omniomni/omni-engineering huggingface dataset:
Robert S. Boyer. Robert Stephen Boyer is an American retired professor of computer science, mathematics, and philosophy at The University of Texas at Austin. He and J Strother Moore invented the Boyer–Moore string-search algorithm, a particularly efficient string searching algorithm, in 1977. He and Moore also collaborated on the Boyer–Moore automated theorem prover, Nqthm, in 1992. Following this, he worked with Moore and Matt Kaufmann on another theorem prover called ACL2. He was elected AAAI Fellow in 1991.

Publications 

Boyer has published extensively, including the following books:

 A Computational Logic Handbook, with J S. Moore. Second Edition. Academic Press, London, 1998. 
 Automated Reasoning: Essays in Honor of Woody Bledsoe, editor. Kluwer Academic, Dordrecht, The Netherlands, 1991.
 A Computational Logic Handbook, with J S. Moore. Academic Press, New York, 1988.
 The Correctness Problem in Computer Science, editor, with J S. Moore. Academic Press, London, 1981.
 A Computational Logic, with J S. Moore. Academic Press, New York, 1979.

See also 

 Boyer–Moore majority vote algorithm
 QED manifesto

References

External links
Home page of Robert S. Boyer. Accessed February 18, 2016.
University of Texas, College of Liberal Arts Honors Retired Faculty - 2008. Accessed March 21, 2009.

Living people
Alumni of the University of Edinburgh
University of Texas at Austin faculty
Fellows of the Association for the Advancement of Artificial Intelligence
Formal methods people
Lisp (programming language) people
1946 births
Chromel. Chromel is an alloy made of approximately 90% nickel and 10% chromium by weight that is used to make the positive conductors of ANSI Type E (chromel-constantan) and K (chromel-alumel) thermocouples. It can be used at temperatures up to  in oxidizing atmospheres. Chromel is a registered trademark of Concept Alloys, Inc.

Chromel A
Chromel A is an alloy containing approximately 80% nickel and 20% chromium (by weight), with low-level quantities of Si (1%), Fe (0.5%), and Ni. It is used for its excellent resistance to high-temperature corrosion and oxidation. It is also commonly called Nichrome 80-20, and is used for electric heating elements.

Chromel C
Chromel C is an alloy containing 60% nickel, 16% chromium and 24% iron. It is also commonly called Nichrome 60 and is used for heating elements, resistance windings, and hot wire cutters.

Chromel-R 

Chromel R has a composition of Cr 20%, Ni 80%. 

Chromel-R was also produced as a woven fabric of chromel wires. It was developed by Litton Industries for use by NASA in the Gemini and Apollo programs. 

The Gemini G4C spacesuit did not use Chromel-R as standard. However the Gemini 9 mission was to test the use of the Astronaut Maneuvering Unit, a free-flying 'rocket pack'. To protect against the hot exhaust of its hydrogen peroxide engine, Gene Cernan's suit was given additional protection with an over-trouser layer of Chromel-R. The spacewalk during this flight gave a number of problems, with Cernan overheating and finding the suit difficult to move in it, with "all the flexibility of a rusty suit of armor". The Chromel-R layer was an integral part of the spacesuit, although the confined Gemini capsule did not require much movement until the spacewalk. Once pressurised, the suit became difficult to move in.

Smaller patches of Chromel-R formed an outer layer of the Apollo spacesuit where abrasion resistance was needed. These patches can be seen as silver-grey areas over the white Beta cloth of the main suit. Using patches, rather than an entire garment, avoided the flexibility problems with Gemini. The upper areas of the overshoes, the gloves and patches beneath the life support backpack were of Chromel-R. Gold-plated open-weave Chromel-R mesh has also been used as the reflecting surface for compact-folding parabolic antenna on spacecraft.

References and notes

External links
  Materials properties of thermocouple wires sold by Omega Engineering, Inc.
  Technical information on alloys at Electrovek-Steel Ltd.

Nickel–chromium alloys
Nickel alloys
Chromium alloys
Special Patrol Insertion/Extraction. The Special Patrol Insertion/Extraction (SPIE) system was developed as a means to rapidly insert and/or extract a reconnaissance patrol from an area that does not permit a helicopter to land.  SPIE has application for rough terrain as well as water inserts/extracts. It is an adaptation of the STABO rig.

Generally, the SPIE rope is lowered into the pickup area from a hovering helicopter.  Patrol personnel, each wearing a harness with an attached carabiner, hook up to a D-ring inserted in the SPIE rope.  A second safety line is attached to a second D-ring located above the first.  The helicopter lifts vertically from an extract zone until the rope and personnel are clear of obstructions, then proceeds in forward flight to a secure insert zone.  The rope and personnel are treated as an external load and airspeeds, altitudes, and oscillations must be monitored.

The United States Coast Guard uses a similar technique to board ships when speed and stealth are required.

History
The Special Personnel Insertion/Extraction was first designed by United States Marines of 1st Force Reconnaissance Company, the Marine division's 1st Reconnaissance Battalion, and the 1st Marine Aircraft Wing riggers. In 1969 they created and actively used several versions of the SPIE in combat before it was officially recommended to be tested. In May 1970, the commanding general of 3rd Marine Amphibious Force coordinated input from the 1st Marine Division and his 1st Marine Aircraft Wing. A request was sent to the Commandant of the Marine Corps and to the Development Center for certification of the SPIE rig and to its safety and use.

The parachute test jumpers of the Naval Parachute Unit (NPU) and Marine Corps, all qualified parachutist designers and engineers, assembled together at NAS El Centro for the initial testing and evaluation of the SPIE rig. After a few test dummies were tried, Marine Major Bruce F. Meyers, along with four Navy NPU parachutist engineers, successfully attempted the first flight on the current SPIE assembly.

See also
 Fulton surface-to-air recovery system
 Helicopter Rope Suspension Technique

References

Military education and training
Military equipment introduced in the 1960s
SPIE (disambiguation). SPIE is the Society of Photo-Optical Instrumentation Engineers, an international optical engineering society.

SPIE may also refer to:
 SPIE SA, a French industrial equipment company
Special Patrol Insertion/Extraction, a military technique for insertion/extraction
Spie Batignolles, France-based multinational engineering company
SPIE Gold Medal, the highest honor of the International Society for Optics and Photonics
SPIE Newsroom, a technical news website launched in March 2006
To reduce the heating and cooling energy demand of buildings and districts novel control strategies are constantly being developed that require information on the future demand of the controlled entity. Demand forecasting is com- monly done with deterministic white box models or ﬁtted grey-box models, however, recently more and more data and machine learning based approaches are being developed. All approaches have weaknesses: white-box models require major modelling e ort, grey-box approaches are limited by their model or parameter complexity and machine learning is dependent on hyperparameters, some of which are randomly chosen, and therefore considered unreliable. Here we develop a forecasting approach based on Artiﬁcial Neural Networks (ANN) and introduce error correction methods based on online learning and the learned autocorrelation of the forecasting error. We compare the approach to other regression based and grey-box methods in a real case study of a small-scale district energy system with mixed use and unknown lower-level control. We show that the proposed method outperforms the other forecasting methods in terms of average error and coe cient of determination. We further demonstrate that in our case study the error correction methods signiﬁcantly reduce variance in ANN performance created by randomly initialized parameters in the networks. Keywords: Artiﬁcial Neural Networks, demand forecasting, online learning, error autocorrelation, building energy demand, district energy demand 1. Introduction Building and district heating and cooling energy amounts to 70% of the total energy demand in house- holds in Switzerland (BFE, 2014) and to more than 44% of the total primary energy consumption world- wide ( ¨Olz et al., 2007). To reduce this demand, novel control strategies are constantly being developed (see for example ˇSirok ´y et al. (2011); Yudong Ma et al. (2012); Oldewurtel et al. (2010); Sturzenegger et al. (2016); B ¨unning et al. (2017), or Hameed Shaikh et al. (2014) and the
This paperdocuments comparisionbetweentraditional FEA andSimsolidassemblyanalysis. Keywords Catia,Ansys,Simsolid,Cotter. Introduction A cotter joint, also known as a socket and spigot joint, is a method of temporarily joining two coaxial rods. Simsolid eliminates geometry preparation and meshing: the two most time-consuming, expertise- extensive,anderror-prone tasks performedina conventional structural simulation. Ansys Mechanical is a best-in-class finite element solver with structural, thermal, acoustics, transient andnonlinearcapabilities toimprove yourmodeling. Design and Analysis Figure 1and2 ThedesignhasbeendoneinCatiaV5usingpartandassemblydesign.(showninfig.1&2)Socket has outer radius of 50 mm and inner radius of 30 mm, length being 100 mm and the pocket has beendone40mmfromspigotinsertionside.Spigotisasolidcylinderhavingradiusof30mmand height of 100 mm of which 30 mm is outside socket. The pocket has been done while keeping alignment in mind. The cotter has dimensions of 10x10x120 and fits so that assembly has horizontal symmmetry. Note:Thegeometryhasbeenexportedto/importedinAnsysaswellasSimsolidinstpfileformat. Figure 3 In Ansys Workbech, Structural steel has been selected as default material as shown in figue 3 above. Figure 4& 5 Theforceof1000Nhasbeendefinedonspigot(fig.4)andafixedconnectionhasbeenappliedon socket (fig.5). FIgure 6(default mesh) Figure 7 Infigure 7,the maximum deformationpredictedbyAnsys is 1.515e-7inmetres. Figure 8 Same geometry has been imported in Altair Simsolid and forces/constraints have been applied appropriatelywithsame material (steel)as illustratedinfigure 8. Figure 9 Infigure9,theresultformaximumdeformationgivenbySimsolid’sanalysisis1.5017e-04inmm which when converted into metres will be the same order of magnitude of the max. def. given by Ansys Mechanical infigure 7. The Similaritytherefore is: (1.5017/1.515)x100%= 99.12% Conclusion Simsolid’s new methodis reliable andfast whencomparedtoAnsys Mechanical’s FEA.
With the increase in depth and complexity, deep learning networks have made significant progress in various directions. However, the theoretical understanding of deep learning is still incomplete. Early research successfully proved the universal approximation theorem for linear networks, but these proofs were limited to linear networks. Subsequent studies attempted to prove the approximation properties of convolutions and Transformers, but the proof processes often relied on complex assumptions or were very intricate. This paper aims to propose a unified approach to demonstrate that multi-layer networks composed of convolutions and Transformers are specific realizations of the universal approximation theorem. This approach does not require any assumptions and proves that most networks composed of convolutions and Transformers can be mathematically written in the same form as the fully proven universal approximation theorem, thus establishing them as specific implementations of the universal approximation theorem. This bridges the gap between deep learning practice and theoretical understanding. The method of unifying them is to represent these network architectures (linear, convolutional, and Transformer) in matrix-vector form, hence this unified approach is called the matrix-vector method. This paper takes an important step towards unifying the entire field of deep learning. It deepens our theoretical understanding and reveals the fundamental principles behind the exceptional performance of these networks. It also paves the way for exploring new research directions and optimizing the learning process in various deep learning applications. Keywords: Universal Approximation, Explainable Neural Network 1. Introduction Deep learning, as the most significant research direction in artificial intelligence, has achieved remarkable advancements in machine intelligence, although it currently lacks general human-like intelligence. However, it has demonstrated extraordinary capabilities and promising future appli- cations in specific domains such as image processing, natural language processing, and temporal analysis. Various deep learning models have been designed, which are essentially stacks of multiple layers of Linear, 1D, 2D, 3D convolutions or Transformers. Given the outstanding performance of deep learning in AI, a multitude of researchers are de- voting themselves to model development, aiming to find efficient, high-performance models that require less data. Despite this, deep learning remains largely empirical, with researchers often de- signing network architectures based on intuition or previous experience, testing their performance, and creating different models for specific problems. This approach consumes substantial human resources and computational power and is inherently speculative. To address this issue, there is a pressing need for a fundamental theoretical framework for deep learning – one that aligns with current experiments and experiences while guiding future developments. This paper proposes a unifying approach to deep learning and, based on this, provides answers to some fundamental questions, offering valuable theoretical
The pursuit of scientific exploration missions to Mercury presents a complex array of challenges arising from the planet's extreme proximity to the Sun and unique environmental conditions. This comprehensive review systematically examines the obstacles inherent in such e ndeavors, including the vast distance between Earth and Mercury, temperature differentials, solar flares, and landing complexities. The challenges encompass communication disruptions, energy production issues, and the critical task of selecting suitable la nding sites. The paper emphasizes the need for strategic solutions and technological advancements to overcome these hurdles, contributing not only to the success of the mission but also to the broader advancement of space exploration. The intricate analysi s underscores the importance of addressing these challenges to enhance our understanding of Mercury and to pave the way for future missions that expand the boundaries of human knowledge in our solar system . Table of Contents 1. Introduction ................................ ................................ ................................ ................................ ......................... 1 2. Distance from Earth ................................ ................................ ................................ ................................ ............ 1 3. High Temperature ................................ ................................ ................................ ................................ ............... 1 4. Solar F lares and Coronal Mass Ejection ................................ ................................ ................................ ............. 2 9. Conclusion ................................ ................................ ................................ ................................ .......................... 2 10.
This study examines the impact of workforce reduction on project completion times in the South African construction industry during the COVID -19 pandemic. Adopting a positivist research philosophy with a quantitative design, the study utilized an online survey targeting CIDB -registered contractors, yielding 62 responses. Despite minimal overall workforce reductions, the loss of skilled labor signiﬁ cantly impeded project progress, primarily due to quarantine protocols. The research applies the Adaptive Chaos Management Theory in Construction (ACMTC), highlighting non -linear dynamics and the critical role of skilled labor. Findings reveal substantial project delays linked to workforce shortages, underscoring the need for ﬂexible workforce strategies and robu st health protocols. Recommendations for the industry include adopting multi -skilling, enhancing health measures, and investing in technology. Policy suggestions advocate for pandemic- speciﬁc construction guidelines and incentives for technological advanc ements. Academia is urged to further explore workforce management strategies and the integration of technology in crisis contexts. This study contributes to both theoretical understanding and practical applications, providing a framework for resilience in construction project management amid global disruptions . Keywords: Construction industry, COVID -19, Project delays, Quarantine impact, Skilled workforce reduction, South Africa. Article type: Full length research paper ( 9,834), this submission does not relate to a conference or a special issue but does relate to the completion of an MSc at the University of Witwatersrand (First Author). The word count excludes title, author names and afﬁliations, keywords, highlights , abbreviations, funding, acknowledgments, conﬂict of interest, data availability statement and
— The process of fitting a prosthetic hand that is a comfortable, functional, easy to use, has an acceptable appearance and overall improves the amputees' quality of life is a complex, tedious and costly process. The very high price tag due to the time spent on manually fitting the device by a trained specialist makes these devices inaccessible to large portions of the population. We present a concept and preliminary results for a fully automated fitting and manufacturing pipeline for a personalized low-cost prosthetic hand. The hand is personalized in almost every aspect, from appearance to user interface, control and feedback. The pipeline only requires a 3D printer, a RealSense camera, a few basic mechanical components and basic tools for the model assembly. The user scan-driven data and the user p
/T_h.ligais preprint concerns polytropic processes, a fundamental process type in engineering thermodynamics. An etymology is presented for the term, and the ties to its usefulness are identi/fi.ligaed. /T_h.ligae seemingly new support concept of ‘logical’ thermodynamic process, as well as the seemingly new working concept of ‘exact’ polytropic process, and a statement for ‘local’ polytropic process, are herein provided. /T_h.ligae proposition of employing local polytropic processes as computational discrete elements for generic engineering thermodynamics process modeling is made. Finally, theoretical requisites for a process to be an exact polytropic one, including the deduction of the most general equation of state of the underlying substance, subject to u:u(T), are discussed beyond a reference. Keywords /T_h.ligaermodynamics — Polytropic Processes — Logical Processes — Etymology Remarks Provides etymolo/g_y.liga for the ‘polytropic’ term — De/fi.liganes logical thermodynamic process — De/fi.liganes exact polytropic process — Presents a statement for local polytropic process — De/fi.liganes theoretical requisites for exact polytropic process /one.lfUniversidade Tecnol ´ogica Federal do Paran ´a – UTFPR, C ˆampus Guarapuava. Grupo de Pesquisa em Ci ˆencias T ´ermicas. ?Corresponding author : NaaktgeborenC ·PhD@gmail ·com License https://creativecommons.org/licenses/by/4.0/ Contents /one.lf Introduction /one.lf /two.lf Etymology of the ‘Polytropic’ Term /two.lf /three.lf Exact and Local Polytropic Processes /two.lf /three.lf./one.lf Logical Processes . . . . . . . . . . . . . . . . . . . . . . . . /two.lf /three.lf./two.lf Exact Polytropic Processes . . . . . . . . . . . . . . . . . /three.lf /three.lf./three.lf Local Polytropic Processes . . . . . . . . . . . . . . . . . /four.lf /four.lf Requisites for Exact Polytropic Processes /five.lf /four.lf./one.lf Substance Equation of State Yielding u:u(T). . . /six.lf /four.lf./two.lf Speci/fi.ligac Heats of a u:u(T)Substance . . . . . . . . . /six.lf /four.lf./three.lf Energy Balance with a u:u(T)Model . . . . . . . . . /seven.lf /five.lf Summary and Conclusions /eight.lf
Over the decades, scholars and data scientists have extensively explored the correlation between satellite mass and its impact on satellite reliability —an essential consideration for satellite manufacturers and space agencies [1]. Initially, a conceptual notion, a group of statisticians has now rigorously defined the reliability parameter of spacecraft across different mass categories, utilizing a survival analysis algorithm pioneered by Kaplan & Meier in 1958 [2]. J.H Saleh's analysis reveals that spacecraft in the medium -range category (with mass ranging from approximately 500 -1000 kilograms) exhibits maximum reliability and a longer lifespan. This statistical model has provided a foundation for the next generation of data scientists to redefine satellite reliability models [3]. Figure -1: (left) Spacecraft Mass Fraction versus reliability & Spacecraft propellant mass fraction versus reliability (right) [Note: These graphs were generated using Kaplan -Meier estimation me thod , whereas the figure graph were estimated from Weibull probability estimation ] Examining mass parameters such as spacecraft dry mass, propellant mass, and payload mass, the role of propellant mass emerges as crucial in determining spacecraft survival in various planetary orbits. Propellant facilitates trajectory raising maneuvers, course corrections, and orbital stabilization (e.g., ESA’s Cassini's final plunge due to propellant exhaustion). Therefore, integrating a larger propellant tank into a relat ively small spacecraft may not extend its lifespan; in fact, it could lead to spacecraft destabilization. Maintaining an optimal propellant and spacecraft mass ratio becomes paramount for effective operations. Addressing this, an innovative mathematical an d statistical model has been introduced and validated, defining a propellant mass fraction limit of 0.2 to 0.6 as optimal for longer survivability [4 -5]. Figure -2: Spacecraft Mass and Propellant mass fraction versus reliability. In conclusion, the various masses of a spacecraft significantly impact its lifespan and reliability. Satellite manufacturers must carefully consider mass and mass fraction parameters during the design and validation phases to ensure the spacecraft's optimal performance before deplo ying it into any interplanetary orbit. This consideration remains a critical task, especially as recovering a spacecraft beyond low -earth orbit poses significant challenges. *Founder & CEO, Acceleron Aerospace, Bangalore, Karnataka, India – 560037. Contact: malaykumar1997@gmail.com **Received: 22 -November -2023 || Revised: 30 -November -2023 || Accepted: 30-December -2023 || Published Online: 30-December -2023 AAJ.2106 -2322