(redirected from Raw Sensor Data)
RSDRoland Sands Design (Los Alamitos, CA)
RSDRecord Store Day (annual event)
RSDReflex Sympathetic Dystrophy (now Complex Regional Pain Disorder, CRPD)
RSDRisque Suicidaire (French: Suicide Risk; psychiatry)
RSDRelative Standard Deviation (statistics)
RSDRichland School District (Washington)
RSDRecovery School District (Louisiana)
RSDRiverview School District (Oakmont, Pennsylvania)
RSDRoadside Delivery (Australia Post)
RSDReally Simple Discoverability
RSDRapid Software Delivery
RSDRestart Data Set
RSDRoot System Description
RSDRiverside County Sheriff's Department
RSDRock Sound, Bahamas (Airport Code)
RSDRèglement Sanitaire Départemental (French: Departmental Health Regulations)
RSDRegulatory Services Division (various locations)
RSDRubber Side Down
RSDRight of Self-Determination
RSDReading School District (Reading, PA)
RSDRefugee Status Determination (UNHCR)
RSDReal Social Dynamics (dating coaches)
RSDRegional Sales Director
RSDRefundable Security Deposit
RSDRaindrop Size Distribution (meteorological studies)
RSDRetinal Scanning Display (aka Virtual Retinal Display)
RSDResearch Skills Development (various locations)
RSDRouted Systems Designer (diagramming tool)
RSDRemote Shut Down
RSDResearch and Statistics Division (various organizations)
RSDRemote Service Delivery (Australia)
RSDRemote Sensing Data
RSDRed Sudamericana de Danza (Spanish: South American Dance Network)
RSDRoad Safety Division (various locations)
RSDRoot Surface Debridement (dental treatment)
RSDRidgefield School District (Washington)
RSDRetail Solutions Division (various businesses)
RSDRational Systems Developer (IBM)
RSDRinggold High School (Monongahela, Pennsylvania)
RSDResearch Software Design (various companies)
RSDRefrigeration Supplies Distributor (various locations)
RSDRetirement Services Division (various locations)
RSDRetirement Systems Division (North Carolina)
RSDRed Shoe Diaries
RSDRoute Server Daemon
RSDRatoon Stunting Disease (sugarcane) (Google Ultimate Frisbee discussion board)
RSDRisk Specific Dose
RSDReporting of Supply Discrepancy (US DoD)
RSDRapid System Development
RSDRetail Services Division (various businesses)
RSDRegular Scheduled Drill
RSDResearch and Statistics Department (Home Office, UK)
RSDRedundant Signed Digit
RSDRevenue Services Department (various locations)
RSDRadiation Safety Division (Occupational Health and Safety Departments in hospitals and universities)
RSDRobla School District (Sacramento, CA)
RSDRapid Securing Device
RSDRegional Seafood Development (taxes; Alaska)
RSDRoyal Schools for the Deaf (now Seashell Trust; UK)
RSDRailhead Supply Detachment (Australia)
RSDRichmond Sound Design (est. 1972)
RSDReactive Sputter Deposition
RSDRéseaux et Systèmes Distribués (French: Networks and Distributed Systems)
RSDRational Software Delivery
RSDRaw Sensor Data
RSDRadiological Support Devices
RSDReparable Support Division
RSDRange Safety Display
RSDRadar Storm Detection
RSDReduced Stopping Distance
RSDRequirements and Specifications Document (project management)
RSDRated Strength of Device
RSDRecitation, Seminar or Discussion (discussion group)
RSDRace Stunt Deathmatch (gaming group)
RSDReparable Stock Division
RSDReflector Surface Distortion
RSDRandom Saturated Degree
RSDRadar Signal Detecting (APR-39 antennas)
RSDRemote Storage Device
RSDRedistribution Stop Date
References in periodicals archive ?
Making sense of the flood of data arriving at widely different rates and latencies requires the use of an onboard sensor fusion platform to perform a series of challenging tasks, beginning with co-registration of raw sensor data, low-level feature detection (edges and blobs), and identifying preliminary feature correspondences.
Caption: FIGURE 3: Raw sensor data of angular rate, acceleration, and Magnetic field.
Injecting synthetically generated raw sensor data into the unit eliminates the drawback of undesired interference with the test surrounding.
“Power plant operators can meet that need by supplementing a preventative and condition-based maintenance program with a predictive analytics solution that transforms raw sensor data into important health and performance information in real-time.
"Because we know we can rely on that 'truth' data we can take the raw sensor data and develop our algorithms so that they align with it.
ManySense provides a unified access to (a) raw sensor data retrieved from both internal and external sensors and (b) high level context data which is based on the inferential analysis of raw data.
In a large safety-critical sensor application, where the sensors and actuators are housed together, the actuator cannot perform any instant intelligent actions from the raw sensor data that have been accumulated.
Raw sensor data can be distilled to remove all the extraneous signals and uncover the hidden characteristic patterns.
Furthermore, this paper presents a new structure for determining dynamic fault probabilities based on raw sensor data and behavior of robot.
Linear inverse theory may be employed in extracting the surface height profiles from the raw sensor data. Schajer and Gazzarri (2004) provide further details on the procedure used to solve Eqs.
One may ask why compression of raw sensor data hasn't been used before for medical imaging applications (e.g., CT, ultrasound, MRI, PET, etc.) The short answer is simple: no high-speed lossless compression algorithm has been available that achieves acceptable (~2:1) compression ratios for the raw sensor data from which medical images are formed.
Our algorithms will help us determine the likelihood of the raw sensor data being associated with activities of interest that we're studying.