Systems and Communications Commons^™

Ict-Enabled Control And Energy Management Of Community Microgrids For Resilient Smart Grid Operation, Mahmoud Saleh

Dissertations and Theses

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances.

The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack …

Software Defined Radio For Hybrid Beamforming Applications, Jianyet Lee

Dissertations and Theses

Beamforming techniques have been deployed in both licensed networks such as LTE network and unlicensed network such as IEEE802.11ac WiFi. The scope of work for this thesis is to leverage the benefits of beamforming techniques and software defined radio platform in developing a fully functioning LTE testbed. The testbed can be further developed to specific application for drone-to-drone or D2D communication independent of intervention from base stations. Applying beamforming techniques to devices such as drones can solve poor quality signal detection at the receivers due to the interference signals generated by other devices in the attempt to communicate with the …

Scheduling For Cooperative Energy Harvesting Sensor Networks, Ahmed Ammar

Graduate Theses, Dissertations, and Problem Reports (ETD)

In cooperative communication networks, the source node transmits its data to the destination either directly or cooperatively with a cooperating node. When using energy harvesting technology, where nodes collect their energy from the environment, the energy availability at the nodes becomes unpredictable due to the stochastic nature of energy harvesting processes. As a result, when the source has a transmission, it cannot immediately transmit its data cooperatively with the cooperating node. It first needs to determine whether the cooperating node has sufficient energy to forward its transmission or not. Otherwise, its transmitted data may get lost. Therefore, when using energy …

On Board Georeferencing Using Fpga-Based Optimized Second Order Polynomial Equation, Dequan Liu, Guoqing Zhou, Jingjin Huang, Rongting Zhang, Lei Shu, Xiang Zhou, Chun Sheng Xin

Electrical & Computer Engineering Faculty Publications

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable …

On The Distortion Of Uwb Circularly Polarized Time-Domain Pulses In Presence Of Rotation, Adam Narbudowicz, Janusz Przewocki, Max Ammann

Conference Papers

The paper provides a first theoretical study on the effect of rotational Doppler on circularly polarized pulsed communication. Despite the circularly polarized communication being considered immune to signal fading due to rotary misalignment, such misalignment will cause a frequency-invariant phase-shift. This phase shift will significantly distort the shape of the time-domain pulse. The property can be used for integration of orientation sensing into well establish pulse-based localization. However, it has also the potential to distort communication for some pulse-modulated UWB systems.

Compact Broadband Triple-Ring Five-Port Reflectometer For Microwave Brain Imaging Applications, Toufiq Md Hossain, Mohd Faizal Jamlos, Mohd Aminudin Jamlos, Ping Jack Shoh, Siti Zuraidah Ibrahim, Muammar Mohamad Isa, Dominque M.M.-P. Schreurs, Adam Narbudowicz, Mohd Fairusham Ghazali

Articles

The broadband five-port refectometer (FPR) is proposed using a triple-ring based technique. The design introduces a tapering in the inter-ring transmission lines (TLs), which provides additional degrees of freedom for optimization and contributes to increased bandwidth. The miniaturization strategy allows incorporating the third ring without signifcant size increase. In addition, a method for expressing the effective physical dimension of a planar symmetric FPR is also presented in an easily comprehensible way, which can be implemented for other symmetric planar junctions with more than four ports. The proposed design comprises three concentric rings with phase-shifting arrangements between the inter-ring TLs and …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Profiling And Identifying Individual Usersby Their Command Line Usage And Writing Style, Darusalam Darusalam, Helen Ashman

Knowledge Engineering and Data Science

Profiling and identifying individual users is an approach for intrusion detection in a computer system. User profiles are important in many applications since they record highly user-specific information - profiles are basically built to record information about users or for users to share experiences with each other. This research extends previous research on re-authenticating users with their user profiles. This research focuses on the potential to add psychometric user characteristics into the user model so as to be able to detect unauthorized users who may be masquerading as a genuine user. There are five participants involved in the investigation for …

Energy Efficiency Metrics Of University Data Centers, Leonel Hernandez, Genett Jimenez, Piedad Marchena

Knowledge Engineering and Data Science

The data centers are fundamental pieces in the network and computing infrastructure,and evidently today more than ever they are relevant. Since they support the processing, analysis, assurance of the data generated in the network and by the applications in the cloud, which every day increases its volume thanks to technologies such as Internet of Things, Virtualization, and cloud computing, among others. Precisely the management of this large volume of information makes the data centers consume a lot of energy, generating great concern to owners and administrators. Green Data Centers offer a solution to this problem, reducing the impact produced by …

Signature Pattern Recognition Using Kohonen Network, Nadia Roosmalita Sari, Mohammad Zoqi Sarwani, Yudha Alif Aulia, Wayan Firdaus Mahmudy

Knowledge Engineering and Data Science

A signature is a special form of handwriting that used for human identification process. The current identification process is extremely ineffective. People have to manually compare signatures with the previously stored data. This study proposed SOM Kohonen algorithm as the method of signature pattern recognition. This method has able to visualize high-dimensional data. The image processing method is used in this study in pre-processing data phase. The accuracy of SOM Kohonen was 70 %, indicated the method used was good enough for pattern recognition.

Digit Classification Of Majapahit Relic Inscriptionusing Glcm-Svm, Tri Septianto, Endang Setyati, Joan Santoso

Knowledge Engineering and Data Science

A higher level of image processing usually contains some kind of classification or recognition. Digit classification is an important subfield in handwritten recognition.Handwritten digits are characterized by large variations so template matching, in general, is inefficient and low in accuracy. In this paper, we propose the classification of the digit of the year of a relic inscription in the Kingdom of Majapahit using Support Vector Machine (SVM). This method is able to cope with very large feature dimensions and without reducing existing features extraction. While the method used for feature extraction using the Gray-Level Co-Occurrence Matrix (GLCM), special for texture …

Change Vulnerability Forecasting For Southeast Asiausing Deep Learning Algorithm, Amelia Ritahani Ismail, Nur 'Atikah Binti Mohd Ali, Junaida Sulaiman

Knowledge Engineering and Data Science

Climate change is expected to change people’s livelihood in significant ways. Several vulnerability factors and readiness factors used for measuring the prediction index of that particular country on how vulnerable of a country towards global change. Primary data was collected from University of Notre Dame Global Adaptation Index (NDGAIN). The data has been trained for the forecasting purpose with support from the validated statistical analysis. The summary of the predicted index is visualized using machine learning tools. The results developed the correlation between vulnerability and readiness factors and shows the stability of the country towards climate change. The framework is …

Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell

Conference papers

Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …

Vision-Based Framework For Monitoring Of Eating Behavior Of Persons With Alzheimer’S Disease, Haitham Al-Anssari

Dissertations

Dementia is a syndrome used to describe an array of significant declines in cognitive abilities due to progressive and irreversible loss of neurons and brain functioning. This neurodegeneration seriously affects daily life activities like driving, shopping, working and speaking. Among these, Alzheimer’s disease is the most common type of dementia, with individuals experiencing loss of memory and thinking and reasoning skills. Due to cognitive decline, individuals with Alzheimer’s often suffer from malnutrition, since they do not eat, even when food is presented, and must be fed with assistance. This assistance presents a significant burden of time to caregivers, and consequently …

Integrated Compressive Sensing And Feature Descriptors- A Framework For Facial Recognition Systems, Ali Kadhem Jaber

Dissertations

Facial recognition is still a challenge in many applications, particularly in surveillance, security systems, and human-computer interactive (HCI) tools. The impact of real-world environmental variations on the performance of any facial recognition system can be significant. These variations may include illumination, facial expressions, poses, disguises (facial hair, glasses or cosmetics) and partial face occlusion. Furthermore, the number of images (samples) needed for facial recognition systems can be very large, much larger than what is typically required by an algorithm, and this is often made worse with expansion of the feature space dimensionality. Truly, the “curse of dimensionality” haunts any real-time …

3d Signal Strength Mapping Of 2.4ghz Wifi Networks, Brett D. Glidden

Electrical Engineering

Many commercial businesses operate out of multi-story office buildings. These companies often use many Wi-Fi access points to set up their own wireless network. IT personnel determine proper Wi-Fi access point placement using Wi-Fi strength maps. Conventional Wi-Fi strength maps only provide a two-dimensional view representing the wireless access point's effective range. The signal quality and strength measurements do not include changing vertical elevation. Efficient network layout in a multi-story building requires a system calculating signal quality metrics in three dimensions.

This project involves designing and prototyping a system to achieve 2.4GHz Wi-Fi signal quality measurements in a three-dimensional reference …

Programmable Time-Domain Digital-Coding Metasurface For Non-Linear Harmonic Manipulation And New Wireless Communication Systems, Jie Zhao, Xi Yang, Jun Yan Dai, Qiang Cheng, Xiang Li, Ning Hua Qi, Jun Chen Ke, Guo Dong Bai, Shuo Liu, Shi Jin, Andrea Alù, Tie Jun Cui

Publications and Research

Optical non-linear phenomena are typically observed in natural materials interacting with light at high intensities, and they benefit a diverse range of applications from communication to sensing. However, controlling harmonic conversion with high efficiency and flexibility remains a major issue in modern optical and radio-frequency systems. Here, we introduce a dynamic time-domain digital-coding metasurface that enables efficient manipulation of spectral harmonic distribution. By dynamically modulating the local phase of the surface reflectivity, we achieve accurate control of different harmonics in a highly programmable and dynamic fashion, enabling unusual responses, such as velocity illusion. As a relevant application, we propose and …

Demand Response Management In Smart Grid Networks: A Two-Stage Game-Theoretic Learning-Based Approach, Pavlos Athanasios Apostolopoulos

Shared Knowledge Conference

In this paper, the combined problem of power company selection and demand response management (DRM) in a smart grid network consisting of multiple power companies and multiple customers is studied via adopting a reinforcement learning and game-theoretic technique. Each power company is characterized by its reputation and competitiveness. The customers, acting as learning automata select the most appropriate power company to be served, in terms of price and electricity needs’ fulfillment, via a reinforcement learning based mechanism. Given customers’ power company selection, the DRM problem is formulated as a two-stage game theoretic optimization framework. At the first stage the optimal …

Optical Wireless Data Center Networks, Abdelbaset S. Hamza

School of Computing: Dissertations, Theses, and Student Research

Bandwidth and computation-intensive Big Data applications in disciplines like social media, bio- and nano-informatics, Internet-of-Things (IoT), and real-time analytics, are pushing existing access and core (backbone) networks as well as Data Center Networks (DCNs) to their limits. Next generation DCNs must support continuously increasing network traffic while satisfying minimum performance requirements of latency, reliability, flexibility and scalability. Therefore, a larger number of cables (i.e., copper-cables and fiber optics) may be required in conventional wired DCNs. In addition to limiting the possible topologies, large number of cables may result into design and development problems related to wire ducting and maintenance, heat …

Non-Parametric Classification Of Time Series Using Permutation Ordinal Statistics, Aldo Duarte Vera Tudela

LSU Master's Theses

The present thesis explores some approaches to classify time series without prior statistical information using the concept of permutation entropy. Motivated by the results from a previous published and relevant work that set similarity relationships between EEG time series, a reproduction of the proposed approach was performed giving negative results. The failure to reproduce those results led to the conclusion that the approach of building statistics from permutation patterns have to be complemented with another metric in order to be used for classification purposes. The concept of Total Variation Distance (TVD) was then used to develop three algorithms to classify …