Differential Power Research Articles

Development of A Higher-Order Thinking Skills (HOTS) Instrument to Measure Student's Critical Thinking Abilities in Class V Elementary School

This research and development aims to produce a feasible and practical Higher Order Thinking Skills (HOTS) instrument to measure students’ critical thinking skills in grade V elementary school mathematics subjects. This research method is development research that refers to the design of Borg & Gall. The research was conduct in class V SDN 3 Sumberejo. Feasibility testing of instruments developed in this study uses expert tests, validity tests, reliability tests, differentiation power tests and difficulty tests. The results of this study showed that an eight-question instrument was obtained, which is suitable for use. The practicality of the instrument, based on the response of educators and learners as practitioners, yielded a very practical assessment. This demonstrates that the developed HOTS instrument is feasible and practical for measuring the critical thinking ability of fifth-grade elementary school students.

A 77 GHz Power Amplifier with 19.1 dBm Peak Output Power in 130 nm SiGe Process.

This article reports a two-stage differential structure power amplifier based on a 130 nm SiGe process operating at 77 GHz. By introducing a tunable capacitor for amplitude and phase balance at the center tap of the secondary coil of the traditional Marchand balun, the balun achieves amplitude imbalance less than 0.5 dB and phase imbalance less than 1 degree within the operating frequency range of 70-85 GHz, which enables the power amplifier to exhibit comparable output power over a wide operating frequency band. The power amplifier, based on a designed 3-bit digital analog convertor (DAC)-controlled base bias current source, exhibits small signal gain fluctuation of less than 5 dB and saturation output power fluctuation of less than 2 dB near the 80 GHz frequency point when the ambient temperature varies in the range of -40 °C to 125 °C. Benefiting from the aforementioned design, the tested single-path differential power amplifier exhibits a small signal gain exceeding 16 dB, a saturation output power exceeding 18 dBm, and a peak saturation output power of 19.1 dBm in the frequency band of 70-85 GHz.

The Effect of Character and Local Wisdom-Integrated Causalitic Model Learning on Problem-Solving Skills and the Development of Environmental Conservation Literacy

The study aims to examine the effect of a causalitic learning model that integrates character and local wisdom on problem solving ability (PSA) physics and environmental conservation literacy (ECL) development of students. The type of research used was quasi-experimental with an untreated control group design with pretest-and posttest. The population is all class X students of SMAN 1 Terara, totaling 206 people. The research sample was taken using purposive sampling technique so that 31 students from X MIPA 6 class were selected as the experimental group and 31 students from X MIPA 3 class as the control group. The experimental group was treated in the form of a causalitic learning model integrated with character and local wisdom, while the control group was treated in the form of a conventional learning model. The PSA instrument consists of tests in the form of descriptive questions taking into account validity, reliability, level of difficulty of the questions, as well as the differential power of the questions and ECL development tests in the form of questionnaires. The average PSA value obtained in the experimental group was 79,87 and in the control group was 72,39. The average score for the development of ECL in the experimental group was 80,00 and that of the control group was 42,58. The data of both classes are homogeneous and normally distributed. Data on PSA and development of ECL were analyzed using t-test polled variance with a significant level of 5%. The results of the PSA analysis were obtained at 4,32 and the results of the ECL development analysis were obtained at 10,94. Thus, it can be concluded that there is an influence of the integrated causalitic learning model of character and local wisdom on PSA and the development of ECL.

Fallen Sanctuary: A Higher-Order and Leakage-Resilient Rekeying Scheme

This paper presents a provably secure, higher-order, and leakage-resilient (LR) rekeying scheme named LR Rekeying with Random oracle Repetition (LR4), along with a quantitative security evaluation methodology. Many existing LR primitives are based on a concept of leveled implementation, which still essentially require a leak-free sanctuary (i.e., differential power analysis (DPA)-resistant component(s)) for some parts. In addition, although several LR pseudorandom functions (PRFs) based on only bounded DPA-resistant components have been developed, their validity and effectiveness for rekeying usage still need to be determined. In contrast, LR4 is formally proven under a leakage model that captures the practical goal of side-channel attack (SCA) protection (e.g., masking with a practical order) and assumes no unbounded DPA-resistant sanctuary. This proof suggests that LR4 resists exponential invocations (up to the birthday bound of key size) without using any unbounded leak-free component, which is the first of its kind. Moreover, we present a quantitative SCA success rate evaluation methodology for LR4 that combines the bounded leakage models for LR cryptography and a state-of-the-art information-theoretical SCA evaluation method. We validate its soundness and effectiveness as a DPA countermeasure through a numerical evaluation; that is, the number of secure calls of a symmetric primitive increases exponentially by increasing a security parameter under practical conditions.

Differentiation of frontotemporal dementia subtypes using neuroimaging‐based multi‐type parallel feature embedding

AbstractBackgroundFrontotemporal dementia (FTD) represents a collection of neurocognitive syndromes with frontotemporal lobar degeneration (FTLD) neuropathology, and is associated with significant clinical, pathological, and genetic heterogeneity. We trained a deep neural network (DNN) classifier to differentiate behavioral‐variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA), and non‐fluent variant (nfvPPA) patients using MRI scans drawn from two multi‐site neuroimaging consortiums.MethodBvFTD (N = 173), nfvPPA (N = 63), and svPPA (N = 41) patients with T1‐MRI were extracted from the FTLD Neuroimaging Initiative (FTLDNI) and the ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) databases. MRI data were preprocessed with FreeSurfer, with cortical thickness, cortical volume, and subcortical volumes extracted. Cortical measures were parcellated into 360 patches (i.e., ROIs) according to the HCP‐MMP1 atlas. Both the patch‐based cortical thickness and volume features were harmonized to control confounding effects of sex, age, total intracranial volume (TIV), cohort, and scanner. Multi‐type features were parallelly fed into a multi‐layer‐perceptron (MLP)‐based classifier. Weighted cross‐entropy loss function was used to account for unbalanced sample sizes across FTD subtypes. 10‐fold nested cross‐validation was used to evaluate the robustness of the classification model, with data split into 80/10/10 of training/validation/test data sets.ResultVisual evaluation z‐scores of cortical features among FTLDNI and ALLFTD groups revealed site‐specific differences significantly reduced by feature harmonization, especially for volume (Figure 1). The balanced accuracy of the ensembled DNN classifier of each FTD subtype on test sets across all ten folds reached 0.76 ± 0.09 for bvFTD, 0.79 ± 0.07 for nfvPPA, and 0.88 ± 0.07 for svPPA (Figure 2). Figure 3 shows confusion matrices for classification performance in the test set across ten cross‐validation folds.ConclusionWe developed a deep‐learning‐based framework to classify three FTD subtypes: bvFTD, nfvPPA, and svPPA. The combination of feature harmonization and parallel multi‐type feature embedding framework showed promising differentiation power. This work can be used to recognize at‐risk populations for early and precise diagnosis, to aid intervention planning. Future studies will compare classification based on different input features and use visualization methods to identify the most discriminative regions and explore their clinical relevance.

Cross-subject emotion EEG signal recognition based on source microstate analysis

Electroencephalogram (EEG) signals are very weak and have low spatial resolution, which has led to less satisfactory accuracy in cross-subject EEG-based emotion classification studies. Microstate analyses of EEG sources can be performed to determine the important spatiotemporal characteristics of EEG signals. Such analyses can be used to cluster rapidly changing EEG signals into multiple brain prototype topographies, fully utilizing the spatial information contained in the EEG signals and providing a neural representation for emotional dynamics. To better utilize the spatial information of brain signals, source localization analysis on the EEG signals was first conducted. Then, a microstate analysis on the source-reconstructed EEG signals is conducted to extract the microstate features of the data. We conducted source microstate analysis on the participant data from the odor-video physiological signal database (OVPD-II) dataset. The experimental results show that the source microstate feature topologies of different participants under the same emotion exhibited a high degree of correlation, which was proven by the analysis of microstate feature topographic maps and the comparison of two-dimensional feature visualization maps of the differential entropy (DE) and power spectral density (PSD). The microstate features represent more abstract emotional information and are more robust. The extracted microstate features were then used with the style transfer mapping method to transfer the feature data from the source domain to the target domain and were then used in support vector machines (SVMs) and convolutional neural networks (CNNs) for emotion recognition. The experimental results show that the cross-subject classification accuracies of the microstate features in SVMs were 84.90 ± 8.24% and 87.43 ± 7.54%, which were 7.19 and 6.95% higher than those obtained with the PSD and 0.51 and 1.79% higher than those obtained with the DE features. In CNN, the average cross-subject classification accuracies of the microstate features were 86.44 and 91.49%, which were 7.71 and 19.41% higher than those obtained with the PSD and 2.7 and 11.76% higher than those obtained with the DE features.

Further research results on confusion coefficient of Boolean functions

Abstract The notion of confusion coefficient (CC) is a property that attempts to characterize the confusion property of cryptographic algorithms against differential power analysis. In this article, we establish a relationship between CC and the transparency order (TO) for any Boolean function and deduce some relationships between the sum-of-squares of CC, signal-to-noise ratio, and TO. We also give a tight upper bound and a tight lower bound on the sum-of-squares of CC for balanced s-plateaued functions. Finally, the results generalized a lower bound on the sum-of-squares of CC of Boolean functions with the Hamming weight k.

A Modular Differential Power Processing Converter Design with Simplified Voltage Equalization for Photovoltaic Systems

Partial shading in series-connected photovoltaic (PV) systems poses a significant challenge as it considerably restricts the system’s output power and has a notable impact on the overall efficiency. Differential power processing (DPP) has emerged as a widely employed solution to mitigate this effect. However, implementing DPP architectures introduces challenges such as system cost, reliability, control implementation, and modularity. This research proposes a simplified voltage equalization (VE) algorithm, executed on a low-cost and modular DPP architecture using bi-directional flyback converters. Notably, under light and moderate partial shading conditions, the PV system’s output power exhibits a significant increase compared to the traditional string configuration with bypass diodes. To further optimize the system performance, a methodology adapted to the VE algorithm is suggested, minimizing the processed power while increasing overall efficiency. The proposed solutions have undergone rigorous testing through simulations and experiments. The results validate that, under moderate shading conditions, the system efficiency reaches approximately 90%.

A table tennis serve versus rally hit elicits differential hemispheric electrocortical power fluctuations.

Human visuomotor control requires coordinated interhemispheric interactions to exploit the brain's functional lateralization. In right-handed individuals, the left hemisphere (right arm) is better for dynamic control and the right hemisphere (left arm) is better for impedance control. Table tennis is a game that requires precise movements of the paddle, whole body coordination, and cognitive engagement, providing an ecologically valid way to study visuomotor integration. The sport has many different types of strokes (e.g., serve, return, and rally shots), which should provide unique cortical dynamics given differences in the sensorimotor demands. The goal of this study was to determine the hemispheric specialization of table tennis serving - a sequential, self-paced, bimanual maneuver. We used time-frequency analysis, event-related potentials, and functional connectivity measures of source-localized electrocortical clusters and compared serves with other types of shots, which varied in the types of movement required, attentional focus, and other task demands. We found greater alpha (8-12 Hz) and beta (13-30 Hz) power in the right sensorimotor cortex than in the left sensorimotor cortex, and we found a greater magnitude of spectral power fluctuations in the right sensorimotor cortex for serve hits than return or rally hits, in all right-handed participants. Surprisingly, we did not find a difference in interhemispheric functional connectivity between a table tennis serve and return or rally hits, even though a serve could arguably be a more complex maneuver. Studying real-world brain dynamics of table tennis provides insight into bilateral sensorimotor integration.NEW & NOTEWORTHY We found different spectral power fluctuations in the left and right sensorimotor cortices during table tennis serves, returns, and rallies. Our findings contribute to the basic science understanding of hemispheric specialization in a real-world context.

Abstract 14892: Sex Difference in the Prognostic Power of Growth Differentiation Factor 15 for Cardiovascular Event: The Japan Morning Surge-Home Blood Pressure Study

Introduction: Growth differentiation factor 15 (GDF-15), a cytokine secreted in response to cellular stress and inflammation, has been associated with cardiovascular event. Although previous studies have reported that there was a close association between sex hormones and GDF-15, data are sparse about sex difference in the prognostic power of GDF-15 for cardiovascular event. Hypothesis: We hypothesized that there is the differential prognostic power of GDF-15 for cardiovascular outcome according to gender. Methods: This prospective practitioner-based cohort study was conducted between 2005 and 2012 and included participants in the Japan Morning Surge-Home Blood Pressure Study with a history of at least one cardiovascular event who had GDF-15 measurements at baseline. Results: The study included 4066 participants (mean age 64.8 years; men, n=1897; women, n=2169). During an average 6.2 years follow-up, 249 cardiovascular events (coronary artery disease, stroke and heart failure) occurred. GDF-15 levels were significantly higher in the male vs. the female group (median [interquartile], 1014 [741.3-1432] ng/L vs. 909.9 [671.6-1257] ng/L; P<0.001). In women, multivariate Cox analysis revealed that after adjusting other potential predictors, log-transformed GDF-15 was independently associated with cardiovascular events (Hazard ratio [HR], 2.09; 95% confidence interval [CI], 1.31-3.35; P=0.002), whereas this association was not found in men. In women, higher GDF-15 (≥1200 ng/L) was independently associated with cardiovascular event (HR, 2.23; 95%CI, 1.41-3.53; P=0.001), whereas this association was not found in men. The interaction between higher GDF-15 and cardiovascular event according to sex tended to be significant (P=0.087). Conclusions: There is a sex difference in the prognostic power of GDF-15 for cardiovascular event.

Ecological vulnerability of China's Yellow River Basin: evaluation and socioeconomic driving factors.

The Yellow River Basin (YRB) is a typical ecologically fragile area in both the Chinese and global contexts. This paper built a sensitivity-resilience-pressure model to evaluate the ecological vulnerability (EV) of the YRB at the grid and prefecture-level regional scales; explored the spatiotemporal characteristics of EV; and scrutinized the impacts of socioeconomic driving factors on EV. The results showed that (1) at the grid and prefecture-level regional scales, EV decreased from the upper to lower reaches, and high vulnerability was observed in the provincial capital city. Mild and severe vulnerability constituted the main EV types in the YRB. (2) The EV index of the YRB decreased from 2.71 to 2.56 in the study period, indicating that the ecological environment improved in the YRB. The slightly and lightly vulnerable areas experienced shrinking-expansion changes, and the overall areas of these two EV types showed expanding trends, while the areal changes and overall trends of the moderately, severely, and extremely vulnerable areas were contrary to those of the slightly and lightly vulnerable areas. (3) The impacts of socioeconomic driving factors on EV dynamically strengthened with the improvement of the socioeconomic level. After considering the interactions of all socioeconomic factors, the explanatory power of the spatial differentiation of EV was enhanced, and the influence of these factors became more prominent.

Ultrafine comminution-assisted ultrasonic-microwave synergistic extraction of Pueraria mirifica (Kudzu flower and root) flavonoids

Extracts of the Pueraria mirifica (Kudzu) plant have several significant human health-promoting benefits. This study utilized orthogonal tests to evaluate the effects of differential ultrasonic power, microwave, and time on the rate of flavonoid extraction from Kudzu samples. Ultrafine processing resulted in finer powder microstructures (SEM) with high solubility. The smallest D50 measurements of ultrafine Kudzu flower and root particles were 11.7 ± 0.004b and 14.3 ± 0.013c μm, respectively. Increasing ultrasonic power from 200 to 600 W yielded increased flavonoids. Increased microwave power from 200 to 800 W also yielded increased flavonoid extract. We found that the best combination factor was A3B2C3 (A-ultrasonic power, B- time, and C- microwave power), showing that flavonoid extraction rate was primarily influenced by microwave power, followed by ultrasonic time and ultrasonic power. Conclusively, ultrafine pulverization increased the flavonoid extraction rate from Kudzu powder particles. Also, scanning electron microscopy results showed that the finer particles had increased solubility.

High-precision laser beam lateral displacement measurement based on differential wavefront sensing.

Accurately lateral displacement measurement is essential for a vast of non-contact sensing technologies. Here, we introduce a high-precision lateral displacement measurement method based on differential wavefront sensing (DWS). Compared to the conventional differential power sensing (DPS) method, the DWS method based on phase readout has the potential to achieve a higher resolution. The beam lateral displacement can be obtained by the curvature distribution of the wavefront on the surface of the detector. According to the theoretical model of the DWS method, the sensitivity of the lateral displacement can be greatly improved by increasing the wavefront curvature of the measured laser beam by means of lenses. An optical system for measuring the lateral displacement of the laser beam is built and calibrated by a high-precision hexapod. The experimental results show that the DWS-based lateral displacement measurement achieves a resolution of 40 pm/Hz1/2 (at 1-10 Hz) with a linear range of about 40 µm, which is consistent with the theoretical model. This technique can be applied to high-precision multi-degree-of-freedom interferometers.

Variation in the Ecological Carrying Capacity and Its Driving Factors of the Five Lake Basins in Central Yunnan Plateau, China

The Five Lakes Basin of Central Yunnan Plateau (FLBOCYP) is located in the core area of Yunnan Province and has a developed economy, but the ecological and environmental problems in the basin are serious and the sustainable economic development is threatened. The analysis of ecological carrying capacity change and the study of influencing factors in the basin is conducive to protecting the ecology of the basin and maintaining the sustainable development of the social economy. Ecological carrying capacity is an important indicator for the quantitative assessment of regional sustainable development, and the assessment of regional ecological carrying capacity based on grid scale can more accurately and vividly reflect the regional sustainable status and provide reference for regional coordinated development. With the support of GIS technology, based on the unique ecosystem characteristics of the river basin itself, the research method of quantifying the ecological carrying capacity from the three perspectives of ecological function elasticity, resource and environmental capacity and socio-economic coordination was carried out, and a relatively complete comprehensive evaluation index system of ecological carrying capacity was constructed. The ecological carrying capacity of the five major lake basins of Qilu Lake and Yangzonghai from 2000 to 2018 was evaluated, and the temporal and spatial changes and driving mechanisms of ecological carrying capacity were analyzed. The results show that: (1) The FLBOCYP has an overall moderate ecological carrying capacity (average of ~0.5). The temporal trend in ecological carrying capacity was an initial rise followed by a fall, but there was an overall increasing trend at a rate of 0.019. (2) Areas with a strong ecological carrying capacity were mainly distributed in the mountainous and semi-mountainous regions outside of the lake area, whereas areas of weaker ecological carrying capacity were mainly distributed in the plain area around the lake. The ecological carrying capacity gradually increased from the area around the lake to the periphery. (3) At a basin scale, the ecological carrying capacities of the Dian, Fuxian, and Yangzong lake basins were relatively high, whereas those of the Xingyun and Qilu lake basins were relatively low. The greatest increase in ecological carrying capacity of Fuxian Lake has occurred since 2000. (4) The spatial pattern of ecological carrying capacity showed clear agglomeration. This agglomeration has been continuously enhanced but remained relatively stable over the past 19 years. The main agglomeration modes were identified as “high-high” (HH), “low-low” (LL), and “not obvious agglomeration”. (5) Among the many driving factors, ecological elasticity, biological abundance index, proportion of forest land, and degree of human disturbance showed the greatest explanatory power for spatial differentiation of ecological carrying capacity, and the interaction of any two factors affected the spatial analysis of ecological carrying capacity even more. In summary, the overall ecological environment of the FLBOCYP has experienced significant improvement since 2000, whereas that of the plain area has deteriorated more seriously in recent years.

Research on acoustic fault diagnosis of bearings based on spatial filtering and time-frequency domain filtering

In conventional methods, vibration-based diagnosis (VBD) is commonly used for identifying rolling bearing faults. In contrast, acoustical-based fault diagnosis (ABD) has been extensively studied as an alternative due to its non-contact measurement capabilities, which are superior to VBD. Nonetheless, the accuracy of machine diagnosis may be compromised by multisource aliasing in the recorded acoustic signals. This research integrates spatial domain filtering and time-frequency domain filtering to address the issue of bearing fault diagnosis. By utilizing the second-order cone optimization method, differential power response beamformers have been established to attain a high signal-to-noise ratio of bearing sound while effectively controlling the noise power level. The output of differential beamformers is analyzed using the parametric adaptive MOMEDA approach. The method presented in this paper enables bearing acoustic fault diagnosis and identification of the faulty bearing location. The validity of the proposed ABD method has been demonstrated through experimental and simulation results.

Development of KASP fingerprinting panel for clonal identification in red raspberry (Rubus idaeus L.)

AbstractRed raspberry is an economically important horticultural crop that is known for its fruit's sweet flavour and nutritional value. A reliable and economic genotyping platform is needed to facilitate clonal/variety identification. Previous attempts for clonal identification utilized morphological traits or low‐throughput, difficult to score dinucleotide‐containing simple sequence repeat molecular markers. Single nucleotide polymorphisms (SNPs), despite having lower allelic diversity, are numerous across the genome and more easily converted to high‐throughput assays restoring differential power. In this study, we use the kompetitive allele‐specific PCR (KASP™) chemistry, an affordable and high‐throughput platform, to develop a panel of SNPs to distinguish a diverse collection of red raspberry accessions for clonal identification. The panel consists of 48 KASP assays that show high concordance with whole genome sequencing, allelic balance, and recovery rate and a minimal set of 24 assays that distinguished the same accessions differentiated by the larger panel.

Spatial distribution analysis and driving factors of traditional villages in Henan province: a comprehensive approach via geospatial techniques and statistical models

Traditional villages are repositories for preserving human artifacts and cultural heritage. An investigation of the spatial distribution characteristics and factors influencing traditional villages in provincial administrative regions can provide new insights regarding the protection of traditional villages and rural development. This study focused on 275 traditional villages in Henan Province. Using ArcGIS and GeoDa software, we analysed the spatial autocorrelation and heterogeneity of the nearest neighbour index, Gini coefficient, Moran’s I, and kernel density of the villages. Additionally, in conjunction with the Python sklearn library and GeoDetector, 15 indicators were selected to construct a decision tree model, spatial lag regression model, and geographic detector. Then the influence and interaction mechanisms of each indicator were analysed. The results revealed that (1) the spatial distribution of traditional villages in Henan Province was clustered and uneven, with a spatial layout comprising “3 high-density areas + 1 medium-density belt”; (2) overall, the number of traditional villages was negatively correlated with altitude, slope, rainfall, population density, proportion of the minority population, and historical-cultural intensity; and (3) the decision tree model results demonstrated that the selected 15 indicators had good predictive ability and that population density was particularly important. The spatial lag regression model results showed that the spatial distribution of traditional villages was positively correlated with distance from rivers, urbanization rate, and tourism resources, and negatively correlated with population density, per capita GRP, historical-cultural intensity, and NDVI. (4) The GeoDetector results indicated that historical-cultural intensity and population density were the two factors with the most significant explanatory power for the spatial differentiation of traditional villages in Henan Province. In terms of interactive factors, population density cap population was the strongest interactive driving force, followed by population cap historical-cultural intensity.

Assessing treatment outcomes of chemoimmunotherapy in extensive-stage small cell lung cancer: an integrated clinical and radiomics approach

BackgroundSmall cell lung cancer (SCLC) is a highly malignant cancer characterized by metastasis and an extremely poor prognosis. Although combined chemoimmunotherapy improves the prognosis of extensive-stage (ES)-SCLC, the survival benefits...

Pincering SKINNY by Exploiting Slow Diffusion

Lightweight cryptography is an emerging field where designers are testing the limits of symmetric cryptography. We investigate the resistance against sidechannel attacks of a new class of lighter blockciphers, which use a classic substitution–permutation network with slow diffusion and many rounds.Among these ciphers, we focus on SKINNY, a primitive used up to the final round ofNIST’s recent lightweight standardisation effort. We show that the lack of diffusion in the key scheduler allows an attacker to combine leakage from the first and the last rounds, effectively pincering its target. Furthermore, the slow diffusion used by its partial key-absorption and linear layers enable, on both sides, to target S-Boxes from several rounds deep.As some of these S-boxes leak on the same part of the key, full key recovery exploiting all leakage requires a clever combining strategy. We introduce the use of cluster graph inference (an established tool from probabilistic graphical model theory) to enhance both unprofiled or profiled differential power analysis, enabling us to handlethe increase of S-Boxes with their intertwined leakage.We evaluate the strength of our attack both in the Hamming weight model and against two implementations running on an STM32F303 ARM Cortex-M4 hosted on a ChipWhisperer target board, showing that our attack reduces the number of traces required to attack SKINNY by a factor of around 2.75.

Project-Based Learning (PjBL) Model in E-Module as an Improvement of Critical Thinking in the Department of Cosmetology And Beauty

The goal of this research is to enhance learning and critical thinking abilities of Cosmetology and Beauty students in e-commerce courses through the implementation of interactive e-commerce e modules. This study uses a quasi-experimental approach with control groups for the pretest and posttest. Data collection was carried out using instruments in the form of open questionnaires and tests. The study's data analysis method is quantitative descriptive analysis, differentiation power analysis using T Test and qualitative descriptive analysis. The independent sample t test findings describe a Sig (2 Tailed) greater in the experimental class compared to the control class, it can be inferred that there is a substantial difference between the two groups. The overall findings support the usage of the e-module in e-commerce courses because it has been shown to enhance critical thinking abilities and learning outcomes.