251 research outputs found
Cross-view Embeddings for Information Retrieval
No full textTesis doctoral en Informática realizada por Parth Gupta bajo la supervisión del Dr. Paolo Rosso (Universitat Politècnica de València) y el Dr. Rafael E. Banchs (Institute for Infocomm Research, Singapore). La tesis se defendió en Valencia (España) el 26 de enero de 2017. El comité de doctorado estuvo compuesto por los siguientes doctores: Eneko Agirre (Universidad del País Vasco), Julio Gonzalo (Universidad Nacional de Educación a Distancia) y Jaap Kamps (Universidad de Amsterdam). La tesis obtuvo la calificación de sobresaliente Cum Laude.Ph.D. thesis in Computer Science written by Parth Gupta under the supervision of Dr. Paolo Rosso (Universitat Politècnica de València) and Dr. Rafael E. Banchs (Institute for Infocomm Research, Singapore). The thesis was defended in Valencia (Spain) on January 26, 2017. The doctoral committee comprised of the following doctors: Eneko Agirre (University of the Basque Country), Julio Gonzalo (Universidad Nacional de Educación a Distancia) and Jaap Kamps (University of Amsterdam). The thesis got the grade of outstanding Cum Laude
Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language
No full textThis is the author’s version of a work that was accepted for publication in Knowledge-Based Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Knowledge-Based Systems 111 (2016) 87–99. DOI 10.1016/j.knosys.2016.08.004.Cross-language (CL) plagiarism detection aims at detecting plagiarised fragments of text among documents
in different languages. The main research question of this work is on whether knowledge graph
representations and continuous space representations can complement to each other and improve the
state-of-the-art performance in CL plagiarism detection methods. In this sense, we propose and evaluate
hybrid models to assess the semantic similarity of two segments of text in different languages. The proposed
hybrid models combine knowledge graph representations with continuous space representations
aiming at exploiting their complementarity in capturing different aspects of cross-lingual similarity. We
also present the continuous word alignment-based similarity analysis, a new model to estimate similarity
between text fragments. We compare the aforementioned approaches with several state-of-the-art
models in the task of CL plagiarism detection and study their performance in detecting different length
and obfuscation types of plagiarism cases. We conduct experiments over Spanish-English and GermanEnglish
datasets. Experimental results show that continuous representations allow the continuous word
alignment-based similarity analysis model to obtain competitive results and the knowledge-based document
similarity model to outperform the state-of-the-art in CL plagiarism detection.
© 2016 Elsevier B.V. All rights reserved.This research has been carried out in framework of the FPI-UPV pre-doctoral grant (No de registro - 3505) awarded to Parth Gupta and in the framework of the national projects DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01), and SomEMBED: SOcial Media language understanding - EMBEDing contexts (TIN2015-71147-C2-1-P). We would like to thank Martin Potthast, Daniel Ortiz-Martinez, and Luis A. Leiva for their support and comments during this research.Franco-Salvador, M.; Gupta, PA.; Rosso, P.; Banchs, R. (2016). Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language. Knowledge-Based Systems. 111:87-99. https://doi.org/10.1016/j.knosys.2016.08.004S879911
Alkylated benzimidazoles: Design, synthesis, docking, DFT analysis, ADMET property, molecular dynamics and activity against HIV and YFV
No full textA series of alkylated benzimidazole derivatives was synthesized and screened for their anti-HIV, anti-YFV, and broad-spectrum antiviral properties. The physicochemical parameters and drug-like properties of the compounds were assessed first, and then docking studies and MD simulations on HIV-RT allosteric sites were conducted to find the possible mode of their action. DFT analysis was also performed to confirm the nature of the hydrogen bonding interaction of active compounds. The in silico studies indicated that the molecules behaved like possible NNRTIs. The nature - polar or non-polar and position of the substituent present at fifth, sixth, and N-1 positions of the benzimidazole moiety played an important role in determining the antiviral properties of the compounds. Among the various compounds, 2-(5,6-dibromo-2-chloro-1H-benzimidazol-1-yl)ethan-1-ol (3a) showed anti-HIV activity with an appreciably low IC50 value as 0.386 × 10-5μM. Similarly, compound 2b, 3-(2-chloro-5-nitro-1H-benzimidazol-1-yl) propan-1-ol, showed excellent inhibitory property against the yellow fever virus (YFV) with EC50 value as 0.7824 × 10-2μM.sponsorship: The author Ritika Srivastava acknowledges financial support in the form of Research Fellowship from the UGC grant, University of Allahabad, Allahabad. Parth Sarthi Sen Gupta sincerely thanks IISER Berhampur, Odisha for postdoctoral fellowship. (IISER Berhampur, Odisha, UGC grant, University of Allahabad, Allahabad)status: Publishe
Methods for cross-language plagiarism detection
No full textThree reasons make plagiarism across languages to be on the rise: (i) speakers of under-resourced languages often consult documentation in a foreign language, (ii) people immersed in a foreign country can still consult material written in their native language, and (iii) people are often interested in writing in a language different to their native one. Most efforts for automatically detecting cross-language plagiarism depend on a preliminary translation, which is not always available.
In this paper we propose a freely available architecture for plagiarism detection across languages covering the entire process: heuristic retrieval, detailed analysis, and post-processing. On top of this architecture we explore the suitability of three cross-language similarity estimation models: Cross-Language Alignment-based Similarity Analysis (CL-ASA), Cross-Language Character n-Grams (CL-CNG), and Translation plus Monolingual Analysis (T + MA); three inherently different models in nature and required resources.
The three models are tested extensively under the same conditions on the different plagiarism detection sub-tasks—something never done before. The experiments show that T+MA produces the best results, closely followed by CL-ASA. Still CL-ASA obtains higher values of precision, an important factor in plagiarism detection when lesser user intervention is desired.Peer ReviewedPostprint (published version
Centrifugal forming and mechanical properties of silicone-based elastomers for soft robotic actuators
No full textThis thesis describes the centrifugal forming and resulting mechanical properties of silicone-based elastomers for the manufacture of soft robotic actuators. This process is effective at removing bubbles that get entrapped within 3D-printed, enclosed molds. Conventional methods for rapid prototyping of soft robotic actuators to remove entrapped bubbles typically involve degassing under vacuum, with open-faced molds that limit the layout of formed parts to raised 2D geometries. As the functionality and complexity of soft robots increase, there is a need to mold complete 3D structures with controlled thicknesses or curvatures on multiples surfaces. In addition, characterization of the mechanical properties of common elastomers for these soft robots has lagged the development of new designs. As such, relationships between resulting material properties and processing parameters are virtually non-existent. One of the goals of this thesis is to provide guidelines and physical insights to relate the design, processing conditions, and resulting properties of soft robotic components to each other. Centrifugal forming with accelerations on the order of 100 g’s is capable of forming bubble-free, true 3D components for soft robotic actuators, and resulting demonstrations in this work include an aquatic locomotor, soft gripper, and an actuator that straightens when pressurized. Finally, this work shows that the measured mechanical properties of 3D geometries fabricated within enclosed molds through centrifugal forming possess comparable mechanical properties to vacuumed materials formed from open-faced molds with raised 2D features.M.S.Includes bibliographical referencesby Parth Kulkarn
Continuous Space Models for CLIR
No full text[EN] We present and evaluate a novel technique for learning cross-lingual continuous space models to aid cross-language information retrieval (CLIR). Our model, which is referred to as external-data composition neural network (XCNN), is based on a composition function that is implemented on top of a deep neural network that provides a distributed learning framework. Different from most existing models, which rely only on available parallel data for training, our learning framework provides a natural way to exploit monolingual data and its associated relevance metadata for learning continuous space representations of language. Cross-language extensions of the obtained models can then be trained by using a small set of parallel data. This property is very helpful for resource-poor languages, therefore, we carry out experiments on the English-Hindi language pair. On the conducted comparative evaluation, the proposed model is shown to outperform state-of-the-art continuous space models with statistically significant margin on two different tasks: parallel sentence retrieval and ad-hoc retrieval.We thank German Sanchis Trilles for helping in conducting experiments with machine translation. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GeForce Titan GPU used for this research. The research of the first author was supported by FPI grant of UPV. The research of the third author is supported by the SomEMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMAMATER (PrometeolI/2014/030).Gupta, P.; Banchs, R.; Rosso, P. (2017). Continuous Space Models for CLIR. Information Processing & Management. 53(2):359-370. https://doi.org/10.1016/j.ipm.2016.11.002S35937053
Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
No full textCross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results in German-English and Spanish-English cross-language plagiarism detection indicate that our knowledge graph-based approach offers a better performance compared to other state-of-the-art models.The research has been carried out in the framework of the European Commission WIQ-EIIRSES (no. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts:Applications (TIN2012-38603-C02-01) projects as well as the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Franco-Salvador, M.; Gupta, P.; Rosso, P. (2013). Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing. En Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures. Springer Verlag (Germany). 227-236. https://doi.org/10.1007/978-3-642-54798-0_12S227236Barrón-Cedeño, A., Vila, M., Martí, M., Rosso, P.: Plagiarism meets paraphrasing: insights for the next generation in automatic plagiarism detection. Computational Linguistics 39(4) (2013)Barrón-Cedeño, A.: On the mono- and cross-language detection of text re-use and plagiarism. Ph.D. thesis, Universitat Politènica de València (2012)Barrón-Cedeño, A., Rosso, P., Pinto, D., Juan, A.: On cross-lingual plagiarism analysis using a statistical model. In: Proc. of the ECAI 2008 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, PAN 2008 (2008)Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using BabelNet’s statistical dictionary. Computación y Sistemas, Revista Iberoamericana de Computación 16(4), 383–390 (2012)Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using a multilingual semantic network. In: Serdyukov, P., Braslavski, P., Kuznetsov, S.O., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., Yilmaz, E. (eds.) ECIR 2013. LNCS, vol. 7814, pp. 710–713. Springer, Heidelberg (2013)Franco-Salvador, M., Gupta, P., Rosso, P.: Graph-based similarity analysis: a new approach to cross-language plagiarism detection. Journal of the Spanish Society of Natural Language Processing (Sociedad Espaola de Procesamiento del Languaje Natural) (50) (2013)Montes-y-Gómez, M., Gelbukh, A., López-López, A., Baeza-Yates, R.: Flexible comparison of conceptual graphs. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 102–111. Springer, Heidelberg (2001)Gupta, P., Barrón-Cedeño, A., Rosso, P.: Cross-language high similarity search using a conceptual thesaurus. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 67–75. Springer, Heidelberg (2012)Mcnamee, P., Mayfield, J.: Character n-gram tokenization for European language text retrieval. Information Retrieval 7(1), 73–97 (2004)Miller, G.A., Leacock, C., Tengi, R., Bunker, R.T.: A semantic concordance. In: Proceedings of the Workshop on Human Language Technology, HLT 1993, pp. 303–308. Association for Computational Linguistics, Stroudsburg (1993)Navigli, R., Ponzetto, S.P.: BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence 193, 217–250 (2012)Och, F.J., Ney, H.: A systematic comparison of various statistical alignment models. Computational Linguistics 29(1), 19–51 (2003)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: An evaluation framework for plagiarism detection. In: Proc. of the 23rd Int. Conf. on Computational Linguistics, COLING 2010, Beijing, China, pp. 997–1005 (2010)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Language Resources and Evaluation, Special Issue on Plagiarism and Authorship Analysis 45(1), 45–62 (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd int. competition on plagiarism detection. In: CLEF (Notebook Papers/Labs/Workshop) (2011)Potthast, M., Gollub, T., Hagen, M., Kiesel, J., Michel, M., Oberländer, A., Tippmann, M., Barrón-Cedeño, A., Gupta, P., Rosso, P., et al.: Overview of the 4th international competition on plagiarism detection. In: CLEF (Online Working Notes/Labs/Workshop) (2012)Pouliquen, B., Steinberger, R., Ignat, C.: Automatic linking of similar texts across languages. In: Proc. Recent Advances in Natural Language Processing III, RANLP 2003, pp. 307–316 (2003)Schmid, H.: Probabilistic part-of-speech tagging using decision trees. In: Proc. Int. Conf. on New Methods in Language Processing (1994)Stein, B., zu Eissen, S.M., Potthast, M.: Strategies for retrieving plagiarized documents. In: Proc. of the 30th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 825–826. ACM (2007)Steinberger, R., Pouliquen, B., Widiger, A., Ignat, C., Erjavec, T., Tufis, D., Varga, D.: The jrc-acquis: A multilingual aligned parallel corpus with +20 languages. In: Proc. 5th Int. Conf. on Language Resources and Evaluation, LREC 2006 (2006)Vossen, P.: Eurowordnet: A multilingual database of autonomous and language-specific wordnets connected via an inter-lingual index. Proc. Int. Journal of Lexicography 17 (2004
Cross-language plagiarism detection using multilingual semantic network
No full textThe final publication is available at Springer via http://10.1007/978-3-642-36973-5_66Cross-language plagiarism refers to the type of plagiarism where the source and suspicious documents are in different languages. Plagiarism detection across languages is still in its infancy state. In this article, we propose a new graph-based approach that uses a multilingual semantic network to compare document paragraphs in different languages. In order to investigate the proposed approach, we used the German-English and Spanish-English cross-language plagiarism cases of the PAN-PC¿11 corpus. We compare the obtained results with two state-of-the-art models. Experimental results indicate that our graph-based approach is a good alternative for cross-language plagiarism detectionWe thank the Conselleria d′educació, Formació i Ocupació of the Generalitat Valenciana for funding the work of the first author with the Gerónimo Forteza program. The research has been carried out in the framework of the European Commission WIQ-EI IRSES project (no. 269180) and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Franco Salvador, M.; Gupta, PA.; Rosso ., P. (2013). Cross-language plagiarism detection using multilingual semantic network. En Advances in Information Retrieval. Springer Verlag (Germany). 7814:710-713. https://doi.org/10.1007/978-3-642-36973-5_66S7107137814Barrón-Cedeño, A.: On the mono- and cross-language detection of text re-use and plagiarism. Ph.D. thesis, Universitat Politènica de València (2012)Barrón-Cedeño, A., Rosso, P., Pinto, D., Juan, A.: On cross-lingual plagiarism analysis using a statistical model. In: Proceedings of the ECAI 2008 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, PAN 2008 (2008)Havasi, C.: Conceptnet 3: A flexible, multilingual semantic network for common sense knowledge. In: The 22nd Conference on Artificial Intelligence (2007)Mcnamee, P., Mayfield, J.: Character n-gram tokenization for European language text retrieval. Inf. Retr. 7(1-2), 73–97 (2004)Montes-y-Gómez, M., Gelbukh, A., López-López, A., Baeza-Yates, R.: Flexible Comparison of Conceptual GraphsWork done under partial support of CONACyT, CGEPI-IPN, and SNI, Mexico. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 102–111. Springer, Heidelberg (2001)Navigli, R., Ponzetto, S.P.: Babelnet: building a very large multilingual semantic network. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010, Stroudsburg, PA, USA, pp. 216–225 (2010)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Language Resources and Evaluation, Special Issue on Plagiarism and Authorship Analysis 45(1) (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd international competition on plagiarism detection. In: CLEF (Notebook Papers/Labs/Workshop) (2011
Knowledge engineering for modern information systems: methods, models and tools De Gruyter series on smart computing applications ;, v. 3./ edited by Anand Sharma, Sandeep Kautish, Prateek Agrawal, Vishu Madaan, Charu Gupta, Saurav Nanda.
No full textIncludes bibliographical references and index.Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledge based systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artificial Intelligence, Cognitive Neuroscience, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.P. Megaladevi -- Saikat Samanta, Achyuth Sarkar, Charu Gupta, Aditi Sharma -- Kudirat Abiola Adegoke, Akor P. Usman, Mohamed Bitagi -- Anagha Shenoy R, Bhoomika M, Annaiah H -- Neeraj Bhanot, Parth Padalkar -- Shubhika Gaur, Vibha Maheshwari -- Sanjive Saxena -- Ria Rawal, Kartik Goel, Akshay Gulati, Shivang Sharma, Palak Girdhar, Charu Gupta, Prateek Agrawal -- A. Ilmudeen -- Andualem Walelign Lale -- Hazik Mohamed -- Priyanka Jain, Ram Bhavsar, B.V. Pawar, N.K. Jain, Hemant Darbari, Virendrakumar C. Bhavsar. Knowledge engineering for industrial expert systems / Machine learning integrated blockchain model for Industry 4.0 smart applications / Prototyping the expectancy disconfirmation theory model for quality service delivery in federal university libraries in Nigeria / Design of chatbot using natural language processing / Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors / Risk analysis and management in projects / Assessing and managing risks in smart computing applications / COVID-19 visualization and exploratory data analysis / Business intelligence and decision support systems: business applications in the modern information system era / Business intelligence implementation in different organizational setup evidence from reviewed literatures / Conceptualization of a modern digital-driven health-care management information system (HMIS) / Knowledge engine for a Hindi text-to-scene generation system /1 online resource (vi, 232 pages)
Characterization and optimization of UAV power system for aerial and submersible multi-medium multirotor vehicle
No full textEven as an emerging technology, Unmanned Aerial Vehicles (UAVs) have had a tremendous impact on the world. From the way wars are fought, to the way we take selfies, drones are well on their way to revolutionizing our daily lives. One of the most innovative applications of these vehicles in the Naviator submersible-UAV. This unique multirotor is capable of aerial flight and underwater operations with seamless Air-Water transitions. In this thesis, the power system of a multirotor UAS is characterized using standard performance models with the goal of designing and optimizing the systems of a new Naviator V5 prototype. Test beds were created to collect data on BLDC motors and propellers and their performance was assessed in air and water. Theoretical models using BEM theory and the 3-constant motor model were validated for their accuracy. Experiments found that RC air propellers are similarly efficient in air and water and BLDC motor performance is partially diminished due to the higher viscosity of water. The effects of input voltage, throttle, Kv rating, and motor size were also evaluated using motor torque curves. Using this data, an optimal power system for the Naviator V5 prototype was designed, tested, and evaluated.M.S.T.Includes bibliographical referencesby Parth V. Son
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