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Zeitschriftenartikel zum Thema "Addressing Machines"
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CURRAN, KEVIN, NEIL McCAUGHLEY und XUELONG LI. „ADDRESSING THE PROBLEMS OF DETECTING FACES WITH NEURAL NETWORKS“. International Journal of Image and Graphics 07, Nr. 04 (Oktober 2007): 617–40. http://dx.doi.org/10.1142/s0219467807002830.
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The face is the most distinctive and widely used key to a person's identity. The area of face detection has attracted considerable attention in the advancement of human-machine interaction as it provides a natural and efficient way to communicate between humans and machines. The problem of facial parts in image sequences has become a popular area of research due to emerging applications in intelligent human-computer interface, surveillance systems, content-based image retrieval, video conferencing, financial transaction, forensic applications, pedestrian detection, image database management system and so on. This paper presents the results of an image based neural network face detection system which seeks to address the problem of detecting faces under gross variations.
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Gulcehre, Caglar, Sarath Chandar, Kyunghyun Cho und Yoshua Bengio. „Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes“. Neural Computation 30, Nr. 4 (April 2018): 857–84. http://dx.doi.org/10.1162/neco_a_01060.
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We extend the neural Turing machine (NTM) model into a dynamic neural Turing machine (D-NTM) by introducing trainable address vectors. This addressing scheme maintains for each memory cell two separate vectors, content and address vectors. This allows the D-NTM to learn a wide variety of location-based addressing strategies, including both linear and nonlinear ones. We implement the D-NTM with both continuous and discrete read and write mechanisms. We investigate the mechanisms and effects of learning to read and write into a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU controller. We provide extensive analysis of our model and compare different variations of neural Turing machines on this task. We show that our model outperforms long short-term memory and NTM variants. We provide further experimental results on the sequential [Formula: see text]MNIST, Stanford Natural Language Inference, associative recall, and copy tasks.
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Rakes, David, Muhammad Arif, Agus Setiawan, Kerina Putri Nasution und Yudi Prastyo. „Preventive Maintenance on CNC Machines Using the OEE Method to Reduce Downtime at PT. MTAT“. Jurnal Impresi Indonesia 3, Nr. 7 (05.07.2024): 481–90. http://dx.doi.org/10.58344/jii.v3i7.5116.
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This study examines the performance of CNC machines at PT MTAT Indonesia from January to March 2023. Monthly production data, machine uptime, defect rates, and non-productive periods were collected to assess Overall Equipment Effectiveness (OEE). This study aims to analyze the effectiveness of preventive maintenance of CNC machines at PT MTAT Indonesia using the Overall Equipment Effectiveness (OEE) method to reduce downtime. This study uses monthly data from January to March 2023, including production uptime, defect rates, and non-productive periods, to calculate OEE. The analysis showed that the CNC machines achieved an average OEE of 86.52%, surpassing the global standard of 85%, indicating high efficiency and quality. The study used Pareto analysis to identify the main causes of downtime, finding technical and maintenance issues as the main contributors. By addressing these factors, PT MTAT Indonesia can further improve machine efficiency and productivity. This study contributes to this field by providing a comprehensive analysis of CNC machine maintenance and proposing strategies for continuous improvement.
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Hosseini, Ahmad, Ola Lindroos und Eddie Wadbro. „A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines“. Canadian Journal of Forest Research 49, Nr. 2 (Februar 2019): 111–20. http://dx.doi.org/10.1139/cjfr-2018-0258.
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Ground-based mechanized forestry requires the traversal of terrain by heavy machines. The routes that they take are often called “machine trails” and are created by removing trees from the trail and placing the logs outside it. Designing an optimal machine trail network is a complex locational problem that requires understanding how forestry machines can operate on the terrain, as well as the trade-offs between various economic and ecological aspects. Machine trail designs are currently created manually based on intuitive decisions about the importance, correlations, and effects of many potentially conflicting aspects. Badly designed machine trail networks could result in costly operations and adverse environmental impacts. Therefore, this study was conducted to develop a holistic optimization framework for machine trail network design. Key economic and ecological objectives involved in designing machine trail networks for mechanized cut-to-length operations are presented, along with strategies for simultaneously addressing multiple objectives while accounting for the physical capabilities of forestry machines, the impact of slope, and the operating costs. Ways of quantitatively formulating and combining these different aspects are demonstrated, together with examples showing how the optimal network design changes in response to various inputs.
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Portase, Raluca Laura, Ramona Tolas und Rodica Potolea. „SmartLaundry: A Real-Time System for Public Laundry Allocation in Smart Cities“. Sensors 24, Nr. 7 (28.03.2024): 2159. http://dx.doi.org/10.3390/s24072159.
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Smart cities facilitate the comprehensive management and operation of urban data generated within a city, establishing the foundation for smart services and addressing diverse urban challenges. A smart system for public laundry management uses artificial intelligence-based solutions to solve the challenges of the inefficient utilization of public laundries, waiting times, overbooking or underutilization of machines, balancing of loads across machines, and implementation of energy-saving features. We propose SmartLaundry, a real-time system design for public laundry smart recommendations to better manage the loads across connected machines. Our system integrates the current status of the connected devices and data-driven forecasted usage to offer the end user connected via a mobile application a list of recommended machines that could be used. We forecast the daily usage of devices using traditional machine learning techniques and deep learning approaches, and we perform a comparative analysis of the results. As a proof of concept, we create a simulation of the interaction with our system.
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Tirkashev Dilshodjon Sharobiddin o’gli. „AI and Pragmalinguistics: Bridging the Gap Between Machines and Human Communication“. Journal of Advanced Zoology 44, S6 (10.12.2023): 1760–66. http://dx.doi.org/10.17762/jaz.v44is6.2614.
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Pragmatic linguistics, a field that examines the connection between language and context, is at the forefront of efforts to enhance machine understanding of human communication. In the context of artificial intelligence (AI), which has transformed various sectors, pragmatic linguistics plays a vital role in addressing the challenges of human-like interaction. This article delves into the intersection of AI and pragmalinguistics, shedding light on the possibilities and obstacles faced in bridging the divide between machines and human communication.
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Flowers, Michael, und Kai Cheng. „Global Manufacturing: Reconfiguration of Machines in Addressing Changing Customer Requirement Scenarios“. Applied Mechanics and Materials 16-19 (Oktober 2009): 15–19. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.15.
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The dynamics of customer requirements in the global domain are dictating a need for the reconfiguration of existing conventional manufacturing systems in order to adapt and respond to the changing functional requirements. This study presents the investigation of the feasibility of adapting a hydraulic cam system to a power press for uphill sheetmetal piercing. The surface topography of sheared edges of blanks and slugs was analyzed using Zygo New View 200 Scanning White Light Interferometer. The piercing force in each trial was monitored and analyzed via computer-press interface data acquisition system (DAS). The average piercing force, 10721N, obtained was found to be nearly constant throughout the experimental trials.
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Manzotti, Riccardo, und Antonio Chella. „Conscious Machines: A Possibility? If So, How?“ Journal of Artificial Intelligence and Consciousness 07, Nr. 02 (24.07.2020): 183–98. http://dx.doi.org/10.1142/s2705078520710022.
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The scope of the paper is to encourage scientists and engineering to avoid to do what Einstein pointed out as being the hallmark of folly. Machine consciousness scholars must be brave enough to step out of the beaten path. There must be some big recurrent conceptual mistakes that prevent science and technology from addressing machine consciousness.
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Stelzner, Marc, Falko Dressler und Stefan Fischer. „Function Centric Nano-Networking: Addressing nano machines in a medical application scenario“. Nano Communication Networks 14 (Dezember 2017): 29–39. http://dx.doi.org/10.1016/j.nancom.2017.09.001.
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Sin, Dong Eui. „A Study on Moral Education in the Age of Artificial Intelligence: Focusing on the Distinction and Application of Ethics of Artificial Moral Agent (AMA)“. Korean Journal of Teacher Education 39, Nr. 3 (31.05.2023): 29–48. http://dx.doi.org/10.14333/kjte.2023.39.3.02.
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Purpose: The purpose of this study is to investigate the ultimate difference and limitations between humans and machines while addressing the most heated controversy in the era of artificial intelligence, particularly the question of “Can machines think?”, which is considered a critical issue in moral education in the age of artificial intelligence. Methods: To this end, the direction of moral education in the AI era is sought through analysis and reflective discourse on literature materials related to digital technologies such as the Fourth Industrial Revolution, artificial intelligence (AI), big data and machine learning. Results: From the perspective of moral education in the era of artificial intelligence, this study discusses the classification of Artificial Moral Agents (AMA) and the application of ethics, focusing on reflective discourse on science and technological civilization. In other words, it examines three principles of machine construction based on Stuart Russell’s belief in “beneficial machines” from the perspective of “preference”, presents Moors four stages of AMAs, and addresses the concept of explicit ethical agents in the third stage. Additionally, it explores Heidegger's critique of technological civilization and discusses creativity in relation to the controversies surrounding artificial intelligence. Conclusion: Based on this, the present study explored the potential application of moral education in artificial intelligence through the question “Can machines think?”, which can be a core topic in the field of artificial intelligence.
Dissertationen zum Thema "Addressing Machines"
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Munnich, Nicolas. „Operational and categorical models of PCF : addressing machines and distributing semirings“. Electronic Thesis or Diss., Paris 13, 2024. http://www.theses.fr/2024PA131015.
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Bien qu'elle ait été introduite il y a plus de 60 ans, PCF reste intéressante. Bien que la quête d'un modèle satisfaisant et totalement abstrait de PCF ait été résolue au tournant du millénaire, de nouveaux modèles de PCF apparaissent encore fréquemment dans la littérature, explorant des voies inexplorées ou utilisant PCF comme une lentille ou un outil pour étudier une autre construction mathématique. Dans cette thèse, nous nous appuyons sur notre connaissance des modèles de PCF de deux manières distinctes : En construisant un tout nouveau modèle, et en s'appuyant sur les modèles existants. Les machines d'adressage sont un type relativement nouveau de machine abstraite qui s'inspire des machines de Turing. Il a déjà été démontré que ces machines peuvent modéliser l'ensemble du ?-calcul non typé. Nous nous appuyons sur ces machines pour construire des machinesd'adressage étendues (EAM) et les doter d'un système de type. Nous montrons ensuite que ces machines peuvent être utilisées pour obtenir un nouveau modèle entièrement abstrait et distinct de PCF : Nous montrons que les machines simulent fidèlement PCF de telle sorte qu'un terme PCF se termine par un chiffre exactement lorsque la machine d'adressage étendue correspondante se termine par le même chiffre. De même, nous montrons que chaque machine d'adressage étendue typée peut être transformée en un programme PCF avec le même comportement d'observation. De ces deux résultats, il découle que le modèle de PCF obtenu en quotientant les EAM typables par une relation logique appropriée est totalement abstrait. Il existe une pléthore de modèles catégoriels solides de PCF, en raison de sa relation étroite avec le ?-calcul. Nous considérons deux modèles similaires (qui sont aussi des modèles de logique linéaire) qui sont basés sur des sémirings : Les modèles pondérés, qui utilisent les sémirations pour quantifier une valeur interne, et les modèles de multiplicité, qui utilisent les sémirations pour modéliser linéairement des fonctions (modèle de l'exponentielle !). Nous étudionsl'intersection entre ces deux modèles en examinant les conditions sous lesquelles deux monades dérivées de sémirings spécifiques se distribuent. Nous découvrons que le fait qu'un semi-anneau ait ou non une somme idempotente fait une grande différence dans sa capacité à distribuer. Notre étude nous conduit à découvrir la notion de distribution non naturelle, qui forme une monade sur une catégorie de Kleisli. Enfin, nous présentons des conditions précises sous lesquelles une distribution particulière peut se former entre deux semisDespite being introduced over 60 years ago, PCF remains of interest. Though the quest for a satisfactory fully abstract model of PCF was resolved around the turn of the millennium, new models of PCF still frequently appear in the literature, investigating unexplored avenues or using PCF as a lens or tool to investigate some other mathematical construct. In this thesis, we build upon our knowledge of models of PCF in two distinct ways: Constructing a brand new model, and building upon existing models. Addressing Machines are a relatively new type of abstract machine taking inspiration from Turing Machines. These machines have been previously shown to model the full untyped ?- calculus. We build upon these machines to construct Extended Addressing Machines (EAMs) and endow them with a type system. We then show that these machines can be used to obtain a new and distinct fully abstract model of PCF: We show that the machines faithfully simulatePCF in such a way that a PCF term terminates in a numeral exactly when the corresponding Extended Addressing Machine terminates in the same numeral. Likewise, we show that every typed Extended Addressing Machine can be transformed into a PCF program with the same observational behaviour. From these two results, it follows that the model of PCF obtained by quotienting typable EAMs by a suitable logical relation is fully abstract. There exist a plethora of sound categorical models of PCF, due to its close relationship with the ?-calculus. We consider two similar models (which are also models of Linear Logic) that are based on semirings: Weighted models, using semirings to quantify some internal value, and Multiplicity models, using semirings to linearly model functions (model the exponential !). We investigate the intersection between these two models by investigating the conditions under which two monads derived from specific semirings distribute. We discover that whether or not a semiring has an idempotent sum makes a large difference in its ability to distribute. Our investigation leads us to discover the notion of an unnatural distribution, which forms a monad on a Kleislicategory. Finally, we present precise conditions under which a particular distribution can form between two semirings
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RICCI, FRANCESCO. „Effective Product Lifecycle Management: the role of uncertainties in addressing design, manufacturing and verification processes“. Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2501694.
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The aim of this thesis is to use the concept of uncertainty to improve the effectiveness of Product Lifecycle Management (PLM) systems. Uncertainty is a rather new concept in PLM that has been introduced with the new technical language, drawn by ISO, to manage Geometrical Product Specification and Verification (GPS) in the challenging environment of modern manufacturing. GPS standards regard in particular design and verification environments, and want to guarantee consistence of information through a technical language which define both specification and verification on sound logical and mathematical bases. In this context, uncertainty is introduced as the instrument that measures consistency: between the designer intentions (specifications) and the manufactured artefact (as it is observed through measurement) as well as between the measurand definition provided by designers (the specification again) and that used by metrologists.
The implications of such an approach have been analyzed through a case study dealing with flatness tolerance and paying particular attention to the verification processes based on Coordinate Measuring Machines (CMM). A Design of Experiment (DoE) has been used and results have been analyzed and used to build a regression model that allows generalization in the experiment validity domain.
Then, using Category Theory, a categorical data model has been defined which represents the operation based structure of GPS language and uses the flatness research results in order to design a software able to concretize the GPS vision of geometrical product specifications management. This software is able to translate specification requirements into verification instructions, estimate the uncertainty introduced by simplified verification operations and evaluate costs and risks of verification operations. It provides an important tool for designers, as it allows a responsible definition of specifications (designer can simulate the interpretation of specifications and have an idea of the costs related with their verification), and for metrologist, as it can be a guide for designing GPS compliant verification missions or handling the usual verification procedures according to the GPS standards.
However, during the study, it has been matured the consciousness that this approach, even if correct and valuable, was not the most suitable to fully exploit the real potential of CMM. Then, aside the GPS oriented work, an adaptive sampling strategy, based on Kriging modelization, has been proposed with very encouraging results.
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Wang, Fulton. „Addressing two issues in machine learning : interpretability and dataset shift“. Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122870.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018Cataloged from PDF version of thesis.
Includes bibliographical references (pages 71-77).
In this thesis, I create solutions to two problems. In the first, I address the problem that many machine learning models are not interpretable, by creating a new form of classifier, called the Falling Rule List. This is a decision list classifier where the predicted probabilities are decreasing down the list. Experiments show that the gain in interpretability need not be accompanied by a large sacrifice in accuracy on real world datasets. I then briefly discuss possible extensions that allow one to directly optimize rank statistics over rule lists, and handle ordinal data. In the second, I address a shortcoming of a popular approach to handling covariate shift, in which the training distribution and that for which predictions need to be made have different covariate distributions. In particular, the existing importance weighting approach to handling covariate shift suffers from high variance if the two covariate distributions are very different. I develop a dimension reduction procedure that reduces this variance, at the expense of increased bias. Experiments show that this tradeoff can be worthwhile in some situations.
by Fulton Wang.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Vendra, Soujanya. „Addressing corner detection issues for machine vision based UAV aerial refueling“. Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4551.
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Thesis (M.S.)--West Virginia University, 2006.Title from document title page. Document formatted into pages; contains xi, 121 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 90-95).
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Heffernan, Rhys. „Addressing One-Dimensional Protein Structure Prediction Problems with Machine Learning Techniques“. Thesis, Griffith University, 2018. http://hdl.handle.net/10072/381401.
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In this thesis we tackle the protein structure prediction subproblems listed previously, by
applying state of the art deep learning techniques.
The work in chapter 2 presents the method SPIDER. In this method, state of the art
deep learning is applied iteratively to the task of predicting backbone torsion angles and
, and dihedral angles and , by applying evolutionary-derived sequence pro les and
physio-chemical properties of amino acid residues. This work is the fi rst method for the
sequence based prediction of and angles.
Chapter 3 presents the method SPIDER2. This method takes the state of the art
iterative deep learning applied in SPIDER, and extends it to the prediction of three-state
secondary structure, solvent accessible surface area, and ; ; , and angles, and achieves
the best reported prediction accuracies for all of them (at the date of publication).
Chapter 4 further builds on the work done in the previous chapters, and now adds
the prediction of half sphere exposure (both C and C based) and contact numbers to
SPIDER2, in a method called SPIDER2-HSE.
In Chapter 5, Long Short-Term Memory Bidirectional Recurrent Neural Networks were
applied to the prediction of three-state secondary structure, solvent accessible surface area,
; ; , and angles, as well as half sphere exposure and contact numbers. Previously
methods used for these predictions (including SPIDER2) were typically window based.
That is to say that the input data made available to the model for a given residue, is
comprised of information for only that residue and a number of residues on either side in the sequence (in the range of 10-20 residues on each side). The use of LSTM-BRNNs in
this method allows SPIDER3 to better learn both long and short term interactions within
proteins. This advancement again lead to the best reported accuracies for all predicted
structural properties.
In Chapter 6, the LSTM-BRNN model used in SPIDER3 is applied to the prediction
of the same structural property predictions, plus the prediction of eight-state secondary
structure, using only single-sequence inputs. That is, structural properties were predicted
without using any evolutionary information. This provides a method that provides not
only the best reported single-sequence secondary structure and solvent accessible surface
area predictions, but the fi rst reported method for the single-sequence based prediction of
half sphere exposure, contact numbers, and ; ; , and angles. This study is important
as most proteins have few homologous sequences and their evolutionary profi les are inac-
curate and time-consuming to calculate. This single-sequence-based technique allows for
fast genome-scale screening analysis of protein one-dimensional structural properties.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
Full Text
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RAGONESI, RUGGERO. „Addressing Dataset Bias in Deep Neural Networks“. Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1069001.
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Deep Learning has achieved tremendous success in recent years in several areas such as image classification, text translation, autonomous agents, to name a few. Deep Neural Networks are able to learn non-linear features in a data-driven fashion from complex, large scale datasets to solve tasks. However, some fundamental issues remain to be fixed: the kind of data that is provided to the neural network directly influences its capability to generalize. This is especially true when training and test data come from different distributions (the so called domain gap or domain shift problem): in this case, the neural network may learn a data representation that is representative for the training data but not for the test, thus performing poorly when deployed in actual scenarios. The domain gap problem is addressed by the so-called Domain Adaptation, for which a large literature was recently developed.
In this thesis, we first present a novel method to perform Unsupervised Domain Adaptation. Starting from the typical scenario in which we dispose of labeled source distributions and an unlabeled target distribution, we pursue a pseudo-labeling approach to assign a label to the target data, and then, in an iterative way, we refine them using Generative Adversarial Networks.
Subsequently, we faced the debiasing problem. Simply speaking, bias occurs when there are factors in the data which are spuriously correlated with the task label, e.g., the background, which might be a strong clue to guess what class is depicted in an image. When this happens, neural networks may erroneously learn such spurious correlations as predictive factors, and may therefore fail when deployed on different scenarios. Learning a debiased model can be done using supervision regarding the type of bias affecting the data, or can be done without any annotation about what are the spurious correlations.
We tackled the problem of supervised debiasing -- where a ground truth annotation for the bias is given -- under the lens of information theory.
We designed a neural network architecture that learns to solve the task while achieving at the same time, statistical independence of the data embedding with respect to the bias label.
We finally addressed the unsupervised debiasing problem, in which there is no availability of bias annotation. we address this challenging problem by a two-stage approach: we first split coarsely the training dataset into two subsets, samples that exhibit spurious correlations and those that do not. Second, we learn a feature representation that can accommodate both subsets and an augmented version of them.
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Al-Shahib, Ali Walid. „Addressing the core challenges in predicting protein function from sequence using machine learning“. Thesis, University of Glasgow, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425167.
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Rendleman, Michael. „Machine learning with the cancer genome atlas head and neck squamous cell carcinoma dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality“. Thesis, University of Iowa, 2019. https://ir.uiowa.edu/etd/6841.
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In recent years, more data is becoming available for historical oncology case analysis. A large dataset that describes over 500 patient cases of Head and Neck Squamous Cell Carcinoma is a potential goldmine for finding ways to improve oncological decision support. Unfortunately, the best approaches for finding useful inferences are unknown. With so much information, from DNA and RNA sequencing to clinical records, we must use computational learning to find associations and biomarkers.
The available data has sparsity, inconsistencies, and is very large for some datatypes. We processed clinical records with an expert oncologist and used complex modeling methods to substitute (impute) data for cases missing treatment information. We used machine learning algorithms to see if imputed data is useful for predicting patient survival. We saw no difference in ability to predict patient survival with the imputed data, though imputed treatment variables were more important to survival models.
To deal with the large number of features in RNA expression data, we used two approaches: using all the data with High Performance Computers, and transforming the data into a smaller set of features (sparse principal components, or SPCs). We compared the performance of survival models with both datasets and saw no differences. However, the SPC models trained more quickly while also allowing us to pinpoint the biological processes each SPC is involved in to inform future biomarker discovery.
We also examined ten processed molecular features for survival prediction ability and found some predictive power, though not enough to be clinically useful.
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Mollen, Anne. „Addressing the ghost in the machine or “Is engagement a sustainable intermediate variable between the website drivers of consumer experience and consumers’ attitudinal and behavioural outputs?”“. Thesis, Cranfield University, 2007. http://hdl.handle.net/1826/2047.
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Background and Purpose: In response to the cost transparency of the internet which has facilitated consumer switching behaviour, marketing practitioners have used the umbrella term of engagement to describe the experiential response to mechanisms by which consumers can be enticed and co-opted into behaviour presumed to be conducive to purchase or future purchase. It is a concept that, until recently, has been largely circumvented by the marketing academic world. Therefore, the purpose of this systematic review is to generate a workable definition of consumer brand engagement online, predicated on a research model that builds on extant academic and practitioner evidence, which by virtue of its construction:
1. Shifts the locus of theoretical attention from a mechanistic/structuralist view of online consumer experience, increasingly recognized by the academic world as insufficient in its explanatory power, to more a more unitary approach that aligns behaviourist causality with ‘experiential intensity’
2. Establishes a common discourse, thereby reconciling academic and practitioner perspectives
3. Provides the theoretical base for preliminary work on experiential metrics, and creates a platform for future research.
Methodology: The review uses ‘realist synthesis’ to refine theory from a broad range of heterogeneous sources. The chapter on methodology provides a clear audit trail showing how decisions were made, evidence scrutinised and evaluated, and findings synthesised.
Findings: The review provides support for the model and the definition of online consumer brand engagement, as well some steps towards operationalising the construct. The limitations of the methodology and learning points are discussed, as well as the contribution to future research and practice.
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Konishcheva, Kseniia. „Novel strategies for identifying and addressing mental health and learning disorders in school-age children“. Electronic Thesis or Diss., Université Paris Cité, 2023. http://www.theses.fr/2023UNIP7083.
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The prevalence of mental health and learning disorders in school-age children is a growing concern. Yet, a significant delay exists between the onset of symptoms and referral for intervention, contributing to long-term challenges for affected children. The current mental health system is fragmented, with teachers possessing valuable insights into their students' well-being but limited knowledge of mental health, while clinicians often only encounter more severe cases. Inconsistent implementation of existing screening programs in schools, mainly due to resource constraints, suggests the need for more effective solutions. This thesis presents two novel approaches for improvement of mental health and learning outcomes of children and adolescents. The first approach uses data-driven methods, leveraging the Healthy Brain Network dataset which contains item-level responses from over 50 assessments, consensus diagnoses, and cognitive task scores from thousands of children. Using machine learning techniques, item subsets were identified to predict common mental health and learning disability diagnoses. The approach demonstrated promising performance, offering potential utility for both mental health and learning disability detection. Furthermore, our approach provides an easy-to-use starting point for researchers to apply our method to new datasets. The second approach is a framework aimed at improving the mental health and learning outcomes of children by addressing the challenges faced by teachers in heterogeneous classrooms. This framework enables teachers to create tailored teaching strategies based on identified needs of individual students, and when necessary, suggest referral to clinical care. The first step of the framework is an instrument designed to assess each student's well-being and learning profile. FACETS is a 60-item scale built through partnerships with teachers and clinicians. Teacher acceptance and psychometric properties of FACETS are investigated. Preliminary pilot study demonstrated overall acceptance of FACETS among teachers. In conclusion, this thesis presents a framework to bridge the gap in detection and support of mental health and learning disorders in school-age children. Future studies will further validate and refine our tools, offering more timely and effective interventions to improve the well-being and learning outcomes of children in diverse educational settingsThe prevalence of mental health and learning disorders in school-age children is a growing concern. Yet, a significant delay exists between the onset of symptoms and referral for intervention, contributing to long-term challenges for affected children. The current mental health system is fragmented, with teachers possessing valuable insights into their students' well-being but limited knowledge of mental health, while clinicians often only encounter more severe cases. Inconsistent implementation of existing screening programs in schools, mainly due to resource constraints, suggests the need for more effective solutions. This thesis presents two novel approaches for improvement of mental health and learning outcomes of children and adolescents. The first approach uses data-driven methods, leveraging the Healthy Brain Network dataset which contains item-level responses from over 50 assessments, consensus diagnoses, and cognitive task scores from thousands of children. Using machine learning techniques, item subsets were identified to predict common mental health and learning disability diagnoses. The approach demonstrated promising performance, offering potential utility for both mental health and learning disability detection. Furthermore, our approach provides an easy-to-use starting point for researchers to apply our method to new datasets. The second approach is a framework aimed at improving the mental health and learning outcomes of children by addressing the challenges faced by teachers in heterogeneous classrooms. This framework enables teachers to create tailored teaching strategies based on identified needs of individual students, and when necessary, suggest referral to clinical care. The first step of the framework is an instrument designed to assess each student's well-being and learning profile. FACETS is a 60-item scale built through partnerships with teachers and clinicians. Teacher acceptance and psychometric properties of FACETS are investigated. Preliminary pilot study demonstrated overall acceptance of FACETS among teachers. In conclusion, this thesis presents a framework to bridge the gap in detection and support of mental health and learning disorders in school-age children. Future studies will further validate and refine our tools, offering more timely and effective interventions to improve the well-being and learning outcomes of children in diverse educational settings
Bücher zum Thema "Addressing Machines"
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Office, General Accounting. International trade: U.S. Customs and Border Protection faces challenges in addressing illegal textile transshipment : report to congressional committees. Washington, D.C: GAO, 2004.
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The World Market for Addressing Machines and Address Plate Embossing Machines: A 2004 Global Trade Perspective. Icon Group International, Inc., 2005.
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Parker, Philip M. The World Market for Addressing Machines and Address Plate Embossing Machines: A 2007 Global Trade Perspective. ICON Group International, Inc., 2006.
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Parker, Philip M. The 2007-2012 World Outlook for Electric Pencil Sharpeners, Staplers, and Other Electric Office Machines Excluding Mailing, Letter Handling, and Addressing Machines. ICON Group International, Inc., 2006.
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The 2006-2011 World Outlook for Electric Pencil Sharpeners, Staplers, and Other Electric Office Machines Excluding Mailing, Letter Handling, and Addressing Machines. Icon Group International, Inc., 2005.
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Parker, Philip M. The 2007-2012 Outlook for Electric Pencil Sharpeners, Staplers, and Other Electric Office Machines Excluding Mailing, Letter Handling, and Addressing Machines in Japan. ICON Group International, Inc., 2006.
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Parker, Philip M. The 2007-2012 Outlook for Electric Pencil Sharpeners, Staplers, and Other Electric Office Machines Excluding Mailing, Letter Handling, and Addressing Machines in India. ICON Group International, Inc., 2006.
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The 2006-2011 World Outlook for Mailing, Letter Handling, and Addressing Machines Excluding Parts and Attachments. Icon Group International, Inc., 2005.
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Parker, Philip M. The 2007-2012 World Outlook for Mailing, Letter Handling, and Addressing Machines Excluding Parts and Attachments. ICON Group International, Inc., 2006.
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Parker, Philip M. The 2007-2012 Outlook for Electric Pencil Sharpeners, Staplers, and Other Electric Office Machines Excluding Mailing, Letter Handling, and Addressing Machines in Greater China. ICON Group International, Inc., 2006.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Addressing Machines"
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Venstermans, Kris, Lieven Eeckhout und Koen De Bosschere. „Object-Relative Addressing: Compressed Pointers in 64-Bit Java Virtual Machines“. In ECOOP 2007 – Object-Oriented Programming, 79–100. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73589-2_5.
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Sotiropoulos, Dionisios N., und George A. Tsihrintzis. „Addressing the Class Imbalance Problem“. In Machine Learning Paradigms, 79–106. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47194-5_4.
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Bernth, Arendse. „EasyEnglish: Addressing Structural Ambiguity“. In Machine Translation and the Information Soup, 164–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49478-2_16.
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Pennekamp, Jan, Anastasiia Belova, Thomas Bergs, Matthias Bodenbenner, Andreas Bührig-Polaczek, Markus Dahlmanns, Ike Kunze et al. „Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead“. In Internet of Production, 1–26. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_2-2.
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AbstractThe Internet of Production (IoP) leverages concepts such as digital shadows, data lakes, and a World Wide Lab (WWL) to advance today’s production. Consequently, it requires a technical infrastructure that can support the agile deployment of these concepts and corresponding high-level applications, which, e.g., demand the processing of massive data in motion and at rest. As such, key research aspects are the support for low-latency control loops, concepts on scalable data stream processing, deployable information security, and semantically rich and efficient long-term storage. In particular, such an infrastructure cannot continue to be limited to machines and sensors, but additionally needs to encompass networked environments: production cells, edge computing, and location-independent cloud infrastructures. Finally, in light of the envisioned WWL, i.e., the interconnection of production sites, the technical infrastructure must be advanced to support secure and privacy-preserving industrial collaboration. To evolve today’s production sites and lay the infrastructural foundation for the IoP, we identify five broad streams of research: (1) adapting data and stream processing to heterogeneous data from distributed sources, (2) ensuring data interoperability between systems and production sites, (3) exchanging and sharing data with different stakeholders, (4) network security approaches addressing the risks of increasing interconnectivity, and (5) security architectures to enable secure and privacy-preserving industrial collaboration. With our research, we evolve the underlying infrastructure from isolated, sparsely networked production sites toward an architecture that supports high-level applications and sophisticated digital shadows while facilitating the transition toward a WWL.
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Pennekamp, Jan, Anastasiia Belova, Thomas Bergs, Matthias Bodenbenner, Andreas Bührig-Polaczek, Markus Dahlmanns, Ike Kunze et al. „Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead“. In Internet of Production, 1–25. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_2-1.
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AbstractThe Internet of Production (IoP) leverages concepts such as digital shadows, data lakes, and a World Wide Lab (WWL) to advance today’s production. Consequently, it requires a technical infrastructure that can support the agile deployment of these concepts and corresponding high-level applications, which, e.g., demand the processing of massive data in motion and at rest. As such, key research aspects are the support for low-latency control loops, concepts on scalable data stream processing, deployable information security, and semantically rich and efficient long-term storage. In particular, such an infrastructure cannot continue to be limited to machines and sensors, but additionally needs to encompass networked environments: production cells, edge computing, and location-independent cloud infrastructures. Finally, in light of the envisioned WWL, i.e., the interconnection of production sites, the technical infrastructure must be advanced to support secure and privacy-preserving industrial collaboration. To evolve today’s production sites and lay the infrastructural foundation for the IoP, we identify five broad streams of research: (1) adapting data and stream processing to heterogeneous data from distributed sources, (2) ensuring data interoperability between systems and production sites, (3) exchanging and sharing data with different stakeholders, (4) network security approaches addressing the risks of increasing interconnectivity, and (5) security architectures to enable secure and privacy-preserving industrial collaboration. With our research, we evolve the underlying infrastructure from isolated, sparsely networked production sites toward an architecture that supports high-level applications and sophisticated digital shadows while facilitating the transition toward a WWL.
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Pennekamp, Jan, Anastasiia Belova, Thomas Bergs, Matthias Bodenbenner, Andreas Bührig-Polaczek, Markus Dahlmanns, Ike Kunze et al. „Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead“. In Internet of Production, 35–60. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-44497-5_2.
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AbstractThe Internet of Production (IoP) leverages concepts such as digital shadows, data lakes, and a World Wide Lab (WWL) to advance today’s production. Consequently, it requires a technical infrastructure that can support the agile deployment of these concepts and corresponding high-level applications, which, e.g., demand the processing of massive data in motion and at rest. As such, key research aspects are the support for low-latency control loops, concepts on scalable data stream processing, deployable information security, and semantically rich and efficient long-term storage. In particular, such an infrastructure cannot continue to be limited to machines and sensors, but additionally needs to encompass networked environments: production cells, edge computing, and location-independent cloud infrastructures. Finally, in light of the envisioned WWL, i.e., the interconnection of production sites, the technical infrastructure must be advanced to support secure and privacy-preserving industrial collaboration. To evolve today’s production sites and lay the infrastructural foundation for the IoP, we identify five broad streams of research: (1) adapting data and stream processing to heterogeneous data from distributed sources, (2) ensuring data interoperability between systems and production sites, (3) exchanging and sharing data with different stakeholders, (4) network security approaches addressing the risks of increasing interconnectivity, and (5) security architectures to enable secure and privacy-preserving industrial collaboration. With our research, we evolve the underlying infrastructure from isolated, sparsely networked production sites toward an architecture that supports high-level applications and sophisticated digital shadows while facilitating the transition toward a WWL.
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Ballestar, María Teresa, María Teresa Freire-Rubio und Arturo Ortigosa-Blanch. „Tutoring and Its Effects on Academic Achievement: A Policy Evaluation with Machine Learning Methods“. In Addressing Inequities in Modern Educational Assessment, 53–70. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-45802-6_4.
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Li, Qiang, Dongdong Zhang, Mu Li, Tong Xiao und Jingbo Zhu. „Better Addressing Word Deletion for Statistical Machine Translation“. In Natural Language Understanding and Intelligent Applications, 91–102. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50496-4_8.
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Satheesh, Meganathan Kumar, und Korupalli V. Rajesh Kumar. „Addressing the Utilization of Popular Regression Models in Business Applications“. In Machine Learning for Business Analytics, 29–43. New York: Productivity Press, 2022. http://dx.doi.org/10.4324/9781003206316-3.
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Bach, Nicolas, Andrew Melnik, Federico Rosetto und Helge Ritter. „An Error-Based Addressing Architecture for Dynamic Model Learning“. In Machine Learning, Optimization, and Data Science, 617–30. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64580-9_51.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Addressing Machines"
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Navas Molina, Jose Antonio, und Shivakant Mishra. „Addressing memory exhaustion failures in Virtual Machines in a cloud environment“. In 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2013. http://dx.doi.org/10.1109/dsn.2013.6575330.
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Islam, Asif, und Nachiket Kapre. „LegUp-NoC: High-Level Synthesis of Loops with Indirect Addressing“. In 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2018. http://dx.doi.org/10.1109/fccm.2018.00027.
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Mellor, Philip H., Callum Heath, Suzanne Collins, Nick Simpson und Ian Bond. „Addressing the Challenges of Lightweight Aircraft Electric Propulsion through Electrical Machines with Air-gap Windings“. In 2019 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2019. http://dx.doi.org/10.1109/ecce.2019.8911841.
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Caulfield, H. John. „Calculating machines based on content addressable memories“. In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.wt1.
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A variety of calculating machines including Turing machines (TMs) and cellular array processors (CAPs) appear to need optical content addressable memories (CAMs) for high speed and/or high flexibility. In all cases auxiliary memories (the tape for TMs and the array for CAPs) are needed as well. Because the requirements on them are not severe, these auxiliary memories need not be optical. This use of optical CAMs permits extremely long and complex operations to be carried out quite rapidly. In the simplest scheme binary input maps are converted into new binary input maps through CAMs. The particular program is fixed. Data input is by pulsed light addressing of acoustooptic cells with a data flow pattern chosen to minimize temporal complexity. In future systems, flexible, more complex or even adaptive CAMs will prove useful.
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Kneissler, Andreas, und Stefan Oelbracht. „Addressing the Practical Challenges of Implementing Blockchain in Engineering and Manufacturing“. In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004313.
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This paper describes the state of the art and the potential for realized application of blockchain technology in the machinery and equipment industry for secure exchange of process and product data between the supplier and the customer.Since its introduction and increasing popularity in the financial industry, Blockchain has become a transformative technology with significant impact on various industries. It has attracted significant attention and interest in sectors such as supply chain management, insurance, and agriculture. The use of blockchain in manufacturing and engineering is even more novel.By providing a decentralized and immutable ledger, blockchains can enable secure and transparent transactions, streamlined supply chain management, improved traceability of products, and greater trust in the integrity and validity of data between participants in a network.Aside from cryptocurrencies, interest, understanding, use, and implementation of blockchain technology are still at an early stage. Consequently, blockchain technologies are still encountering various problems and limitations. These include excessive energy consumption for computational tasks, suboptimal efficiency of consensus mechanisms, significant computational overhead in network systems, and low transaction throughput rates. The significant latency in transactions can lead to uncertainty among participants. In addition, blockchain is not suitable for current engineering and manufacturing applications due to its high energy requirements and the need for high computational power, large storage space, and high CPU power for the consensus algorithms.In reviewing the existing literature, it becomes evident that while a significant amount of research has been conducted on blockchain applications in various fields, the focus has been primarily on descriptive and theoretical proposals. Despite the increasing focus on research and the growing number of published papers on blockchain applications outside of cryptocurrencies, there is a distinct lack of empirical studies that provide an accurate analysis of the technology's effectiveness in practice.While new frameworks are being proposed that attempt to address these issues and limitations, their validation and testing in real-world operational environments is limited.The limited number of cases in the literature addressing the operational implementation of blockchain-based approaches indicates that significant practical challenges, such as the speed of communication between machines, must be resolved before the technology can gain widespread adoption beyond the cryptocurrency space.With this in mind, it is critical to test blockchain applications in some real industrial environments to determine their viability and address any practical shortcomings. Identifying and addressing these challenges will be necessary to improve the effectiveness and efficiency of Blockchain-based systems.In addition, it is imperative to investigate whether blockchain approaches are suitable for manufacturing and engineering applications. This can be achieved by exploring potential hybrid systems that incorporate proven data management approaches, especially for simple components (e.g., temperature sensors). The aim is to ensure optimal performance and minimize potential risks and unnecessary complexity without sacrificing the positive aspects such as anti-counterfeiting and barrier-free data availability.
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Honegger, A., A. Tulsian, E. Creighton, A. Phillip und D. Mukhopadhyay. „Development of a Small 5-Axis Micro-Milling Center for Parts Up to 100 mm in Diameter“. In ASME 2010 International Manufacturing Science and Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/msec2010-34221.
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In this paper, the development of a small 5-axis machine tool (the Microlution 5100-S) for production-level micro-machining applications is presented. This machine is based on the concept that small parts should be manufactured on specially designed small machines, a.k.a. micro-machine tools (mMTs). The performance goals for this development effort were established as follows: ±1 micron linear positioning accuracy, capability to perform simultaneous 5-axis machining on parts up to 100 mm in diameter, maximum acceleration of 2g and a high-speed spindle with a maximum speed between 50,000 and 70,000 RPM. Additionally, this development is directed at addressing the needs of high-volume micro-machining applications. Hence, the machine required the development of a reliable, high-capacity tool-changer and compatibility with many productivity enhancing equipments viz. palette transfer robots and chip conveyors. Lastly the advantages of using this machine for miniature part production are presented with respect to savings in energy, increase in productivity and lowering of floor-space requirements.
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Taylor, Frank, S. Jayaram, U. Jayaram und Tatsuki Mitsui. „Functionality to Facilitate Assembly of Heavy Machines in a Virtual Environment“. In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/cie-14590.
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Abstract This paper describes a methodology for simulating the virtual assembly of heavy machinery. Heavy machinery or parts are described in this paper as objects too heavy to safely lift with two hands. Virtual assembly of heavy machinery poses special problems that are not seen in assemblies composed of parts easily manipulated with human hands. This paper identifies some of the difficulties associated with real-time virtual assembly of heavy machinery, and proposes methods for addressing these problems. We describe a method for reorganizing the assembly tree outside of traditional CAD systems to better simulate assemblies with numerous parts. This allows the user to control the assembly sequences, which are simulated in the virtual environment without changing the assembly hierarchy of the original CAD model. This paper also proposes methods for simulation of overhead cranes and the physical modeling of crane-part interactions, providing real-time virtual manipulation of heavy objects.
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Kravchenko, Sergey, Natalia Kravchenko, Nikolay Kuleshov, Igor Laptinov, Andrey Kravchenko und Daria Panova. „Vacuum evaporating machine for liquid products based on flammable solvents“. In 23rd International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering and Information Technologies, 2024. http://dx.doi.org/10.22616/erdev.2024.23.tf197.
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In various biochemical technologies, it is necessary to isolate useful substances from solutions derived from plant or animal raw materials using flammable solvents such as ethanol, acetone, and toluene, or to concentrate these solutions. The challenge lies in ensuring that the volatile substances, which have low boiling points and are obtained after solvent removal, retain their biological activity without degradation due to high temperatures. To preserve the biological activity of these substances, solvent removal must occur at relatively low temperatures. This requirement can be met by using a vacuum drying machine equipped with a cooling system that allows precise temperature control of the drying solution. This machine substantially differs from traditional sublimation machines, particularly in its vacuum pumping equipment and the design of the vacuum chamber, which are tailored to safely dry flammable materials. Moreover, the machine control system is designed to safely manage the drying process, preemptively addressing potential risks associated with drying solutions derived from animal or plant raw materials. SIA Cryogenic and Vacuum Systems from Ventspils has developed a prototype of an industrial vacuum evaporating machine, which is detailed in this article.
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Krishnaswamy, Kailash, und Perry Y. Li. „Bondgraph Based Approach to Passive Teleoperation of a Hydraulic Backhoe“. In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-61244.
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Human operated, hydraulic actuated machines are widely used in many high-power applications. Improving productivity, safety and task quality (eg. force feedback to the operator in a teleoperated scenario) has been the focus of past research. In addressing these issues, our research proposes and experimentally demonstrates a control technique that renders a hydraulic machine (teleoperated backhoe in this case) as a two-port, co-ordinated, passive machine. The passive teleoperated backhoe is driven by a human operator at one-port and interacts with the environment at the other. It guarantees interaction stability and safety with the human / work environment as the latter are usually passive. In previous work, a passive teleoperation algorithm was proposed for multi degree of freedom teleoperation of a hydraulic backhoe approximated by its kinematic behavior. The approximation led to severe performance deterioration under certain operating conditions. In this paper, a bondgraph based passive teleoperation architecture is proposed for the non-linear dynamic modeled backhoe. Passive control is designed in two stages. In the first stage, bondgraph based system inversion ideas are used to determine a coordination control law. In the second stage, a desired locked system (desired dynamics of the coordinated teleoperator) is defined and an appropriate control law is determined to ensure the passivity property of the locked teleoperator. The proposed passive control law is experimentally verified for its bilateral energy transfer ability and performance enhancements.
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Kessler, Melanie, Oliver Antons und Julia Arlinghaus. „Designing hybrid intelligence: understanding the impact of human decision-making on AI“. In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005148.
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In many domains such as management, production and government, established control approaches struggle to address increasing complexity in a timely manner, resulting in a demand for more agile methods. Hybrid intelligence and decision support systems are useful approaches to augment human decision-making through artificial intelligence (AI). Various application of AI methods to estimate production parameters or to provide forecasts are discussed in the literature or already being implemented, however, human decision-making is still required for either deciding whether to follow specific suggestions or for monitoring their respective implementation. But human behavioral research has shown that human decision-making is rather biased than fully rational, leading to unintended consequences in the collaborative work of humans and machines. Subsequently, the research stream of hybrid intelligence has gained interest recently, aiming to study the collaboration between humans and machines. We contribute to this issue by combining a systematic literature review on AI and cognitive biases combined with practical insights from discussions with experts in order to derive first guidelines addressing the human factor in the design of AI-based decision support systems for complex production environments.
Berichte der Organisationen zum Thema "Addressing Machines"
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Baker, James E., Laurie Hobart und Matthew Mitterlsteadt. AI for Judges. Center for Security and Emerging Technology, Dezember 2021. http://dx.doi.org/10.51593/20190019.
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As artificial intelligence transforms the economy and American society, it will also transform the practice of law and the role of courts in regulating its use. What role should, will, or might judges play in addressing the use of AI? And relatedly, how will AI and machine learning impact judicial practice in federal and state courts? This report is intended to provide a framework for judges to address AI.
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Kim, Kyungmee, und Boulanin Vincent. Artificial Intelligence for Climate Security: Possibilities and Challenges. Stockholm International Peace Research Institute, Dezember 2023. http://dx.doi.org/10.55163/qdse8934.
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Recent advances in artificial intelligence (AI)—largely based on machine learning—offer possibilities for addressing climate-related security risks. AI can, for example, make disaster early-warning systems and long-term climate hazard modelling more efficient, reducing the risk that the impacts of climate change will lead to insecurity and conflict. This SIPRI Policy Report outlines the opportunities that AI presents for managing climate-related security risks. It gives examples of the use of AI in the field and delves into the problems—notably methodological and ethical—associated with the use of AI for climate security. The report concludes with recommendations for policymakers and researchers who are active in the area of climate security or who use AI for sustainability.
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Dudoit, Alain. European common data spaces: a structuring initiative that is both necessary and adaptable to Canada. CIRANO, November 2023. http://dx.doi.org/10.54932/skhp9567.
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Faced with the acceleration of the digital economy, the governance and effective sharing of data have become fundamental issues for public policy at all levels of jurisdictions and in all areas of human activity. This paper reviews the initiatives and challenges associated with data governance, with a particular focus on the European Common Data Spaces (ECDS) and their direct relevance to the Canadian context. It explores the inherent complexity of data governance, which must reconcile sector-specificities with more horizontal governance principles. In doing so, it highlights the importance of strategic and coordinated action to maximize the social and economic benefits of data. The Burgundy Report, published by CIRANO in July 2023, calls for the creation of a common data space in the Great Lakes-St. Lawrence Strategic Trade Corridor by 2030. This proposal builds in particular on three separate policy reports published in 2022 by the National Supply Chain Task Force, the Council of Ministers Responsible for Transportation and Highway Safety (COMT) and the House of Commons Standing Committee on Transportation, Infrastructure and Communities. The findings and recommendations of these reports raise fundamental questions that are central to the critical issues of governance, organizational culture, execution capacity, public and private stakeholder engagement, and data underutilization within the Canadian government machinery strained by years of delay and exacerbated by recent disruptions related to anticipated climate disasters. The creation of a common data space is envisaged as a structuring investment in Canada's essential infrastructure for intermodal transport and the supply chain. This working paper on European Common Data Spaces (ECDS) extends the synthesis and recommendations published last July 2023 by providing an operational analysis of the transformative initiative currently underway within the European Union (EU). This major policy development stems from the 2020 European Data Strategy and seeks to establish twelve common data spaces in strategic sectors, including mobility and transport. The document is divided into three main parts. The first part provides an overview of data-related public policies in Canada and the EU between 2018 and 2023. The second part focuses on the implications and lessons learned from the impact assessment supporting the adoption of data governance legislation by the European institutions. This directive establishes a regulatory framework for the creation of common data spaces in the EU. The third section discusses the current deployment of ECDSs, highlighting key milestones and ongoing processes. The paper highlights notable similarities between the EU and Canada in the identification of data issues and the formulation of public policy objectives. It also highlights differences in optimizing data sharing between jurisdictions and stakeholders. A fundamental difference between these two strategic partners is the absence of an effective and sustained pooling of resources within the Canadian intergovernmental machinery in pursuit of common objectives in the face of major shared challenges such as data accessibility and sharing. This situation is in stark contrast to the EU's groundbreaking deployment of the ECDS in pursuit of identical objectives of positioning itself as a world leader in the data economy. This lack of consideration, let alone joint action, by Canada's intergovernmental machinery to implement a common data strategy in Canada is damaging. To be effective, the Canadian response must be agile, results-oriented, and interoperable across jurisdictions. The rigorous management, responsible use, and organized sharing of data within and between jurisdictions are crucial to addressing the complex challenges and major risks facing Canada. Neither the federal nor provincial governments are currently well positioned to treat data as a shared strategic asset. The resolution of regulatory, legal, and technical obstacles to data exchange between jurisdictions and organizations cannot be achieved without the creation of a common data space. This can only be achieved by combining the necessary tools and infrastructures, and by addressing issues of trust, for example by means of common rules drawn up for this purpose. “The barriers that prevent the establishment of robust health data sharing systems are not technical, but rather fundamentally political and cultural.”
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Sheets, Colton. PR-201-154500-R01 Composite Repair Load Transfer Study. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), März 2018. http://dx.doi.org/10.55274/r0011468.
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The objective of the PRCI MATR-3-11 Composite Repair Load Transfer Study was to evaluate the effect of internal pipe pressure during installation of composite reinforcement systems. Historically, there has been little work evaluating the effect of internal pressure during installation, even though almost all composite installations on transmission pipelines are performed with internal pressure present in the pipe. The focus of this work was specifically limited to reinforcement of pipelines containing simulated corrosion anomalies. Five composite repair technologies from four composite manufacturers were evaluated in this study including: � Western Specialties Ultra-Wrap (E-glass/epoxy) � Western Specialties Composi-Sleeve (steel sleeve with E-glass overwrap) � Citadel (carbon fiber/epoxy) � Furmanite (carbon fiber/epoxy) � NRI Steel Wrap (high-modulus carbon fiber/epoxy) This study used full-scale testing to analyze the load transfer between the composite repair and pipe with internal pressure present during installation and whether this condition impacts the reinforcement provided by the composite repair system. The anomaly configuration evaluated in this study was a machined corrosion defect simulating 50% wall loss in 12.75-inch x 0.375-inch, Grade X42 pipe material. For safety, internal pressure during installation was limited to 50% SMYS (1,236 psig) for the corrosion samples. The composite repairs for the corrosion defects were installed at internal pressure levels of 0 psig, 25% SMYS (618 psig), and 50% SMYS (1,236 psig). Following repair installation, the reinforced full-scale samples were burst tested or pressure cycled to failure to evaluate the repair's performance. Results indicated that, in general, internal pressure during installation did not significantly impact the ability of the composite systems to reinforce the corrosion anomalies evaluated in this study when installed at or below 50% SMYS. Installation pressures up to 50% SMYS had no noticeable effect on the burst pressure of the corroded sample composite repairs, and the burst pressure of all repairs were equivalent to pressure levels for an unreinforced, undamaged pipe. Also, all repairs failed at approximately the same average burst pressure, regardless of installation pressure. Furthermore, installation pressures up to 50% SMYS had little or no noticeable effect on the fatigue life of reinforced corrosion samples; all sample repairs reached the target runout of 250,000 cycles. Observations from the burst testing suggested that loads from the corroded region were not transferred to the composite repair until the corroded region began to yield, regardless of the pressure at which the composite was installed (applicable for installation pressures at or below 50% SMYS and a corrosion depth of 50%). The results and findings of this study provide valuable information to the pipeline industry for addressing an issue of significant interest for many years, and one not previously addressed in a comprehensive manner via full-scale testing. An important observation from this study is that the performance of composite repairs made on corrosion defects does not appear to be appreciably reduced when internal pressures up to 50% SMYS are present during installation.
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Petit, Vincent. Road to a rapid transition to sustainable energy security in Europe. Schneider Electric Sustainability Research Institute, Oktober 2022. http://dx.doi.org/10.58284/se.sri.bcap9655.
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Decarbonization and energy security in Europe are two faces of the same coin. They are both related to the large dependency of the European Union economy on fossil fuels, which today represent around 70% of the total supply of energy. The bulk of these energy resources are imported, with Russia being the largest supplier, accounting for 40% of natural gas and 27% of oil imports. However, fossil fuels are also the primary root cause of greenhouse gas emissions, and the European Union is committed to reduce those by 55% by 2030 (versus 1990). This report is based on the landmark research from the Joint Research Center of the European Commission, the “Integrated Database of the European Energy Sector”, which for the first time mapped actual energy uses for each country within the European Union, across 17 sectors of activity, with data granularity at the level of each process step (or end-use) of each of these sectors. Our approach here has been to systematically review these process steps (or end-uses) and qualify the extent to which they could be electrified, effectively removing the demand for fossil fuels as a result. We have focused only on those process steps where technology was already widely available and for which we evaluated the switch to be relatively easy (or attractive). In other words, we estimated the impact of rapid electrification of “easy to abate” activities. The conclusion of this evaluation is that the share of electricity demand in the final energy mix could jump from around 20% today to 50%, which would drive a reduction in emissions at end-use of around 1,300 MtCO2 /y, as well as a drop in natural gas and oil supply of around 50%. As a result of such transformation, electricity demand would nearly double, with the bulk of that growth materializing in the building sector. Short-term, the challenge of addressing climate targets while providing for energy security is thus intimately connected to buildings. While such transition would certainly require major infrastructure upgrades, which may prove a roadblock to rapid deployment, we find that the combination of energy efficiency measures (notably digital) and distributed generation penetration (rooftop solar) could significantly tame the issue, and hence help accelerate the move away from fossil fuels, with energy spend savings as high as 80% across some building types; a major driver of change. Beyond this, further potential exists for electrification. Other measures on the demand-side will include deeper renovations of the industrial stock (notably in the automotive, machinery, paper, and petrochemical industries for which our current assessment may be underestimated) and further electrification of mobility (trucks). The transition of the power system away from coal (and ultimately natural gas) will then also play a key role, followed ultimately by feedstocks substitution in industry. Some of these transitions are already on the way and will likely bring further improvements. The key message, however, is that a significant opportunity revolves around buildings to both quickly decarbonize and reduce energy dependencies in Europe. Rapid transformation of the energy system may be more feasible than we think. We notably estimate that, by 2030, an ambitious and focused effort could help displace 15% to 25% of natural gas and oil supply and reduce emissions by around 500 MtCO2 /y (note that these savings would come on top of additional measures regarding energy efficiency and flexibility, which are not the object of this study). For this to happen, approximately 100 million buildings will need renovating, and a similar number of electric vehicles would need to hit the road.