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Avoid Fines! Complete Locations of Karachi’s E-Challan Cameras
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November 3, 2025 at 8:22 AM
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October 17, 2025 at 6:07 AM
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Versitron highway incident response video amplifier provides stable, long-distance video transmission for faster, safer traffic incident management.

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October 17, 2025 at 6:05 AM
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Best AI Tools to Analyze Your Website Traffic - Article For U
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October 2, 2025 at 2:00 AM
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September 4, 2025 at 10:00 AM
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Daggett County's airports could be on the brink of transformation as a seasoned pilot calls for strategic planning to boost traffic and development.

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Skypark Airport Owners Discuss Development and Traffic Monitoring Plans
Airport managers propose mechanisms for Dutch John and Manila airport development oversight.
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August 20, 2025 at 1:50 AM
helpnetsecurity.com
Open-source flow monitoring with SENSOR: Benefits and trade-offs

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Open-source flow monitoring with SENSOR: Benefits and trade-offs - Help Net Security
An open source flow monitoring platform delivers unsampled traffic analysis using interchangeable, standards-compliant tools.
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August 14, 2025 at 10:30 AM
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Google Search Console launches comparison mode for 24-hour performance data #GoogleSearchConsole #SEOTools #DigitalMarketing #TrafficMonitoring #PerformanceData
Google Search Console launches comparison mode for 24-hour performance data
Real-time search data comparison provides marketers enhanced traffic monitoring capabilities.
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July 16, 2025 at 1:49 PM
ppc.land
Google Search Console launches comparison mode for 24-hour performance data #GoogleSearchConsole #SEOTools #DigitalMarketing #TrafficMonitoring #PerformanceData
Google Search Console launches comparison mode for 24-hour performance data
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July 16, 2025 at 1:49 PM
citizenptnewstx.bsky.social
Clute City is taking a bold step towards enhanced public safety by introducing a new license plate reader system that could transform community crime prevention.

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City plans to deploy five license plate readers and a mobile unit for traffic monitoring
City announces installation of five fixed license plate readers and one mobile unit for monitoring.
citizenportal.ai
July 14, 2025 at 5:37 PM
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June 4, 2025 at 8:33 AM
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Unmasking Unexpected Visitors: A Guide to Sudden Referral Traffic from Niche Sites

Read on- [Your Guide to Investigation & Action](www.seosiri.com/2025/05/nich...)

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Increased, Sudden Niche Site Referral Traffic? Your Guide to Investigation & Action
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May 31, 2025 at 12:23 AM
lawrencesystems.com
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May 23, 2025 at 10:02 AM
helpnetsecurity.com
SafeLine Bot Management: Self-hosted alternative to Cloudflare

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April 17, 2025 at 1:05 PM
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March 28, 2025 at 8:55 PM
ivojuri.bsky.social
Detecting earthquakes or just passing cars? 🌍🚗 A research uses deep learning to distinguish seismic signals from earthquakes, vehicles, and noise with 99% accuracy!📡🔬

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https://link.springer.com/article/10.1007/s10950-024-10267-8 Figure 2: Frequency Analysis of Noise, Vehicle, and Earthquake Signals Axes Explanation: X-Axis (Frequency in Hz): Represents the frequency content of the seismic signals. Frequency (Hertz, Hz) refers to the number of oscillations per second. Y-Axis (Amplitude, not explicitly labeled but inferred): Represents the strength or power of the seismic signal at different frequencies. Color Representation: Green: Noise signal components. Blue: Vehicle-related seismic signals. Red: Earthquake-related seismic signals. Types of Lines (Dotted vs. Solid): Each color has three dotted lines, corresponding to the East, North, and Vertical components of motion. - East, North, and Vertical refer to the three axes of ground motion measured by a seismometer. - Vertical component measures up-down movement. - East and North components measure horizontal movements in their respective directions. Interpretation & Relevance: Noise (Green): Dominates at high frequencies (>30 Hz), which indicates environmental or anthropogenic disturbances. Vehicle (Blue): Peaks between 5 Hz and 20 Hz, showing the frequency range of seismic signals generated by passing vehicles. Earthquake (Red): Stronger in the lower frequency range (0-10 Hz), which is typical for seismic events as earthquake waves have lower frequencies and longer wavelengths. Relevance to the Study: Helps in distinguishing between different seismic sources by analyzing their frequency characteristics. Relevance to Real Life: Understanding frequency differences is crucial for earthquake detection, noise filtering, and distinguishing between natural and human-made seismic events. Figure 6: Model Prediction for Noise, Earthquake, and Vehicle Seismic Signals Over Time Axes Explanation: X-Axis (Time in Minutes, 0–60 min): Represents an hour-long seismic recording. Y-Axis (Seismic Signal & Model Prediction): Represents seismic activity in three orientations: - East-West (Top Panel) - North-South (Middle Panel) - Vertical (Bottom Panel) Color Representation: Red (Earthquake): Indicates moments when the model predicts earthquake activity. Blue (Vehicle): Shows periods when the model detects seismic signals from vehicles. Green (Noise): Represents background noise detected by the model. Black (Seismic Data): The actual recorded seismic signal. Interpretation & Relevance: The model successfully identifies different sources of seismic activity. Noise (Green) is persistent and appears frequently in the vertical component. Vehicles (Blue) appear intermittently in the North-South component, matching expected vehicle movement. Earthquakes (Red) are rare and appear as spikes in the East-West component. Relevance to the Study: Demonstrates the model's capability to classify seismic events accurately. Relevance to Real Life: Helps in automatic seismic monitoring, reducing false alarms, and improving earthquake early warning systems. Figure 9: Impact of Time-Shifted Vehicle Noise on Earthquake Seismic Signals and Their Frequency Response X and Y Axes Left Side (Time-Domain Signal) - X-axis: Time (in seconds) → Shows how the signal changes over time. - Y-axis: Amplitude (measured in acceleration or velocity) → Represents the strength of the signal. A strong earthquake will have a high-amplitude waveform, while weaker signals will have lower amplitudes. Right Side (Frequency-Domain - FFT Representation) - X-axis: Frequency (Hz) → Represents how often a certain vibration occurs per second. - Y-axis: Amplitude (Intensity in frequency domain) → Shows how strong the signal is at different frequencies. FFT helps separate different sources of vibrations: - Low frequencies (~0-5 Hz): Typically associated with earthquakes. - Higher frequencies (~10-20 Hz): More likely caused by vehicles or human activity. Colors Red Line: Represents the original earthquake signal. Blue Line: Represents the vehicle signal (vibrations caused by a vehicle). Black Line: Represents the combined signal (earthquake + vehicle noise). By comparing these colors, researchers can determine how vehicle noise affects earthquake signal detection. Type of Lines Used Solid lines are used for all signals, but different colors distinguish earthquake signals, vehicle-induced noise, and their combination. The presence of overlapping or diverging lines indicates interference between signals. Explanation of Technical Words & Abbreviations FFT (Fast Fourier Transform): A mathematical technique that converts a time-domain signal into a frequency-domain signal. It helps analyze the different sources contributing to the signal. Why This Figure is Important (Scientific & Practical Relevance) For Earthquake Studies: Helps understand how human activity (e.g., vehicle movement) interferes with seismic readings. This can improve earthquake detection and help seismologists filter out noise. For Urban Planning. For Public Safety.
February 25, 2025 at 2:41 AM