Increasing Student Motivation and Achievement Using Interactive Technology

I investigated ways that the use of technology will motivate and affect fifth and sixth grade students with special needs and influence their achievement in reading and writing. I created with the students, podcasts of 3 reader\u27s theater performances in order to practice reading fluency. The students used sound recording software, to listen and see (through sound waves) how they read. Various on-line tools for students to practice word formations, vowel combinations as well as other reading and language elements were used as well. I also looked at ways my students can use technology to publish and share their completed work, such as a classroom webpage, classroom blog, and video conferencing with classrooms in other districts. Finally I investigated the use of iPods for testing modifications

Permission-based Privacy Analysis for Android Applications

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety mostly relies on the features like rating and popularity, rather than in understanding context of listed permissions. In this work, we investigate the relationship between the features collected from Android Market API 23 and app’s privacy violation. These features include Popularity, Total Number of Permissions, Number of Dangerous Permissions, Rating and Package Size. To show the influence of each feature we use linear regression and Pearson R statistics. The conducted research can contribute to the classification of mobile applications concerning the threat on user’s privacy

Formal Requirements Analysis and Specification-Based Testing in Cyber-Physical Systems

openFormal requirements analysis plays an important role in the design of safety- and security-critical complex systems such as, e.g., Cyber-Physical Systems (CPS). It can help in detecting problems early in the system development life-cycle, reducing time and cost to completion. Moreover, its results can be employed at the end of the process to validate the implemented system, guiding the testing phase. Despite its importance, requirements analysis is still largely carried out manually due to the intrinsic difficulty of dealing with natural language requirements, the most common way to represent them. However, manual reviews are time-consuming and error-prone, reducing the potential benefit of the requirement engineering process. Automation can be achieved with the employment of formal methods, but their application is still limited by their complexity and lack of specialized tools. In this work we focus on the analysis of requirements for the design of CPSs, and on how to automatize some activities related to such analysis. We first study how to formalize requirements expressed in a structured English language, encode them in linear temporal logic, check their consistency with off-the-shelf model checkers, and find minimal set of conflicting requirements in case of inconsistency. We then present a new methodology to automatically generate tests from requirements and execute them on a given system, without requiring knowledge of its internal structure. Finally, we provide a set of tools that implement the studied algorithms and provide easy-to-use interfaces to help their adoption from the users.openXXXIII CICLO - INFORMATICA E INGEGNERIA DEI SISTEMI/ COMPUTER SCIENCE AND SYSTEMS ENGINEERING - Informatica/computer sciencePULINA, LUCAVuotto, Simon

The Chronicle [July 25, 2005]

The Chronicle, July 25, 2005https://repository.stcloudstate.edu/chron/4632/thumbnail.jp

Improving accountability reporting: How to make the best of journalism better for audiences

In this report, we want to explore a series of ideas people in news are working on that, taken together, will create a different approach to accountability journalism — work that encompasses fact-checking, explanatory and investigative reporting, but more generally applies to the journalistic work of holding the powerful accountable. Our proposals include recommendations about tools and technology, but also about format, tone and presentation

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

A Professional Development Manual for Online Learning at Savannah State University

A capstone submitted in partial fulfillment of the requirements for the degree of Doctor of Education in the College of Education At Morehead State University by Patrice C. Nyatuame on April 17, 2017

College ESL Writers: Applied Grammar and Composing Strategies for Success

Authors\u27 Description: College ESL Writers: Applied Grammar and Composing Strategies for Success is designed as a comprehensive grammar and writing etext for high intermediate and advanced level non-native speakers of English. We open the text with a discussion on the sentence and then break it down into its elemental components, before reconstructing them into effective sentences with paragraphs and larger academic assignments. Following that, we provide instruction in paragraph and essay writing with several opportunities to both review the fundamentals as well as to demonstrate mastery and move on to more challenging assignments. We have structured the etext into three basic parts. Part I, Composing Strategies and Techniques, includes a sequenced discussion from composing effective sentences through paragraph and essay writing. This includes the prewriting and planning stages of writing as well as the revising and editing stage in the first five chapters. Part II, Language Use, Grammar, and Mechanics, is meant to be used as a grammar and mechanics handbook as well as the practice and review of idiomatic wording. Part III, All About Writing: Samples, Topics, and Rubrics, has chapters with additional writing topics for practice, sample student papers, and rubrics for evaluating writing. This open textbook was created through a Round Six ALG Textbook Transformation Grant. Accessible files with optical character recognition (OCR) and auto-tagging provided by the Center for Inclusive Design and Innovation.https://oer.galileo.usg.edu/english-textbooks/1014/thumbnail.jp