Search results for: post-editing machine translation output

Authors: Nor Ruba’Yah Binti Abd Rahim, Norsyahidah Binti Jaafar

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Translating Malay idiomatic expressions into other languages presents unique challenges due to the deep cultural nuances and linguistic intricacies embedded within these expressions. This study examined these challenges through a two-pronged methodology: a comparative analysis using survey questionnaires and a quiz administered to 50 semester 6 students who are taking Translation 1 course, and in-depth interviews with their lecturers. The survey aimed to capture students’ experiences and difficulties in translating selected Malay idioms into English, highlighting common errors and misunderstandings. Complementing this, interviews with lecturers provided expert insights into the nuances of these expressions and effective translation strategies. The findings revealed that literal translations often fail to convey the intended meanings, underscoring the importance of cultural competence and contextual awareness. The study also identified key factors that contribute to successful translations, such as the translator’s familiarity with both source and target cultures and their ability to adapt expressions creatively. This research contributed to the field of translation studies by offering practical recommendations for improving the translation of idiomatic expressions, thereby enhancing cross-cultural communication. The insights gained from this study are valuable for translators, educators, and students, emphasizing the need for a nuanced approach that respects the cultural richness of the source language while ensuring clarity in the target language.

Keywords: idiomatic expressions, cultural competence, translation strategies, cross-cultural communication, students’ difficulties

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Authors: Bahia Braktia, Ahlem Ghamri

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Years ago, faculties and administrators realized that students entering college were not prepared for the academic sphere; however, as a type of collaborative learning, peer-review gave students a social context in which they could learn more efficiently. Peer-review has proven its effectiveness in higher education. Numerous studies have been conducted on peer review and its effects on the quality of students’ writing, and several publications recommended peer-review as part of the feedback process. Student writers showed a tendency towards making significant meaning-level revisions and surface-level revisions. Last but not least, studies reported that peer-review helps students develop their self-assessment skills as well as critical thinking. The use of peer-review has become well known and widely adopted to the L2 classroom environment. However, little is known about peer review on translation students. The purpose of this study was to investigate the students' perspective on peer-review, and whether this method affected the quality of their translation. A mixed method design was adopted. Students were requested to translate two texts from Arabic into English, and they gave and received structured feedback to their classmates' translations. A survey was administered, followed by semi-structured interviews, to examine the students' attitudes toward peer-review. The results of the study showed that peer-review was considered a good proofreading method for most students. The students also showed a positive attitude toward it, and they reported that they benefited from the interaction with their peers. The findings implied that the inclusion of peer-review can be an effective pedagogical practice for teaching translation and writing to foreign language learners.

Keywords: language teaching, feedback, peer-review, translation

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Authors: Lopamudra Malek

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Bangladesh continues a compacted bilateral relationship with Japan since 1971, but the seed of this vital relationship had been sown much earlier in 1863 when MadhushudhonMukhapaddhay translated Commodore Mathew’s book, and the seed was nourished and nurtured by Rabindranath and other writers by translating Japanese literature in Bengali. Sano Jinnotsuke translated Rabindranath’s novel ‘Gora’ in 1924. Concentrating on formal literary translation, Jyotirmoy Mukhopadhyay, Jalal Ahmed continued to translate important novels, short poems, and short stories as well. Kyoko Niwa - GouriAiyub and Monjurul Huq and Swandip Tagore had translated one of the master pieces of Matsuo Basho and 万葉集. Gita A. Keeni has translated few stories from Kenji Miyazawa and in contemporary literature, Abhijit Mukherjee translating Yukio Mishima and Haruki Murakami in Bengali language.

Keywords: literary translation, bengali, Japanese, book

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Authors: Walter Evaldo Kuchenbecker, Julio Carlos Teixeira

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Since efficiency became a challenge to reduce energy consumption of all electrical machines applications, the permanent magnet machine raises up as a better option, because its performance, robustness and simple control. Even though, the electrical machine was developed through analyses of magnetism effect, permanent magnet machines still not well dominated. As permanent magnet machines are becoming popular in most applications, the pressure to standardize this type of electrical machine increases. However, due limited domain, it is still nowadays without any standard to manufacture, test and application. In order to determine an inductance of the machine, a new method is proposed.

Keywords: permanent magnet generators (pmg), synchronous machine parameters, test procedures, inductances

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

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Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Marcel Lehr, Andreas Binder

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This paper compares three different permanent magnet synchronous machines (Doubly-Salient-Permanent-Magnet-Machine (DSPM), Flux-Reversal-Permanent-Magnet-Machine (FRPM), Flux-Switching-Permanent-Magnet-Machine (FSPM)) with the permanent magnets in the stator of the machine for use as an industrial drive for 400 V Y, 45 kW and 1000 ... 3000 min-1. The machines are compared based on the magnetic co-energy and Finite-Element-Method-Simulations regarding the torque density. The results show that the FSPM provides the highest torque density of the three machines. Therefore, an FSPM prototype was built, tested on a test bench and finally compared with an already built conventional permanent magnet synchronous machine (PMSM) of the same size (stator outer diameter dso = 314 mm, axial length lFe = 180 mm) and rating with surface-mounted rotor magnets. These measurements show that the conventional PMSM and the FSPM machine are roughly equivalent in their electrical behavior.

Keywords: doubly-salient-permanent-magnet-machine, flux-reversal-permanent-magnet-machine, flux-switching-permanent-magnet-machine, industrial drive

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Authors: Abhinav Purohit, Shruthi S. Pradeep

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In today’s world, aviation industries are using turbofan engines (permutation of turboprop and turbojet) which meet the obligatory requirements to be fuel competent and to produce enough thrust to propel an aircraft. But one can imagine increasing the work output of this particular machine by reducing the input power. In striving to improve technologies, especially to augment the efficiency of the engine with some adaptations, which can be crooked to new concepts by introducing a step change in the turbofan engine development. One hopeful concept is, to de-couple the fan with the help of reduction gear box in a two spool shaft engine from the rest of the machinery to get more work output with maximum efficiency by reducing the load on the turbine shaft. By adapting this configuration we can get an additional degree of freedom to better optimize each component at different speeds. Since the components are running at different speeds we can get hold of preferable efficiency. Introducing water alcohol mixture to this concept would really help to get better results.

Keywords: emissions, fuel consumption, more power, turbofan

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Ezzeldin M. T. Ali

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Arguably viewers hardly benefit from screen subtitles due to the inconsistency between scenarios and their subtitles. Research in this area will provide an understanding of the association between these scenarios and subtitles via context. It attempts to eliminate the inconsistency existing between contexts and screen subtitles providing insights into the problem. Specifically, the study aims at examining the extent to which the understanding of screen subtitles largely depends on the force of linguistic and situational contexts. This is because the context is assumed to have a powerful effect on the interpretation of the source text. Both descriptive and experimental methods were adopted for data collection. These included a test and paper-pencil-questionnaires where participants provided their impressions about the role of context in eliminating interpretation problems of screen subtitles. Participants developed a good background about screen subtitles watching films. Results showed that context forms a powerful element in understanding screen subtitles. Results also revealed that communicative translation fits well screen translation boosting the contextual meaning. The association of context and communicative translation makes subtitles globally more economical and intelligible. Context forms a central element for film language to be intelligible.

Keywords: communicative translation, context, scenario, powerful, intellgible

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Authors: Ahmed A. D. Sarhan, S. R. Besharaty, Javad Akbaria, M. Hamdi

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The capability of CNC gantry milling machines in manufacturing long components has caused the expanded use of such machines. On the other hand, the machines’ gantry rigidity can reduce under severe loads or vibration during operation. Indeed, the quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. For this reason, this type of machines has always been used prudently and are non efficient. Therefore, they can usually be employed for rough machining and may not produce adequate surface finishing. In this paper, a CNC gantry milling machine with the potential to produce good surface finish has been designed and analyzed. The lowest natural frequency of this machine is 202 Hz at all motion amplitudes with a full range of suitable frequency responses. Meanwhile, the maximum deformation under dead loads for the gantry machine is 0.565µm, indicating that this machine tool is capable of producing higher product quality.

Keywords: frequency response, finite element, gantry machine, gantry design, static and dynamic analysis

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Authors: Ge Zheng, Jun Peng

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Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

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Authors: Yan Yue

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Huang Di Nei Jing (HDNJ) is one of the significant traditional Chinese medicine (TCM) classics which lays the foundation of TCM theory and practice. It is an important work for the world to study the ancient civilizations and medical history of China. Language in HDNJ is highly concise and vague, and notably challenging to translate. This paper investigates the translatability of one particular vagueness in HDNJ: the conceptual vagueness which carries the Chinese philosophical and cultural connotations. The corpora tool Sketch Engine is used to provide potential online contexts and word behaviors. Selected two English translations of HDNJ by TCM practitioner and non-practitioner are used to examine frequency and distribution of linguistic features of the translation. It was found the hypothesis about the universals of translated language (explicitation, normalisation) is true in one translation, but it is on the sacrifice of some original contextual connotations. Transliteration is purposefully used in the second translation to retain the original flavor, which is argued as a violation of the principle of relevance in communication because it yields little contextual effects and demands more processing effort of the reader. The translatability of conceptual vagueness in HDNJ is constrained by source language context and the reader’s cognitive environment.

Keywords: corpus-based translation, translatability, TCM classics, vague language

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Fatima S. Rodriguez, Victorino T. Taylan, Manolito C. Bulaong, Helen F. Gavino, Vitaliana U. Malamug

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In sundrying the quality of the grains are greatly reduced when paddy grains were caught by the rain unsacked and unstored resulting to reduced profit. The objectives of this study were to design and fabricate a quick covering machine for grain drying pavement; to test and evaluate the operating characteristics of the machine according to its deployment speed, recovery speed, deployment time, recovery time, power consumption, aesthetics of laminated sack; and to conduct partial budget and cost curve analysis. The machine was able to cover the grains in a 12.8 m x 22.5 m grain drying pavement at an average time of 17.13 s. It consumed 0.53 W-hr for the deployment and recovery of the cover. The machine entailed an investment cost of $1,344.40 and an annual cost charge of $647.32. Moreover, the savings per year using the quick covering machine was $101.83.

Keywords: quick covering machine, grain drying pavement, laminated polypropylene, recovery time

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Authors: Parisi L., Hamili D., Azlan N.

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The aim of this study was to design and simulate a particular type of Asynchronous State Machine (ASM), namely a ‘traffic light controller’ (TLC), operated at a frequency of 0.5 Hz. The design task involved two main stages: firstly, designing a 4-bit binary counter using J-K flip flops as the timing signal and subsequently, attaining the digital logic by deploying ASM design process. The TLC was designed such that it showed a sequence of three different colours, i.e. red, yellow and green, corresponding to set thresholds by deploying the least number of AND, OR and NOT gates possible. The software Multisim was deployed to design such circuit and simulate it for circuit troubleshooting in order for it to display the output sequence of the three different colours on the traffic light in the correct order. A clock signal, an asynchronous 4-bit binary counter that was designed through the use of J-K flip flops along with an ASM were used to complete this sequence, which was programmed to be repeated indefinitely. Eventually, the circuit was debugged and optimized, thus displaying the correct waveforms of the three outputs through the logic analyzer. However, hazards occurred when the frequency was increased to 10 MHz. This was attributed to delays in the feedback being too high.

Keywords: asynchronous state machine, traffic light controller, circuit design, digital electronics

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Authors: Jeremy Faludi, Zhongyin Hu, Shahd Alrashed, Christopher Braunholz, Suneesh Kaul, Leulekal Kassaye

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Environmental impacts of six 3D printers using various materials were compared to determine if material choice drove sustainability, or if other factors such as machine type, machine size, or machine utilization dominate. Cradle-to-grave life-cycle assessments were performed, comparing a commercial-scale FDM machine printing in ABS plastic, a desktop FDM machine printing in ABS, a desktop FDM machine printing in PET and PLA plastics, a polyjet machine printing in its proprietary polymer, an SLA machine printing in its polymer, and an inkjet machine hacked to print in salt and dextrose. All scenarios were scored using ReCiPe Endpoint H methodology to combine multiple impact categories, comparing environmental impacts per part made for several scenarios per machine. Results showed that most printers’ ecological impacts were dominated by electricity use, not materials, and the changes in electricity use due to different plastics was not significant compared to variation from one machine to another. Variation in machine idle time determined impacts per part most strongly. However, material impacts were quite important for the inkjet printer hacked to print in salt: In its optimal scenario, it had up to 1/38th the impacts coreper part as the worst-performing machine in the same scenario. If salt parts were infused with epoxy to make them more physically robust, then much of this advantage disappeared, and material impacts actually dominated or equaled electricity use. Future studies should also measure DMLS and SLS processes / materials.

Keywords: 3D printing, additive manufacturing, sustainability, life-cycle assessment, design for environment

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Authors: Ifeoluwa Omotehinse Oloruntoba

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Through comparative and causal models of translation, this paper examined the translation of ‘bread’ into the Yoruba language in three Yoruba versions of the Bible: Bibeli Yoruba Atoka (YBA), Bibeli Mimo ni Ede Yoruba Oni (BMY) and Bibeli Mimo (BM). In biblical times, bread was a very important delicacy that it was synonymous with food in general and in the Bible, bread sometimes refers to a type of food (a mixture of flour, water, and yeast that is baked) or food in general. However, this is not the case in the Yoruba culture. In fact, some decades ago, bread was not known in Nigeria and had no name in the Yoruba language until the 1900s when it was codified as burẹdi in Yoruba, a term borrowed from English and transliterated. Nevertheless, in Nigeria presently, bread is not a special food and it is not appreciated or consumed like in the West. This makes it difficult to translate bread in the Bible into Yoruba. From an investigation on the translation of this term, it was discovered that bread which has 330 occurrences in the English Bible translation (King James) has few occurrences in the three Yoruba Bible versions. In the first version (YBA) published in the 1880s, where bread is synonymous with food in general, it is mostly translated as oúnjẹ (food) or the verb jẹ (to eat), revealing that something is eaten but not indicating what it is. However, when the bread is a type of food, it is rendered as akara, a special delicacy of the Yoruba people made from beans flour. In the later version (BMY) published in the 1990s, bread as food, in general, is also mainly translated as oúnjẹ or the verb jẹ, but when it is a type of food, it is translated as akara with few occurrences of burẹdi. In the latest edition (BM), bread as food is either rendered as ounje or literally translated as burẹdi. Where it is a type of food in this version, it is mainly rendered as burẹdi with few occurrences of akara, indicating the assimilation of bread into the Yoruba culture. This result, although limited, shows that the Bible was translated into Yoruba to make it accessible to Yoruba speakers in their everyday language, hence the application of both domesticating and foreignising strategies. This research also emphasizes the role of the translator as an intermediary between two cultures.

Keywords: translation, Bible, Yoruba, cultural problems

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Juliana C. Salvadori, Jose Carlos Felix

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This paper aims at discussing the role literary translation has played in Brazilian Concrete Poetry Movement – an aesthetic, critical and pedagogical project which conceived translation as poiesis, i.e., as both creative and critic work in which the potency (dynamic) of literary work is unfolded in the interpretive and critic act (energeia) the translating practice demands. We argue that translation, for concrete poets, is conceived within the framework provided by the reinterpretation –or deglutition– of Oswald de Andrade’s anthropophagy – a carefully selected feast from which the poets pick and model their Paideuma. As a case study, we propose to approach and analyze two of Augusto de Campos’s long-term translation projects: the translation of Emily Dickinson’s and E. E. Cummings’s works to Brazilian readers. Augusto de Campos is a renowned poet, translator, critic and one of the founding members of Brazilian Concrete Poetry movement. Since the 1950s he has produced a consistent body of translated poetry from English-speaking poets in which the translator has explored creative translation processes – transcreation, as concrete poets have named it. Campos’s translation project regarding E. E. Cummings’s poetry comprehends a span of forty years: it begins in 1956 with 10 poems and unfolds in 4 works – 20 poem(a)s, 40 poem(a)s, Poem(a)s, re-edited in 2011. His translations of Dickinson’s poetry are published in two works: O Anticrítico (1986), in which he translated 10 poems, and Emily Dickinson Não sou Ninguém (2008), in which the poet-translator added 35 more translated poems. Both projects feature bilingual editions: contrary to common sense, Campos translations aim at being read as such: the target readers, to fully enjoy the experience, must be proficient readers of English and, also, acquainted with the poets in translation – Campos expects us to perform translation criticism, as Antoine Berman has proposed, by assessing the choices he, as both translator and poet, has presented in order to privilege aesthetic information (verse lines, word games, etc.). To readers not proficient in English, his translations play a pedagogycal role of educating and preparing them to read both the target poet works as well as concrete poetry works – the detailed essays and prefaces in which the translator emphasizes the selection of works translated and strategies adopted enlighten his project as translator: for Cummings, it has led to the oblieraton of the more traditional and lyrical/romantic examples of his poetry while highlighting the more experimental aspects and poems; for Dickinson, his project has highligthed the more hermetic traits of her poems. To the domestic canons of both poets in Brazilian literary system, we analyze Campos’ contribution in this work.

Keywords: translation criticism, Augusto de Campos, E. E. Cummings, Emily Dickinson

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Authors: Yo-Sheng Lin, Chien-Chin Wang, Yun-Wen Lin, Chien-Yo Lee

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A wide band power amplifier (PA) for 60 GHz and 77 GHz direct-conversion transceiver using standard 90 nm CMOS technology is reported. The PA comprises a cascode input stage with a wide band T-type input-matching network and inductive interconnection and load, followed by a common-source (CS) gain stage and a CS output stage. To increase the saturated output power (PSAT) and power-added efficiency (PAE), the output stage adopts a two-way power dividing and combining architecture. Instead of the area-consumed Wilkinson power divider and combiner, miniature low-loss transmission-line inductors are used at the input and output terminals of each of the output stages for wide band input and output impedance matching to 100 ohm. This in turn results in further PSAT and PAE enhancement. The PA consumes 92.2 mW and achieves maximum power gain (S21) of 23.3 dB at 56 GHz, and S21 of 21.7 dB and 14 dB, respectively, at 60 GHz and 77 GHz. In addition, the PA achieves excellent saturated output power (PSAT) of 10.6 dB and maximum power added efficiency (PAE) of 12.3% at 60 GHz. At 77 GHz, the PA achieves excellent PSAT of 10.4 dB and maximum PAE of 6%. These results demonstrate the proposed wide band PA architecture is very promising for 60 GHz wireless personal local network (WPAN) and 77 GHz automobile radar systems.

Keywords: 60 GHz, 77 GHz, PA, WPAN, automotive radar

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Authors: Anek Apipatkul, Paphakorn Pitayachaval

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Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

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Authors: Ana Sofia Saldanha

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The answer is yes. Globalization is changing the translation world day after day, year after year. The need to know more about new technologies, clients, companies, project management and social networks is becoming more and more demanding and increasingly competitive. The great majority of the recently graduated Translators do not know where to go, what to do or even who to contact to start their careers in translation. It is well known that there are innumerous webinars, books, blogs and webpages with the so-called “tips do become a professional translator” indicating for example, what to do, what not to do, rates, how your resume should look like, etc. but are these pieces of advice coming from real translators? Translators who work daily with clients, who understand their demands, requests, questions? As far as today`s trends, the answer is no. Most of these pieces of advice are just theoretical and coming from “brilliant minds” who are more interested in spreading their word and winning “likes” to become, in some way, “important people in some area. Mentoring is, indeed, a highly important tool to help and guide new translators starting their career. An effective and well oriented Mentoring is a powerful way to orient these translators on how to create their resumes, where to send resumes, how to approach clients, how to answer emails and how to negotiate rates in an efficient way. Mentoring is a crucial tool and even some kind of “psychological trigger”, when properly delivered by professional and experienced translators, to help in the so aimed career development. The advice and orientation sessions which can bem 100% done online, using Skype for example, are almost a “weapon” to destroy the barriers created by opinions, by influences or even by universities. This new orientation trend is the future path for new translators and is the future of the Translation industry and professionals and Universities who must update their way of approaching the real translation world, therefore, minds and spirits need to be opened and engaged in this new trend of developing skills.

Keywords: mentoring, orientation, professional follow-up, translation

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Long Kun

Abstract:

The educated youth(also known as sent-down youth or rusticated youth)novels came into being with China’s movement of the educated youth “going up to the mountains and down to the countryside”(上山下乡运动, also known as the Rustication Movement)during the cultural revolution.1 Since the 1980s, educated youth novels have been gradually translated into the English-speaking world and attracted great attention. As an important part of contemporary Chinese literature, the English translation of educated youth novels provides a platform for English-speaking readers to understand China in the Cultural Revolution, which reflects the social changes of more than 70 years since the founding of New China. At present, there is a lack of systematic research on the translation of educated youth novels in the English-speaking world. This article sorts out and analyzes the dissemination and reception of educated youth novels in the English-speaking world in different periods, providing a further reference for Chinese literature ‘going out’.

Keywords: educated youth novels, english translation, english-speaking world, dissemination, reception

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Authors: Jennifer Leach, Umashanger Thayasivam

Abstract:

The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

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Authors: Yousef Sahari, Eisa Asiri

Abstract:

Hollywood films are produced in an open and liberal context, and when subtitling for a more conservative and closed society such as an Arabic society, religious words can pose a thorny challenge for subtitlers. Using a corpus of 90 Hollywood films released between 2000 and 2018 and applying insights from Descriptive Translation Studies (Toury, 1995, 2012) and the dichotomy of domestication and foreignization, this paper investigates three main research questions: (1) What are the dominant religious terms and functions in the English subtitles? (2) What are the dominant translation strategies used in the translation of religious words? (3) Do these strategies tend to be SL-oriented or TL-oriented (domesticating or foreignising)? To answer the research questions above, a quantitative and qualitative analysis of the corpus is conducted, in which the researcher adopts a self-designed, parallel, aligned corpus of ninety films and their Arabic subtitles. A quantitative analysis is performed to compare the frequencies and distribution of religious words, their functions, and the translation strategies employed by the subtitlers of ninety films, with the aim of identifying similarities or differences in addition to identifying the impact of functions of religious terms on the use of subtitling strategies. Based on the quantitative analysis, a qualitative analysis is performed to identify any translational patterns in Arabic translations of religious words and the possible reasons for subtitlers’ choices. The results show that the function of religious words has a strong influence on the choice of subtitling strategies. Also, it is found that foreignization strategies are applied in about two-thirds of the total occurrences of religious words.

Keywords: religious terms, subtitling, audiovisual translation, modern standard arabic, subtitling strategies, english-arabic subtitling

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Authors: Y. Kobori, S. Tanaka, N. Tsukiji, N. Takai, H. Kobayashi

Abstract:

This paper proposes two kinds of new single-inductor dual-output (SIDO) DC-DC switching converters with ripple-based hysteretic control. First SIDO converters of type 1 utilize the triangular signal generated by the CR-circuit connected across the inductor. This triangular signal is used for generating the PWM signal instead of the saw-tooth signal used in the conventional converters. Second SIDO converters of type 2 utilize the triangular signal generated by the CR-circuit connected across the voltage error amplifier. This paper describes circuit topologies, Operation principles, simulation results and experimental results of the proposed SIDO converters. In simulation results of both type of SIDO converters, static output voltage ripples are less than 5mVpp and over/under shoots of the dynamic load regulations for the output current step are less than +/- 10mV. In experimental results of single output converter of type 2, static output voltage ripples are about 20mVpp. Output ripples of SIDO type 1 converter are about 80mVpp.

Keywords: DC-DC converter, switching converter, SIDO converter, hysteretic control, ripple-based control

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Authors: Chee Sun Won

Abstract:

This paper presents the size reduction of images for machine-to-machine communications. Here, the salient image regions to be preserved include the image patches of the key-points such as corners and blobs. Based on a saliency image map from the key-points and their image patches, an axis-aligned grid-size optimization is proposed for the reduction of image size. To increase the size-reduction efficiency the aspect ratio constraint is relaxed in the constraint optimization framework. The proposed method yields higher matching accuracy after the size reduction than the conventional content-aware image size-reduction methods.

Keywords: image compression, image matching, key-point detection and description, machine-to-machine communication

Procedia PDF Downloads 418