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Detecting and Integrating Multiword Expression into English-Arabic Statistical Machine Translation

Procedia computer Science 2017年 117卷 111-118页

作者： Sara Ebrahim Doaa Hegazy Mostafa Gadal-Haqq M. Mostafa Samhaa R. El-Beltagy Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Center of Informatics Science Nile University Giza Egypt

In this paper we introduce a new method for detecting a type of English Multiword Expressions (MWEs), which is phrasal verbs, into an English-Arabic phrase-based statistical machine translation (PBSMT) system. The detection starts with parsing the English side of the parallel corpus, detecting various linguistic patterns for phrasal verbs and finally integrate them into the En-Ar PBSMT system. In addition, the paper explores the effect of cliticizing specific words in English that have no Arabic equivalent. The results, which reported with the BLEU scores, showed that some patterns achieved significant improvements compared to other patterns and still the baseline achieves the highest score. This paper shows that, by detecting more linguistic patterns and integrating them into En-Ar SMT system, translation quality could be improved with other integration methods. Yet, the results show which path is worth to follow and clarifies the perspective that linguistic features are not handled properly in the statistically learned models.

关键词： Statistical Machine Translation (SMT) Phrase-based SMT Arabic Natural Language Processing Multiword Expressions

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Deep Learning Architiectures for Aided Melanoma Skin Disease Recognition: A Review

Deep Learning Architiectures for Aided Melanoma Skin Disease...

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2021 International Mobile, Intelligent, and Ubiquitous computing Conference, MIUCC 2021

作者： Diame, Zahraa E. Al-Berry, Maryam N. Salem, Mohammed A.-M. Roushdy, Mohamed Ain Shams University Faculty of Computers and Information Sciences Department of Computer Science Cairo Egypt Ain Shams University Faculty of Computers and Information Sciences Scientific Computing Department Cairo Egypt Computer and Information Sciences Ain Shams University Media Eng. and Technology German University in Cairo Egypt Future University in Egypt New Cairo Faculty of Computers and Information Technology Cairo Egypt

ISBN: (纸本)9781665412438

Melanoma, a sort of skin disease, in spite of the fact that it represents a little percentage of skin malignancies in the USA, it represents higher than seventy five percent of all skin diseases connected to all fatalities in the USA alone. This motivated researcher to seek automated techniques that facilitates early diagnosis of skin cancer. Skin lesion segmentation using machine learning became one of the best ways used for early detection and treatment of skin cancer. Recently, the researchers used a different deep network architectures, to segment and diagnose skin cancer. In this paper, we introduce a review of existing deep network architectures that have been suggested to segment skin lesions, pre-processing and post-processing methods with the available datasets that can be used for research in this area, also presented a comparison between the results of different methods used for skin lesion segmentation showing the strengths and weaknesses of each method. © 2021 IEEE.

关键词： Network architecture

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New expansions of numerical eigenvalues by Wilson's element

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Journal of Computational and Applied Mathematics 2009年第1期225卷 213-226页

作者： Lin, Qun Huang, Hung-Tsai Li, Zi-Cai Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences P.O. Box 2719 Beijing 1000080 China Department of Applied Mathematics I-Shou University 840 Taiwan Department of Applied Mathematics National Sun Yat-sen University Kaohsiung 80424 Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung 80424 Taiwan

The paper explores new expansions of eigenvalues for - Δ u = λ ρ u in S with Dirichlet boundary conditions by Wilson's element. The expansions indicate that Wilson's element provides lower bounds of the eigenvalues. By the extrapolation or the splitting extrapolation, the O (h4) convergence rate can be obtained, where h is the maximal boundary length of uniform rectangles. Numerical experiments are carried to verify the theoretical analysis made. It is worth pointing out that these results are new, compared with the recent book, Lin and Lin [Q. Lin, J. Lin, Finite Element Methods;Accuracy and Improvement, Science Press, Beijing, 2006]. © 2009.

关键词： Extrapolation

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Impacts of oxytactic microorganisms and viscous dissipation in Carreau nanoliquid featuring ferromagnetic nanoparticles

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Partial Differential Equations in Applied Mathematics 2025年 13卷

作者： Tabrez, Muhammad Hussain, I. Khan, W.A. Khan, S.U. Waqas, M. Rashid, Rzgar Farooq Anwar, M.I. Ammar, Mohamed Ben Zamri, Nurnadiah Abiyev, Ruzimurod Garalleh, Hakim AL Department of Mathematics Mohi-ud-Din Islamic University Nerian Sharif Azad Jammu and Kashmir 12010 Pakistan Department of Mathematics Namal University Mianwali 42250 Pakistan NUTECH School of Applied Sciences and Humanities National University of Technology Islamabad 44000 Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut 22200 Malaysia Department of Medical Laboratory Science College of Science Knowledge University Erbil 44001 Iraq Department of Medical Laboratory Technique College of Medical Technology AL-Kitab University Kirkuk Iraq Department of Mathematics School of Sciences and Humanities Nazarbayev University Astana Kazakhstan Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Department of Mathematics and its Teaching Methods in Primary Education Tashkent State Pedagogical University Tashkent Uzbekistan Department of Mathematical Science College of Engineering University of Business and Technology Jeddah 21361 Saudi Arabia

Owing to rapid progress in field of nanotechnology, various mathematical model has been proposed regarding the flow of nanofluids. Based on boosted thermal properties, multidisciplinary applications of such materials has been claimed in various engineering and industrial processes. In current work, a theoretical analysis is performed for bioconvective flow of Carreau fluid with applications of magnetic dipole. The significance of magnetic dipole are presented with interaction of ferrofluid. The applications of viscous dissipation have also been entertained. The flow is subject to applications of stretched surface. Similarity variables are used for making transformation to obtain set of nonlinear ODEs from set of PDEs. The numerical computation is also made by using of well-known numerical method termed as bvp4c. Influences of various non dimensional fluid parameters like Brownian motion, viscous dissipation, Curie temperature, Weissenberg number, motile difference parameter and bioconvection Paclet number are examined and expressed graphically. It is perceived that ferrofluid's concentration declines when Brownian diffusive variable is augmented while opposite characteristics are reported for Schmidt number. Current results conveying applications in the biofuels, better heat transport medium, fertilizers, catalysts, electronics, paints, semiconductors, speakers, drug delivery, fertilizers etc. © 2024 The Author(s)

关键词： Bioconvection Carreau fluid Ferromagnetic flow Magnetic dipole Viscous dissipation

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Informational infrastructure of the common digital space of scientific knowledge

Informational infrastructure of the common digital space of ...

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2020 International Conference "Common Digital Space of scientific Knowledge: Problems and Solutions", CDSSK 2020

作者： Ataeva, Olga Kalenov, Nikolay Serebriakov, Vladimir Sotnikov, Alexander Computing Center FRS "Computer Sciences and Control" of Russian Academy of Sciences Vavilova str. 40b Moscow119333 Russia Joint Supercomputer Center of Russian Academy of Sciences – Branch of Federal State Institution "Scientific Research Institute for System Analysis" of Russian Academy of Sciences Leninskiy pr. 32a Moscow119334 Russia

The space of scientific knowledge is understood as a system of knowledge from various fields of science tested by the scientific community. The Common Digital Space of scientific Knowledge (CDSSK) is a digital environment into which information resources and objects that have been tested by the scientific community and that reflect scientific knowledge from a different fields of science are integrated. The common digital space of scientific knowledge consists of a set of thematic subspaces related to various areas of science, built according to common principles. The first step towards the implementation of the CDSSK is the development of its ontology, i.e. a multi-level system of concepts describing resources and objects of subject areas, concepts, terms and connections between them, characterized by an open hierarchical and dynamic structuring, oriented both for storing existing knowledge and for extracting new ones. Since the CDSSK is a fundamentally new information environment, there are a number of significant problems on the way to its implementation. The paper deals with the problems and tasks of forming such a space and developing tools for implementation and support the CDSSK. © 2021 Copyright for this paper by its authors

关键词： Ontology

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Rate scalable video compression based on flexible block wavelet coding technique

Rate scalable video compression based on flexible block wave...

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Data Compression Conference (DCC)

作者： Ming Wei Hongyang Chao Department of Computer Sciences University of North Texas Denton TX USA Department of Scientific Computing and Computer Applications Zhongshan University Guangzhou China

ISBN: (纸本)0769514774

Summary form only given. We present a new wavelet coding technique, flexible block wavelet coding (FBWC). It is specially designed for delta frame compression. FBWC not only makes delta frame compression more efficient but also keeps the rate scalability and other scalabilities of wavelet based scalable video compression techniques. Based on this new delta frame compression technique, we have implemented a highly efficient rate scalable video codec. Its overall performance surpasses the video codec based on SPIHT and is comparable to that of H.263. Using FBWC, delta frames are compressed in three steps: First, we use motion compensation to eliminate the temporal redundancy between adjacent frames and the predicted error frames (PEF) are generated. Next, the PEF are transformed into the wavelet domain using the flexible block wavelet transform (FBWT). Finally, the zerotree coding mechanism and entropy coder are used to actually compress the FBWT transformed wavelet coefficients to the target data rate.

关键词： Video compression Wavelet transforms Scalability Motion compensation Chaos Video codecs Wavelet domain PSNR scientific computing computer applications

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Approximation and competitive algorithms for single-minded selling problem 1

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12th International Conference on Algorithmic Aspects in Information and Management, AAIM 2018

作者： Chin, Francis Y. L. Poon, Sheung-Hung Ting, Hing-Fung Xu, Dachuan Yu, Dongxiao Zhang, Yong Department of Computer Science The University of Hong Kong Pok Fu Lam Hong Kong School of Computer Science University of Nottingham Ningbo China Ningbo China Beijing Institute for Scientific and Engineering Computing Beijing University of Technology Beijing China Institute of Intelligent Computing School of Computer Science and Technology Shandong University Qingdao266237 China Research Center for High Performance Computing Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9783030046187

ISBN: (纸本)9783030046170

The problem of item selling with the objective of maximizing the revenue is studied. Given a seller with k types of items and n single-minded buyers, i.e., each buyer is only interested in a particular bundle of items, to maximize the revenue, the seller must carefully assign some amount of bundles to each buyer with respect to the buyer’s accepted price. Each buyer bi is associated with a value function vi(·) such that vi(x) is the accepted unit bundle price bi is willing to pay for x bundles. We show that the single-minded item selling problem is NP-hard. Moreover, we give an O(√k)-approximation algorithm. For the online version, i.e., the buyers come one by one and the decision on each buyer must be made before the arrival of the next buyer, an O(√k · (log h + log k))- competitive algorithm is achieved, where h is the highest unit item price among all buyers. © Springer Nature Switzerland AG 2018.

关键词： Sales

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Transformers Utilization in Chart Understanding: A Review of Recent Advances & Future Trends

arXiv

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arXiv 2024年

作者： Al-Shetairy, Mirna Hindy, Hanan Khattab, Dina Aref, Mostafa M. Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Scientific Computing Department Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt

In recent years, interest in vision-language tasks has grown, especially those involving chart interactions. These tasks are inherently multimodal, requiring models to process chart images, accompanying text, underlying data tables, and often user queries. Traditionally, Chart Understanding (CU) relied on heuristics and rule-based systems. However, recent advancements that have integrated transformer architectures significantly improved performance. This paper reviews prominent research in CU, focusing on State-of-The-Art (SoTA) frameworks that employ transformers within End-to-End (E2E) solutions. Relevant benchmarking datasets and evaluation techniques are analyzed. Additionally, this article identifies key challenges and outlines promising future directions for advancing CU solutions. Following the PRISMA guidelines, a comprehensive literature search has been conducted across Google Scholar, focusing on publications from January 2020 to June 2024. After rigorous screening and quality assessment, 32 studies have been selected for in-depth analysis. The CU tasks are categorized into a three-layered paradigm based on the cognitive task required. Recent advancements in the frameworks addressing various CU tasks are also reviewed. These frameworks are categorized into single-task or multi-task based on the number of tasks solvable by the E2E solution. Within multi-task frameworks, pre-trained and prompt-engineering-based techniques are explored. Furthermore, this review provides an overview of leading architectures, datasets, and pre-training tasks. Despite significant progress, challenges remain in OCR dependency, handling low-resolution images, and enhancing visual reasoning. Future directions include addressing these challenges, developing robust benchmarks, and optimizing model efficiency. Additionally, integrating explainable AI techniques and exploring the balance between real and synthetic data are crucial for advancing CU research. © 2024, CC BY.

关键词： Distribution transformers

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Maximal constraint satisfaction problems solved by continuous hopfield networks

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WSEAS Transactions on computers 2013年第2期12卷 29-40页

作者： Ettaouil, Mohamed Loqman, Chakir Haddouch, Khalid Hami, Youssef UFR: Scientific Computing and Computer sciences Engineering Sciences Modeling and Scientific Computing Laboratory Faculty of Science and Technology of Fez University Sidi Mohammed ben Abdellah Box 2202 Fez Morocco Department of Computer Engineering High School of Technology Moulay Ismaïl University B. P. 3103 50000 Toulal Meknes Morocco

In this paper, we propose a new approach to solve the maximal constraint satisfaction problems (Max-CSP) using the continuous Hopfield network. This approach is divided into two steps: the first step involves modeling the maximal constraint satisfaction problem as 0-1 quadratic programming subject to linear constraints (QP). The second step concerns applying the continuous Hopfield network (CHN) to solve the QP problem. Therefore, the generalized energy function associated with the CHN and an appropriate parametersetting procedure about Max-CSP problems are given in detail. Finally, the proposed algorithm and some computational experiments solving the Max-CSP are shown.

关键词： Quadratic programming

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NNMF-Based Factorization Techniques for High-Accuracy Privacy Protection on Non-negative-valued Datasets

NNMF-Based Factorization Techniques for High-Accuracy Privac...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Jie Wang Weijun Zhong Jun Zhang Department of Management Sciences and Engineering South-East University Nanjing China Laboratory for High Performance Scientific Computing and Computer Simulation Department of Computer Sciences University of Kentucky USA

The challenge in preserving data privacy is how to protect attribute values without jeopardizing the similarity between data objects under analysis. In this paper, we further our previous work on applying matrix techniques to protect privacy and present a novel algebraic technique based on iterative methods for non-negative-valued data distortion. As an unsupervised learning method for uncovering latent features in high-dimensional data, a low rank nonnegative matrix factorization (NNMF) is used to preserve natural data non-negativity and avoid subtractive basis vector and encoding interactions present in techniques such as principal component analysis. It is the first in privacy preserving data mining in our paper that combining non-negative matrix decomposition with distortion processing. Two iterative methods to solve bound-constrained optimization problem in NMF are compared by experiments on Wisconsin Breast Cancer Dataset. The overall performance of NMF on distortion level and data utility is compared to our previously-proposed SVD-based distortion strategies and other existing popular data perturbation methods. Data utility is examined by cross validation of a binary classification using the support vector machine. Our experimental results on data mining benchmark datasets indicate that, in comparison with standard data distortion techniques, the proposed NMF-based method are very efficient in balancing data privacy and data utility, and it affords a feasible solution with a good promise on high-accuracy privacy preserving data mining

关键词： Data privacy Protection Iterative methods Matrix decomposition Data analysis Unsupervised learning Encoding Principal component analysis Optimization methods Breast cancer

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