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Full-Text Articles in Computer Sciences

An Assessment Of Pet Dose Reduction With Penalized Likelihood Image Reconstruction Using A Computationally Efficient Model Observer, Howard C. Gifford, C. Ross Schmidtlein, Andrzej Krol, Yuesheng Xu Jan 2020

An Assessment Of Pet Dose Reduction With Penalized Likelihood Image Reconstruction Using A Computationally Efficient Model Observer, Howard C. Gifford, C. Ross Schmidtlein, Andrzej Krol, Yuesheng Xu

Mathematics & Statistics Faculty Publications

Developing PET reconstruction algorithms with improved low-count capabilities may provide a timely and cost- effective means of reducing radiation dose in promising clinical applications such as immuno-PET that require long-lived radiotracers. For many PET clinics, the reconstruction protocol consists of postsmoothed ordered-sets expectation-maximization (OSEM) reconstruction, but penalized likelihood methods based on total-variation (TV) regularization could substantially reduce dose. We performed a task-based comparison of postsmoothed OSEM and higher-order TV (HOTV) reconstructions using simulated images of a contrast-detail phantom. An anthropomorphic visual-search model observer read the images in a location-known receiver operating characteristic (ROC) format. Acquisition counts, target uptake, and target …

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Musical Cryptography Using Long Short-Term Memory Networks, Curtis Helsel Jan 2020

Musical Cryptography Using Long Short-Term Memory Networks, Curtis Helsel

Honors Undergraduate Theses

Musical cryptography is a technique in which plain text messages are enciphered into a musical composition. Recently, a surge of music composition by means of machine learning have produced natural-sounding music that can be deemed as composed by humans. The combination of machine-generated music and enciphering a message into the composition is a logical step in musical cryptography. Outlined in this thesis is a method that incorporates the use of a specific type of recurrent neural network, Long Short-Term Memory, and a variant of the substitution cipher to form of symmetric-key cryptography system. Exploration was also completed to determine how …

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Understanding The Challenges Child Welfare Workers Encounter Related To Promoting The Online Safety Of Foster Youth, Denielle Kirk L. Abaquita Jan 2020

Understanding The Challenges Child Welfare Workers Encounter Related To Promoting The Online Safety Of Foster Youth, Denielle Kirk L. Abaquita

Honors Undergraduate Theses

Foster care case managers are responsible for the wellbeing of foster youth in the foster care system. Teens (ages 13-17) in foster care are most vulnerable to serious risks, such as sex trafficking. Such risks have been heightened by the advent of internet-based technologies that connect foster youth with unsafe others at unprecedented frequency and speed. This thesis examines how case managers tackle the challenge of online safety as it relates to adolescents in the foster care system in the United States. I conducted 32 semi-structured interviews with case managers who worked with foster teens (ages 13-17) within the past …

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Co-Designing "Teenovate": An Intergenerational Online Safety Design Team, Arianna J. Davis Jan 2020

Co-Designing "Teenovate": An Intergenerational Online Safety Design Team, Arianna J. Davis

Honors Undergraduate Theses

The Socio-Technical Interaction Research (STIR) Lab at UCF intends to create a new participatory design program, called "Teenovate," where teenagers and adults work together to design technologies that keep teens safe online. Previous participatory design projects, however, commonly focus on younger children under the age of 13. Teens differ significantly from young children in how they develop, socialize, and perceive the world. To inform the design of Teenovate, so that their unique needs are appropriately met, we conducted a participatory design study with 21 teens using polls, open-ended response questions, and subsequent group discussions. The teens were intrigued by the …

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Equivariance And Invariance For Robust Unsupervised And Semi-Supervised Learning, Liheng Zhang Jan 2020

Equivariance And Invariance For Robust Unsupervised And Semi-Supervised Learning, Liheng Zhang

Electronic Theses and Dissertations, 2020-2023

Although there is a great success of applying deep learning on a wide variety of tasks, it heavily relies on a large amount of labeled training data, which could be hard to obtain in many real scenarios. To address this problem, unsupervised and semi-supervised learning emerge to take advantage of the plenty of cheap unlabeled data to improve the model generalization. In this dissertation, we claim that equivariant and invariance are two critical criteria to approach robust unsupervised and semi-supervised learning. The idea is as follows: the features of a robust model ought to be sufficiently informative and equivariant to …

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Stochastic Sampling And Machine Learning Techniques For Social Media State Production, Neda Hajiakhoond Bidoki Jan 2020

Stochastic Sampling And Machine Learning Techniques For Social Media State Production, Neda Hajiakhoond Bidoki

Electronic Theses and Dissertations, 2020-2023

The rise in the importance of social media platforms as communication tools has been both a blessing and a curse. For scientists, they offer an unparalleled opportunity to study human social networks. However, these platforms have also been used to propagate misinformation and hate speech with alarming velocity and frequency. The overarching aim of our research is to leverage the data from social media platforms to create and evaluate a high-fidelity, at-scale computational simulation of online social behavior which can provide a deep quantitative understanding of adversaries' use of the global information environment. Our hope is that this type of …

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High Performance And Secure Execution Environments For Emerging Architectures, Mazen Alwadi Jan 2020

High Performance And Secure Execution Environments For Emerging Architectures, Mazen Alwadi

Electronic Theses and Dissertations, 2020-2023

Energy-efficiency and performance have been the driving forces of system architectures and designers in the last century. Given the diversity of workloads and the significant performance and power improvements when running workloads on customized processing elements, system vendors are drifting towards new system architectures (e.g., FAM or HMM). Such architectures are being developed with the purpose of improving the system's performance, allow easier data sharing, and reduce the overall power consumption. Additionally, current computing systems suffer from a very wide attack surface, mainly due to the fact that such systems comprise of tens to hundreds of sub-systems that could be …

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Unitary And Symmetric Structure In Deep Neural Networks, Kehelwala Dewage Gayan Maduranga Jan 2020

Unitary And Symmetric Structure In Deep Neural Networks, Kehelwala Dewage Gayan Maduranga

Theses and Dissertations--Mathematics

Recurrent neural networks (RNNs) have been successfully used on a wide range of sequential data problems. A well-known difficulty in using RNNs is the vanishing or exploding gradient problem. Recently, there have been several different RNN architectures that try to mitigate this issue by maintaining an orthogonal or unitary recurrent weight matrix. One such architecture is the scaled Cayley orthogonal recurrent neural network (scoRNN), which parameterizes the orthogonal recurrent weight matrix through a scaled Cayley transform. This parametrization contains a diagonal scaling matrix consisting of positive or negative one entries that can not be optimized by gradient descent. Thus the …

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Application Of The Benford’S Law To Social Bots And Information Operations Activities, Lale Madahali, Margeret Hall Jan 2020

Application Of The Benford’S Law To Social Bots And Information Operations Activities, Lale Madahali, Margeret Hall

Interdisciplinary Informatics Faculty Proceedings & Presentations

Benford's law shows the pattern of behavior in normal systems. It states that in natural systems digits' frequency have a certain pattern such that the occurrence of first digits in numbers are unevenly distributed. In systems with natural behavior, numbers begin with a “1” are more common than numbers beginning with “9”. It implies that if the distribution of first digits deviate from the expected distribution, it is indicative of fraud. It has many applications in forensic accounting, stock markets, finding abnormal data in survey data, and natural science. We investigate whether social media bots and Information Operations activities are …

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Text Mining Methods For Analyzing Online Health Information And Communication, Sifei Han Jan 2020

Text Mining Methods For Analyzing Online Health Information And Communication, Sifei Han

Theses and Dissertations--Computer Science

The Internet provides an alternative way to share health information. Specifically, social network systems such as Twitter, Facebook, Reddit, and disease specific online support forums are increasingly being used to share information on health related topics. This could be in the form of personal health information disclosure to seek suggestions or answering other patients' questions based on their history. This social media uptake gives a new angle to improve the current health communication landscape with consumer generated content from social platforms. With these online modes of communication, health providers can offer more immediate support to the people seeking advice. Non-profit …

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“Distance Learning” In The Ninth Century?: Micro-Cluster Analysis Of The Epistolary Network Of Alcuin After 796, William James Mattingly Jan 2020

“Distance Learning” In The Ninth Century?: Micro-Cluster Analysis Of The Epistolary Network Of Alcuin After 796, William James Mattingly

Theses and Dissertations--History

Scholars of eighth- and ninth-century education have assumed that intellectuals did not write works of Scriptural interpretation until that intellectual had a firm foundation in the seven liberal arts.This ensured that anyone who embarked on work of Scriptural interpretation would have the required knowledge and methods to read and interpret Scripture correctly. The potential for theological error and the transmission of those errors was too great unless the interpreter had the requisite training. This dissertation employs computistical methods, specifically the techniques of social network mapping and cluster analysis, to study closely the correspondence of Alcuin, a late-eighth- and early-ninth-century scholar …

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Orthogonal Recurrent Neural Networks And Batch Normalization In Deep Neural Networks, Kyle Eric Helfrich Jan 2020

Orthogonal Recurrent Neural Networks And Batch Normalization In Deep Neural Networks, Kyle Eric Helfrich

Theses and Dissertations--Mathematics

Despite the recent success of various machine learning techniques, there are still numerous obstacles that must be overcome. One obstacle is known as the vanishing/exploding gradient problem. This problem refers to gradients that either become zero or unbounded. This is a well known problem that commonly occurs in Recurrent Neural Networks (RNNs). In this work we describe how this problem can be mitigated, establish three different architectures that are designed to avoid this issue, and derive update schemes for each architecture. Another portion of this work focuses on the often used technique of batch normalization. Although found to be successful …

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Design Of A Remote Real-Time Groundwater Level And Water Quality Monitoring System For The Philippine Groundwater Management Plan Project, Carlos M. Oppus, Ma. Aileen Leah G. Guzman, Maria Leonora Guico, Jose Claro N. Monje, Mark Glenn F. Retirado, John Chris T. Kwong, Genevieve C. Ngo, Annael J. Domingo Jan 2020

Design Of A Remote Real-Time Groundwater Level And Water Quality Monitoring System For The Philippine Groundwater Management Plan Project, Carlos M. Oppus, Ma. Aileen Leah G. Guzman, Maria Leonora Guico, Jose Claro N. Monje, Mark Glenn F. Retirado, John Chris T. Kwong, Genevieve C. Ngo, Annael J. Domingo

Electronics, Computer, and Communications Engineering Faculty Publications

Recent technological advances allow us to utilize remote monitoring systems or real-time access of data. While the use of remote monitoring systems is not new, there are still numerous applications that can be explored and improved on, one such is groundwater level and quality monitoring. In the Philippines, the extraction of groundwater for both domestic use and industrial use are manually monitored by the government’s concerned agency and is done at least once per year. With this current setup, the real and significant state of the groundwater is not reflected in a way that is most valuable to the government …

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Endpoints And Interdependencies In Internet Of Things Residual Artifacts: Measurements, Analyses, And Insights Into Defenses, Jinchun Choi Jan 2020

Endpoints And Interdependencies In Internet Of Things Residual Artifacts: Measurements, Analyses, And Insights Into Defenses, Jinchun Choi

Electronic Theses and Dissertations, 2020-2023

The usage of Internet of Things (IoT) devices is growing fast. Moreover, the lack of security measures among the IoT devices and their persistent online connection give adversaries an opportunity to exploit them for multiple types of attacks, such as distributed denial-of-service (DDoS). To understand the risks of IoT devices, we analyze IoT malware from an endpoint standpoint. We investigate the relationship between endpoints infected and attacked by IoT malware, and gain insights into the underlying dynamics in the malware ecosystem. We observe the affinities and different patterns among endpoints. Towards this, we reverse-engineer 2,423 IoT malware samples and extract …

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Improving Security Of Crypto Wallets In Blockchain Technologies, Hossein Rezaeighaleh Jan 2020

Improving Security Of Crypto Wallets In Blockchain Technologies, Hossein Rezaeighaleh

Electronic Theses and Dissertations, 2020-2023

A big challenge in blockchain and cryptocurrency is securing the private key from potential hackers. Nobody can rollback a transaction made with a stolen key once the network confirms it. The technical solution to protect private keys is the cryptocurrency wallet, software, hardware, or a combination to manage the keys. In this dissertation, we try to investigate the significant challenges in existing cryptocurrency wallets and propose innovative solutions. Firstly, almost all cryptocurrency wallets suffer from the lack of a secure and convenient backup and recovery process. We offer a new cryptographic scheme to securely back up a hardware wallet relying …

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Multi-Agent Reinforcement Learning For Defensive Escort Teams, Hassam Sheikh Jan 2020

Multi-Agent Reinforcement Learning For Defensive Escort Teams, Hassam Sheikh

Electronic Theses and Dissertations, 2020-2023

Reinforcement learning has been applied to solve several real world challenging problems, from robotics to data center cooling. Similarly, adaption of reinforcement learning for multi-agent systems facilitated applications such as optimal multi-robot control and analysis of social-dilemmas. In this dissertation, we show that multi-agent reinforcement learning algorithms suffer from several stability issues such as multi-scenario learning, unstable training in dual-reward setting, overestimation bias and value function collapse, and provide solutions to each of these problems respectively. Several contributions of this dissertation have been formalized within the framework of a defensive escort team problems, a scenario where a team of learning …

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Interdisciplinary Cybersecurity For Resilient Cyberdefense, Rachid Ait Maalem Lahcen Jan 2020

Interdisciplinary Cybersecurity For Resilient Cyberdefense, Rachid Ait Maalem Lahcen

Electronic Theses and Dissertations, 2020-2023

Cybersecurity's role is to protect confidentiality, integrity, and availability of enterprise assets. Confidentiality secures data from theft, integrity mitigates modification of data in a malicious way, and availability assures continuation of systems' access and services. However, achieving these goals is difficult due to the mushrooming of various cyber attackers that come from individuals or state actors with motives ranging from ideological, financial, state-sponsored espionage, revenge, or simple curiosity and boredom. The difficulty also lies in the complexity of the cyber layers that are not well studied. Layers that interconnect and require effective communication and collaboration. This effectiveness is still lacking …

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Reconstruction Of Bacterial Strain Genomes From Shotgun Metagenomic Reads, Xin Li Jan 2020

Reconstruction Of Bacterial Strain Genomes From Shotgun Metagenomic Reads, Xin Li

Electronic Theses and Dissertations, 2020-2023

It is necessary to study bacterial strains in environmental samples. The environmental samples are mixed DNA samples collected from the ocean, soil, lake, human body sites, etc. In a natural environment, they provide us new insights into the diversity of our earth. As for bacterial strains on or inside human bodies, to select the proper treatment for diseases caused by bacterial strains, it is critical to identify the corresponding strains and reconstruct their genomes. However, it is a challenge to do so with the DNA from a large number of unknown microbial species mixed together in an environmental sample. The …

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Deep Recurrent Networks For Gesture Recognition And Synthesis, Mehran Maghoumi Jan 2020

Deep Recurrent Networks For Gesture Recognition And Synthesis, Mehran Maghoumi

Electronic Theses and Dissertations, 2020-2023

It is hard to overstate the importance of gesture-based interfaces in many applications nowadays. The adoption of such interfaces stems from the opportunities they create for incorporating natural and fluid user interactions. This highlights the importance of having gesture recognizers that are not only accurate but also easy to adopt. The ever-growing popularity of machine learning has prompted many application developers to integrate automatic methods of recognition into their products. On the one hand, deep learning often tops the list of the most powerful and robust recognizers. These methods have been consistently shown to outperform all other machine learning methods …

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Analyzing User Behavior In Collaborative Environments, Samaneh Saadat Jan 2020

Analyzing User Behavior In Collaborative Environments, Samaneh Saadat

Electronic Theses and Dissertations, 2020-2023

Discrete sequences are the building blocks for many real-world problems in domains including genomics, e-commerce, and social sciences. While there are machine learning methods to classify and cluster sequences, they fail to explain what makes groups of sequences distinguishable. Although in some cases having a black box model is sufficient, there is a need for increased explainability in research areas focused on human behaviors. For example, psychologists are less interested in having a model that predicts human behavior with high accuracy and more concerned with identifying differences between actions that lead to divergent human behavior. This dissertation presents techniques for …

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Distance Oracles For Interval Graphs Via Breadth-First Rank/Select In Succinct Trees, Meng He, J. Ian Munro, Yakov Nekrich, Sebastian Wild, Kaiyu Wu Jan 2020

Distance Oracles For Interval Graphs Via Breadth-First Rank/Select In Succinct Trees, Meng He, J. Ian Munro, Yakov Nekrich, Sebastian Wild, Kaiyu Wu

Michigan Tech Publications, Part 1

We present the first succinct distance oracles for (unweighted) interval graphs and related classes of graphs, using a novel succinct data structure for ordinal trees that supports the mapping between preorder (i.e., depth-first) ranks and level-order (breadth-first) ranks of nodes in constant time. Our distance oracles for interval graphs also support navigation queries – testing adjacency, computing node degrees, neighborhoods, and shortest paths – all in optimal time. Our technique also yields optimal distance oracles for proper interval graphs (unit-interval graphs) and circular-arc graphs. Our tree data structure supports all operations provided by different approaches in previous work, as well …

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Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan Jan 2020

Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally …

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Computer Science For Equity: Teacher Education, Agency, And Statewide Reform, Joanna Goode, Max Skorodinsky, Jill Hubbard, James Hook Jan 2020

Computer Science For Equity: Teacher Education, Agency, And Statewide Reform, Joanna Goode, Max Skorodinsky, Jill Hubbard, James Hook

Computer Science Faculty Publications and Presentations

This paper reports on a statewide “Computer Science for All” initiative in Oregon that aims to democratize high school computer science and broaden participation in an academic subject that is one of the most segregated disciplines nationwide, in terms of both race and gender. With no statewide policies to support computing instruction, Oregon's legacy of computer science education has been marked by both low participation and by rates of underrepresented students falling well-below the already dismal national rates. The study outlined in this paper focuses on how teacher education can support educators in developing knowledge and agency, and impacting policies …

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On Basing One-Way Permutations On Np-Hard Problems Under Quantum Reductions, Nai-Hui Chia, Sean Hallgren, Fang Song Jan 2020

On Basing One-Way Permutations On Np-Hard Problems Under Quantum Reductions, Nai-Hui Chia, Sean Hallgren, Fang Song

Computer Science Faculty Publications and Presentations

A fundamental pursuit in complexity theory concerns reducing worst-case problems to average-case problems. There exist complexity classes such as PSPACE that admit worst-case to average-case reductions. However, for many other classes such as NP, the evidence so far is typically negative, in the sense that the existence of such reductions would cause collapses of the polynomial hierarchy(PH). Basing cryptographic primitives, e.g., the average-case hardness of inverting one-way permutations, on NP-completeness is a particularly intriguing instance. As there is evidence showing that classical reductions from NP-hard problems to breaking these primitives result in PH collapses, it seems unlikely to base cryptographic …

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Selectivity And Robustness Of Sparse Coding Networks, Dylan M. Paiton, Charles Frye, Sheng Y. Lundquist, Joel D. Bowen, Ryan Zarcone, Bruno A. Olshausen Jan 2020

Selectivity And Robustness Of Sparse Coding Networks, Dylan M. Paiton, Charles Frye, Sheng Y. Lundquist, Joel D. Bowen, Ryan Zarcone, Bruno A. Olshausen

Computer Science Faculty Publications and Presentations

We investigate how the population nonlinearities resulting from lateral inhibition and thresholding in sparse coding networks influence neural response selectivity and robustness. We show that when compared to pointwise nonlinear models, such population nonlinearities improve the selectivity to a preferred stimulus and protect against adversarial perturbations of the input. These findings are predicted from the geometry of the single-neuron iso-response surface, which provides new insight into the relationship between selectivity and adversarial robustness. Inhibitory lateral connections curve the iso-response surface outward in the direction of selectivity. Since adversarial perturbations are orthogonal to the iso-response surface, adversarial attacks tend to be …

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Continuous Deployment Transitions At Scale, Laurie Williams, Kent Beck, Jeffrey Creasey, Andrew Glover, James Holman, Jez Humble, David Mclaughlin, John Thomas Micco, Brendan Murphy, Jason A. Cox, Vishnu Pendyala, Steven Place, Zachary T. Pritchard, Chuck Rossi, Tony Savor, Michael Stumm, Chris Parnin Jan 2020

Continuous Deployment Transitions At Scale, Laurie Williams, Kent Beck, Jeffrey Creasey, Andrew Glover, James Holman, Jez Humble, David Mclaughlin, John Thomas Micco, Brendan Murphy, Jason A. Cox, Vishnu Pendyala, Steven Place, Zachary T. Pritchard, Chuck Rossi, Tony Savor, Michael Stumm, Chris Parnin

Faculty Research, Scholarly, and Creative Activity

Predictable, rapid, and data-driven feature rollout; lightning-fast; and automated fix deployment are some of the benefits most large software organizations worldwide are striving for. In the process, they are transitioning toward the use of continuous deployment practices. Continuous deployment enables companies to make hundreds or thousands of software changes to live computing infrastructure every day while maintaining service to millions of customers. Such ultra-fast changes create a new reality in software development. Over the past four years, the Continuous Deployment Summit, hosted at Facebook, Netflix, Google, and Twitter has been held. Representatives from companies like Cisco, Facebook, Google, IBM, Microsoft, …

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Evolution Of Integration, Build, Test, And Release Engineering Into Devops And To Devsecops, Vishnu Pendyala Jan 2020

Evolution Of Integration, Build, Test, And Release Engineering Into Devops And To Devsecops, Vishnu Pendyala

Faculty Research, Scholarly, and Creative Activity

Software engineering operations in large organizations are primarily comprised of integrating code from multiple branches, building, testing the build, and releasing it. Agile and related methodologies accelerated the software development activities. Realizing the importance of the development and operations teams working closely with each other, the set of practices that automated the engineering processes of software development evolved into DevOps, signifying the close collaboration of both development and operations teams. With the advent of cloud computing and the opening up of firewalls, the security aspects of software started moving into the applications leading to DevSecOps. This chapter traces the journey …

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Supp & Mapp: Adaptable Structure-Based Representations For Mir Tasks, Claire Savard, Erin H. Bugbee, Melissa R, Mcguirl, Katherine M. Kinnaird Jan 2020

Supp & Mapp: Adaptable Structure-Based Representations For Mir Tasks, Claire Savard, Erin H. Bugbee, Melissa R, Mcguirl, Katherine M. Kinnaird

Statistical and Data Sciences: Faculty Publications

Accurate and flexible representations of music data are paramount to addressing MIR tasks, yet many of the existing approaches are difficult to interpret or rigid in nature. This work introduces two new song representations for structure-based retrieval methods: Surface Pattern Preservation (SuPP), a continuous song representation, and Matrix Pattern Preservation (MaPP), SuPP’s discrete counterpart. These representations come equipped with several user-defined parameters so that they are adaptable for a range of MIR tasks. Experimental results show MaPP as successful in addressing the cover song task on a set of Mazurka scores, with a mean precision of 0.965 and recall of …

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Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇ Jan 2020

Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Personalization is a common technique used in Web search engines to improve the effectiveness of retrieval. While personalizing some queries yields significant improvements in user experience by providing a ranking in line with the user preferences, it fails to improve or even degrades the effectiveness for less ambiguous queries. A potential personalization metric could improve search engines by selectively applying personalization. One such measure, click entropy uses the query history and the clicked documents for the query, which might be sparse for some queries. In this article, the topic entropy measure is improved by integrating the user distribution into the …

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An Alternative Method Of Biomedical Signal Transmission Through The Gsm Voice Channel, Seyedmohsen Dehghan, Mehmet Kaya Jan 2020

An Alternative Method Of Biomedical Signal Transmission Through The Gsm Voice Channel, Seyedmohsen Dehghan, Mehmet Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a new solution for online and accurate biomedical data transmission is presented. For this purpose, a global system for mobile (GSM) communication voice channel is, for the first time, used as a communication link between the patient and healthcare provider. Biomedical signals are converted into speech-like signals before being transferred over a GSM voice channel. On the receiver side, speech-like symbols are stored in a symbols bank, and constructed using random stochastic signals. On the receiver end, the index of the symbol with the most similarity to the received signal is selected as the identified sample. This …

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