Search results for: machine translation (MT)
2963 Flood-prone Urban Area Mapping Using Machine Learning, a Case Sudy of M'sila City (Algeria)
Authors: Medjadj Tarek, Ghribi Hayet
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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management
Procedia PDF Downloads 822962 The Role of Optimization and Machine Learning in e-Commerce Logistics in 2030
Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni
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Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization
Procedia PDF Downloads 2312961 Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Authors: Ioannis P. Panapakidis, Marios N. Moschakis
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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.Keywords: deregulated energy market, forecasting, machine learning, system marginal price
Procedia PDF Downloads 2052960 Volume Density of Power of Multivector Electric Machine
Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev
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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor
Procedia PDF Downloads 3272959 A Deep Learning Approach to Subsection Identification in Electronic Health Records
Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan
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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification
Procedia PDF Downloads 2052958 An Investigation of the Mystic Term on 'The Conference of the Birds' of Attar on the Basis of Van Doorslaer's Map
Authors: Saber Noie
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This research follows some objectives to consider the mystic terms as one of the main issues in translation of poems. Firstly, it is an attempt to find out what strategies have been used to find equivalents for source text mystic. Second, it is hoped that this study of the translations of the mystic terms in Attar’s poems will further address and explore the problems in translating mystic texts, proposed by other Persian poets and suggest instructional points from Davis work for translation education. In order to deal with such a breadth of work, a new conceptual tool was developed, as explained by Van Doorslaer (2007). This study shows that according to Van Doorslaer’s map, the mystic terms can be transferred to the target language (TL) with their exact content of the source language (SL) if the translator has a good choice for any term.Keywords: metaphor, mystic, mysticism, source language (SL), target language (TL)
Procedia PDF Downloads 2482957 Multi-Level Air Quality Classification in China Using Information Gain and Support Vector Machine
Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li
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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation
Procedia PDF Downloads 2292956 Intelligent Production Machine
Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan
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This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.Keywords: cutting process, sound processing, intelligent late, sound analysis
Procedia PDF Downloads 3272955 Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms
Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang
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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.Keywords: bioassay, machine learning, preprocessing, virtual screen
Procedia PDF Downloads 2642954 The Accuracy of Parkinson's Disease Diagnosis Using [123I]-FP-CIT Brain SPECT Data with Machine Learning Techniques: A Survey
Authors: Lavanya Madhuri Bollipo, K. V. Kadambari
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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)
Procedia PDF Downloads 3852953 Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks
Authors: Anne-Lena Kampen, Øivind Kure
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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN
Procedia PDF Downloads 1402952 Original and the Translated: A Comparative Evaluation of Native and Non-Native English Translations of Faiz
Authors: Anam Nawaz
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The present study is an attempt to compare the translations of Faiz’s poetry made by native and non-native translators, to determine the role of the translator in terms of preserving the cultural ethos of the original text. Peter Newmark and Katharine Reiss’s approaches to translation criticism have been used to provide a theoretical framework for the study. This study also emphasizes those cultural and semantic aspects of the original which are translated more convincingly by a native translator, and contrasting those features which the non-natives can tackle more ably. The research also highlights the linguistic sockets, ignored by the interpreters in the translation process. The analysis showed that both native and non-native translators have made an admirable effort to stay as close to the original as possible. The natives with their advantage of belonging to the same culture have excelled in preserving the original subject matter, whereas the non-native renderings have been presented in a much rhythmic and poetic manner with an excellent choice of words. Though none of the four translators has been successfully able to recreate Faiz’s magic, however V. G. Kiernan and Sarvat Rahman’s translations can be regarded as the closest to the original. Whereas V. G. Kiernan with his outstanding command over English mesmerizes the readers, Sarvat Rahman’s profound understanding of cultural ties helps establish her translations as a brilliant example of faithful re-renderings.Keywords: comparative translations, linguistic and cultural constraints, native translators, non-native translators, poetry and translation, Faiz Ahmad Faiz
Procedia PDF Downloads 2492951 The Challenges of Intercultural Transfer: The Italian Reception of Aotearoa/New Zealand Films
Authors: Martina Depentor
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While the cinematic medium contributes to bringing images of a culture to foreign audiences, Audiovisual Translation contributes to deciphering those cultural representations to those same audiences. Through Audiovisual Translation, in fact, elements permeate the reception system and contribute to forging a cultural image of the original/source system in the target/reception system. By analyzing a number of Italian critical reviews, blogs and forum posts, this paper examines the impact and reception in Italy of five of the most successful and influential New Zealand films of the last two decades - An Angel at my Table (1990), The Piano (1993), Heavenly Creatures (1994), Once Were Warriors (1994), Whale Rider (2002) - with the aim of exploring how the adaptation of New Zealand films might condition the representation of New Zealand in the Italian imaginary. The analysis seeks to identify whether a certain degree of cultural loss results from the 'translation' of these films. The films selected share common ground in that they all reveal cultural, social and historical characteristics of New Zealand, from aspects that are unique to this country and that on the surface may render it difficult to penetrate (unfamiliar landscapes, aspects of indigenous culture) to more universal themes (intimate family stories, dysfunctional relationship). They contributed to situating New Zealand on an international stage and to bringing images of the country to many audiences, the Italian one included, with little previous cultural knowledge of the social and political history of New Zealand. Differences in film types pose clearly different levels of interpretative challenges to non-New Zealander audiences, and examples from the films will show how these challenges are or are not overcome if the adaptations display misinterpretations or rendition gaps, and how the process of intercultural transfer further 'domesticates' or 'exoticises' the source culture.Keywords: audiovisual translation, cultural representation, intercultural transfer, New Zealand Films
Procedia PDF Downloads 2882950 Fundamental Research Dissension between Hot and Cold Chamber High Pressure Die Casting
Authors: Sahil Kumar, Surinder Pal, Rahul Kapoor
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This paper is focused on to define the basic difference between hot and cold chamber high pressure die casting process which is not fully defined in a research before paper which we have studied. The pressure die casting is basically defined into two types (1) Hot chamber Die Casting (2) Cold chamber Die Casting. Cold chamber die casting is used for casting alloys that require high pressure and have a high melting temperature, such as brass, aluminum, magnesium, copper based alloys and other high melting point nonferrous alloys. Hot chamber die casting is suitable for casting zinc, tin, lead, and low melting point alloys. In hot chamber die casting machine, the molten metal is an integral pan of the machine. It mainly consists of hot chamber and gooseneck type metal container made of cast iron. This machine is mainly used for low melting alloys and alloys of metals like zinc, lead etc. Metals and alloys having a high melting point and those which are having an affinity for iron cannot be cast by this machine, which could otherwise attack the shot sleeve and damage the machine.Keywords: hot chamber die casting, cold chamber die casting, metals and alloys, casting technology
Procedia PDF Downloads 6082949 Spatial Setting in Translation: A Comparative Evaluation of translations from Pre-Islamic Poetry
Authors: Raja Lahiani
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This study is concerned with scrutinising translations into English and French of references to locations in the desert of pre-Islamic Arabia. These references are used in the Source Text (ST) within a poetic image. Reference is made to the names of three different mountains in Arabia, namely Qatan, Sitar, and Yadhbul. As these mountains are referred to in the context of the poet’s description of the density and expansion of the clouds, it is crucial to know that while Sitar and Yadhbul are close to each other, Qatan is far away from them. This distance was functional for the poet to describe the expansion of the clouds. This reflects the spacious place (desert) he handled, and the fact that it was possible for him to physically see what he described. The purpose of this image is for the poet to communicate the vastness of the space he managed to see as he was in a moment of contemplation. Thus, knowledge of this characteristic about the setting is capital for the receiver to understand the communicative function of the verse. A corpus of eighteen translations is gathered. These vary between verse and prose renderings. The methodology adopted in this research work is comparative. Comparison is conducted at both the synchronic and diachronic levels; every translation shall be compared to the ST and then to previous translations. The comparative work will prove at the end that the translators who target historical facts do not necessarily succeed in preserving the image of the ST. It also proves that the more recent the translation is, the deeper the translator’s awareness is the link between imagery, setting, and point of view. Since the late eighteenth century and until nowadays, pre-Islamic poetry has been translated into Western languages. Translators differ as to motives, sources, priorities and intellectual backgrounds. A translator's skopoi undoubtedly affect the way s/he handles aspects of the ST. When it comes to culture-specific aspects and details related to setting, the problem is even more complex. Setting is a very important factor that reveals a great deal of the culture of pre-Islamic Arabia as this is remote in place, historical framework and literary tradition from its translators. History is present in pre-Islamic poetry, which justifies the important literature that has been written to extract information and data from it. These are imbedded not only by signalling given facts, events, and meditations but also by means of references to specific locations and landmarks that used to exist at the time. Spatial setting is an integral part of a literary text as it places it within its historical context. The importance of the translator’s awareness of spatial anthropological data before indulging in the process of translation is tested. This is also crucial in measuring the effect of setting loss and setting gain in translation. The findings of this research would ultimately evaluate the extent to which a comparative methodology is reliable in investigating the role of spatial setting awareness in translation.Keywords: historical context, translation, comparative literature, spatial setting
Procedia PDF Downloads 2422948 Spectral Clustering for Manufacturing Cell Formation
Authors: Yessica Nataliani, Miin-Shen Yang
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Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.Keywords: group technology, cell formation, spectral clustering, grouping efficiency
Procedia PDF Downloads 3932947 Design and Performance Analysis of a Hydro-Power Rim-Driven Superconducting Synchronous Generator
Authors: A. Hassannia, S. Ramezani
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The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.Keywords: coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator
Procedia PDF Downloads 1622946 Cyclone Driven Variation of Chlorophyll-a Concentration in Bay of Bengal
Authors: Nowshin Nabila Siddique, S. M. Mustafizur Rahman
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There is evidence of cyclonic events in Bay of Bengal (BoB) throughout the year. These cyclones cause a variety of fluctuations along its track including the is the influence in Chlorophyll-a (chl-a) concentration. The main purpose of this paper is to justify this variation pattern. Six Tropical Cyclones (TC) are studied using observational method. The result suggests that there is a noticeable change in productivity after a cyclone passes, when the pre cyclonic and post cyclonic condition is observed. In case of Cyclone Amphan, it shows 1.79 mg/m3 of chlorophyll-a concentration increase after a week of cyclonic occurrence. This change is affected by several attributes such as translation speed, intensity and Ocean Pre-condition, specifically Mixed Layer Depth (MLD). Translation Speed and MLD shows a strong negative correlation with the induced chlorophyll concentration. Whereas the effect of the intensity on a cyclone is not that prominent. It is also found that the period of starting an induction is not same for all cyclone such as in case of Cyclone Amphan, the changes started to occur after one day however for Cyclone Sidr and Cyclone Mora it started after three days. Furthermore, a slightly increase in overall productivity is also observed after a cyclone. In the case of Cyclone Amphan, Hudhud, Phailin it shows a rise up to 0.12 mg/m3 in productivity which decreases gradually taking around the period of two months. On a whole this paper signifies the changes in chlorophyll concentration caused by numerous cyclones and its different characteristics that regulates these changes.Keywords: tropical cyclone, chlorophyll-a concentration, mixed layer depth, translation speed
Procedia PDF Downloads 782945 Automatic Generating CNC-Code for Milling Machine
Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert
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G-code is the main factor in computer numerical control (CNC) machine for controlling the tool-paths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.Keywords: geometric shapes, milling operation, minor changes, CNC Machine, G-code, cutting parameters
Procedia PDF Downloads 3432944 An Analysis of Classification of Imbalanced Datasets by Using Synthetic Minority Over-Sampling Technique
Authors: Ghada A. Alfattni
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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates.Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour
Procedia PDF Downloads 3352943 Use of Fractal Geometry in Machine Learning
Authors: Fuad M. Alkoot
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The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.Keywords: fractal geometry, machine learning, classifier, fractal dimension
Procedia PDF Downloads 2032942 Teaching English to Engineers: Between English Language Teaching and Psychology
Authors: Irina-Ana Drobot
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Teaching English to Engineers is part of English for Specific Purposes, a domain which is under the attention of English students especially under the current conditions of finding jobs and establishing partnerships outside Romania. The paper will analyse the existing textbooks together with the teaching strategies they adopt. Teaching English to Engineering students can intersect with domains such as psychology and cultural studies in order to teach them efficiently. Textbooks for students of ESP, ranging from those at the Faculty of Economics to those at the Faculty of Engineers, have shifted away from using specialized vocabulary, drills for grammar and reading comprehension questions and toward communicative methods and the practical use of language. At present, in Romania, grammar is neglected in favour of communicative methods. The current interest in translation studies may indicate a return to this type of method, since only translation specialists can distinguish among specialized terms and determine which are most suitable in a translation. Engineers are currently encouraged to learn English in order to do their own translations in their own field. This paper will analyse the issue of the extent to which it is useful to teach Engineering students to do translations in their field using cognitive psychology applied to language teaching, including issues such as motivation and social psychology. Teaching general English to engineering students can result in lack of interest, but they can be motivated by practical aspects which will help them in their field. This is why this paper needs to take into account an interdisciplinary approach to teaching English to Engineers.Keywords: cognition, ESP, motivation, psychology
Procedia PDF Downloads 2552941 General Architecture for Automation of Machine Learning Practices
Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain
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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler
Procedia PDF Downloads 452940 Laundering vs. Blanqueo: Translating Financial Crime Metaphors From English to Spanish
Authors: Stephen Gerome
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This study examines the translation and use of metaphors in the realm of public safety discourse and intends to shed light on a continuing problem in cross-cultural communication. Metaphors can cause problems not only within languages but also in interlingual communication. The use and misuse of metaphors may hinder the ability to adequately communicate prevention efforts and, in some cases, facilitate and allow financial crime to go undetected. The use of lexicalized metaphors in communications by political entities, journalists, and legal agents in communications regarding law, policy making, compliance monitoring and enforcement as well as in adjudication can have negative consequences if misconstrued. This study provides examples of metaphor usage in published documents in a corpus linguistic study that compares the use of lexicalized metaphors in this discourse to shed light on possible unexpected consequences as well as counterproductive ones.Keywords: translation, legal, corpus linguistics, financial
Procedia PDF Downloads 1052939 Machine Installation and Maintenance Management
Authors: Mohammed Benmostefa
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In the industrial production of large series or even medium series, there are vibration problems. In continuous operations, technical devices result in vibrations in solid bodies and machine components, which generate solid noise and/or airborne noise. This is because vibrations are the mechanical oscillations of an object near its equilibrium point. In response to the problems resulting from these vibrations, a number of remedial acts and solutions have been put forward. These include insulation of machines, insulation of concrete masses, insulation under screeds, insulation of sensitive equipment, point insulation of machines, linear insulation of machines, full surface insulation of machines, and the like. Following this, the researcher sought not only to raise awareness on the possibility of lowering the vibration frequency in industrial machines but also to stress the significance of procedures involving the pre-installation process of machinery, namely, setting appropriate installation and start-up methods of the machine, allocating and updating imprint folders to each machine, and scheduling maintenance of each machine all year round to have reliable equipment, gain cost reduction and maintenance efficiency to eventually ensure the overall economic performance of the company.Keywords: maintenance, vibration, efficiency, production, machinery
Procedia PDF Downloads 692938 The Cultural and Semantic Danger of English Transparent Words Translated from English into Arabic
Authors: Abdullah Khuwaileh
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While teaching and translating vocabulary is no longer a neglected area in ELT in general and in translation in particular, the psychology of its acquisition has been a neglected area. Our paper aims at exploring some of the learning and translating conditions under which vocabulary is acquired and translated properly. To achieve this objective, two teaching methods (experiments) were applied on 4 translators to measure their acquisition of a number of transparent vocabulary items. Some of these items were knowingly chosen from 'deceptively transparent words'. All the data, sample, etc., were taken from Jordan University of Science and Technology (JUST) and Yarmouk University, where the researcher is employed. The study showed that translators might translate transparent words inaccurately, particularly if these words are uncontextualised. It was also shown that the morphological structures of words may lead translators or even EFL learners to misinterpretations of meaning.Keywords: english, transparent, word, processing, translation
Procedia PDF Downloads 662937 Inferring Human Mobility in India Using Machine Learning
Authors: Asra Yousuf, Ajaykumar Tannirkulum
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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.Keywords: development, migration, internal migration, machine learning, prediction
Procedia PDF Downloads 2592936 Comparative Analysis of Hybrid and Non-hybrid Cooled 185 KW High-Speed Permanent Magnet Synchronous Machine for Air Suspension Blower
Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya
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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network
Procedia PDF Downloads 2212935 The Condition Testing of Damaged Plates Using Acoustic Features and Machine Learning
Authors: Kyle Saltmarsh
Abstract:
Acoustic testing possesses many benefits due to its non-destructive nature and practicality. There hence exists many scenarios in which using acoustic testing for condition testing shows powerful feasibility. A wealth of information is contained within the acoustic and vibration characteristics of structures, allowing the development meaningful features for the classification of their respective condition. In this paper, methods, results, and discussions are presented on the use of non-destructive acoustic testing coupled with acoustic feature extraction and machine learning techniques for the condition testing of manufactured circular steel plates subjected to varied levels of damage.Keywords: plates, deformation, acoustic features, machine learning
Procedia PDF Downloads 3272934 Design of a Customized Freshly-Made Fruit Salad and Juices Vending Machine
Authors: María Laura Guevara Campos
Abstract:
The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.Keywords: design, design methodology, mechatronics systems, vending machines
Procedia PDF Downloads 127