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There is a gap in aerial logging techniques that has to be filled. The need for a simple, safe, sizeable system has to be developed before aerial logging will become effective and accepted in the logging industry. This paper presents such a system designed on simple principles with realistic cost and ecological benefits.
The program theory used to obtain the software package, MAIL LOG, developed for the Scout Project Automatic Data System, SPADS, is described. The program is written in FORTRAN for the PRIME 300 computer system. The MAIL LOG data base consists of three main subfiles: (1) incoming and outgoing mail correspondence; (2) design information releases and reports; and (3) drawings and engineering orders. All subroutine descriptions, flowcharts, and MAIL LOG outputs are given and the data base design is described.
The operating instructions for the software package, MAIL LOG, developed for the Scout Project Automatic Data System, SPADS, are provided. The program is written in FORTRAN for the PRIME 300 computer system. The MAIL LOG program has the following four modes of operation: (1) INPUT - putting new records into the data base (2) REVISE - changing or modifying existing records in the data base (3) SEARCH - finding special records existing in the data base (4) ARCHIVE - store or put away existing records in the data base. The output includes special printouts of records in the data base and results from the INPUT and SEARCH modes. The MAIL LOG data base consists of three main subfiles: Incoming and outgoing mail correspondence; Design Information Releases and Releases and Reports; and Drawings and Engineering orders.
Log-Hough transform is basis of improved method for recognition of patterns - particularly, straight lines - in noisy images. Takes advantage of rotational and scale invariance of mapping from Cartesian to log-polar coordinates, and offers economy of representation and computation. Unification of iconic and Hough domains simplifies computations in recognition and eliminates erroneous quantization of slopes attributable to finite spacing of Cartesian coordinate grid of classical Hough transform. Equally efficient recognizing curves. Log-Hough transform more amenable to massively parallel computing architectures than traditional Cartesian Hough transform. "In-place" nature makes it possible to apply local pixel-neighborhood processing.
Currently existing message logging protocols demonstrate a classic pessimistic vs. optimistic tradeoff. We show that the optimistic-pessimistic tradeoff is not inherent to the problem of message logging. We construct a message-logging protocol that has the positive features of both optimistic and pessimistic protocol: our protocol prevents orphans and allows simple failure recovery; however, it requires no blocking in failure-free runs. Furthermore, this protocol does not introduce any additional message overhead as compared to one implemented for a system in which messages may be lost but processes do not crash.
The use of neutron and gamma ray measurements for the analysis of material composition has become well established in the last 40 years. Schlumberger has pioneered the use of this technology for logging wells drilled to produce oil and gas, and for this purpose has developed neutron generators that allow measurements to be made in deep (5000 m) boreholes under adverse conditions. We also make ruggedized neutron and gamma ray detector packages that can be used to make reliable measurements on the drill collar of a rotating drill string while the well is being drilled, where the conditions are severe. Modern nuclear methods used in logging measure rock formation parameters like bulk density and porosity, fluid composition, and element abundances by weight including hydrogen concentration. The measurements are made with high precision and accuracy. These devices (well logging sondes) share many of the design criteria required for remote sensing in space; they must be small, light, rugged, and able to perform reliably under adverse conditions. We see a role for the adaptation of this technology to lunar or planetary resource assessment missions.
ELDEC Corp., Lynwood, Wash., built a weight-recording system for logging trucks based on electronic technology the company acquired as a subcontractor on space programs such as Apollo and the Saturn launch vehicle. ELDEC employed its space-derived expertise to develop a computerized weight-and-balance system for Lockheed's TriStar jetliner. ELDEC then adapted the airliner system to a similar product for logging trucks. Electronic equipment computes tractor weight, trailer weight and overall gross weight, and this information is presented to the driver by an instrument in the cab. The system costs $2,000 but it pays for itself in a single year. It allows operators to use a truck's hauling capacity more efficiently since the load can be maximized without exceeding legal weight limits for highway travel. Approximately 2,000 logging trucks now use the system.
The heart of flight operations control involves a) communicating effectively in real time with other controllers in the room and/or in remote locations and b) tracking significant events, decisions, and rationale to support the next set of decisions, provide a thorough shift handover, and troubleshoot/improve operations. International Space Station (ISS) flight controllers speak with each other via multiple voice circuits or loops, each with a particular purpose and constituency. Controllers monitor and/or respond to several loops concurrently. The primary tracking tools are console logs, typically kept by a single operator and not visible to others in real-time. Information from telemetry, commanding, and planning systems also plays into decision-making. Email is very secondary/tertiary due to timing and archival considerations. Voice communications and log entries supporting ISS operations have increased by orders of magnitude because the number of control centers, flight crew, and payload operations have grown. This paper explores three developmental ground system concepts under development at Johnson Space Center s (JSC) Mission Control Center Houston (MCC-H) and Marshall Space Flight Center s (MSFC) Payload Operations Integration Center (POIC). These concepts could reduce ISS control center voice traffic and console logging yet increase the efficiency and effectiveness of both. The goal of this paper is to kindle further discussion, exploration, and tool development.
Technologies including NMR logging apparatus and methods are disclosed. Example NMR logging apparatus may include surface instrumentation and one or more downhole probes configured to fit within an earth borehole. The surface instrumentation may comprise a power amplifier, which may be coupled to the downhole probes via one or more transmission lines, and a controller configured to cause the power amplifier to generate a NMR activating pulse or sequence of pulses. Impedance matching means may be configured to match an output impedance of the power amplifier through a transmission line to a load impedance of a downhole probe. Methods may include deploying the various elements of disclosed NMR logging apparatus and using the apparatus to perform NMR measurements.
Techniques are provided for globally appending data from a group of distributed processes to a shared file using a log-structured file system. Data generated by a plurality of processes in a parallel computing system are appended to a shared file by storing the data to the shared file using a log-structured file system (such as a Parallel Log-Structured File System (PLFS)); and generating an index entry for the data, the index entry comprising a logical offset entry and a timestamp entry indicating a time of the storage, wherein the logical offset entry is resolved at read time. The logical offset entry can be populated with an append placeholder that is resolved when the shared file is read. At read time, a plurality of the index entries associated with the shared file can be sorted using the timestamp entry to deliver the requested shared file to a requesting application.
The Log-N/Period system utilizes a compensated ion chamber to measure neutron radiation in the reactor core. This analysis focuses on determining a more accurate value for the sensitivity of the installed compensated ion chambers for the Log-N/Period system at the ATR. Using calibration procedures a formula for indirectly calculating the sensitivity of the chambers was derived. Using historical data from approximately ten reactor cycles a new average sensitivity for both channels of the Log-N/Period system was determined.
This dataset is a collection of well logs provided by Schlumberger Technologies from the Utah FORGE well 16B(78)-32 drilling project. Information here includes critical borehole information collected by an ultrasonic borehole imager (UBI) and a fullbore formation microimager (FMI). Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The total depth measured 10,947 feet and the vertical depth measured 8,357 feet.
Data, logs, and graphics associated with the drilling and testing of Utah FORGE deep test well 58-32 (MU-ESW1) near Roosevelt Hot Springs.
These are production logging tests (PLT) results from Halliburton collected during the nine hour circulation test performed at Utah FORGE on April 27th, 2024. The circulation test involved injecting into well 16A(78)-32 and producing out of well 16B(78)-32) and was carried out after the fracturing of both of those wells. Data attached here includes raw and processed PLT logs from both wells, as well as technical reports summarizing the data collection and results.
This submission includes drilling logs, mud log, deviation survey, site observation notes, and whole core scans from the Citizen Green #1 well drilled on King Island, CA (API 07720688) as part of the WESTCARB partnership basin characterization effort. These datasets were gathered by JAF but created and compiled by a variety of WESTCARB operations team members and contractors including Sandia Resources, Stratagraphic Corp, John Henry Beyer, Paul Graham Drilling, and Core Labs.
Molecular-replacement phasing of macromolecular crystal structures is often fast, but if a molecular-replacement solution is not immediately obtained the crystallographer must judge whether to pursue molecular replacement or to attempt experimental phasing as the quickest path to structure solution. The introduction of the expected log-likelihood gain has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is the log-likelihood gain on intensity expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error and the measurement errors in the data. It is shown how the eLLG may be used to answer the question 'can I solve my structure by molecular replacement?'. However, this is only the most obvious of the applications of the eLLG. It is also discussed how the eLLG may be used to determine the search order and minimal data requirements for obtaining a molecular-replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement and likelihood-guided model pruning.
Deep learning has recently demonstrated state-of-the art performance on key tasks related to the maintenance of computer systems, such as intrusion detection, denial of service attack detection, hardware and software system failures, and malware detection. In these contexts, model interpretability is vital for administrator and analyst to trust and act on the automated analysis of machine learning models. Deep learning methods have been criticized as black box oracles which allow limited insight into decision factors. In this work we seek to "bridge the gap'' between the impressive performance of deep learning models and the need for interpretable model introspection. To this end we present recurrent neural network (RNN) language models augmented with attention for anomaly detection in system logs. Our methods are generally applicable to any computer system and logging source. By incorporating attention variants into our RNN language models we create opportunities for model introspection and analysis without sacrificing state-of-the art performance. We demonstrate model performance and illustrate model interpretability on an intrusion detection task using the Los Alamos National Laboratory (LANL) cyber security dataset, reporting upward of 0.99 area under the receiver operator characteristic curve despite being trained only on a single day's worth of data.
This is the full wireline geophysical datasets for characterization of the EGS Collab Experiment #1 testbed on the 4850 level. A metadata file is included within the dataset explaining the logs, fracture picks, etc. Eight boreholes were drilled for this testbed and each one was logged with north seeking gyro, optical televiewer, acoustic televiewer, fluid temperature conductivity, resistivity and gamma, and full waveform sonic. In these folders are the processed results as text, csv, and pdf files, along with the raw data which will need to be read using WellCAD software.