Mariofanna Milanova

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Verified

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• PhD
• Professor (Full) at University of Arkansas at Little Rock

The inherent challenges of financial time series forecasting demand advanced modeling techniques for reliable predictions. Effective financial time series forecasting is crucial for financial risk management and the formulation of investment decisions. The accurate prediction of stock prices is a subject of study in the domains of investing and nat...

Background Artificial intelligence (AI) is rapidly being adopted to build products and aid in the decision-making process across industries. However, AI systems have been shown to exhibit and even amplify biases, causing a growing concern among people worldwide. Thus, investigating methods of measuring and mitigating bias within these AI-powered to...

Examine the synergistic possibilities of combining blockchain, IoT, and AI technologies in supply chain management. This book will address the difficulties and possibilities of integrating these technologies and offer helpful implementation advice. The current state of supply chain management involves several challenges, including lack of transpar...

The global economy relies on logistics companies to help transfer commodities and goods worldwide. However, logistics firms are feeling the heat to cut costs and improve efficiency in light of the growing interest in sustainability. One strategy for accomplishing this goal is to streamline operations through the use of Internet of Things technologi...

This chapter compares how blockchain, the Internet of Things (IoT), and artificial intelligence (AI) technologies are used in supply chain to promote sustainability. The chapter starts with explaining the concept of supply chains and their increasing importance in today’s business world. It explores the challenges and objectives involved in managin...

Audio classification using deep learning models, which is essential for applications like voice assistants and music analysis, faces challenges when deployed on edge devices due to their limited computational resources and memory. Achieving a balance between performance, efficiency, and accuracy is a significant obstacle to optimizing these models...

This paper introduces a new classifier based on the Hellinger distance to overcome the challenges encountered by standard classifiers in accurately diagnosing seizure epilepsy using electroencephalogram (EEG) signals. They mainly suffer from poor discriminative capacity and sensitivity towards datasets with class imbalance and inefficiency towards...

Audio classification using deep learning models, essential for applications like voice assistants and music analysis, faces challenges when deployed on edge devices due to their limited computational resources and memory. Achieving a balance between performance, efficiency, and accuracy is a significant obstacle in optimizing these models for such...

For both teachers and students studying science, technology, engineering, and mathematics (STEM), active learning is more likely to be productive because learners engage in a variety of classroom activities. As instructors are trying different pedagogies in the classroom, it is also important to check the effectiveness of those methods. Our work ai...

Humans can provide arguments, cite proof, and express confidence in their predictions. They may also say, “I don’t know,” if there isn’t enough information. However, only some of the multimodal image retrieval techniques now in use have these characteristics, making the models extremely opaque and unreliable. Additionally, the vision-language task...

Multimodal learning is omnipresent in our lives. Human absorbs features in different ways, whether through pictures or text. Combining these features in computational science, especially in Image retrieval problems, poses two significant challenges: how and when to fuse them. Most image retrieval systems use images or text data associated with the...

Active learning can be immensely beneficial for science, technology, engineering, and mathematics (STEM) students as well as instructors because they engage themselves with various activities in the classroom so that lectures will be more effective. Automatic audio classification for classroom activities can help us to improve the active learning s...

Nowadays, wearing a face mask is a vital routine in life, but threats are increasing in public due to the advantage of wearing face masks. Existing works do not perfectly detect the human face and also not possible to apply for different faces detection. To overwhelm this issue, in this paper we proposed real-time face mask detection. The proposed...

Human gait is essential for long-term health monitoring as it reflects physical and neurological aspects of a person’s health status. In this paper, we propose a non-invasive video-based gait analysis system to detect abnormal gait, and record gait and postural parameters framework on a day-to-day basis. It takes videos captured from a single camer...

This paper presents the implementation of a markerless mobile augmented reality application called a virtual eye glasses try-on system. The system first detects and tracks human face and eyes. Then, the system overlays the 3D virtual glasses over the face in real time. This system helps the consumer to select any style of glasses available on the v...

Internet of Things (IoT) studies inter connected devices that consumes web facilities over the internet. Smart phones, smart TVs, medical devices or industrial devices can be examples of things that may connect via internet. IoT devices are supported by many standards like: HTTP (Hypertext Transferring Protocol), MQTT (Message Queue Telemetry Trans...

Internet of Things (IoT) studies interconnected devices that consumes web facilities over the internet. Smart phones, smart TVs, medical devices or industrial devices can be examples of things that may connect via internet. IoT devices are supported by many standards like: HTTP (Hypertext Transferring Protocol), MQTT (Message Queue Telemetry Transp...

Many companies are working to create inside-out marker-less tracking for virtual reality headsets. Inside-out marker-less tracking can be found on consumer augmented reality devices, but currently there is no system available to researchers, developers, or consumers that provides this feature without custom hardware and software. Our research provi...

In this work we show that the sentiment of the broader stock market, namely the S&P 500, is related to the activity of individual stocks intraday. We introduce a concept we term as embedded context which is an approach to improving unigram language models for restricted use cases. We use a Gaussian Mixture Model to create different sentiment regime...

With the fast evolution of medical imaging study, a great interest in skin cancer detection has been investigated with numerous computer algorithms. Generally, skin lesions are examined with a limited quantity of ground truth labeling. The most important part of the medical image's detection is calculating the localization function which is normall...

With the fast evolution of medical imaging study, a great interest in skin cancer detection has been investigated with numerous computer algorithms. Generally, skin lesions are examined with a limited quantity of ground truth labeling. The most important part of the medical image's detection is calculating the localization function which is normall...

This paper presents a new method of image captioning, which generate textual description of an image. We applied our method for infant sleeping environment analysis and diagnosis to describe the image with the infant sleeping position, sleeping surface and bedding condition, which involves recognition and representation of body pose, activity and s...

There has been an increasing interest in developing methods for image representation learning, focused in particular on training deep neural networks to synthesize images. Generative adversarial networks (GANs) are used to apply face aging, to generate new viewpoints, or to alter face attributes like skin color. For forensics specifically on faces,...

This paper presents a new method of image captioning, which generate textual description of an image. We applied our method for infant sleeping environment analysis and diagnosis to describe the image with the infant sleeping position, sleeping surface and bedding condition, which involves recognition and representation of body pose, activity and s...

Designing systems to detect the human gestures and movements is an important area in computer vision. In this chapter, a method to detect human eye blink patterns is proposed. Our system detects the user’s eye blink patterns in real time and responds with an action on a mobile device, such as the phone call, text message, and/or an alarm. In this c...

A design of elliptical printed dipole antenna based on neural network approach is presented in this paper for recent WiMAX, Bluetooth, WLAN, LTE, and future 5G applications. The dipole patch is printed on top of substrate which has relative permittivity of 2.2 and 0.787mm of thickness. The elliptical dipole antenna is single band and the operationa...

The papers in this special section focus on cardiovascular system monitoring and therapy. The number of devices for the measurement and interpretation of biological systems that describe performance of the cardiovascular system is growing. Among others, this is due to the improvement of circuit and system design that renders the devices wearable an...

In this paper, we proposed EREGE system, EREGE system considers as a face analysis package including face detection, eye detection, eye tracking, emotion recognition, and gaze estimation. EREGE system consists of two parts; facial emotion recognition that recognizes seven emotions such as neutral, happiness, sadness, anger, disgust, fear, and surpr...

Introduction When facing a complex visual scene, human can efficiently locate region of interest and analyze the scene by selectively processing subsets of visual input. Attention was employed to narrow down the search and speed up the process. 1 Visual attention is a hot topic in computer vision, neuroscience and deep learning area. It's widely us...

A new method to detect human health-related actions (HHRA) from a video sequence using an Android camera. The Android platform works not only to capture video images through its camera, but also to detect emergency actions. An application for HHRA is to help monitor unattended children, individuals with special needs or the elderly. The application...

As Facial Emotion Recognition is becoming more important everyday, A research experiment was conducted to find the best approach for Facial Emotion Recognition. Deep Learning (DL) and Active Shape Model (ASM) were tested. Researchers have worked with Facial Emotion Recognition in the past, with both Deep learning and Active Shape Model, with wantin...

This paper explains research based on improving real time face recognition system using new Radix-(2 × 2) Hierarchical Singular Value Decomposition (HSVD) for 3rd order tensor. The scientific interest, aimed at the processing of image sequences represented as tensors, was significantly increased in the last years. Current home security solutions ca...

This paper presents a new model of scale, rotation, and translations invariant interest point descriptor for human actions recognition. The descriptor, HMIV (Hu Moment Invariants on Videos) is used for solving surveillance camera recording problems under different conditions of side, position, direction and illumination. The proposed approach deals...

There is a great benefit of Alzheimer disease (AD) classification for health care application. AD is the most common form of dementia. This paper presents a new methodology of invariant interest point descriptor for Alzheimer disease classification. The descriptor depends on the normalized Hu Moment Invariants (NHMI). The proposed approach deals wi...

People can accurately identify a common face and understand a facial expression in a single glance. However, children with autism spectrum disorder (ASD) often have problems communicating with their parents, teachers, and other kids. In this paper, we present an innovative system to recognize facial expressions in children with ASD during playtime....

In this paper we present an automatic face recognition system based on incremental Singular Values Decomposition (SVD) and subject dependent Hidden Markov Models (HMM). For each subject, an individual HMM is trained with features, extracted from the orthogonal decomposition (SVD) of the subject's training images. The main advantage of the proposed...

Remote sensing image analysis has been a topic of ongoing research for many years and has led to paradigm shifts in the areas of resource management and global biophysical monitoring. Due to distortions caused by variations in signal/image capture and environmental changes, there is not a definite model for image processing tasks in remote sensing...

The paper presents a new technique for archiving and protecting content of visual medical information. A special format is developed based on a new Inverse Pyramid decomposition. The images are archived with the highest quality but their restoration is performed in accordance with the application. The image content is protected by inserting multipl...

The objective of this study is to explore the effectiveness of three digital shopping platforms (Plain Interactive, Marker-based Augmented Reality and Markerless Augmented Reality), on the impressions and purchase intentions of consumers. The study is mainly interested in analysing whether intelligent shopping platforms with AR elements provide any...

This paper presents a new algorithm for human action recognition in videos. This algorithm is based on a combination of two different feature types extracted from Aligned Motion Images (AMIs). The AMI is a method for capturing the motion of all frames in a human action video in one image. The first feature is a contour-based type and is employed to...

In this paper a new adaptive Brain Computer Interface (BCI) architecture is proposed that allows to autonomously adapt the BCI parameters in malfunctioning situations. Such situations are detected by discriminating EEG Error Potentials and when necessary the BCI mode is switched back to the training stage in order to improve its performance. First,...

Human action recognition in videos is a desired field in computer vision applications since it can be applied in human computer interaction, surveillance monitors, robot vision, etc. Two approaches of features are investigated in this chapter. First approach is a contour-based type. Four features are investigated in this approach such as Cartesian...

Owing to compound textural features, intensity inhomogeneity, image layers, and variations of statistics inherent, the segmenting of complicated images into areas of similarity for scene analysis is a challenging task. In this work, a morphological active contour is developed to increase efficiency of current active contour schemes and a fuzzy clus...

In this work, the Inverse Difference Pyramid (IDP) and its modification – the Reduced IDP (RIDP), are compared and evaluated with the famous Laplacian Pyramid (LP) for multi-level decomposition of digital images. The comparison comprises: the structures of LP and IDP, the image representation through LP and IDP in the pixel space and in the spectru...

Human action recognition in videos is a prominent field in image processing research and it is a frequently required technique for many computer vision applications. In this paper, a new novel algorithm for human action recognition is presented. This algorithm depends on aligned motion images (AMIs). Three types of AMIs are used: aligned motion his...

This chapter is focused on recent advances in electroencephalogram (EEG) signal processing for brain computer interface (BCI) design. A general overview of BCI technologies is first presented, and then the protocol for motor imagery noninvasive BCI for mobile robot control is discussed. Our ongoing research on noninvasive BCI design based not on re...

In this work is presented one new method for invariant object representation based on the Inverse Pyramidal Decomposition (IPD) and modified Mellin-Fourier Transform (MFT). The so prepared object representation is invariant against 2D rotation, scaling, and translation (RST). The representation is additionally made invariant to significant contrast...

This paper presents a morphological active contour ideal for vascular segmentation in biomedical images. The unenhanced images of vessels and background are successfully segmented using a two-step morphological active contour based upon Chan and Vese’s Active Contour without Edges. Using dilation and erosion as an approximation of curve evolution,...

In this work, the structures of the Inverse Difference Pyramid (IDP) and its modification - the Reduced IDP (RIDP), are compared and evaluated with the famous Laplacian Pyramid for multi-level decomposition of digital images. The computational complexity of both decompositions is also evaluated. On the basis of the comparison of the block diagrams,...

The segmentation of natural images remains a challenging task in image processing. Many methods have been proposed in the literature regarding algorithms for the segmentation of such images. Many of the algorithms are complex in nature and inefficient in practice with unaltered images. In order to efficiently use the algorithms it is beneficial to...

In this chapter we propose a solution to the Electroencephalography (EEG) inverse problem combining two techniques, which are the Sequential Monte Carlo (SMC) method for estimating the coordinates of the first two non-correlated dominative brain zones (represented by their respective current dipoles) and spatial filtering which is done by beamformi...

In this paper a new approach is offered for efficient processing and analysis of groups of multispectral images of same objects. It comprises several tools: the Modified Inverse Pyramid Decomposition; the invariant object representation with Modified Mellin-Fourier transform, and the hierarchical search in image databases, for which the invariant r...

In this paper is offered one new approach for efficient processing and analysis of groups of multispectral images of same objects. It comprises several tools: the Inverse pyramid decomposition for still images; the invariant object representation with Modified Mellin-Fourier transform, and the hierarchical search in image databases, for which the i...

In this paper, we study a class of univariate skewed distributions, obtained by converting the symmetric inverted weibull distribution into a skew one. We discuss basic properties of skewed double inverted weibull distribution SDIW , the probability density function, cumulative distribution function, the moments, maximum entropy are derived. Maximu...

The exponentiated -parent distribution is a generalization of the standard parent distribution. [7] introduced a simple generalization to weibull distribution namely the exponentiated weibull distribution. The new distribution was applied to analyzing bathtub failure rates lifetime data. In this paper, we consider the standard exponentiated inverte...

The ability to automatically detect visually interesting regions in images and video has many practical applications, especially in the design of active machine vision and automatic visual surveillance systems.

In this paper, we present a faceted search on a dataset of reports having same structure, which consists of both non-narrative and narrative fields. Our approach exploits prop- erties associated with the dataset especially non-narrative fields, and at the same time gets enjoys full semantic lever-ages of the terms present under the narrative fields...

In this paper is offered one new algorithm for global description of pre-segmented objects in a halftone image. The new algorithm has relatively low computational complexity than the famous Mellin-Fourier transform and permits multi-layer access which enhances the search by content in indexed image databases. The new algorithm is based on the previ...

The paper presents a system for human action recognition using contour based shape representation. With the rapid progress of computing and communication technology smart user computer interfaces are becoming most widespread. A major goal is to go further than traditional human computer interaction (like mouse or keyboard) and to find more natural...