Semantics - Science topic

I saw your upload video ,its well organized and meaning full..I want to be part of your research works..Can u help me to start my journey.. So that i contribute my first research paper.

Dear Professor Yucong Duan,

I would like to express my admiration for your research on DIKWP Artificial Consciousness. Your work is highly commendable and demonstrates significant potential in the field.

I don't think the English language is set up to nest separate questions this way, at least not to do that and be grammatically correct. It is logical that if someone heard a story about themselves, then the question could always follow, as to what that story was, so these 2 questions can be logically nested.

But I think you're trying to ask "what were the stories, if the person heard stories about themselves ?" But you can't do that by just using "what stories" since it becomes grammatically incorrect, so to be correct you need to use "which questions" but this then becomes a logical problem because "which stories" implies the selection of stories has already been determined, and a choice just needs to be as to which one, which isn't the case here.

If you cannot find a study questionnaire specifically designed for semantic comprehension and online informal language exposure, you have a few options:

1. Modify Existing Questionnaires: Look for existing questionnaires related to semantic comprehension, online language exposure, or related topics such as language attitudes or language use. You can modify these questionnaires to include specific items or sections that address your research objectives regarding semantic comprehension and online informal language exposure.

2. Create Your Own Questionnaire: If existing questionnaires do not cover the specific aspects you are interested in, you can create your own questionnaire from scratch. Start by clearly defining the objectives and research questions of your study. Then, design a set of questions that measure the variables you want to explore, such as semantic comprehension and online informal language exposure. Ensure that the questions are clear, concise, and aligned with your research objectives.

3. Consult with Experts: Seek advice from experts in the field of linguistics or language acquisition. They may be able to provide guidance on questionnaire design or suggest existing measures that could be adapted to your study. Experts can also help ensure that your questionnaire aligns with current research standards and methodologies.

4. Pilot Testing: Before using the questionnaire in your actual study, conduct a pilot test with a small group of participants. This will help identify any issues or areas for improvement, such as ambiguous questions or response options. Based on the feedback from the pilot test, make necessary revisions to enhance the clarity and effectiveness of the questionnaire.

5. Consider Qualitative Approaches: If quantitative questionnaires are not available or suitable for your study, consider incorporating qualitative methods such as interviews or focus groups. These methods can provide in-depth insights into participants' experiences and perceptions related to semantic comprehension and online informal language exposure.

Remember to obtain ethical approval for your study and ensure the confidentiality and anonymity of participants' responses. Additionally, consider the cultural and linguistic diversity of your target population when designing the questionnaire to ensure its relevance and appropriateness.

Oui "quantifier le degré de force de la collocation" et aussi son véritable fonctionnement syntaxique car l'adverbe revêt aussi des fonctions de connecteur à côté des fonctions qui lui sont plus traditionnellement attachées

Remember, typos happen to everyone, and it's essential to handle them with grace and willingness to correct any mistakes. When it comes to dealing with typos, here are a few ethical guidelines to consider:

1. Take responsibility: If you make a typo in your work, acknowledge it and take responsibility for it.

2. Correct when necessary: If a typo changes the meaning of your message or leads to confusion, it's important to correct it. This ensures that your audience understands your intended message accurately.

3. Strive for accuracy: Proofread your work before sharing or publishing it to minimize the chances of typos.

We found differences in the placement of the point of view within an argumentative structure. Chat GPT places it in the conclusion, while the samples of humans we have analyzed position it in the data (Toulmin, 1958)

I suggest: V. Bambini and C. Barattieri di San Pietro (eds.), "Multidisciplinary perspectives on ChatGPT and other Artificial Intelligence Models"

Anton: Excellent response. It's OK if the levels remain separated as long as there is eventually an interface between the two. This is the tricky part.

Rhetoric, oxymore, hyperbole, etc

Dear Vijay Lakshmy K V ,

The reason for your observation is that the paper entitled “MISSION STATEMENT ANALYSIS OF SELECTED PUBLIC SECTOR AND PRIVATE SECTOR BANKS IN INDIA” is not mentioned in Google Scholar. The publisher behind this paper is not indexed in Google Scholar.

You can try the following:

-First add as much as possible the correct info to the paper here on RG (the publishing date, issue nr, vol. nr, pages, order of author(s) etc.)

-Upload your paper to Academia.edu as well, thanks to Anton Vrdoljak there are indications that GS is picking up these papers faster Just select the correct options for free use of Academia.edu

Best regards.

PS. At least one of the papers that cited yours is present here on RG, if you click on references then you see that your paper reference is not recognized by the RG search engine. You might try to add another ‘version’ of your name in order to see whether now does the RG software recognize your paper.

Verbal working memory and semantic working memory are two different components of working memory, which is a cognitive system responsible for temporarily holding and manipulating information for various mental tasks. Here's the difference between them:

According to the Treccani Dictionary (the most authoritative Italian dictionary) rappresentazione is "Il processo mediante il quale un contenuto di percezioni, immaginazioni, giudizi e concetti, si presenta alla coscienza, e quanto viene così rappresentato". Accordingly, 'representation' may apply both to the past and to the future and the re- prefix is no longer bound to its original Lat. meaning "back" --though even in Latin re- did not mean just "back". You may have a mental representation ( immaginazione, Vorstellung) of what will be the situation in Israel next month.

On the other hand, rappresentazione can have a more concrete, physical meaning, exactly as Vorstellung: La rappresentazione alla Scala dello Zauberfluete di Mozart. I do not know whether Engl. representation can have this meaning: I do not think so. As for French, représentation may refer, among many other meanings, to 'Action de donner un spectacle devant un public, en particulier au théâtre' and also to 'Perception, image mentale, etc., dont le contenu se rapporte à un objet, à une situation, à une scène, etc., du monde dans lequel vit le sujet'.

Such an interesting topic. I would be pleased to collaborate if possible. I have expertise in Moroccan Arabic and etymology in Arabic. If relevant, please let me know more about the project.

Semantic segmentation and instance segmentation both heavily rely on convolutional operations, specifically convolutional neural networks (CNNs).

In semantic segmentation, the goal is to assign each pixel in an image to a specific class. This requires analyzing the local context around each pixel, which can be achieved using sliding convolutional filters that scan the entire image. By applying convolutional operations to these filters, the network can learn to detect features such as edges, corners, and textures, which are then used to make predictions about the class of each pixel.

Instance segmentation goes a step further than semantic segmentation by not only assigning each pixel to a specific class but also identifying individual instances of that class. This requires the network to differentiate between objects that may overlap or occlude one another. Similar to semantic segmentation, instance segmentation relies on convolutional operations to analyze the local context around each pixel and identify unique object boundaries.

In summary, both semantic segmentation and instance segmentation rely on convolutional operations to extract relevant features from an image and make accurate predictions about the class and/or instance of each pixel.

Prof. Kallaway me segue no RGate, e eu a ele. Semântica teria mais a ver com pessoas se falando, semântica, a prática da fala, e Lógica tem a ver com filosofia da matematicidade, descartiana, com a verdade de dois mais dois é igual a quatro. Portanto, ter consistência semântica é falar e escrever bem, pragmaticamente, como o grupo quer que se fale, talvez, uma verdade, para aquele grupo.

MAS PARA O GRUPO DOS FILÓSOFOS LÕGICOS, a consistência lógica está acima da existência. Para mim, concordo com estes últimos.

These articles might be helpful....

Kerry Sluchinski You might try the following user-friendly POS taggers/segmenters for Korean language data:

1. KoNLPy: KoNLPy is a Python module for Korean natural language processing. It features a POS tagger as well as numerous tools for Korean language processing. KoNLPy is straightforward and well-documented.

2. KOMORAN: KOMORAN is a Korean morphological analyzer and POS tagger that is free source. It is available as a command-line utility and as a Java library. For testing reasons, KOMORAN offers a user-friendly online interface.

3. Hannanum is a Korean morphological analyzer and POS tagger. It is a Java library that is built on a dictionary-based approach. Hannanum is simple to use and provides a user-friendly online interface for testing.

4. Korean Parser: Korean Parser is a dependency parser and part-of-speech tagger for Korean. It is written in Python and may be used as either a command-line utility or a Python library. Korean Parser is straightforward and well-documented.

5. Lingua-STS: Lingua-STS is a web-based tool for processing Korean language. It features a POS tagger as well as numerous tools for Korean language processing. Lingua-STS is simple to use and features an intuitive online interface.

These tools are all simple to use and may be used to separate Korean text data and conduct POS tagging.

Stoic logic did deal with quantification, but the surviving fragments do not provide a complete picture of their system. However, based on what we do have, it appears that the Stoics used a form of propositional logic that did not include quantifiers. Instead, they relied on various techniques to express the ideas of universality and particularity without using quantifiers.

For example, the Stoics used the concepts of "everything" and "something" to express the ideas of universality and particularity, respectively. They also employed the notion of "correlatives," which are pairs of terms that have a certain logical relationship to each other, such as "master/slave" or "father/son." The Stoics used these correlatives to express universal propositions by saying that something is the correlate of everything, and particular propositions by saying that something is the correlate of something.

Overall, the Stoic treatment of quantification was limited, and it is difficult to determine exactly how they would have dealt with more complex quantificational expressions. However, their focus on universal and particular propositions, as well as their use of correlatives, provides some insight into their approach to quantification.

There has been some discussion about the potential connections between Stoicism and process philosophy, particularly in regards to the Stoic concept of logos and its relationship to Whitehead's process philosophy. Some scholars have argued that the Stoic understanding of logos as an organizing principle that governs the universe can be seen as a precursor to Whitehead's concept of the creative advance of nature, which posits that the universe is constantly evolving and creating new forms of organization.

In addition, some scholars have suggested that the Stoic idea of the unity of all things and the interconnectedness of the universe can be seen as a precursor to the process philosophy concept of interconnectedness and interdependence. However, it should be noted that these connections are speculative and have not been widely accepted in the academic community.

The idea of diagonalization in operad theory has been studied in the literature, although it is typically formulated in terms of "partial compositions" rather than "variable identification" as in your proposed Dij operation.

One approach to diagonalization in operads is to define a "partial composition" operation that takes two elements of an operad P and produces a new element by composing them along a diagonal. More precisely, given elements f ∈ P(m) and g ∈ P(n), we define their diagonal composition f ∘g ∈ P(m+n-1) as follows:

(f ∘g)(x1,...,xm+n-1) = f(x1,...,xi,...,xm,g(i-m+1),...,g(n))

where i is the unique index such that i-m+1 ≤ j < i for all j ∈ {1,...,m+n-1}.

This partial composition operation satisfies some important algebraic properties and has been extensively studied in the context of operad theory. However, it may not be directly applicable to your specific problem of identifying variables in an operad.

Another approach to diagonalization in operad theory involves the use of "modular operads", which are operads that allow for the composition of operations in a non-symmetric fashion. Modular operads provide a powerful framework for studying algebraic structures that arise in geometry, topology, and mathematical physics, and they have been used to study a wide range of phenomena, including Feynman diagrams, string field theory, and knot invariants.

In summary, while the specific operation you propose (Dij : P(n) -> P(n-1)) may not have been studied in the literature, there are related concepts in operad theory that may be useful for your purposes, such as diagonal composition and modular operads. I would recommend exploring these ideas further to see if they can be adapted to your specific problem.

It is possible in YoloV8. YoloV8 is used for real-time classification, segmentation, and both tasks. You can use semantic annotation for YoloV8. You can also use the Roboflow website for this purpose.

As Tomasz Michta wrote, it's worth a try to request. However, unless the book is self-published, the author might not have permission to share it. Generally, the publisher of a book holds the copyright, and the book is not open access. (Publishers, after all, have to cover their not inconsiderable costs.) I like Tomasz Michta 's suggestion to thank a response--whether it is a positive response or a decline to share with explanation.

I start my search with Emerald and ScienceDirect (Elsevier), and then end my search with Google Scholar!

Semantic segmentation is a technique used in image processing and computer vision to identify and classify different objects in an image. It is often used for image recognition tasks, such as character recognition. To use semantic segmentation for character recognition, you would first need to train a semantic segmentation model on a dataset of labeled images that include characters. This would involve feeding the model a large number of images, along with the corresponding labels for each image, so that it can learn to identify and classify different characters.

Once the model is trained, you can then use it to segment characters in new images. This involves providing the model with an input image and asking it to predict the labels for each pixel in the image. The model will then output a segmented image, with each pixel labeled according to the character it belongs to. This can be used to identify and recognize the different characters in the image.

One important thing to note is that semantic segmentation is not a perfect solution for character recognition, and it may not always be able to accurately identify and classify every character in an image. However, it can be a useful tool in certain situations, particularly when combined with other techniques, such as optical character recognition (OCR).

@Sant Gadge Baba Amravati University

Hi Jasna,

Do these papers give you ideas?

Best wishes,

Hello,

I don't know of such a relationship between TR and stimulus duration, but my main concern is whether masking is necessary when evaluating the semantic competition, and if necessary, to get an idea about durations.

King regards

Maryam Tavakol Elahi Take a look

Jiaying Ye, I am including the following open access articles for your consideration.

Christianson, K., Hollingworth, A., Halliwell, J. F., & Ferreira, F. (2001). Thematic roles assigned along the garden path linger. Cognitive psychology, 42(4), 368-407. http://www2.psychology.uiowa.edu/faculty/hollingworth/documents/Christetal_CogPsych01.pdf

Christianson, K., Williams, C. C., Zacks, R. T., & Ferreira, F. (2006). Younger and older adults "good-enough" interpretations of garden-path sentences. Discourse processes, 42(2), 205-238. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1761649/

Farmer, T. A., Anderson, S. E., & Spivey, M. J. (2007). Gradiency and visual context in syntactic garden-paths. Journal of memory and language, 57(4), 570-595. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2084067/

Ferreira, F., Christianson, K., & Hollingworth, A. (2001). Misinterpretations of garden-path sentences: Implications for models of sentence processing and reanalysis. Journal of psycholinguistic research, 30(1), 3-20. https://d1wqtxts1xzle7.cloudfront.net/30937949/Ferreira_etal_2001-with-cover-page-v2.pdf?Expires=1667579002&Signature=TNxK2IHAg39QuBAy5msOW~mDNCeds1mpF5wU3Ks3ty9HPNsIQWddC-Yl9rL2d-JS~-JenNe7P941dJ7Aghem9OGx0c-4l1KjKH0EkmWNtFWX1LJ3fWtFA-Cum5kPJOVj5ogD9pBCvSc2G9i1ElmsDTLEFYTOJskq6zZgjqube27HJgjw92RpNRkiOApJdot~eHRNovrwNO2JaKexyhm3I3D-hoSInkMG0HIMjMouGn5s2kJEsTwjAxYC0d-VaUcCZ~avFazT3V5IFS3xJnp-K3v4jviUEWjfwFr-PGTGXJsQFIS1Ms1SvFWF1V4DVI43XTi2G-xjJHM0yzHRDsF6Cw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA

Malaia, E., Wilbur, R. B., & Weber-Fox, C. (2009). ERP evidence for telicity effects on syntactic processing in garden-path sentences. Brain and language, 108(3), 145-158. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720995/

Kaan, E., & Swaab, T. Y. (2003). Repair, revision, and complexity in syntactic analysis: An electrophysiological differentiation. Journal of cognitive neuroscience, 15(1), 98-110. https://pages.ucsd.edu/~scoulson/CNL/kaan-p600.pdf

Kemper, S., Crow, A., & Kemtes, K. (2004). Eye-fixation patterns of high-and low-span young and older adults: down the garden path and back again. Psychology and Aging, 19(1), 157. https://kuscholarworks.ku.edu/bitstream/handle/1808/8605/Kemper%20Eye%20Fixation%20author%20final.pdf?sequence=1&isAllowed=y

Kidd, E., Stewart, A. J., & Serratrice, L. (2011). Children do not overcome lexical biases where adults do: The role of the referential scene in garden-path recovery. Journal of Child Language, 38(1), 222-234. https://pure.mpg.de/rest/items/item_2495736/component/file_2495759/content

Lin, C. J. C., & Bever, T. G. (2010). Garden path and the comprehension of head-final relative clauses. In Processing and producing head-final structures (pp. 277-297). Springer, Dordrecht. https://www.researchgate.net/profile/Chien-Jer-Lin/publication/226996824_Garden_Path_and_the_Comprehension_of_Head-Final_Relative_Clauses/links/02e7e5184bd3cf086b000000/Garden-Path-and-the-Comprehension-of-Head-Final-Relative-Clauses.pdf

Slattery, T. J., Sturt, P., Christianson, K., Yoshida, M., & Ferreira, F. (2013). Lingering misinterpretations of garden path sentences arise from competing syntactic representations. Journal of Memory and Language, 69(2), 104-120. eprints.bournemouth.ac.uk/22639/3/SlatteryetalJML3final.docx.pdf

We in USW Ltd work on creating smart systems, which is obviously related to a semantics processing.

We work with graph organized data since 1997 year. This experience helped us to define the so called by us Semantic Network Based Architecture -https://www.researchgate.net/publication/334680146_Semantic_Network_Based_Architecture. Using this architecture we developed our Unified Platform for Innovations(UPI). Till now we built two UPI-based workflow management systems- one for administration (Smart DOCMAN), and a second for the industry. A general presentation can be found on www.usw.bg.

Currently we work on tools and technologies in UPI-environment, ensuring us to make our systems “smart”. Clearing our understanding about semantics, concepts, data and so on, we have reached to our definition for KG and the idea, that the KG has to be unified- Unified Knowledge Graph (uKG)- https://www.researchgate.net/publication/361532200_Unified_Knowledge_Graph.

Our next step was to clear our understanding about semantic constructions, which led us to the concept for The Ontology as a Unified Knowledge Graph construction- https://www.researchgate.net/publication/361813986_The_Ontology_as_a_Unified_Knowledge_Graph_construction.

We think, that smart systems have not to be learned, they have to be educated, as is described in Root Language and Machine Education- https://www.researchgate.net/publication/361814428_Root_Language_and_Machine_Education.

شليحي الصالح What are the details of the process of interest to you?

Agreeableness: 1. I Sympathize with others’ feelings

Openness to experience: 1. I Have a vivid imagination.

Perceived consumer effectiveness (Roberts, 1996) 1. It is worthless for the individual consumer to do anything about pollution.

Hi! This is the first of the topics that we talk about in the following podcast: https://youtu.be/LyIINgdVQ8Y

The short answer is that the communication of data and the use of that data within an application is co-optimized, so that we only communicate what is needed and measure performance of the communications based on the end-user application.

Node level attention aims to learn the importance between nodes and their neighbors based on meta-paths, while semantic level attention can learn the importance of different meta-paths.

I think for sentence clustering it is better to use Sentence-BERT model a modified version of BERT based on siamese network, which very suitable for sentence clustering. Please refer to the original paper of sentence- bert

You could train a machine learning algorithm, for example a neural network, to do this, by using a corpus of raw text as the input and splitted sentences as the output.

That said, I think the models from the spacy library in python https://spacy.io do a pretty good job. I'm quite sure they can handle cases where somebody forgot to put a blank space between sentences quite accurately. Just use the default settings when calling the function nlp(text).

Yes amazing topic and a great question even I was trying to get some data and would be really helpful for one of my research if you come across any details or the data meanwhile I just gone thru the details shared by Bruno De Lièvre and yes the thesis is of great helpful to me

Dear Sven Beecken

I'm sorry I can't say anything about Chomsky's claims, but I'd like to try to add a few things to the discussion. Frege did not establish that words correspond to things but that it is possible to differentiate, within the meaning, between sense and reference; that is, "the morning star" and "the evening star" are two expressions that have different meanings (for example, because one alludes to morning situations and the other does not) but name, designate or refer to the same object or referent (the planet Venus). It must be said, however, that in order to metalinguistically affirm that these two expressions designate the same object, it is necessary to assume an ontology according to which what is seen in the morning and in the afternoon is the same thing; that is, when Cicero wrote De natura deorum, alluding to the morning star (Phosphorus, Lucero or Lucifer) and the evening star (Vesperus or Hespero) as two different entities, the Fregean distinction could have been made but not with these examples. What Tarski does - which to me has little to do with this semantic distinction - is to provide a criterion for any definition of truth in the "material" correspondence sense (in the sense of correspondence to extralinguistic reality), using a formula for expressions different level linguistic sentences (for a metalinguistic sentence and an object sentence): "X is true if and only if p", which is typically exemplified by the famous sentence "'Snow is white' is a true sentence if and only if snow is white". However, in the text itself, where he states that "truth" is a semantic term, he refers to "the truth" as if it were some kind of substance or entity and -fundamentally- as if it were the same as speaking of a term or a definition, which in my opinion rather obscures his claims. But, furthermore, since it can also be said " 'Nothing nothings' is a true sentence if and only if nothing nothings", it seems to me that the formula has much the aspect of a circular or tautological logical device and that, most importantly, which is to explain why a "material" sentence is true and what exactly it means to correspond to a fact precisely remains unexplained.

Also -and despite Chomsky's affirmations-, one must not confuse the thesis that natural language has no reference with the one that it does not describe in the material sense (that it does not describe facts that actually exist), because these affirmations are not equivalents. To speak of reference is to speak of language, and only of language. It can be said that a term or a sentence refers and that does not commit one to the affirmation that this referent exists beyond language, that it can be sustained or not. On the other hand, when it is affirmed that a thing exists or that an event occurs, we are not talking about language, but about a part of the extralinguistic reality that is assumed to exist. For example, and given the Fregean distinction, it can be said that the phlogiston theory refers, because the phlogiston theory is language and the reference is a semantic relation: the phlogiston is the object to which it alludes (its referent), and that in her the term "phlogiston" has a certain meaning, and to say at the same time that her affirmations do not describe any fact or any entity of the world (that phlogiston does not exist), and in the first case, from our metalanguage something is affirmed about a language object (the phlogiston theory) but when it is said that there is no entity in the world that is phlogiston, one is not talking about language and, therefore, nothing is being said about semantic relations. Now, the thesis that natural language does not have a descriptive function, or does not describe extralinguistic facts or entities and properties, has been confuted in various ways, fundamentally assuming different assumptions about its nature, for example, by pragmatist, neopragmatist arguments, by those who maintain that languages ​​are acts or actions, etc. In an article on the beginnings of the Vienna Circle, Carl Hempel says that the thesis that there could be a correspondence between language and facts was already rejected because they were things of a different nature between which there was an "abyss". Perhaps a quick way to express it is to say that there will always be an insurmountable metaphysical difference between the word table, with its meaning, and table, and for some authors that means that "correspondence" is impossible. If you want to complicate things further, a Kantian or neo-Kantian might say that correspondence with facts is impossible because at best there may be a correspondence with what appears to us as facts in the mind.

If we are talking about language, reference and correspondence with facts, it can be problematic to offer arguments that speak of perceptions or words as mental states, since there are several arguments that have opposed the thesis of the mental or internal nature of language natural, from the sciences considering that it is a system of (physical) signs that responds to certain rules and is intended for communication between speakers, and from philosophy authors such as Reichenbach or Carnap have considered that it is not mental, and even Karl Popper has been emphatic about it, considering that it is abstract in nature. Another way of understanding it is by thinking that natural language is a collective evolutionary product of a species of animals, that words and meanings existed before any of us, that we have simply learned to reproduce it in consciousness and use it. That is, is this a philosophy of language debate or a philosophy of mind debate? Thank you.

You can't combine them in a single value. Each scale has a meaning and interpretation different from the other. What you may do is to convert values in each scale into one standard scale such as percentile, Likert, Z or T, so that the differences values become comparable.

You can also download Louw's (2000) Contextual prosodic theory: Bringing semantic prosodies to life, and Rundell's (2018) Searching for extended units of meaning—and what to do when you find them, from the following links:

Best regards.

To start our collaborative work, I'll let you propose a case study and we shall try together to apply the knowledge acquired through modelling: what are the challenge facing humanity today: 1) covid 19, 2) Climate change 3) wars in the middle east? but I won't accept to make you select one of these three proposals, since collaborative work requires to share our knowledge equally, should we succeed that should be a great achievement, thank you

Dear Researcher,

Please refer to the below links for GeoNetwork Metadata plugins @ OWL Resources. I think this might be helpful.

https://trac.osgeo.org/geonetwork/wiki/rdfstore

Dear Emma,

I think the following article might be of help. Although most articles on the topic I came across are focused on animals and fruits, the following one includes clothes as well.

Kind regards

Nibras Husein Mhawesh – that is not an answer, that is spam. Please do not reply to questions unless you have something to contribute. If you are trying to improve your RG score, you are going about it the wrong way. You are simply looking foolish. I note that you have left this "answer" on about 90 questions so far. That's enough. RG is for research.

thisdict = { "brand": "Ford", "model": "Mustang", "year": 1964 }

I have no good idea on this and want to know from others.

Thanks!

Thank you for your answer Nawel Zaatout. However, the most important databases actually vary depending on geographical location, language and field of research. Salatino & Ruiz (2021) have conducted an empirical research on 10.104 scientific journals from Latin America and showed that, for this group of journals, the most important databases are Latindex, DOAJ, Redalyc and Scielo.

Salatino, M., & Ruiz, O. L. (2021). El fetichismo de la indexación. Una crítica latinoamericana a los regímenes de evaluación de la ciencia mundial. Revista Iberoamericana de Ciencia, Tecnología y Sociedad, 16(46), 73–100. http://ojs.revistacts.net/index.php/CTS/article/view/212

Look at the journals listed in the bibliography of the entry for "Intensional Logic" in the Stanford Encyclopedia of Philosophy:

Some more recent work by Bealer is also referenced.

I would offer you our approach for semantics representation which you can find in https://www.researchgate.net/publication/340886106_Semantics_representation_regarding_establishing_and_maintaining_a_Semantic_Interoperability_in_the_e-Governance's_environment.

It is seems to be of both syntactic and semantic nature: classes of vebs are made on the basis of shared semantic and syntactic behaviour.

I think the best way is to use the results of the semantic segmentation and samples of leaves from fieldwork to create your mathematical expression using any curve fitting mathematical tool.

pls see this paper

Here is a PowerPoint about "Plant and Food Metaphors." Best of luck with your research.

Semantics is long-term and theoretical; pragmatics is here-and-now, practical, applied. There are many different types of context, linguistic, musical, geographical, historical, cultural, etc., and Pragmatics deals with these contexts in terms of HERE AND NOW. Semantics is able to transcend from the here-and-now to deal with these issues in a broader sense. Here is a PowerPoint on "Semantics," and one on "Pragmatics." These PowerPoints illustrate this distinction.

Thank you so much, Mr.Nilsen, I just had an overview, it perturbs the logic succinctly.

Play is an extremely important aspect of children's development, and adult development as well. Associated with play is laughter (mainly a public phenomienon), and smililng (mainly an individual phenomenon). Here is a PowerPoint about "Play," one about "Laughter and Smiling," and one about "Humor and Education." Enjoy:

Prasath Sivasubramanian Thank you for your answer, it seems like all Javascript tools listed on w3.org aren't maintained anymore though. Like Hercules last released was in 2009, OAT is not reachable anymore...

The Eye (https://github.com/josd/eye) engine looks quite interesting I wonder if it's comparable to https://github.com/ucbl/HyL ?

Thanks to all

In the Arabic language the meaning of these words is determined by the context in which they are spoken and not in the lexical or semantic sense, and in some contexts (emotional, Situational , linguistic, cultural) 'hear/listen' meaning 'be effective/work'

Dear Nshimyimana Dominique

that mean your dataset is imbalanced-classes. there are a confusion matrix and geometric mean for measuring performance of model. Also, this article may help you how to evaluate ur model.

A Unified Architecture for Semantic Role Labeling and Relation Classification Jiang Guo, Wanxiang Che, Haifeng Wang , Ting Liu and Jun Xu

IOU region overlapping ratio

Could you just say: my plate has plain plasta?

Hello David,

Thank you for your input. In the above research problem, that has been solved a while ago, the dummy variables have to be treated as binary. This is because each one of the disease dimensions (chronicity/persistence) needs to be represented as a separate variable in the dataset. Apparently, the model coefficients are required in order to understand the "contribution" that each of those dimensions have on the outcome under study (dependent variable).

My question was primarily a logical/philosophical one, rather than a statistical:

If a variable contains information which is a dimension of another variable [e.g: "Type of diabetes (1/2)" is a dimension of "Diabetes (y/n)"], these two variables need to be included to the model because we need to know (1) the contribution of the presence of diabetes and ALSO (2) the contribution of different diabetes types, to, (for instance) the development of heart disease.

As a sidenote, I believe the role of this forum is beyond recommending a list of textbooks, but to provide meaningful insights and suggestions. With all respect.

Dear Abdul Sattar

You may read the article below, which I think can help you . Please, if still interested, send me an email by RG, since it is in private mode due to copyright.

Sincerely,

Luis

That seems to be possible only if the authors of the works that cited you add their research onto ResearchGate and/or vice versa. RG counts citations through scanning the texts uploaded onto its own database. Regards.