This document summarizes previous research on automatic term extraction from text. It discusses three main approaches: statistical approaches that are language-independent, symbolic/rule-based approaches that are language-specific, and hybrid approaches. Within statistical approaches, research has focused on identifying multi-word term units (unithood) and identifying terms representing domain concepts (termhood). Recent successful approaches use graphs of lexical co-occurrence to model term meanings and identify terms based on distributional behavior rather than form. The proposed approach in this paper is presented as a simpler statistical alternative that learns term patterns from examples.
Taxonomy extraction from automotive natural language requirements using unsup...ijnlc
In this paper we present a novel approach to semi-automatically learn concept hierarchies from natural
language requirements of the automotive industry. The approach is based on the distributional hypothesis
and the special characteristics of domain-specific German compounds. We extract taxonomies by using
clustering techniques in combination with general thesauri. Such a taxonomy can be used to support
requirements engineering in early stages by providing a common system understanding and an agreedupon
terminology. This work is part of an ontology-driven requirements engineering process, which builds
on top of the taxonomy. Evaluation shows that this taxonomy extraction approach outperforms common
hierarchical clustering techniques.
Improving a Lightweight Stemmer for Gujarati Languageijistjournal
The origin of route of text mining is the process of stemming. It is usually used in several types of applications such as Natural Language Processing (NLP), Information Retrieval (IR) and Text Mining (TM) including Text Categorization (TC), Text Summarization (TS). Establish a stemmer effective for the language of Gujarati has been always a search domain hot since the Gujarati has a very different structure and difficult that the other language due to the rich morphology.
Dictionary based concept mining an application for turkishcsandit
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
In recent years, great advances have been made in the speed, accuracy, and coverage of automatic word
sense disambiguator systems that, given a word appearing in a certain context, can identify the sense of
that word. In this paper we consider the problem of deciding whether same words contained in different
documents are related to the same meaning or are homonyms. Our goal is to improve the estimate of the
similarity of documents in which some words may be used with different meanings. We present three new
strategies for solving this problem, which are used to filter out homonyms from the similarity computation.
Two of them are intrinsically non-semantic, whereas the other one has a semantic flavor and can also be
applied to word sense disambiguation. The three strategies have been embedded in an article document
recommendation system that one of the most important Italian ad-serving companies offers to its customers
DICTIONARY-BASED CONCEPT MINING: AN APPLICATION FOR TURKISHcscpconf
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
In recent years, great advances have been made in the speed, accuracy, and coverage of automatic word
sense disambiguator systems that, given a word appearing in a certain context, can identify the sense of
that word. In this paper we consider the problem of deciding whether same words contained in different
documents are related to the same meaning or are homonyms. Our goal is to improve the estimate of the
similarity of documents in which some words may be used with different meanings. We present three new
strategies for solving this problem, which are used to filter out homonyms from the similarity computation.
Two of them are intrinsically non-semantic, whereas the other one has a semantic flavor and can also be
applied to word sense disambiguation. The three strategies have been embedded in an article document
recommendation system that one of the most important Italian ad-serving companies offers to its customers.
Taxonomy extraction from automotive natural language requirements using unsup...ijnlc
In this paper we present a novel approach to semi-automatically learn concept hierarchies from natural
language requirements of the automotive industry. The approach is based on the distributional hypothesis
and the special characteristics of domain-specific German compounds. We extract taxonomies by using
clustering techniques in combination with general thesauri. Such a taxonomy can be used to support
requirements engineering in early stages by providing a common system understanding and an agreedupon
terminology. This work is part of an ontology-driven requirements engineering process, which builds
on top of the taxonomy. Evaluation shows that this taxonomy extraction approach outperforms common
hierarchical clustering techniques.
Improving a Lightweight Stemmer for Gujarati Languageijistjournal
The origin of route of text mining is the process of stemming. It is usually used in several types of applications such as Natural Language Processing (NLP), Information Retrieval (IR) and Text Mining (TM) including Text Categorization (TC), Text Summarization (TS). Establish a stemmer effective for the language of Gujarati has been always a search domain hot since the Gujarati has a very different structure and difficult that the other language due to the rich morphology.
Dictionary based concept mining an application for turkishcsandit
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
In recent years, great advances have been made in the speed, accuracy, and coverage of automatic word
sense disambiguator systems that, given a word appearing in a certain context, can identify the sense of
that word. In this paper we consider the problem of deciding whether same words contained in different
documents are related to the same meaning or are homonyms. Our goal is to improve the estimate of the
similarity of documents in which some words may be used with different meanings. We present three new
strategies for solving this problem, which are used to filter out homonyms from the similarity computation.
Two of them are intrinsically non-semantic, whereas the other one has a semantic flavor and can also be
applied to word sense disambiguation. The three strategies have been embedded in an article document
recommendation system that one of the most important Italian ad-serving companies offers to its customers
DICTIONARY-BASED CONCEPT MINING: AN APPLICATION FOR TURKISHcscpconf
In this study, a dictionary-based method is used to extract expressive concepts from documents.
So far, there have been many studies concerning concept mining in English, but this area of
study for Turkish, an agglutinative language, is still immature. We used dictionary instead of
WordNet, a lexical database grouping words into synsets that is widely used for concept
extraction. The dictionaries are rarely used in the domain of concept mining, but taking into
account that dictionary entries have synonyms, hypernyms, hyponyms and other relationships in
their meaning texts, the success rate has been high for determining concepts. This concept
extraction method is implemented on documents, that are collected from different corpora.
In recent years, great advances have been made in the speed, accuracy, and coverage of automatic word
sense disambiguator systems that, given a word appearing in a certain context, can identify the sense of
that word. In this paper we consider the problem of deciding whether same words contained in different
documents are related to the same meaning or are homonyms. Our goal is to improve the estimate of the
similarity of documents in which some words may be used with different meanings. We present three new
strategies for solving this problem, which are used to filter out homonyms from the similarity computation.
Two of them are intrinsically non-semantic, whereas the other one has a semantic flavor and can also be
applied to word sense disambiguation. The three strategies have been embedded in an article document
recommendation system that one of the most important Italian ad-serving companies offers to its customers.
A SURVEY OF GRAMMAR CHECKERS FOR NATURAL LANGUAGEScsandit
ABSTRACT
Natural Language processing is an interdisciplinary branch of linguistic and computer science studied under the Artificial Intelligence (AI) that gave birth to an allied area called
‘Computational Linguistic’ which focuses on processing of natural languages on computational devices. A natural language consists of a large number of sentences which are linguistic units involving one or more words linked together in accordance with a set of predefined rules called grammar. Grammar checking is the task of validating sentences syntactically and is a prominent tool within language engineering. Our review draws on the recent development of various grammar checkers to look at past, present and the future in a new light. Our review covers grammar checkers of many languages with the aim of seeking their approaches, methodologies for developing new tool and system as a whole. The survey concludes with the discussion of various features included in existing grammar checkers of foreign languages as well as a few Indian Languages.
Design of A Spell Corrector For Hausa LanguageWaqas Tariq
In this article, a spell corrector has been designed for the Hausa language which is the second most spoken language in Africa and do not yet have processing tools. This study is a contribution to the automatic processing of the Hausa language. We used existing techniques for other languages and adapted them to the special case of the Hausa language. The corrector designed operates essentially on Mijinguini’s dictionary and characteristics of the Hausa alphabet. After a brief review on spell checking and spell correcting techniques and the state of art in the Hausa language processing, we opted for the data structures trie and hash table to represent the dictionary. The edit distance and the specificities of the Hausa alphabet have been used to detect and correct spelling errors. The implementation of the spell corrector has been made on a special editor developed for that purpose (LyTexEditor) but also as an extension (add-on) for OpenOffice.org. A comparison was made on the performance of the two data structures used.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages
around the world, research in WSD has been conducted upto different extents. In this paper, we have gone
through a survey regarding the different approaches adopted in different research works, the State of the
Art in the performance in this domain, recent works in different Indian languages and finally a survey in
Bengali language. We have made a survey on different competitions in this field and the bench mark
results, obtained from those competitions.
Smart grammar a dynamic spoken language understanding grammar for inflective ...ijnlc
Spoken language understanding (SLU) is a key requirement of spoken dialogue systems (SDS). The role of
SLU parser is to robustly interpret the meanings of users’ utterance using a hand-crafted grammar that is
expensive to build. This task becomes even harder when the developer is creating a SLU grammar for
inflectional languages due to the different conjugations and declensions. This causes long grammar
definition files that are hard to structure and also to manage. In this paper, we propose a new and
alternative method, called Smart Grammar to facilitate the development of speech enabled applications.
This uses a morphological analyzer, in addition to the semantic parser, in order to convert each user
utterance in the canonical form.
Building of Database for English-Azerbaijani Machine Translation Expert SystemWaqas Tariq
In the article the results of development of machine translation expert system is presented. The approach of translation correspondences defining is suggested as a background for creation of data base and knowledge base of the system. Methods of transformation rules compiling applied for linguistic knowledge base of the expert system are based on the defining of translation correspondences between Azerbaijani and English languages.
A COMPREHENSIVE ANALYSIS OF STEMMERS AVAILABLE FOR INDIC LANGUAGES ijnlc
Stemming is the process of term conflation. It conflates all the word variants to a common form called as stem. It plays significant role in numerous Natural Language Processing (NLP) applications like morphological analysis, parsing, document summarization, text classification, part-of-speech tagging, question-answering system, machine translation, word sense disambiguation, information retrieval (IR), etc. Each of these tasks requires some pre-processing to be done. Stemming is one of the important building blocks for all these applications. This paper, presents an overview of various stemming techniques, evaluation criteria for stemmers and various existing stemmers for Indic languages.
Phrase Identification is one of the most critical and widely studied in Natural Language processing (NLP) tasks. Verb Phrase Identification within a sentence is very useful for a variety of application on NLP. One of the core enabling technologies required in NLP applications is a Morphological Analysis. This paper presents the Myanmar Verb Phrase Identification and Translation Algorithm and develops a Markov Model with Morphological Analysis. The system is based on Rule-Based Maximum Matching Approach. In Machine Translation, Large amount of information is needed to guide the translation process. Myanmar Language is inflected language and there are very few creations and researches of Lexicon in Myanmar, comparing to other language such as English, French and Czech etc. Therefore, this system is proposed Myanmar Verb Phrase identification and translation model based on Syntactic Structure and Morphology of Myanmar Language by using Myanmar- English bilingual lexicon. Markov Model is also used to reformulate the translation probability of Phrase pairs. Experiment results showed that proposed system can improve translation quality by applying morphological analysis on Myanmar Language.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Emotional telugu speech signals classification based on k nn classifiereSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Emotional telugu speech signals classification based on k nn classifiereSAT Journals
Abstract Speech processing is the study of speech signals, and the methods used to process them. In application such as speech coding, speech synthesis, speech recognition and speaker recognition technology, speech processing is employed. In speech classification, the computation of prosody effects from speech signals plays a major role. In emotional speech signals pitch and frequency is a most important parameters. Normally, the pitch value of sad and happy speech signals has a great difference and the frequency value of happy is higher than sad speech. But, in some cases the frequency of happy speech is nearly similar to sad speech or frequency of sad speech is similar to happy speech. In such situation, it is difficult to recognize the exact speech signal. To reduce such drawbacks, in this paper we propose a Telugu speech emotion classification system with three features like Energy Entropy, Short Time Energy, Zero Crossing Rate and K-NN classifier for the classification. Features are extracted from the speech signals and given to the K-NN. The implementation result shows the effectiveness of proposed speech emotion classification system in classifying the Telugu speech signals based on their prosody effects. The performance of the proposed speech emotion classification system is evaluated by conducting cross validation on the Telugu speech database. Keywords: Emotion Classification, K-NN classifier, Energy Entropy, Short Time Energy, Zero Crossing Rate.
Query Answering Approach Based on Document SummarizationIJMER
The growing of online information obliged the availability of a thorough research in the
domain of automatic text summarization within the Natural Language Processing (NLP)
community.The aim of this paper is to propose a novel approach for a language independent automatic
summarization approach that combines three main approaches. The Rhetorical Structure Theory
(RST), the query processing approach, and the Network Representationapproach (NRA). RST, as a
theory of major aspect for the structure of natural text, is used to extract the semantic relation behind
the text.Query processing approachclassifies the question type and finds the answer in a way that suits
the user’s needs. The NRA is used to create a graph representing the extracted semantic relation. The
output is an answer, which not only responses to the question, but also gives the user an opportunity to
find additional information that is related to the question.We implemented the proposed approach. As a
case study, the implemented approachis applied on Arabic text in the agriculture field. The
implemented approach succeeded in summarizing extension documents according to user's query. The
approach results have been evaluated using Recall, Precision and F-score measures.
A SURVEY OF GRAMMAR CHECKERS FOR NATURAL LANGUAGEScsandit
ABSTRACT
Natural Language processing is an interdisciplinary branch of linguistic and computer science studied under the Artificial Intelligence (AI) that gave birth to an allied area called
‘Computational Linguistic’ which focuses on processing of natural languages on computational devices. A natural language consists of a large number of sentences which are linguistic units involving one or more words linked together in accordance with a set of predefined rules called grammar. Grammar checking is the task of validating sentences syntactically and is a prominent tool within language engineering. Our review draws on the recent development of various grammar checkers to look at past, present and the future in a new light. Our review covers grammar checkers of many languages with the aim of seeking their approaches, methodologies for developing new tool and system as a whole. The survey concludes with the discussion of various features included in existing grammar checkers of foreign languages as well as a few Indian Languages.
Design of A Spell Corrector For Hausa LanguageWaqas Tariq
In this article, a spell corrector has been designed for the Hausa language which is the second most spoken language in Africa and do not yet have processing tools. This study is a contribution to the automatic processing of the Hausa language. We used existing techniques for other languages and adapted them to the special case of the Hausa language. The corrector designed operates essentially on Mijinguini’s dictionary and characteristics of the Hausa alphabet. After a brief review on spell checking and spell correcting techniques and the state of art in the Hausa language processing, we opted for the data structures trie and hash table to represent the dictionary. The edit distance and the specificities of the Hausa alphabet have been used to detect and correct spelling errors. The implementation of the spell corrector has been made on a special editor developed for that purpose (LyTexEditor) but also as an extension (add-on) for OpenOffice.org. A comparison was made on the performance of the two data structures used.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages
around the world, research in WSD has been conducted upto different extents. In this paper, we have gone
through a survey regarding the different approaches adopted in different research works, the State of the
Art in the performance in this domain, recent works in different Indian languages and finally a survey in
Bengali language. We have made a survey on different competitions in this field and the bench mark
results, obtained from those competitions.
Smart grammar a dynamic spoken language understanding grammar for inflective ...ijnlc
Spoken language understanding (SLU) is a key requirement of spoken dialogue systems (SDS). The role of
SLU parser is to robustly interpret the meanings of users’ utterance using a hand-crafted grammar that is
expensive to build. This task becomes even harder when the developer is creating a SLU grammar for
inflectional languages due to the different conjugations and declensions. This causes long grammar
definition files that are hard to structure and also to manage. In this paper, we propose a new and
alternative method, called Smart Grammar to facilitate the development of speech enabled applications.
This uses a morphological analyzer, in addition to the semantic parser, in order to convert each user
utterance in the canonical form.
Building of Database for English-Azerbaijani Machine Translation Expert SystemWaqas Tariq
In the article the results of development of machine translation expert system is presented. The approach of translation correspondences defining is suggested as a background for creation of data base and knowledge base of the system. Methods of transformation rules compiling applied for linguistic knowledge base of the expert system are based on the defining of translation correspondences between Azerbaijani and English languages.
A COMPREHENSIVE ANALYSIS OF STEMMERS AVAILABLE FOR INDIC LANGUAGES ijnlc
Stemming is the process of term conflation. It conflates all the word variants to a common form called as stem. It plays significant role in numerous Natural Language Processing (NLP) applications like morphological analysis, parsing, document summarization, text classification, part-of-speech tagging, question-answering system, machine translation, word sense disambiguation, information retrieval (IR), etc. Each of these tasks requires some pre-processing to be done. Stemming is one of the important building blocks for all these applications. This paper, presents an overview of various stemming techniques, evaluation criteria for stemmers and various existing stemmers for Indic languages.
Phrase Identification is one of the most critical and widely studied in Natural Language processing (NLP) tasks. Verb Phrase Identification within a sentence is very useful for a variety of application on NLP. One of the core enabling technologies required in NLP applications is a Morphological Analysis. This paper presents the Myanmar Verb Phrase Identification and Translation Algorithm and develops a Markov Model with Morphological Analysis. The system is based on Rule-Based Maximum Matching Approach. In Machine Translation, Large amount of information is needed to guide the translation process. Myanmar Language is inflected language and there are very few creations and researches of Lexicon in Myanmar, comparing to other language such as English, French and Czech etc. Therefore, this system is proposed Myanmar Verb Phrase identification and translation model based on Syntactic Structure and Morphology of Myanmar Language by using Myanmar- English bilingual lexicon. Markov Model is also used to reformulate the translation probability of Phrase pairs. Experiment results showed that proposed system can improve translation quality by applying morphological analysis on Myanmar Language.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Emotional telugu speech signals classification based on k nn classifiereSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Emotional telugu speech signals classification based on k nn classifiereSAT Journals
Abstract Speech processing is the study of speech signals, and the methods used to process them. In application such as speech coding, speech synthesis, speech recognition and speaker recognition technology, speech processing is employed. In speech classification, the computation of prosody effects from speech signals plays a major role. In emotional speech signals pitch and frequency is a most important parameters. Normally, the pitch value of sad and happy speech signals has a great difference and the frequency value of happy is higher than sad speech. But, in some cases the frequency of happy speech is nearly similar to sad speech or frequency of sad speech is similar to happy speech. In such situation, it is difficult to recognize the exact speech signal. To reduce such drawbacks, in this paper we propose a Telugu speech emotion classification system with three features like Energy Entropy, Short Time Energy, Zero Crossing Rate and K-NN classifier for the classification. Features are extracted from the speech signals and given to the K-NN. The implementation result shows the effectiveness of proposed speech emotion classification system in classifying the Telugu speech signals based on their prosody effects. The performance of the proposed speech emotion classification system is evaluated by conducting cross validation on the Telugu speech database. Keywords: Emotion Classification, K-NN classifier, Energy Entropy, Short Time Energy, Zero Crossing Rate.
Query Answering Approach Based on Document SummarizationIJMER
The growing of online information obliged the availability of a thorough research in the
domain of automatic text summarization within the Natural Language Processing (NLP)
community.The aim of this paper is to propose a novel approach for a language independent automatic
summarization approach that combines three main approaches. The Rhetorical Structure Theory
(RST), the query processing approach, and the Network Representationapproach (NRA). RST, as a
theory of major aspect for the structure of natural text, is used to extract the semantic relation behind
the text.Query processing approachclassifies the question type and finds the answer in a way that suits
the user’s needs. The NRA is used to create a graph representing the extracted semantic relation. The
output is an answer, which not only responses to the question, but also gives the user an opportunity to
find additional information that is related to the question.We implemented the proposed approach. As a
case study, the implemented approachis applied on Arabic text in the agriculture field. The
implemented approach succeeded in summarizing extension documents according to user's query. The
approach results have been evaluated using Recall, Precision and F-score measures.
Similar to A statistical approach to term extraction.pdf (20)
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.