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Journal articles on the topic 'Automatically aligned'
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Rosolen, Grahame C. "Automatically aligned electron beam lithography on the nanometre scale." Applied Surface Science 144-145 (April 1999): 467–71. http://dx.doi.org/10.1016/s0169-4332(98)00841-1.
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Anees, Abu Sneineh, and A. Salah Wael. "Design and implementation of an automatically aligned solar tracking system." International Journal of Power Electronics and Drive System (IJPEDS) 10, no. 4 (2019): 2055–64. https://doi.org/10.11591/ijpeds.v10.i4.pp2055-2064.
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This paper presents the design and implementation of a closed-loop solar tracker system. The demand for clean energy sources has increased along with the rising demand for electrical energy and the increasing amount of environment pollution triggered by fuel consumption. Among these sources, solar energy is considered the most feasible given its wide availability and easy operation in different environments. The main purpose of this study is to maximize the generated photovoltaic power and reduce CO2 emissions by designing an efficient and low-cost solar tracking system. An aligned closedloop solar tracker is designed and constructed to achieve the best accuracy. The proposed system shows more freedom in its movement to overcome the problems associated with the tilt of the frame-holder. A PIC microcontroller based on the Flowcode programming language is used, the position feedback is detected by using a photo-sensor, and the H-Bridge driver is used to control two DC motors. According to the experimental results, the proposed system shows significant improvements in efficiency compared with stationary solar tracking systems.
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Abu Sneineh, Anees, and Wael A. Salah. "Design and implementation of an automatically aligned solar tracking system." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 4 (2019): 2055. http://dx.doi.org/10.11591/ijpeds.v10.i4.pp2055-2064.
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This paper presents the design and implementation of a closed-loop solar tracker system. The demand for clean energy sources has increased along with the rising demand for electrical energy and the increasing amount of environment pollution triggered by fuel consumption. Among these sources, solar energy is considered the most feasible given its wide availability and easy operation in different environments. The main purpose of this study is to maximize the generated photovoltaic power and reduce CO<sub>2</sub> emissions by designing an efficient and low-cost solar tracking system. An aligned closed-loop solar tracker is designed and constructed to achieve the best accuracy. The proposed system shows more freedom in its movement to overcome the problems associated with the tilt of the frame-holder. A PIC microcontroller based on the Flowcode programming language is used, the position feedback is detected by using a photo-sensor, and the H-Bridge driver is used to control two DC motors. According to the experimental results, the proposed system shows significant improvements in efficiency compared with stationary solar tracking systems.
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Makinen, Erno, and Roope Raisamo. "Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces." IEEE Transactions on Pattern Analysis and Machine Intelligence 30, no. 3 (2008): 541–47. http://dx.doi.org/10.1109/tpami.2007.70800.
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Yoon, Won-Jin, Kyung Min Lee, Dean R. Evans, Michael E. McConney, Dae-Yoon Kim, and Kwang-Un Jeong. "Giant surfactants for the construction of automatic liquid crystal alignment layers." Journal of Materials Chemistry C 7, no. 28 (2019): 8500–8514. http://dx.doi.org/10.1039/c9tc00422j.
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Nageler, Marcel, Shibam Ghosh, Marlene Jüttler, and Maria Eichlseder. "AutoDiVer: Automatically Verifying Differential Characteristics and Learning Key Conditions." IACR Transactions on Symmetric Cryptology 2025, no. 1 (2025): 471–514. https://doi.org/10.46586/tosc.v2025.i1.471-514.
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Differential cryptanalysis is one of the main methods of cryptanalysis and has been applied to a wide range of ciphers. While it is very successful, it also relies on certain assumptions that do not necessarily hold in practice. One of these is the hypothesis of stochastic equivalence, which states that the probability of a differential characteristic behaves similarly for all keys. Several works have demonstrated examples where this hypothesis is violated, impacting the attack complexity and sometimes even invalidating the investigated prior attacks. Nevertheless, the hypothesis is still typically taken for granted. In this work, we propose AutoDiVer, an automatic tool that allows to thoroughly verify differential characteristics. First, the tool supports calculating the expected probability of differential characteristics while considering the key schedule of the cipher. Second, the tool supports estimating the size of the space of keys for which the characteristic permits valid pairs, and deducing conditions for these keys. AutoDiVer implements a custom SAT modeling approach and takes advantage of a combination of features of advanced SAT solvers, including approximate model counting and clause learning. To show applicability to many different kinds of block ciphers like strongly aligned, weakly aligned, and ARX ciphers, we apply AutoDiVer to GIFT, PRESENT, RECTANGLE, SKINNY, Midori, WARP, SPECK, and SPEEDY.
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Levy, Jacob T. "FEDERALISM AND THE OLD AND NEW LIBERALISMS." Social Philosophy and Policy 24, no. 1 (2006): 306–26. http://dx.doi.org/10.1017/s0265052507070136.
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The transition from a relatively federal to a relatively centralized constitutional structure in the United States has often been identified with the shift from classical to welfare liberalism as a matter of public philosophy. This article argues against that distinction. The liberal argument for federalism is a contingent one, built on approximations, counterbalancing, and political power. A more federalist constitution is not automatically a freer one on classical liberal understandings of freedom. Neither is a more centralized constitution automatically a better match with the ideals of welfare liberalism. The article sketches a constitutional history of federalism from the founding, through an era in which centralization was aligned with skepticism about liberal constitutionalism (for both meanings of liberal), to an era in which centralization was aligned with increases in liberal freedom (for both meanings of liberal).
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Gippert, Jost, and Daniel Stökl Ben Ezra. "Reading Georgian Manuscripts Automatically on the eScriptorium Platform." Digital Kartvelology 3 (December 27, 2024): 5–24. https://doi.org/10.62235/dk.3.2024.8508.
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The article outlines the development of means for an automatic reading of Georgian manuscripts on the eScriptorium platform and the first results achieved with them. After an overview of the efforts undertaken in applying Optical Character Recognition (OCR) to Georgian printed books since the late 1980’s and a short introduction into the basics of the eScriptorium approach to Handwritten Text Recognition (HCR) and its functionalities, it exemplifies the application of the three core procedures of eScriptorium, which consist in the automatic segmentation of text-covered regions and lines, the automatic transcription of the detected lines based on manual input and the training of appropriate models, and the alignment with existing electronic texts in order to provide reliable ground truth for further training. With a total of 292 manually transcribed pages and 3812 pages with aligned (but not yet always corrected) text that have been processed so far, there is a strong material basis for further improvement of the models and the reading results depending on them.
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Repar, Andraž, Vid Podpečan, Anže Vavpetič, Nada Lavrač, and Senja Pollak. "TermEnsembler." Terminology 25, no. 1 (2019): 93–120. http://dx.doi.org/10.1075/term.00029.rep.
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Abstract This paper describes TermEnsembler, a bilingual term extraction and alignment system utilizing a novel ensemble learning approach to bilingual term alignment. In the proposed system, the processing starts with monolingual term extraction from a language industry standard file type containing aligned English and Slovenian texts. The two separate term lists are then automatically aligned using an ensemble of seven bilingual alignment methods, which are first executed separately and then merged using the weights learned with an evolutionary algorithm. In the experiments, the weights were learned on one domain and tested on two other domains. When evaluated on the top 400 aligned term pairs, the precision of term alignment is over 96%, while the number of correctly aligned multi-word unit terms exceeds 30% when evaluated on the top 400 term pairs.
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Repar, Andraž, Vid Podpečan, Anže Vavpetič, Nada Lavrač, and Senja Pollak. "TermEnsembler: An enseble learning approach to bilingual term extraction and alignment." Terminology. International Journal of Theoretical and Applied Issues in Specialized Communication 25, no. 1 (2019): 93–120. https://doi.org/10.1075/term.00029.rep.
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This paper describes TermEnsembler, a bilingual term extraction and alignment system utilizing a novel ensemble learning approach to bilingual term alignment. In the proposed system, the processing starts with monolingual term extraction from a language industry standard file type containing aligned English and Slovenian texts. The two separate term lists are then automatically aligned using an ensemble of seven bilingual alignment methods, which are first executed separately and then merged using the weights learned with an evolutionary algorithm. In the experiments, the weights were learned on one domain and tested on two other domains. When evaluated on the top 400 aligned term pairs, the precision of term alignment is over 96%, while the number of correctly aligned multi-word unit terms exceeds 30% when evaluated on the top 400 term pairs.
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Hotomski, Sofija, and Martin Glinz. "GuideGen: An approach for keeping requirements and acceptance tests aligned via automatically generated guidance." Information and Software Technology 110 (June 2019): 17–38. http://dx.doi.org/10.1016/j.infsof.2019.01.011.
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Tiedemann, Jörg. "Can bilingual word alignment improve monolingual phrasal term extraction?" Terminology 7, no. 2 (2001): 199–215. http://dx.doi.org/10.1075/term.7.2.05tie.
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This paper focuses on the improvement of statistically-extracted phrase lists by applying word alignment approaches to bitext. Such phrase lists serve several tasks such as the compilation of terminology or translation databases. Our investigations are based on the assumption that word alignment favors well-formed phrase structures rather than irregular text segments. If this is the case, word alignment will filter out irregular structures from automatically generated phrase lists. As a result, an improved phrase list, in terms of precision, may be compiled. Furthermore, word alignment approaches can be used to identify additional multi-word units, e.g. multi-word cognates. Our investigations are focused on a Swedish/English text corpus that has been aligned with the Uppsala Word Aligner (UWA). Finally, we describe and apply three approaches to evaluate the automatically generated phrase lists: an evaluation by comparing results with existing reference data (prior reference), an evaluation against given syntactic patterns (prior reference patterns), and a manual evaluation of sample data (posterior reference). The evaluations of the extraction of phrasal terms in English substantiate the assumption: precision has improved significantly with little loss in recall.
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Hu, Shaoxing, Shen Xiao, Aiwu Zhang, Yiming Deng, and Bingke Wang. "Continuous-Time Laser Frames Associating and Mapping via Multilayer Optimization." Sensors 21, no. 1 (2020): 97. http://dx.doi.org/10.3390/s21010097.
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To achieve the ability of associating continuous-time laser frames is of vital importance but challenging for hand-held or backpack simultaneous localization and mapping (SLAM). In this study, the complex associating and mapping problem is investigated and modeled as a multilayer optimization problem to realize low drift localization and point cloud map reconstruction without the assistance of the GNSS/INS navigation systems. 3D point clouds are aligned among consecutive frames, submaps, and closed-loop frames using the normal distributions transform (NDT) algorithm and the iterative closest point (ICP) algorithm. The ground points are extracted automatically, while the non-ground points are automatically segmented to different point clusters with some noise point clusters omitted before 3D point clouds are aligned. Through the three levels of interframe association, submap matching and closed-loop optimization, the continuous-time laser frames can be accurately associated to guarantee the consistency of 3D point cloud map. Finally, the proposed method was evaluated in different scenarios, the experimental results showed that the proposed method could not only achieve accurate mapping even in the complex scenes, but also successfully handle sparse laser frames well, which is critical for the scanners such as the new Velodyne VLP-16 scanner’s performance.
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Kim, Jonghoek. "Automatic Thread Defect Examination System." Applied Sciences 12, no. 12 (2022): 6109. http://dx.doi.org/10.3390/app12126109.
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This article addresses a Thread Hole (TH) examination system capable of automatically examining a TH. We introduce a contact-based examination system with simple hardware. Our examination system examines TH defects by observing the torque generated when tightening the Inspection Device (ID) through the TH. A buffer with springs is utilized to overcome instances where the TH is not accurately aligned with the axis of the ID. The examination system observes the TH size utilizing a camera, then automatically performs an examination utilizing the optimal torque threshold associated with the TH size; in this way, our examination system is able to examine a TH regardless of its size. In this paper, the performance of the proposed system utilizing the optimal torque threshold is verified through experiments.
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Luo, Simon, and Dave Hale. "Unfaulting and unfolding 3D seismic images." GEOPHYSICS 78, no. 4 (2013): O45—O56. http://dx.doi.org/10.1190/geo2012-0350.1.
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Identifying and extracting geologic horizons is useful for interpretation of stratigraphic features as well as analysis of structural deformation. To extract horizons from a seismic image, we developed methods for automatically unfaulting and unfolding an image to restore all horizons to an undeformed, horizontal state. First, using fault surfaces and dip-separation vectors estimated from an image, we interpolated dip-separation vectors at locations between fault surfaces, and then we used the interpolated dip-separation vectors to unfault an image. Then, using a method for automatic seismic image flattening, we unfolded the unfaulted image to obtain a new image in which sedimentary layering is horizontal and also aligned across faults. From this unfaulted and unfolded image, we automatically extracted geologic horizons.
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Michaels, Maria, Sameemuddin Syed, and William B. Lober. "Blueprint for aligned data exchange for research and public health." Journal of the American Medical Informatics Association 28, no. 12 (2021): 2702–6. http://dx.doi.org/10.1093/jamia/ocab210.
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Abstract Making EHR Data More Available for Research and Public Health (MedMorph) is a Centers for Disease Control and Prevention-led initiative developing and demonstrating a reference architecture (RA) and implementation, including Health Level Seven International Fast Healthcare Interoperability Resources (HL7 FHIR) implementation guides (IGs), describing how to leverage FHIR for aligned research and public health access to clinical data for automated data exchange. MedMorph engaged a technical expert panel of more than 100 members to model representative use cases, develop IGs (architectural and content), align with existing efforts in the FHIR community, and demonstrate the RA in research and public health uses. The RA IG documents common workflows needed to automatically send research data to Research Patient Data Repositories for multiple use cases. Sharing a common RA and canonical data model will improve data sharing for research and public health needs and generate evidence. MedMorph delivers a robust, reusable method to utilize data from electronic health records addressing multiple research and public health needs.
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Vatnehol, Sindre, Hector Peña, and Nils Olav Handegard. "A method to automatically detect fish aggregations using horizontally scanning sonar." ICES Journal of Marine Science 75, no. 5 (2018): 1803–12. http://dx.doi.org/10.1093/icesjms/fsy029.
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Abstract Pelagic fishes are a major source of protein and unsaturated fatty acids, and robust management is critical to avoid overfishing. Fisheries management is often supported by indices from scientific acoustic-trawl surveys, where vertically aligned echo sounders and trawl samples are used to provide an estimate of abundance. Survey biases may be introduced when fish are located near the sea surface or if they avoid the survey vessel. Horizontally scanning acoustic equipment, such as fish-detection sonars, have been proposed as a method to quantify such biases; however, manual interpretation of the data hamper further development. An automated method for identifying fish aggregations within large volumes of sonar data has been developed. It exploits the fact that near-stationary targets, i.e. a fish school, have distinct patterns through the data. The algorithm is not instrument specific, and was tested on data collected from several acoustic-trawl surveys in the Norwegian Sea. The automatic algorithm had a similar performance to manual interpretation, and the main cause of discrepancies was aggregations overlooked in the manual work. These discrepancies were substantially reduced in a second round of manual interpretation. We envision that this method will facilitate a labour efficient and more objective analysis of sonar data and provide information to support fisheries management for pelagic fish.
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Konecny, Jaromir, Michaela Bailova, Petr Beremlijski, Michal Prauzek, and Radek Martinek. "Adjusting products with compensatory elements using a digital twin: Model and methodology." PLOS ONE 18, no. 1 (2023): e0279988. http://dx.doi.org/10.1371/journal.pone.0279988.
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The article presents a novel strategy for reducing the geometric error of a vehicle headlamp equipped with a set of calibration screws, which represents a product assembly. Using a general method for designing and implementing a digital twin, we determined the optimal configuration for a compensatory element that minimizes the total geometric error. Formulated as a problem of constrained minimization, we solved the error using the gradient method and the Broyden–Fletcher–Goldfarb–Shanno method. Products are automatically adjusted according to this optimal setting during the manufacturing process. The results of this novel method indicate that all points can be aligned when the non-individual calibration satifies a geometrical specification of 92%. The digital twin approach was compared to the manufacturing process on 84,055 samples. Overall, 98.19% of the samples were perfectly aligned.
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Rubbert, Christian, Bernd Turowski, and Julian Caspers. "Automatic Alignment of Cranial CT Examinations to the Anterior Commissure/Posterior Commissure (ACPC) Reference Plane for Reliable Interpretation and Quality Assurance." RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 193, no. 01 (2020): 61–67. http://dx.doi.org/10.1055/a-1167-8368.
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Alignment of cranial CT scans (cCTs) to a common reference plane simplifies anatomical-landmark-based orientation and eases follow-up assessment of intracranial findings. We developed and open sourced a fully automated system, which aligns cCTs to the Anterior Commissure/Posterior Commissure (ACPC) line and exports the results to the PACS. FMRIB’s Linear Image Registration Tool (FLIRT) with an ACPC-aligned atlas is used in the alignment step. Five mm mean slabs are generated with the top non-air slice as the starting point. For evaluation, 301 trauma cCTs from the CQ500 dataset were processed. In visual comparison with the respective ACPC-aligned atlas, all were successfully aligned. Image quality (IQ) and ease of identification of the central sulcus (CS) were rated on a Likert scale (5 = excellent IQ/immediate CS identification). The median IQ was 4 (range: 2–4) in the original series and 5 (range: 4–5) in the ACPC-aligned series (p < 0.0001). The CS was more easily identified after fatbACPC (original scans: 4 (range: 2–5); ACPC-aligned: 5 (range: 4–5); p < 0.0001). The mean rotation to achieve alignment was |X| = 6.4 ± 5.2° ([–X,+X] = –26.8°–24.2°), |Y| = 2.1 ± 1.7° ([-Y,+Y] = –8.7°–9.8°), and |Z| = 3.1 ± 2.4° ([–Z,+Z] = –14.3°–12.5°). The developed system can robustly and automatically align cCTs to the ACPC line. Degrees of deviation from the ideal alignment could be used for quality assurance. Key Points: Citation Format
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Colhon, Mihaela. "Language engineering for syntactic knowledge transfer." Computer Science and Information Systems 9, no. 3 (2012): 1231–47. http://dx.doi.org/10.2298/csis120130032c.
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In this paper we present a method for an English-Romanian treebank construction, together with the obtained evaluation results. The treebank is built upon a parallel English-Romanian corpus word-aligned and annotated at the morphological and syntactic level. The syntactic trees of the Romanian texts are generated by considering the syntactic phrases of the English parallel texts automatically resulted from syntactic parsing. The method reuses and adjusts existing tools and algorithms for cross-lingual transfer of syntactic constituents and syntactic trees alignment.
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Hensel, S., S. Goebbels, and M. Kada. "FACADE RECONSTRUCTION FOR TEXTURED LOD2 CITYGML MODELS BASED ON DEEP LEARNING AND MIXED INTEGER LINEAR PROGRAMMING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 37–44. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-37-2019.
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<p><strong>Abstract.</strong> The paper describes a workflow for generating LoD3 CityGML models (i.e. semantic building models with structured facades) based on textured LoD2 CityGML models by adding window and door objects. For each wall texture, bounding boxes of windows and doors are detected using “Faster R-CNN”, a deep neural network. We evaluate results for textures with different resolutions on the ICG Graz50 facade dataset. In general, detected bounding boxes match very well with the rectangular shape of most wall openings. Thus, no further classification of shapes is required. Windows are typically aligned to rows and columns, and only a few different types of windows exist for each facade. However, the neural network proposes rectangles of varying sizes, which are not always aligned perfectly. Thus, we use post-processing to obtain a more realistic appearance of facades. Window and door rectangles get aligned by solving a mixed integer linear optimization problem, which automatically leads to a clustering of these openings into few different classes of window and door types. Furthermore, an a-priori knowledge about the number of clusters is not required.</p>
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Osipenko, Maria. "Online Learning from the Learning Cycle Perspective: Discovering Patterns in Recent Research." Information 15, no. 11 (2024): 665. http://dx.doi.org/10.3390/info15110665.
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We propose a method for automatically extracting new trends and best practices from the recent literature on online learning, aligned with the learning cycle perspective. Using titles and abstracts of research articles published in high ranked educational journals, we assign topic proportions to the articles, where the topics are aligned with the components of the learning cycle: engagement, exploration, explanation, elaboration, evaluation, and evolution. The topic analysis is conducted using keyword-based Latent Dirichlet allocation, and the topic keywords are chosen to reflect the nature of the learning cycle components. Our analysis reveals the time dynamics of research topics aligned on learning cycle components, component weights, and interconnections between them in the current research focus. Connections between the topics and user-defined learning elements are discovered. Concretely, we examine how effective learning elements such as virtual reality, multimedia, gamification, and problem-based learning are related to the learning cycle components in the literature. In this way, any innovative learning strategy or learning element can be placed in the landscape of the learning cycle topics. The analysis can be helpful to other researches when designing effective learning activities that address particular components of the learning cycle.
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Лунюшкин, Сергей, Sergey Lunyushkin, Юрий Пенских, and Yury Penskikh. "Diagnostics of auroral oval boundaries on the basis of the magnetogram inversion technique." Solar-Terrestrial Physics 5, no. 2 (2019): 88–100. http://dx.doi.org/10.12737/stp-52201913.
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It is shown that the convection reversal boundary is a fundamental parameter of the magnetosphere-ionosphere coupling, which determines a strong analogy between the electrostatic potential of the ionosphere and the equivalent current function in the dipole geomagnetic field approximation and the uniform ionospheric conductance. We have developed a new ground-based method for automatically diagnosing boundaries of the auroral oval using output data obtained with the magnetogram inversion technique (MIT). Using maps of the current function and field-aligned currents, calculated at the first stage of MIT with uniform ionospheric conductance, we determine the convection reversal boundary, polar cap boundary, equatorial boundary of the auroral oval, and line of maximum density of auroral electrojets. These parameters have previously been determined by a visual-manual method: analyzing maps of field-aligned and equivalent currents on the monitor screen and carrying out predetermined boundaries with the mouse — this took a very long time (weeks and months). The comparison between manually and automatically obtained boundaries has shown that the correlation coefficient between the two boundaries is, on average, 0.85, and the root-mean-square deviation does not exceed 2° in latitude. By providing an adequate accuracy for the boundary determination, the automatic method reduces the time for map processing by a factor of 2–3 (to minutes and hours), releasing a researcher from laborious visual work. The new method is implemented as one of the important modules in the updated MIT software.
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Лунюшкин, Сергей, Sergey Lunyushkin, Юрий Пенских, and Yury Penskikh. "Diagnostics of auroral oval boundaries on the basis of the magnetogram inversion technique." Solnechno-Zemnaya Fizika 5, no. 2 (2019): 97–113. http://dx.doi.org/10.12737/szf-52201913.
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It is shown that the convection reversal boundary is a fundamental parameter of the magnetosphere-ionosphere coupling, which determines a strong analogy between the electrostatic potential of the ionosphere and the equivalent current function in the dipole geomagnetic field approximation and the uniform ionospheric conductance. We have developed a new ground-based method for automatically diagnosing boundaries of the auroral oval using output data obtained with the magnetogram inversion technique (MIT). Using maps of the current function and field-aligned currents, calculated at the first stage of MIT with uniform ionospheric conductance, we determine the convection reversal boundary, polar cap boundary, equatorial boundary of the auroral oval, and line of maximum density of auroral electrojets. These parameters have previously been determined by a visual-manual method: analyzing maps of field-aligned and equivalent currents on the monitor screen and carrying out predetermined boundaries with the mouse — this took a very long time (weeks and months). The comparison between manually and automatically obtained boundaries has shown that the correlation coefficient between the two boundaries is, on average, 0.85, and the root-mean-square deviation does not exceed 2° in latitude. By providing an adequate accuracy for the boundary determination, the automatic method reduces the time for map processing by a factor of 2–3 (to minutes and hours), releasing a researcher from laborious visual work. The new method is implemented as one of the important modules in the updated MIT software.
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Favre, Liliana Maria. "Formal Metamodeling for Secure Model-Driven Engineering." International Journal of Systems and Software Security and Protection 12, no. 2 (2021): 46–67. http://dx.doi.org/10.4018/ijsssp.2021070104.
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Systems and applications aligned with new paradigms such as cloud computing and internet of the things are becoming more complex and interconnected, expanding the areas in which they are susceptible to attacks. Their security can be addressed by using model-driven engineering (MDE). In this context, specific IoT or cloud computing metamodels emerged to support the systematic development of software. In general, they are specified through semiformal metamodels in MOF style. This article shows the theoretical foundations of a method for automatically constructing secure metamodels in the context of realizations of MDE such as MDA. The formal metamodeling language Nereus and systems of transformation rules to bridge the gap between formal specifications and MOF are described. The main contribution of this article is the definition of a system of transformation rules called NEREUStoMOF for transforming automatically formal metamodeling specifications in Nereus to semiformal-MOF metamodels annotated in OCL.
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Moeller, Sarah, Alexis Davis, Wilermine Previlon, Michael Bottini, and Kevin Tang. "Compiling a corpus of African American Language from oral histories." Research in Corpus Linguistics 12, no. 2 (2024): 45–79. http://dx.doi.org/10.32714/ricl.12.02.04.
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African American Language (AAL) is a marginalized variety of American English that has been understudied due to a lack of accessible data. This lack of data has made it difficult to research language in African American communities and has been shown to cause emerging technologies such as Automatic Speech Recognition (ASR) to perform worse for African American speakers. To address this gap, the Joel Buchanan Archive of African American Oral History (JBA) at the University of Florida is being compiled into a time-aligned and linguistically annotated corpus. Through Natural Language Processing (NLP) techniques, this project will automatically time-align spoken data with transcripts and automatically tag AAL features. Transcription and time-alignment challenges have arisen as we ensure accuracy in depicting AAL morphosyntactic and phonetic structure. Two linguistic studies illustrate how the African American Corpus from Oral Histories betters our understanding of this lesser-studied variety.
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Hull, David A. "Automating the construction of bilingual terminology lexicons." Terminology 4, no. 2 (1997): 225–44. http://dx.doi.org/10.1075/term.4.2.02hul.
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Translation is a labor intensive process. We propose a general methodology for automatic terminology extraction and alignment which could substantially reduce the translator's workload. The goal is to take advantage of existing technology in terminology extraction and statistical word alignment to automatically construct a bilingual terminology lexicon by exploiting bilingual parallel aligned corpora. This paper introduces the technology in each area and discusses some simple heuristic methods for using the output from each component to build a bilingual terminology lexicon. The process is illustrated by an in-depth analysis of a single sentence pair.
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Garabík, Radovan, and Ludmila Dimitrova. "Extraction and Presentation of Bilingual Correspondences from Slovak-Bulgarian Parallel Corpus." Cognitive Studies | Études cognitives, no. 15 (December 31, 2015): 327–34. http://dx.doi.org/10.11649/cs.2015.022.
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Extraction and Presentation of Bilingual Correspondences from Slovak-Bulgarian Parallel CorpusIn this paper the results of the automatic extraction and presentation of bilingual correspondences from Slovak-Bulgarian Parallel corpus are described. The equivalent phrases are extracted from sentence and word level automatically aligned corpus, filtered, indexed and presented in a dictionary-like interface. The bilingual dictionary database contains 80 thousand phrase pairs consisting of approximately 350 thousand words (per each language). Counting unique word forms, the size is 31 thousand in the Slovak part of the dictionary, 26 thousand in the Bulgarian part.
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Melby, Alan K. "Terminology in the age of multilingual corpora." Journal of Specialised Translation, no. 18 (July 25, 2012): 7–29. https://doi.org/10.26034/cm.jostrans.2012.436.
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Terminology management has long played an important role in translation and localisation. It has been asserted, however, that the need for terminology management is declining with the rise of widely accessible aligned multilingual corpora, such as bi-texts. In this view, translators will be able to identify terms and their translations by using previous translations to automatically identify the best translation for a term. This article, however, argues that while bi-text resources will assist in human-oriented terminology management, they will actually increase the need for skilled terminology work and termbases. Furthermore, because more tools will generate terminological data, the need for exchange between tools will increase. After discussing the case for terminology management and terminology exchange in the age of aligned multilingual corpora, the paper describes the role of the TermBase eXchange (TBX) standard in terminology exchange, including typical scenarios for its use, and some of the challenges faced in using it.
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Gong, Heng, Xiaocheng Feng, and Bing Qin. "Quality Control for Distantly-Supervised Data-to-Text Generation via Meta Learning." Applied Sciences 13, no. 9 (2023): 5573. http://dx.doi.org/10.3390/app13095573.
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Data-to-text generation plays an important role in natural language processing by processing structured data and helping people understand those data by generating user-friendly descriptive text. It can be applied to news generation, financial report generation, customer service, etc. However, in practice, it needs to adapt to different domains that may lack an annotated training corpus. To alleviate this dataset scarcity problem, distantly-supervised data-to-text generation has emerged, which constructs a training corpus automatically and is more practical to apply to new domains when well-aligned data is expensive to obtain. However, this distant supervision method of training induces an over-generation problem since the automatically aligned text includes hallucination. These expressions cannot be inferred from the data, misguiding the model to produce unfaithful text. To exploit the noisy dataset while maintaining faithfulness, we empower the neural data-to-text model by dynamically increasing the weights of those well-aligned training instances and reducing the weights of the low-quality ones via meta learning. To our best knowledge, we are the first to alleviate the noise in distantly-supervised data-to-text generation via meta learning. In addition, we rewrite those low-quality texts to provide better training instances. Finally, we construct a new distantly-supervised dataset, DIST-ToTTo (abbreviation for Distantly-supervised Table-To-Text), and conduct experiments on both the benchmark WITA (abbreviation for the data source Wikipedia and Wikidata) and DIST-ToTTo datasets. The evaluation results show that our model can improve the state-of-the-art DSG (abbreviation for Distant Supervision Generation) model across all automatic evaluation metrics, with an improvement of 3.72% on the WITA dataset and 3.82% on the DIST-ToTTo dataset in terms of the widely used metric BLEU (abbreviation for BiLingual Evaluation Understudy). Furthermore, based on human evaluation, our model can generate more grammatically correct and more faithful text compared to the state-of-the-art DSG model.
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BIEMANN, CHRIS, STEFANO FARALLI, ALEXANDER PANCHENKO, and SIMONE PAOLO PONZETTO. "A framework for enriching lexical semantic resources with distributional semantics." Natural Language Engineering 24, no. 2 (2018): 265–312. http://dx.doi.org/10.1017/s135132491700047x.
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AbstractWe present an approach to combining distributional semantic representations induced from text corpora with manually constructed lexical semantic networks. While both kinds of semantic resources are available with high lexical coverage, our aligned resource combines the domain specificity and availability of contextual information from distributional models with the conciseness and high quality of manually crafted lexical networks. We start with a distributional representation of induced senses of vocabulary terms, which are accompanied with rich context information given by related lexical items. We then automatically disambiguate such representations to obtain a full-fledged proto-conceptualization, i.e. a typed graph of induced word senses. In a final step, this proto-conceptualization is aligned to a lexical ontology, resulting in a hybrid aligned resource. Moreover, unmapped induced senses are associated with a semantic type in order to connect them to the core resource. Manual evaluations against ground-truth judgments for different stages of our method as well as an extrinsic evaluation on a knowledge-based Word Sense Disambiguation benchmark all indicate the high quality of the new hybrid resource. Additionally, we show the benefits of enriching top-down lexical knowledge resources with bottom-up distributional information from text for addressing high-end knowledge acquisition tasks such as cleaning hypernym graphs and learning taxonomies from scratch.
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Choi, Min-Hyuk, Sang-Jeong Lee, Hoon Joo Yang, et al. "Automatic Reproduction of Natural Head Position Using a Portable 3D Scanner Based on Immediate Calibration." Applied Sciences 10, no. 1 (2019): 174. http://dx.doi.org/10.3390/app10010174.
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This paper developed a new method to easily record and automatically reproduce the 3D natural head position (NHP) of patients using a portable 3D scanner based on immediate calibration. We first optically scanned the patient’s face using a portable 3D scanner, and the scanned model was easily aligned with the global horizon based on an immediate calibration procedure using a developed calibration plate. The 3D patient NHP Computed Tomography(CT) model was reproduced automatically by performing registration between the CT model and the optically scanned model in the NHP using a modified coherent point drift (CPD) algorithm. In a phantom experiment, we evaluated the developed method’s accuracy using the error between the true and the calculated orientations in roll, pitch, and yaw directions. The mean difference was −0.05 ± 0.13°, 0.08 ± 0.22°, and −0.05 ± 0.18° in the roll, pitch, and yaw directions, respectively. The measured roll, pitch, and yaw directions were not significantly different from the true directions (p > 0.05). The calibration procedure for aligning the scanner coordinate system was easy enough for an inexperienced user to operate, and the 3D NHP CT model could be reproduced automatically. The developed method could be used for diagnosing and treating orthognathic patients with facial asymmetry accurately and conveniently in dental clinics.
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Leung, Hui Min, Hong Bin Yu, Guang Ya Zhou, A. Senthil Kumar, and Fook Siong Chau. "Development of Liquid Tunable Diffractive/Refractive Hybrid Lens Based on Combination of Diamond Turning and Soft Lithography." Advanced Materials Research 74 (June 2009): 85–88. http://dx.doi.org/10.4028/www.scientific.net/amr.74.85.
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A liquid tunable diffractive/refractive hybrid lens which combines the use of high precision diamond turning and soft lithography is developed in this work. This diffractive/refractive hybrid lens comprises a Fresnel lens and a tunable refractive lens automatically aligned during the fabrication process. Multiple PDMS hybrid lens devices can be fabricated from the diamond-turned master mould and AFM results show that the surface quality of the PDMS lenses meets the requirements for optical purposes. The hybrid lens is tested with a green laser (λ = 532nm) and experimental results demonstrate a tunability of more than 20mm.
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Puts, M. J. H., and C. M. M. de Weert. "Completion under Isoluminance." Perception 26, no. 1_suppl (1997): 323. http://dx.doi.org/10.1068/v970124.
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It is known that monocular depth cues become much less effective under isoluminance. One of these depth cues, occlusion, gives rise to surface completion. A study is reported in which the loss of completion under isoluminance was tested. A pair of horizontally aligned bars of different lengths is detected automatically in a display filled with pairs of bars of the same length. The pair is detected serially, when vertical bars are placed over the gaps between the pairs. Because the vertical bars are occluders, and the pairs of horizontal bars are aligned, completion behind the vertical bars takes place and the two parts together behave perceptually as a single bar. We used this knowledge to measure completion under isoluminance. When occlusion is lost under isoluminance, we expect that an occluding surface, isoluminant with the background, will not lead to object completion and as a consequence, the pair with unequal lengths of the parts will pop out. Using this procedure we have demonstrated that completion is lost under isoluminance.
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Pak, Nikita, Joshua H. Siegle, Justin P. Kinney, Daniel J. Denman, Timothy J. Blanche, and Edward S. Boyden. "Closed-loop, ultraprecise, automated craniotomies." Journal of Neurophysiology 113, no. 10 (2015): 3943–53. http://dx.doi.org/10.1152/jn.01055.2014.
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A large array of neuroscientific techniques, including in vivo electrophysiology, two-photon imaging, optogenetics, lesions, and microdialysis, require access to the brain through the skull. Ideally, the necessary craniotomies could be performed in a repeatable and automated fashion, without damaging the underlying brain tissue. Here we report that when drilling through the skull a stereotypical increase in conductance can be observed when the drill bit passes through the skull base. We present an architecture for a robotic device that can perform this algorithm, along with two implementations—one based on homebuilt hardware and one based on commercially available hardware—that can automatically detect such changes and create large numbers of precise craniotomies, even in a single skull. We also show that this technique can be adapted to automatically drill cranial windows several millimeters in diameter. Such robots will not only be useful for helping neuroscientists perform both small and large craniotomies more reliably but can also be used to create precisely aligned arrays of craniotomies with stereotaxic registration to standard brain atlases that would be difficult to drill by hand.
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Priyam, Sharma, and Honade Shrikant. "Geometrical Pattern Recognition for Rearranging Chairs." International Journal of Soft Computing and Engineering (IJSCE) 10, no. 2 (2020): 1–4. https://doi.org/10.35940/ijsce.B3464.0910220.
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Currently, furniture is used by every person and all working people in their lives. In office hours, it is necessary for the people to keep the furniture organized after the completion of meeting or event. Now a day’s every student, every employee and all the working people having rush in their life. So they forget to arrange their furniture in working space which will create bad look for professional environment and also affect the psychology. The common thoughts now a day in educational institutions is that after every laboratory session is over, the students left the chair unarranged and the corresponding lab assistant’s need to arrange the chairs after session is over in order to keep laboratory ready for the upcoming sessions. For this situation, in this paper we proposed a robotic chair which move automatically and follow the tag. These tags are predefined and fixed at valve or table. Whenever program runs these chairs automatically goes to the tag nearby and will aligned at its original position.
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Li, Hongyi, Jiawei Ye, Jie Wu, Tianjie Yan, Chu Wang, and Zhixin Li. "JailPO: A Novel Black-Box Jailbreak Framework via Preference Optimization Against Aligned LLMs." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 26 (2025): 27419–27. https://doi.org/10.1609/aaai.v39i26.34953.
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Large Language Models (LLMs) aligned with human feedback have recently garnered significant attention. However, it remains vulnerable to jailbreak attacks, where adversaries manipulate prompts to induce harmful outputs. Exploring jailbreak attacks enables us to investigate the vulnerabilities of LLMs and further guides us in enhancing their security. Unfortunately, existing techniques mainly rely on handcrafted templates or generated-based optimization, posing challenges in scalability, efficiency and universality. To address these issues, we present JailPO, a novel black-box jailbreak framework to examine LLM alignment. For scalability and universality, JailPO meticulously trains attack models to automatically generate covert jailbreak prompts. Furthermore, we introduce a preference optimization-based attack method to enhance the jailbreak effectiveness, thereby improving efficiency. To analyze model vulnerabilities, we provide three flexible jailbreak patterns. Extensive experiments demonstrate that JailPO not only automates the attack process while maintaining effectiveness but also exhibits superior performance in efficiency, universality, and robustness against defenses compared to baselines. Additionally, our analysis of the three JailPO patterns reveals that attacks based on complex templates exhibit higher attack strength, whereas covert question transformations elicit riskier responses and are more likely to bypass defense mechanisms.
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Babinski, Sarah, Rikker Dockum, J. Hunter Craft, Anelisa Fergus, Dolly Goldenberg, and Claire Bowern. "A Robin Hood approach to forced alignment: English-trained algorithms and their use on Australian languages." Proceedings of the Linguistic Society of America 4, no. 1 (2019): 3. http://dx.doi.org/10.3765/plsa.v4i1.4468.
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Forced alignment automatically aligns audio recordings of spoken language with transcripts at the segment level, greatly reducing the time required to prepare data for phonetic analysis. However, existing algorithms are mostly trained on a few well-documented languages. We test the performance of three algorithms against manually aligned data. For at least some tasks, unsupervised alignment (either based on English or trained from a small corpus) is sufficiently reliable for it to be used on legacy data for low-resource languages. Descriptive phonetic work on vowel inventories and prosody can be accurately captured by automatic alignment with minimal training data. Consonants provided significantly more challenges for forced alignment.
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Yang, Runze, Yuan Chai, Wei He, Yuwei Cai, and Ying Wang. "X-ray computed tomography analysis of defects in 3D printed continuous carbon fibre-reinforced polymers aided by deep learning." Journal of Physics: Conference Series 2954, no. 1 (2025): 012121. https://doi.org/10.1088/1742-6596/2954/1/012121.
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Abstract 3D-printed continuous carbon fibre-reinforced polymers (C-CFRPs) often suffer from higher porosity than conventionally manufactured composites. Here, the volume, distribution, and morphology of defects in 3D-printed C-CFRPs were investigated using X-ray computed tomography. The defects were automatically segmented based on the U-Net deep learning neural network and quantitatively analyzed. The defects are periodically distributed following the laminar structure, featuring ellipsoidal and net-like shapes. The long axes of the ellipsoidal-shaped pores are found to be generally aligned along the fibre direction in each layer, and these pores are more elongated in the top layer than in the bottom layer.
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Trupti Lotlikar. "A User Consent Framework for Privacy-Aligned Data Deletion in Retail Solutions." Journal of Information Systems Engineering and Management 10, no. 48s (2025): 1449–57. https://doi.org/10.52783/jisem.v10i48s.10189.
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In the digital age, businesses gather and keep enormous volumes of user data, frequently requiring the explicit consent of the user for processing and storage. However, it is still exceedingly difficult to guarantee total data erasure upon consent revocation, especially in systems that have disaster recovery databases and synced data centers. The Consent-Driven Data Erasure System presented in the paper is intended to solve this problem by enabling the automated deletion of sensitive and personal data upon user revocation of consent. MS SQL Server is used to create the suggested system, where sensitive information, including payment details, is kept in a separate Consented Data Table and user registration details are kept in a Login Table. Personal information is stored in the consented table automatically when a user registers and accepts the terms and conditions. The solution guarantees total and irreversible data erasure by deleting all associated data from both the primary data center and the disaster recovery database when users withdraw their consent. In order to accomplish this, we implement stored procedures and database triggers that control ongoing synchronization and deletion operations. In order to address concerns about unlawful data retention, the system makes sure that privacy laws like the GDPR and the Digital Personal Data Protection (DPDP) Act are followed. Our findings show that this strategy minimizes privacy threats, improves user control over personal data, and creates a strong foundation for consent-based data lifecycle management in digital platforms.
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Li, Yi, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi, and Yiming Wang. "GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (2021): 4206–14. http://dx.doi.org/10.1609/aaai.v35i5.16544.
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Heterogeneous information networks (HINs) are ideal for describing real-world data with different types of entities and relationships. To carry out machine learning on HINs, meta-paths are widely utilized to extract semantics with pre-defined patterns, and models such as graph convolutional networks (GCNs) are thus enabled. However, previous works generally assume a fixed set of meta-paths, which is unrealistic as real-world data are overwhelmingly diverse. Therefore, it is appealing if meta-paths can be automatically selected given an HIN, yet existing works aiming at such problem possess drawbacks, such as poor efficiency and ignoring feature heterogeneity. To address these drawbacks, we propose GraphMSE, an efficient heterogeneous GCN combined with automatic meta-path selection. Specifically, we design highly efficient meta-path sampling techniques, and then injectively project sampled meta-path instances to vectors. We then design a novel semantic feature space alignment, aiming to align the meta-path instance vectors and hence facilitate meta-path selection. Extensive experiments on real-world datasets demonstrate that GraphMSE outperforms state-of-the-art counterparts, figures out important meta-paths, and is dramatically (e.g. 200 times) more efficient.
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Roth, Michael, and Anette Frank. "Inducing Implicit Arguments from Comparable Texts: A Framework and Its Applications." Computational Linguistics 41, no. 4 (2015): 625–64. http://dx.doi.org/10.1162/coli_a_00236.
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In this article, we investigate aspects of sentential meaning that are not expressed in local predicate–argument structures. In particular, we examine instances of semantic arguments that are only inferable from discourse context. The goal of this work is to automatically acquire and process such instances, which we also refer to as implicit arguments, to improve computational models of language. As contributions towards this goal, we establish an effective framework for the difficult task of inducing implicit arguments and their antecedents in discourse and empirically demonstrate the importance of modeling this phenomenon in discourse-level tasks. Our framework builds upon a novel projection approach that allows for the accurate detection of implicit arguments by aligning and comparing predicate–argument structures across pairs of comparable texts. As part of this framework, we develop a graph-based model for predicate alignment that significantly outperforms previous approaches. Based on such alignments, we show that implicit argument instances can be automatically induced and applied to improve a current model of linking implicit arguments in discourse. We further validate that decisions on argument realization, although being a subtle phenomenon most of the time, can considerably affect the perceived coherence of a text. Our experiments reveal that previous models of coherence are not able to predict this impact. Consequently, we develop a novel coherence model, which learns to accurately predict argument realization based on automatically aligned pairs of implicit and explicit arguments.
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Chen, Wei-An, Ya-Wen Tang, S. D. Clarke, and Patricio Sanhueza. "Alignment Parameters: Quantifying Dense Core Alignment in Star-forming Regions." Astrophysical Journal 979, no. 1 (2025): 67. https://doi.org/10.3847/1538-4357/ad9a5b.
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Abstract Recent high-resolution observations at millimeter (mm) and submillimeter wavelengths reveal a diverse spatial distribution for subparsec-scale dense cores within star-forming regions, ranging from clustered to aligned arrangements. To address the increasing volume of observational and simulation data, we introduce “alignment parameters” as a quantitative and reproducible method to automatically assess core alignment. We first demonstrate the effectiveness of these parameters by applying them to artificial test clumps and comparing the results with labels from visual inspection. A threshold value is then proposed to differentiate between “clustered” and “aligned” categories. Subsequently, we apply these parameters to dense cores identified from a sample of Atacama Large Millimeter/submillimeter Array 1.3 mm dust continuum images in high-mass star-forming regions. Analysis exploring correlations between alignment parameters and clump properties rules out the presence of a moderate or strong correlation, indicating that clump properties do not appear to strongly influence the outcome of fragmentation. One possible explanation for this is that the fragmentation process is chaotic, meaning that small variations in initial conditions can lead to significant differences in fragmentation outcomes, thus obscuring any direct link between clump properties and core alignment/distribution.
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Michel, F. Curtis. "Pair-Production Avalanches Revisited." International Astronomical Union Colloquium 128 (1992): 235–36. http://dx.doi.org/10.1017/s0002731600155234.
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As noted previously in this meeting, any millisecond pulsar that is not perfectly aligned must obviously be strongly charged electrostatically simply because the wave zone is so close to the surface that any trapped neutralizing electrosphere over the polar caps will be driven away beyond 6 or 7 neutron-star radii. Acceleration of stray charges (e.g., from the ISM or a nearby orbiting disk) in such a highly charged system automatically produces coherently radiating bunches of downward moving particles (Michel 1990), this coherent radiation simply reflecting from the surface (or missing the star entirely, as an alternative possibility). This mechanism, suggestive of how pulsars might operate, we will call a pair-production avalanche.
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Vijayaraghavan, D., and T. G. Keith. "An Efficient, Robust, and Time Accurate Numerical Scheme Applied to a Cavitation Algorithm." Journal of Tribology 112, no. 1 (1990): 44–51. http://dx.doi.org/10.1115/1.2920229.
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In this paper, an implicit numerical scheme, based on an approximate factorization technique, is applied to a cavitation algorithm. The algorithm is a modified version of the Elrod cavitation algorithm, which automatically predicts film rupture and reformation in bearings. At each time step, Newton iterations are performed to achieve time accurate solutions for unsteady problems. This numerical scheme is applied in both orthogonal and nonorthogonal grid arrangements. An aligned finite grooved bearing and a flared, misaligned line grooved bearing are analyzed using this new approach. The predictions are compared with the results obtained with procedures currently being used. The new scheme is robust, quickly convergent, and provides time accurate solutions with a minimum expenditure of CPU time.
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Chávez-Aragón, Alberto, Rizwan Macknojia, Pierre Payeur, and Robert Laganière. "Rapid 3D Modeling and Parts Recognition on Automotive Vehicles Using a Network of RGB-D Sensors for Robot Guidance." Journal of Sensors 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/832963.
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This paper presents an approach for the automatic detection and fast 3D profiling of lateral body panels of vehicles. The work introduces a method to integrate raw streams from depth sensors in the task of 3D profiling and reconstruction and a methodology for the extrinsic calibration of a network of Kinect sensors. This sensing framework is intended for rapidly providing a robot with enough spatial information to interact with automobile panels using various tools. When a vehicle is positioned inside the defined scanning area, a collection of reference parts on the bodywork are automatically recognized from a mosaic of color images collected by a network of Kinect sensors distributed around the vehicle and a global frame of reference is set up. Sections of the depth information on one side of the vehicle are then collected, aligned, and merged into a global RGB-D model. Finally, a 3D triangular mesh modelling the body panels of the vehicle is automatically built. The approach has applications in the intelligent transportation industry, automated vehicle inspection, quality control, automatic car wash systems, automotive production lines, and scan alignment and interpretation.
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Wydyanto, Wydyanto, Norshita Mat Nayan, Riza Sulaiman, Deshinta Arrova Dewi, and Tri Basuki Kurniawan. "A Hybrid Approach to Detect and Identify Text in Picture." Emerging Science Journal 8, no. 1 (2024): 218–38. http://dx.doi.org/10.28991/esj-2024-08-01-016.
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In order to create computer systems that can automatically read text from images or pictures, researchers focus on detecting and recognizing text in images. This issue is particularly difficult because images often have complicated backgrounds and a wide range of properties, including color, size, shape, orientation, and texture. Our proposed approach is based on morphology, which consists of a dilation and erosion process to extract text and recognize black-and-white text areas that contain document text or images. This suggested approach has been investigated for its ability to automatically identify text aligned with text pictures, such as store names, street names, banners, and posters. The design, application, and outcomes of the device's experiments are covered in this manuscript using Optical Character Recognition (OCR) Tesseract standards and the optimized OCR Tesseract. Our result shows that the optimized OCR Tesseract performs much better compared to the standard. Image preprocessing and text processing modules comprise this device's two modules. With an Arduino Uno and drawbot/flutter for text printing, this device was created using the Raspberry Pi and a 1.2GHz processor. Doi: 10.28991/ESJ-2024-08-01-016 Full Text: PDF
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Verhoeven, Floor, Amir Vaxman, Tim Hoffmann, and Olga Sorkine-Hornung. "Dev2PQ: Planar Quadrilateral Strip Remeshing of Developable Surfaces." ACM Transactions on Graphics 41, no. 3 (2022): 1–18. http://dx.doi.org/10.1145/3510002.
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We introduce an algorithm to remesh triangle meshes representing developable surfaces to planar quad dominant meshes. The output of our algorithm consists of planar quadrilateral (PQ) strips that are aligned to principal curvature directions and closely approximate the curved parts of the input developable, and planar polygons representing the flat parts of the input that connect the PQ strips. Developable PQ-strip meshes are useful in many areas of shape modeling, thanks to the simplicity of fabrication from flat sheet material. Unfortunately, they are difficult to model due to their restrictive combinatorics. Other representations of developable surfaces, such as arbitrary triangle or quad meshes, are more suitable for interactive freeform modeling but generally have non-planar faces or are not aligned to principal curvatures. Our method leverages the modeling flexibility of non-ruling-based representations of developable surfaces while still obtaining developable, curvature-aligned PQ-strip meshes. Our algorithm optimizes for a scalar function on the input mesh, such that its isolines are extrinsically straight and align well to the locally estimated ruling directions. The condition that guarantees straight isolines is non-linear of high order and numerically difficult to enforce in a straightforward manner. We devise an alternating optimization method that makes our problem tractable and practical to compute. Our method works automatically on any developable input, including multiple patches and curved folds, without explicit domain decomposition. We demonstrate the effectiveness of our approach on a variety of developable surfaces and show how our remeshing can be used alongside handle-based interactive freeform modeling of developable shapes.
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Sawada, Hidetaka, Masashi Watanabe, and Izuru Chiyo. "Ad Hoc Auto-Tuning of Aberrations Using High-Resolution STEM Images by Autocorrelation Function." Microscopy and Microanalysis 18, no. 4 (2012): 705–10. http://dx.doi.org/10.1017/s1431927612001304.
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AbstractA method for measurement of the aberration status from high-resolution dark-field images is developed using scanning transmission electron microscopy (STEM), called the Segmented Image Autocorrelation function Matrix (SIAM). The method employs an autocorrelation function from the segmented area in the defocused STEM images from an aligned crystalline specimen to measure the defocus and twofold astigmatism for the probe-forming system. The values measured using this method can be fed directly back to the instrument by changing the strength of the stigmator and the objective lens of the microscope. It is successfully demonstrated that the feedback system can automatically correct the defocus and twofold astigmatism of the microscope after several iterations using practical STEM images from an actual crystalline specimen.
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Fictumova, Jarmila, Adam Obrusnik, and Kristyna Stepankova. "Teaching Specialized Translation. Error-tagged Translation Learner Corpora." Sendebar 28 (October 19, 2017): 209–41. http://dx.doi.org/10.30827/sendebar.v28i0.5419.
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This paper describes the method used in teaching specialised translation in the English Language Translation Master’s programme at Masaryk University. After a brief description of the courses, the focus shifts to translation learner corpora (TLC) compiled in the new Hypal interface, which can be integrated in Moodle. Student translations are automatically aligned (with possible adjustments), PoS (part-of-speech) tagged, and manually error-tagged. Personal student reports based on error statistics for individual translations to show students’ progress throughout the term or during their studies in the four-semester programme can be easily generated. Using the data from the pilot run of the new software, the paper concludes with the first results of the research examining a learner corpus of translations from Czech into English.