RSS feed source: USGS Earthquake Hazards Program
Time2025-06-04 02:39:41 UTC2025-06-04 02:39:41 UTC at epicenterLocation29.623°N 140.706°EDepth126.20 km (78.42 mi)
Click this link to continue reading the article on the source website.
Author: WeWorldMedia-admin
RSS feed source: USGS Earthquake Hazards Program
Date and TimeMag
DepthDistanceLocationDetailsMap May 4, 05:44 pm (GMT +9)
4.5
79 km65 km (40 mi) to the SEIzu Islands, Japan Region InfoMar 31, 09:09 pm (GMT +9)
4.4
10 km96 km (59 mi) to the E Izu Islands, Japan Region InfoNov 26, 2024 12:37 am (GMT +9)
5.0
94 km41 km (25 mi) to the S Philippine Sea, 282 km northwest of Chichijima Island, Japan InfoNov 25, 2024 04:51 pm (GMT +9)
4.1
102 km85 km (53 mi) to the SBonin Islands, Japan Region InfoSep 14, 2024 07:11 am (GMT +9)
4.1
93 km33 km (21 mi) to the NIzu Islands, Japan Region InfoJun 11, 2024 07:09 am (GMT +9)
4.8
181 km46 km (29 mi) to the W Izu Islands, Japan Region InfoJan 14, 2024 12:10 am (GMT +9)
4.9
71 km81 km (50 mi) to the E Izu Islands, Japan Region InfoNov 2, 2023 01:53 am (GMT +9)
4.7
103 km49 km (31 mi) to the S Izu Islands, Japan Region InfoOct 30, 2023 12:06 am (GMT +9)
4.7
111 km50 km (31 mi) to the S Izu Islands, Japan Region InfoOct 6, 2023 02:49 pm (GMT +9)
5.5
10 km87 km (54 mi) to the NW Philippine Sea, 335 km south of Hachijo Jima Island, Tokyo, Japan InfoOct 6, 2023 10:31 am (GMT +9)
6.1
10 km91 km (57 mi) to the NW Philippine Sea, 331 km south of Hachijo Jima Island, Tokyo, Japan 1 reportInfoOct 5, 2023 03:22 pm (GMT +9)
5.7
10 km83 km (52 mi) to the NW Philippine Sea, 337 km south of Hachijo Jima Island, Tokyo, Japan InfoOct 5, 2023 11:53 am (GMT +9)
5.7
10 km88 km (55 mi) to the NW Philippine Sea, 352 km south of
Click this link to continue reading the article on the source website.
RSS feed source: USGS Earthquake Hazards Program
Time2025-06-03 23:13:06 UTC2025-06-03 23:13:06 UTC at epicenterLocation33.498°N 81.857°EDepth10.00 km (6.21 mi)
Click this link to continue reading the article on the source website.
RSS feed source: USGS Earthquake Hazards Program
U.S. citizens are strongly encouraged to apply
The Adaptive Real-Time Systems Laboratory (ARTS-Lab) at the University of South Carolina invites applications for a fully funded Ph.D. research assistant position devoted to advancing artificial-intelligence and machine-learning methods on small, power-constrained hardware—edge AI—for real-time, in-situ manufacturing. Our group develops novel sensors for metal and polymer additive-manufacturing (AM) processes and couples them with embedded AI to detect, diagnose, and ultimately prevent defects as parts are being built. The successful candidate will help design secure sensing pipelines, craft physics-aware ML models that ingest vibration, acoustic, thermal, LiDAR, and event-camera streams, and deploy those models on microcontrollers, FPGAs (including side-channel-resistant and cyber-hardened implementations), and emerging neuromorphic chips. Cybersecurity is a first-class concern: you will explore lightweight encryption, anomaly detection, and trusted-execution primitives so that edge devices remain resilient against tampering and data exfiltration even in harsh industrial environments. Although
Click this link to continue reading the article on the source website.