Nonparametric Statistical Techniques Research Articles

The challenge of dissecting the frog: cartoonists analyze their creative process

Abstract This article delves into two intrinsic tensions present in humor and cartoons: funniness-seriousness and repetition-novelty. The focus is on the perspectives of cartoonists regarding the semiotic and rhetorical resources they put into play to create humor and satire. In this way, the study echoes a key question in semiotics, and particularly in multimodal studies: how image and words interplay in meaning-making. With that aim, a questionnaire was designed and filled out by 100 cartoonists from 22 different countries. The responses were analyzed applying mixed methods (content analysis, non-parametric statistical techniques, and network analysis). Based on the findings, four distinct profiles of cartoonists were identified, ranging from those who prioritize multimodality (the largest group) to those who favor the verbal mode. Cartoonists who prioritize the visual mode and skeptics to humor analysis fall in between. The article also discusses the various rhetorical resources that cartoonists declare to use to create humor, with irony and sarcasm being the most frequent ones, while puns are the least common. The results are examined in relation to the cartoonists’ conceptions of humor, satire, and the cartoon genre, as well as the different dimensions they considered when discussing their humor style. The study contributes to gaining a deeper understanding of the ways cartoonists use image and writing to create humor and satire and sheds light on an under-researched area in this field.

Compliance with MAB-UNESCO Functions and Management Effectiveness Evaluation between 2017 and 2024: Case Study of the El Cielo Biosphere Reserve, Mexico’s Only State-Run Reserve Belonging to MAB-UNESCO

UNESCO’s MAB Programme promotes a people-centered conservation strategy to strengthen the sustainability of social and ecological systems. However, there exist knowledge gaps regarding its implementation in specific contexts. For this study, a mixed-methods sequential exploratory design was employed. In the first phase, an initial content analysis of the management program of the El Cielo Biosphere Reserve (CBR) and the functions of the statutory framework of UNESCO’s MAB program was conducted. This analysis, which was human-driven but facilitated by artificial intelligence tools, underwent rigorous triangulation and expert validation to strengthen the reliability and robustness of the findings. Subsequently, the Management Effectiveness Tracking Tool (METT3) was issued to researchers, community members, civil servants, and former civil servants related to the management of the CBR. The 2024 results (n = 15) were contrasted with those obtained in 2017 (n = 15) using a quantitative approach consisting of descriptive, non-parametric, and Bayesian statistical techniques. We identified some problems in the implementation of the MAB-UNESCO Programme in the CBR, mainly due to the outdated management program and lack of effective governance, as well as the lack of understanding of the implications of being a MAB-UNESCO biosphere reserve. A numerical trend of deterioration in the effectiveness of the CBR’s management was detected, with overall ratings of 44.78% and 29.62% in 2017 and 2024, respectively. This was associated with a lack of regulation, weak coordination among key actors, and a progressive reduction in funding. The findings of this study are useful to guide the transition of the CBR towards a conservation model that responds to current problems and contributes to the advancement of knowledge on the implementation of the MAB Programme in specific contexts.

Malignant thyroid lump multi classification by TIRADS using DBA with transfer learning

Thyroid diseases have developed into significant illnesses in recent decades. These diseases affect the thyroid glands and are caused by elevated thyroid hormone levels or infections in the thyroid organs. It is challenging to resolve thyroid diagnosis using conventional parametric and nonparametric statistical techniques since it can be viewed as a classification problem. However, there are certain barriers in the manner of obtaining both efficacy and accuracy in thyroid nodule diagnosis. Deep learning (DL) and machine learning (ML) models have emerged as useful instruments for the diagnosis of sickness in the modern era. For the purpose of diagnosing and classifying thyroid diseases, this research introduces a novel deep belief network (DBF) with transfer learning, known as DBNTL. In this study, the pre-processed image was first pre-processed using a conventional multiresolution bilateral technique, and then it was subjected to a novel segmentation technique called fusion pooling integrated U-net segmentation. The DBN with transfer learning model is used to classify and grade malignant thyroid nodules in compliance with thyroid imaging-reporting-and-data-system (TIRADS) guidelines. In this model, the model's weights are obtained by transfer learning. A major metric for evaluating the efficacy of biological image processing applications, good sensitivity and specificity (97.28 and 97.22, respectively) were obtained for the recommended modes.

Functional clustering of NPLs recovery curves

The recovery performance of a portfolio of Non-Performing Loans can be measured in terms of recovery rate and liquidation time jointly through a “recovery curve” representative of recovery rates over time. When portfolio heterogeneity is very high, it is informative to estimate more than just one curve by dividing the portfolio into several homogeneous subsets, i.e. clusters, and calculating a recovery curve for each of them. The aim of this work is to estimate the optimal portfolio partition and the smoothed recovery curves of each cluster by means of non-parametric statistical learning techniques.

Reducing costs and improving patient recovery through a nurse-driven centralized spinal orthoses program on a post-surgical unit: A quality improvement initiative

BackgroundAn external vendor providing off-the-shelf spinal orthoses to inpatients created significant costs and barriers to quality care for spinal surgery patients. A nursing leadership team initiated a quality improvement project to reduce the cost of providing off-the-shelf spinal orthoses and improve the care provided to spinal patients. ObjectiveTo develop and evaluate a nursing-led process for providing off-the-shelf orthoses to spinal surgery patients and eliminate high costs. DesignQuality improvement project evaluated as a retrospective interrupted time-series SettingPost Surgery Inpatient Unit Level II Trauma Center in a United States hospital located in Florida ParticipantsVendor Program: 134 patients; Centralized Program: 155 patients MethodsThe nursing leadership team developed a centralized spinal orthoses program where the bedside nurse fitted the patient with a spinal orthosis, eliminating the need for an external orthotist. The study quantifies changes in study metrics by comparing patients identified through chart review who received care in the vendor program to those who received care in the centralized program utilizing nonparametric statistical techniques. ResultsThe centralized nursing-led spinal orthosis program allowed the unit to mobilize patients more quickly than patients managed under the vendor program (3.85 hr. [95 % CI: 1.27 to 7.26 hrs] reduction; p = 0.004). The overall length of stay was reduced by 0.78 days ([1.34 – 0.02 days]; p = 0.063) or 18.72 h. While the statistical test did not indicate significance, the 18.72-hour reduction in length of stay represents a potential clinically relevant finding. Evaluating patients that suffered a primary spinal injury and no complications (vendor program: 54 patients; centralized program: 86 patients) showed a similar reduction in time to mobilization (4.5 hr reduction [0.53 to 12.93 hrs]; p = 0.025), but the length of stay reduction increased to 1.02 days [0.12 to 1.97 days], a difference determined to be statistically significant (p = 0.014). Centralizing the process for providing off-the-shelf spinal orthoses reduced the cost of a thoracic-lumbar sacral orthosis by $1,483 and the price of a lumbar-sacral orthosis by $1,327. Throughout the study, the new program reduced the cost of providing spinal orthoses by $175,319. ConclusionsThe results demonstrate that the nursing-led centralized spinal orthosis program positively impacted the quality of care provided to our patients while also reducing the cost of delivering the orthoses. Tweetable abstractA nursing-led centralized spinal orthosis program reduces the cost of care while reducing time to mobilization and length of stay.

Remote sensing-based estimation of precipitation data (2000-2015) in Ecuador's Loja province

The primary climatic parameter frequently scrutinized in water balance assessments for water utilization is precipitation. Given its considerable variability across locations and over time, it is imperative to rely on high-quality statistical information to facilitate accurate analyses. This study aims to refine the estimation of precipitation data by enhancing information obtained from freely accessible satellite sensors with data collected from established observation stations. Monthly precipitation data spanning from 2000 to 2015 were gathered from 24 stations. Three distinct methodologies were employed to adjust individual station data to address missing data. Consistency analysis and data refinement were conducted for stations requiring adjustments, utilizing graphical analysis and non-parametric statistical techniques. The satellite products under evaluation correspond to the IMERG v6 algorithm. Subsequently, statistical metrics were used to compare observed and estimated data. A correction coefficient was computed by aligning monthly means between observed and calculated data to mitigate random and systemic errors. The IMERG algorithm demonstrates proficiency in accounting for altitude and seasonal variations, with the adjustment significantly enhancing its performance under these conditions.

Evaluating rail transit assignment models in the temporal dimension: The problem and its solution

Passenger flow is the foundation for urban rail transit (URT) operations. However, its calculated results from assignment models may deviate from the actual situation in both spatial and temporal dimensions, which arouses more attention and needs to be evaluated in particular. On the other hand, onboard video data from URT trains provides a potential way for model evaluation. This study defines the evaluation problem and proposes a methodological solution for evaluating rail transit assignment models in the temporal dimension, including qualitative validation and difference quantification. A suitable time granularity is determined for the best effectiveness and onboard video data is used for actual passenger flow extraction. The gap between the actual and the calculated by the model is identified with nonparametric statistical techniques (NPSTs) and quantified with time series similarity measurement (TSSM) methods. A case study on the Shanghai metro demonstrates the performance of the proposed approach, and several practice implications for URT operation agencies are also discussed.

A Consumer Data Privacy Protection Model Based on Non-Parametric Statistics for Dynamic Data Publishing in e-Commerce Platforms

Objectives: Consumer data privacy on e-commerce platforms is increasingly crucial. This study aims to investigate privacy protection mechanisms, particularly focusing on personal and corporate secrets. It seeks to understand individual perspectives on privacy and preferences for data disclosure. The primary objective is to explore methods for safeguarding personal information while maintaining data integrity. Methods/Analysis: We employ non-parametric statistical techniques to analyze consumer behavior and preferences on e-commerce platforms. This involves examining patterns of data disclosure and identifying sensitive information shared by users. By studying communication dynamics and recording practices, we assess the efficacy of current privacy protection measures. Novelty/Improvement: This study contributes to the understanding of consumer privacy protection by emphasizing the importance of non-parametric statistical methods in e-commerce research. Our findings underscore the need for enhanced privacy measures. We advocate for further research and development of innovative privacy-enhancing technologies to address evolving privacy challenges in online commerce. Findings:Our research highlights the significance of personal privacy concerns in e-commerce settings. We identify a spectrum of privacy attitudes among users, ranging from strict confidentiality to selective disclosure. Furthermore, our analysis reveals potential vulnerabilities in current privacy safeguards, particularly regarding the collection and storage of sensitive data on e-commerce platforms. Doi: 10.28991/HIJ-2024-05-02-013 Full Text: PDF

On Some Factors Contributing to Entrepreneurial Economic Success in South-West, Nigeria: An Empirical Approach

This essay explores the elements that lead to the financial success of entrepreneurs. In particular, it conducted an empirical investigation into the possibility that factors such as age, religious beliefs, risk-taking, marketing strategies, timely and adequate planning, employees’ commitment, accessibility to working capital, reduced bureaucratic steps on import and export matters, education level, and age and technology infrastructure could influence an entrepreneur’s level of success. The study used a descriptive survey research design. The study’s participants were business owners in the six states that make up Nigeria’s southwest region who operated on a micro, small, and medium scale. The 720 entrepreneurs who made up the study’s sample were chosen through a multi-stage sampling process. A self-structured questionnaire covering all the objectives was used as the data collection tool, and it was administered to a select group of entrepreneurs. In addition to applying non-parametric statistical techniques like the chi-squared test and phi statistic, the collected data were analyzed using descriptive statistics like frequencies, percentages, and graphics. In the R-Studio (Posit) environment, the data analysis operations were carried out. The findings showed that a successful entrepreneurship is greatly influenced by a number of factors, including the availability of operating capital, the degree of employee commitment, technological and infrastructural capabilities, risk-taking, effective marketing strategies, adequate and appropriate planning, educational attainment, and age. Success in entrepreneurship, however, is unrelated to fewer bureaucratic procedures involved in the import and export of goods. It was determined that the bulk of the previously mentioned elements affect any business’s ability to succeed in today’s world. Thus, it was suggested that all tiers of government be counselled to provide funding, among other things, to serious business owners.

Spatial and Temporal Analysis of Road Traffic Accidents in Major Californian Cities Using a Geographic Information System

Road traffic accidents have increased globally, which has led to significant challenges to urban safety and public health. This concerning trend is also evident in California, where major cities have seen a rise in accidents. This research conducts a spatio-temporal analysis of traffic accidents across the four major Californian cities—Los Angeles, Sacramento, San Diego, and San Jose—over five years. It achieves this through an integration of Geographic Information System (GIS) functionalities (space–time cube analysis) with non-parametric statistical and spatial techniques (DBSCAN, KDE, and the Getis-Ord Gi* method). Our findings from the temporal analysis showed that the most accidents occurred in Los Angeles over five years, while San Diego and San Jose had the least occurrences. The severity maps showed that the majority of accidents in all cities were level 2. Moreover, spatio-temporal dynamics, captured via the space–time cube analysis, visualized significant accident hotspot locations. The clustering of accidents using DBSCAN verified the temporal and hotspot analysis results by showing areas with high accident rates and different clustering patterns. Additionally, integrating KDE with the population density and the Getis-Ord Gi* method explained the relationship between high-density regions and accident occurrences. The utilization of GIS-based analytical techniques in this study shows the complex interplay between accident occurrences, severity, and demographic factors. The insight gained from this study can be further used to implement effective data-driven road safety strategies.

Integrating industry-crowdsourced projects in university capstone courses: A comparative study using parametric statistics and sentiment analysis

This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program’s learning objectives. The study aimed to evaluate the efficacy of this pedagogical approach compared to traditional capstone courses. This evaluation involved collecting data from grading systems and anonymous course surveys. A novel aspect of the research design was the synergetic combination of nonparametric and parametric statistical techniques with modern machine learning (ML) algorithms to analyse the students’ grades, survey comments and third-party course opinion comments. Additionally, independent third-party course ratings were examined to triangulate the results. Findings revealed that while the academic performance in the industry-crowdsourced capstone course mirrored that of the traditional course, the industry-crowdsourced variant elicited significantly more positive responses in course surveys. Furthermore, ML sentiment analysis of comments from third-party forums indicated a stronger positive reception for the industry-crowdsourced course over the traditional approach.

Module Discovery Learning Biodiversity Material Based on Gunungkidul Beach to Increasing Interest and Independence in Learning of High School Students

The research carried out aims to determine the feasibility, practicality and effectiveness of the Gunung Kidul beach-based Discovery Learning module, on biodiversity material in increasing high school students' interest and independence in learning. The research carried out is a type of development research using the ADDIE model which consists of several stages, namely analysis, design, development, implementation and evaluation. The product produced in this research is a biology learning module on biodiversity material which is integrated with the Gunung Kidul beach-based Discovery Learning learning model. The learning module developed was validated by expert validators and practitioners, then tested for effectiveness on class X students of SMA N 1 Depok Sleman using the non-equivalent pre-test, post-test control group design technique. Data collection was carried out using direct interview techniques with biology teachers and distribution of student needs analysis questionnaires, assessment of material experts, media experts, learning experts, teacher and student practicality, student learning interest questionnaires, and student learning independence questionnaires. Data analysis uses non-parametric statistical test techniques with the Mann-Withney model, parametric statistical tests with the independent sample t test model and N-gain score. Gunung Kidul beach-based discovery learning learning modules on biodiversity material are feasible, and can be practically used in learning activities and are effectively used in increasing high school students' interest and independence in learning

Organizational Commitment: The Key to Reduce Employees’ Resistance to Change

This report recognizes some of the most important causes of resistance to organizational change; some of which are related to the skills of employees and others to the company's communication procedures, which affects the work performance of employees and the image of the organization. To achieve the organization's objectives, the importance of structural change management, organizational culture, and the ability to modify strategies when circumstances warrant is also documented: First to contain, and then to reduce resistance to organizational change. The report includes a comparison of the proportion of successful and unsuccessful efforts regarding resistance to "organizational change"; a process that can be conceived as a "dialectical progression", whose main support is the institutional commitment implicit in the mission, vision, and core values of the organization. A nonparametric statistical technique: Jonckheere-Terpstra test was selected to perform the data analysis.

Covid-19 Dan Dampaknya Pada Kinerja Keuangan Perusahaan Manufaktur Di Indonesia

At the end of 2019, the world was startled by the emergence of a new disease caused by the Sars CoV-2 virus, now known as Coronavirus Disease-19 (Covid-19). The manufacturing sector is one of the industries affected by the onset of Covid-19 in Indonesia. Covid-19 forced manufacturing companies to lay off employees and caused a decline in the Manufacturing Purchasing Managers Index in 2020. This research aims to analyze the financial performance of manufacturing companies in Indonesia, specifically focusing on profitability ratios before and during the Covid-19 pandemic in 2020. This study is a quantitative research type using descriptive analysis. The hypothesis testing in this research utilizes non-parametric statistical analysis techniques, employing the Wilcoxon Signed Rank Test approach with the statistical tool SPSS version 25.0. The results of the research indicate that Net Profit Margin (NPM), Return On Asset (ROA), and Return On Equity (ROE) before Covid-19 in 2019 were better compared to Net Profit Margin (NPM), Return On Asset (ROA), and Return On Equity (ROE) during the Covid-19 pandemic in 2020 for manufacturing companies in Indonesia.

Role of government as moderator: Porter’s diamond firm strategy, structure, and rivalry attribute and industry’s performance

The prime purpose of the research was to examine, through empirical study, and help determine the government’s role as moderator in the relationship between Porter’s diamond firm strategy, structure, and rivalry construct and the firm’s performance in Pakistan’s automotive sector. In the study, the research philosophy was positivism, and a deductive approach was applied as the main reason to establish generalizations in the results. With a view to determining the magnitude, direction, and significance, researchers emphasized descriptive and inferential statistical techniques. Data was solicited from 166 sample respondents through a structured questionnaire. To establish the reliability perspective and validity context of the questionnaire constructs, a pilot study was part of the research study. Parametric and nonparametric statistical techniques also became an integral part of analysis for drawing objectively based conclusions. For moderation purposes, the tool was macro, Process v3.0 (model 1). The study findings aptly indicate that in a theoretical context, the relationship is not significant, whereas the practical perspective reflects that government policy does influence industry firms’ performance; however, the mediating role of government between Porter’s constructs, viz., firm strategy, structure, and rivalry, and industry firms’ performance documented no impact. In the constituencies of academia, automotive sector players, and policymakers, the moderation results shed light on theoretical and practical contextualization.

Hubungan Antara Regulasi Diri Dengan Efikasi Diri Pengambilan Keputusan Karier Pada Siswa SMK Wikrama Bogor

This research aims to determine the relationship between self-regulation and career decision-making self-efficacy among students at Wikrama Vocational School, Bogor. Vocational school graduates are the biggest contributor to the unemployment rate. One that influences. Vocational school education is provided to prepare students for the transition from school to the world of work. This research is quantitative research using a survey method distributed online. The research participants were 486 grade 12 students at Wikrama Vocational School, Bogor, aged 16-18 years. The measuring tools in this research used the Self-Regulation Questionnaire (SRQ) and Career Decision Self-Efficacy (CDSE). Data analysis used non-parametric statistical techniques with the Spearman's Rho correlation test technique. The results of the research analysis show that there is a significant positive relationship between self-regulation and career decision-making self-efficacy for Wikrama Bogor Vocational School students (r = 0.545; p = <0.001). So, the higher the self-regulation that Wikrama Bogor Vocational School students have, the higher the self-efficacy they have in making career decisions.

Analysis of The Influence of Accounting Information System and Leadership Style on Performance of Employees in National Poultry Farming Company

The era of globalization, which increases information technology, has increased competition in the business world. Companies in this era are increasingly complex and competitive. Every business must be prepared to deal with technical advancements, all consumer wants, and fierce rivalry from other businesses. Companies need a solid plan if they wish to survive the competition. The purpose of this study is to examine how leadership style and the caliber of accounting information systems affect employee performance. This study makes use of first-hand information gathered via accountant survey data. Nonprobability sampling was the method of selection that was employed in this study. This study adopts a quantitative methodology and makes use of IBM SPSS and non-parametric statistical analysis techniques. The test results demonstrate that leadership style and the caliber of the accounting information system are key determinants of employee success.

Comparison of Rally Length between Women and Men in High-Level Spanish Volleyball.

The aim of this study was to evaluate whether the rally length in high-level Spanish volleyball was longer in women than in men. A total of 1,786 rallies were observed: 792 for women and 994 for men. The recorded variables were match (quarter-final 1, quarter-final 2, semi-final 1, semi-final 2, final), gender (men, women), rally length (seconds), pseudo-rally (no, yes), and terminal event (ball out of sight, ball in/out, fault). Different non-parametric statistical techniques were used to compare the rally length between groups or subsets of data, i.e., the Kruskal-Wallis H test, the Mann-Whitney U test, quantile regression, and survival analysis. The mean and median rally length was significantly and slightly longer in women than in men. The rally length difference between genders was barely 1 s in quantile 0.5 or median, while in quantile 0.95, it was just over 4 s. In women, the probability of ending the rally at 3.9, 5.1, 10.2, and 43.9 s (at 4.4, 6.3, 11.6, and 43.9 s without pseudo-rallies) was 25%, 50%, 75%, and 100%, respectively. In men, the probability of ending the rally at 3.2, 4.3, 7.9, and 29.1 s (at 3.9, 4.8, 8.8, and 29.1 s without pseudo-rallies) was 25%, 50%, 75%, and 100%, respectively. These temporal thresholds can help volleyball coaches to train their players in a coherent manner.

Analysis of The Influence of Accounting Information System and Leadership Style on Performance of Employees in National Poultry Farming Company

The era of globalization, which increases information technology, has increased competition in the business world. Companies in this era are increasingly complex and competitive. Every business must be prepared to deal with technical advancements, all consumer wants, and fierce rivalry from other businesses. Companies need a solid plan if they wish to survive the competition. The purpose of this study is to examine how leadership style and the caliber of accounting information systems affect employee performance. This study makes use of first-hand information gathered via accountant survey data. Nonprobability sampling was the method of selection that was employed in this study. This study adopts a quantitative methodology and makes use of IBM SPSS and non-parametric statistical analysis techniques. The test results demonstrate that leadership style and the caliber of the accounting information system are key determinants of employee success.

An increasing trend in daily monsoon precipitation extreme indices over Pakistan and its relationship with atmospheric circulations

This study assessed spatiotemporal trends in daily monsoon precipitation extremes at seasonal and sub-seasonal scales (June, July, August, and September) and their links with atmospheric circulations over Pakistan. The study used observed precipitation data from fifty in-situ stations and reanalysis products from the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction/the National Center for Atmospheric Research (NCEP/NCAR) during 1981–2018. A suite of seven extreme precipitation indices and non-parametric statistical techniques were used to infer trends in the frequency and intensity of extreme precipitation indices. An increase in frequency and intensity of overall extreme indices was evident, with a maximum tendency in the country’s northwestern (z-score=>2.5), central, and eastern (z-score > 4) monsoon-dominant parts. The northern and southwestern parts of the country exhibited a slight decrease (z-score <–2) in frequency and intensity. The Sen’s Slope estimator (SSE) shows an increase in western parts (0.20 days) indicating a shift in the maxima of the monsoon precipitation. The regional precipitation shows an increase in wet days (R1 mm) with higher values of mMK (3.71) and SSE (0.3) in region 2 Similar results of moderate regional increase are evident for extreme indices except regions 1 and 3. The extreme 1-day maximum precipitation increased in region 3 (mMK: 1.39, SSE: 2.32). The extremely wet days (R99p TOT) precipitation has a moderate increase in all regions with a decrease in region 1. The temporal mutations showed dynamic changes, clearly reflecting the country’s historical extreme events. The frequency and intensity of precipitation extremes negatively correlated with the altitude (R = −0.00039). The probability density function (PDF) showed a significant increase in the density during June and September with a probabilistic positive shift during July and August. The intensified mid-latitude westerlies and subtropical zonal easterlies teleconnections, strengthening of the monsoon trough, and land-ocean thermal contrast are the potential drivers of the increasing trend in precipitation extremes. The current study could serve as a benchmark for future researchers and policymakers to devise effective mitigation strategies for sustainable development.