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The existing plethora of document classification techniques exploits different data sources either from the content or metadata of research articles. Various journal publishers like Springer, Elsevier, IEEE, etc., do not provide open access to the content of research articles, whereas metadata is freely available there. Metadata like title, keyword, and abstract can serve as a better alternative to the content in various scenarios. In the current literature, researchers have assessed the role of some of the metadata individually. We believe that the collective contribution of metadata parameters can play a significant role in classifying research papers. This paper presents a comprehensive evaluation of the role of metadata, individually as well as in combinations to achieve the objective of research paper classification. Moreover, we have classified the research articles into ACM hierarchy root categories (e.g. general literature, hardware, software, etc.). In this comprehensive evaluation, we have assessed all the possible combinations of metadata features against different classifiers such as Random Forest, K Nearest Neighbor, and Decision Tree. The results of this research reveal that the title & keywords combination outperforms other combinations with an F-measure score of 0.88.

Paper-based digital microfluidic biochips (or P-DMFBs) are becoming highly impelling due to its low-cost and in-place fabrication of electrodes and control wiring on a single piece of paper having an inkjet printer and conductive ink. Despite enormous advantages, several complex design rules also subsist, such as avoidance of induced control interference, minimum separation among the control lines, and congestion-free wiring on a single layer, which is to be correlated leading toward overall feasibility of the design. Several cost raising issues, such as schedule length, control pin count, and wire length, must be considered for attaining a successful fluid-control codesign. Moreover, design gaps exist among the subtasks of the fluid level, control level, and fluid-control design as a whole, which undeniably impose expensive design cycles increasing overall cost. This article builds a machine learning-based model for the pin-constrained P-DMFBs to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring. This model effectively eliminates the design cycles producing a low-cost platform. The predictive model has been evaluated over a balanced data set. Several benchmarks for assessing the performance are studied.

Over the decades, the immense growth has been reported in research publications due to continuous developments in science. To date, various approaches have been proposed that find similarity between research papers by applying different similarity measures collectively or individually based on the content of research papers. However, the contemporary schemes are not conceptualized enough to find related research papers in a coherent manner. This paper is aimed at finding related research papers by proposing a comprehensive and conceptualized model via building ontology named COReS: Content-based Ontology for Research Paper Similarity. The ontology is built by finding the explicit relationships (i.e., super-type sub-type, disjointedness, and overlapping) between state-of-the-art similarity techniques. This paper presents the applications of the COReS model in the form of a case study followed by an experiment. The case study uses InText citation-based and vector space-based similarity measures and relationships between these measures as defined in COReS. The experiment focuses on the computation of comprehensive similarity and other content-based similarity measures and rankings of research papers according to these measures. The obtained Spearman correlation coefficient results between ranks of research papers for different similarity measures and user study-based measure, justify the application of COReS for the computation of document similarity. The COReS is in the process of evaluation for ontological errors. In the future, COReS will be enriched to provide more knowledge to improve the process of comprehensive research paper similarity computation.

Due to the increasing size of s (s), their design and optimization phases (i.e., ) grow increasingly complex. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. At run time, a large configuration space needs to be searched to find the best set of parameters (e.g., voltage/frequency) to further optimize the system. Both spaces are infeasible for exhaustive search typically leading to heuristic optimization algorithms that find some trade-off between design quality and computational overhead. ML can build powerful models that have successfully been employed in related domains. In this survey, we categorize how () may be used and is used for design-time and run-time optimization and exploration strategies of s. A meta-study of published techniques unveils areas in that are well-explored and underexplored with, as well as trends in the employed algorithms. We present a comprehensive categorization and summary of the state of the art on for. Finally, we summarize remaining challenges and promising open research directions.

In this article, we put forward the substantial challenges in cyber resilience in the domain of autonomous systems and outline foundational solutions to address these challenges. These solutions fall into two broad themes: resilience-by-design and resilience-by-reaction . We use several application drivers from autonomous systems to motivate the challenges in cyber resilience and to demonstrate the benefit of the solutions. We focus on some autonomous systems in the near horizon (autonomous ground and aerial vehicles) and also a little more distant (autonomous rescue and relief). For resilience-by-design , we focus on design methods in software that are needed for our cyber systems to be resilient. In contrast, for resilience-by-reaction , we discuss how to make systems resilient by responding, reconfiguring, or recovering at runtime when failures happen. We also discuss the notion of adaptive execution to improve resilience, execution transparently and adaptively among available execution platforms (mobile/embedded, edge, and cloud). For each of the two themes, we survey the current state, and the desired state and ways to get there. We conclude the paper by looking at the research challenges we will have to solve in the short and the mid-term to make the vision of resilient autonomous systems a reality. This article came out of discussions that started at the NSF-sponsored Grand Challenges in Resilience Workshop held at Purdue in 2019 with the co-authors contributing to going into the depth of the issues and then this article.

Transmission of video traffic over the Internet has grown exponentially in the past few years with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise the Quality of Experience (QoE) of end users video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted., 18 pages, 7 figures

Introduction: The electrocardiogram (ECG) plays an important role in the diagnosis of heart diseases. However, most patterns of diseases are based on old datasets and stepwise algorithms that provide limited accuracy. Improving diagnostic accuracy of the ECG can be done by applying machine learning algorithms. This requires taking existing scanned or printed ECGs of old cohorts and transforming the ECG signal to the raw digital (time (milliseconds), voltage (millivolts)) form. Objectives: We present a MATLAB-based tool and algorithm that converts a printed or scanned format of the ECG into a digitized ECG signal. Methods: 30 ECG scanned curves are utilized in our study. An image processing method is first implemented for detecting the ECG regions of interest and extracting the ECG signals. It is followed by serial steps that digitize and validate the results. Results: The validation demonstrates very high correlation values of several standard ECG parameters: PR interval 0.984 +/−0.021 (p-value < 0.001), QRS interval 1+/− SD (p-value < 0.001), QT interval 0.981 +/− 0.023 p-value < 0.001, and RR interval 1 +/− 0.001 p-value < 0.001. Conclusion: Digitized ECG signals from existing paper or scanned ECGs can be obtained with more than 95% of precision. This makes it possible to utilize historic ECG signals in machine learning algorithms to identify patterns of heart diseases and aid in the diagnostic and prognostic evaluation of patients with cardiovascular disease., We present a MATLAB-based tool and algorithm that converts a printed or scanned ECG into a digitized ECG signal. Validation on 30 ECG scanned curves more than 95% precision. This makes it possible to utilize historic ECG signals in machine learning algorithms to identify patterns of heart diseases and aid in the diagnosis and evaluation of patients with cardiovascular disease.

Digital pen and paper technologies are proving increasingly popular in vertical markets such as health care and manufacturing, which make heavy use of standardized forms that can easily be produced on specialized paper. But the still-untapped frontier is the horizontal zone of everyday consumers. Within this vast and tempting territory resides the commercial digital pen's most-often targeted subgroup: notetakers - whether they're journalists, lawyers, or the many students who sit daily with their heads bobbing between their paper or computer notebooks and the lecturer at the podium. In the past year, several new digital pens have targeted this group in the hope of uniting the broader market's paper and digital worlds. And one digital pen - Livescribe's Pulse smartpen - is working out its grand vision of a paper-based mobile computing platform that it hopes will radically alter how we view pens and their possibilities.

Arguably, usability testing is most effective when integrated into the user-centered design process. One way to encourage this integration is to reemphasize the value of paper prototyping. In a recent test of a university library website, we married low-fidelity paper prototyping with medium-fidelity wireframe prototyping. When user navigation led to nonexisting pages or dead ends, users were encouraged to create what they thought should be where there was nothing. This blank-page technique gave us insights into users' mental models regarding site content and design, providing developers with useful data concerning how users conceptualized information they encountered.

THE YEAR IS 2028. IT'S 8 P.M. ON A Wednesday night and you're famished. You're staring wistfully at the only remaining item in your refrigerator: a package of sausages with an unappetizing grayish hue. Ugh. Did they always look like that? Are they still safe to eat? In 2018, you'd have to rely on your sense of smell and take a gamble. But in 2028, you might simply wave your smartphone over the package. The smartphone interrogates the package's embedded sensor, which measures the concentration of gases associated with meat decomposition. The smartphone displays the message "Safe to eat within the next 20 hours," and then offers a list of recipes for cooking with sausages. Too hungry to bother with the recipes, you tear open the package, toss the sausages into a frying pan, and discard the package-along with its sensor technology.

A rule-based expert system for the integrated control and supervision of the dry-end sections of a paper machine is proposed. This system is capable of recognizing all the normal and abnormal changes in process operating conditions, including acceleration of sections, threading of paper sheet, nip pressure activation, activation and deactivation of tension control loops, change of parent roll, and sheet break. A core part of the system is the supervision of the sensorless tension control of the dry-end sections, assuring its long-term stability.

The eminent growth in connected devices technologies, like the Internet of Things (IoT), 5 th generation (5G) and beyond communication systems, lead to innovations for human beings. The uninterrupted data communication services play diverse roles in the mobile user's routine life. The various changing user group patterns are unpredictable due to the day-by-day up-gradation of user devices. Even though the existing telecommunication services have upgraded up to 5G with high performance distributed computing (HPDC) in the distributed data networks (DDN) for ultra-reliable and low latency communication (URLLC) services, yet the backend distributed database systems (DDS) are facing serious security and privacy issues due to lack of federated intelligence in the data networks. Recently, we have seen an increased focus and effort by users and policymakers toward enhancing security and privacy related to the collection and usage of the data in DDNs. When it comes to the intelligence using machine/deep learning (ML/DL) of the HPDC systems for security and privacy, enough dataset is required, which often includes personal user information to train ML/DL models. As data privacy and security represents a growing critical concern, given the above-mentioned new areas of legislation and policies, novel ML methodologies like federated learning (FL) have been developed in part to address these concerns.

The minimum variance controller has been extensively used as a benchmark in the performance assessment of both univariate and multivariate control loops when time delay is the fundamental performance limitation. In this paper, the spatial and temporal performance limitations in the cross-directional (CD) control of paper machines are analyzed. The idea of minimum variance benchmarking is extended to the CD process based on these performance limitations. Based on an industrial CD controller, a user-specified benchmark, which is more practical and less aggressive, is also proposed. In addition, several related performance indices are proposed for the CD process based on both the minimum variance benchmark and the user-specified benchmark. Illustrative examples from a paper machine simulator and industrial data sets are provided to show the effectiveness of the proposed performance indices.

A course on the emerging topic “Smart Sensors and Internet of Things (IoT)” has been designed, developed, and delivered from 21st March 2016 to 31st March 2016 in the Department of Electrical Engineering, Jamia Millia Islamia (Central University), New Delhi-110025, India. This course was organized under a program initiated by the Government of India, entitled “Global Initiative of Academic Networks” for higher education. The basic objective is to bring the internationally and nationally acclaimed scientists on a single platform to motivate young minds of India so that India’s scientific and technological capacity reach global excellence. The course was designed to develop the technical skills for the students, the researchers, the engineers, and the faculties, who desire to address some of the issues faced by the people around the world in the fields of smart sensors and IoTs with applications in smart homes, smart cities, smart grids, smart environment, smart transport, and so on. The assessment of the course by the participants shows extreme usefulness of it.

In the city of Buenos Aires, paper-based management had prevented improvement in state services. The authors discuss their work transforming this environment to one that completely eliminated paper. Implementing a full electronic document management system has resulted in the massive involvement of citizens in administrative procedures, new behaviors in the organization, and improved expeditiousness in processing, operational control, and transparency. The next step is to bring similar changes to the federal government of Argentina.

The objective of this paper was to provide an automatic engine to classify and locate information using natural language. The proposal integrates a set of two algorithms to extract information from different repositories using their own open APIs and creates a knowledge database using a natural language approach using a Bayesian algorithm to classify and a second algorithm to clean the paper. Putting said techniques together derived in a strong alternative which reach common gaps in classification and location of information including avoid the use of the whole paper to get information and not only the information introduced at the moment of upload the paper in the digital library. The proposal was oriented to classify and locate research papers in order to better describe this contribution, however, findings could be applicable to a vast range of scenarios. An adaptation of the popular methodology Crisp-DM was used to evaluate the performance of the algorithm obtaining good results in classifying, searching, and feeding the knowledge base.

This special issue is the fourth highlighting selected papers from the IEEE Symposium on Security and Privacy. Several articles presented address vulnerabilities, and possible mitigation strategies, related to smart devices, home systems, entertainment systems, and smartphones, while others study human behavior in managing devices, security- and privacy-relevant code development, and critical infrastructure management. Given the intense discussions in the Internet of Things (IoT) community and the increasing complexity of human-system interactions, these are timely topics.

In this paper, we investigate a very challenging task of automatically generating presentation slides for academic papers. The generated presentation slides can be used as drafts to help the presenters prepare their formal slides in a quicker way. A novel system called PPSGen is proposed to address this task. It first employs the regression method to learn the importance scores of the sentences in an academic paper, and then exploits the integer linear programming (ILP) method to generate well-structured slides by selecting and aligning key phrases and sentences. Evaluation results on a test set of 200 pairs of papers and slides collected on the web demonstrate that our proposed PPSGen system can generate slides with better quality. A user study is also illustrated to show that PPSGen has a few evident advantages over baseline methods.

In a previous article, i wrote a brief piece on how to enhance papers that have been published at one of the IEEE Consumer Electronics (CE) Society conferences to create papers that can be considered for publishing in IEEE Transactions on Consumer Electronics (T-CE) [1]. Basically, it included some hints and tips to enhance a conference paper into what is required for a full archival journal paper and not fall foul of self-plagiarism. This article focuses on writing original papers specifically for T-CE.

Writer verification is a method to specify an authentic writer from handwriting. Automated writer verification methods are required for various applications (e.g., credit cards, checks, and passports). However, there is room for improvement in the performance of such methods compared with the performance of human beings, for example, forensic document examiners. Because automated writer verification systems do not always return correct results under any circumstances, which can lead to grave consequences, further research is required to improve the performance of such methods. Furthermore, problems caused by limited samples must be solved for real applications. To improve verification accuracy with limited samples, we propose a text and user generic model for writer verification that uses a combination of pen pressure information from ink intensity and writing indentations obtained by a multiband image scanner. We introduce a writer-specific dissimilarity representation to consider individual handwriting characteristics that affect model performance. Experimental results obtained using handwriting samples collected from 54 volunteers are reported. The results show a decrease in error rate compared with conventional methods from 10.0% to 4.0%.

Under the umbrella of ubiquitous technologies, many computational artifacts have been designed to enhance the learning experience in physical settings such as classrooms or playgrounds, but few of them focus on aiding orchestration. This paper presents a systematic evaluation of the signal orchestration system (SOS) used by students for a jigsaw activity in an authentic classroom setting. The SOS comprises multiple wearable personal signal devices and an orchestration signal manager. Color and sound signals can be configured in the manager to be transmitted to the personal devices worn by the students to indicate orchestration signals for collaboration. The comparison between the SOS and a paper-based method traditionally employed for the orchestration of the jigsaw collaborative pattern showed that students in the SOS group spent significantly less time organizing the activity, obtained higher scores in the tests, experienced a stronger feeling of group formation awareness, and reported having enjoyed the experience to a greater degree.

Visualizing the intellectual structure of scientific domains using co-cited units such as references or authors has become a routine for domain analysis. In previous studies, paper-reference matrices are usually transformed into reference-reference matrices to obtain co-citation relationships, which are then visualized in different representations, typically as node-link networks, to represent the intellectual structures of scientific domains. Such network visualizations sometimes contain tightly knit components, which make visual analysis of the intellectual structure a challenging task. In this study, we propose a new approach to reveal co-citation relationships. Instead of using a reference-reference matrix, we directly use the original paper-reference matrix as the information source, and transform the paper-reference matrix into an FP-tree and visualize it in a Java-based prototype system. We demonstrate the usefulness of our approach through visual analyses of the intellectual structure of two domains: Information Visualization and Sloan Digital Sky Survey (SDSS). The results show that our visualization not only retains the major information of co-citation relationships, but also reveals more detailed sub-structures of tightly knit clusters than a conventional node-link network visualization.

This paper presents CoScribe, a concept and prototype system for the combined work with printed and digital documents, which supports a large variety of knowledge work settings. It integrates novel pen-and-paper-based interaction techniques that enable users to collaboratively annotate, link and tag both printed and digital documents. CoScribe provides for a very seamless integration of paper with the digital world, as the same digital pen and the same interactions can be used on paper and displays. As our second contribution, we present empirical results of three field studies on learning at universities. These motivated the design of CoScribe and were abstracted to a generic framework for the design of intuitive pen-and-paper user interfaces. The resulting interaction design comprising collaboration support and multiuser visualizations has been implemented and evaluated in user studies. The results indicate that CoScribe imposes only minimal overhead on traditional annotation processes and provides for a more efficient structuring and retrieval of documents.

It sounds like a trick question, but it's not: Do white papers need to be either white or paper? Authors are preparing a small but growing number of technical documents today that are intended to be read on a tablet or smartphone screen. And some of these multicolored, multimedia presentations and PowerPoint-style slideshows are having as big an impact as that of any traditionally arranged document.

Despite their widespread deployment, questions about electronic voting systems' performance emerge following many elections. To encourage full public confidence in the electoral process, some researchers recommend equipping electronic voting machines with voter-verifiable audit trails that print out paper records that voters can read and verify. In this article, the authors report on their analysis and testing of one US state's criteria for direct-recording electronic (DRE) voting machines equipped with voter-verified paper-record (VVPR) systems. The criteria and analysis cover various categories, including privacy, security, verification, integrity, functionality, and examination. The authors describe their testing methodologies, discuss issues exhibited by different voting systems, and propose solutions to address those issues.

When faced with the tasks of reading and writing a complex technical paper, many nonnative scientists and engineers who have a solid background in English grammar and vocabulary lack an adequate knowledge of commonly used structural patterns at the discourse level. In this paper, we propose a novel computer software tool that can assist these people in the understanding and construction of technical papers, by automatically identifying the structure of writing in different fields and disciplines. The system is tested using research article abstracts and is shown to be a fast, accurate, and useful aid in the reading and writing process.

The basic tabletop microscope hasn't changed much in fundamental design in nearly 100 years. At least its design hadn't changed until a Stanford engineer started playing with innovative microscopy ideas in 2011.

Wireless communication is continuing to make inroads into many facets of society and is gradually becoming more and more ubiquitous. While in the past wireless communication (as well as mobility) was largely limited to the first and last transmission hops, today's wireless networks are starting to offer purely wireless, often mobile, and even opportunistically connected operation. The purpose of this article is to examine security and privacy issues in some new and emerging types of wireless networks, and attempt to identify directions for future research.

Sketches are hand-drawn informal figures often created as a way of thinking about or working through a problem. Sketch-understanding systems let users interact with computers by drawing naturally, offering a freedom not available with traditional CAD systems.

This paper is an attempt to give some guidelines on how to write a good technical paper and to make good presentations, important skills for a successful career in research and teaching.

Personal computers (PCs) are increasingly being used in industrial applications. Graphical user interface (GUI) software and Windows-based operating systems are proving to be cost-effective, rugged and reliable. This paper describes how these advances have, over the past four years, allowed the successful installation of several human-machine interface (HMI) systems for paper machine winders.

In this paper a new technique is proposed to improve the recognition ability and the transaction speed to classify the Japanese and US paper currency. Two types of data sets, time series data and Fourier power spectra, are used in this study. In both cases, they are directly used as inputs to the neural network. Furthermore, we also refer a new evaluation method of recognition ability. Meanwhile, a technique is proposed to reduce the input scale of the neural network without preventing the growth of recognition. This technique uses only a subset of the original data set which is obtained using random masks. The recognition ability of using large data set and a reduced data set are discussed. In addition to that the results of using a reduced data set of the Fourier power spectra and the time series data are compared. >

Since the origins of science, researchers' main output has been books and papers that describe new theoretical and practical ideas and results. These sources are useful and important, but learning from them is often not easy. How can we facilitate this learning process?

Over the period of 1985 through 1990, numerous papers were published on the subject of artificial intelligence (AI) and expert systems (ES) applications at nuclear power plants. A selection of these papers is given, arranged in the following categories: general descriptions of AI/ES techniques, specific AI/ES applications, knowledge-base development and modeling techniques, maintenance and diagnostics, operations and training support, procedural assistance and emergency response, risk assessment and reliability, and design tools. >

To celebrate the achievements of the magazine and to recognize the profound contributions from authors, IEEE MultiMedia has establish two annual awards starting this year--best article and best department. Learn about the first winners of these two new awards.

EIC Yong Rui announces this year’s winners of IEEE MultiMedia’s Best Article and Best Department Article awards, one of which explores the spatiotemporal characteristics of landmarks using multimodal signals of social media with geo-tag and timestamp information. The other studies a person-centered, adaptive approach to multimedia computing to meet the needs of people with disabilities.

The principles of the model-based document analysis system called Pi ODA (paper interface to office document architecture), which was developed as a prototype for the analysis of single-sided business letters in German, are presented. Initially, Pi ODA extracts a part-of hierarchy of nested layout objects such as text-blocks, lines, and words based on their presentation on the page. Subsequently, in a step called logical labeling, the layout objects and their compositions are geometrically analyzed to identify corresponding logical objects that can be related to a human perceptible meaning, such as sender, recipient, and date in a letter. A context-sensitive text recognition for logical objects is then applied using logical vocabularies and syntactic knowledge. As a result, Pi ODA produces a document representation that conforms to the ODA international standard. >

Instructions providing basic guidelines for preparing camera-ready (CR) Transactions-styled papers for IEEE Power Engineering Society (PES) Transactions are presented. This document is itself an example of the desired layout for CR papers (inclusive of this abstract). The document contains information regarding desktop publishing format, type sizes, and type faces. Style rules are provided that explain how to handle equations, units, figures, tables, references, abbreviations, and acronyms. Sections are also devoted to the preparation of acknowledgments, references, and authors' biographies. Abstracts are limited to 150 words and can not contain equations, figures, or tables.

The three articles in this special section were selected as the "Best Papers" presented at IEEE WiVeC 2013.

In Part II of this series, I went over how to make life easy for the IEEE MTT-S International Microwave Symposium (IMS) reviewer so that we can increase the chances of getting a paper accepted. It is important to devote conscious effort into making it easy for the reviewer to give high scores in the originality, clarity, quantitative, and interest categories. In this part, I concentrate on what I feel is the most important category, quantitative. Note that all four categories are formally assigned equal weights when assigning scores, and other reviewers might have different opinions, so this represents only my personal views on the matter.

The two papers in this special section are extended papers chosen from nine peer-reviewed papers originally presented at the 2008 International Workshops on Data Mining in Bioinformatics (BIOKDD), held 24-27 August in Las Vegas, NV.

The 13 papers in this special section were originally presented at the 60th Electronic Components and Technology Conference (ECTC).

The Guest Editor summarizes the three papers in this special section. These papers were presented at the Annual International Conference on Mobile Computing and Networking (MobiCom) held in August 2012 in Istanbul, Turkey.

Objective: We present a Matlab-based tool to convert electrocardiography (ECG) information from paper charts into digital ECG signals. The tool can be used for long-term retrospective studies of cardiac patients to study the evolving features with prognostic value. Methods and procedures: To perform the conversion, we: 1) detect the graphical grid on ECG charts using grayscale thresholding; 2) digitize the ECG signal based on its contour using a column-wise pixel scan; and 3) use template-based optical character recognition to extract patient demographic information from the paper ECG in order to interface the data with the patients' medical record. To validate the digitization technique: 1) correlation between the digital signals and signals digitized from paper ECG are performed and 2) clinically significant ECG parameters are measured and compared from both the paper-based ECG signals and the digitized ECG. Results: The validation demonstrates a correlation value of 0.85–0.9 between the digital ECG signal and the signal digitized from the paper ECG. There is a high correlation in the clinical parameters between the ECG information from the paper charts and digitized signal, with intra-observer and inter-observer correlations of 0.8–0.9 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$({\rm p}