7,055 research outputs found

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    A Bibliography of NPS Space Systems Related Student Research, 2013-2022

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    Dudley Knox Library, Naval Postgraduate School.Approved for Public Release; distribution is unlimite

    GPT-3.5, GPT-4, or BARD? Evaluating LLMs Reasoning Ability in Zero-Shot Setting and Performance Boosting Through Prompts

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    Large Language Models (LLMs) have exhibited remarkable performance on various Natural Language Processing (NLP) tasks. However, there is a current hot debate regarding their reasoning capacity. In this paper, we examine the performance of GPT-3.5, GPT-4, and BARD models, by performing a thorough technical evaluation on different reasoning tasks across eleven distinct datasets. Our paper provides empirical evidence showcasing the superior performance of ChatGPT-4 in comparison to both ChatGPT-3.5 and BARD in zero-shot setting throughout almost all evaluated tasks. While the superiority of GPT-4 compared to GPT-3.5 might be explained by its larger size and NLP efficiency, this was not evident for BARD. We also demonstrate that the three models show limited proficiency in Inductive, Mathematical, and Multi-hop Reasoning Tasks. To bolster our findings, we present a detailed and comprehensive analysis of the results from these three models. Furthermore, we propose a set of engineered prompts that enhances the zero-shot setting performance of all three models.Comment: Accepted for publication at Elsevier's Natural Language Processing Journa

    Studies in the Life and Work of Jean Baptiste Andre Dumas (1800-1884): The Period up to 1850.

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    Jean Baptiste Dumas (1800-188U) was an outstanding experimental chemist who gave a sense of direction to the study of organic chemistry in the second quarter of the 19th century. He did this by framing hypotheses boldly and fruitfully, believing in the simplicity of nature's fundamental relationships and a need for classification as a means of emphasising this. Stress has been placed on the important period of, Dumas' formation in Geneva, his research in physiology and the transition period in Paris where he was drawn to chemical research by appointments at the Ecole Polytechnique and the Athenee. An interest in industrial chemistry led to his textbook in applied chemistry and to the founding of an industrial journal and school. In the College de France he gave an influential course on chemical philosophy. His election to the Academy in 1832 was followed by appointments to the Faculty of Sciences and the Faculty of Medicine, where he gained a reputation as an outstanding professor of chemistry, and a guide for research students, both French and foreign. His practical contributions to chemistry included procedures for measuring vapour densities, organic nitrogen analysis and accurate determination of atomic weights, to which he was led by Prout's hypothesis. His unique combination of creative intuition, sound judgment, a strong reliance on experimental data and a virtually limitless capacity for work made possible his seminal contributions to the theory of organic chemistry: ethers, amides, substitution, types, a law of fat acids. New compounds were discovered as a result, but more important, he laid the foundations for more general modes of classification, the homologues and types of one of his students, Gerhardt. Dumas was the first to make extensive and successful use of chemical formulae and equations to explain reactions in organic chemistry. His influence on classification of the elements and atomic theory was profound. This thesis provides the necessary documentation to integrate the various aspects of Dumas' life and work up to 1850, after which he became increasingly involved in national politics and administration

    Micro-Electro Discharge Machining: Principles, Recent Advancements and Applications

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    Micro electrical discharge machining (micro-EDM) is a thermo-electric and contactless process most suited for micro-manufacturing and high-precision machining, especially when difficult-to-cut materials, such as super alloys, composites, and electro conductive ceramics, are processed. Many industrial domains exploit this technology to fabricate highly demanding components, such as high-aspect-ratio micro holes for fuel injectors, high-precision molds, and biomedical parts.Moreover, the continuous trend towards miniaturization and high precision functional components boosted the development of control strategies and optimization methodologies specifically suited to address the challenges in micro- and nano-scale fabrication.This Special Issue showcases 12 research papers and a review article focusing on novel methodological developments on several aspects of micro electrical discharge machining: machinability studies of hard materials (TiNi shape memory alloys, Si3N4–TiN ceramic composite, ZrB2-based ceramics reinforced with SiC fibers and whiskers, tungsten-cemented carbide, Ti-6Al-4V alloy, duplex stainless steel, and cubic boron nitride), process optimization adopting different dielectrics or electrodes, characterization of mechanical performance of processed surface, process analysis, and optimization via discharge pulse-type discrimination, hybrid processes, fabrication of molds for inflatable soft microactuators, and implementation of low-cost desktop micro-EDM system

    CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

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    This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship

    Utilizing the Value of Smart Sensor Data in Motor Manufacturing

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    The topic of this master’s thesis was the utilizing of the value of smart sensor data in motor manufacturing at an electric motor factory in Vaasa. The target company has developed and manufactured smart sensors to customers for years and is now implementing them in its own production. In the thesis’s the possibilities of utilization of the data of smart sensor utilization in the Vaasa factory has been studied through a specified case study. The motors included in the pilot were selected by their usage in the process. The target was to identify improvement potentials for smart sensors in discrete industries and to create a plan for sensor data usage and further development. With the increased value of the efficient data usage, the target is to reduce unplanned stoppages, improve safety, and minimize the penalties and other costs paid because of delayed motors. An additional target was to improve the service and spare part activities with better utilization of data from the sensors as well as define the suitability of current motors in use to their current intended use. The concrete target of this thesis was to create reporting tools to the target company. First, a literature study was carried out for the basics in sensors, smart sensors, and electric motors. Special focus was on the target company’s smart motor sensors and their competitors on the market. With the information available the products were compared to each other. Conclusion were made on the basis of the pilot installation on the target factory’s premises on the value of the smart sensors on discrete production. Through the case study the additional value created to the target company of the smart sensor data was analyzed. A roadmap was created for the smart sensor data for further analyses, storing data and user experience. The outcome of this thesis was several Power BI templates, a fleet report and several recommendations for further development. Through a comparison it was noted that the ABB Ability Smart Sensor TM as a product is slightly more advanced than the smart sensors of the competitors. It was observed that only measuring the data does not bring value to the company, but the data has to be transformed into understandable and visual information and only after that it can bring real value to the company. In the case study it was also noted that actions based on the data created by the sensors can be performed in order to reduce unplanned outages in the motor manufacturing with the predictive data for timing of services and repairs. It was also observed that the data and information provided by the smart sensors can also be utilized in discrete manufacturing on motors that are not continuously used. This is additionally to the knowledge compared to the motors used in process industries where the value of the sensor data was already confirmed in earlier studies.Diplomityön aiheena on kohdeyrityksen älykkään anturin tuottama lisäarvo yhtiön Vaasan moottoritehtaan moottorivalmistuksessa. Kohdeyritys on valmistanut älykkäitä antureita asiakkaille myytäväksi jo useita vuosia ja on nyt käyttöönottamassa tuotteen omassa prosessissaan. Työssä tutkitaan älykkään anturin tuottaman datankäytön mahdollisuuksia kohdeyrityksen Vaasan yksikössä, määritellyn pilotin avulla. Pilottiin valittiin moottorit käyttötarkoituksen mukaan. Tavoitteena on tunnistaa kehittämiskohteita älykkäälle sensorille kappaletavaratuotannossa sekä luoda suunnitelma sensoridatan käytölle ja sen kehittämiseen. Datan tehokkaan käytön tavoitteina on pienentää suunnittelemattomia käyttökatkoksia, parantaa työturvallisuutta ja minimoida moottorien viivästyneiden toimitusten aiheuttamat lisääntyneet rahti ja muut ylimääräiset kustannukset. Lisäksi datankäytön tuomalla lisäarvolla pyritään kehittämään huolto- ja varaosatoimintaa, sekä määrittelemään käytössä olevien moottorien soveltuvuus nykyiseen käyttötarkoitukseensa. Konkreettisena tavoitteena on luoda toimeksiantoyritykselle raportointityökaluja. Työ alussa on kirjallisuuskatsaus anturien, älykkäiden anturien ja sähkömoottoreiden perusteisiin. Erityisesti tarkasteltiin kohdeyrityksen älykkäitä antureita ja sen kilpailijoita. Näitä vertailtiin toisiinsa saatavilla olevan tiedon avulla. Älykkään anturin pilottiasennuksen perusteella tehtiin johtopäätöksiä antureiden soveltuvuudesta kappaletavaratuotantoon esimerkkiyrityksen kautta. Pilotin perusteella pyrittiin analysoimaan tuotteen käyttöönoton kannattavuutta kohdeyritykselle. Lopuksi luotiin tiekartta antureista saatavan datan analysoinnille, tallettamiselle ja esittämiselle. Työn tuloksena syntyi Power BI raportointipohjia ja fleet report sekä kehitysehdotuksia jatkotoimenpiteille. Lisäksi työssä havaittiin, että ABB:n Ability Smart Sensor TM on tuotteena kilpailijoitaan hieman edellä tuotteen ominaisuuksien ja käytettävyyden osalta. Työssä havaittiin, että pelkkä datan mittaaminen sensoreilla ei itsessään tuo lisäarvoa yritykselle, vaan data pitää muuttaa ymmärrettäväksi informaatioksi ja vasta sen jälkeen se tuo lisäarvoa kohdeyritykselle. Edellisten lisäksi pilotissa havaittiin, että anturien tuottaman datan perusteella voidaan tehdä toimenpiteitä, jotta tuotannon suunnittelemattomia katkoksia pystyttäisiin vähentämään käyttämällä Smart Sensorin tuottamia tietoja ennakoivien huoltojen ja korjausten ajastamisessa. Ilmi tuli myös, että Smart Sensoreiden tuottamaa dataa voi käyttää myös kappaletavarateollisuudessa käytössä olevissa moottoreissa, jotka eivät ole jatkuvassa käytössä. Näin on siis prosessiteollisuudessa jatkuvassa käytössä olevien moottorien lisäksi, jossa sensorien tuotta-man datan hyöty on vahvistettu jo aikaisemmin

    Technologies and Applications for Big Data Value

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    This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
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