vision for the inclusion of engineering as a compulsory subject, content organization for the dimensions of engineering literacy, and a plan for the realization of this vision. The absence of such a framework could yield inconsistency in authentically educating students in engineering. In response, this study was conducted to establish a taxonomy of concepts related to both engineering knowledge and practices to support the development of a P-12 curricular framework. A modified Delphi method and a series of focus groups—which included teachers, professors, industry professionals, and other relevant stakeholders—were used to reach a consensus on engineering concepts deemed appropriate for secondary study. As a result, a content taxonomy for knowledge and practices appropriate for P-12 engineering emerged through multiple rounds of refinement. This article details the efforts to develop this taxonomy, and discusses how it can be used for standards creation, curriculum development, assessment of learning, and teacher preparation.

Elastic graph matching is one of the most well known techniques for frontal face recognition/verification and one of the few techniques that can be combined successfully with fully automatic face localization and alignment methods. In this paper, we propose an algorithm for finding the most discriminant features upon a person's face and a person-specific graph is placed in the spatial coordinates that correspond to these discriminant features. We illustrate the improvements in performance by applying the proposed method in frontal face verification using the XM2VTS database.

The status quo of operation and maintenance of power optical fiber transmission communication network and the feasibility of using digital means to realize remote operation and maintenance are analyzed in this paper. And the structure mode of optical path self-healing system of power optical fiber network by using mature ideas of SCADA system is also designed. According to the structure of main station, data channel and substation, all functions of each part are studied and realized, such as automatic search and discovery of optical fiber topology resources, automatic adjustment and switching of links, periodic detection of health status of spare fiber cores, remote monitoring of operation process and historical video retrospective functions. The practical results of this paper have considerable innovative value. After popularization and application, it will greatly promote the digital operation and maintenance process of optical fiber communication networks.

PurposeThis paper deals with user‐generated interest indicators (ratings, bookmarks and tags). The authors aim to answer two research questions: Can search strategies based on social information retrieval (SIR) make the discovery of learning resources more efficient for users? Can Community search help users discover a wider variety of cross‐boundary resources?Design/methodology/approachCross‐boundary is defined as that the user and resource come from different countries and that the language of the resource is different from that of the user's mother tongue. The authors focus on a portal that accesses a federation of multilingual learning resource repositories. The authors collect users' attentional metadata based on a server‐side logging scheme and use this empirical data to answer two hypotheses.FindingsThe search‐play‐annotation ratio is more efficient with social information retrieval strategies, but community browsing alone does not help users to discover more cross‐boundary resources.Practical implicationsBy social tagging and bookmarking resources from a variety of repositories, users create underlying connections between resources that otherwise do not cross‐reference, for example, via hyperlinks. This is important for bringing them under the umbrella of SIR methods. Future studies should include testing wider range of SIR methods to leverage these user‐made connections between resources that originate from a number of countries and are in a variety of languages.Originality/valueThe use of attentional metadata to model the ecology of social search adds value to the actors of learning object economy, e.g. educational institutions, digital libraries and their managers, content providers, policy makers, educators and learners.