Hypothesis Testing Method Research Articles

Dynamic Defect Detection in Fast, Robust NDE Methods by Transfer Learning Based Optimally Binned Hypothesis Tests

ABSTRACT The structural integrity of safety-critical infrastructures diminishes over time, necessitating periodic inspections. The gathering of low-noise, precise nondestructive evaluation (NDE) readings for defect detection can be both time-consuming and costly. In practical applications, NDE data can be highly noisy due to factors like liftoff/stand-off distances, probe drift, scanning speed, and variations in data acquisition rates. Given the broad spectrum of potential uncertainties that can contribute to noise accumulation, characterizing the noise in such NDE data presents significant difficulties. As a result, the extraction of defect signals through deconvolution becomes challenging. This article introduces an NDE-based dynamic defect tracking framework designed for robust conditions. It incorporates regular periodic monitoring of the material under test (MUT) using a cost-effective, easy-to-implement magnetic flux leakage (MFL) probe. The framework proposes a dynamic setup that includes occasional, highly accurate, expensive MFL scans among regular, low-cost, noisy MFL scans. The objective is to detect and precisely track defect formation in metallic pipes over time, thereby enabling the efficient alarming and localization of defects before they reach detrimental sizes. A key characteristic of the proposed dynamic monitoring method is its noise type agnosticism in the low-cost MFL scans. It remains effective even when the underlying noise-producing uncertainties fluctuate significantly over time, a feature achieved through the use of transfer learning. The method transfers accurate information regarding the locations and sizes of existing corrosions from the detailed MFL scan to the subsequent noisy MFL inspections. With this supportive information from defective scan-points, it estimates the degradation of the signal-to-noise ratio (SNR) in the noisy MFL scans. The framework suggests binned hypothesis tests in noisy MFL scans, setting the level of aggregation based on the SNR estimate in the scan data. This proposed binned hypothesis test optimizes defect coverage and maintains control over the false discovery rate (FDR). Experimental MFL data, gathered under a wide range of uncertainties and defect types, illustrates the highly heterogeneous nature of noise distributions in low-cost MFL scans and the significant variance in SNR deteriorations. The necessity of using binned hypothesis tests in these low-cost MFL data is highlighted by the poor performance of pointwise multiple hypothesis tests. Finally, the high effectiveness of the proposed transfer learning-based binned hypothesis testing method is demonstrated. Although the method was applied to MFL data in this instance, it is also suitable for other NDE applications. The applicability of the algorithms has also been confirmed through validation on experimentally generated Eddy Current (EC) data.

The Influence of Learning Style on Students' Concentration

Research between learning styles and learning concentration is rarely done. Learning styles are related to how students can be comfortable with a learning method, so learning styles can be a good indication of influencing learning concentration. This study aims to determine the influence of the three learning styles on learning concentration. The study uses a non-experimental quantitative method with a correlational design. The subjects of this study were 202 undergraduate students. The sampling technique used is convenience sampling. This research uses the Indonesian language learning style scale and the Indonesian language learning concentration scale. The hypothesis testing method used in this research is a multiple regression test. The results of this study found that the three learning styles did not have a significant effect on learning concentration.
 Keywords: learning styles, learning concentration

The Influence of Service Quality on Train Passenger Satisfaction at Rantau Prapat Station PT KAI Persero Divre I North Sumatra

In order to keep clients using this kind of transportation and to keep the business afloat, PT KAI places a high priority on their satisfaction. Employees of KAI are required to utilize five dimensions in its implementation: tangibles, assurance, responsiveness, empathy, and consistency. It is undoubtedly not ideal in its implementation at each station, as some travelers continue to be dissatisfied with the offers that are made. Examples of this include the fact that some people are still unable to board the train without a ticket and the indifference of staff members. Following basic observations by the researchers, there was a decline in staff responsiveness and overall satisfaction. The goal of this study is to determine how much the independent variable affects the dependent variable. In this quantitative analysis, primary and secondary data sources are consulted. Three techniques were employed to gather data: questionnaire completion, documentation, and observation. Using SPSS (Statistical Product and Service Solution), the instrument test, classical assumption test, hypothesis test, and simple linear regression method are the data analysis techniques employed. Once the researcher had finished using the data that had been collected. With a significance value (Sig) of 0.000, it may be inferred that the quality of the services offered significantly affects passenger happiness. Less than 0.05. The T test decision-making framework indicates that H1 is accepted and H0 is rejected, indicating that service quality has an impact on passengers' pleasure with trains. When the coefficient of determination hypothesis is evaluated using the SPSS version 26 software, a value of 0.906 can be obtained. This indicates that there is a 90.6% link between passenger satisfaction and service quality, with the remaining 9.4% coming from factors that have not been thoroughly investigated.

PENGARUH PENGGUNAAN MEDIA FLASH CARD TERHADAP HASIL BELAJAR MATEMATIKA SISWA SLOW LEARNER

Students with slower learning abilities face difficulties in receiving information. Therefore, they require engaging learning media, and one of them is the use of learning cards. This research aims to evaluate the impact of using learning cards in teaching mathematics, specifically in the topic of spatial structures, on the learning outcomes of students with slower learning abilities at Madrasah Ibtidaiyah. This study employs a quasi-experimental method at Madrasah Ibtidaiyah Negeri OKU Timur in the academic year 2022/2023. The research design adopts a time series format, and data analysis is carried out using an associative hypothesis testing method. The analysis results show a Z value of 2.70, exceeding the critical value of 1.96. Therefore, H0 is rejected, and H1 is accepted. This finding indicates a significant influence of using learning cards on improving the mathematics learning outcomes of students with slower learning abilities. The pretest data reveals an average score of 54.4, while the posttest data yields an average score of 77.2. This analysis indicates a significant difference between mathematics learning outcomes before and after the implementation of learning cards. The average learning outcomes increased after using learning cards, demonstrating the effectiveness of this media in enhancing the understanding of students with slower learning abilities regarding spatial structures

The Scientology of Hypothesis Testing in Empirical Research: Emphasizing Economic Significance

Over the decades, scientists across various disciplines have cautioned against the practice of over-emphasizing statistical significance at the expense of economic or practical significance. It seems that empirical researchers in the 21st century have not heeded the caution because meeting statistical significance targets continue to take precedence over the wider discovery and publication of scientifically objective findings. Statistically insignificant results are rarely reported, in part due to publication bias towards statistically significant findings. The survey finds that although large sample sizes are widely used in empirical economics and finance research, none of the surveyed papers adopted alternative methods of hypothesis testing, such as Bayesian methods. All of them explicitly or implicitly used the classical Fisher’s hypothesis testing methods. This study finds that discussions on economic significance in nearly all papers (almost 97% of papers) only wrote one sentence or two regarding the magnitude of the effect of the regressors and a declaration that the findings were economically significant. We recommend that to enhance research credibility, other methods of hypothesis testing such as Bayesian methods, should be adopted. Journal article publishers should encourage the publication of statistically insignificant empirical findings. Economic or practical significance should be emphasized and comprehensively discussed.

Research on a 44 Day Quasi-periodic Oscillation of Optical Bands for BL Lac S5 0716+714

By means of astronomical observation data from the 60 cm Telescope at Yunnan Observatory, optical data in the g, r, and i bands were collected for BL Lac S5 0716+714, spanning from 2017 November 10 to 2018 May 15. The original data set contains 21,396 quasi-simultaneous multiband points, with 7132 data points for each band. The Lomb–Scargle periodogram method and the weighted wavelet Z-transform method were used to search for a quasi-periodic oscillation (QPO) signal in the data. For the first time, we report a QPO signal at 44 ± 6 days with a final significance of 3.98σ. Further analysis of the spectrum index reveals that the 44 day QPO signal is most likely explained by a helical motion of a blob with velocity β in the jet, where the viewing angle of the emission region in the jet undergoes periodic variations. In addition, we employed the hypothesis testing method (the null hypothesis) to analyze the flux distribution and determined that a double log-normal distribution provides a better fit; thus, there may be two radiative mini-regions within a jet in this source, so this 44 day QPO signal may be superimposed on a longer-term outburst.

Improved target detection method for space-based optoelectronic systems

The detection of faint and small targets by space-based surveillance systems is difficult owing to the long distances, low energies, high speeds, high false alarm rates, and low algorithmic efficiencies involved in the process. To improve space object detection and help prevent collisions with critical facilities such as satellites, this study proposes an improved method for the detection of faint and small space-based targets. The proposed method consists of two components: star atlas preprocessing and space-based target detection. The star atlas preprocessing step applies multi-exposure image pyramidal weighted fusion to the original image containing the faint and small space-based target. After obtaining the image pyramidal weighted fusion result atlas, the algorithm employs threshold segmentation to improve the overall image clarity, highlight image details, and provide additional information for target detection. The detection of targets partially relies on the local symmetry of the image. Accordingly, a diffusion function describing the local symmetry is established to precisely locate stars by measuring the symmetry factor in a small area surrounding each pixel in the star atlas. This effectively removes the background stars while retaining high-definition and high-contrast images. The efficacy of the algorithm is validated using simulated datasets consisting of space-based and real images. The results demonstrate that the proposed technique improves the applicability of the multistage hypothesis testing (MHT) method in the context of a complex space environment, thus improving the performance of the space-based electro-optical detection system to better catalogue, identify, and track space targets.

Changes in cardiohemodynamics and cardiac arrhythmias in patients after coronavirus infection

Aim: To study cardiac arrhythmias and morpho-functional changes in patients in 3 months after a coronavirus infection.Material and methods. 96 patients, mean age 36 years, treated for coronavirus infection, after 3 months underwent Echo and Holter ECG monitoring. Patients were divided into groups depending on the degree of lung tissue damage according to computed tomography (CT): 1st 27 patients CT0, 2nd 39 patients CT1-2, 3rd 30 patients CT3-4; 22 patients control group. Statistics: considering the distribution of features different from normal, nonparametric methods of hypothesis testing were used.Results. In patients recovered from coronavirus infection a violation of heart rhythm conduction was established after 3 months. An increase in the activity of the sympathetic part of the autonomic nervous system (LF/HF) was found: in patients of group 2, the median value was – 5.9, in group 3 – 6.0; in addition, the global longitudinal systolic strain of the left ventricle decreased (–17.7 and –17.2, respectively). In patients with CT3–4, systolic pressure in the pulmonary artery increased (37.0 mmHg), the size of the left atrium increased, and segmental systolic LV strain decreased in comparison with the studied groups (p < 0.001). Correlations between left ventricular dysfunction and heart rate variability disorders, as well as prolongation of the QT interval (p < 0.001) were established.Conclusion. Cardiac arrhythmias were detected in patients in 3 months after the coronavirus infection. In patients with moderate and severe disease, the activity of the autonomic nervous system also increases, the global systolic strain of the left ventricle decreases. In addition, patients with CT3-4 increased systolic pressure in the pulmonary artery, increased the size of the left atrium, decreased segmental systolic strain of the left ventricle.

Analysis of Computed Tomography Dose Index (CTDI) And Dose Length Product (DLP) Dose Values On Non-Contrast Head, Chest And Abdominal CT Scan Examination At RSUD Ulin Banjarmasin

Background: CT scans produce the largest dose of radiation compared to other radiology modalities. The parameters for measuring the amount of radiation dose from the CT Scan aircraft are the Computed Tomography Dose Index (CTDI) and the Dose Lenght Product (DLP). One form of Bapeten supervision in controlling radiation protection is to optimize the Diagnostic Raference Level (DRL). At RSUD Ulin Banjarmasin, the CT Scan modality has never been measured for CT Scan dose on CT Scan examination of the Head, Thorax and Abdomen Non Contrast which are the most frequent examinations. Dosage parameters are important to see the values exposed to the patient. The purpose of this study was to determine the amount of radiation dose of patients on CT Scan examination of the Head, Thorax and Non-Contrasting Abdomen. Method: The research design used is quantitative descriptive. The method of collecting data is observational and uses secondary data. Data processing uses the descriptive hypothesis test method one sample t-test, by analyzing the value of radiation dose and comparing the DRL value set by Bapeten as a means to monitor the dose given α=0.05. Results: Dose values for CT Scan of Non Contrast Head 33.90±3.66 mGy for CTDIvol and 933.07±415.63 mGy.cm for DLP. CT Scan Thorax Non Contrast 5.83±1.90 mGy for CTDIvol and 179.80±63.72 mGy.cm for DLP. Non Contrast Abdominal CT Scan 10.88±2.30 mGy for CTDIvol and 528.70±137.75 mGy.cm for DLP. Conclusion: The dose value at RSUD Ulin Banjarmasin in each CT Scan examination of the Head, Thorax and Abdomen Non Contrast is still below the National DRL value set by BAPETEN.

PERAN WORD OF MOUTH MEMEDIASI PENGARUH SOCIAL MEDIA MARKETING INSTAGRAM TERHADAP KEPUTUSAN PEMBELIAN KULINER

This research aims to test and analyze how the influence of word of mouth mediates social media marketing on purchasing decisions. The population that will be used as research is 100 people. The sampling technique in this research was carried out using a purposive sampling method. The design used in this research is based on survey research hypothesis testing method data. The types of data in this research are qualitative and quantitative data. The collected data will be analyzed descriptively and processed using PLS version 4.0. The results of the analysis show that Social Media Marketing significantly strengthens the influence on Purchasing Decisions, Word of Mouth significantly strengthens the influence on Purchasing Decisions. And Word of Mouth significantly weakens the negative influence of Social Media Marketing on Purchasing Decisions.

Ukrainian Startup Ecosystem as a Driver of Economic and Strategic Resilience

The aim of the article is to comprehensively analyze the key adaptive transformations in the technological ecosystem of Ukraine during the wartime period as a driver of its economic and strategic development, in particular in the period of post-war reconstruction, as well as to generalize the most relevant approaches and features of evaluation of startups. Particular attention is paid to strategic startups in the field of defense, cybersecurity, deep learning algorithms, space and other advanced production technologies, in particular in the context of specific aspects that should be taken into account when assessing their value. The study uses general scientific methods and specific economic and statistical approaches, in particular methods of analysis and synthesis to classify approaches to evaluating startups, as well as descriptive statistics and graphical analysis to identify structural changes in the technological ecosystem of Ukraine. The carried out study showed that in recent years there has been a significant increase in the number and variety of startups specializing in strategic sectors of the economy. Their development is due to both the strategic needs of the State for means to increase defense capability and national security, and global technological trends, in particular in the field of artificial intelligence and cybersecurity. In addition, it is determined that for assessing the value of startups in strategic sectors of the economy, the most flexible and relevant are the method of real options, the method of testing hypotheses, and the approaches based on scenario analysis. The results of the presented study can be taken into account when improving traditional and new methods of evaluating startups and new companies, in particular in terms of taking into account their strategic value using premiums or other valuation techniques. Prospects for future research in this direction are to improve the existing methods for evaluating startups from strategic industries, taking into account the specifics of the sector and the high level of geopolitical and macroeconomic uncertainty.

Enhancing system safety in critical architectures: Augmented hypothesis testing with early design knowledge.

Hypothesis testing is a valuable method used to investigate ideas and test predictions arising from theories based on available data. In the context of critical system architecture, there is a need to effectively utilize hypothesis testing to identify faulty paths and improve system safety. This research aims to propose guidelines and best practices for presenting hypothesis testing in critical system architecture. The problem addressed in this study is the underutilization of hypothesis testing in life-critical system methods, resulting in a lack of identification of faulty paths. To address this challenge, we propose an enhanced pathway analysis technique that integrates error-derived information from a system's architectural description, thereby augmenting traditional hypothesis testing methods. By investigating various paths, we aim to identify false positive and false negative errors in life-critical system architecture. Furthermore, the proposed method is validated based on specific validation criteria for each step such as system boundary, assumption, content/architecture, and traceability validations. Also, the method is evaluated based on our claims. The results of our research highlight the significance of tracing errors in early system knowledge. By leveraging the augmented hypothesis testing method, we are able to identify hazards, safety constraints, and specific causes of unsafe actions more effectively. The findings emphasize the importance of integrating early design knowledge into hypothesis testing for enhanced hazard identification and improved system safety.

The Impact on Service Orientation and Organizational Support towards Organizational Commitment and Business Sustainability on Healthcare Providers in Surabaya

Competition has forced companies to not only focus on internal organizations, but also externally. Focusing on customers’ service provides ways to better identify, better serve, and better understand customers. While companies need support that comes from internal organizations to better support the day-to-day operation. Healthcare industries provided care in so many ways to the patients, such as clinical services, manufacture and medical equipment, and other healthcare related services such as insurance. This paper aims to better understand the commitment and sustainability of organizations, focusing on healthcare providers. While reviewing the current literature, this paper will also explain some of the views on previous studies and the relationship between the variables. A comprehensive analysis of the literature review on the research object will deepen our understanding of the selected topic. Healthcare in Indonesia has so many challenges and yet opportunities. With better management, better programs, it is expected that the healthcare industry will increase its sustainability and performance over the next couple decades. This study used 100 healthcare providers in Surabaya as samples using random sampling method. The questionnaires will be distributed to measure the samples’ level of agreement on the statements provided. The hypothesis testing method will be used to see the significance of each variable toward the dependent variables. From five hypotheses proposed, the highest value in regression testing will be used to provide suggestions and implications. The result of the study is expected to better understand on how to sustain the performance of healthcare industry in Surabaya.

Investigation of Methods for Determining the Aspect Angle of a Spatially Distributed Target in its Radar Image

The article is devoted to the problem of determining the aspect angle of a surface ship based on its radar image obtained in synthetic aperture radars. Among the main methods of solving this problem are the classical Bayesian method of multi-alternative hypothesis testing and its modifications, and/or the method of classifying surface ships located at different angles using artificial neural networks (ANNs). The study demonstrates that achieving high efficiency in aspect recognition using ANNs requires significant computational resources, as well as an access large, representative, and scalable training dataset. ANNs demonstrates high performance in various observation conditions in case sufficient computational and time resources; however, it is noteworthy that their effective training requires a substantial amount of processing time, reaching several hours. At the same time, classical methods are capable of performing calculations in fractions of a second, even on relatively low-powered devices. It is also worth noting that as the number of recognised classes increases, ANNs may consume up to tens of gigabytes of RAM, limiting the accessibility of this method in the aspect of task recognition of spatially distributed targets.

Nonparametric bootstrap methods for hypothesis testing in the event of double-censored data

<abstract><p>This paper illustrated how nonparametric bootstrap methods for double-censored data can be used to conduct some hypothesis tests, such as quartiles' hypothesis tests. Through simulation studies, the smoothed bootstrap (SB) method performed better results than Efron's method in most scenarios, particularly for small datasets. The SB method provided smaller discrepancies between the actual and nominal error rates.</p></abstract>

Climate change-induced degradation of expert range maps drawn for kissing bugs (Hemiptera: Reduviidae) and long-standing current and future sampling gaps across the Americas.

Kissing bugs are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease (CD). Despite their epidemiological relevance, kissing bug species are under sampled in terms of their diversity and it is unclear what biases exist in available kissing bug data. Under climate change, range maps for kissing bugs may become less accurate as species shift their ranges to track climatic tolerance. Quantify inventory completeness in available kissing bug data. Assess how well range maps are at conveying information about current distributions and potential future distributions subject to shift under climate change. Intersect forecasted changes in kissing bug distributions with contemporary sampling gaps to identify regions for future sampling of the group. Identify whether a phylogenetic signal is present in expert range knowledge as more closely related species may be similarly well or lesser understood. We used species distribution models (SDM), specifically constructed from Bayesian additive regression trees, with Bioclim variables, to forecast kissing bug distributions into 2100 and intersect these with current sampling gaps to identify priority regions for sampling. Expert range maps were assessed by the agreement between the expert map and SDM generated occurrence probability. We used classical hypothesis testing methods as well as tests of phylogenetic signal to meet our objectives. Expert range maps vary in their quality of depicting current kissing bug distributions. Most expert range maps decline in their ability to convey information about kissing bug occurrence over time, especially in under sampled areas. We found limited evidence for a phylogenetic signal in expert range map performance. Expert range maps are not a perfect account of species distributions and may degrade in their ability to accurately convey distribution knowledge under future climates. We identify regions where future sampling of kissing bugs will be crucial for completing biodiversity inventories.

Menjelajahi Nirwana Akademik Analisis Keberhasilan Universitas Muhammadiyah Jawa Timur dalam Memenangkan Hati Mahasiswa Melalui Kompetensi Staff Akademik, Keandalan Layanan dan Kilau Reputasi

This research aims to analyze the influence of the variables of Academic Staff Competence, Service Reliability, and University Reputation on Student Satisfaction in Muhammadiyah Universities in East Java using hypothesis testing method with the assistance of SPSS (Statistical Package for the Social Sciences) software. Data collected from 240 student respondents were analyzed to test the impact of these variables on student satisfaction. The SPSS analysis results show that all three variables, namely Academic Staff Competence, Service Reliability, and University Reputation, both simultaneously and partially, have a significant positive influence on student satisfaction. These findings have significant implications for higher education institutions, especially in designing strategies to improve service quality, develop academic staff competence, and enhance university reputation collectively.
 
 Keywords: Academic Staff Competence, Muhammadiyah Universities in East Java, University Reputation, Student Satisfaction, Service Reliability.

The Influence Of Learning Models On Students' Integrated Economic Sciences Learning Outcomes

This research aims to reveal the influence of the learning model on the economics integrated social science (IPS) learning outcomes of Setu Bekasi State Junior High School (SMP) 1 students. The research method used is quantitative research with an experimental approach. The population in this study was class VIII students at SMP Negeri 1 Setu Bekasi, totaling 400 students. The sample used in this research was divided into two classes, namely class VIII.1 which was the experimental class with 40 students and class VIII.2 which was the control class with 40 students. The experimental class applies power point learning media and the control class uses conventional learning media. Data collection for this research used an integrated Social Studies Economics learning outcomes test. The data analysis technique uses comparative quantitative. The hypothesis testing method used is t test analysis. The research results revealed: The t test calculation was 0.000 < 0.05, or Ho was rejected. Thus the hypothesis proposed is supported by empirical data and from the results of further tests it can be seen that the learning outcomes of students who use Power Point media are higher than students who use conventional media, so it can be concluded that Power Point learning media influences the learning outcomes of class VIII students in integrated economics social studies subject at SMPN 1 Setu Bekasi

Uncertainty quantification in computed tomography pulmonary angiography.

Computed tomography (CT) imaging of the thorax is widely used for the detection and monitoring of pulmonary embolism (PE). However, CT images can contain artifacts due to the acquisition or the processes involved in image reconstruction. Radiologists often have to distinguish between such artifacts and actual PEs. We provide a proof of concept in the form of a scalable hypothesis testing method for CT, to enable quantifying uncertainty of possible PEs. In particular, we introduce a Bayesian Framework to quantify the uncertainty of an observed compact structure that can be identified as a PE. We assess the ability of the method to operate under high-noise environments and with insufficient data.

Вплив оборотності оборотного капіталу, ліквідності, левериджу на прибутковість: Компанії харчової промисловості, що котируються на Індонезійській фондовій біржі

To measure how much success the company has in obtaining a rate of return on profit, it is necessary to conduct financial analysis with profitability ratios. This study aims to examine the effect of working capital turnover, liquidity, and leverage on profitability. This research is focused on Food & Beverage companies listed on the Indonesia Stock Exchange (IDX) for the period 2013-2018 with a population of 15 companies. Determination of the number of samples using purposive sampling method, so that a sample of 10 food & beverage companies was obtained. Hypothesis testing is done with multiple linear regression analysis techniques. The hypothesis testing method uses a significance level of 5%. Based on the test results and discussion that has been put forward by researchers Working Capital Turnover, Liquidity, and Leverage affect Profitability in Food & Beverage Companies listed on the Indonesia Stock Exchange for the 2013-2018 period.