Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Line, Surface, and Volume Integrals01:15

Line, Surface, and Volume Integrals

4.4K
A line integral for a vector field is defined as the integral of the dot product of a vector function with an infinitesimal displacement vector along a prescribed path. If the prescribed path is closed, the integrals reduce to a closed-line integral. The closed-contour integral of the vector field is referred to in terms of the circulation of the vector field around the closed path. A vector with zero circulation around every closed path is called a conservative field, while one with non-zero...
4.4K
Integration by Parts: Indefinite Integrals01:26

Integration by Parts: Indefinite Integrals

230
Integration by parts is a fundamental technique in calculus for evaluating integrals involving the product of two functions. It is particularly useful when direct integration is not feasible. The method is based on the product rule for differentiation, which states that the derivative of a product equals the derivative of the first function times the second, plus the first function times the derivative of the second. By integrating this identity and rearranging terms, the integration by parts...
230
Integration by Parts: Definite Integrals01:23

Integration by Parts: Definite Integrals

91
Definite integrals involving the product of two functions over a fixed interval can be evaluated using integration by parts. This method rewrites the integral as the difference of a product evaluated at the endpoints and a remaining definite integral that is often simpler to compute.A representative example is the definite integral of the inverse tangent function. Since there is no direct integration formula for arctan ⁡x, the integrand is rewritten as a product of arctan⁡ x and the...
91
Definite Integral01:29

Definite Integral

81
Consider a real-valued function defined on a closed interval. One of the fundamental objectives in calculus is to determine the area under the graph of such a function. When an exact computation is not readily available, this area can be estimated by dividing the interval into a finite number of equal subintervals. Each subinterval corresponds to a rectangle whose width is the length of the subinterval and whose height is determined by the value of the function at a selected point within that...
81
Indefinite Integrals01:25

Indefinite Integrals

75
The water inflow rate into a storage tank is not constant but increases over time. Initially, the pump delivers water at a rate of 5 L/min. However, the inflow rate increases by 2 L/min for each additional minute due to rising pressure or system adjustments. This scenario can be described mathematically by a linear function:It is necessary to integrate the inflow rate function to measure the total volume of water added to the tank over time. The total water volume V(t) is obtained by performing...
75
Integration by Parts: Problem Solving01:29

Integration by Parts: Problem Solving

75
Smart speakers process voice commands by modeling audio inputs as piecewise functions and analyzing them through integration against trigonometric functions, such as cosine. This mathematical approach is fundamental in signal processing, where complex sound waves are decomposed into simpler frequency components.Consider a definite integral involving a piecewise function multiplied by a cosine function. Because the function is defined differently over separate intervals, the integral is split...
75

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Suture Materials, Needles, and Methods of Skin Closure: What Every Hand Surgeon Should Know.

The Journal of hand surgery·2021
Same author

Secondary Management of Nonnail Perionychial Deformities: Restoring Aesthetic and Functional Subunits.

Hand clinics·2020
Same author

Designing Laboratory for IoT Communication Infrastructure Environment for Remote Maritime Surveillance in Equatorial Areas Based on the Gulf of Guinea Field Experiences.

Sensors (Basel, Switzerland)·2020
Same author

Why you should wear your seatbelt on an airplane: Burst fracture of the atlas (jefferson fracture) due to in-flight turbulence.

Journal of orthopaedics·2019
Same author

Fuzzy Functional Dependencies as a Method of Choice for Fusion of AIS and OTHR Data.

Sensors (Basel, Switzerland)·2019
Same author

A Prospective Study on the Effect of Corticosteroid Injection Dosage for Hand Disorders in Non-Insulin Dependent Diabetics.

Bulletin of the Hospital for Joint Disease (2013)·2019

Related Experiment Video

Updated: Feb 12, 2026

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations
06:51

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations

Published on: August 21, 2018

7.5K

Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System

Dejan Nikolic1, Nikola Stojkovic2, Nikola Lekic3

  • 1Vlatacom Institute, Bulevar Milutina Milankovića 5, Beograd 11070, Serbia. dejan.nikolic@vlatacom.com.

Sensors (Basel, Switzerland)
|April 13, 2018
PubMed
Summary
This summary is machine-generated.

This study presents an algorithm for integrating maritime data from High Frequency Surface Wave Radar (HFSWR) and Automatic Identification System (AIS) to improve the operational picture in Exclusive Economic Zones (EEZs). The method effectively fuses sensor data, even with AIS latency, for enhanced maritime surveillance.

Keywords:
HF radarLAISOTH radarSAISdata integrationmarine systemsradarradar tracking

More Related Videos

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.2K
Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

29.0K

Related Experiment Videos

Last Updated: Feb 12, 2026

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations
06:51

Microparticle Manipulation by Standing Surface Acoustic Waves with Dual-frequency Excitations

Published on: August 21, 2018

7.5K
Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
07:14

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

8.2K
Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

29.0K

Area of Science:

  • Maritime Surveillance Technology
  • Sensor Data Fusion
  • Oceanographic Remote Sensing

Background:

  • Achieving a comprehensive maritime operational picture beyond the horizon (OTH) in Exclusive Economic Zones (EEZs) necessitates integrating diverse sensor data.
  • Existing surveillance systems face challenges in data synchronization and latency, particularly in remote maritime areas.

Purpose of the Study:

  • To develop and validate an algorithm for fusing data from High Frequency Surface Wave Radar (HFSWR), Satellite Automatic Identification System (SAIS), and Land Automatic Identification System (LAIS).
  • To enhance maritime situational awareness by creating integrated data pairs from disparate sensor inputs, addressing OTH challenges.

Main Methods:

  • Utilized a multi-target tracking algorithm to process HFSWR tracks.
  • Developed a data association algorithm to pair HFSWR tracks with SAIS and LAIS data based on a matching factor.
  • Accounted for potential high latency in AIS data transmission, especially in developing countries' EEZs.

Main Results:

  • Successfully designed, implemented, and tested the data integration algorithm in a real-world maritime environment.
  • Demonstrated effective data fusion even with varying data quality and latency.
  • The algorithm prioritizes the best data association when multiple sensor inputs are available.

Conclusions:

  • The proposed algorithm effectively integrates HFSWR, SAIS, and LAIS data to provide a more complete maritime operational picture.
  • The system is robust to AIS data latency, making it suitable for surveillance in EEZs of developing nations.
  • Validated testing in the Gulf of Guinea confirms the algorithm's practical applicability for enhanced maritime security.