Frequency Analysis Research Articles

Playing without goalkeeper: the use of an empty goal in high-performance men’s handball

ABSTRACT The study aimed to 1) assess the risk of conceding a goal in an empty net; 2) characterise the context when using the empty goal (EG) rule (4:1) in handball and 3) identify the performance variables that influence the EG attacks’ efficacy. A total of 974 EG attacks were sampled from 65 matches of the 2022 European Men’s Handball Championship. An observational tool was developed to analyse all EG attacks. Frequency analysis and the chi-square test have been performed to analyse the use of EG according to the match context. The binomial logistic regression was used to identify the variables that influence the EG attacks’ effectiveness. The results demonstrated that the goalkeeper was replaced mainly to maintain numerical equality. To create offensive superiority, the teams mostly used EG during the last quarter of the match playing under a small score disadvantage. The risk of conceding a goal in the empty net was higher if a team failed to score in previous possession. No relationship was found between the team’s final classification and the frequency of EG use, nor the efficacy of EG situations. Two variables have been identified as significant for the 6 × 6 + GK possession outcome: 2nd pivot position and shot zone.

The future of droughts in Iran according to CMIP6 projections

ABSTRACT Anthropogenic climate change is exerting immense pressure on water resources in Iran. This study investigates future precipitation and meteorological droughts across the country considering performances of 41 general circulation models (GCMs). The findings indicate a significant increase in long-term average annual precipitation (LAAP) across Iran with an overall north-to-south increasing gradient, particularly in areas prone to extreme events. However, focusing solely on LAAP is misleading. Projected precipitation reveals substantial inter-annual variability, impacting both the severity and duration of meteorological droughts. For instance, 100-year return period droughts are expected to intensify in severity (The Shared Socio-economic Pathway SSP1-2.6: 4–91%, SSP8-5.5: 46–204%) and duration (SSP1-2.6: 19–76%, SSP8-5.5: 40–127%) across most regions, except the Persian Gulf coastal zone, where droughts may become less severe (SSP1-2.6: 23%, SSP8-5.5: 23%) and shorter in duration (SSP1-2.6: 27%, SSP8-5.5: 10%). Additionally, bivariate frequency analysis suggests that major droughts could become significantly more frequent in the future.

An observational cross-sectional study of the role of magnetic resonance imaging in the evaluation of T2-weighted hyperintensities in the spinal cord in tertiary care hospital in central India

Background T2-weighted hyperintensities in the spinal cord are a complex and diagnostically challenging entity that can present with diverse clinical features. This study protocol outlines a comprehensive investigation to understand the causes, clinical and imaging characteristics, and correlation with pathological findings of T2-weighted hyperintensities in the spinal cord. By establishing a systematic assessment approach, this study seeks to provide valuable insights into these abnormalities’ diagnostic and prognostic implications. Methods The study will be conducted as a prospective observational design. Patients with clinically diagnosed or suspected spinal cord injury presenting with intramedullary T2-weighted hyperintensity and referred for MRI evaluation will be included. Data collection will encompass patient demographics, clinical features, and extensive imaging parameters. Pathological data, when available, will be correlated with imaging findings. Various statistical methods will be employed to analyse the data, including frequency analysis, comparative tests, logistic regression, and survival analysis. Expected Results The study anticipates elucidating the spectrum of etiologies underlying T2-weighted hyperintensities in the spinal cord and their clinical and imaging profiles. The systematic approach will offer a structured diagnostic method, while correlations with pathological data will provide an enhanced understanding of these conditions. The results are expected to provide clinicians with valuable insights into diagnosing, treating, and prognosticating patients with spinal cord hyperintensities.

Expanding information for flood frequency analysis using a weather generator: Application in a Spanish Mediterranean catchment

Study regionThe proposed methodology has been applied in the Segura River basin (south-eastern Spain) whose hydrological regime has a high anthropic alteration and catastrophic floods have occurred at different times for centuries. The climate is generally semi-arid, with frequent droughts but also floods caused mainly by rainfall associated with mesoscale convective systems. Study focusWe present a methodology that exploits all available information to obtain reliable low-frequency flood quantiles through the integration of different methods. First, a Weather Generator (WG) was implemented with the results from a regional study of annual maximum precipitation. Second, a rainfall temporal disaggregation procedure was carried out to capture the sub-daily behavior of flood generating storms. Third, a fully-distributed Hydrological Model (HM) was implemented including the role of sediments in extreme events. Finally, the estimation of flood quantiles using plotting positions was validated with systematic and non-systematic information. New Hydrological Insights for the regionThe use of this process-based approach allows to reproduce the main hydrometeorological mechanisms associated with floods in the region studied. Accurate flood quantiles up to 200 years have been possible to obtain, which represents an important advance in the knowledge of the basin since reliable flood quantiles of only 20 years were adequately captured with the current observations. Finally, sediment yield has been proven to be an important factor for the region hydrographs’ reconstruction.

Lexical Expressions of Motion in Physical Environments a Cognitive Linguistics Perspective

This study aims to delve into the interaction between motion verbs, manners, and paths in the Vietnamese language to look at the lexicalization of motion occurrences. Utilizing Talmy's lexicalization patterns for cognitive linguistics, the study seeks to understand how Vietnamese encodes and conceptualizes motion events in a variety of physical contexts, such as the air, water, and land. A mixed-methods approach is used in this work, integrating qualitative analysis of annotated textual data with quantitative frequency analysis. Vietnamese has a rich system of motion verbs that may be paired with manner and path expressions to produce complex and subtle descriptions of movement, according to the research. The language displays intricate differences when describing the direction, velocity, and kind of vehicle of motion, in addition to various linear, curved, vertical, circular, and multidirectional routes. The complex interplay between language, cognition, and the embodied experience of motion is highlighted by this linguistic variety, which is a reflection of Vietnamese speakers' astute observation and interpretation of the physical world. The work adds to our knowledge of how language organizes and expresses the basic idea of motion and provides insights into the cognitive and cultural bases of language expression.

Early Holocene inundation of Doggerland and its impact on hunter-gatherers: An inundation model and dates-as-data approach

Sea-level rise was a key factor changing environments during the Early Holocene in Northwest Europe. It affected Mesolithic hunter-gatherer communities by inundating large areas in the current North Sea, commonly referred to as Doggerland. In this paper we present novel inundation models for the southern North Sea providing visualisations of lateral inundation driven by sea-level rise and relate it to frequency analysis of radiocarbon dates from archaeological sites. These improve on previous studies that relied on bathymetric data, which includes post-inundation overprints of Holocene sedimentation and erosion, and thus significantly underestimates the timing of inundation in some areas.We constructed a paleoDEM (a composite elevation grid of the top of the Pleistocene) for the eastern part of the southern North Sea; and sea level surfaces that combine relative sea-level curves from glacio-isostatic adjustment models optimised for Britain and southern Scandinavia respectively. We corrected our paleoDEMs for tectonic background basin subsidence, and in the inundation modelling account for pre-compaction elevation of peat in coastal areas. We evaluated the impact of these model components on our results and describe the possible inundation history of Doggerland. We suggest earlier inundation than predicted by previous models, showing significant area loss around 10.5–10 ka cal BP.Palaeogeographic changes are compared with archaeological radiocarbon data using a dates-as-data approach. Composite Kernel Density Estimate and permutation tested Summed Probability Distributions are used as a proxy for the visibility, nature and intensity of human activity. Results indicate key periods of growth and decline recorded in the dataset, as well as regional differences in growth rate, some correlating with inundation phases. Chiefly, we find elevated growth rates around 10.5–10 ka in northwest Germany and the Netherlands, contemporaneous with the abovementioned phase of extensive area loss, and moreover, with changes in culture and practices on Early Mesolithic sites.However, the spatiotemporal distribution of archaeological data is significantly influenced by accessibility and preservation of sediments of a certain age. We discuss the importance of inundation modelling and sediment data in understanding how landscape taphonomy affects archaeological patterning, especially in dates-as-data approaches.

When algebra makes you smile: Playful engagement with early algebraic practices

BackgroundThe typical competitive and results-driven approach to school mathematics has traditionally been conceived as devoid of play, joy, and positive affect. AimsIn this paper we address the following questions: What markers of positive affect are observed while students are doing early algebra? Specifically, how are students’ markers of joy related to early algebraic practices? What are the characteristics of playful stances to learning early algebra that are observed when children express positive epistemic affect? SampleWe analyze three cases in which elementary school students engaged in tasks from an early algebra classroom teaching experiment. MethodsDrawing from two theoretical frameworks, epistemic affect and early algebra, we conducted microgenetic analyses of lesson transcripts to identify markers of joy and early algebraic practices. We conducted frequency analyses to determine their co-occurrence. ResultsOur results indicate that children expressed joy while engaging in early algebraic practices, evidence of positive epistemic affect. We describe the aspects of each of the cases we present in terms of prior literature on playful stances to learning to further bolster our claims about the relationship between joy and engagement with the early algebraic practices. ConclusionsWe conclude that mathematical learning environments should include open opportunities for students to engage with mathematical content, with multiple entry points and ways to respond. We also conclude that early algebraic practices provide opportunities for playfully engagement and positive epistemic affect.

Innovative AI methods for monitoring front-of-package information: A case study on infant foods.

Front-of-package (FOP) is one of the most direct communication channels connecting manufacturers and consumers, as it displays crucial information such as certification, nutrition, and health. Traditional methods for obtaining information from FOPs often involved manual collection and analysis. To overcome these labor-intensive characteristics, new methods using two artificial intelligence (AI) approaches were applied for information monitoring of FOPs. In order to provide practical implementations, a case study was conducted on infant food products. First, FOP images were collected from Amazon.com. Then, from the FOP images, 1) the certification usage status of the infant food group was obtained by recognizing the certification marks using object detection. Moreover, 2) the nutrition and health-related texts written on the images were automatically extracted based on optical character recognition (OCR), and the associations between health-related texts were identified by network analysis. The model attained a 94.9% accuracy in identifying certification marks, unveiling prevalent certifications like Kosher. Frequency and network analysis revealed common nutrients and health associations, providing valuable insights into consumer perception. These methods enable fast and efficient monitoring capabilities, which can significantly benefit various food industries. Moreover, the AI-based approaches used in the study are believed to offer insights for related industries regarding the swift transformations in product information status.

Estimating rainfall-runoff parameters for ungauged catchments: a case study in Turkiye

ABSTRACT Determining water yield and flood discharges in catchments is a vital aspect of hydrology. This entails considering precipitation and runoff as key hydrological parameters. Constructing infrastructure like hydroelectric plants and regulators over streams necessitates continuous, accurate flow, and meteorological observations spanning at least 25 years. However, in developing nations, economic factors often impede such observations. This study proposes a method to estimate peak rainfall and flow values for ungauged basins with varying return periods by utilizing from gauged basins and spatial variables. Flood calculations were carried out for the ungauged Rabat River basin. In this study, regional flood frequency analysis was carried out using the flow values of the flow gauging stations neighboring the basin. In addition, maximum flow values were calculated using Moscus and the DSI synthetic method. Two- and three-parameter distributions were used to estimate 50-, 100-, 200- and 500-year flood return values at stations with observation periods ranging from 15 to 64 years. Kolmogorov–Smirnov and Probability Line Correlation coefficient (Chi-square) tests were applied to check the suitability of these distributions and the most appropriate distributions were found. This yielded an estimation for the flow values of the Rabat River, indicating the method's reliability for forecasting runoff-rainfall in the ungauged basin.

Attitudes of 3PL Providers of the Companies towards the Activities of Organizational Performance

Businesses today specialize in their core competencies and outsource their other operations due to the emerging perception of competition brought on by the large-scale similarity of production, the quick spread of technology and information systems, and the disappearance of international borders. One of the most common fields of outsourcing activity is Third Party Logistics (3PL) service, and the Organizational Performance elements of 3PL service providers are listed as Service Quality, Relationship Management and Organizational Effectiveness. This research aims to examine the Organizational Performance criteria of the 3PL providers serving the production enterprises and to evaluate the relationship structure between the mean and standard deviation values of the statements in the survey. The empirical results obtained from frequency, regression and standard deviation analyses show that Guanxi, Reliability, Assurance, and Trust positively affect Organizational Effectiveness. However, only Trust has a positive and statistically significant impact on Service Quality

대학 강의평가 서술형 문항의 감정분석 및 의미연결망 분석

Objectives The purpose of this study was to derive directions and implications for quality of education through sentiment analysis and semantic network analysis of university descriptive course evaluations. Methods The analysis data consisted of 243,900 descriptive lecture evaluations from the first semester of 2020 to the first semester of 2023 at University A. Emotion words were classified in the order of positive, negative, and neutral, and the frequency and ratio of descriptive lecture evaluation contents by year, subject, and college were calculated. N-gram and clustering were analyzed using Textome, and network centrality between keywords was analyzed and visualized using Ucinet 6. Results First, in the sentiment analysis trend for descriptive lecture evaluation questions by year, course com-pleted, and university, positive opinions were found to be dominant. Second, as a result of the keyword frequency and N-gram analysis of the lecture evaluation contents, the frequency of ‘class’ and ‘thank you’ was high in pos-itive evaluations, and the frequency of ‘class’, ‘assignment’, and ‘unsatisfactory’ was high in negative descriptive course evaluations. In addition, ‘class’ was expanded around the keywords ‘content’, ‘progress’, ‘time’, and ‘regrettable’. Third, the results of semantic network analysis between keywords in the lecture evaluation contents showed that in the positive type, ‘gratitude’, ‘class’, ‘hard work’, ‘explanation’, ‘student’, ‘kindness’, ‘help’, ‘understanding’, ‘assignment’, ‘time’ were the most important and connected keywords. In the negative course evaluation, keywords including ‘class’, ‘lecture’, ‘professor’, ‘assignment’, ‘disappointing’, ‘difficult’, ‘anxiety of test’ were analyzed as the most connected. Conclusions This study showed the possibility of suggesting directions for education improvement through de-scriptive lecture evaluation using sentiment analysis and semantic network analysis.

빗속의 사람 그림 검사(PITR) 반응에 대한 대학생의 우울, 불안, 부정정서에 관한 연구

Objectives This study aims to identify the responses shown in the picture test and negative psychological aspects such as depression, anxiety, and negative emotions by using both the subjective responses shown in the People-in-the-Rain Picture Test(PITR), a projective test, and a multiple-choice self-report test. Methods The target was college students attending K University in Region P. 146 copies were distributed and 125 copies were collected. Of these, the data from 108 people, excluding 17 who responded insincerely, was analyzed. The collected data were subjected to frequency analysis, reliability analysis, descriptive statistics, and correlation analysis using the SPSS statics 26.0 program. An independent sample t-test was conducted to confirm gender differences in variables, and a simple regression analysis was conducted to determine the effect of the PITR re-sponse on depression, anxiety, and negative emotions. An independent samples t-test was conducted to confirm the differences in responses to the PITR according to the upper and lower levels of the average emotional score. Results First, as a result of checking the correlation between variables, the ‘stress’ response did not have a stat-istically significant relationship with depression, anxiety, and negative emotions in the PITR response, and the ‘coping resources’ response did not have a statistically significant relationship with depression, it was found to be negatively correlated with anxiety and negative emotions, and the ‘coping ability’ response was also found to be negatively correlated with depression, anxiety, and negative emotions. Second, differences in variables according to gender were confirmed in the ‘coping resources’ response and the ‘coping ability’ response among the PITR responses. Third, PITR response was found to affect depression, anxiety, and negative emotions. Fourth, as a re-sult of checking whether there was a difference in the response to the PITR depending on the average score of depression, anxiety, and negative emotions, it was found that there was no difference in the response to the PITR according to depression, the differences in responses to the PITR according to anxiety and negative emotions were verified to have statistically significant differences in both ‘coping ability’ responses. Conclusions Through the results of this study, it was confirmed that negative psychological aspects such as de-pression, anxiety, and negative emotions can vary depending on how one copes with the stress rather than the stress itself, and that the response to the PITR differs depending on gender in terms of coping with stress. It was confirmed that there was a difference. In addition, we were able to understand that depression, anxiety, and neg-ative emotions are different psychological characteristics, and it was confirmed that coping abilities vary accordingly. The significance of this study is that it provided evidence for early detection, appropriate treatment, and prevention education for college students with mental health difficulties.

Building a Value-Based Workforce Through Islamic Work Value-Based Recruitment: A Conceptual Review

The increasing ethical infringements, moral violations, and disciplinary problems among employees point to the deteriorations in employee values. Hiring employees merely on common competency-based recruitment (CBR) versus value-based recruitment (VBR) ignores the critical role of values in guiding employee behaviours, thus contributing further to the problems. This study involves a qualitative approach using NVivo text analysis tool to analyse texts and word frequency from 44 references, including 35 journal articles, six policy papers, two books or book chapters and one conference proceedings. The results show that Public Sector ICT Management Review was the top journal with the highest coverage of the study’s main themes, followed by the Journal of Education for Teaching, the Human Resource Management Review, and the Advances in Health Science Education indicating the importance of the value-based workforce in these four areas of employment (i.e., public sector, education, human resource, and health). The word frequency analysis also shows the five most-used words were “values,” “work,” “based,” “selection,” and “recruitment.” These findings show that the references used in this study are valid and reliable relevant to the study’s main themes. Value-based workforce relates to value-based recruitment – building a value-based workforce begins with a good recruitment strategy. In the Islamic context, Islamic work values are highly influential and Islamic work-related values have been used as recruitment conditions for hiring employees during the Prophet Muhammad’s (pbuh) time and the rightly guided caliphs. If incorporated into the value- based model of recruitment, Islamic-related work values could potentially build a value- based workforce. This study has a significant implication to managers especially in finding good employees for the success of the organisation. Recruiting employees through value-based recruitment and selection is believed could reduce many work-related issues and improve organisational effectiveness. This study adds to the body of knowledge on value- based hiring by incorporating theories and Islamic work ideals, which can be used as a guide for future research.

Peak frequency analysis and differentiation between near-field and far-field electrograms of the ventricular tachycardia circuit leads to successful ablation of arrhythmia.

Peak frequency analysis and differentiation between near-field and far-field electrograms of the ventricular tachycardia circuit leads to successful ablation of arrhythmia.

A Study on MBTI Perceptions in South Korea: Big Data Analysis from the Perspective of Applying MBTI to Contribute to the Sustainable Growth of Communities

This study aimed to assess the potential contributions of the Myers–Briggs Type Indicator (MBTI) to the sustainable growth of communities by conducting a comprehensive analysis of social perceptions of the MBTI in South Korea through big data analysis. The investigation encompasses three primary stages: data collection, preprocessing, and analysis, involving text mining, network analysis, CONCOR analysis, and sentiment analysis. A total of 31,308 text data pieces (13.73 MB) from various sources, including news, blogs, and other sections of Naver and Google, over the past three years, were collected and analyzed using the keyword “MBTI”. Tools, such as Textom SV, UCINET, and NetDraw, were employed for data collection and analysis. The study’s key findings include the identification, through term frequency (TF) and TF-inverse document frequency analyses, of top-ranking terms, such as 16Types, 4Indicators, Test, Myself, OthersMBTI, Situation, and Contents. The CONCOR analysis further revealed six clusters, encompassing themes like interest in MBTI personality tests, application of 16 types in daily life, MZ’s MBTI consumption patterns, trending of MBTI characters, extension to K-Test, and professional use of MBTI. Moreover, sentiment analysis indicated that 68.5% of individuals in South Korea expressed a positive sentiment towards MBTI, while 31.5% conveyed a negative sentiment. The specific emotions identified included liking (Good Feeling), disgust, and interest, in order of prominence. In light of these findings, this study delineates a spectrum of perceptions regarding MBTI in South Korea, encompassing both positive interests and negative concerns. To ensure the responsible use of MBTI, it is imperative to implement reliable scientific testing and education, mitigate the potential harm of stereotyping, and reshape social perceptions surrounding MBTI usage. Only through these measures can MBTI genuinely contribute to the sustainable growth of communities without being confined to limiting stereotypes.

Advanced Deep Learning for ECG Anomaly Detection in Imbalanced Data

Advanced Deep Learning for ECG Anomaly Detection in Imbalanced Data

Evaluation and SAR Analysis of Low Frequency and Broadband Electric Field Exposure Measurement Values in the Home Environment

In this study, the effective value of low-frequency (50 Hz) and high-frequency (700–2500 MHz) broadband electric field exposures was measured for 24 h in four different selected environments in a house. All the statistical values of 1000 data points recorded with two measuring devices for 24 h in each environment are calculated, the most appropriate curves are fitted to the data, and the curves are plotted by expressing their changes with respect to time. All statistical and parametric values of the density and cumulative probability functions of the curves are calculated and plotted. In broadband measurements, the broadband is divided into fifteen sub-bands, but the data are available in only six of these sub-bands. The six-layer human head model is created by using the middle frequencies of the six sub-bands used, and taking the permittivity (εr) and conductivity (σ) of each layer into consideration. The specific absorption rate (SAR) value in the brain is calculated by using the total transmission coefficient of six layers. The SAR value surrounding the head is obtained. These SAR values are interpreted by considering the Federal Communications Commission (FCC) and the Community European (CE) occupational and general public SAR limits.

Genetic variability profiling of the p53 signaling pathway in chronic lymphocytic leukemia. Individual and combined analysis of TP53, MDM2 and NQO1 gene variants.

TP53 gene disruption, including 17p13 deletion [del(17p)] and/or TP53 mutations, is a negative prognostic biomarker in chronic lymphocytic leukemia (CLL) associated with disease progression, treatment failure and shorter survival. Germline variants in p53 signaling pathway genes could also lead to p53 dysfunction, but their involvement in CLL has not been thoroughly evaluated. The aim of this study was to determine the association of TP53, MDM2 and NQO1 gene variability with clinical and genetic data of CLL patients. Individual genotype and haplotype data of CLL patients were compared with clinical prognostic factors, cytogenetic and molecular cytogenetic findings as well as IGHV and TP53 mutational status. The study included 116 CLL patients and 161 healthy blood donors. TP53 (rs1042522, rs59758982, rs1625895), NQO1 (rs1800566) and MDM2 (rs2279744, rs150550023) variants were genotyped using different PCR approaches. Analysis of genotype frequencies revealed no association with the risk of CLL. TP53 rs1042522, rs1625895 and MDM2 rs2279744 variants were significantly associated with abnormal karyotype and the presence of del(17p). Similarly, these two TP53 variants were associated with TP53 disruption. Moreover, TP53 C-A-nondel and G-A-del haplotypes (rs1042522-rs1625895-rs59758982) were associated with an increased likelihood of carrying del(17p) and TP53 disruptions. MDM2 T-nondel haplotype (rs2279744-rs150550023) was found to be a low risk factor for del(17p) (OR = 0.32; CI: 0.12-0.82; p = 0.02) and TP53 disruptions (OR = 0.41; CI: 0.18-0.95; p = 0.04). Our findings suggest that TP53 and MDM2 variants may modulate the risk to have chromosome alterations and TP53 disruptions, particularly del(17p). To our knowledge this is the first study of several germline variants in p53 pathway genes in Argentine patients with CLL.

Non-Differentiable Loss Function Optimization and Interaction Effect Discovery in Insurance Pricing Using the Genetic Algorithm

Non-Differentiable Loss Function Optimization and Interaction Effect Discovery in Insurance Pricing Using the Genetic Algorithm

Regional Flood Frequency Analysis of Northern Iran

The combination of the L-moment approach and multiple regression offers an attractive solution to provide flood estimation at ungauged sites within the Gorganrood and Ghare-sou river basins in the north of Iran. This research has two main goals including regionalization by cluster analysis and regional estimation of flood quantile at the site of interest. After data analysis regarding climatic and hydrologic data series, hierarchical approach was carried out to identify homogeneous regions. The homogeneity test was done by H-Statistic, a testing method based on L-moments. The results showed that a subdivision of selected watersheds into homogenous groups is necessary; therefore, two homogenous regions were formed. In the present study, five three-parameter distributions were fitted to the homogeneous regions and the best-fit one was identified using the L-moments approach. The results of the goodness-of-fit analysis for the two regions introduced the Generalized Pareto (GPA) distribution for both regions as acceptably close fits to the regional average L-moments. Besides, multiple regression was applied to diagnose the effective independent parameters on discharge value. The results reported percent of permeable formations, average annual precipitation, and stream slope as the most effective variables.