XLIndy: interactive recognition and information extraction in spreadsheets

Over the years, spreadsheets have established their presence in many domains, including business, government, and science. However, challenges arise due to spreadsheets being partially-structured and carrying implicit (visual and textual) information. This translates into a bottleneck, when it comes to automatic analysis and extraction of information. Therefore, we present XLIndy, a Microsoft Excel add-in with a machine learning back-end, written in Python. It showcases our novel methods for layout inference and table recognition in spreadsheets. For a selected task and method, users can visually inspect the results, change configurations, and compare different runs. This enables iterative fine-tuning. Additionally, users can manually revise the predicted layout and tables, and subsequently save them as annotations. The latter is used to measure performance and (re-)train classifiers. Finally, data in the recognized tables can be extracted for further processing. XLIndy supports several standard formats, such as CSV and JSON.Peer ReviewedPostprint (author's final draft

FPGA-Based PUF Designs: A Comprehensive Review and Comparative Analysis

Field-programmable gate arrays (FPGAs) have firmly established themselves as dynamic platforms for the implementation of physical unclonable functions (PUFs). Their intrinsic reconfigurability and profound implications for enhancing hardware security make them an invaluable asset in this realm. This groundbreaking study not only dives deep into the universe of FPGA-based PUF designs but also offers a comprehensive overview coupled with a discerning comparative analysis. PUFs are the bedrock of device authentication and key generation and the fortification of secure cryptographic protocols. Unleashing the potential of FPGA technology expands the horizons of PUF integration across diverse hardware systems. We set out to understand the fundamental ideas behind PUF and how crucially important it is to current security paradigms. Different FPGA-based PUF solutions, including static, dynamic, and hybrid systems, are closely examined. Each design paradigm is painstakingly examined to reveal its special qualities, functional nuances, and weaknesses. We closely assess a variety of performance metrics, including those related to distinctiveness, reliability, and resilience against hostile threats. We compare various FPGA-based PUF systems against one another to expose their unique advantages and disadvantages. This study provides system designers and security professionals with the crucial information they need to choose the best PUF design for their particular applications. Our paper provides a comprehensive view of the functionality, security capabilities, and prospective applications of FPGA-based PUF systems. The depth of knowledge gained from this research advances the field of hardware security, enabling security practitioners, researchers, and designers to make wise decisions when deciding on and implementing FPGA-based PUF solutions.publishedVersio

SISO Space Reference FOM - Tools and Testing

The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE

A Newcomer's Guide to EICS, the Engineering Interactive Computing Systems Community

[EN] Welcome to EICS, the Engineering Interactive Computing Systems community, PACMHCI/EICS journal, and annual conference! In this short article, we introduce newcomers to the field and to our community with an overview of what EICS is and how it positions with respect to other venues in Human-Computer Interaction, such as CHI, UIST, and IUI, highlighting its legacy and paying homage to past scientific events from which EICS emerged. We also take this opportunity to enumerate and exemplify scientific contributions to the field of Engineering Interactive Computing Systems, which we hope to guide researchers and practitioners towards making their future PACMHCI/EICS submissions successful and impactful in the EICS community.We acknowledge the support of MetaDev2 as the main sponsor of EICS 2019. We would like to thank the Chairs of all the tracks of the EICS 2019 conference, the members of the local organization team, and the web master of the EICS 2019 web site. EICS 2019 could not have been possible without the commitment of the Programme Committee members and external reviewers. This work was partially supported by the Spanish Ministry of Economy, Industry and Competitiveness, State Research Agency / European Regional Development Fund under Vi-SMARt (TIN2016-79100-R), the Junta de Comunidades de Castilla-La Mancha European Regional Development Fund under NeUX (SBPLY/17/180501/000192) projects, the Generalitat Valenciana through project GISPRO (PROMETEO/2018/176), and the Spanish Ministry of Science and Innovation through project DataME (TIN2016-80811-P).López-Jaquero, VM.; Vatavu, R.; Panach, JI.; Pastor López, O.; Vanderdonckt, J. (2019). A Newcomer's Guide to EICS, the Engineering Interactive Computing Systems Community. Proceedings of the ACM on Human-Computer Interaction. 3:1-9. https://doi.org/10.1145/3300960S193Bastide, R., Palanque, P., & Roth, J. (Eds.). (2005). Engineering Human Computer Interaction and Interactive Systems. Lecture Notes in Computer Science. doi:10.1007/b136790Beaudouin-Lafon, M. (2004). Designing interaction, not interfaces. Proceedings of the working conference on Advanced visual interfaces - AVI ’04. doi:10.1145/989863.989865Bodart, F., & Vanderdonckt, J. (Eds.). (1996). Design, Specification and Verification of Interactive Systems ’96. Eurographics. doi:10.1007/978-3-7091-7491-3Gallud, J. A., Tesoriero, R., Vanderdonckt, J., Lozano, M., Penichet, V., & Botella, F. (2011). Distributed user interfaces. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems - CHI EA ’11. doi:10.1145/1979742.1979576Graham, T. C. N., & Palanque, P. (Eds.). (2008). Interactive Systems. Design, Specification, and Verification. Lecture Notes in Computer Science. doi:10.1007/978-3-540-70569-7Proceedings of the 1st ACM SIGCHI symposium on Engineering interactive computing systems - EICS ’09. (2009). doi:10.1145/1570433Lawson, J.-Y. L., Vanderdonckt, J., & Vatavu, R.-D. (2018). Mass-Computer Interaction for Thousands of Users and Beyond. Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. doi:10.1145/3170427.3188465Lozano, M. D., Galllud, J. A., Tesoriero, R., Penichet, V. M. R., Vanderdonckt, J., & Fardoun, H. (2013). 3rd workshop on distributed user interfaces. Proceedings of the 5th ACM SIGCHI symposium on Engineering interactive computing systems - EICS ’13. doi:10.1145/2494603.2483222Proceedings of the 2014 Workshop on Distributed User Interfaces and Multimodal Interaction - DUI ’14. (2014). doi:10.1145/2677356Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems. (2019). doi:10.1145/3319499Tesoriero, R., Lozano, M., Vanderdonckt, J., Gallud, J. A., & Penichet, V. M. R. (2012). distributed user interfaces. CHI ’12 Extended Abstracts on Human Factors in Computing Systems. doi:10.1145/2212776.2212704Vanderdonckt, J. (2005). A MDA-Compliant Environment for Developing User Interfaces of Information Systems. Active Flow and Combustion Control 2018, 16-31. doi:10.1007/11431855_2Vatavu, R.-D. (2012). User-defined gestures for free-hand TV control. Proceedings of the 10th European conference on Interactive tv and video - EuroiTV ’12. doi:10.1145/2325616.2325626Vatavu, R.-D. (2017). Beyond Features for Recognition: Human-Readable Measures to Understand Users’ Whole-Body Gesture Performance. International Journal of Human–Computer Interaction, 33(9), 713-730. doi:10.1080/10447318.2017.1278897Wobbrock, J. O., & Kientz, J. A. (2016). Research contributions in human-computer interaction. Interactions, 23(3), 38-44. doi:10.1145/290706

Model-driven engineering techniques and tools for machine learning-enabled IoT applications: A scoping review

This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services.info:eu-repo/semantics/publishedVersio

Applications in security and evasions in machine learning : a survey

In recent years, machine learning (ML) has become an important part to yield security and privacy in various applications. ML is used to address serious issues such as real-time attack detection, data leakage vulnerability assessments and many more. ML extensively supports the demanding requirements of the current scenario of security and privacy across a range of areas such as real-time decision-making, big data processing, reduced cycle time for learning, cost-efficiency and error-free processing. Therefore, in this paper, we review the state of the art approaches where ML is applicable more effectively to fulfill current real-world requirements in security. We examine different security applications' perspectives where ML models play an essential role and compare, with different possible dimensions, their accuracy results. By analyzing ML algorithms in security application it provides a blueprint for an interdisciplinary research area. Even with the use of current sophisticated technology and tools, attackers can evade the ML models by committing adversarial attacks. Therefore, requirements rise to assess the vulnerability in the ML models to cope up with the adversarial attacks at the time of development. Accordingly, as a supplement to this point, we also analyze the different types of adversarial attacks on the ML models. To give proper visualization of security properties, we have represented the threat model and defense strategies against adversarial attack methods. Moreover, we illustrate the adversarial attacks based on the attackers' knowledge about the model and addressed the point of the model at which possible attacks may be committed. Finally, we also investigate different types of properties of the adversarial attacks

Improving the translation environment for professional translators

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project