Significance Tests Research Articles

How the Post-Data Severity Converts Testing Results into Evidence for or against Pertinent Inferential Claims.

The paper makes a case that the current discussions on replicability and the abuse of significance testing have overlooked a more general contributor to the untrustworthiness of published empirical evidence, which is the uninformed and recipe-like implementation of statistical modeling and inference. It is argued that this contributes to the untrustworthiness problem in several different ways, including [a] statistical misspecification, [b] unwarranted evidential interpretations of frequentist inference results, and [c] questionable modeling strategies that rely on curve-fitting. What is more, the alternative proposals to replace or modify frequentist testing, including [i] replacing p-values with observed confidence intervals and effects sizes, and [ii] redefining statistical significance, will not address the untrustworthiness of evidence problem since they are equally vulnerable to [a]-[c]. The paper calls for distinguishing between unduly data-dependant 'statistical results', such as a point estimate, a p-value, and accept/reject H0, from 'evidence for or against inferential claims'. The post-data severity (SEV) evaluation of the accept/reject H0 results, converts them into evidence for or against germane inferential claims. These claims can be used to address/elucidate several foundational issues, including (i) statistical vs. substantive significance, (ii) the large n problem, and (iii) the replicability of evidence. Also, the SEV perspective sheds light on the impertinence of the proposed alternatives [i]-[iii], and oppugns [iii] the alleged arbitrariness of framing H0 and H1 which is often exploited to undermine the credibility of frequentist testing.

Real-world overall survival and time to next treatment in patients with metastatic pancreatic ductal adenocarcinoma who received FOLFIRINOX and modified FOLFIRINOX in the first line.

629 Background: FOLFIRINOX (FFX) is a recommended first line (1L) treatment option for patients (pts) with mPDAC but is known for its high toxicity. Efforts to balance pts’ quality of life (QoL) during treatment with treatment effectiveness have led to the use of modified FOLFIRNOX (mFFX) regimens that employ decreased doses of FFX components. Further evidence is needed to assess OS and progression-free survival (PFS) among pts who receive FFX or mFFX treatment in the real world compared to the trial setting. We identified a real-world (RW) sample of pts with mPDAC treated with FFX and mFFX in 1L and assessed their OS, and, as a RW proxy for PFS, TTNT. Methods: This retrospective observational study utilized the Flatiron Metastatic Pancreatic Cancer Enhanced Data Mart. Adult pts diagnosed with mPDAC between January 2014 and May 2022 who initiated treatment with FFX or mFFX in 1L within 90 days of their diagnosis for metastatic disease were included in the study. mFFX was defined as administration of <150mg/m2 of irinotecan or <2,720mg/m2 5-FU total (bolus+infusion) during cycle 1; doses greater than these were considered FFX. TTNT was defined as duration between 1L treatment initiation and the start of second line therapy or death. Kaplan-Meier analyses were used to assess median OS and TTNT from the start of 1L FFX or mFFX treatment and log-rank tests for the statistical significance of differences in OS and TTNT. Results: 2,212 mPDAC pts met the study inclusion criteria, with 507 pts (23%) receiving FFX and 1,705 pts (77%) receiving mFFX in 1L. For FFX vs. mFFX, the median age at 1L initiation was 63yr vs. 65yr, 72% vs. 56% were male, 67% vs. 63% were white, 36% vs. 30% had an ECOG score of 0, 31% vs. 32% had an ECOG score of 1, and 83% vs. 81% received treatment at community oncology centers. For FFX vs. mFFX, median OS was 9.5 (95% CI: 8.9–10.7) vs. 9.0 months (95% CI: 8.4–9.7) (p=.452) and median TTNT was 4.8 (95% CI: 4.5–5.5) vs. 4.8 months (95% CI: 4.5–5.2) (p=.256). Conclusions: In a RW sample of 2,212 pts receiving 1L FFX and mFFX at primarily community oncology practices in the United States from 2014–2022, more than three-quarters received mFFX. Pts experienced similar median OS and TTNT across the two regimens, indicating that full-strength FFX may provide little benefit to OS in exchange for its increased toxicity. In the PRODIGE 4/ACCORD 11 trial of unmodified FFX, conducted earlier (2005–2009) among a group of 342 French pts, median OS was 11.1 months (95% CI: 9.0–13.1) and median PFS was 6.4 months (95% CI: 5.5–7.2). The median RW OS of FFX and mFFX pts in our study was numerically lower than the trial, as was RW TTNT compared with trial PFS. Future research should seek to understand the factors driving differences in RW and clinical trial outcomes as well as to assess the tradeoff between regimen toxicity and survival benefit.

The Effectiveness of Listening to Music on Learning English as a Foreign Language on UAD English Literature Students

Music serves as a valuable tool for enhancing English language proficiency. By incorporating music into their learning practices, students can improve their listening comprehension and overall speaking abilities. The present study aims to investigate the impact of listening to music on English language acquisition among English literature students as foreign language learners. Employing quantitative research methods, the researchers utilized a questionnaire as the data collection instrument, gathering responses from 6 English literature students at University of Ahmad Dahlan. The conclusion of the analysis is supported by the significant regression test result of 0.596, indicating an R-squared value that falls within the range of significant numbers. Consequently, the frequency of listening to music directly correlates with its effectiveness in influencing English language proficiency. It is important to acknowledge that other factors also contribute to English learning outcomes, including individual factors, social factors and instructional factors.

The Sailing Boat Price Study Based on Principal Component Regression Analysis

This paper conducts research on the pricing of second-hand sailboats under certain assumptions. Initially, a substantial amount of potentially relevant indicators and data related to sailboat pricing were collected from the internet. The Pearson correlation coefficient was used to investigate the correlation between these indicators and to filter them. Due to the distinctive characteristics of sailboats, they were categorized into monohull sailboats and catamarans for separate analysis. Subsequently, the processed data were used for price prediction using a BP neural network, yielding preliminary results. To obtain an explicit method for calculating sailboat prices, this paper employed principal component analysis to calculate the pricing objective function for both types of sailboats. This led to the derivation of two multivariate linear regression equations, which were subjected to significance testing. The results indicate that the objective functions obtained in this paper can serve as references for pricing second-hand sailboats.

Influence of depressurization mode on natural gas hydrate production characteristics: One-dimensional experimental study

The latest research suggests that using depressurization methods and their enhancements could be the most effective way to produce natural gas hydrates efficiently in marine areas. Therefore, it's crucial to investigate the gas production behavior and the changes in temperature and pressure within natural gas hydrate reservoirs under different depressurization methods. In this paper, the self-developed one-dimensional natural gas hydrate production simulation test system was utilized to conduct one-dimensional depressurization production tests during two depressurization modes of significant depressurization and slow depressurization. The findings indicated that the minimum temperature increment-depressurization rate curves in significant depressurization tests exhibited irregular patterns, primarily due to the frequency and intensity of hydrate reformation, while the smaller the depressurization rate, the larger the minimum temperature increment and the smaller the maximum dissociation rate under slow depressurization. In addition, when maintaining a fixed hydrate saturation level, the peak gas production rate showed a decline with decreasing depressurization rate. However, the exact correlation between the peak gas production rate and the depressurization rate remained uncertain due to the unpredictable nature of the “armoring” effect.

The Correlation of Calistung Ability With Readiness Elementary School TK B Children In Seluma District Seluma Regency City

Finding out how calistung abilities relate to kids' preparedness for kindergarten B primary school in Seluma Kota District, Seluma Regency, was the aim of this study. This study used a correlational quantitative approach. The population amounted to 168 people and the sample taken amounted to 42 children with sampling techniques using proportional cluster sampling. A questionnaire served as the method of data collecting. Product moment correlation is the analytical method used to analyze research data. The average value in the low group was 2.516, according to the data. There is a strong correlation between preparation for entry into primary school and calistung abilities. This is based on the Pearson product moment significance test which is obtained from a significance value of less than 0.05 (0.306 < 0.05) so that Ha is accepted. It is suggested to future researchers to use different factors such as parents' perceptions of literacy skills.

Pengembangan Gim Serius Untuk Pengenalan Jamu Menggunakan Metodologi Putaran Permainan

Jamu is a traditional herbal beverage that represents a cultural heritage with various health benefits. Despite this, adolescents tend to turn to chemical medications. This research proposes the development of an educational and engaging serious game to introduce jamu to the adolescent age group. The gameplay loop methodology is employed to ensure optimal connectivity between the game system and jamu educational content. The game design has been successfully implemented in the development of the game using the Unity game engine, resulting in an educational game based on significance testing and GUESS validation. The game is also deemed engaging based on the correlation test results. The Gameplay Loop method successfully maintains the connectivity between educational content and the game system, indicating that the game effectively imparts understanding of jamu to its players.

Impact of Auxiliary Features on Retention of Short Dental Crowns: An In-Vitro Analysis of Box and Groove Preparations.

BACKGROUND Several auxiliary features have been proposed to achieve sustainable retention for short-prepared dental crowns; however, achieving retention is challenging. This study aimed to assess the impact of increased total occlusal convergence and auxiliary preparation factors like box and groove on the retention form of short tooth preparations. MATERIAL AND METHODS Eighty resin machine-milled dies with a height of 3 mm and a deep chamfer margin of 1 mm were prepared to mimic the short-prepared molar. Initially, 2 teeth were prepared following the guidelines, and the total occlusal convergence was kept at 10° and 20°, respectively. Auxiliary features such as the proximal box and buccal groove were prepared on separate 20° dies. Eighty dies were prepared with 10 samples each for 10°, 20°, 20° with proximal box and 20° with buccal groove for zirconia (n=40) and metal crowns (n=40). Cementation was done with glass ionomer luting cement, and a pull-off test was conducted. Data were analyzed using one-way analysis of variance and post hoc fisher least significant difference test (P<0.05). RESULTS The highest mean was observed in the proximal box group with the metal crown (14.59), and the lowest in the group with 20° zirconia crowns (9.12). Within groups, the highest retentive values were found for the 20° taper with proximal box preparation; the lowest was for the 20° taper group. CONCLUSIONS Within the study limitations, it could be concluded that incorporating a proximal box or buccal groove in short tooth preparations with an increased total occlusal convergence improved retentive values.

Analisis Pengaruh Harga, Word Of Mouth Dan Kualitas Produk Terhadap Keputusan Pembelian Konsumen Pada Restoran Seafood Syurga Medan

This research aims to find out the relationship of price variables, word of mouth and product quality to consumer purchasing decisions at Restaurant Seafood Syurga Medan. The purchase decision is a consideration made by the consumer before deciding to buy or consume a good or service in a certain place. In this study, it analyzes about the price, word of mouth and quality of the product that is supposed to affect consumer purchase decisions. The research uses descriptive analysis methods, classical assumption tests, double linear regression tests, partial tests (T-tests), simultaneous significance tests (F-testes) and determination coefficients (R2) with the help of Software Statistical Program of Social Science (SPSS) version 26 for Windows. The objects of the study are 90 people consumer. The results of the analysis show that simultaneously price, word of mouth and product quality influence consumer decisions on seafood dining house of Syurga city of Medan. Results of the determination coefficient testing showed the influence of price variables, Word of Mouth and quality of products on consumer purchasing decisions with an influence contribution of 53% and the remaining 47% are influenced by other variables outside the research such as promotional factors, customer service, appearance, road access and so on.&#x0D; Keywords : Price, Word Of Mouth, Product Quality, Purchasing Decisions

Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric chest X-ray images.

Model initialization techniques are vital for improving the performance and reliability of deep learning models in medical computer vision applications. While much literature exists on non-medical images, the impacts on medical images, particularly chest X-rays (CXRs) are less understood. Addressing this gap, our study explores three deep model initialization techniques: Cold-start, Warm-start, and Shrink and Perturb start, focusing on adult and pediatric populations. We specifically focus on scenarios with periodically arriving data for training, thereby embracing the real-world scenarios of ongoing data influx and the need for model updates. We evaluate these models for generalizability against external adult and pediatric CXR datasets. We also propose novel ensemble methods: F-score-weighted Sequential Least-Squares Quadratic Programming (F-SLSQP) and Attention-Guided Ensembles with Learnable Fuzzy Softmax to aggregate weight parameters from multiple models to capitalize on their collective knowledge and complementary representations. We perform statistical significance tests with 95% confidence intervals and p-values to analyze model performance. Our evaluations indicate models initialized with ImageNet-pretrained weights demonstrate superior generalizability over randomly initialized counterparts, contradicting some findings for non-medical images. Notably, ImageNet-pretrained models exhibit consistent performance during internal and external testing across different training scenarios. Weight-level ensembles of these models show significantly higher recall (p<0.05) during testing compared to individual models. Thus, our study accentuates the benefits of ImageNet-pretrained weight initialization, especially when used with weight-level ensembles, for creating robust and generalizable deep learning solutions.

Reproductive Health Problems and Health Care Services Offered to Female Inmates of Women Jail Multan

Background: Women prisoners’ health is one of the major challenges among public health issues since the increasing incarceration rate has a direct impact on prisoners’ health status. Female prisoners often face many health issues in which most important are reproductive health problems. The prison services regarding reproductive health needs of female inmates vary in every jail. Unfortunately, in many prisons, health care services for women are still not adequate. &#x0D; Objectives: The objectives of the study are to determine the frequency of reproductive health problems of female inmates and to assess the health care services offered to female inmates of Women Jail Multan. &#x0D; Method: It was cross-sectional descriptive study in which 118 female inmates of reproductive age group were included. Data was collected through questionnaire which was entered in to computer using SPSS 20.0. Frequencies and percentages were calculated and data was presented in tables. Means, Standard Deviations and Correlation were calculated. ANOVA was applied to test significance and Chi-square test was applied. Level of significance was kept at p ≤ 0.05. &#x0D; Results: Among 118 female inmates, 33.9% were 31-40 years old, 87.3% were married and 78.0% were illiterate. The length of incarceration of 42.4% female inmates was upto 12 months. 35.0% had 1-2 children and 16.5% were living in jail with their children. Majority (92.4%) had gynecological problem and 82.2% had medical problems while 11.0% had experienced sexual violence by jail staff. Only 2 females were pregnant. 100.0% female inmates had availability of lady doctor or LHV for antenatal check-up.100.0% female inmates were provided proper diet and food supplements and the quality of food was satisfactory. &#x0D; Conclusion: Study revealed that health care services for reproductive problems including obstetric and gynecological issues was satisfactory however prevalence of gynecological issues was high. Sexual violence of female inmates faced by jail staff during imprisonment was noticed for which strict legislative measures should be taken.&#x0D;

Effectiveness of typodont, quail egg and virtual simulation for ultrasonic periodontal scaling teaching among pre-clinical students: a randomized trial

BackgroundThis study aimed to compare the efficacy of three different techniques, namely virtual simulation technology (VS), traditional pathological typodont (TT), and quail egg (QE), in pre-clinical training of periodontal ultrasonic scaling. It also aimed to propose an integrated teaching approach for ultrasonic scaling teaching.MethodsThis single-blind randomized multi-arm trial enrolled 108 fourth-year students from Guanghua School of Stomatology at Sun Yat-sen University. The participants were randomly, evenly assigned to VS, TT, or QE group. First, the participants received theoretical review on ultrasonic scaling and demonstrative teaching. Then in the 90-minute operation training by group, students used traditional typodont equipped in head-simulators, raw quail eggs, or scaling module of the UniDental VS system respectively. Then all participants practiced on pathological models for 30 min. In the final operation examination, participants were instructed to remove the supra- and sub-gingival calculi pre-set on designated teeth by ultrasonic scalers within 30 min. Their performances were evaluated by residual calculus rate and a multi-perspective scoring scale. After the examination, questionnaires were provided to assess the teaching effects of each method and the fidelity of VS. Statistical analysis was carried out using one-way, two-way ANOVA, and multiple t-test.ResultsStudents in VS group had significant higher total test scores than QE group (87.89 ± 6.81, 83.53 ± 8.14) and TT group (85.03 ± 6.81). VS group scored higher in several dimensional comparisons with the other two groups, especially in difficult situations. QE group had higher scores particularly in force application and supra-gingival scaling. TT group scored the highest in pivot stability practice and body position training. Students gave higher scores when assessing the fidelity of VS than experienced teachers.ConclusionThe study highlights the importance of specialized pre-clinical training on ultrasonic scaling for dental students. The methods adopted in current study (VS, TT and QE) each offered unique advantages in education, which can be combined to create an integrative teaching procedure. This procedure aims to provide an effective, advisable and normative pre-clinical training procedure for ultrasonic scaling. By utilizing the strengths of each method, dental educators can deliver high-quality training and ensure that students are well-prepared for clinical practice.

Abstract C070: Management of resectable pancreatic adenocarcinoma: Results from a data-driven approach across University of California system

Abstract Introduction Practice guidelines for resection of surgical candidates in pancreatic adenocarcinoma are consensus-driven to ensure patients receive standardized care, but current evidence regarding peri-operative strategies regarding systemic and chemoradiation treatment is based on retrospective and metanalysis, which may lead to wide variation in implementation. Methods We used a database containing deidentified data patients with pancreatic adenocarcinoma who received surgical resections across five California academic medical centers to assess peri-operative outcomes and treatment strategies. We identified length of post-operative stay, rates of post-surgical hospital readmissions, pre-operative CA19-9 values, rates, type, duration and amount of neo-adjuvant, adjuvant, and chemoradiation therapy using structured data from EMR records at these sites. ANOVA, t-test and fisher exact tests were used to determine statistical significance of differences across institutions. Cox regression models were used to determine significance in survival differences between populations. Results. We identified 2,564 patients with PDAC diagnosis who had a surgical resection of the pancreas across five University of California sites. 1948 received pancreaticoduodenectomy, 549 received distal pancreatectomies, and 67 received total pancreatectomies. Median LOS was 8.0 days, with 7-day, 30-day, and 90-day readmission rates of 7.6, 17.7 and 23.2% respectively. There were significant differences in these rates across the five medical centers, though no association with site volume. Rate of completion of 6 months of peri-operative 5-FU based systemic therapy was 62% across all sites, but only 47% for 12 cycles of FOLFIRINOX. Patients receiving at least some NAC therapy more likely to complete the recommend six months than those who did not get any systemic therapy prior to surgical resection (77.8% vs 49.3%, p-value&amp;lt;0.001, Logistic regression with Wald test for significance). There were significant differences in the timing of peri-operative therapy across the sites, as well as the frequency of using pre- and post-operative chemo-radiation. Pre-operatively CA19-9, as well as use of perioperative Gemcitabine/Abraxane or FOLFIRINOX over Gemcitabine monotherapy were significant predictors of overall survival. Conclusion Post-operative length of stay and readmission rates were significantly different across these institutions, suggesting differential efficacy in supportive care strategies. Similarly, there is significant variation of peri-operative systemic therapy strategies. Patients receiving neoadjuvant systemic therapy are significantly more likely to complete the guideline recommended six months of treatment. Rates of peri-operative chemoradiation were significantly different across medical centers, without corresponding difference in overall survival. By comparing practice differences across institutions, we may better understand how these differences affect efficacy. Citation Format: Travis Zack, Amir Ashraf-Ganjouei, Kurt Giles, Mohammed Adam, Julian Hong, Margaret Tempero, Eric Collisson. Management of resectable pancreatic adenocarcinoma: Results from a data-driven approach across University of California system [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C070.

A stable model for maximizing the number of significant features

AbstractIdentifying significant features (SFs) is important because they are driving factors of a target outcome. However, it is difficult when they have much more features than observations. The problem becomes more challenging when there are multicollinearity and infrequent common features. In such case, standard explainable methods such as OLS and Lasso often fail to identify many SF. To tackle these problems, we propose a stable model to maximize the number of SFs using selective inference called SFLasso-SI. First, in each point in the regularization path, SFLasso-SI conducts selective inference for conservative significance test. Then, it chooses the optimum value of regularization that maximizes the number of SFs. Our extensive experiments across different types of data - text, image, and video show that our SFLasso-SI can find the biggest number of SFs while maintaining similar prediction accuracy as the benchmarking methods.

Using Ant Colony Optimization to Identify Optimal Sample Allocations in Cluster-Randomized Trials

When designing cluster-randomized trials (CRTs), one important consideration is determining the proper sample sizes across levels and treatment conditions to cost-efficiently achieve adequate statistical power. This consideration is usually addressed in an optimal design framework by leveraging the cost structures of sampling and optimizing the sampling ratios across treatment conditions and levels of the hierarchy. Traditionally, optimization is done through the first-order derivative approach by setting the first-order derivatives equal to zero to solve for the optimal design parameters. However, the first-order derivative method is incapable of properly handling the optimization task when statistical power formulas are complex, such as those for CRTs detecting mediation effects under the joint significance test. The current study proposes using an ant colony optimization (ACO) algorithm to identify optimal allocations. We evaluate the algorithm’s performance for CRTs detecting main and mediation effects. The results show that the ACO algorithm can identify optimal sample allocations for CRTs investigating main effects with the same design efficiency as those identified through the first-order derivative method. Furthermore, it can efficiently identify optimal sample allocations for CRTs investigating mediation effects under the joint significance test. We have implemented the proposed methods in the R package odr.

Pengaruh HCE, SCE, CEE, Liquidity, dan Firm Size terhadap Firm Performance

The purpose of this research is to empirically prove the effect of the variable human capital efficiency (HCE), structural capital efficiency (SCE), capital employed efficiency (CEE), liquidity, dan firm size to the variable firm performance, using 84 manufacturing companies listed at the Indonesia Stock Exchange in 2017-2019. Data processing in this research using software program the Eviews version 12.0. The results of the research that have been carried out on the simultaneous test shows that bahwa human capital efficiency, structural capital efficiency, capital employed efficiency, liquidity, dan firm size have a significant simultaneous effect on firm performance, while the partial significance test shows that SCE and liquidity have a significant effect on CAR, but for HCE, CEE, and firm size have no significant effect on firm performance.

An Empirical Study on the Relationship Between Energy Transformation and Economic Growth – Based on Ramsey Model

The study analyzed the interactive relationship between energy transformation and economic growth through the Ramsey model. The energy factor was introduced as an independent factor into the Ramsey model and an application improvement design was carried out. From a micro perspective, the impact of energy and economic factors on net output was analyzed. The research results indicate that the estimated coefficients of fossil energy output elasticity, labor output elasticity, capital output elasticity, and renewable energy output elasticity are 0.740602, 0.708407, 0.454672, and 0.304065, respectively. In addition, the significance tests were all below 0.05, indicating significance. Meanwhile, the elasticity of capital output and labor output complement each other; The output elasticity of fossil fuels and renewable energy are also complementary to each other. In a complementary relationship, the downward trend of one element is often accompanied by the upward trend of another element. This study sorts out the interactive relationship between energy transformation and economic growth, pointing out the direction for the future development of China’s energy economy.

Analisis Dimensi Berpikir Kritikal dalam Program Membaca Ekstensif

This research aims to analyze critical thinking dimensions in an extensive reading program. The research qualitative research approach, with a case study design. The participants consist of students at the university who take part in extensive reading programs. Data were collected through reading reading logs and tests that measured students' critical thinking. The data collected from the critical thinking test was then analyzed statistically, while the log reading data was processed using a qualitative analysis approach. The results showed that there were differences in students' critical thinking test results before and after participating in the extensive reading program. This result was supported by the participants’ reading logs. The extensive reading program implemented by the researchers may not directly create significant changes in terms of average grades, but the results indicate that the program effectively improves students' overall understanding and critical thinking abilities. Therefore, although the results of the significance test are able to provide an idea of whether the changes that occur between the Pre-Test and Post-Test are random or not, the results of the Ho analysis highlight the substantial impact achieved through the treatment that the researcher provided.

Hybrid Quantum Genetic Algorithm with Fuzzy Adaptive Rotation Angle for Efficient Placement of Unmanned Aerial Vehicles in Natural Disaster Areas

A Hybrid Quantum Genetic Algorithm with Fuzzy Adaptive Rotation Angle (HQGAFARA) is introduced in this work to determine the optimal placements for Unmanned Aerial Vehicles (UAVs) aimed at maximizing coverage in disaster-stricken areas. The HQGAFARA is a hybrid quantum fuzzy meta-heuristic that uses the Deutsch–Jozsa quantum circuit to generate quantum populations synergistically working as haploid recombination and mutation operators that take advantage of quantum entanglement, providing exploitative and explorative features to produce new individuals. In place of the conventional lookup table or mathematical equation, we introduced a fuzzy heuristic to adapt the rotation angle employed in quantum gates. The hybrid nature of this algorithm becomes evident through its utilization of both classical and quantum computing components. Experimental evaluations were conducted using two distinct test sets. The first set, termed the “best case”, represents conditions that are the most favorable for determining the UAV positions, while the second set, the “worst-case”, simulates highly challenging conditions for locating the UAV positions, thereby posing a significant test for the proposed algorithm. We carried out statistical comparative analyses, assessing the HQGAFARA against other hybrid quantum algorithms that employ different rotation angles and against the classical genetic algorithm. The experimental results demonstrated that the HQGAFARA performed comparably, if not better, to the classical genetic algorithm regarding precision. Furthermore, quantum algorithms showcased their computational prowess in experiments related to the convergence time.

Appraisal of EnMAP hyperspectral imagery use in LULC mapping when combined with machine learning pixel-based classifiers

The recent availability of satellite hyperspectral imaging combined with the developments in the classification techniques have paved the way towards improving our ability to obtain information on the spatiotemporal distribution of land use/land cover (LULC) at improved accuracy. In this context, the present study aims at evaluating the combined use of the recently launched Environmental Mapping and Analysis Program (EnMAP) hyperspectral satellite mission with two powerful machine learning (ML) classifiers. In particular, the Support Vector Machines (SVM) and Random Forest (RF) are used synergistically with EnMAP imagery in performing LULC mapping at a typical Mediterranean setting located in northern Greece. Evaluation of the derived LULC maps is based on the computation of a series classification accuracy metrics. The McNemar's chi-square statistical significance testing was also computed to confirm the statistical significance of the differences between the classifiers. In overall, results showed that SVM slightly outperformed RF, exhibiting a higher overall accuracy, of 92.6% and 88.1%, respectively, whereas the statistical significance of the findings was also attested by the McNemar's statistical test results. To our knowledge, this study is one of the first published so far focusing on exploring the capabilities of ENMAP imagery when combined with different ML pixel-based classifiers in the context of LULC mapping. Our results, indeed provided useful insights on the potential of EnMAP datasets in deriving information on the spatiotemporal distribution of LULC at a highly fragmented Mediterranean landscape, evidencing the EnMAP promising potential in this field.