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Foundations of software science and computation structures ; 24th International conference, FOSSACS 2021, Held as Part of the European joint conferences on theory and practice of software, ETAPS 2021, Luxembourg City, Luxembourg, March 27 – April 1, 2021, proceedings
This book constitutes the proceedings of the 24th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2021, which was held during March 27 until April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic.
Finite-state methods and natural language processing ; 5th International Workshop, FSMNLP 2005, Helsinki, Finland, September 1-2, 2005, Revised Papers
This book constitutes the thoroughly refereed post-proceedings of the 5th International Workshop on Finite-State Methods in Natural Language Processing, FSMNLP 2005, held in Helsinki, Finland, September 2005. The book presents 24 revised full papers and seven revised poster papers together with two invited contributions and abstracts of six software demos. Topics include morphology, optimality theory, some special FSM families, weighted FSM algorithms, FSM representations, exploration, ordered structures, and surface parsing.
Dream catcher
Dream Catcher is a video generation application that helps in many fields as science fiction, imagine event’s scenarios, education, animation and montage. By applying artificial algorithms implemented and trained on a dataset containing video samples and there descriptions to generate videos from any given text. The idea of generating videos from text is a new idea that was first presented at 2017, even that international companies like Google and OpenAi In the last year, was working on developing models to generate images from text. To make it easier to use the application, there are many ways to enter the text either by an image, voice or Typing from the keyboard.
Digitization of healthcare data using blockchain
Gives a detailed description of the integration of blockchain technology for Electronic Health Records and provides the research challenges to consider in various disciplines such as supply chain, drug discovery, and data management. he aim of the book is to investigate the concepts of blockchain technology and its association with the recent development and advancements in the medical field. Moreover, it focuses on the integration of workflow strategies like NLP, and AI which could be adopted for boosting the clinical documentation and electronic healthcare records (EHR) usage by bringing down the physician EHR data entry. Also, the book covers the usage of smart contracts for securing patient records. Digitization of Healthcare Data Using Blockchain presents the practical implementations that deal with developing a web framework for building highly usable healthcare applications, a simple blockchain-powered EHR system.
Developing secure auto-scaling military postponement e-service in Syria
This study is about developing a secure, autoscaling military postponement e-service in Syria, that allows Syrian citizens to conveniently access services provided by the Syrian Recruitment Department conveniently through their smartphones. Currently, many Syrian citizens need to use the services offered by the Recruitment Department, resulting in overcrowding in a single location for similar purposes. This situation places a significant burden on both citizens and the government. The mobile application will facilitate various services such as enlistment and postponing military service by employing a well-designed software architecture that ensures scalability and efficient distribution of these services.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Deep Learning with PyTorch Lightning : Build and train high-performance artificial intelligence and self-supervised models using Python
You’ll learn how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. You’ll build a neural network architecture, deploy an application from scratch, and see how you can expand it based on your specific needs, beyond what the framework can provide. In the later chapters, you’ll also learn how to implement capabilities to build and train various models like Convolutional Neural Nets (CNN), Natural Language Processing (NLP), Time Series, Self-Supervised Learning, Semi-Supervised Learning, Generative Adversarial Network (GAN) using PyTorch Lightning.
Constraint solving and language processing
Contains selected and thoroughly revised papers plus contributions from invited speakers presented at the First International Workshop on C- straint Solving and Language Processing, held in Roskilde, Denmark, September 1–3, 2004. Constraint Programming and Constraint Solving, in particular Constraint Logic Programming, appear to be a very promising platform, perhaps the most promising present platform, for bringing forward the state of the art in natural language processing, this due to the naturalness in speci?cation and the direct relation to e?cient implementation. Language, in the present context, may - fer to written and spoken language, formal and semiformal language, and even general input data to multimodal and pervasive systems, which can be handled in very much the same ways using constraint programming. The notion of constraints, with slightly differing meanings, apply in the characterization of linguistic and cognitive phenomena, in formalized linguistic m- els as well as in implementation-oriented frameworks. Programming techniques for constraint solving have been, and still are, in a period with rapid devel- ment of new eficient methods and paradigms from which language processing can prompt. A common metaphor for human language processing is one big c- straint solving process in which the differently specified linguistic and cognitive phases take place in parallel and with mutual cooperation, which ?ts quite well with current constraint programming paradigms.
Computing Attitude and Affect in Text : Theory and Applications
Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the “factual” aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented.
Computer Vision Metrics : Survey, Taxonomy, and Analysis
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more.
Computational Processing of the Portuguese Language ; 8th International Conference, PROPOR 2008 Aveiro, Portugal, September 8-10, 2008 Proceedings
This book constitutes the thoroughly refereed proceedings of the 8th International Workshop on Computational Processing of the Portuguese Language, PROPOR 2008, held in Aveiro, Portugal, in September 2008.
Computational Processing of the Portuguese Language ; 7th International Workshop, PROPOR 2006, Itatiaia, Brazil, May 13-17, 2006, Proceedings
Since 1993, PROPOR Workshops have become an important forum for - searchers involved in the Computational Processing of Portuguese,both written and spoken. The workshop and this book were structured around the following main t- ics, seven for full papers: (i) automatic summarization; (ii) resources; (iii) au- matic translation; (iv) named entity recognition; (v) tools and frameworks; (vi) systems and models; and another ?ve topics for short papers; (vii) information extraction; (viii) speech processing; (ix) lexicon; (x) morpho-syntactic studies; (xi) web, corpus and evaluation.
Computational linguistics and intelligent text processing ; 9th International Conference, CICLing 2008, Haifa, Israel, February 17-23, 2008. Proceedings
The CICLing conferences are intended to provide a wide-scope forum for the discussion of both the art and craft of natural language processing research and the best practices in its applications. This volume contains the papers accepted for oral presentation at the c- ference, as well as several of the best papers accepted for poster presentation.
Computational linguistics and intelligent text processing ; 8th International Conference, CICLing 2007, Mexico City, Mexico, February 18-24, 2007, Proceedings
This book cover all current issues in computational linguistics research and present intelligent text processing applications. The papers are organized in topical sections on: lexical resources, corpus-based knowledge acquisition, morphology and part-of-speech tagging, named entity recognition, temporal expression treatment, word segmentation, sentence splitting, chunking, grammar formalisms and syntax, word sense disambiguation and discrimination and semantics.
Computational linguistics and intelligent text processing ; Vol. 3406 ; 6th International Conference, CICLing 2005, Mexico City, Mexico, February 13-19, 2005, Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2005, held in Mexico City, Mexico in February 2005. An approach that involves natural language analysis techniques for the treatment of software system functional requirements is described in this book. This approach is used as the basis for a process developed to generate sequence diagrams automatically from the textual specification of use cases. This facility has been integrated in the Requirements Engineering Phase of OO-Method, an automatic production environment of software. For this purpose, a translator that is based on natural language parser is used. The translator provides grammatical information to each use case sentence and it identifies the corresponding interaction. The automatic transformation is conceived and specified following an orientation that is based on models and patterns. The results of the validation of the transformation patterns are presented.
Computational Forensic ; 2nd International Workshop, IWCF 2008, Washington, DC, USA, August 7-8, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Workshop, IWCF 2008, held in Washington, DC, USA, August 2008. The papers are organized in topical sections on trends and challenges; scanner, printer, and prints; human identification; shoeprints; linguistics;decision making and search; speech analysis; signatures and handwriting.
Combinatorial pattern matching ; 19th Annual Symposium, CPM 2008, Pisa, Italy, June 18-20, 2008 Proceedings
This book constitutes the refereed proceedings of the 19th Annual Symposium on Combinatorial Pattern Matching, CPM 2008, held in Pisa, Italy, in June 2008.
Collaboration Technologies and Social Computing ; 26th International Conference, CollabTech 2020, Tartu, Estonia, September 8–11, 2020, Proceedings
This book constitutes the proceedings of the 26th International Conference on Collaboration Technologies and Social Computing, CollabTech 2020. The conference was scheduled to take place in Tartu, Estonia, in September 2020. It was held virtually due to the COVID-19 pandemic. The 10 full and 5 work-in-progress papers presented in this volume were carefully reviewed and selected from 25 submissions.
Markov Models for Pattern Recognition : From Theory to Applications
Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
