Computer Engineering Commons^™

Modulation Recognition Algorithm Based On Truncated Migration And Parallel Resnet, Yecai Guo, Qingwei Wang

Journal of System Simulation

Abstract: A truncated migration data preprocessing algorithm is proposed for the problem of limited time series characteristics of the signal extracted by convolutional neural network. The distance unit at one end of the sampling matrix is truncated, migrated to the other end to form a new matrix, allowing the convolutional neural network to extract more sampling points and compare more symbolic information.An improved parallel ResNet is proposed, which focuses on features in both horizontal and vertical directions simultaneously by two parallel branches. The results show that the algorithm has an accuracy rate of about 10% higher than that of ordinary …

Exploring The Math In Support Vector Machines, Vishnu Pendyala

Open Educational Resources

“SVMs are a rare example of a methodology where geometric intuition, elegant mathematics, theoretical guarantees, and practical algorithms meet” – Bennet and Campbell

Support Vector Machines (SVMs) are used for supervised machine learning and have been successful in many applications, including those like image classification that favor deep learning. SVM owes its power to the intriguing math involved in its fabrication. This talk will introduce SVM and cover some of that math. Topics covered will include constrained and unconstrained optimization, convexity, the general notion of a function space, minmax equilibrium, duality, the Cover theorem, Kernels, and the Mercer theorem.

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Effect Of Degradation Of Methylene Blue Dye (Mb) By Using Erbium Oxide (Er2o3) Nps, Hind Ahmed Jasim, Farah Farman Abbass, Sarah A. Hamood, Hind Mohammed Hassan, Mohammed Sellab Hamza

Al-Esraa University College Journal for Engineering Sciences

In an experiment investigating the photo catalytic degradation of methylene blue using varied concentrations of Er2O3 nanoparticles, different conditions were tested including with and without sunshine, as well as in the absence of a UV source. The presence of a UV source was also considered in the research. UV-Visible spectroscopy was utilized to characterize the catalysts. The degradation of methylene blue dye was monitored by spectrophotometry by tracking dye absorbance at regular time intervals and adjusting the dye concentration. The results indicated that the most effective degradation of methylene blue dye occurred during a 5-hour irradiation time and in the …

Architecture Between Development And Ability Programs, Allaa Ahmed Rasheed, Ibrahim Jawad Kadhim

Al-Esraa University College Journal for Engineering Sciences

The development of architecture and its pursuit of perfection can only be achieved through society to reach a specific result when meeting new desires that arise as a result of human development, expanding individual and societal needs, and deepening their relationships in multifaceted ways. The research focuses on development as it requires a clear cumulative vision of the integrative relationship between practice and participation in interpreting the act (effect) from the force (influence). It emphasizes that the power of capabilities is understood through learning and education in describing the capabilities of architecture. This involves adopting new ideas and intellectual premises …

The Designing Of Contemporary Teaching- Learning Spaces According To Interactive Flow Action Local School Spaces-A Case Study, Aseel Jasem Al-Ataby, Anwar Subhi Ramadan Al-Qaraghuli

Al-Esraa University College Journal for Engineering Sciences

The world today faces many challenges related to environmental issues, as well as other social and economic challenges, and in light of intellectual, cognitive, and technical transformations, which led to the emergence of many new phenomena and concepts that correspond to them, including the concept of flow. This concept has been associated with many aspects of life, including architecture, whose importance has emerged recently in light of the challenge of the spread of the Corona virus and its effects on architecture with its residential, educational, and other spaces. This research focuses on the flow in the architectural space in general, …

A New Compact Triple-Band Micro-Strip Monopole Antenna Based On Minkowski Fractal Geometry, Hayder S. Ahmed, Zahra' Salah Ahmed, Sarah A. Hamood, Mohammed Sellab Hamza, Taha A. Elwi

Al-Esraa University College Journal for Engineering Sciences

Wireless communication systems have made significant advancements in size reduction, with antenna terminals remaining a primary challenge for system compatibility. As a result, much of industrial research is focused on antenna miniaturization in wireless systems. In this work, a novel compact Triple-Band Fractal (TBF) antenna is proposed, utilizing three coupling fractal patches with varying iteration levels of Minkowski geometry to provide three resonant bands. The antenna design is implemented using an antenna substrate with a dielectric constant of 10.8 and a thickness of 1.27 mm within the CST Microwave Studio environment. The zero iteration patch resonator is responsible for the …

The Role Of Community Participation In The Architectural Production, Allaa Ahmed Rasheed, Ibrahim Jawad Kadhim

Al-Esraa University College Journal for Engineering Sciences

The role of community participation as a power in building architectural output at the level of the act of thinking in architecture and the design process in non-existence is related to power and presence with act. The research is concerned with expanding knowledge in the direction of the holistic language and searching for the role that builds the privacy of the architectural product versus the community's societal identity. It studies the concept of act within the limits of existence at the level of community participation since the act of architecture is the act of man to meet certain needs and …

The Communicative Deviation In Contemporary Architectural Production, Haneen Hosham Abd-Alrahman, Panrizat Q. Hussein Fehmi

Al-Esraa University College Journal for Engineering Sciences

Deviation is one of the most important concepts discussed in various architectural and non-architectural theses when addressing the topic of creative production. It involves breaking away from the familiar and surpassing established architectural rules to create unique and excellent products that are characterized by their creativity and aesthetic appeal. Recognizing the significance of this concept in shaping contemporary architectural production, the research endeavors to explore the concept of connective displacement in architecture and delve into its essential aspects. The research identifies the research problem as the "cognitive deficiency surrounding connective displacement in the semantic structures embedded in architecture." The objective …

Developed Rc4 Algorithm With Double Reverse For Better Data Protect, Fouad Sahib Muhamed Alkhazraji

Al-Esraa University College Journal for Engineering Sciences

Computer security plays a crucial role in protecting users' data, and cryptographic techniques are commonly used for this purpose. Encryption is a method employed to ensure data confidentiality, whether it is stored on hard drives or transferred through various media. RC4 (Rivest Cipher 4) is a cryptographic algorithm that utilizes the same key for both encryption and decryption processes. It falls under the category of stream ciphers, which are widely utilized in numerous protocols due to their flexibility and speed. RC4 employs XOR (exclusive OR) function to implement its encryption and decryption steps. In this paper, a technique known as …

Sers Spectroscopy With Machine Learning To Analyze Human Plasma Derived Sevs For Coronary Artery Disease Diagnosis And Prognosis, Xi Huang, Bo Liu, Shenghan Guo, Weihong Guo, Ke Liao, Guoku Hu, Wen Shi, Mitchell Kuss, Michael J. Duryee, Daniel R. Anderson, Yongfeng Lu, Bin Duan

Department of Electrical and Computer Engineering: Faculty Publications

Coronary artery disease (CAD) is one of the major cardiovascular diseases and represents the leading causes of global mortality. Developing new diagnostic and therapeutic approaches for CAD treatment are critically needed, especially for an early accurate CAD detection and further timely intervention. In this study, we successfully isolated human plasma small extracellular vesicles (sEVs) from four stages of CAD patients, that is, healthy control, stable plaque, non-ST-elevation myocardial infarction, and ST-elevation myocardial infarction. Surface-enhanced Raman scattering (SERS) measurement in conjunction with five machine learning approaches, including Quadratic Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor, Artificial Neural network, were then …

Sers Spectroscopy With Machine Learning To Analyze Human Plasma Derived Sevs For Coronary Artery Disease Diagnosis And Prognosis, Xi Huang, Bo Liu, Shenghan Guo, Weihong Guo, Ke Liao, Guoku Hu, Wen Shi, Mitchell Kuss, Michael J. Duryee, Daniel R. Anderson, Yongfeng Lu, Bin Duan

Department of Electrical and Computer Engineering: Faculty Publications

Coronary artery disease (CAD) is one of the major cardiovascular diseases and represents the leading causes of global mortality. Developing new diagnostic and therapeutic approaches for CAD treatment are critically needed, especially for an early accurate CAD detection and further timely intervention. In this study, we successfully isolated human plasma small extracellular vesicles (sEVs) from four stages of CAD patients, that is, healthy control, stable plaque, non-ST-elevation myocardial infarction, and ST-elevation myocardial infarction. Surface-enhanced Raman scattering (SERS) measurement in conjunction with five machine learning approaches, including Quadratic Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor, Artificial Neural network, were then …

Towards Efficient Scoring Of Student-Generated Long-Form Analogies In Stem, Thilini Wijesiriwardene, Ruwan Wickramarachchi, Valerie L. Shalin, Amit P. Sheth

Publications

Switching from an analogy pedagogy based on comprehension to analogy pedagogy based on production raises an impractical manual analogy scoring problem. Conventional symbol-matching approaches to computational analogy evaluation focus on positive cases, and challenge computational feasibility. This work presents the Discriminative Analogy Features (DAF) pipeline to identify the discriminative features of strong and weak long-form text analogies. We introduce four feature categories (semantic, syntactic, sentiment, and statistical) used with supervised vector-based learning methods to discriminate between strong and weak analogies. Using a modestly sized vector of engineered features with SVM attains a 0.67 macro F1 score. While a semantic feature …

Height Information Aided 3d Real-Time Large-Scale Underground User Positioning, Houbing Song, Chengkai Tang, Cunle Zhang, Lingling Zhang, Yi Zhang

Publications

Due to the cost of inertial navigation and visual navigation equipment and lake of satellite navigation signals, they cannot be used in large‐scale underground mining environment. To solve this problem, this study proposes large‐scale underground 3D real‐time positioning method with seam height assistance. This method uses the ultrawide band positioning base station as the core and is combined with seam height information to build a factor graph confidence transfer model to realise3D positioning. The simulation results show that the proposed real‐time method is superior to the existing algorithms in positioning accuracy and can meet the needs of large‐scale underground users.

Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry

Faculty Publications

Securing distributed device communication is critical because the private industry and the military depend on these resources. One area that adversaries target is the middleware, which is the medium that connects different systems. This paper evaluates a novel security layer, DDS-Cerberus (DDS-C), that protects in-transit data and improves communication efficiency on data-first distribution systems. This research contributes a distributed robotics operating system testbed and designs a multifactorial performance-based experiment to evaluate DDS-C efficiency and security by assessing total packet traffic generated in a robotics network. The performance experiment follows a 2:1 publisher to subscriber node ratio, varying the number of …

Parasol: Efficient Parallel Synthesis Of Large Model Spaces, Clay Stevens, Hamid Bagheri

School of Computing: Conference and Workshop Papers

Formal analysis is an invaluable tool for software engineers, yet state-of-the-art formal analysis techniques suffer from well-known limitations in terms of scalability. In particular, some software design domains—such as tradeoff analysis and security analysis—require systematic exploration of potentially huge model spaces, which further exacerbates the problem. Despite this present and urgent challenge, few techniques exist to support the systematic exploration of large model spaces. This paper introduces Parasol, an approach and accompanying tool suite, to improve the scalability of large-scale formal model space exploration. Parasol presents a novel parallel model space synthesis approach, backed with unsupervised learning to automatically derive …

A Framework For Sexism Detection On Social Media Via Byt5 And Tabnet, Arjumand Younus, Muhammad Atif Qureshi

Articles

Hateful and offensive content on social media platforms particularly content directed towards a specific gender is a great impediment towards equality, diversity and inclusion. Social media platforms are facing increasing pressure to work towards regulation of such content; and this has directed researchers in text mining to work towards hate speech identification algorithms. One such attempt is sexism detection for which mostly transformer-based text methods have been proposed. We propose a combination of byte-level model ByT5 with tabular modeling via TabNet that has at its core an ability to take into account platform and language aspects of the challenging task …

Optimal Inverter And Wire Selection For Solar Photovoltaic Fencing Applications, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

Despite the benefits and the economic advantages of agrivoltaics, capital costs limit deployment velocity. One recent potential solution to this challenge is to radically reduce the cost of racking materials by using existing farm fencing as vertical photovoltaic (PV) racking. This type of fenced-based PV system is inherently electrically challenging because of the relatively long distances between individual modules that are not present in more densely packed conventional solar PV farms. This study provides practical insights for inverter selection and wire sizing optimization for fence-based agrivoltaic systems. Numerical simulation sensitivities on the levelized cost of electricity (LCOE) were performed for …

Artificial Justice: The Quandary Of Ai In The Courtroom, Paul W. Grimm, Maura R. Grossman, Sabine Gless, Mireille Hildebrandt

Judicature International

No abstract provided.

A Conical-Beam Dual-Band Double Aperture-Coupled Stacked Elliptical Patch Antenna Design For 5g, Feza Turgay Çeli̇k, Kami̇l Karaçuha

Turkish Journal of Electrical Engineering and Computer Sciences

This study investigates a dual-band, aperture coupled and stacked elliptical patch antenna with conical radiation. To obtain such characteristics, the TM21 mode of the radiating elliptical patches is excited by utilizing two special apertures and shorting planes. The proposed antenna operates both at 2.45 GHz and 3.5 GHz. The design aims to be used indoor applications of 5G operating in both free and planned 5G bands, respectively. Therefore, the low-profile antenna element that has a monopole-like radiation pattern is a good candidate for two-dimensional arraying. The design steps and the evolution of the proposed antenna are presented in detail. The …

Segmentation Of Diatoms Using Edge Detection And Deep Learning, Hüseyi̇n Gündüz, Cüneyd Nadi̇r Solak, Serkan Günal

Turkish Journal of Electrical Engineering and Computer Sciences

Diatoms are photosynthesizing algae found in almost every aquatic environment. Detecting the number and diversity of diatoms is very important to analyze water quality appropriately. Accurate segmentation of diatoms is therefore crucial for this detection process. In this study, a new and effective model for the automatic segmentation of diatoms based on image processing and deep learning algorithms is proposed. In the proposed model, edge segments of a given image containing diatoms and nondiatom particles are first obtained. These edge segments are then combined, resulting in closed contours representing diatom candidates. In the final step, the diatom candidates are classified …

Evaluation Of Artificial Neural Network Methods To Forecast Short-Term Solar Power Generation: A Case Study In Eastern Mediterranean Region, Heli̇n Bozkurt, Ramazan Maci̇t, Özgür Çeli̇k, Ahmet Teke

Turkish Journal of Electrical Engineering and Computer Sciences

Solar power forecasting is substantial for the utilization, planning, and designing of solar power plants. Global solar irradiation (GSI) and meteorological variables have a crucial role in solar power generation. The ever-changing meteorological variables and imprecise measurement of GSI raise difficulties for forecasting photovoltaic (PV) output power. In this context, a major motivation appears for the accurate forecast of GSI to perform effective forecasting of the short-term output power of a PV plant. The presented study comprises of four artificial neural network (ANN) methods; recurrent neural network (RNN) method, feedforward backpropagation neural network (FFBPNN) method, support vector regression (SVR) method, …

Error Analysis Of Siso And Dual-Branch Communications With Generalized Gaussian Noise Over Ftr Fading Channels, Mehmet Bi̇li̇m

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present error probability analysis for single-input single-output (SISO) and asymmetric dual-branch networks with additive white generalized Gaussian noise (AWGGN) over millimeter-wave (mmW) fluctuating two-ray (FTR) fading channels. Then, we examine the error probability evaluation of a SISO system with imperfect phase errors over mmW FTR fading channels. The probability density function (PDF) approach is employed for the error probability performance evaluation and the novel PDF of the asymmetric dual-branch system over Nakagami-m/mmW FTR fading channels is obtained. Specifically, closed-form expressions are derived for the error probability of the SISO and asymmetric dual-branch networks. The derived error …

Comparison Of Ml Algorithms To Distinguish Between Human Or Human-Like Targets Using The Hog Features Of Range-Time And Range-Doppler Images In Through-The-Wall Applications, Yunus Emre Acar, İsmai̇l Saritaş, Ercan Yaldiz

Turkish Journal of Electrical Engineering and Computer Sciences

When detecting the human targets behind walls, false detections occur for many systematic and environmental reasons. Identifying and eliminating these false detections is of great importance for many applications. This study investigates the potential of machine learning (ML) algorithms to distinguish between the human and human-like targets behind walls. For this purpose, a stepped-frequency continuous-wave (SFCW) radar has been set up. Experiments have been carried out with real human targets and moving plates imitating a regular breath of a healthy human. Unlike conventional methods, human and human-like returns are classified using range-Doppler images containing range and Doppler information. Then, the …

Track Density Imaging Using Diffusion Tensor Imaging Data From 1.5 T Mri Scanner, Fatma Betül Köşker, Kazim Zi̇ya Gümüş, Mahmut Tokmakçi, Ni̇yazi̇ Acer, Serkan Şenol, Mehmet Bi̇lgen

Turkish Journal of Electrical Engineering and Computer Sciences

Superresolution track density imaging (TDI) has recently been developed for achieving high resolution track density maps from low-resolution diffusion images acquired at 3 T. But, the utility of the approach is still unclear when applied to diffusion tensor imaging (DTI) data acquired at lower 1.5 T magnetic field strength and thus its advantages or disadvantages awaits for exploration. We implemented an algorithm to generate track density maps of human white matter using streamline tracking and tested its performance with data acquired from two healthy volunteers at 1.5 Tesla. The effects of number of diffusion directions and seed selections on the …

Building A Surrogate Model Of A Perfect Electric Conductor Using Polynomial Chaos Expansion And The Characteristic Mode Analysis, Adem Yilmaz, Hulusi̇ Açikgöz, Alaaldeen Barakat Ahmed Elrouby

Turkish Journal of Electrical Engineering and Computer Sciences

A surrogate model for a perfect electric conductor plate is built by using the polynomial chaos expansion method. The plate is excited via four capacitive coupling elements for which the locations are determined by the analysis of the current distribution for each mode provided by the characteristic mode analysis. A numerical model based on the method of moments is then created to generate a database needed to build the surrogate model. Radiation patterns calculated by the surrogate model are compared with those given by the numerical model. The results show that the surrogate model can mimic the numerical model and …

A New Approach For Congestive Heart Failure And Arrhythmia Classification Using Downsampling Local Binary Patterns With Lstm, Süleyman Akdağ, Fatma Kuncan, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Electrocardiogram (ECG) is a vital diagnosis approach for the rapid explication and detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart failure. For this purpose, in this study, a different perspective based on downsampling one-dimensional-local binary pattern (1D-DS-LBP) and long short-term memory (LSTM) is presented for the categorization of Electrocardiogram (ECG) signals. A transformation method named 1DDS-LBP has been presented for Electrocardiogram signals. The 1D-DS-LBP method processes the bigness smallness relationship between neighbors. According to the proposed method, by downsampling the signal, the histograms of 1D local binary patterns (1D-LBP) calculated from the obtained signal groups are …

A Compact Pattern Reconfigurable Antenna Employing Shorted Quarterwave Patch Antennas, Feza Turgay Çeli̇k, Lale Alatan, Hati̇ce Özlem Aydin Çi̇vi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a compact pattern reconfigurable antenna structure is proposed. The proposed antenna is a half-wave square microstrip patch antenna divided into two quarter-wave antenna portions by a conducting wall. This wall forces potential zero at the connection point; therefore, it separates the antenna into two independent quarter-wave portions. Pattern reconfiguration is achieved by separate feeding of the quarter-wave portions. Phase difference between excitations of antenna ports result in variation at the maximum beam direction. Hence, pattern reconfiguration is achieved. Within such a compact antenna, beam steering up to 400 is achieved

A Quantitative Evaluation Of Explainable Ai Methods Using The Depth Of Decision Tree, Nizar Abdulaziz Mahyoub Ahmed, Adi̇l Alpkoçak

Turkish Journal of Electrical Engineering and Computer Sciences

It is necessary to develop an explainable model to clarify how and why a medical model makes a particular decision. Local posthoc explainable AI (XAI) techniques, such as SHAP and LIME, interpret classification system predictions by displaying the most important features and rules underlying any prediction locally. Therefore, in order to compare two or more XAI methods, they must first be evaluated qualitatively or quantitatively. This paper proposes quantitative XAI evaluation metrics that are not based on biased and subjective human judgment. On the other hand, it is dependent on the depth of the decision tree (DT) to automatically and …

A New Network-Based Community Detection Algorithm For Disjoint Communities, Peli̇n Çeti̇n, Şahi̇n Emrah Amrahov

Turkish Journal of Electrical Engineering and Computer Sciences

A community is a group of people that shares something in common. The definition of the community can be generalized as things that have common properties. By using this definition, community detection can be used to solve different problems in various areas. In this study, we propose a new network-based community detection algorithm that can work on different types of datasets. The proposed algorithm works on unweighted graphs and determines the weight by using cosine similarity. We apply a bottom-up approach and find the disjoint communities. First, we accept each node as an independent community. Then, the merging process is …

On Approximate Nash Equilibria Of The Two-Source Connection Game, Buğra Çaşkurlu, Utku Umur Açikalin, Fati̇h Erdem Kizilkaya, Özgün Eki̇ci̇

Turkish Journal of Electrical Engineering and Computer Sciences

The arbitrary-sharing connection game is prominent in the network formation game literature [1]. An undirected graph with positive edge weights is given, where the weight of an edge is the cost of building it. An edge is built if agents contribute a sufficient amount for its construction. For agent i, the goal is to contribute the least possible amount while assuring that the source node si is connected to the terminal node ti . In this paper, we study the special case of this game in which there are only two source nodes. In this setting, we prove that there …