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Development of signal processing online labs using HTML5 and mobile platforms

Published on Oct 1, 2017 in FIE (Frontiers in Education Conference)
· DOI :10.1109/FIE.2017.8190657
Abhinav Dixit , Sameeksha Katoch1
Estimated H-index: 1
+ 3 AuthorsAndreas Spanias25
Estimated H-index: 25
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Abstract
Several web-based signal processing simulation packages for education have been developed in a Java environment. Although this environment has provided convenience and accessibility using standard browser technology, it has recently become vulnerable to cyber-attacks and is no longer compatible with secure browsers. In this paper, we describe our efforts to transform our award-winning J-DSP online laboratory by rebuilding it on an HTML5 framework. Along with a new simulation environment, we have redesigned the interface to enable several new functionalities and an entirely new educational experience. These new features include functions that enable real-time interfaces with sensor boards and mobile phones. The Web 4.0 HTML5 technology departs from older Java interfaces and provides an interactive graphical user interface (GUI) enabling seamless connectivity and both software and hardware experiences for students in DSP classes.
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References20
Newest
Published on Dec 1, 2016 in ISSPIT (International Symposium on Signal Processing and Information Technology)
Jongmin Lee3
Estimated H-index: 3
(ASU: Arizona State University),
Michael Stanley1
Estimated H-index: 1
(NXP Semiconductors)
+ 1 AuthorsCihan Tepedelenlioglu26
Estimated H-index: 26
(ASU: Arizona State University)
Interpreting sensor data in Internet-of-Things applications is a challenging problem particularly in embedded systems. We consider sensor data analytics where machine learning algorithms can be fully implemented on an embedded processor/sensor board. We develop an efficient real-time realization of a Gaussian mixture model (GMM) for execution on the NXP FRDM-K64F embedded sensor board. We demonstrate the design of a customized program and data structure that generates real-time sensor features, ...
Published on Jul 1, 2016in IEEE Signal Processing Magazine 7.60
Thomas A. Baran5
Estimated H-index: 5
(MIT: Massachusetts Institute of Technology),
Richard G. Baraniuk82
Estimated H-index: 82
(Rice University)
+ 2 AuthorsMartin Vetted90
Estimated H-index: 90
(EPFL: École Polytechnique Fédérale de Lausanne)
In higher education circles, 2012 may be known as the "year of the MOOC"; the launch of several high-profile initiatives, both for profit (Coursera, Udacity) and not for profit (edX), created an electrified feeling in the community, with massive open online courses (MOOCs) becoming the hottest new topic in academic conversation. The sudden attention was perhaps slightly forgetful of many notable attempts at distance learning that occurred before, from campus TV networks to well-organized online ...
Published on Mar 1, 2016 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
Cameron H. G. Wright15
Estimated H-index: 15
(UW: University of Wyoming),
Thad B. Welch15
Estimated H-index: 15
(BSU: Boise State University),
Michael G. Morrow11
Estimated H-index: 11
(UW: University of Wisconsin-Madison)
The challenge of teaching practical optical engineering in a single course can be overcome by taking advantage of existing student knowledge of signal processing concepts. Such an approach greatly facilitates student mastery of new topics. This paper describes how professors can use this technique to efficiently teach optical engineering.
Published on Feb 1, 2016in IEEE Transactions on Signal Processing 5.23
Visar Berisha11
Estimated H-index: 11
(ASU: Arizona State University),
Alan Wisler4
Estimated H-index: 4
(ASU: Arizona State University)
+ 1 AuthorsAndreas Spanias25
Estimated H-index: 25
(ASU: Arizona State University)
Information divergence functions play a critical role in statistics and information theory. In this paper we show that a nonparametric f-divergence measure can be used to provide improved bounds on the minimum binary classification probability of error for the case when the training and test data are drawn from the same distribution and for the case where there exists some mismatch between training and test distributions. We confirm these theoretical results by designing feature selection alg...
Published on Nov 19, 2014in Journal of geoscience education
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(ASU: Arizona State University),
Linda A. Hinnov34
Estimated H-index: 34
(Johns Hopkins University),
Andreas Spanias25
Estimated H-index: 25
(ASU: Arizona State University)
ABSTRACT Modern data collection in the Earth Sciences has propelled the need for understanding signal processing and time-series analysis techniques. However, there is an educational disconnect in the lack of instruction of time-series analysis techniques in many Earth Science academic departments. Furthermore, there are no platform-independent freeware tools available for teaching Earth signals analysis. In order to address these issues, we developed the Java-Digital Signal Processing/Earth Sys...
Published on Oct 12, 2014 in EMSOFT (Embedded Software)
Garvit Juniwal5
Estimated H-index: 5
(University of California, Berkeley),
Alexandre Donzé19
Estimated H-index: 19
(University of California, Berkeley)
+ 1 AuthorsSanjit A. Seshia36
Estimated H-index: 36
(University of California, Berkeley)
We consider the problem of designing an automatic grader for a laboratory in the area of cyber-physical systems. The goal of this laboratory is to program a robot for specified navigation tasks. Given a candidate student solution (control program for the robot), our grader first checks whether the robot performs the task correctly under a representative set of environment conditions. If it does not, the grader automatically generates feedback hinting at possible errors in the program. The auto-g...
Athanasios Kalantzopoulos4
Estimated H-index: 4
(University of Patras),
Evangelos Zigouris7
Estimated H-index: 7
(University of Patras)
The education of students in the design of DSP (Digital Signal Processor) based systems is achieved through courses including lectures and laboratory sessions. Traditionally, the laboratory sessions take place in the hands-on laboratories and the physical presence of both students and instructors is required. This paper presents the online conduction of the System Design with DSPs postgraduate course's laboratory sessions utilizing the R-DSP Lab (Remote Digital Signal Processors Laboratory). Thi...
Published on Mar 31, 2014
Shalin Mehta2
Estimated H-index: 2
,
Andreas Spanias25
Estimated H-index: 25
+ 6 AuthorsJayaraman J. Thiagarajan10
Estimated H-index: 10
In this paper, we present an integrated learning framework that includes course delivery, interactive online laboratories, video streaming, Java visualization modules, testing, and assessment. The proposed framework uses HTML and Java based technologies to augment the existing J-DSP environment, in order to improve the overall learning experience of students in both undergraduate and graduate level signal processing courses. An interactive DSP quiz forms the central part of the proposed interfac...
Published on Oct 1, 2013in Synthesis Lectures on Signal Processing
Narayan Kovvali9
Estimated H-index: 9
(ASU: Arizona State University),
Mahesh K. Banavar12
Estimated H-index: 12
(ASU: Arizona State University),
Andreas Spanias25
Estimated H-index: 25
The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalma...
Published on Jan 1, 2011 in DSP (International Conference on Digital Signal Processing)
Chih Wei Huang3
Estimated H-index: 3
(ASU: Arizona State University),
Jayaraman J. Thiagarajan10
Estimated H-index: 10
(ASU: Arizona State University)
+ 1 AuthorsConstantinos S. Pattichis34
Estimated H-index: 34
(UCY: University of Cyprus)
Java-DSP is a freely accessible web-based software, primarily used in signal processing education and research. In this paper, we present Java-DSP modules that have been developed for the study and analysis of the MPEG-1 Layer III algorithm. We have embedded JLayer1.0, an open source MP3 library, to Java-DSP and developed an intuitive interface to expose undergraduate and graduate students to the several modules in the encoding/decoding process. The Java-DSP MP3 decoder block is an interactive f...
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Published on Oct 1, 2018
Abhinav Dixit , Uday Shankar Shanthamallu2
Estimated H-index: 2
+ 2 AuthorsMahesh K. Banavar12
Estimated H-index: 12
(Clarkson University)
This work in progress paper describes software that enables online machine learning experiments in an undergraduate DSP course. This software operates in HTML5 and embeds several digital signal processing functions. The software can process natural signals such as speech and can extract various features, for machine learning applications. For example in the case of speech processing, LPC coefficients and formant frequencies can be computed. In this paper, we present speech processing, feature ex...
Published on Jul 1, 2018
Farib Khondoker (ASU: Arizona State University), Sunil Rao2
Estimated H-index: 2
(ASU: Arizona State University)
+ 1 AuthorsCihan Tepedelenlioglu26
Estimated H-index: 26
(ASU: Arizona State University)
When collecting solar energy via photovoltaic (PV) panel arrays, one common issue is the potential occurrence of faults. Faults arise from panel short-circuit, soiling, shading, ground leakage and other sources. Machine learning algorithms have enabled data-based classification of faults. In this paper, we present an Internet-based PV array fault monitoring simulation using the Java-Dsp(j-Dsp)simulation environment. We first develop a solar array simulation in J-DSP and then form appropriate gra...
Published on May 1, 2018
Sameeksha Katoch1
Estimated H-index: 1
(ASU: Arizona State University),
Gowtham Muniraju1
Estimated H-index: 1
(ASU: Arizona State University)
+ 5 AuthorsDevarajan Srinivasan2
Estimated H-index: 2
This paper describes three methods used in the development of a utility-scale solar cyber-physical system. The study describes remote fault detection using machine learning approaches, power output optimization using cloud movement prediction and consensus-based solar array parameter estimation. Dynamic cloud movement, shading and soiling, lead to fluctuations in power output and loss of efficiency. For optimization of output power, a cloud movement prediction algorithm is proposed. Integrated f...