Computer Engineering Commons^™

Sdn Testbed For Evaluation Of Large Exo-Atmospheric Emp Attacks, Diogo Oliveira, Nasir Ghani, Majeed M. Hayat, Jorge Crichigno, Elias Bou-Harb

Electrical and Computer Engineering Faculty Research and Publications

Large-scale nuclear electromagnetic pulse (EMP) attacks and natural disasters can cause extensive network failures across wide geographic regions. Although operational networks are designed to handle most single or dual faults, recent efforts have also focused on more capable multi-failure disaster recovery schemes. Concurrently, advances in software-defined networking (SDN) technologies have delivered highly-adaptable frameworks for implementing new and improved service provisioning and recovery paradigms in real-world settings. Hence this study leverages these new innovations to develop a robust disaster recovery (counter-EMP) framework for large backbone networks. Detailed findings from an experimental testbed study are also presented.

Microscale Direct Measurement Of Localized Photothermal Heating In Tissue-Mimetic Hydrogels, Benyamin Davaji, James E. Richie, Chung-Hoon Lee

Electrical and Computer Engineering Faculty Research and Publications

Photothermal hyperthermia is proven to be an effective diagnostic tool for cancer therapy. The efficacy of this method directly relies on understanding the localization of the photothermal effect in the targeted region. Realizing the safe and effective concentration of nano-particles and the irradiation intensity and time requires spatiotemporal temperature monitoring during and after laser irradiation. Due to uniformities of the nanoparticle distribution and the complexities of the microenvironment, a direct temperature measurement in micro-scale is crucial for achieving precise thermal dose control. In this study, a 50 nm thin film nickel resistive temperature sensor was fabricated on a 300 nm …

Predicting Cascading Failures In Power Grids Using Machine Learning Algorithms, Rezoan Ahmed Shuvro, Pankaz Das, Majeed M. Hayat, Mitun Talukder

Electrical and Computer Engineering Faculty Research and Publications

Although there has been notable progress in modeling cascading failures in power grids, few works included using machine learning algorithms. In this paper, cascading failures that lead to massive blackouts in power grids are predicted and classified into no, small, and large cascades using machine learning algorithms. Cascading-failure data is generated using a cascading failure simulator framework developed earlier. The data set includes the power grid operating parameters such as loading level, level of load shedding, the capacity of the failed lines, and the topological parameters such as edge betweenness centrality and the average shortest distance for numerous combinations of …

Immunity-Based Framework For Autonomous Flight In Gps-Challenged Environment, Mohanad Al Nuaimi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this research, the artificial immune system (AIS) paradigm is used for the development of a conceptual framework for autonomous flight when vehicle position and velocity are not available from direct sources such as the global navigation satellite systems or external landmarks and systems. The AIS is expected to provide corrections of velocity and position estimations that are only based on the outputs of onboard inertial measurement units (IMU). The AIS comprises sets of artificial memory cells that simulate the function of memory T- and B-cells in the biological immune system of vertebrates. The innate immune system uses information about …

Identifying Key Topics Bearing Negative Sentiment On Twitter: Insights Concerning The 2015-2016 Zika Epidemic, Ravali Mamidi, Michele Miller, Tanvi Banerjee, William Romine, Amit Sheth

Publications

Background To understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies’ efforts to disseminate relevant information to the public about Zika-related issues.

Objective The purpose of this study was to analyze the public sentiment concerning Zika using posts on Twitter and determine the qualitative characteristics of positive, negative, and neutral sentiments expressed.

Methods Machine learning techniques and algorithms were used to analyze the sentiment of tweets concerning Zika. A supervised …

Software Defined Networks Based Smart Grid Communication: A Comprehensive Survey, Mubashir Husain Rehmani, Alan Davy, Brendan Jennings, Chadi Assi

Publications

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is …

On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa

UNF Graduate Theses and Dissertations

Preferences are very important in research fields such as decision making, recommendersystemsandmarketing. The focus of this thesis is on preferences over combinatorial domains, which are domains of objects configured with categorical attributes. For example, the domain of cars includes car objects that are constructed withvaluesforattributes, such as ‘make’, ‘year’, ‘model’, ‘color’, ‘body type’ and ‘transmission’.Different values can instantiate an attribute. For instance, values for attribute ‘make’canbeHonda, Toyota, Tesla or BMW, and attribute ‘transmission’ can haveautomaticormanual. To this end,thisthesis studiesproblemsonpreference visualization and learning for lexicographic preference trees, graphical preference models that often are compact over complex domains of objects built of …

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 …

Nanopower Analog Frontends For Cyber-Physical Systems, Kenji Aono

McKelvey School of Engineering Graduate Student Theses & Dissertations

In a world that is increasingly dominated by advances made in digital systems, this work will explore the exploiting of naturally occurring physical phenomena to pave the way towards a self-powered sensor for Cyber-Physical Systems (CPS). In general, a sensor frontend can be broken up into a handful of basic stages: transduction, filtering, energy conversion, measurement, and interfacing. One analog artifact that was investigated for filtering was the physical phenomenon of hysteresis induced in current-mode biquads driven near or at their saturation limit. Known as jump resonance, this analog construct facilitates a higher quality factor to be brought about without …

A Distributed Real-Time Short-Term Solar Irradiation Forecasting Network For Photovoltaic Systems, Michael Adelbert Gacusan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Solar irradiation forecasting is essential for PV connected electrical grids to maintain reliability, stability, and effective matching of real-time demand to power distribution. This research paper develops and evaluates proposed forecasting methods using wireless sensor networks. Each node of the network is capable of monitoring illuminance data and communicate it through RF and/or WiFi. The nodes are calibrated with respect to irradiance data from an industry-standard pyranometer. Power consumption of each node type is also collected at different operating states. The proposed sensor network can estimate a cloud motion vector or a cloud shadow’s speed and direction from the data …

Structure-Mediated Excitation Of Air Plasma And Silicon Plasma Expansion In Femtosecond Laser Pulses Ablation, Qingsong Wang, Lan Jiang, Changji Pan, Weina Han, Guoyan Wang, Feifei Wang, Kaihu Zhang, Ming Li, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Femtosecond laser-induced surface structures upon multiple pulses irradiation are strongly correlated with the pulse number, which in turn significantly affects successive laser-material interactions. By recording the dynamics of femtosecond laser ablation of silicon using time-resolved shadowgraphy, here we present direct visualization of the excitation of air plasma induced by the reflected laser during the second pulse irradiation. The interaction of the air plasma and silicon plasma is found to enhance the shockwave expansion induced by silicon ablation in the longitudinal direction, showing anisotropic expansion dynamics in different directions. We further demonstrate the vanishing of air plasma as the pulse number …

Smart Iot Sprinkler System, Galib F. Rahman

Publications and Research

The average family spends more than $1000 in water costs per year. One-way water is commonly wasted in many households is via inefficient sprinkler systems for lawns. Current technology has enabled the development of automatic sprinkler systems, which can be preconfigured to operate at desired times of day and intervals. Although these systems may reduce the amount of water utilized overall, they are not weather forecast aware. In situations when rainfall is upcoming the systems still water the lawn. In this project, we plan to implement a smart sprinkler system that has full awareness of upcoming weather and take account …

Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith

Information Science Faculty Publications

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …

Conversion Of Heat Energy From Cooling Water Of Diesel Engine To Electrical Energy Using Thermoelectric Generator, Muhammad Hasan Albana

Makara Journal of Technology

This research objective is to convert heat from the radiator fluid of a diesel engine to electrical energy by utilizing a thermoelectric generator (TEG). The TEG consists of 20 semiconductors (TE modules) and is equipped with a heat sink. The research shows that using the TEG, the heat of radiator fluid can be converted to electrical energy, although the electricity generated is small. The maximum electrical voltage generated by the TEG when modules were connected in series was 10 volts. When the TE modules were connected in parallel and series-parallel, the maximum voltages generated were 2.11 and 2.53 volts, respectively. …

Immittance Response On Carboxymethyl Cellulose Blend With Polyvinyl Alcohol- Doped Ammonium Bromide-Based Biopolymer Electrolyte, Norfatihah Mazuki, Yuki Nagao, Ahmad Salihin Samsudin

Makara Journal of Technology

The blended carboxymethyl cellulose (CMC) and polyvinyl alcohol (PVA) doped with various compositions of ammonium bromide (NH4Br)-based solid biopolymer electrolytes (SBEs) were prepared by using the casting method. In this present work, CMC/PVA–NH4Br SBE thin film was used to investigate the electrical conductivity via electrical impedance spectroscopy. The maximum conductivity obtained was 3.21 X 10−4 S cm−1 for sample AB20 at ambient temperature (303 K), and this result might be due to the increased number of charge carrier. A dielectric study was conducted to understand the conductivity behavior. The electrical properties have been measured as a function of frequency of …

Transition Metal Dichalcogenide For High-Performance Electrode Of Supercapacitor, Saifful Kamaluddin Muzakir, Ahmad Salihin Samsudin, Bouchta Sahraoui

Makara Journal of Technology

Molybdenum dichalcogenides have been reviewed from the perspectives of bandgap, conductivity, and oxidation states of transition metal. Researchers have concluded that a narrow-bandgap transition metal dichalcogenide with high conductivity could be achieved for the high-performance electrode of a supercapacitor.

Automated Compilation Test System For Embedded System, Mohamad Khairi Ishak, Ooi Jun Hwan, Teh Jiashen, Nor Ashidi Mat Isa

Makara Journal of Technology

Embedded system testing involves testing an integration of software and hardware. It is increasingly difficult to evaluate the functionality of each module within a short time because of the increasing number of tests required. In this paper, a novel stepwise methodology involving the use of an automated compilation test system (ACTS) is proposed, to improve the quality of testing and optimize the testing time using automation. Using the proposed method, the testing coverage can be maximized, while minimizing the manual work and testing time required. This ACTS was used to automate the test code compilation and execution for different hardware …

Activated Carbon Fixed-Bed Adsorber Design For Treating Chromium Hexavalent Wastewater, Tedi Hudaya, Velicia Rachmat

Makara Journal of Technology

Pollution caused by industrial wastewater containing heavy metals is a major issue, primarily due to its toxic nature. A cheap yet effective method to deal with such wastewater is activated carbon adsorption. The purpose of this research is to evaluate and design a fixed bed adsorber with granular activated carbon as an adsorbent to process wastewater-containing chromium hexavalent (Cr 6+). Experiments show that the Langmuir isotherm fits the equilibrium data as effectively as the Freundlich isotherm. Activated carbon used in this research is Jacobi 2000® derived from bituminous coal. The lab scale inlet volumetric flow is 100 mL/h with different …

A 2.3/3.3-Ghz Dual Band Low Noise Amplifier Using Switchable Load Inductor In 0.18-Um Cmos Technology, Taufiq Alif Kurniawan, Hsiao-Chin Chen

Makara Journal of Technology

In this paper, the dual band low noise amplifier is designed in 0.18-μm CMOS technology. By combining the proposed switchable load inductor for gain controlling and the conventional inductive source degeneration topology, narrow band gain and good impedance matching are achieved at 2.3/3.3-GHz frequency bands. The new mathematical analysis of low noise amplifier design is derived to define the component parameters of the proposed circuits. The proposed low noise amplifier exhibits gain of 17.18 dB and 15.5 dB, and noise figure of 2.67 dB and 2.52 dB at the two frequency bands, respectively.

Ascorbic Acid Degradation In Cut Lemon Packaged Using Oxygen Scavenging Active Film During Storage, Kurniawan Yuniarto, Setyo Purwanto, Bruce Ari Welt, Anang Lastriyanto

Makara Journal of Technology

Oxygen scavenging active film can be used to prevent diffusion of free oxygen due to the action of permeation mechanism. In this study, biodegradable oxygen scavenging plastic film was designed by incorporating an antioxidant agent into plasticized polylactic acid or PLA-PEG (PPLA). Butylated hydroxytoluene (BHT) was added at different concentrations into the matrix of the PPLA film using a direct casting method to produce oxygen scavenging active film. The antiradical activity of the oxygen scavenging active film was observed, which could be applied for preventing vitamin C degradation in cut lemon during storage. The antiradical activity of the active film …

The Importance Of Usability Aspect In M-Commerce Application For Satisfaction And Continuance Intention, Yassierli Yassierli, Vinsensius Vinsensius, M. S. Syed Mohamed

Makara Journal of Technology

There has been a rapid growing of m-commerce application in recent years due to the development of mobile communication technology and e-commerce business. However, only about 30% of online users, who conduct online searching, make online purchases. The low conversion rate seems to be correlated with poor usability aspect of most m-commerce applications and poor satisfaction reported by users. Research has reported that satisfaction and continuance intention in using m-commerce applications have relationships with service quality and information quality. In this study, a new model of user satisfaction and continuance intention in the context of mobile application was proposed by …

Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage

Electronic Theses and Dissertations

The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in …

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 …

Design And Analysis Of Binary Driven Coherent M-Ary Qam Transmitter For Next Generation Optical Networks, Naji Albakay

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This work presents a design for a binary driven optical square M-ary quadrature amplitude modulation (QAM) transmitter for high speed optical networks. The transmitter applies tandem quadrature phase shift keying (QPSK) modulators to eliminate the need for linear broadband amplifiers and high-resolution digital to analog converters (DACs), which are both required by conventional transmitters. The transmitter design could be scaled to any order of square M-ary QAM by simply adding more QPSK modulators in tandem. It also provides a Gray coded symbol constellation, insuring the lowest bit error rate possible during symbol recovery. We also provide the design for the …

Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen

Master's Theses

There are approximately 23.14 billion IoT(Internet of Things) devices currently in use worldwide. This number is projected to grow to over 75 billion by 2025. Despite their ubiquity little is known about the security and privacy implications of IoT devices. Several large-scale attacks against IoT devices have already been recorded.

To help address this knowledge gap, we have collected a year’s worth of network traffic and power data from 16 common IoT devices. From this data, we show that we can identify different smart speakers, like the Echo Dot, from analyzing one minute of power data on a shared power …

Study On The Pattern Recognition Enhancement For Matrix Factorizations With Automatic Relevance Determination, Hau Tao

Electronic Theses, Projects, and Dissertations

Learning the parts of objects have drawn more attentions in computer science recently, and they have been playing the important role in computer applications such as object recognition, self-driving cars, and image processing, etc… However, the existing research such as traditional non-negative matrix factorization (NMF), principal component analysis (PCA), and vector quantitation (VQ) has not been discovering the ground-truth bases which are basic components representing objects. On this thesis, I am proposed to study on pattern recognition enhancement combined non-negative matrix factorization (NMF) with automatic relevance determination (ARD). The main point of this research is to propose a new technique …