Size Dimensions Research Articles

NipalsMCIA: flexible multi-block dimensionality reduction in R via nonlinear iterative partial least squares.

With the increased reliance on multi-omics data for bulk and single-cell analyses, the availability of robust approaches to perform unsupervised learning for clustering, visualization, and feature selection is imperative. We introduce nipalsMCIA, an implementation of multiple co-inertia analysis (MCIA) for joint dimensionality reduction that solves the objective function using an extension to Nonlinear Iterative Partial Least Squares. We applied nipalsMCIA to both bulk and single-cell datasets and observed significant speed-up over other implementations for data with a large sample size and/or feature dimension. nipalsMCIA is available as a Bioconductor package at https://bioconductor.org/packages/release/bioc/html/nipalsMCIA.html, and includes detailed documentation and application vignettes.

Optimisation of gradation based on fractal dimension for large-size graded crushed stone

To improve the mechanical properties of large particle size graded crushed stone mixture and obtain the optimal grading. By using different design methods to obtain the grading of large particle size graded crushed stone, the maximum dry density test, CBR penetration test, static pressure test, and cyclic repeated compaction test were conducted on the large particle size graded crushed stone samples. Finally, fractal theory was introduced to quantitatively calculate the grading of large particle size graded crushed stone, and the fractal dimension of large particle size graded crushed stone was obtained. The relationship between the fractal dimension of large particle size graded crushed stone and density, CBR value, compressive strength, and deformation resistance was analyzed through grey correlation analysis. The experimental results show that large particle size graded crushed stone has better skeleton performance than conventional graded crushed stone; The density, CBR value, compressive strength, and deformation resistance of large-sized graded crushed stone are related to the grading. The skeleton dense grading ratio has stronger mechanical properties compared to the suspended dense grading and skeleton interlocking grading. And the optimal fractal dimension for the optimal configuration should be between 2.59−2.61.

Fractal dynamics model of gas adsorption in porous media

Adsorption temperature, pressure, and pore structure parameters are the key factors affecting gas adsorption in porous media. However, an adsorption dynamics model has not been established that comprehensively couples adsorption temperature, adsorption pressure, and pore structure parameters. In this study, the methane adsorption and pore structure measurements are conducted, and a novel fractal dynamics model of gas adsorption in porous media is proposed. The research results show the proposed model is a function of adsorption temperature (T), adsorption pressure (P), pore size parameters (γmax and γmin), fractal dimension (Df) for pore size, and fractal dimension (DT) for pore tortuosity. The error analysis indicates the predicted adsorption amount from the proposed model matches the measured adsorption amount. The proposed model achieves the determination of the critical point of gas absorption's temperature and pressure effects through a temperature-pressure dynamics analysis. This model provides a methodological basis for clean production based on the adsorption principle and also establishes a significant foundation for the fractal design strategies of novel materials.

Bursty, Irregular Speech Input to Children Predicts Vocabulary Size.

Children learn language by listening to speech from caregivers around them. However, the type and quantity of speech input that children are exposed to change throughout early childhood in ways that are poorly understood due to the small samples (few participants, limited hours of observation) typically available in developmental psychology. Here we used child-centered audio recorders to unobtrusively measure speech input in the home to 292 children (aged 2-7 years), acquiring English in the United States, over 555 distinct days (approximately 8600 total hours of observation, or 29.62 h/child). These large timescales allowed us to compare how different dimensions of child-directed speech input (quantity, burstiness) varied throughout early childhood. We then evaluated the relationship between each dimension of input and children's concurrent receptive vocabulary size. We found that the burstiness of speech input (spikes of words) was a stronger correlate with age than the quantity of speech input. Input burstiness was also a stronger predictor than input quantity for children's vocabulary size: children who heard spiky, more intense bouts of input had larger vocabularies. Overall, these results reaffirm the importance of speech input in the home for children's language development and support exposure-consolidation models of early languagedevelopment.

Peculiarities of head size, total and longitudinal body dimensions in Ukrainian men and women with multiple sclerosis

Annotation. Understanding the anthropometric characteristics of patients with multiple sclerosis is important for identifying potential links between somatotype and the course of the disease. The study of parameters such as head size, total and longitudinal body dimensions is important given the prevalence and severity of multiple sclerosis. This may improve the approach to the diagnosis, treatment and rehabilitation of patients with multiple sclerosis. The aim of the study is to establish the characteristics and gender differences in cephalometric indicators, total and longitudinal body dimensions in young Ukrainian men and women with multiple sclerosis. Cephalometric indicators, total and longitudinal body dimensions were determined in 35 Ukrainian men and 59 young women with multiple sclerosis with mild, moderate and moderately severe disorders. As a control group, similar anthropometric indicators of 82 practically healthy Ukrainian men and 101 young women were taken from the data bank of the National Pirogov Memorial Medical University, Vinnytsya Research Center. Statistical analysis was performed in the licensed statistical package “Statistica 6.0” using non-parametric evaluation methods. In all groups of sick men and women, smaller values of the greatest head width and sagittal arc and larger values of the greatest head length were established compared to practically healthy men or women. In sick men with mild and moderately severe disorders, as well as in sick women of the general group and moderate disorders, larger values of mass and body surface area were established compared to practically healthy men or women. In most groups of sick men and women, higher values of the height of the suprasternal, acromial and finger anthropometric points and lower values of the height of the pubic and acetabular anthropometric points were established compared to practically healthy men or women, which, against the background of the practical absence of body length differences between healthy and sick men or women, indicate a more elongated torso and shorter lower limbs (a manifestation of a “subpathological” constitutional type). Only single reliable or trends in the above body dimensions were established between sick men or women. Pronounced manifestations of sexual dimorphism were established for most cephalometric dimensions, total and longitudinal body dimensions between men with multiple sclerosis (larger values) and women.

Elliptical Fourier analysis of molar outlines in Late Pliocene Parapapio whitei from Makapansgat Limeworks, South Africa

Introduction: Alongside Australopithecus africanus at Makapansgat South Africa, dated to nearly 3 million years before present, are remnants of Parapapio (Cercopithecinae). The extreme variability of this fossil assemblage has stymied efforts to specify the taxon parameters for Parapapio, which are attributed to at least three species. Study aims: The first maxillary molar occlusal outlines of the two most complete fossils attributed to Parapapio whitei are compared. The degree of group cohesion in Parapapio whitei is evaluated using three extant cercopithecoid taxa. Methods and Materials: The fossil crania from Makapangsat Members 3–4, MP 221 and MP 223, both referred to Parapapio whitei, are compared to three extant cercopithecoid taxa including Cercocebus agilis (n=8), Colobus angolensis (n=8) and Papio anubis (n=8). Molar shape is captured using elliptical Fourier analysis of occlusal outlines and molar size dimensions are estimated from measuring software. Results: MP 223 is larger than MP 221 in occlusal area and the minimum buccolingual length of M1 although the variability between the two Parapapio whitei fossils is commensurate with that observed in Papio anubis. MP 221 and MP 223 are more similar to one another in occlusal outline shape than to any other taxon. However, MP 223 falls consistently closer to Papio anubis whereas MP 221 resembles Papio anubis in some respects and Cercocebus agilis in others. Conclusion: MP 221 and MP 223 likely belong to a single species with no clear affinity to any of the extant taxa examined. The differences in molar size characterizing Parapapio whitei, a terrestrial forager, is potentially indicative of male bimaturatism or ecological variability which may also characterize Australopithecus africanus at Makapansgat.

Dental Cast Measurement Variations in Patients with Maxillary Anterior Crowding: A Comparative Study

Background: Dental crowding, a common orthodontic issue, arises due to a mismatch between tooth size and jaw dimensions, significantly affecting dentofacial aesthetics. This study focused on maxillary anterior crowding (M x AC) to investigate its relationship with the tooth size and jaw dimensions. Materials and Methods: This retrospective cross-sectional study included 80 participants divided into two groups: 40 with normal occlusion (control) and 40 with MxAC occlusion. Dental casts were prepared using alginate impressions and dental stones, and measurements were taken for mesiodistal dimensions, arch width, arch depth, overbite, overjet, and arch length discrepancy using a modified sliding caliper gauge. Differences between the two groups were compared using an independent t-test. Statistical significance was set at P < 0.05. Results: Significant differences were observed in tooth dimensions and arch measurements between the M × AC and control groups (P< 0.001). The M × AC group had larger dental crowns (except for the first molar), smaller overjet, and greater arch length discrepancy. The control group exhibited larger arch widths in the first premolar, second premolar, and first molar positions, but not in the canine position (P=0.420). Additionally, the M x AC group had significantly smaller arch depths at the canine, first, and second premolar positions (P< 0.001). However, no significant difference was observed between the groups in dental arch depth at the first molar position (P=0.120). Conclusion: The study found significant differences in tooth dimensions and dental arch measurements between the M × AC and control groups. The M × AC group had larger dental crowns (except for the first molar), less overjet, and greater arch length discrepancy. Arch widths for the premolars and the first molar were larger in the control group, while the M x AC group had smaller arch depths at the canine and premolar positions. These findings underscore the need for customized orthodontic treatment.

Dark Dimension With (Little) Strings Attached

AbstractA relation between dark energy and the scale of new physics in weakly coupled string theory is motivated. This mixing between infrared and ultraviolet physics leads to a unique corner for real‐world phenomenology: barring fine‐tunings, the authors are naturally led to the “dark dimension” scenario, a single mesoscopic extra dimension of micron size with the standard model localized on D‐branes. Our explicit top‐down worldsheet derivation establishes it on a more solid grounding. Allowing some fine‐tuning, such that the vacuum energy only arise at higher orders in string perturbation theory, the “little string theory” scenario with a very weakly coupled string is an alternative possibility. In this case, the string scale lies at the edge of detectability of particle accelerators.

An effective heuristic for developing hybrid feature selection in high dimensional and low sample size datasets.

High-dimensional datasets with low sample sizes (HDLSS) are pivotal in the fields of biology and bioinformatics. One of core objective of HDLSS is to select most informative features and discarding redundant or irrelevant features. This is particularly crucial in bioinformatics, where accurate feature (gene) selection can lead to breakthroughs in drug development and provide insights into disease diagnostics. Despite its importance, identifying optimal features is still a significant challenge in HDLSS. To address this challenge, we propose an effective feature selection method that combines gradual permutation filtering with a heuristic tribrid search strategy, specifically tailored for HDLSS contexts. The proposed method considers inter-feature interactions and leverages feature rankings during the search process. In addition, a new performance metric for the HDLSS that evaluates both the number and quality of selected features is suggested. Through the comparison of the benchmark dataset with existing methods, the proposed method reduced the average number of selected features from 37.8 to 5.5 and improved the performance of the prediction model, based on the selected features, from 0.855 to 0.927. The proposed method effectively selects a small number of important features and achieves high prediction performance.

FLEXIBILITY IN GENE COEXPRESSION AT DEVELOPMENTAL AND EVOLUTIONARY TIMESCALES.

The explosion of next-generation sequencing technologies has allowed researchers to move from studying single genes, to thousands of genes, and thereby to also consider the relationships within gene networks. Like others, we are interested in understanding how developmental and evolutionary forces shape the expression of individual genes, as well as the interactions among genes. To this end, we characterized the effects of genetic background and developmental environment on brain gene coexpression in two parallel, independent evolutionary lineages of Trinidadian guppies ( Poecilia reticulata ). We asked whether connectivity patterns among genes differed based on genetic background and rearing environment, and whether a gene's connectivity predicted its propensity for expression divergence. In pursuing these questions, we confronted the central challenge that standard approaches fail to control the Type I error and/or have low power in the presence of high dimensionality (i.e., large number of genes) and small sample size, as in many gene expression studies. Using our data as a case study, we detail central challenges, discuss sample size guidelines, and provide rigorous statistical approaches for exploring coexpression differences with small sample sizes. Using these approaches, we find evidence that coexpression relationships differ based on both genetic background and rearing environment. We report greater expression divergence in less connected genes and suggest this pattern may arise and be reinforced by selection.

Ultrasound Characteristics of Thyroid Nodules: Differentiating Benign from Malignant Nodules Using Histopathology as the Gold Standard.

Background: Thyroid nodules are a common clinical finding. Accurate differentiation between benign and malignant nodules is crucial for determining appropriate management and treatment. Ultrasound is the primary imaging modality for evaluating thyroid nodules, providing valuable information on characteristics such as echogenicity, size, and vascularity. Despite its widespread use, the diagnostic accuracy of ultrasound in distinguishing benign from malignant nodules varies, necessitating further research to establish reliable ultrasound markers. Therefore, this study aimed to evaluate ultrasound characteristics of thyroid nodules to differentiate benign from malignant nodules using histopathology as the gold standard. Materials and Methods: This retrospective study analyzed 175 thyroid nodules from 155 patients who underwent thyroid ultrasound and subsequent fine-needle aspiration (FNA) or core-needle biopsy (CNB) at King Fahad Hospital, Saudi Arabia, between 2021 and 2024. Ultrasound features, including echogenicity, size, and vascularity, were recorded and analyzed. The Chi-square test was used for categorical variables, and the Mann-Whitney U test was employed for nodule size measurements. Results: Out of 175 nodules, 154 were benign and 21 were malignant. A significant association was found between gender and nodule diagnosis (p=0.05), with overall and malignant thyroid nodules more frequently observed in females than in males. Malignant nodules were more likely to be hypoechoic when compared to surrounding normal thyroid tissue than benign nodules (p=0.002). No significant differences were observed in hyperechoic, isoechoic, mixed echogenicity, or vascularity patterns, nor in nodule size dimensions between benign and malignant thyroid nodules. Conclusion: This study highlights the importance of thyroid nodules echogenicity as a predictor of malignancy in thyroid nodules, while other ultrasound features, such as size and vascularity, did not significantly correlate with malignancy. Further prospective, multi-center research is needed to validate these findings and improve diagnostic accuracy in thyroid nodule management.

Comparative analysis of hidden damage caused by the stem borer Ceutorhynchus species in oilseed rape using computer tomography

Abstract The weevils of the Ceutorhynchus (Coleoptera: Curculionidae) are significant pests, posing a threat to oilseed rape cultivation in Central Europe. Due to their lifestyle, these weevils cause hidden damage within the stems. Our non‐invasive computer tomography‐based study aimed to compare the damage characteristics of three species within this genus: C. pallidactylus (Marsham), C. napi (Gyll.), and C. picitarsis (Gyll.), in oilseed rape stems. During the CT analysis of the plant samples from axial, coronal, and sagittal approaches at different points, we measured the length of the damaging larvae, their number per plant, their distance from each other, the volume of the formed cavity, and the diameter of the damaged plant stems. Additionally, we investigated the closeness of the connections between these forms of damage. Our study found that damage to plant samples during the period of interest was species‐specific. Significant differences were observed in the longitudinal size dimensions of the larvae, the volume of the formed cavities, and the diameters of the stems of the attacked plants among the species causing the damage. The Pearson correlation results confirmed a strong correlation between the volumes of the formed cavities and the values of larval length (l) and stem diameter (⌀), as well as between stem diameter and larval length data for each species (C. pallidactylus: l = 6.903 ± 1.332 mm, ⌀ = 11.43 ± 0.707 mm; C. napi: l = 9.868 ± 0.617 mm, ⌀ = 23.11 ± 2.813 mm; C. picitarsis: l = 3.772 ± 0.967 mm, ⌀ = 11.16 ± 0.365 mm). These results suggest that the damages caused by these hidden lifestyle stem pests of oilseed rape are species‐specific.

How to Combine SHJ Cell-Edge Passivation and Module Reliability?

The use of cut-cells in most of the current modules is now the norm to maximise the final product performances. But the integration of such new cell configurations also comes with new challenges, especially if small cell size dimensions such as shingle are considered. Indeed, specific edge passivation processes are often used to recover for the cut-cell losses. Alumina Oxide or Polymer deposition are the most studied approaches, with in general promising benefits proven at cell level. However, only few communications after module integration are available, in particular about the impact of these additional layers on final module reliability. We show for example that it is crucial to avoid direct deposition of AlOX over the cell metal pattern in the future interconnection area, as TC (Thermal Cycling) resilience of such modules is clearly degraded. Proper edge localization of the AlOX layer is needed to recover the initial reliability behaviour. To preserve the interconnection quality, three different approaches are investigated: (1) edge localisation of the layer by wafer stacking during deposition (2) introduction of adapted copper plating solutions allowing metal growth through the passivation layer (3) edge passivation process directly applied on final strings just before lamination.

Hydrodynamic and reaction kinetic responses of CaO/CaCO3 carbonation in bubbling fluidized bed reactors for thermochemical energy storage: Influence of CO2 mole fraction, grain size, and reactor dimensions

The CaO/CaCO3 thermochemical energy storage system offers a promising method for the efficient utilization of solar energy. However, the reactor design remains underdeveloped. In this study, the Eulerian-Eulerian two-fluid model is employed to systematically investigate the effects of CO2 mole fraction, particle size, and reactor dimensions on the carbonation process in a bubbling fluidized bed reactor. Increasing the CO2 mole fraction from 50 % to 80 % reduces the duration of the chemical-reaction-kinetics controlled stage from 118.5 s to 65.3 s, and the transition stage from 64.6 s to 36.7 s, with minimal impact on the final conversion rate. High CO2 concentrations cause insufficient bed fluidization and uneven local conversion rate distribution within the bed. As the grain size increases from 150 nm to 300 nm and 600 nm, the duration of the chemical-reaction-kinetics controlled stage decreases from 118.5 s to 104.0 s and 76.2 s, respectively. This causes the reaction to enter the transition phase earlier, ultimately leading to a reduction in the maximum conversion rate. Altering the height and width of the reactor does not significantly impact the conversion processes within the reactor. These findings provide valuable insights for the optimization and practical industrial application of efficient reactors.

A local and global feature fusion network for Super-Resolution reconstruction of turbulent flows

The resolution of flow fields represents a significant factor influencing the accuracy of turbulent flow analysis. Nevertheless, the acquisition of high-resolution turbulence data remains a challenge due to the limitations imposed by computing resources. The interpolation method, while capable of achieving high-resolution turbulence at low cost, faces challenges in capturing details of turbulent flows. In this study, a local and global feature fusion network (LGFN) is designed for the reconstruction of high-resolution turbulent flows with high quality. First, dual parallel branches made of dense blocks are introduced into the LGFN to extract local features of turbulent flows. Moreover, the features after the first dense block of each branch are summarized into the self-attention block to obtain global features. The extracted local and global features are aggregated through learnable weight parameters to achieve feature fusion. Finally, the fused turbulence features are scaled to the same dimensional size as the high-resolution turbulence through the implementation of multilayer pixel shuffle layers and convolution layers. The effectiveness of the proposed network was evaluated using datasets of forced isotropic turbulence and channel turbulence. The results demonstrate that the reconstructed velocity fields of the LGFN exhibit the highest degree of similarity to the direct numerical simulation results, in comparison with bicubic interpolation, static convolutional neural network, and super-resolution dense connection network results. In addition, compared to alternative methods, the proposed network effectively captures the characteristics of isotropic or anisotropic turbulence even at larger scales.

Changes in the ideal body shape associated with adolescent rowing-ergometry performance following a 6-week training intervention: New scaling insights using three-dimensional allometry.

Scaling, to remove the effects of body size, is an important methodological approach for enabling an equitable comparison of performance differences between individuals who vary in anthropometric characteristics. Many previous studies using scaling in sport have done so based on only one or two anthropometric characteristics, with only one study to date adopting a three-dimensional approach. To apply a three-dimensional allometric model to rowing ergometer performance (REP) in adolescents, and to detect whether key 'scaling' parameters remain stable when scaling REP both before and after a 6-week training intervention. Novel three-dimensional allometric models were used, incorporating body mass, stature and waist circumference (WC) to detect the most appropriate body size dimension(s) and scaling parameters associated with REP before and after a 6-week training intervention. Using this more flexible and sensitive three-dimensional allometry demonstrated that, following 6-weeks of training, there was a change in the ideal body shape associated with REP. Before training, taller, but not heavier, adolescents performed better. After 6-weeks of training, older participants with a greater body mass but smaller WC performed better. Scaling approaches are important for evaluating performance differences between individuals of differing body size. The findings from the current study (using a novel three-dimensional allometry approach) emphasise that relatively subtle changes in individuals' behavioural characteristics, such as changes in their training/fitness status, can result in quite dramatic changes in the body dimension characteristics and scaling parameters deemed to be key for performance in activities such as REP.

Image-based weight estimation and grading of post-harvested Indian potato (Solanum tuberosum) using dimensional analysis integrated with adaptive neuro fuzzy inference system approach

ABSTRACT The current study builds a model of the link between the image-based weights of Indian Potatoes extracted using the built computer vision system using a dimensional analysis integrated with the adaptive neuro-fuzzy inference system. An atomized sorting system must be developed to enhance the exportation quality. A soft computing method is applied to nonlinear data training. The features include size (dimensions, area, and volumes), shapes, and gravimetric properties were chosen. As per standards and export criteria, potatoes should be divided into three groups (small, medium, and big) based on their estimated weight. A self-build image-based system was designed for capturing an image. The experimental outcomes were contrasted with the presented integrated predicted outcomes. A respectable level of agreement is noted with good competency and dependability by the strong correlation coefficient (0.9975). Hence, the presented approach is strongly recommended for image-based weight estimation and classification. Code: https://colab.research.google.com/drive/1g-B81q8284Hw1QFwAJjqpmDEV35KsNzV

Sex-Specific Left Ventricular and Aorta Size Cut-Off Values for Hemodynamically Significant Chronic Aortic Regurgitation - Implications for Treatment in Asian Populations.

There are no sex-specific guidelines for chronic aortic regurgitation (AR). This retrospective study examined sex-specific differences and propose treatment criteria from an Asian AR cohort.Methods and Results: Consecutive 1,305 patients with moderate-severe AR or greater at 3 tertiary centers in Taiwan and Japan (2008-2022) were identified. Study endpoints were aortic valve surgery (AVS), all-cause death (ACD), and cardiovascular death (CVD). The median follow up was 3.9 years (interquartile range 1.3-7.1 years). Compared with men (n=968), women (n=337) were older, had more advanced symptoms, more comorbidities, larger indexed aorta size (iAortamax) and indexed left ventricular (LV) end-systolic dimension (LVESDi; P<0.001 for all). Symptomatic status was poorly correlated with the degree of LV remodeling in women (P≥0.18). Women received fewer AVS (P≤0.001) and men had better overall 10-year survival (P<0.01). Ten-year post-AVS survival (P=0.9) and the progression of LV remodeling were similar between sexes (P≥0.16). Multivariable determinants of ACD and CVD were age, advanced symptoms, iAortamax, LV ejection fraction (LVEF), LVESDi, LV end-systolic volume index (LVESVi), and Taiwanese ethnicity (all P<0.05), but not female sex (P≥0.05). AVS was associated with better survival (P<0.01). Adjusted LVEF, LVESDi, LVESVi, and iAortamaxcut-off values for ACD were 53%, 24.8 mm/m2, 44 mL/m2, and 25.5 mm/m2, respectively, in women and 52%, 23.4 mm/m2, 52 mL/m2, and 23.2 mm/m2, respectively, in men. Early detection and intervention using sex-specific cut-off values may improve survival in women with AR.

User Behavior and Satisfaction in AI-Generated Video Tools: Insights from Surveys and Online Comments

Abstract. With the rapid advancement of AI, AI-generated video tools have become essential in digital content creation. However, there are significant differences in user acceptance and satisfaction with these tools. This study aims to explore the underlying reasons for these differences by analyzing user behavior, satisfaction levels, and preference characteristics through a questionnaire survey and online review data. Ridge regression analysis identified usage frequency and data security concerns as key factors influencing satisfaction, with familiarity and education level also playing significant roles. Based on these factors, K-means clustering categorized users into three groups: occasional users with high satisfaction, functionality-focused users with the highest satisfaction, and frequent users with lower satisfaction due to data security concerns. Sentiment analysis and LDA topic modeling of online reviews for five AI video tools-Animoto, Invideo, Lumen5, Pictory, and Synthesia-revealed differences in user evaluations. The findings indicate that Lumen5 excels in social media content creation, while Pictory has a weaker user experience with more negative feedback. The study concludes that developers should focus on increasing tool usage frequency and enhancing data security to improve user satisfaction. Moreover, targeted strategies based on different user segments can aid in more precise product optimization and market promotion. This research provides practical guidance for the further development of AI-generated video tools. Future studies could expand the sample size and data dimensions to further validate and deepen these conclusions.

User Behavior and Satisfaction in AI-Generated Video Tools: Insights from Surveys and Online Comments

Abstract. With the rapid advancement of AI, AI-generated video tools have become essential in digital content creation. However, there are significant differences in user acceptance and satisfaction with these tools. This study aims to explore the underlying reasons for these differences by analyzing user behavior, satisfaction levels, and preference characteristics through a questionnaire survey and online review data. Ridge regression analysis identified usage frequency and data security concerns as key factors influencing satisfaction, with familiarity and education level also playing significant roles. Based on these factors, K-means clustering categorized users into three groups: occasional users with high satisfaction, functionality-focused users with the highest satisfaction, and frequent users with lower satisfaction due to data security concerns. Sentiment analysis and LDA topic modeling of online reviews for five AI video tools-Animoto, Invideo, Lumen5, Pictory, and Synthesia-revealed differences in user evaluations. The findings indicate that Lumen5 excels in social media content creation, while Pictory has a weaker user experience with more negative feedback. The study concludes that developers should focus on increasing tool usage frequency and enhancing data security to improve user satisfaction. Moreover, targeted strategies based on different user segments can aid in more precise product optimization and market promotion. This research provides practical guidance for the further development of AI-generated video tools. Future studies could expand the sample size and data dimensions to further validate and deepen these conclusions.