scholarly journals Method for a cloud based remaining-service-life-prediction for vehicle-gearboxes based on big-data-analysis and machine learning

2020 ◽  
Vol 84 (4) ◽  
pp. 305-314
Author(s):  
Daniel Vietze ◽  
Michael Hein ◽  
Karsten Stahl
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Service Life ◽  
Operating Time ◽  
The Other ◽  
Learning Approaches ◽  
State Of Health ◽  
Remaining Service Life ◽  
Other Hand ◽  
The One

AbstractMost vehicle-gearboxes operating today are designed for a limited service-life. On the one hand, this creates significant potential for decreasing cost and mass as well as reduction of the carbon-footprint. On the other hand, this causes a rising risk of failure with increasing operating time of the machine. Especially if a failure can result in a high economic loss, this fact creates a conflict of goals. On the one hand, the machine should only be maintained or replaced when necessary and, on the other hand, the probability of a failure increases with longer operating times. Therefore, a method is desirable, making it possible to predict the remaining service-life and state of health with as little effort as possible.Centerpiece of gearboxes are the gears. A failure of these components usually causes the whole gearbox to fail. The fatigue life analysis deals with the dimensioning of gears according to the expected loads and the required service-life. Unfortunately, there is very little possibility to validate the technical design during operation, today. Hence, the goal of this paper is to present a method, enabling the prediction of the remaining-service-life and state-of-health of gears during operation. Within this method big-data and machine-learning approaches are used. The method is designed in a way, enabling an easy transfer to other machine elements and kinds of machinery.

scholarly journals On Achieving and Evaluating Language-Independence in NLP

2011 ◽  
Vol 6 ◽  
Author(s):  
Emily M. Bender
Keyword(s):  
Machine Learning ◽  
Computational Linguistics ◽  
Position Paper ◽  
The Other ◽  
Learning Approaches ◽  
Important Type ◽  
Other Hand ◽  
The One ◽  
Modern Machine

Language independence is commonly presented as one of the advantages of modern, machine-learning approaches to NLP, and it is an important type of scalability. In this position paper, I critically review the widespread approaches to achieving and evaluating language independence in the field of computational linguistics and argue that, on the one hand, we are not truly evaluating language independence with any systematicity and on the other hand, that truly language-independent technology requires more linguistic sophistication than is the norm.

scholarly journals Bachelor Thesis Analytics: Using Machine Learning to Predict Dropout and Identify Performance Factors

2019 ◽  
Vol 1 (1) ◽  
pp. 116 ◽  
Author(s):  
Jalal Nouri ◽  
Ken Larsson ◽  
Mohammed Saqr
Keyword(s):  
Higher Education ◽  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
The Other ◽  
Data Systems ◽  
Academic Institutions ◽  
Other Hand ◽  
Desirable Outcome ◽  
The One

<p class="0abstractCxSpLast">The bachelor thesis is commonly a necessary last step towards the first graduation in higher education and constitutes a central key to both further studies in higher education and employment that requires higher education degrees. Thus, completion of the thesis is a desirable outcome for individual students, academic institutions and society, and non-completion is a significant cost. Unfortunately, many academic institutions around the world experience that many thesis projects are not completed and that students struggle with the thesis process. This paper addresses this issue with the aim to, on the one hand, identify and explain why thesis projects are completed or not, and on the other hand, to predict non-completion and completion of thesis projects using machine learning algorithms. The sample for this study consisted of bachelor students’ thesis projects (n=2436) that have been started between 2010 and 2017. Data were extracted from two different data systems used to record data about thesis projects. From these systems, thesis project data were collected including variables related to both students and supervisors. Traditional statistical analysis (correlation tests, t-tests and factor analysis) was conducted in order to identify factors that influence non-completion and completion of thesis projects and several machine learning algorithms were applied in order to create a model that predicts completion and non-completion. When taking all the analysis mentioned above into account, it can be concluded with confidence that supervisors’ ability and experience play a significant role in determining the success of thesis projects, which, on the one hand, corroborates previous research. On the other hand, this study extends previous research by pointing out additional specific factors, such as the time supervisors take to complete thesis projects and the ratio of previously unfinished thesis projects. It can also be concluded that the academic title of the supervisor, which was one of the variables studied, did not constitute a factor for completing thesis projects. One of the more novel contributions of this study stems from the application of machine learning algorithms that were used in order to – reasonably accurately – predict thesis completion/non-completion. Such predictive models offer the opportunity to support a more optimal matching of students and supervisors.</p>

scholarly journals A Critical Review of Online Battery Remaining Useful Lifetime Prediction Methods

2021 ◽  
Vol 7 ◽  
Author(s):  
Shunli Wang ◽  
Siyu Jin ◽  
Dan Deng ◽  
Carlos Fernandez
Keyword(s):  
Machine Learning ◽  
Service Life ◽  
Lithium Ion Batteries ◽  
Adaptive Filtering ◽  
Lithium Ion ◽  
The Other ◽  
Daily Lives ◽  
Remaining Service Life ◽  
Average Accuracy ◽  
Useful Lifetime

Lithium-ion batteries play an important role in our daily lives. The prediction of the remaining service life of lithium-ion batteries has become an important issue. This article reviews the methods for predicting the remaining service life of lithium-ion batteries from three aspects: machine learning, adaptive filtering, and random processes. The purpose of this study is to review, classify and compare different methods proposed in the literature to predict the remaining service life of lithium-ion batteries. This article first summarizes and classifies various methods for predicting the remaining service life of lithium-ion batteries that have been proposed in recent years. On this basis, by selecting specific criteria to evaluate and compare the accuracy of different models, find the most suitable method. Finally, summarize the development of various methods. According to the research in this article, the average accuracy of machine learning is 32.02% higher than the average of the other two methods, and the prediction cycle is 9.87% shorter than the average of the other two methods.

scholarly journals RGen: Data Generator for Benchmarking Big Data Workloads

2021 ◽  
Vol 7 (1) ◽  
pp. 13
Author(s):  
Rubén Pérez-Jove ◽  
Roberto R. Expósito ◽  
Juan Touriño
Keyword(s):  
Big Data ◽  
Experimental Evaluation ◽  
The Other ◽  
Text Generation ◽  
Other Hand ◽  
Parallel Data ◽  
Data Generator ◽  
The One ◽  
Graph Generation

This paper presents RGen, a parallel data generator for benchmarking Big Data workloads, which integrates existing features and new functionalities in a standalone tool. The main functionalities developed in this work were the generation of text and graphs that meet the characteristics defined by the 4 Vs of Big Data. On the one hand, the LDA model has been used for text generation, which extracts topics or themes covered in a series of documents. On the other hand, graph generation is based on the Kronecker model. The experimental evaluation carried out on a 16-node cluster has shown that RGen provides very good weak and strong scalability results. RGen is publicly available to download at https://github.com/rubenperez98/RGen, accessed on 30 September 2021.

A Chronicle of Infant Development and Characteristics

1893 ◽  
Vol 39 (167) ◽  
pp. 498-505 ◽  
Author(s):  
Wr. G. Simpson
Keyword(s):  
Infant Development ◽  
Apparent Size ◽  
The Other ◽  
State Of Health ◽  
Other Hand ◽  
The One ◽  
Bright Blue ◽  
Apparently Healthy

July 15th.—The following differences between James and Odo were noted in the first few months of the latter's existence:—James's eyes from the first were noticeably wide open, and seemed to look. They seemed much larger than Odo's. Now they are soft and languid. James was somewhat delicate during infancy, but grew out of it; stomach easily deranged. Softness of eyes in some measure due to very long lashes; but I find comparative brightness or languor of eyes a sure guide to his state of health. Odo's eyes have steadily grown in apparent size, because (the converse from James) the older he has grown the wider he has opened them. They are now wide, round, and bright (blue). James has very large pupils; Odo not. Odo apparently healthy, can partially raise himself up; has cut thirteenth tooth; has a placid temperament; does not cry much, i.e., will lie awake for long periods, which James never would do; sleeps all night for most part, which James seldom did. In short, thus early the one shows an excitable, the other a placid temper. Odo objects to being taken by a stranger, although he very soon gets over his misgivings. At this age James showed no distrust of strangers. Odo has a distinct manner to the three persons he knows best—nurse, mother, and father. He coos and smiles to mother when she comes to take him. He only smiles to father. Smiles more but talks less than James did at same age. By talking I mean saying “coo,” “ug-gug, and the expression called “crowing” Cries at once on being scolded. James did not understand a scold at same age. Odo always tries to seize father's moustache when taken by him. In the case of women it is the hair he goes for in preference to anything. Odo makes use of smiles at five months old, and used them unconsciously at four months, which James (see notes on him) did not do till his seventh month. On the other hand, Odo uses his hands only to grasp things, or at most to put them to his mouth. At the same age James always put them to his mouth and could play with them, that is, pull them about.

scholarly journals Machine Learning Approach for the Classification of Demonstrative Pronouns for Indirect Anaphora in Hindi News Items

2011 ◽  
Vol 95 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Kamlesh Dutta ◽  
Saroj Kaushik ◽  
Nupur Prakash
Keyword(s):  
Machine Learning ◽  
Noun Phrase ◽  
The Other ◽  
Learning Approach ◽  
Learning Approaches ◽  
Demonstrative Pronoun ◽  
Other Hand ◽  
Machine Learning Approach ◽  
Demonstrative Pronouns

Machine Learning Approach for the Classification of Demonstrative Pronouns for Indirect Anaphora in Hindi News Items In this paper, we present machine learning approach for the classification indirect anaphora in Hindi corpus. The direct anaphora is able to find the noun phrase antecedent within a sentence or across few sentences. On the other hand indirect anaphora does not have explicit referent in the discourse. We suggest looking for certain patterns following the indirect anaphor and marking demonstrative pronoun as directly or indirectly anaphoric accordingly. Our focus of study is pronouns without noun phrase antecedent. We analyzed 177 news items having 1334 sentences, 780 demonstrative pronouns of which 97 (12.44 %) were indirectly anaphoric. The experiment with machine learning approaches for the classification of these pronouns based on the semantic cue provided by the collocation patterns following the pronoun is also carried out.

scholarly journals Designing Image Based Captcha using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 3678-3682
Author(s):  
Piyush Sable
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Computer Networks ◽  
The Other ◽  
Learning Approaches ◽  
Semantic Data ◽  
Other Hand ◽  
Learning Techniques ◽  
The Creation

Captchas, or Completely Automated Public Turing Tests to Tell Computers and Humans Apart, were created in response to programmers' ability to breach computer networks via computer attack programmes and bots. Because of its ease of development and use, the Text Captcha is the most well-known Captcha scheme. Hackers and programmers, on the other hand, have weakened the assumed security of Captchas, leaving websites vulnerable to assault. Text Captchas are still widely used since it is assumed that the attack speeds are moderate, typically two to five seconds for each image, and that this is not considered a significant concern. Style Area Captcha (SACaptcha) is a revolutionary image-based Captcha suggested in this paper, which relies on semantic data comprehension, pixel-level segmentation, and deep learning approaches. The suggested SACaptcha highlights the creation of image-based Captchas utilising deep learning techniques for boosting the security purpose, demonstrating that text Captchas are no longer secure.

Stories and the Self

2020 ◽  
Vol 32 (2) ◽  
pp. 47-58 ◽  
Author(s):  
Stefan Krause ◽  
Markus Appel
Keyword(s):  
Meta Analysis ◽  
The Self ◽  
The Other ◽  
Lower Degree ◽  
Contrast Effects ◽  
Self Perception ◽  
Self Perceptions ◽  
Other Hand ◽  
The One ◽  
Implicit And Explicit

Abstract. Two experiments examined the influence of stories on recipients’ self-perceptions. Extending prior theory and research, our focus was on assimilation effects (i.e., changes in self-perception in line with a protagonist’s traits) as well as on contrast effects (i.e., changes in self-perception in contrast to a protagonist’s traits). In Experiment 1 ( N = 113), implicit and explicit conscientiousness were assessed after participants read a story about either a diligent or a negligent student. Moderation analyses showed that highly transported participants and participants with lower counterarguing scores assimilate the depicted traits of a story protagonist, as indicated by explicit, self-reported conscientiousness ratings. Participants, who were more critical toward a story (i.e., higher counterarguing) and with a lower degree of transportation, showed contrast effects. In Experiment 2 ( N = 103), we manipulated transportation and counterarguing, but we could not identify an effect on participants’ self-ascribed level of conscientiousness. A mini meta-analysis across both experiments revealed significant positive overall associations between transportation and counterarguing on the one hand and story-consistent self-reported conscientiousness on the other hand.

Radioimmunotherapy for treatment of acute myeloid leukaemia and myelodysplastic syndrome

2005 ◽  
Vol 44 (03) ◽  
pp. 107-117
Author(s):  
R. G. Meyer ◽  
W. Herr ◽  
A. Helisch ◽  
P. Bartenstein ◽  
I. Buchmann
Keyword(s):  
Acute Myeloid Leukaemia ◽  
Myeloid Leukaemia ◽  
Primary Tumour ◽  
The Other ◽  
Haematopoietic Stem Cell ◽  
Other Hand ◽  
Primary Reduction ◽  
The One ◽  
Acute Myeloid

SummaryThe prognosis of patients with acute myeloid leukaemia (AML) has improved considerably by introduction of aggressive consolidation chemotherapy and haematopoietic stem cell transplantation (SCT). Nevertheless, only 20-30% of patients with AML achieve long-term diseasefree survival after SCT. The most common cause of treatment failure is relapse. Additionally, mortality rates are significantly increased by therapy-related causes such as toxicity of chemotherapy and complications of SCT. Including radioimmunotherapies in the treatment of AML and myelodyplastic syndrome (MDS) allows for the achievement of a pronounced antileukaemic effect for the reduction of relapse rates on the one hand. On the other hand, no increase of acute toxicity and later complications should be induced. These effects are important for the primary reduction of tumour cells as well as for the myeloablative conditioning before SCT.This paper provides a systematic and critical review of the currently used radionuclides and immunoconjugates for the treatment of AML and MDS and summarizes the literature on primary tumour cell reductive radioimmunotherapies on the one hand and conditioning radioimmunotherapies before SCT on the other hand.

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