The April 2026 edition of IJSECS arrives at a productive tension — between technical precision and social accountability. Thirty-five articles span a range that few journals manage without losing coherence: from dual-band microstrip antenna design for 2.4 GHz and 5.3 GHz WiFi networks to driver drowsiness detection via facial landmark modeling, each contribution anchored in a specific, testable problem rather than abstract ambition. Methodologically, several pieces stand out. SettingsAutoClusterAPI proposes a lightweight backend architecture for automated unsupervised clustering pipelines — a quiet but genuinely useful contribution to backend engineering. The comparative study of Naïve Bayes, LSTM, and BiLSTM on EasyCash sentiment reviews offers an honest account of performance trade-offs that similar literature tends to gloss over. On the security front, the ensemble learning approach to SQLi and XSS detection using character-level N-Gram features, paired with a layered JWT authentication model in Golang Echo, signals that old vulnerabilities still demand architecturally serious responses. What gives this volume its character, though, is its willingness to treat so-called peripheral concerns as central ones — gender bias in AI-driven recruitment systems, crypto scam prevention through digital literacy, personal data security awareness among social media users, all examined through structured systematic reviews. The edition rounds out with decision support systems, mixed reality learning tools, ETL pipeline design, and a candid evaluation of vibe coding as an AI-orchestrated development methodology. Taken together, this is a research community that has moved past building systems for their own sake — and started asking, with some urgency, who those systems are actually built for.