Integration of traditional imaging, expert systems, and neural network techniques for enhanced recognition of handwritten information

Includes bibliographical references (p. 33-37).Research supported by the I.F.S.R.C. at M.I.T.Amar Gupta, John Riordan, Evelyn Roman

Decision Fusion and Contextual Information for Arabic Words Recognition for Computing and Informatics

The study of multiple classifier systems has become recently an area of intensive research in pattern recognition. Also in handwriting recognition, systems combining several classifiers have been investigated. An approach for recognizing the legal amount for handwritten Arabic bank check is described in this article. The solution uses multiple information sources to recognize words. The recognition step is preformed with a parallel combination of three kinds of classifiers using holistic word structural features. The classification stage results are first normalized, and the sum combination is performed as a decision fusion scheme, after which a syntactic analyzer makes final decision on the candidate words. Using this approach, the obtained results are very interesting and promising

Oceanus.

v. 26, no. 2 (1983

Solving the ‘Wicked Problem’ of China’s Environmental Future: Cautious Optimism in the Face of Unprecedented Threats

China’s global position as an exporter of inexpensive, low-value goods has been sustained by a coal-fired growth model whose devastating environmental and social consequences are only recently being acknowledged properly by party leadership. A systematic review and analysis has been conducted of the most current academic literature addressing China’s environmental challenges. A sizeable amount of research (around 360 publications) was amassed in this pursuit, covering not only China’s environment, but also related governmental, economic, and social factors. The author has defined China\u27s environmental future as a \u27wicked problem\u27, which creates two allowances by default. First, it communicates that the problem is highly complex, involves multiple stakeholders, and has no easy solutions. Second, it recognizes that only a uniquely multi- sectoral approach can achieve accurate forecasting and sound recommendations. This paper follows this multi-sectoral approach, crossing institutional lines in search of developments economically and politically, as well as prevailing trends in both technology and culture. Scenario building of divergent futures has been visualized in order to generate confident and informed forecasting of China\u27s environmental future. The author remains cautiously optimistic regarding these future projections. However, heroic innovations in technology and environmental efficiency must be matched by seismic shifts in economic, social, and political policy. Real solutions and recommendations are prescribed in the final section of this Capstone. The importance of these recommendations cannot be overestimated. Expert consensus has equated humanity\u27s avoidance of climate fallout with the need for transformative solutions in China

Appraisal of Cashless Policy on the Nigerian Financial System

The Central Bank of Nigeria (CBN) has been active in the inauguration of policies and schemes to foster the implementation of the cashless policy in Nigeria. However the current transition to cashless economy raises a lot of concerns with no substantial evidence yet to justify its implementation. This study was carried out in order to appraise the implementation of the cashless policy since its introduction into the Nigerian financial system in 2012 and also to examine the persistent challenges facing its implementation. In view of the above stated objective, primary data were collected with the aid of the questionnaire, which was randomly administered to 120 respondents ranging from First Bank, Zenith Bank and United Bank for Africa. The banks were selected based on their total assets and the information collected covered the activities of the CBN and that of these banks towards implementation of the cashless policy from 2012 till date.The data collected were presented and analyzed with the aid of the Statistical Package for Social Sciences (SPSS) using descriptive statistics and one-sample t-test. The results led to the conclusion that despite the need to operate cashless transactions dominating the modern Nigerian economy, the cashless policy will have the desired impact only if a lot is done to ensure the implementation of an effective cashless system

Spartan Daily, March 2, 1981

Volume 76, Issue 24https://scholarworks.sjsu.edu/spartandaily/6728/thumbnail.jp

The role of communicative creativity in starting regional trade relationships with China: An action research practitioner case study

The Action Research project studies the role of information management and knowledge generation in establishing overseas political and trade activity to assist regional development in Australia. It is the work of a researcher whose background in information management ranges across more than 30 years working in the newspaper and regional economic development industries. It applies a hybrid term called “communicative creativity” – distilled from Wieman’s (1963) Doctrine of Creative Interchange and Habermas’s (1984) Theory of Communicative Action – to the researcher’s professional practice of facilitating the development of two entities – the economic development organization and its method of facilitating opportunities in China – against Nonaka and Takeuchi’s (1995) Five-Phase Model of the Organisational Creation Process. The thesis describes how the researcher’s previous career and life experience in China are used in the establishment of a model that will assist his current career in regional economic development. It explains the reasons for choosing the Participatory Action Research method and uses the researcher’s personal and professional voices in a multi-vocal, neopragmatic style blended with visual rich picture presentation involving graphics and photos to tell the story. The thesis – with its style and voices – is a soft systems picture in its own right. The research outcome is a knowledge management model for promoting. Selling, organising and conducting a trade mission into China

Advanced document data extraction techniques to improve supply chain performance

In this thesis, a novel machine learning technique to extract text-based information from scanned images has been developed. This information extraction is performed in the context of scanned invoices and bills used in financial transactions. These financial transactions contain a considerable amount of data that must be extracted, refined, and stored digitally before it can be used for analysis. Converting this data into a digital format is often a time-consuming process. Automation and data optimisation show promise as methods for reducing the time required and the cost of Supply Chain Management (SCM) processes, especially Supplier Invoice Management (SIM), Financial Supply Chain Management (FSCM) and Supply Chain procurement processes. This thesis uses a cross-disciplinary approach involving Computer Science and Operational Management to explore the benefit of automated invoice data extraction in business and its impact on SCM. The study adopts a multimethod approach based on empirical research, surveys, and interviews performed on selected companies.The expert system developed in this thesis focuses on two distinct areas of research: Text/Object Detection and Text Extraction. For Text/Object Detection, the Faster R-CNN model was analysed. While this model yields outstanding results in terms of object detection, it is limited by poor performance when image quality is low. The Generative Adversarial Network (GAN) model is proposed in response to this limitation. The GAN model is a generator network that is implemented with the help of the Faster R-CNN model and a discriminator that relies on PatchGAN. The output of the GAN model is text data with bonding boxes. For text extraction from the bounding box, a novel data extraction framework consisting of various processes including XML processing in case of existing OCR engine, bounding box pre-processing, text clean up, OCR error correction, spell check, type check, pattern-based matching, and finally, a learning mechanism for automatizing future data extraction was designed. Whichever fields the system can extract successfully are provided in key-value format.The efficiency of the proposed system was validated using existing datasets such as SROIE and VATI. Real-time data was validated using invoices that were collected by two companies that provide invoice automation services in various countries. Currently, these scanned invoices are sent to an OCR system such as OmniPage, Tesseract, or ABBYY FRE to extract text blocks and later, a rule-based engine is used to extract relevant data. While the system’s methodology is robust, the companies surveyed were not satisfied with its accuracy. Thus, they sought out new, optimized solutions. To confirm the results, the engines were used to return XML-based files with text and metadata identified. The output XML data was then fed into this new system for information extraction. This system uses the existing OCR engine and a novel, self-adaptive, learning-based OCR engine. This new engine is based on the GAN model for better text identification. Experiments were conducted on various invoice formats to further test and refine its extraction capabilities. For cost optimisation and the analysis of spend classification, additional data were provided by another company in London that holds expertise in reducing their clients' procurement costs. This data was fed into our system to get a deeper level of spend classification and categorisation. This helped the company to reduce its reliance on human effort and allowed for greater efficiency in comparison with the process of performing similar tasks manually using excel sheets and Business Intelligence (BI) tools.The intention behind the development of this novel methodology was twofold. First, to test and develop a novel solution that does not depend on any specific OCR technology. Second, to increase the information extraction accuracy factor over that of existing methodologies. Finally, it evaluates the real-world need for the system and the impact it would have on SCM. This newly developed method is generic and can extract text from any given invoice, making it a valuable tool for optimizing SCM. In addition, the system uses a template-matching approach to ensure the quality of the extracted information