Digital Commons Network^™

6g Enabled Smart Infrastructure For Sustainable Society: Opportunities, Challenges, And Research Roadmap, Abotinam Lucky Imoize, Oluwadara Adedeji, Nistha Tandiya, Sachin Shetty

VMASC Publications

The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to …

Detection And Recognition Of Moving Video Objects: Kalman Filtering With Deep Learning, Hind Rustum Mohammed, Zahir M. Hussain

Research outputs 2014 to 2021

© 2021. All rights reserved. Research in object recognition has lately found that Deep Convolutional Neuronal Networks (CNN) provide a breakthrough in detection scores, especially in video applications. This paper presents an approach for object recognition in videos by combining Kalman filter with CNN. Kalman filter is first applied for detection, removing the background and then cropping object. Kalman filtering achieves three important functions: predicting the future location of the object, reducing noise and interference from incorrect detections, and associating multi-objects to tracks. After detection and cropping the moving object, a CNN model will predict the category of object. The …

Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong

Dissertations

A parallel decentralized binary decision fusion architecture employs a bank of local detectors (LDs) that access a commonly-observed phenomenon. The system makes a binary decision about the phenomenon, accepting one of two hypotheses (H0 (“absent”) or H1 (“present”)). The k 1 LD uses a local decision rule to compress its local observations yk into a binary local decision uk; uk = 0 if the k 1 LD accepts H0 and uk = 1 if it accepts H1. The k 1 LD sends its decision uk over a noiseless dedicated channel to a Data Fusion Center (DFC). The DFC combines the …

Ieee Access Special Section Editorial: Green Signal Processing For Wireless Communicationsand Networking, Wen-Long Chin, David Shiung, Yi Qian, Woongsup Lee, Andres Kwasinki, Yansha Deng

Department of Electrical and Computer Engineering: Faculty Publications

No abstract provided.

Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun

Turkish Journal of Electrical Engineering and Computer Sciences

JPEG is the most widely used image compression standard for sensing, medical, and security applications. JPEG provides a high degree of compression but field devices relying on battery power must further economize on data transmissions to prolong deployment duration with particular use cases in wireless sensor networks. Transmitting a subset of image data could potentially enhance the battery life of power-constrained devices and also meet the application requirements to identify the objects within an image. Depending on an application's needs, after the first selected subset is received at the base station, further transmissions of the image data for successive refinements …

A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …

Development Of A Supervised Classification Method To Construct 2d Mineral Mapson Backscattered Electron Images, Mahmut Camalan, Mahmut Çavur

Turkish Journal of Electrical Engineering and Computer Sciences

The Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators also suggest that the proposed method may be applied to classify minerals with similar appearances under BSE imaging. Meanwhile, random forest predicts fewer middling particles with binary and ternary …

Performance Analysis Of A Fuzzy Disparity Selector For Stereo Matching Of Imagesegments Under Radiometric Variations, Akhil Appu Shetty, Vadakekara Itty George, Chempi Gurudas Nayak, Raviraj Shetty

Turkish Journal of Electrical Engineering and Computer Sciences

Stereo matching algorithms generate disparity maps, which contain the depth information of the environment, from two or more images of a scene taken from different viewpoints. The process of obtaining dense disparity maps is a problem which is still being actively researched. The presence of radiometric differences in the images only further complicates the stereo matching problem. In the present research work, the images are initially split into small patches of pixels, such that pixels in each patch have similar intensities. The authors attempt to study the effect of the parameters, namely, tuning parameter `?? and the number of segments, …

Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar

Publications

The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive …

Emotion Recognition Using Facial Feature Extraction, Demiyan Smirnov

Theses and Dissertations

Computerized emotion recognition systems can be powerful tools to help solve problems in a wide range of fields including education, healthcare, and marketing. Existing systems use digital images or live video to track facial expressions on a person's face and deduce that person's emotional state. The research presented in this thesis explores combinations of several facial feature extraction techniques with different classifier algorithms. Namely, the feature extraction techniques used in this research were Discrete Cosine/Sine Transforms, Fast Walsh-Hadamard Transform, Principle Component Analysis, and a novel method called XPoint. Features were extracted from both global (using the entire facial image) and …

Comparison Of Activity Recognition Using 2d And 3d Skeletal Joint Data, Fiona Marshall, Shuai Zhang, Bryan Scotney

Session 1: Active Vision, Tracking, Motion Analysis

No abstract provided.

Matlab Gui Based Educational Simulation Tool Box For Power Analysis, Tharuka Senevirathne

All Graduate Theses, Dissertations, and Other Capstone Projects

One of the most important and complex tasks in power engineering is the analysis of power systems under fault conditions. The detection and analysis of these faults are important to guarantee that the dependability and stability of the power system does not decline as a result of a critical event such as a fault. This thesis will conduct research on how a power system under fault conditions behaves and will examine the various scenarios of faults such as three-phase, single line-to-ground, line-to-line, and double line-to-ground faults. A simplified method based on symmetrical components is used to construct the mathematical models …

Spatial-Aware Global Contrast Representation For Saliency Detection, Dan Xu, Shucheng Huang, Xin Zuo

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning networks have been demonstrated to be helpful when used in salient object detection and achieved superior performance than the methods that are based on low-level hand-crafted features. In this paper, we propose a novel spatial-aware contrast cube-based convolution neural network (CNN) which can further improve the detection performance. From this cube data structure, the contrast of the superpixel is extracted. Meanwhile, the spatial information is preserved during the transformation. The proposed method has two advantages compared to the existing deep learning-based saliency methods. First, instead of feeding the deep learning networks with raw image patches or pixels, we …

A Computational Study On Aging Effect For Facial Expression Recognition, Elena Sönmez

Turkish Journal of Electrical Engineering and Computer Sciences

This work uses newly introduced variations of the sparse representation-based classifier (SRC) to challenge the issue of automatic facial expression recognition (FER) with faces belonging to a wide span of ages. Since facial expression is one of the most powerful and immediate ways to disclose individuals? emotions and intentions, the study of emotional traits is an active research topic both in psychology and in engineering fields. To date, automatic FER systems work well with frontal and clean faces, but disturbance factors can dramatically decrease their performance. Aging is a critical disruption element, which is present in any real-world situation and …

Fpga-Based Dsp System, Aaron Nguyen

Computer Engineering

The purpose of this project is to create a modular FPGA-based filtering system for audio in VHDL. The final implementation has a working input, output, and filtering system but the filtering system still must be fine-tuned.

Volumetric 3d Reconstruction Of Real Objects Using Voxel Mapping Approach In A Multiple-Camera Environment, Tushar Jadhav, Kulbir Singh, Aditya Abhyankar

Turkish Journal of Electrical Engineering and Computer Sciences

Extracting 3D information from 2D images is an inverse estimation problem and a challenging task in itself. The aim of 2D to 3D reconstruction is to generate either a volume or a surface representing the object from multiple views. This paper presents a simple and accurate multiple-view volumetric 3D reconstruction method using an integrated approach based on homography estimation and voxel mapping. The homography-based approaches give accurate estimates but do not provide system dynamics. The voxel-based volumetric reconstruction methods provide system dynamics that are essential for system modeling. However, they face challenges while modeling the concavities. This paper presents a …

An Adaptive Machine Learning-Based Qoe Approach In Sdn Context For Video-Streaming Services, Asma Ben Letaifa

Turkish Journal of Electrical Engineering and Computer Sciences

In data service applications over the Internet, user perception and satisfaction can be assessed by quality of experience (QoE) metrics. QoE depends both on the users' perception and the used service, which together form end-to-end metrics. While network optimization has traditionally focused on optimizing network properties such as QoS, we focus in this work on optimizing end-to-end QoE metrics with the aim to deliver to the client a good QoE that can be monitored in real time. We argue that end-user QoE is a relevant measurement for network operators and service providers. In this paper, we present a machine learning …

Can Threshold-Based Sensor Alerts Be Analysed To Detect Faults In A District Heating Network?, Liam Cantwell

Dissertations

Older IoT “smart sensors” create system alerts from threshold rules on reading values. These simple thresholds are not very flexible to changes in the network. Due to the large number of false positives generated, these alerts are often ignored by network operators. Current state-of-the-art analytical models typically create alerts using raw sensor readings as the primary input. However, as greater numbers of sensors are being deployed, the growth in the number of readings that must be processed becomes problematic. The number of analytic models deployed to each of these systems is also increasing as analysis is broadened. This study aims …

Implementation And Comparison Of Serial And Parallel Algorithms Of Sao In Hevc, Harsha Nagathihalli Jagadish

Electrical Engineering Theses - Archive

The High Efficiency Video Coding (HEVC) standard is the latest video coding project developed by the Joint Collaborative Team on Video Coding (JCT-VC) which involves the International Telecommunication Union (ITU-T) Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) standardization organizations. HEVC also known as H.265 supports encoding videos with wide range of resolutions, starting from low resolution to beyond High Definition i.e. 4k or 8k. The HEVC standard is an optimization of the previous standard H.264/AVC (Advanced Video coding) which is a very well established and widely used standard in industry and finds its applications …

Case Study On Wavelet Choice Based On Statistical Image Quality Measures, Igor Vujovic, Ivica Kuzmanic

Turkish Journal of Electrical Engineering and Computer Sciences

Surveillance applications are under many negative influences, which should be suppressed, because these negative influences result in incorrectness of the motion mask. Suppression of several conflicting requirements can be optimized by a multiobjective approach. This paper proposes a multiobjective approach to selection of wavelets based on two main objectives: statistical image quality measures and execution time. Execution time is a measure of wavelets complexity. Segmentation is the final goal in order to insure precise operation of any surveillance algorithm. This paper presents a case study considering one, two, three, and four goals for wavelet selection comparison. Different wavelets are found …

Rainbow Peacock Spiders Inspire Miniature Superiridescent Optics, Bor-Kai Hsiung, Radwanul Hasan Siddique, Doekele G. Stavenga, Jürgen C. Otto, Michael C. Allen, Ying Liu, Yongfeng Lu, Dimitri D. Deheyn, Matthew D. Shawkey, Todd A. Blackledge

Department of Electrical and Computer Engineering: Faculty Publications

Colour produced by wavelength-dependent light scattering is a key component of visual communication in nature and acts particularly strongly in visual signalling by structurallycoloured animals during courtship. Two miniature peacock spiders (Maratus robinsoni and M. chrysomelas) court females using tiny structured scales (~ 40 × 10 μm²) that reflect the full visual spectrum. Using TEM and optical modelling, we show that the spiders’ scales have 2D nanogratings on microscale 3D convex surfaces with at least twice the resolving power of a conventional 2D diffraction grating of the same period. Whereas the long optical path lengths required …

Electrical And Computer Engineering Annual Report 2017, Department Of Electrical And Computer Engineering, Michigan Technological University

Department of Electrical and Computer Engineering Annual Reports

• Early Career Awards
• Faculty Directory
• Faculty Highlights
• Special Report: Mobility at Michigan Tech
• Faculty Publications
• Staff Profile & Directory
• Graduate Student Research
• Accelerated Master's Degree
• Graduate Student Awards & Degrees
• Undergraduate Highlights
• Senior Design
• Enterprise
• Undergraduate Student Awards & Advisory
• Grants & Contracts
• Departmental Statistics
• A Pioneer's Story

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Annual ADFSL Conference on Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …

Hdr Video Compression Using H.265 (Hevc) Main 10 Profile, Srikanth Vasireddy

Electrical Engineering Theses - Archive

Increasing the resolution of the video has been the main interest in the television industry for a long time. More recently the industry is studying techniques to increase the range of luminance and color representation in videos. This is achieved through High Dynamic Range/ Wide Color Gamut (HDR/WCG) videos by providing visual quality of experience to the end consumers close to that of real life compared to the Standard Dynamic Range (SDR) videos.In order to deliver high-quality video services to consumers, efficient compression techniques are required to store or transmit a video especially for high resolution video formats whilst maintaining …

Reversible Data Hiding Using Histogram Shifting, Sai Saketh Nandagiri

Electrical Engineering Theses - Archive

With the current state-of-the-art technology, intruders can easily gain access to sensitive information. To avoid this, different methods with improved security to hide information have been developed like, covert channels, hiding data in images, null ciphers, etc. The focus of this work is to enhance the security and data hiding capacity of the current state-of-the-art reversible data hiding algorithms. The proposed data hiding method is designed such that the original image is losslessly restored after extraction of a payload. The proposed framework allows embedding of a binary bit stream into the host or cover image while retaining the quality of …

Electrical And Computer Engineering Annual Report 2016, Department Of Electrical And Computer Engineering, Michigan Technological University

Department of Electrical and Computer Engineering Annual Reports

• Faculty Directory
• Faculty Highlights
• Faculty Fellow Program
• Multidisciplinary Research Fills Critical Needs
• Better, Faster Technology
• Metamaterials: Searching for the Perfect Lens
• The Nontraditional Power of Demand Dispatch
• Space, Solar Power's Next Frontier
• Kit Cischke, Award-Winning Senior Lecturer
• Faculty Publications
• ECE Academy Class of 2016
• Staff Profile: Michele Kamppinen
• For the Love of Teaching: Jenn Winikus
• Graduate Student Highlights
• Undergraduate Student Highlights
• External Advisory Committee
• Contracts and Grants
• Department Statistics
• AAES National Engineering Award

An Efficient Method For Optimizing Segmentation Parameters, Jacob D' Avy, Wei-Wen Hsu, Chung-Hao Chen, Andreas F. Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Segmenting an image into meaningful regions is an important step in many computer vision applications such as facial recognition, target tracking and medical image analysis. Because image segmentation is an ill-posed problem, parameters are needed to constrain the solution to one that is suitable for a given application. For a user, setting parameter values is often unintuitive. We present a method for automating segmentation parameter selection using an efficient search method to optimize a segmentation objective function. Efficiency is improved by utilizing prior knowledge about the relationship between a segmentation parameter and the objective function terms. An adaptive sampling of …

Countering Noise-Based Splicing Detection Using Noise Density Transfer, Thibault Julliand, Vincent Nozick, Hugues Talbot

Journal of Digital Forensics, Security and Law

Image splicing is a common and widespread type of manipulation, which is defined as pasting a portion of an image onto a second image. Several forensic methods have been developed to detect splicing, using various image properties. Some of these methods exploit the noise statistics of the image to try and find discrepancies. In this paper, we propose a new counter-forensic approach to eliminate the noise differences that can appear in a spliced image. This approach can also be used when creating computer graphics images, in order to endow them with a realistic noise. This is performed by changing the …

Novel H.265 Video Traffic Prediction Models Using Artificial Neural Networks, Collin Daly

Honors College Theses

In this work, we propose the use of non-linear, autoregressive neural network models for predicting video frame sizes. This model utilizes H.265 encoded video traces as inputs and the predicted future frame sizes as outputs. This model is developed to predict ultra-high definition video frame encoded with H.265 within IP networks. The video I, P, and B frames are predicted separately to improve model prediction accuracy. This approach is verified in MATLAB using various H.265 video traces. The results indicate that the proposed models were able to predict the video traffic fairly accurately.

H.265 (Hevc) Bitstream To H.264 (Mpeg 4 Avc) Bitstream Transcoder, Deepak Hingole

Electrical Engineering Theses - Archive

With every new video coding standard the general rule of thumb has been to maintain same video quality at a reduced bit rate of about 50% as compared to the previous standard. H.265 is the latest video coding standard with support for encoding videos with wide range of resolutions, starting from low resolution to beyond High Definition i.e. 4k or 8k. H.265 also known as HEVC was preceded by H.264 which is very well established and widely used standard in industry and finds its applications in broadcast, storage, multimedia telephony. Currently almost all devices including low power handheld mobile devices …