MATRIX Academic International Online Journal Of Engineering And Technology

Sales Trends and Operational Efficiency in Indian Online Fashion Retail: Evidence from Multi-Platform Transaction Data

2026-06-27T13:05:24+00:00

This study analyses sales trends and operational efficiency in
the Indian online fashion retail sector using multi-platform transaction
data spanning domestic Amazon orders, international shipments, and
platform-level pricing and prot-and-loss records.We rst derive baseline
operating metricstotal revenue, average order value, order-cancellation
rate, and gross marginand quantify category-level revenue concentra-
tion. International monthly revenue is modelled with a second-degree
polynomial regression to capture its non-linear seasonal trajectory. We
then construct a deterministic ve-year forecast (20222027) that cou-
ples a domestic compound annual growth rate, an international growth
rate, a declining cancellation rate, gradual margin erosion from platform
commissions, and operating-expenditure eciency gains attributable to
cloud-warehouse automation. The model projects combined annual rev-
enue rising from approximately INR 490Mto INR 1,287 M, with earnings
before interest and taxes (EBIT) increasing from roughly INR 123 M to
INR 379 M over the horizon. The results indicate that domestic expan-
sion and improving fullment reliability, rather than international growth
alone, are the principal drivers of protability, and that warehouse-cost
optimisation materially widens operating margins in later years.

A Machine Learning Framework for Gen-Z College Admission Prediction with a Five-Year Forecast

2026-06-27T13:45:49+00:00

College admission decisions increasingly draw on diverse aca-
demic, extracurricular, and digital-engagement signals, making them a
natural target for data-driven prediction. This study develops a super-
vised machine-learning framework to predict the admission status of
Generation-Z applicants from a large tabular dataset and to forecast
admission-rate trends through 2030. Sixteen raw applicant attributes are
augmented with four engineered composite indicesacademic, extracur-
ricular, digital-readiness, and holisticand three classiers (Random
Forest, Gradient Boosting, and Logistic Regression) are trained and com-
pared using accuracy, the area under the receiver-operating-characteristic
curve (ROC-AUC), and ve-fold cross-validated AUC. On an illustra-
tive run the three models achieve comparable discrimination (AUC ≈
0.760.77), with academic composite, GPA, and standardised-test scores
emerging as the dominant predictors of admission. A quadratic trend
model projects overall, STEM-track, and AI-assisted-screening admis-
sion rates upward over the 20262030 horizon, saturating against an
upper bound. The framework oers an interpretable, reproducible basis
for admission analytics and capacity planning.

Click, Trust, Lose: An Analysis of Social Engineering Vulnerabilities in Uzbekistan

2026-06-27T12:56:16+00:00

Social engineeringthe psychological manipulation of peo-
ple into actions that compromise their own securityhas become a dom-
inant cyber-threat in rapidly digitalising economies. This paper analyses
the forms social engineering has taken in Uzbekistan, drawing on docu-
mented incidents and direct observation. Four recurring attack patterns
are identied and organised into a taxonomy: the self-propagating Tro-
jan le (and its newer bot mini-app variant), fake-prize phishing that
clones domestic payment brands, a patient trust-building long-con, and
the fraudulent security call. We show that these patterns separate into
two groups: attacks that depend on intercepting a one-time SMS code,
which have been substantially blunted by the introduction of mandatory
OneID transaction verication, and attacks that exploit curiosity and
emotional investment, which no single regulatory measure can patch. A
light conceptual model formalises the exponential, self-replicating spread
of the Trojan pattern. We argue that Uzbekistan's elevated exposure re-
ects the timing of its digital transitionconvenience arriving ahead of
protective infrastructure and user literacyrather than any unique defficiency, and we outline a layered set of technical and educational coun-
termeasures.

Technology for Developing Intellectual Abilities of Older Preschool Children in Preschool Educational Organizations

2026-06-27T12:56:39+00:00

The senior preschool period (roughly ages ve to seven) is de-
cisive for the formation of intellectual abilities, yet practice in preschool
educational organizations often lacks a systematic, technology-based ap-
proach to developing them. This paper proposes a pedagogical technology
a structured, reproducible system of goals, content, methods, and assessment
for developing the intellectual abilities of older preschool children. The
technology integrates ve developmental components (thinking, atten-
tion, memory, imagination, and speech) and organises the educational
process into four interconnected blocks: target-diagnostic, content, procedural-
technological, and result-evaluative. Its procedural core combines devel-
opmental play, theory-of-inventive-problem-solving (TRIZ) tasks, visual
modelling, problem situations, project activity, and interactive digital
and augmented-reality tools. An integrated index of intellectual devel-
opment is dened to classify children into low, medium, and high levels
and to measure progress. An illustrative formative experiment indicates
that, under the proposed technology, the proportion of children at the
high level rises substantially relative to a control group, while the share
at the low level falls. The work oers preschool educators a coherent,
measurable framework that aligns activity-based pedagogy with modern
educational technology.