SRJ: International Journal of Scientific Research

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Call for Papers – October 2026 Issue | SRJ: IJSR invites original research papers from all disciplines for publication in the upcoming October issue. Submit your manuscript now. • Call for Papers – October 2026 Issue | SRJ: IJSR invites original research papers from all disciplines for publication in the upcoming October issue. Submit your manuscript now. •

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Open Access Article

4565 KB

COMPARATIVE EFFICACY OF AGNUS CASTUS AND LYCOPODIUM CLAVATUM IN THE HOMOEOPATHIC MANAGEMENT OF OLIGOSPERMIA

by Dr. Mandar Kapare, Dr. Abhishek P. Kulkarni, Dr. Vipul R. Shastri and Dr. Pankaj N. Lathiya

SRJ 2026, 1(10), 99; https://doi.org/10.68295/SRJ/NRHG1813 - 26 Oct 2026

Abstract Background: Oligozoospermia is a semen abnormality encountered during the assessment of Male Infertility. Agnus Castus and Lycopodium Clavatum appear in Homoeopathic prescribing literature, but prescribing frequency is distinct from evidence of treatment benefit. Methods: A structured search and source-verification exercise considered scholarly r... [...] Read more.

Open Access Article

4756 KB

FACTORS ASSOCIATED WITH TRUST IN DEEP-LEARNING-BASED THREAT DETECTION FOR ENCRYPTED DARKNET TRAFFIC

by Blessing Thomas Udoh

SRJ 2026, 1(10), 98; https://doi.org/10.68295/SRJ/PTBX5261 - 25 Oct 2026

Abstract Encrypted traffic and anonymity-oriented networks create challenges for cybersecurity monitoring because the content of communications may not be directly inspected. This study examines factors associated with trust in deep-learning-based, real-time threat detection for encrypted darknet traffic, focusing on privacy issues, threat experience, and e... [...] Read more.

Open Access Article

2573 KB

AN INTELLIGENT CONSUMER BEHAVIOUR PREDICTION SYSTEM USING HYBRID MACHINE LEARNING ALGORITHMS

by Ms. Munesh Yadav, Mr. Dilip Kumar and Mr. Praveen Kumar

SRJ 2026, 1(10), 95; https://doi.org/10.68295/SRJ/XPGP2552 - 22 Oct 2026

Abstract Predicting whether a website visitor will make a purchase is one of the most commercially valuable problems in online marketing, yet it is difficult because conversion is rare and visitor behaviour is noisy. This paper presents an intelligent consumer behaviour prediction system that combines unsupervised segmentation with a stacked ensemble of Ran... [...] Read more.

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