Fused Text Recogniser and Deep Embeddings Improve Word Recognition and Retrieval

Recognition and retrieval of textual content from the large document collections have been a powerful use case for the document image analysis community. Often the word is the basic unit for recognition as well as retrieval. Systems that rely only on the text recogniser (OCR) output are not robust enough in many situations, especially when the word recognition rates are poor, as in the case of historic documents or digital libraries. An alternative has been word spotting based methods that retrieve/match words based on a holistic representation of the word. In this paper, we fuse the noisy output of text recogniser with a deep embeddings representation derived out of the entire word. We use average and max fusion for improving the ranked results in the case of retrieval. We validate our methods on a collection of Hindi documents. We improve word recognition rate by 1.4 and retrieval by 11.13 in the mAP.Comment: 15 pages, 8 figures, Accepted in IAPR International Workshop on Document Analysis Systems (DAS) 2020, "Visit project page, at http://cvit.iiit.ac.in/research/projects/cvit-projects/fused-text-recogniser-and-deep-embeddings-improve-word-recognition-and-retrieval

Community College Advisors\u27 Understandings and Uses of Colorado Statewide Transfer Articulation Policy

This interpretivist descriptive case study examines how community college academic advisors understand and use Colorado statewide transfer articulation policy (STAP) in their work with transfer students. Using systems theory to analyze data collected through 28 semi-structured individual interviews, document review, and field notes, I describe how academic advisors at a selected two-year institution understand and use STAP. The final product includes a rich and thick description of the findings presented through a systems theory framework. Among this study’s primary findings is that academic advisors’ understandings of STAP affects the ways they use articulation. Participants understand that STAP can improve advising by creating pathways, providing assurance, protecting credits, standardizing the transfer process, and supporting state goals. Based on these understandings, advisors use STAP to providing guidance and build confidence in their work with transfer students. My analysis of interview data reveals that advisors’ understandings emerge through their use of STAP in the daily work of problem-solving with students. Using systems theory analysis allows for a discussion of findings and provide recommendations for future research. Implications of this study include recommendation for policy makers, institutional leaders, faculty, and academic advisors iv responsible for creating, updating, and implementing statewide transfer articulation policy

Are Meaningful Use Stage 2 certified EHRs ready for interoperability? Findings from the SMART C-CDA Collaborative

Background and objective Upgrades to electronic health record (EHR) systems scheduled to be introduced in the USA in 2014 will advance document interoperability between care providers. Specifically, the second stage of the federal incentive program for EHR adoption, known as Meaningful Use, requires use of the Consolidated Clinical Document Architecture (C-CDA) for document exchange. In an effort to examine and improve C-CDA based exchange, the SMART (Substitutable Medical Applications and Reusable Technology) C-CDA Collaborative brought together a group of certified EHR and other health information technology vendors. Materials and methods We examined the machine-readable content of collected samples for semantic correctness and consistency. This included parsing with the open-source BlueButton.js tool, testing with a validator used in EHR certification, scoring with an automated open-source tool, and manual inspection. We also conducted group and individual review sessions with participating vendors to understand their interpretation of C-CDA specifications and requirements. Results: We contacted 107 health information technology organizations and collected 91 C-CDA sample documents from 21 distinct technologies. Manual and automated document inspection led to 615 observations of errors and data expression variation across represented technologies. Based upon our analysis and vendor discussions, we identified 11 specific areas that represent relevant barriers to the interoperability of C-CDA documents. Conclusions: We identified errors and permissible heterogeneity in C-CDA documents that will limit semantic interoperability. Our findings also point to several practical opportunities to improve C-CDA document quality and exchange in the coming years

Document analysis with neural net circuits

Document analysis is one of the main applications of machine vision today and offers great opportunities for neural net circuits. Despite more and more data processing with computers, the number of paper documents is still increasing rapidly. A fast translation of data from paper into electronic format is needed almost everywhere, and when done manually, this is a time consuming process. Markets range from small scanners for personal use to high-volume document analysis systems, such as address readers for the postal service or check processing systems for banks. A major concern with present systems is the accuracy of the automatic interpretation. Today's algorithms fail miserably when noise is present, when print quality is poor, or when the layout is complex. A common approach to circumvent these problems is to restrict the variations of the documents handled by a system. In our laboratory, we had the best luck with circuits implementing basic functions, such as convolutions, that can be used in many different algorithms. To illustrate the flexibility of this approach, three applications of the NET32K circuit are described in this short viewgraph presentation: locating address blocks, cleaning document images by removing noise, and locating areas of interest in personal checks to improve image compression. Several of the ideas realized in this circuit that were inspired by neural nets, such as analog computation with a low resolution, resulted in a chip that is well suited for real-world document analysis applications and that compares favorably with alternative, 'conventional' circuits

Automatic Generation of Data Flow Diagrams From A Requirements Specification Language

Escalating manpower costs in developing systems has caused an increasing need for greater productivity in system development particularly in the analysis and design phases. Productivity in the system analysis phase can be increased with the use of computer- aided tools such as SPSL/SPSA for specifying system requirements and methodologies such as structured analysis. A structured analysis and documentation tool-the data flow diagram-allows an analyst to model and document a system with relative ease; however, the manual production of a data flow diagram is a time consuming process Combining the production of data flow diagrams with SPSL/SPSA produces a synergistic effect on the increases in productivity and ensures the use of standards andthe completenessof the diagram. This paperdescribes the problems and design of the systemMONDRIAN that generates data flow diagrams from an SPSA database. A variety of placement and routing algorithms that address the layout problem are discussed. The results of a preliminary study of the effectiveness of these algorithms and the adaptations required to improve and refine the prototype version of MONDRIAN are presented

WorkMail: collaborative document workflow by email

Processing documents is a critical and crucial aspect in an enterprise environment. The management of documents involves several people and many times becomes a long and wasting-time process. Many systems of document workflow have been proposed but usually they are too rigid and complex. Therefore we have developed a document workflow engine based on the email paradigm. When a user wants to make an order, a request of authorization and, in general, any kind of procedure that involve a document, starts her/his request by filling in a form and sending it by attaching it to an email. To this purpose the user has to use our web application that appears as a normal webmail client. Our solution overcomes the actual limitation in the use of document workflow software, especially for what concern the user experience; with our system there is no need, for users, to learn the functioning of a new framework. In addition, users with different roles have different customized view of the document. According with the roles of the users, we trained the system to suggest to the user, at each step, a possible receiver of the email. Currently this feature is based on the fact that the system knows in advance the flow associated with different type of documents. As improvement, we will perform a statistical analysis of interactions between senders and receivers. This analysis will be used to improve the suggestion mechanism: the system will learn the most frequent interactions for each user, depending on the history of previous flow and the document involved. Exploiting these information, the suggestion mechanism will advise to the user the possible receiver of the document

Unsupervised Polygonal Reconstruction of Noisy Contours by a Discrete Irregular Approach

International audienceIn this paper, we present an original algorithm to build a polygonal reconstruction of noisy digital contours. For this purpose, we first improve an algorithm devoted to the vectorization of discrete irregular isothetic objects. Afterwards we propose to use it to define a reconstruction process of noisy digital contours. More precisely, we use a local noise detector, introduced by Kerautret and Lachaud in IWCIA 2009, that builds a multi-scale representation of the digital contour, which is composed of pixels of various size depending of the local amount of noise. Finally, we compare our approach with previous works, by con- sidering the Hausdorff distance and the error on tangent orientations of the computed line segments to the original perfect contour. Thanks to both synthetic and real noisy objects, we show that our approach has interesting performance, and could be applied in document analysis systems

ENTERPRISE CONTENT MANAGEMENT SYSTEM IMPLEMENTATION READINESS TO IMPROVE MEDICAL RECORDS MANAGEMENT IN LIMPOPO PROVINCE, SOUTH AFRICA

This study sought to establish readiness for implementation of ECM to improve medical records management in the public hospitals of the Limpopo Province in South Africa. The use of digital systems such as enterprise content management (ECM) to manage medical records is fundamental to ensure timely access, sharing and use of the medical records by healthcare providers and hospital management. This is because timely access to medical records will result in timely healthcare service delivery to the patients. There have been many different kinds of digital systems applied in different organisations for different categories of records throughout the world. Quantitative data were collected through questionnaires directed to the Records Management Units at the public hospitals in the Limpopo Province of South Africa supported with observation and document/system analysis. The study reveals that the hospitals in the Limpopo Province had not yet implemented ECM as a system and had limited IT resources like computers, printers, servers, network points and internet access. This study appears to be the first of its nature to investigate the readiness of the hospitals in Limpopo province of South Africa for implementation of enterprise content management system. The study recommends that ECM be implemented to improve medical records management in the public hospitals of Limpopo since the hospitals had no effective systems for proper management of medical records

Sustainable technologies for aircraft energy generation, storage, and distribution

It is estimated that the contribution of the aviation industry to global warming is currently 2-3%. The projected growth of the industry may increase this to 10-20% by 2050. As such, the aim of this research is to explore how proposed aircraft energy generation, storage, and distribution technologies can improve sustainability in the aviation industry. The primary research question addressed by this work is: What are the current technological trends in aircraft energy generation, storage, and distribution and how much will these technologies help reduce the aviation industries contribution to climate change? An explanatory case study methodology was utilised in this research. A number of research tools were used, specifically document analysis, trend analysis, and technology forecasting methods. The technological developments were identified with a preliminary document analysis. The trend analysis identified which technologies were of importance in terms of the historical development and technology effectiveness. A number of trends were identified in aircraft technologies for energy generation, storage and distribution to improve sustainability. The primary consideration identified was energy storage. That is, energy generation and distribution technologies are a significant facet of future more electric aircraft, and even all-electric aircraft. However, the key enabling technology is the storage of energy, specifically the energy densities in terms of either battery capacity, or hydrogen storage (for use with fuel cells). Aircraft energy generation, storage, and distribution technologies are a single facet of the airframe and avionic systems for greener aircraft; the contributions from other facets maybe more significant, specifically in terms of fuels and engines