Confidence Indexing of Automated Detected Synsets: A Case Study on Contemporary Turkish Dictionary

In this study, a novel confidence indexing algorithm is proposed to minimize human labor in controlling the reliability of automatically extracted synsets from a non-machine-readable monolingual dictionary. Contemporary Turkish Dictionary of Turkish Language Association is used as the monolingual dictionary data. First, the synonym relations are extracted by traditional text processing methods from dictionary definitions and a graph is prepared in Lemma-Sense network architecture. After each synonym relation is labeled by a proper confidence index, synonym pairs with desired confidence indexes are analyzed to detect synsets with a spanning tree-based method. This approach can label synsets with one of three cumulative confidence levels (CL-1, CL-2, and CL-3). According to the confidence levels, synsets are compared with KeNet which is the only open access Turkish Wordnet. Consequently, while most matches with the synsets of KeNet is determined in CL-1 and CL-2 confidence levels, the synsets determined at CL-3 level reveal errors in the dictionary definitions. This novel approach does not find only the reliability of automatically detected synsets, but it can also point out errors of detected synsets from the dictionary.

Confidence levels under complex q-rung orthopair fuzzy aggregation operators and their applications

The major contribution of this analysis is to analyze the confidence complex q-rung orthopair fuzzy weighted averaging (CCQROFWA) operator, confidence complex q-rung orthopair fuzzy ordered weighted averaging (CCQROFOWA) operator, confidence complex q-rung orthopair fuzzy weighted geometric (CCQROFWG) operator, and confidence complex q-rung orthopair fuzzy ordered weighted geometric (CCQROFOWG) operator and invented their feasible properties and related results. Future more, under the invented operators, we diagnosed the best crystalline solid from the family of crystalline solids with the help of the opinion of different experts in the environment of decision-making strategy. Finally, to demonstrate the feasibility and flexibility of the invented works, we explored the sensitivity analysis and graphically shown of the initiated works.

Multicriteria q-Rung Orthopair Fuzzy Decision Analysis: A Novel Approach Based on Archimedean Aggregation Operators with the Confidence Levels

The confidence levels can reduce the influence of the unreasonable evaluation value was given by the decision maker on the decision-making results. The Archimedean t-norm and t-conorm (ATS) also have many advantages for the processing of uncertain data. Under this environment, the confidence q-rung orthopair fuzzy aggregation operators based on ATS is one of the most successful extensions of confidence q-rung orthopair fuzzy numbers (Cq-ROFNs) in which decrease the deviation caused by the subjective perspective of the decision maker in the multicriteria group decision-making (MCGDM) problems. In this paper, we propose weighted, ordered weighted averaging aggregation operators and weighted, ordered weighted geometric aggregation operators based on ATS, respectively. Moreover, the properties and four specific forms associated with aggregation operators are also investigated. In this study, a novel MCGDM approach is introduced by using the proposed operator. A reasonable example is proposed and compared the results which are obtained by our operators and that in existing literature, so as to verify the rationality and flexible of our method. From the study, we concluded that the proposed method can reduce the impact of extreme data, and makes decision-making results more reasonable by considering the attitudes of decision-makers.

Determination of the Uncertainties in S-Curve Logistic Fits

Look-up tables and graphs are provided for determining the uncertainties during logistic fits, on the three parameters M, α and to describing an S-curve of the form: S(t) = M/(1+exp(-α(t-t0))).The uncertainties and the associated confidence levels are given as a function of the uncertainty on the data points and the length of the historical period. Correlations between these variables are also examined; they make “what-if” games possible even before doing the fit.The study is based on some 35,000 S-curve fits on simulated data covering a variety of conditions and carried out via a χ2 minimization technique. A rule-of-thumb general result is that, given at least half of the S-curve range and a precision of better than 10% on each historical point, the uncertainty on M will be less than 20% with 90% confidence level.

Dynamic cyber risk estimation with competitive quantile autoregression

The increasing value of data held in enterprises makes it an attractive target to attackers. The increasing likelihood and impact of a cyber attack have highlighted the importance of effective cyber risk estimation. We propose two methods for modelling Value-at-Risk (VaR) which can be used for any time-series data. The first approach is based on Quantile Autoregression (QAR), which can estimate VaR for different quantiles, i. e. confidence levels. The second method, we term Competitive Quantile Autoregression (CQAR), dynamically re-estimates cyber risk as soon as new data becomes available. This method provides a theoretical guarantee that it asymptotically performs as well as any QAR at any time point in the future. We show that these methods can predict the size and inter-arrival time of cyber hacking breaches by running coverage tests. The proposed approaches allow to model a separate stochastic process for each significance level and therefore provide more flexibility compared to previously proposed techniques. We provide a fully reproducible code used for conducting the experiments.

Analysing the donor behaviour of a Muslim diaspora in Australia

Diaspora communities are an important source of charitable giving to their original homelands. This study explores a Muslim diaspora's motivations behind donation-giving. A two-year donation dataset of an overseas charity organisation registered in Australia was analysed. Findings show that, overall, donations are significantly related to the prevailing consumer confidence levels (r = 0.4277). However, there was also a strong, inverse correlation (r = - 0.4376) during 2020, suggesting that the plummeting consumer sentiment during COVID-19 did not impact donation revenue. As expected, during periods of religious significance (Ramadan) across both years, donations to the charity increased substantially, with the relative effect of Ramadan calculated as over 800%. This study makes a contribution by providing insights to donor behaviour through the examination of a donation dataset. This study also uses ‘causal impact analysis’ to calculate the effect of Ramadan on donations. Results have implications for the not-for-profit sector in Australia and other countries with Muslim diaspora communities. Limitations and suggestions for future research are also discussed.

The Effect of Sport Activities on Self-Confidence Levels of 13-14 Year-Olds

This study is conducted to determine the effect of the sport activities on the self-confidence levels of 13-14 year-olds. Self-confidence formation starts especially at ages of 13-14 and affects the success of the individuals. Therefore, whether sport activities have any effects on self-confidence and whether the demographic characteristics affect self-confidence are analyzed in our study. Total of 272 individuals, 159 individuals participating in sport activities and 113 individuals not participating in sport activities at Ilkadım, Carsamba and Bafra Youth Centers providing services under the scope of the sport activities by the Samsun Youth and Sports Provincial Directorate in the season of 2018-2019 have participated voluntarily in this study. In this research, survey method among the methods used in applied research is preferred. As the data collection tool, a survey form consisting of two sections is used. In the first section the ‘Personal Information Form’ prepared by the researcher is used. In the personal information form, demographic information as father’s employment status, mother’s employment status, mother and father’s marital status, number of siblings and familial income status are included. In the second section, the ‘Self-confidence scale’ developed by Akın (2007) is used. Acquired data is tested at 95% confidence level with the aid of SPSS program and the significance level is determined as 0.05. In the light of the date in the study, before the statistical analysis was begun, normality assumption and homogeneity tests are applied, as the result of the Kolmogorov-Smirnov and Levene tests conducted it is determined that the data has normal distribution (p > 0.05). As the data shows normal distribution, it is decided to conduct parametric analysis. In comparison of the groups, independent sample t-test and one way ANOVA analyses are used. According to the acquired data and the analyses conducted, as the result of comparison of the Internal and External Self-confidence scores of the individuals participating in the sport activities according to the father’s employment status, mother’s employment status, mother and father’s marital status, number of siblings and familial income status, it is concluded that there is no significant differences. Whereas in the gender variable, while there is no significant difference in the Internal Self-confidence sub dimension, in the External Self-confidence sub dimension it is found out that the males have significantly higher scores compared to the females. Also it is seen that the self-confidence levels of individuals participating in sport activities are statistically higher than the ones who do not participate in the sport activities (p < 0.05).

A Mixed Method Study on the Effectiveness of Using Virtual Reality to Improve Adolescent Public Speaking

This study analyzes the extent to which virtual reality technology is effective in improving self-confidence in children and adolescents ages 12-18 when public speaking. Using a mixed method of both quantitative and qualitative data, subject responses were collected through a pre- and post-test survey prior to and after completing a set of three virtual reality simulations. The data demonstrated that with an increasing number of audience members present in a virtual simulation, subject confidence levels decreased, suggesting that virtual reality can be used as an effective tool in reducing public speaking anxiety. While the current study supports this claim, additional research should be conducted based on the limitations of this study, specifically to enlarge the sample size beyond 20 subjects.

A Hard-Science Approach to Kondratieff’s Economic Cycle

In an effort to evidence the Kondratieff cycle more scientifically than the way economists do, physical variables are studied rather than monetary indicators. Previously published graphs are reproduced and updated here with recent data. A cyclical rather regular variation of energy consumption reveals a 56-year cycle. A dozen human endeavors/phenomena, such as bank failures, homicides, hurricanes, feminism, and sunspot activity are shown to resonate with this cycle. Possible explanations for this phenomenon may have to do with a climatic variation or with the length of time any individual actively influences the environment. There is some evidence that the cycle may be getting shorter in amplitude and duration in recent years. All quantitative confidence levels involved in these observations are poor by scientific standards and permit critics to question the very existence of this phenomenon.

Facilitating reflection in teletandem through automatically generated conversation metrics and playback video

This pilot study focuses on a tool called L2L that allows second language (L2) learners to visualise and analyse their Zoom interactions with native speakers. L2L uses the Zoom transcript to automatically generate conversation metrics and its playback feature with timestamps allows students to replay any chosen portion of the conversation for post-session reflection and self-review. This exploratory study investigates a seven-week teletandem project, where undergraduate students from an Irish university learning French (B2) interacted with their peers from a French university learning English (B2+) via Zoom. The data collected from a survey (N=43) and semi-structured interviews (N=35) show that the quantitative conversation metrics and qualitative review of the synchronous content helped raise students’ confidence levels while engaging with native speakers. Furthermore, it allowed them to set tangible goals to improve their participation, and be more aware of what, why, and how they are learning.