Papers by Anke Meyer-Baese
Communication Systems
Springer eBooks, 2014
Advanced Topics
Springer eBooks, 2001
Dynamical graph networks may aid in phenotyping prognostically different brain tumor types
Emerging Topics in Artificial Intelligence (ETAI) 2022
An Evolutionary Framework for Real-Time Fraudulent Credit Detection
2021 IEEE Congress on Evolutionary Computation (CEC)
Fraud has been a worldwide issue that is facing the major economies of the world. Within an econo... more Fraud has been a worldwide issue that is facing the major economies of the world. Within an economical system, undetected and unpunished fraudulent activities can erode the public trust in law enforcement institutions and even incentivize more fraud. Therefore, detection of fraudulent activities and prosecution of responsible entities is of utmost importance for financial regulatory bodies around the globe. Of the challenges rising with this task is the scarcity of detection resources (auditors) and the fraudsters constantly adapting to the new circumstances of the market. To address these issues, this paper proposes an evolutionary framework for credit fraud detection with the ability to incorporate (and adapt to) the incoming data in real-time. The goal of the framework is to identify the entities with high a risk of fraud for efficient targeting of the scarce resources. The data that is generated as a result of the audits are fed into the framework for further training.
Multi-stage Optimization Of A Deep Model
PLOS ONE, 2018
Computer Arithmetic
Digital Signal Processing with Field Programmable Gate Arrays, 2014
Genetic Algorithms
Elsevier eBooks, 2014
Genetic algorithms (GA) like neural networks are biologically inspired and represent a new comput... more Genetic algorithms (GA) like neural networks are biologically inspired and represent a new computational model having its roots in evolutionary sciences. In this chapter, we review the basics of GAs, briefly describe the schema theorem and the building block hypothesis, and describe feature selection based on GAs, as one of the most important applications of GAs.
Dynamics of a nonlocal dispersal in‐host viral model with humoral immunity
Studies in Applied Mathematics
Analysis of a stochastic reaction–diffusion Alzheimer’s disease system driven by space–time white noise
Applied Mathematics Letters
Disruptive Technologies in Information Sciences, 2018
The Internet of Things concept is described as a network of interconnected physical objects capab... more The Internet of Things concept is described as a network of interconnected physical objects capable of gather, process, and communicate information about their environment, and potentially affect the physical world around them through their sensors, embedded processors, communication modules, and actuators, respectively. Such a network can provide vital information on events, processes, activities, and future projections about the state of a distributed system. In addition, it can give the devices inside the network awareness about their environment far beyond the range of their dedicated sensors through communication with other devices. In most cases, such network consists of devices with different processing and communication capacities and protocols, from a variety of hardware vendors. This paper introduces an abstracted messaging and commanding framework for smart objects, aimed towards making the network capable of including various communication standards. This issue is addressed by proposing a messaging structure based on JavaScript object notation (JSON) format so the new devices connecting to the network can introduce themselves to the central coordinator. The introduction includes a list of functionalities that the device is capable of, and the information it needs to carry out those tasks. This platform makes the network capable of incorporating different devices with various purposes and functions with ease and flexibility. Having a fast, reliable, and scalable communication scheme is critical for realization of a robust and flexible network.
Owgis 2.0: Open Source Java Application that Builds Web GIS Interfaces for Desktop Andmobile Devices
AGU Fall Meeting Abstracts, Dec 1, 2016
Breast lesion segmentation software for DCE-MRI: An open source GPGPU based optimization
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018
Efficient algorithms for segmentation are a key step in medical imaging and of fundamental import... more Efficient algorithms for segmentation are a key step in medical imaging and of fundamental importance in computer aided diagnosis of breast cancer for: diagnostics, evaluation of neoadjuvant therapy, or surgery. With the advance of high resolution images, as 3D dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) images, the computational cost of segmentation methods has become more expensive as the amount of data has grown. In this work, a segmentation method for breast cancer lesions in DCE-MRI images based on the active contour without edges (ACWE) algorithm and using parallel programming with general purpose computing on graphics processing units (GPGPUs) is presented. The performance of the segmentation algorithm is evaluated on a set of 32 breast DCE-MRI cases in terms of speedup, and compared to non-GPU based approaches. A high speedup (40 or more) is obtained for high resolution images, providing real-time outputs.
Smart Biomedical and Physiological Sensor Technology XV, 2018
This article presents a prototype of a wearable instrument for oxygen saturation and ECG monitori... more This article presents a prototype of a wearable instrument for oxygen saturation and ECG monitoring. The proposed measuring system is based on the variability of the light reflection of a LED emission placed on the subject's temple. Besides, the system has the capacity to incorporate electrodes to obtain ECG measurements. The activity of the user can be monitored through an accelerometer. All measurements are stored and transmitted to a mobile device (tablet or smartphone) through a Bluetooth link where the information is treated and shown to the user.
The current method for the extraction of olive oil consists on the use of a decanter to split it ... more The current method for the extraction of olive oil consists on the use of a decanter to split it by centrifugation. During this process, different olive oil samples are analyzed in a chemical laboratory in order to determine moisture levels in the oil, which is a decisive factor in olive oil quality. However, these analyses are usually both costly and slow. The developed prototype is the foundation of an instrument for real-time monitoring of moisture in olive oil. Using the olive oil as the dielectric of a parallel-plate capacitor, a model to relate the moisture in olive oil and capacitance has been created. One of the challenges for this application is the moisture range, which is usually between 1 and 2%, thus requiring the detection of pF-order variations in capacitance. This capacitance also depends on plate size and the distance between plates. The presented prototype, which is based on a PSoC (Programmable System-on-Chip), includes a reconfigurable digital and analog subsyste...
Case-Based Support Vector Optimization for Medical-Imaging Imbalanced Datasets
Imbalanced datasets constitute a challenge in medical-image processing and machine learning in ge... more Imbalanced datasets constitute a challenge in medical-image processing and machine learning in general. When the available training data is highly imbalanced, the risk for a classifier to find the trivial solution increases dramatically. To control the risk, an estimate on the prior class probabilities is usually required. In some medical datasets, such as breast cancer imaging techniques, estimates on the priors are intractable. Here we propose a solution to the imbalanced support vector classification problem when prior estimations are absent based on a case-dependent transformation on the decision function.
Big Data: Learning, Analytics, and Applications, 2019
The advancement of Internet of Things (IoT) technologies, such as low-cost embedded single board ... more The advancement of Internet of Things (IoT) technologies, such as low-cost embedded single board computers which integrate sensors, communication hardware, and processing power in one unit, has given more traction to the concept of Smart Cities. Having cheaper processing power at their disposal, the sensing units are capable of gathering increasingly larger amounts of raw data locally, which must be processed before being usable. One concern for this scheme is the amount of infrastructure and network bandwidth needed to transfer the data from the acquisition location to a server, which may be miles away, for further processing. The bandwidth available to the sensor network, distributed through the city, is expanding in a lower rate than the size and bandwidth demand of the network it serves. Therefore, transferring the unprocessed data to a central server does not seem feasible unless major compromises are made in terms of data resolution and size. This paper proposes a local big da...
Reproducible Evaluation of Registration Algorithms for Movement Correction in Dynamic Contrast Enhancing Magnetic Resonance Imaging for Breast Cancer Diagnosis
Accurate methods for computer aided diagnosis of breast cancer increase accuracy of detection and... more Accurate methods for computer aided diagnosis of breast cancer increase accuracy of detection and provide support to physicians in detecting challenging cases. In dynamic contrast enhancing magnetic resonance imaging (DCE-MRI), motion artifacts can appear as a result of patient displacements. Non-linear deformation algorithms for breast image registration provide with a solution to the correspondence problem in contrast with affine models. In this study we evaluate 3 popular non-linear registration algorithms: MIRTK, Demons, SyN Ants, and compare to the affine baseline. We propose automatic measures for reproducible evaluation on the DCE-MRI breast-diagnosis TCIA-database, based on edge detection and clustering algorithms, and provide a rank of the methods according to these measures.
and Phenotype Presentation of Breast Cancer with a Special Focus on High-Risk Women
Breast cancer is a diverse collection of diseases with varying clinical presentations, subtypes, ... more Breast cancer is a diverse collection of diseases with varying clinical presentations, subtypes, and treatment responses. In the past decade, gene-expression profiling has revolutionized breast cancer classifications, and the traditional classifications based on immunohistochemistry have been replaced by molecular subtype profiles. Breast cancer has four distinct molecular subtypes: luminal A; luminal B; human epidermal growth factor receptor 2 (HER2)-enriched; and basal-like. These subtypes are unevenly distributed among women with breast cancer and demonstrate distinct differences in tumor phenotypic presentations. In addition, each molecular subtype has shown varying risk for progression, response to treatment, and survival outcomes; and currently, subtype-based recommendations for systemic therapies for breast cancer are used in clinical practice. As medical research and therapy have entered the genomic era in which personalized approaches toward treatment are being explored, di...
Probabilistic neural networks
Handbook of Probabilistic Models, 2020
Abstract Probabilistic neural networks (PNNs) offer a scalable alternative to the conventional ba... more Abstract Probabilistic neural networks (PNNs) offer a scalable alternative to the conventional back-propagation neural networks in classification problems without the need for massive forward and backward calculations that is associated with the ordinary neural networks. In addition, they can work with smaller sets of training data. However, this advantage may come at a cost of requiring large amounts of memory as the training data get larger. This chapter takes a look at the fundamental mathematics behind the modern PNNs, their application, and approaches that address some practical issues that come with them.
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Papers by Anke Meyer-Baese