The statistic shows the meaning of term “financial peace of mind” to Americans as of 2016. In that year, ** percent of the respondents defined financial peace of mind as the ability to live comfortably within their means.

Percentage of persons aged 15 years and over by level of sense of meaning and purpose, by gender, for Canada, regions and provinces.

The coordinates above and below the separation line correspond to Experiment 1 and Experiment 2 respectively.

Performance Measure Definition: Average Call Processing Interval

Volunteer rate and distribution of volunteer hours, for the population aged 15 and over, by definition of volunteering and age group, Canada and provinces.

This dataset identifies all regions in which the full 95% confidence interval is between 4 and 16 �C for all 12 months. The sea surface temperature data includes the mean sea surface temperature per month, the standard deviation and the number of observations used to calculate the mean. Based on these values, the 95% upper and lower confidence levels about the mean for each month have been generated.

Clear Spelling Dataset

  Overview

The Mistake to Meaning (M2M) dataset is a carefully crafted synthetic collection of 100,000 unique English spelling mistakes and their correct forms, intended for training high-quality typo correction and spell checking AI models. It covers various types of common mistakes observed frequently in real-world scenarios, such as:

Keyboard adjacency typos Letter swaps and omissions Duplicate characters Phonetic substitution errors Commonly… See the full description on the dataset page: https://huggingface.co/datasets/ProCreations/Mistake-To-Meaning.

The use theory of meaning-making (UTMM) was subjected to a small focus group study to confirm the theory. The population was a typical agile team of nine plus one. Four short self-assessed surveys tested the historical and current experience and interpretation of the form-function problem using industry examples. The results showed the theory holds within the boundaries of requirements specifications. The researcher’s arguments and interpretations proved to be plausibly acceptable.

Neither linguistics nor psychology offers a single, unified notion of simplicity, and therefore the simplest “core” layer of vocabulary is hard to define in theory and hard to pinpoint in practice. In section 1 we briefly survey the main approaches, and distinguish two that are highly relevant to lexicography: we will call these common and basic. In sections 2 and 3 we compare these approaches, and in section 4 we point the reader to Kolmogorov complexity, unfamiliar as it may be to most working psychologists, lexicographers, and educators, as the best formal means to deal with core vocabulary.

The Parallel Meaning Bank (PMB), developed at the University of Groningen and building upon the Groningen Meaning Bank, comprises sentences and texts in raw and tokenised format, syntactic analysis, word senses, thematic roles, reference resolution, and formal meaning representations. The main objective of the PMB is to provide fine-grained meaning representations for words, sentences and texts. Sentences are, in isolation, often ambiguous. The aim is to provide the most likely interpretation for a sentence, with a minimal use of underspecification.

The PMB annotations include gold standard data, which is fully manually corrected, as well as silver (partially manually corrected) and bronze (with no manual corrections) data. The releases so far contain documents for English, German, Italian and Dutch, but for future releases it is planned to include Chinese and Japanese.

This statistic illustrates the results of a survey regarding the opinion on the meaning of the term fake news in Turkey in 2018. According to data published by IPSOS, ** percent of Turkish adults stated that they personally thought of politicians and the media using the term to discredit news they did not agree with.

The study was conducted to determine the prevalance of physical and sexual victimization, and to develop a new model of victimization. A total of 600 women participated in the study, consisting of two samples: a sample of 403 incarcerated women at the Metro State Women's Prison in Atlanta, Georgia, and a sample of 197 poor urban women in nonemergency health care clinics. Participants were interviewed once for approximately 1 1/2 to 2 hours, and answered questions about intimate partner violence (with their most recent partner and/or with a previous partner), physical health, emotional well-being, experiences of traumatic life events, strategic responses to abuse, experiences of child abuse, and other related experiences/knowledge. In addition to self-reports, data was gathered from prison records for the incarcerated sample.

This dataset identifies all regions in which the full 95% confidence interval is wholly between 2.5 and 19 �C for all 12 months. The sea surface temperature data includes the mean sea surface temperature per month, the standard deviation and the number of observations used to calculate the mean. Based on these values, the 95% upper and lower confidence levels about the mean for each month have been generated.

Question-Answer Meaning Representation (QAMR) represents a predicate-argument structure of a sentence with a set of question-answer pairs, so that annotations can be easily provided by non-experts. QAMR is a dataset of over 5,000 sentences and 100,000 questions created by crowdsourcing workers.

This section presents a discussion of the research data. The data was received as secondary data however, it was originally collected using the time study techniques. Data validation is a crucial step in the data analysis process to ensure that the data is accurate, complete, and reliable. Descriptive statistics was used to validate the data. The mean, mode, standard deviation, variance and range determined provides a summary of the data distribution and assists in identifying outliers or unusual patterns. The data presented in the dataset show the measures of central tendency which includes the mean, median and the mode. The mean signifies the average value of each of the factors presented in the tables. This is the balance point of the dataset, the typical value and behaviour of the dataset. The median is the middle value of the dataset for each of the factors presented. This is the point where the dataset is divided into two parts, half of the values lie below this value and the other half lie above this value. This is important for skewed distributions. The mode shows the most common value in the dataset. It was used to describe the most typical observation. These values are important as they describe the central value around which the data is distributed. The mean, mode and median give an indication of a skewed distribution as they are not similar nor are they close to one another. In the dataset, the results and discussion of the results is also presented. This section focuses on the customisation of the DMAIC (Define, Measure, Analyse, Improve, Control) framework to address the specific concerns outlined in the problem statement. To gain a comprehensive understanding of the current process, value stream mapping was employed, which is further enhanced by measuring the factors that contribute to inefficiencies. These factors are then analysed and ranked based on their impact, utilising factor analysis. To mitigate the impact of the most influential factor on project inefficiencies, a solution is proposed using the EOQ (Economic Order Quantity) model. The implementation of the 'CiteOps' software facilitates improved scheduling, monitoring, and task delegation in the construction project through digitalisation. Furthermore, project progress and efficiency are monitored remotely and in real time. In summary, the DMAIC framework was tailored to suit the requirements of the specific project, incorporating techniques from inventory management, project management, and statistics to effectively minimise inefficiencies within the construction project.

The goal of the Uniform Meaning Representation (UMR) project is to design a meaning representation that can be used to annotate the semantic content of a text. UMR is primarily based on Abstract Meaning Representation (AMR), an annotation framework initially designed for English, but also draws from other meaning representations. UMR extends AMR to other languages, particularly morphologically complex, low-resource languages. UMR also adds features to AMR that are critical to semantic interpretation and enhances AMR by proposing a companion document-level representation that captures linguistic phenomena such as coreference as well as temporal and modal dependencies that potentially go beyond sentence boundaries. UMR is intended to be scalable, learnable, and cross-linguistically plausible. It is designed to support both lexical and logical inference.

It is the electoral district in which a general councillor is elected. The cantons, like the departments, were created by the law of 22 December 1789. In most cases, the cantons comprise several municipalities. But the cantons do not always respect the municipal boundaries: in the most populated municipalities, several cantons are defined.

Groningen Meaning Bank is a semantic resource that anyone can edit and that integrates various semantic phenomena, including predicate-argument structure, scope, tense, thematic roles, animacy, pronouns, and rhetorical relations.

Percentage of persons aged 15 years and over by level of sense of meaning and purpose, by gender and other selected sociodemographic characteristics: age group; immigrant status; visible minority group; Indigenous identity; persons with a disability, difficulty or long-term condition; LGBTQ2+ people; highest certificate, diploma or degree; main activity; and urban and rural areas.

Volunteer rate and distribution of volunteer hours, for the population aged 15 and over, by definition of volunteering and religious attendance, Canada and provinces.