- #UNF ELECTRICAL ENGINEERING CALCULATOR HOW TO#
- #UNF ELECTRICAL ENGINEERING CALCULATOR DRIVER#
- #UNF ELECTRICAL ENGINEERING CALCULATOR SOFTWARE#
Read and interpret HVEDR data using the Synercon Forensic Link Adapter with Synercon and truck engine manufacturer software. Assist automobile manufacturers in improving new releases to Bosch CDR.Ĭonsult on accident reconstruction and analysis including human factors, restraint systems performance in crashes, and occupant kinematics.
Perform beta testing for the Bosch Crash Data Retrieval system. Speak at national and regional accident reconstruction conferences on new developments in EDR’s.
Instruct police officers and accident reconstructionists in reading and interpreting EDR’s as contractor to UNF-IPTM, SAE, and custom instruction through Ruth Consulting.Ĭonduct EDR accuracy research and publish findings in peer reviewed professional journals to pave the way for improved data admissibility. Assist crash reconstructionists and attorneys in getting EDR data from manufacturers not covered by any publicly available tool. Assist prosecutors and other attorneys in EDR data admissibility hearings.
#UNF ELECTRICAL ENGINEERING CALCULATOR HOW TO#
Assist engineers and lawyers in understanding how to make the best use of EDR data in their cases.
#UNF ELECTRICAL ENGINEERING CALCULATOR DRIVER#
Apply the data to Traffic Crash Reconstruction to determine vehicle speeds and driver behavior prior to impact.
#UNF ELECTRICAL ENGINEERING CALCULATOR SOFTWARE#
Also read vehicles not covered by Bosch CDR using the specialty GIT Hyundai & Kia EDR kits, the Subaru SSM3/SSM4 software w/Denso interface, the Mitsubishi EDR tool and the Tesla tool. Read automotive Event Data Recorders (EDR’s) using the Bosch Crash Data Retrieval (CDR) system. of Michigan - Ann ArborĪnalyze performance of automotive restraint systems in crashes. Electrical Engineering (with Honors) Michigan Technological UniversityĠ9/73 - 04/78 M.B.A. The proposed energy-reducing technique is potentially applicable to other key elements of blockchain computations, potentially affording even "greener" blockchain-powered systems than implied by only the Merkle Tree and Proof of Work results obtained thus far.Ruth Consulting 910-5809, 3275 Van Hazen NW, Washington, DC 20015.Ġ9/69 - 03/73 B.S. For Proof-of-Work calculations, our results show an average energy reduction of 20\% across typical difficulty levels.
Our results show up to 98\% reduction in energy consumption is possible within the blockchain's Merkle Tree construction module, such reductions typically increasing with larger input sizes. Using pyRAPL, a python library to measure computational energy, we experiment with both the standard and energy-reduced implementations of the Merkle Tree for different input sizes (in bytes) and of the Proof of Work for different difficulty levels. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application.