Computer Engineering Commons^™

Doctor Of Philosophy In Information Assurance, Nova Southeastern University

College of Engineering and Computing Course Catalogs

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Threshold-Based Distributed Ddos Attack Detection In Isp Networks, Karanbir Singh, Kanwalvir Singh Dhindsa, Bharat Bhushan

Turkish Journal of Electrical Engineering and Computer Sciences

The purpose of this paper is to propose a more efficient and accurate distributed denial of service (DDoS) attack detection mechanism that detects DDoS attacks by monitoring the incoming traffic on the edge routers of ISP networks. It can be implemented as a module or agent function on the machine that is responsible for processing router traffic. The detection algorithm works by monitoring the traffic passing through the edge routers and identifying the occurrence of DDoS attacks or flash events. The algorithm calculates different values like the normalized router entropy, packet rate, and entropy rate and compares them against the …

Mazetec: A Scenario-Based Learning Platform, Daniel Bietz

College of Graduate Studies: Theses & Dissertations

This work presents Mazetec, a scenario-based learning platform for delivering non-linear scenarios format asynchronously. It enables subject matter experts to create interactive, state-dependent case studies or courses with branching logic for online learning and knowledge testing. Mazetec is a complex web application designed to deliver decision-based or case-based educational scenarios and simulations in a time-limited, non-linear format. There are many e-learning systems in the open source and commercial markets, but while these systems may have similar functions, we have found none that are both domain independent and able to deliver state-dependent content asynchronous and non-linearly. Mazetec can serve as …

Establishing A Need For A Protocol For The Interoperability Of Heterogeneous Iot Home Devices, Jenna Bayto

College of Graduate Studies: Theses & Dissertations

The Internet of Things (IoT) refers to the field of connecting devices consumers use every day to the internet. As the world relies on more and more internet-driven technological devices to control functions within the home, issues with compatibility of those devices are surfacing. This research was created to establish the need for standardization of IoT devices within the home.

Development, Manufacture And Application Of A Solid-State Ph Sensor Using Ruthenium Oxide, Wade Lonsdale

Theses: Doctorates and Masters

The measurement of pH is undertaken frequently in numerous settings for many applications. The common glass pH probe is almost ideal for measuring pH, and as such, it is used almost ubiquitously. However, glass is not ideal for all applications due to its relatively large size, fragility, need for recalibration and wet-storage. Therefore, much research has been undertaken on the use of metal oxides as an alternative for the measurement of pH.

Here, a solid-state potentiometric pH sensor is developed using ruthenium metal oxide (RuO2). Initially, pH sensitive RuO2 electrodes were prepared by deposition with radio frequency magnetron sputtering (RFMS) …

Automated Optical Mark Recognition Scoring System For Multiple-Choice Questions, Murtadha Alomran

Theses: Doctorates and Masters

Multiple-choice questions are one of the questions commonly used in assessments. It is widely used because this type of examination can be an effective and reliable way to examine the level of student’s knowledge. So far, this type of examination can either be marked by hand or with specialised answer sheets and scanning equipment. There are specialised answer sheets and scanning equipment to mark multiple-choice questions automatically. However, these are expensive, specialised and restrictive answer sheets and optical mark recognition scanners.

This research aims to design and implement a multiple-choice answer sheet and a reliable image processing-based scoring system that …

Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia

Theses: Doctorates and Masters

This thesis investigates a precise and efficient pattern-based intrusion detection approach by extracting patterns from sequential adversarial commands. As organisations are further placing assets within the cyber domain, mitigating the potential exposure of these assets is becoming increasingly imperative. Machine learning is the application of learning algorithms to extract knowledge from data to determine patterns between data points and make predictions. Machine learning algorithms have been used to extract patterns from sequences of commands to precisely and efficiently detect adversaries using the Secure Shell (SSH) protocol. Seeing as SSH is one of the most predominant methods of accessing systems it …

Next Generation Wireless Communication Networks: Energy And Quality Of Service Considerations, Md Munjure Mowla

Theses: Doctorates and Masters

The rapid growth in global mobile phone users has resulted in an ever-increasing demand for bandwidth and enhanced quality-of-service (QoS). Several consortia comprising major international mobile operators, infrastructure manufacturers, and academic institutions are working to develop the next generation wireless communication systems fifth generation (5G) - to support high data rates and increased QoS. 5G systems are also expected to represent a greener alternative for communication systems, which is important because power consumption from the information and communication technology (ICT) sector is forecast to increase significantly by 2030. The deployment of ultra-dense heterogeneous small cell networks (SCNs) is expected to …

Service Integration Design Patterns In Microservices, Meng Wang

Electronic Theses and Dissertations

“Microservices” is a new term in software architecture that was defined in 2014 [1]. It is a method to build a software application with a set of small services. Each service has its process to serve a single purpose and communicates with other services through lightweight mechanisms. Because of a great deal of independently distributed services, it is a challenge to integrate the loose services fully. Too many trivial relationships can be messed up easily during deployment. Also, it is hard to modify the relationships if the services are updated as the source codes need to be re-edited and tested. …

Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha

Electronic Theses and Dissertations

Individuals with chronic conditions are the ones who use health care most frequently and more than 50% of top ten causes of death are chronic diseases in United States and these members always have health high risk scores. In the field of population health management, identifying high risk members is very important in terms of patient health care, disease management and cost management. Disease management program is very effective way of monitoring and preventing chronic disease and health related complications and risk management allows physicians and healthcare companies to reduce patient’s health risk, help identifying members for care/disease management along …

Design, Implementation And A Pilot Study Of Mobile Framework For Pedestrian Safety Using Smartphone Sensors, Aawesh Man Shrestha

Electronic Theses and Dissertations

Pedestrian distraction from smartphones is a serious social problem that caused an ever increasing number of fatalities especially as virtual reality (VR) games have gained popularity recently. In this thesis, we present the design, implementation, and a pilot study of WiPedCross, a WiFi direct-based pedestrian safety system that senses and evaluates a risk, and alerts accordingly the user to prevent traffic accidents. In order to develop a non-intrusive, accurate, and energy-efficient pedestrian safety system, a number of technical challenges are addressed: to enhance the positioning accuracy of the user for precise risk assessment, a map-matching algorithm based on a Hidden …

Enabling Low Cost Wifi-Based Traffic Monitoring System Using Deep Learning, Sayan Sahu

Electronic Theses and Dissertations

A traffic monitoring system (TMS) is an integral part of Intelligent Transportation Systems (ITS) for traffic analysis and planning. However, covering huge miles of rural highways (119,247 miles in U.S.) with a large number of TMSs is a very challenging problem due to the cost issue. This paper aims to address the problem by developing a low-cost and portable TMS called DeepWiTraffic based on COTs WiFi devices. The proposed system enables accurate vehicle detection (counting) and classification by exploiting the unique WiFi Channel State Information (CSI) of passing vehicles. Spatial and temporal correlations of CSI amplitude and phase data are …

Cyber-Physical Embedded Systems With Transient Supervisory Command And Control: A Framework For Validating Safety Response In Automated Collision Avoidance Systems, Daniel K. Trembley

Graduate Dissertations and Theses

The ability to design and engineer complex and dynamical Cyber-Physical Systems (CPS) requires a systematic view that requires a definition of level of automation intent for the system. Since CPS covers a diverse range of systemized implementations of smart and intelligent technologies networked within a system of systems (SoS), the terms “smart” and “intelligent” is frequently used in describing systems that perform complex operations with a reduced need of a human-agent. The difference between this research and most papers in publication on CPS is that most other research focuses on the performance of the CPS rather than on the correctness …

Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian

Electrical and Computer Engineering Faculty Publications

A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined- network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to …

Lab Manual Design With Engineering Learning Style And Flipped Learning Model In Computer Engineering Technology Education, Yu Wang, Sunghoon Jang

Publications and Research

We have designed a lab manual based on Felder-Silverman learning style model (FSLSM) and the flipped classroom model for engineering education. This lab manual is developed for early junior year course of “Microcomputer Systems Technology” and emphasizes student-centered active learning experiences with more practical exercises and open-ended questions. Instead of taking traditional assembly language to study computer architecture, we are looking for a different approach to teach students to learn the assembly language by embedding an inline assembly language module into a C program. Our lab guide consists of online videos and practical exercises on various platforms including Microsoft Windows …

Blockchain Scalability And Security, Tuyet Duong

Theses and Dissertations

Cryptocurrencies like Bitcoin have proven to be a phenomenal success. The underlying techniques hold huge promise to change the future of financial transactions, and eventually the way people and companies compute, collaborate, and interact. At the same time, the current Bitcoin-like proof-of-work based blockchain systems are facing many challenges. In more detail, a huge amount of energy/electricity is needed for maintaining the Bitcoin blockchain. In addition, their security holds if the majority of the computing power is under the control of honest players. However, this assumption has been seriously challenged recently and Bitcoin-like systems will fail when this assumption is …

A New Method Based On Pixel Density In Salt And Pepper Noise Removal, Uğur Erkan, Levent Gökrem

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we deliver a new method to remove salt and pepper noise, which we refer to as based on pixel density filter (BPDF). The first step of the method is to determine whether or not a pixel is noisy, and then we decide on an adaptive window size that accepts the noisy pixel as the center. The most repetitive noiseless pixel value within the window is set as the new pixel value. By using 18 test images, we give the results of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), image enhancement factor (IEF), standard median filter (SMF), adaptive …

Transient- And Probabilistic Neural Network-Based Fault Classification In Ehv Three-Terminal Lines, Ravi Kumar Varma Bhupatiraju, Venkata Sesha Samba Siva Sarma Dhanikonda, Venkata Ramana Rao Pulipaka

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a fast and accurate fault classifier for three-terminal transmission circuits. Traditional phasor-based methods fail to meet the high speed requirements of modern power grids and necessitate alternative solutions. The transient-based schemes use advanced signal processing techniques to achieve fast and accurate fault classification. As the three-terminal lines experience very pronounced transients during faults, the proposed method makes use of the fault-generated transients to quickly and correctly classify the fault. Many transient-based schemes fail to give the required accuracy since the transient patterns with relay-measured signals are highly influenced by fault conditions. Therefore, a thorough analysis of transient …

Bagged Tree Classification Of Arrhythmia Using Wavelets For Denoising, Compression, And Feature Extraction, Özgür Tomak, Temel Kayikçioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Arrhythmia, also known as dysrhythmia, is a condition involving an irregular heartbeat. A problem in the heart may cause problems in other organs, and as time passes, this will lead to more severe problems. Arrhythmia must be detected at an early stage to prevent such a problem occurring in the heart. Detection of arrhythmia from an electrocardiogram is an easy method that does not need much equipment and does not harm the patient. The purpose of this research is to find a faster and more accurate system to classify nine classes of arrhythmia. The St. Petersburg Institute of Cardiological Technics …

Multilabel Learning For The Online Transient Stability Assessment Of Electric Power Systems, Peyman Beyranvand, Veysel Murat İstemi̇han Genç, Zehra Çataltepe

Turkish Journal of Electrical Engineering and Computer Sciences

Dynamic security assessment of a large power system operating over a wide range of conditions requires an intensive computation for evaluating the system's transient stability against a large number of contingencies. In this study, we investigate the application of multilabel learning for improving training and prediction time, along with the prediction accuracy, of neural networks for online transient stability assessment of power systems. We introduce a new multilabel learning method, which uses a contingency clustering step to learn similar contingencies together in the same multilabel multilayer perceptron. Experimental results on two different power systems demonstrate improved accuracy, as well as …

Novel Modified Impedance-Based Methods For Fault Location In The Presence Of A Fault Current Limiter, Javad Barati, Aref Doroudi

Turkish Journal of Electrical Engineering and Computer Sciences

A fault current limiter (FCL) is promising novel electric equipment to effectively reduce excessive short circuit current in power networks. The presence of a FCL at the time of a fault occurrence makes it necessary to consider new settings for protective relays and fault locators. This paper examines the presence of a FCL in power networks and its effects on single-ended impedance-based fault location methods. It will be shown that FCL deployment in a transmission line makes the traditional fault location method inefficient. Two modified methods are presented to solve the problem. The modified methods locate the fault point using …

Performance Evaluation Of Alumina Trihydrate And Silica-Filled Silicone Rubber Composites For Outdoor High-Voltage Insulations, Hidayatullah Khan, Muhammad Amin, Ayaz Ahmad

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, silicone rubber-based composites have been widely investigated for outdoor applications due to their promising insulating properties. However, mechanical, thermal, and tracking properties of pure silicone rubber are very poor, which restrains its application for long-term performance. In this research work, the influence of microsized alumina trihydrate (ATH) and micro/nanosized silica (SiO$_{2})$ fillers on mechanical, thermal, and electrical properties of room temperature vulcanized silicone rubber (RTV-SiR) has been studied. SiR-blends with varying amounts of ATH and SiO$_{2}$ particles were prepared by blending in a two-roll mixing mill, compression molding, and postcuring processes in sequence. In order to evaluate …

A Selective Frequency Reconfigurable Bandstop Metamaterial Filter For Wlan Applications, Bachir Belkadi, Zoubir Mahdjoub, Mohammed Lamine Seddiki, Mourad Nedil

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two designs of bandstop filters are presented and implemented, each one composed of a coplanar waveguide loaded with a resonator. The first design has a structure with circular resonators, and the second design is a frequency reconfigurable filter with a rectangular spiral resonator and PIN diodes. The designs are based on the use of metamaterial to create notch filters for microwave applications. The Nicolson--Ross--Weir method, used to extract the refractive index, is also described to highlight the supernatural electromagnetic characteristic of metamaterials. From the simulation results, the filters exhibit high frequency selectivity via the presence of reflection …

Application Of Synthetic Informative Minority Over-Sampling (Simo) Algorithm Leveraging Support Vector Machine (Svm) On Small Datasets With Class Imbalance, Akshatha Fakkeriah Kallappanamatt

Dissertations

Developing predictive models for classification problems considering imbalanced datasets is one of the basic difficulties in data mining and decision-analytics. A classifier’s performance will decline dramatically when applied to an imbalanced dataset. Standard classifiers such as logistic regression, Support Vector Machine (SVM) are appropriate for balanced training sets whereas provides suboptimal classification results when used on unbalanced dataset. Performance metric with prediction accuracy encourages a bias towards the majority class, while the rare instances remain unknown though the model contributes a high overall precision. There are chances where minority instances might be treated as noise and vice versa. (Haixiang et …

Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang

Electronic Theses and Dissertations

Breast cancer is the most common cancer in women worldwide, and the mammogram is the most widely used screening technique for breast cancer. To make a diagnosis in the early stage of breast cancer, the appearance of masses and microcalcifications on the mammogram are two crucial indicators. Notably, the early detection of malignant microcalcifications can facilitate the diagnosis and the treatment of breast cancer at the appropriate time. Making an accurate evaluation on microcalcifications is a timeconsuming and challenging task for the radiologists due to the small size and the low contrast of microcalcification. Compared to the background and mammogram …

An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang

Electronic Theses and Dissertations

With ever-increasing number of vehicles and shortages of parking spaces, parking has always been a very important issue in transportation. It is necessary to use advanced intelligent technologies to help drivers find parking spaces, quickly. In this thesis, an approach to finding empty spaces in parking lots using the CSI-based WiFi technology is presented. First, the channel state information (CSI) of received WiFi signals is analyzed. The features of CSI data that are strongly correlated with the number of empty slots in parking lots are identified and extracted. A machine learning technique to perform multi-class classification that categorizes the input …

Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri

Electronic Theses and Dissertations

Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly …

Review Of The Effectiveness Of Impulse Testing For The Evaluation Of Cable Insulation Quality And Recommendations For Quality Testing, Adrian Coughlan, Joseph Kearney, Tom Looby

Conference papers

Abstract— This project investigates impulse breakdown testing as a means of determining the as constructed standard of MV power cable. A literature survey is undertaken to elucidate the place of this test in an overall cable test regime and to determine the factors that impact on the performance of the test method. Testing was undertaken on ESB Networks cables to establish if a merit order ranking was feasible based on this test and to determine if the test could detect defects in the inner semiconducting layer. Based on this, conclusions and recommendations are made regarding the overall applicability and usefulness …

Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez

Other resources

As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other …

Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …