Computer Engineering Commons^™

Improving Anomaly Detection In Bgp Time-Series Data By New Guide Features And Moderated Feature Selection Algorithm, Mahmoud Hashem, Ahmed Bashandy, Samir Shaheen

Turkish Journal of Electrical Engineering and Computer Sciences

The Internet infrastructure relies on the Border Gateway Protocol (BGP) to provide essential routing information where abnormal routing behavior impairs global Internet connectivity and stability. Hence, employing anomaly detection algorithms is important for improving the performance of BGP routing protocol. In this paper, we propose two algorithms; the first is the guide feature generator (GFG), which generates guide features from traditional features in BGP time-series data using moving regression in combination with smoothed moving average. The second is a modified random forest feature selection algorithm which is employed to automatically select the most dominant features (ASMDF). Our mechanism shows that …

A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari

Turkish Journal of Electrical Engineering and Computer Sciences

Decimal floating point (DFP) number representation was proposed in IEEE-754-2008 in order to overcome binary floating point inaccuracy. Neglecting binary floating point verification has resulted in significant validity and economic losses. Formal verification can be a solution to similar DFP design problems. Verification techniques aiming at DFP are limited to functional methods whereas formal approaches have been neglected and traditional decision diagrams cannot model DFP representation complexity. In this paper, we propose an efficient canonical data structure that can model DFP properties. Our novel data structure models coefficient, exponent, sign, and bias of a DFP number. We will prove mathematically …

Automatic Concept Identification Of Software Requirements In Turkish, Fatma Bozyi̇ği̇t, Özlem Aktaş, Deni̇z Kilinç

Turkish Journal of Electrical Engineering and Computer Sciences

Software requirements include description of the features for the target system and express the expectations of users. In the analysis phase, requirements are transformed into easy-to-understand conceptual models that facilitate communication between stakeholders. Although creating conceptual models using requirements is mostly implemented manually by analysts, the number of models that automate this process has increased recently. Most of the models and tools are developed to analyze requirements in English, and there is no study for agglutinative languages such as Turkish or Finnish. In this study, we propose an automatic concept identification model that transforms Turkish requirements into Unified Modeling Language …

Formally Analyzed M-Coupon Protocol With Confirmation Code (Mcwcc), Keri̇m Yildirim, Gökhan Dalkiliç, Nevci̇han Duru

Turkish Journal of Electrical Engineering and Computer Sciences

There are many marketing methods used to attract customers' attention and customers search for special discounts and conduct research to get products cheaper. Using discount coupons is one of the widely used methods for obtaining discounts. With the development of technology, classical paper-based discount coupons become e-coupons and then turn into mobile coupons (m-coupons). It is inevitable that retailers will use m-coupon technology to attract customers while mobile devices are used in daily life. As a result, m-coupon technology is a promising technology. One of the significant problems with using m-coupons is security. Here it is necessary to ensure the …

Detection Of Hemorrhage In Retinal Images Using Linear Classifiers And Iterative Thresholding Approaches Based On Firefly And Particle Swarm Optimization Algorithms, Kemal Adem, Mahmut Heki̇m, Seli̇m Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

We propose a novel iterative thresholding approach based on firefly and particle swarm optimization to be used for the detection of hemorrhages, one of the signs of diabetic retinopathy disease. This approach consists of the enhancement of the image using basic preprocessing methods, the segmentation of vessels with the help of Gabor and Top-hat transformation for the removal of the vessels from the image, the determination of the number of regions with hemorrhages and pixel counts in these regions using firefly algorithm (FFA) and particle swarm optimization algorithm (PSOA)-based iterative thresholding, and the detection of hemorrhages with the help of …

Local Directional-Structural Pattern For Person-Independent Facial Expression Recognition, Farkhod Makhmudkhujaev, Md Tauhid Bin Iqbal, Byungyong Ryu, Oksam Chae

Turkish Journal of Electrical Engineering and Computer Sciences

Existing popular descriptors for facial expression recognition often suffer from inconsistent feature description, experiencing poor accuracies. We present a new local descriptor, local directional-structural pattern (LDSP), in this work to address this issue. Unlike the existing local descriptors using only the texture or edge information to represent the local structure of a pixel, the proposed LDSP utilizes the positional relationship of the top edge responses of the target pixel to extract more detailed structural information of the local texture. We further exploit such information to characterize expression-affiliated crucial textures while discarding the random noisy patterns. Moreover, we introduce a globally …

Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin

Turkish Journal of Electrical Engineering and Computer Sciences

Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. …

A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri

Turkish Journal of Electrical Engineering and Computer Sciences

A support vector machine (SVM) is not a popular method for a very large dataset classification because the training and testing time for such data are computationally expensive. Many researchers try to reduce the training time of SVMs by applying sample reduction methods. Many methods reduced the training samples by using a clustering technique. To reduce its high computational complexity, several data reduction methods were proposed in previous studies. However, such methods are not effective to extract informative patterns. This paper demonstrates a new supervised classification method, multiseed-based SVM (MSB-SVM), which is particularly intended to deal with very large datasets …

Optimal Set Of Eeg Features In Infant Sleep Stage Classification, Maja Cic, Mario Milicevic, Igor Mazic

Turkish Journal of Electrical Engineering and Computer Sciences

This paper evaluates six classification algorithms to assess the importance of individual EEG rhythms in the context of automatic classification of infant sleep. EEG features were obtained by Fourier transform and by a novel technique based on the empirical mode decomposition and generalized zero crossing method. Of six evaluated classification algorithms, the best classification results were obtained with the support vector machine for the combination of all presented features from four EEG channels. Three methods of attribute ranking were assessed: relief, principal component analysis, and wrapper-based optimized attribute weights. The outcomes revealed that the optimal selection of features requires one …

Improvement Of Quantized Adaptive Switching Median Filter For Impulse Noise Reduction In Gray-Scale Digital Images, Haidi Ibrahim, Ahmed Khaldoon Abdalameer

Turkish Journal of Electrical Engineering and Computer Sciences

Digital images may suffer from fixed value impulse noise due to several causes. The noise significantly degrades the quality of the image, which may affect the subsequence image processing. Therefore, a noise reduction technique is required to restore the image. In this paper, a new method, which is called improvement of quantized adaptive switching median filter (IQASMF), has been proposed to reduce the fixed value impulse noise from gray-scale digital images. The implementation of IQASMF has five processing blocks. The first processing block is the noise detection block, where the noise pixel candidates are detected based on the intensity value. …

Boltzmann Analysis Of Electron Swarm Parameters In Chf3+Cf4 Mixtures, Hidir Düzkaya, Süleyman Sungur Tezcan

Turkish Journal of Electrical Engineering and Computer Sciences

The electron drift velocity, mean energy, ionization, attachment, effective ionization coefficient, limit electrical field, and synergism of pure CHF3 (fluoroform), pure CF4 (tetrafluoromethane), and CHF3+CF4 gas mixtures are calculated by Boltzmann equation analysis in a wide range of density normalized electrical fields (E/N). The finite difference method is used to solve the two-term approximation of the Boltzmann equation under steady-state Townsend conditions. To our knowledge, no previous electron swarm parameters of these mixtures have been published. At constant E/N values, the electron mean energies and drift velocities increase with decreasing CHF3 content. The addition of CF4 into the mixture increases …

Comparative Analysis Of A Novel Topology For Single-Phase Z-Source Inverter With Reduced Number Of Switches, Himanshu Sharma, Rintu Khanna, Neelu Jain

Turkish Journal of Electrical Engineering and Computer Sciences

Z-source inverter has recently been introduced to overcome the limitations of conventional voltage source inverter. This paper deals with a novel topology of single-phase Z-source inverter (ZSI). This topology reduced the number of passive elements and active switches in order to make the inverter cheaper and smaller in size compared to traditional ZSI. Detailed analysis of the proposed topology is presented in this paper which includes calculations of boost factor, total harmonic disorder, magnitude of output voltage etc. Modulation technique used to control the switching of the proposed inverter is explained in detail. This paper also compares the proposed topology …

On The Stability Of Inverse Dynamics Control Of Flexible-Joint Parallel Manipulators In The Presence Of Modeling Error And Disturbances, Sitki Kemal İder, Ozan Korkmaz, Mustafa Semi̇h Deni̇zli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Inverse dynamics control is considered for flexible-joint parallel manipulators in order to obtain a good trajectory tracking performance in the case of modeling error and disturbances. It is known that, in the absence of modeling error and disturbance, inverse dynamics control leads to linear fourth-order error dynamics, which is asymptotically stable if the feedback gains are chosen to make the real part of the eigenvalues of the system negative. However, when there are modeling errors and disturbances, a linear time-varying error dynamics is obtained whose stability is not assured only by keeping the real parts of the frozen-time eigenvalues of …

Neural Network Controller For Nanopositioning Of A Smooth Impact Drive Mechanism, Xiaohui Lu, Dong Chen, Tinghai Cheng, Zhe Li

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, neural network theory is used to improve the positioning accuracy of smooth impact drive mechanisms (SIDMs), by designing a displacement controller that consists of a neural network identification (NNI) and a neural network controller (NNC). The dynamics of the SIDM are described by the NNI, which consists of an input layer, hidden layer, and output layer. The parameters of the NNI are adjusted using back propagation. The NNC is designed as a proportional-derivative (PD) controller, which is used to accurately control the displacement of the SIDM. The PD parameters are adjusted with an adaptive adjustment algorithm. A …

Synchronization And Antisynchronization Protocol Design Of Chaotic Nonlinear Gyros: An Adaptive Integral Sliding Mode Approach, Fazal Ur Rahman, Qudrat Khan, Rini Akmeliawati

Turkish Journal of Electrical Engineering and Computer Sciences

A novel control protocol design, via integral sliding mode control with parameter update laws, for synchronization and desynchronization of a chaotic nonlinear gyro with unknown parameters is the focus of this work. The error dynamics of the actual system are substructured into nominal and uncertain parts to employ adaptive integral sliding mode (AISM) control. The uncertain parameters are estimated via devised adaptive laws. Then the disagreement dynamics are guided to origin via AISM control. The stabilizing controller is also designed in terms of nominal control along with a compensating component. The control and the parameter update laws are constructed to …

Youtube’S Terms Of Service: Posthumanism, Algorithms, And Professional Writing, Sarah Bresnahan

Graduate Research Theses & Dissertations

This thesis aims to examine YouTube’s Terms of Service as it applies to content creators (known as YouTubers) who use the platform as a means of financial gain and how YouTube’s demonetization policy via an algorithm is negatively affecting them. I conducted a case study featuring one creator, Michelle Guido, and attempted to determine why some of her content is demonetized when it fulfills YouTube’s content standards for monetization. This study is meant as an examination through the lens of Dr. N. Katherine Hayles’s theory of posthumanism as stated in her book, How We Became Posthuman, and will offer insight …

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …

Small Non-Profit Website And Social Media Efficacy, Juliana Maria Leprich

Graduate Research Theses & Dissertations

This thesis examines the website design and social media platform usage of small non-profit organizations (defined as less than $1M operating budget and less than ten staff). This research will be completed by first reviewing other studies that have been done on marketing in the non-profit sector, then by exploring marketing challenges firsthand through a mini-ethnographic case study as described in the mini-ethnographic case study approach, and finally through the examination of tax and financial data provided by Guidestar. The researcher was involved in website collaboration with The Gracie Center in a volunteer capacity and was employed with the two …

Accessibility And Decay Of Web Citations In Computer Science Journals, Mohsen Jalali

Library Philosophy and Practice (e-journal)

The aim of this research is to scrutiny the accessibility and decay of web citations (URLs) used in refereed articles published by 27 Computer Science open access journals as indexed by Scopus. To do this, at first, we downloaded 1000 articles of Computer Science open access journals from 2009 to 2018. After acquiring articles, their web citations are extracted and analyzed from the accessibility and decay point of view. Moreover, for initially missed web citations complementary pathways such as using Google search engine are employed. Then, data collected are analyzed using descriptive statistical methods. Research findings indicated that 80.7% of …

Volumetric Error Compensation For Industrial Robots And Machine Tools, Le Ma

Doctoral Dissertations

“A more efficient and increasingly popular volumetric error compensation method for machine tools is to compute compensation tables in axis space with tool tip volumetric measurements. However, machine tools have high-order geometric errors and some workspace is not reachable by measurement devices, the compensation method suffers a curve-fitting challenge, overfitting measurements in measured space and losing accuracy around and out of the measured space. Paper I presents a novel method that aims to uniformly interpolate and extrapolate the compensation tables throughout the entire workspace. By using a uniform constraint to bound the tool tip error slopes, an optimal model with …

Hydrogen Fuel Cell Gasket Handling And Sorting With Machine Vision Integrated Dual Arm Robot, Devin C. Fowler

College of Graduate Studies: Theses & Dissertations

Recently demonstrated robotic assembling technologies for fuel cell stacks used fuel cell components manually pre-arranged in stacks (presenters), all oriented in the same position. Identifying the original orientation of fuel cell components and loading them in stacks for a subsequent automated assembly process is a difficult, repetitive work cycle which if done manually, deceives the advantages offered by automated fabrication technologies of fuel cell components and by robotic assembly processes. We present an innovative robotic technology which enables the integration of automated fabrication processes of fuel cell components with robotic assembly of fuel cell stacks into a fully automated fuel …

Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana

College of Graduate Studies: Theses & Dissertations

This paper proposes to tackle Question Answering on a specific domain by developing a multi-tier system using three different types of data storage for storing answers. For testing our system on University domain we have used extracted data from Georgia Southern University website. For the task of faster retrieval we have divided our answer data sources into three distinct types and utilized Dialogflow's Natural Language Understanding engine for route selection. We compared different word and sentence embedding techniques for making a semantic question search engine and BERT sentence embedding gave us the best result and for extracting answer from a …

A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made

Research outputs 2014 to 2021

In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking …

Effective Plant Discrimination Based On The Combination Of Local Binary Pattern Operators And Multiclass Support Vector Machine Methods, Vi N T Le, Beniamin Apopei, Kamal Alameh

Research outputs 2014 to 2021

Accurate crop and weed discrimination plays a critical role in addressing the challenges of weed management in agriculture. The use of herbicides is currently the most common approach to weed control. However, herbicide resistant plants have long been recognised as a major concern due to the excessive use of herbicides. Effective weed detection techniques can reduce the cost of weed management and improve crop quality and yield. A computationally efficient and robust plant classification algorithm is developed and applied to the classification of three crops: Brassica napus (canola), Zea mays (maize/corn), and radish. The developed algorithm is based on the …

Real-Time Classification Of Multivariate Olfaction Data Using Spiking Neural Networks, Arnup Vanarse, Adam Osseiran, Alexander Rassau, Therese O'Sullivan, Jonny Lo, Amanda Devine

Research outputs 2014 to 2021

Recent studies in bioinspired artificial olfaction, especially those detailing the application of spike-based neuromorphic methods, have led to promising developments towards overcoming the limitations of traditional approaches, such as complexity in handling multivariate data, computational and power requirements, poor accuracy, and substantial delay for processing and classification of odors. Rank-order-based olfactory systems provide an interesting approach for detection of target gases by encoding multi-variate data generated by artificial olfactory systems into temporal signatures. However, the utilization of traditional pattern-matching methods and unpredictable shuffling of spikes in the rank-order impedes the performance of the system. In this paper, we present an …

Smart Control Of Automatic Voltage Regulators Using K-Means Clustering, Brook Abegaz, J. Kueber

Engineering Science Faculty Publications

The future cyber physical systems consist of voltage regulators distributed across wide geographical areas. In this paper, a smart control approach of voltage regulators is presented for cyber physical system applications. The approach is implemented using K-means clustering algorithms that use data from voltage and current sensors, compute the correlation of changes across the regulators and generate a proportional feedback. Advanced estimation methods are used in cases where the data from the sensors was not available. The results show that the approach could be used to improve the performance of networked, power dependent systems by 94.5% in terms of overshoot …

Big Five Technologies In Aeronautical Engineering Education: Scoping Review, Ruth Martinez-Lopez

International Journal of Aviation, Aeronautics, and Aerospace

The constant demands that technology creates in aerospace engineering also influence education. The identification of the technologies with practical application in aerospace engineering is of current interest to decision makers in both universities and industry. A social network approach enhances this scoping review of the research literature to identify the main topics using the Big Five technologies in aerospace engineering education. The conceptual structure of the dataset (n=447) was analyzed from different approaches: at macro-level, a comparative of the digital technology identified by cluster analysis with the number of co-words established in 3 and 8 and, a keyword central structure …

Determination Of Personalized Asthma Triggers From Multimodal Sensing And A Mobile App: Observational Study, Revathy Venkataramanan, Krishnaprasad Thirunarayan, Utkarshani Jaimini, Dipesh Kadariya, Hong Yung Yip, Maninder Kalra, Amit Sheth

Publications

Background: Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients’ environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management.

Objective: In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan. …

Computational Modeling Of Trust Factors Using Reinforcement Learning, C. M. Kuzio, A. Dinh, C. Stone, L. Vidyaratne, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

As machine-learning algorithms continue to expand their scope and approach more ambiguous goals, they may be required to make decisions based on data that is often incomplete, imprecise, and uncertain. The capabilities of these models must, in turn, evolve to meet the increasingly complex challenges associated with the deployment and integration of intelligent systems into modern society. Historical variability in the performance of traditional machine-learning models in dynamic environments leads to ambiguity of trust in decisions made by such algorithms. Consequently, the objective of this work is to develop a novel computational model that effectively quantifies the reliability of autonomous …

Inception: Virtual Space In Memory Space In Real Space, Peter Casey, Rebecca Lindsay-Decusati, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Virtual Reality (VR) has become a reality. With the technology's increased use cases, comes its misuse. Malware affecting the Virtual Environment (VE) may prevent an investigator from ascertaining virtual information from a physical scene, or from traditional “dead” analysis. Following the trend of antiforensics, evidence of an attack may only be found in memory, along with many other volatile data points. Our work provides the primary account for the memory forensics of Immersive VR systems, and in specific the HTC Vive. Our approach is capable of reconstituting artifacts from memory that are relevant to the VE, and is also capable …