Computer Sciences Commons^™

Skin Lesion Segmentation Based On U-Shaped Network, Muna Khalaf, Ban N. Dhannoon

Karbala International Journal of Modern Science

Skin lesion segmentation is an essential step toward accurate skin lesion diagnosis. The need to automate Skin lesion segmentation on the one hand, and the challenges it faces, on the other hand, have made it a growing area of research and focus. Automation of skin lesion segmentation helps reduce the effort and time needed for diagnosis and treatment and helps make better utilization of available data and shared experiences. The challenges faced by the automation of skin lesion segmentation can be broadly defined by (but not limited to); variations in texture, shape, and size for skin lesions and the low …

C60 Hydrofullerene Induced Autophagy And Ameliorated Gfap In H2o2 Treated Human Malignant Glioblastoma U-373 Cell Line, Aryan M. Faraj, Can A. Agca, Victor S. Nedzvetsky, Artem A. Tykhomyrov

Karbala International Journal of Modern Science

Glioblastoma is one of the most combative astrocytoma that is resistant to chemotherapy and radiotherapy. This resistance makes it very difficult to treat. However, researches have shown that nanoparticles especially C60 hydrofullerene have antioxidant and anticancer activity. The effect of C60 hydrofullerene in cancer has been extensively studied; however, the potential regulation of autophagy and modulation of the Glial Fibrillary Acidic Protein (GFAP) gene has not been addressed in glioblastomas. Glioblastoma U-373 cell was treated with 0.5 µM of C60 hydrofullerene and/or 1 mM of hydrogen peroxide (H2O2) for 24 hours. This study demonstrated that C60 hydrofullerene and H2O2 significantly …

Improving Prediction Of Arabic Fake News Using Fuzzy Logic And Modified Random Forest Model, Tahseen A. Wotaifi, Ban N. Dhannoon

Karbala International Journal of Modern Science

Throughout the last few years, the world is witnessing the so-called age of social media, as there is a complete dependence on these sites for following up on events and activities. The problem is that the misinformation or fake news is always released at the appropriate time, so this false news spreads quickly and takes a very wide resonance. Although several studies are performed to determine English fake news, the identification of Arabic misinformation remains underdeveloped. This study aims to build an improved learning model for detecting fake news in the Arabic language. Unlike previous studies that depended on analyzing …

Synthesized Zinc Nanoparticles Via Pulsed Laser Ablation: Characterization And Antibacterial Activity, Sahar Naji Rashid, Kadhim A. Aadim, Awatif Sabir Jasim, Arshad Mahdi Hamad

Karbala International Journal of Modern Science

The pulsed laser ablation of a metallic target in the liquid (PLAL) is a modern and good method for creating a variety of nanomaterials that have piqued the interest of researchers in the last decade. It is used in this work to prepare zinc na-noparticles and zinc oxide nanoparticles (ZnPNs and ZnO NPs) using Nd: YAG laser with the two wavelengths (532 nm) and (355 nm) using the energies (600 mJ) and (500 mJ) respectively, and the number of the pulse (500, 600, 700, 800, and 900 Pulses); for each wavelength used in this work. The properties of the prepared …

Continuum Damping Effects In Nuclear Collisions, Hossein Sadeghi, Mahdieh Ghafouri

Karbala International Journal of Modern Science

The Time-Dependent Skyrme Hartree-Fock (TDSHF) calculations have been conducted to study 100Sn+16O, 116Sn+16O, and 122Sn+16O collisions on a 3-Dimensional (3D) mesh with SV-bas SF. For the 100Sn+16O collision, the continuum damping width of the rotational amplitudes in Ecm = 100, 150, 200, and 250 MeV has been achieved around 108, 185, 277, and 318, with the time evolution width for z2 around 15/5, 13/5, 13/9, or 14/3 fm2. The quadrupole deformation, kinetic energy, and rotational amplitude are studied. It is seen that the compound nucleus becomes uniform and spherical as time grows. The results of the time evolution show the …

A Successful Elimination Of Indonesian Sars-Cov-2 Variants And Airborne Transmission Prevention By Cold Plasma In Fighting Covid-19 Pandemic: A Preliminary Study, Muhammad Nur, Chairul A. Nidom, Setyarina Indrasari, Arif N. M. Ansori, Mohamad Y. Alamudi, Astria N. Nidom, Sumariyah Sumariyah, Eva Sasmita, Eko Yulianto, Andi W. Kinandana, Anwar Usman, Muhammad K. J. Kusala, Irine Normalina, Reviany V. Nidom

Karbala International Journal of Modern Science

Global infection and mortality rates have soared to millions due to SARS-CoV-2 human-to-human transmission from via droplets which then declared as pandemic. This study examined the created cold plasma equipment (CPE) effectiveness in reducing COVID-19 transmission in a confined space. CPE sucked air using a fan in a test chamber then pushed it into a cold plasma reactor. The results indicated that it was able to terminate all SARS-CoV-2 variants along with bacteria and fungi indoors by keeping it turned on for 30 minutes’ minimum. CPE was proven as safe and effective to hinder virus transmission with the acceptable ozone …

The Distinction Of Logical Decision According To The Model Of The Analysis Of Brain Signals (Eeg), Akeel Abdulkareem Al-Sakaa, Zaid H. Nasralla, Mohsin Hasan Hussein, Saif A. Abd, Hazim Alsaqaa, Kesra Nermend, Anna Borawska

Karbala International Journal of Modern Science

Recently, brain signal patterns have been recruited by researchers in different life activities. Researchers have studied each life activity and how brain signal patterns appear. These patterns could then be generalised and used in different disciplines. In this paper, we study the brain state during decision making in a lottery experiment. An EEG device is used to capture brain signals during an experiment to extract the optimal state for logical decision making. After collecting data, extracting useful information and then processing it, the proposed method is able to identify rational decisions from irrational ones with a success rate of 67%.

X-Ray Vision At Action Space Distances: Depth Perception In Context, Nate Phillips

Theses and Dissertations

Accurate and usable x-ray vision has long been a goal in augmented reality (AR) research and development. X-ray vision, or the ability to comprehend location and object information when such is viewed through an opaque barrier, would be imminently useful in a variety of contexts, including industrial, disaster reconnaissance, and tactical applications. In order for x-ray vision to be a useful tool for many of these applications, it would need to extend operators’ perceptual awareness of the task or environment. The effectiveness with which x-ray vision can do this is of significant research interest and is a determinant of …

Classification Models For 2,4-D Formulations In Damaged Enlist Crops Through The Application Of Ftir Spectroscopy And Machine Learning Algorithms, Benjamin Blackburn

Theses and Dissertations

With new 2,4-Dichlorophenoxyacetic acid (2,4-D) tolerant crops, increases in off-target movement events are expected. New formulations may mitigate these events, but standard lab techniques are ineffective in identifying these 2,4-D formulations. Using Fourier-transform infrared spectroscopy and machine learning algorithms, research was conducted to classify 2,4-D formulations in treated herbicide-tolerant soybeans and cotton and observe the influence of leaf treatment status and collection timing on classification accuracy. Pooled Classification models using k-nearest neighbor classified 2,4-D formulations with over 65% accuracy in cotton and soybean. Tissue collected 14 DAT and 21 DAT for cotton and soybean respectively produced higher accuracies than the …

Gpgpu Microbenchmarking For Irregular Application Optimization, Dalton R. Winans-Pruitt

Theses and Dissertations

Irregular applications, such as unstructured mesh operations, do not easily map onto the typical GPU programming paradigms endorsed by GPU manufacturers, which mostly focus on maximizing concurrency for latency hiding. In this work, we show how alternative techniques focused on latency amortization can be used to control overall latency while requiring less concurrency. We used a custom-built microbenchmarking framework to test several GPU kernels and show how the GPU behaves under relevant workloads. We demonstrate that coalescing is not required for efficacious performance; an uncoalesced access pattern can achieve high bandwidth - even over 80% of the theoretical global memory …

3d Vision With Transformers: A Survey, Jean Lahoud, Jiale Cao, Fahad Shahbaz Khan, Hisham Cholakkal, Rao Anwer, Salman Khan, Ming-Hsuan Yang

Computer Vision Faculty Publications

The success of the transformer architecture in natural language processing has recently triggered attention in the computer vision field. The transformer has been used as a replacement for the widely used convolution operators, due to its ability to learn long-range dependencies. This replacement was proven to be successful in numerous tasks, in which several state-of-the-art methods rely on transformers for better learning. In computer vision, the 3D field has also witnessed an increase in employing the transformer for 3D convolution neural networks and multi-layer perceptron networks. Although a number of surveys have focused on transformers in vision in general, 3D …

28 Ghz Patch Antenna Array With Reduced Mutual Coupling For 5g Communications Systems, Rahabu F. Mwang’Amba, Hashimu Uledi Iddi

Tanzania Journal of Engineering and Technology (TJET)

A 28 GHz patch antenna array with reduced mutual coupling for 5G communication systems is presented in this paper. Two elements antenna array was simulated with a periodic boundary to represent an infinity array. The antenna array is attached with a pair of the coupled directional coupler with a coupling value of -3.47 dB, and transmission lengths of 3.40 mm and 7.62 mm depending on the antenna array's magnitude and phase coefficient were designed and simulated. A reduced mutual coupling of -31.86 dB compared to -10.75 dB for an array without a decoupling network was observed. The wide scanning angle …

(2022 Revision) Chapter 6: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Appendix: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 4: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

(2022 Revision) Chapter 7: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana

Open Educational Resources

No abstract provided.

Feed Forward Neural Networks With Asymmetric Training, Archit Srivastava

School of Computing: Dissertations, Theses, and Student Research

Our work presents a new perspective on training feed-forward neural networks(FFNN). We introduce and formally define the notion of symmetry and asymmetry in the context of training of FFNN. We provide a mathematical definition to generalize the idea of sparsification and demonstrate how sparsification can induce asymmetric training in FFNN.

In FFNN, training consists of two phases, forward pass and backward pass. We define symmetric training in FFNN as follows-- If a neural network uses the same parameters for both forward pass and backward pass, then the training is said to be symmetric.

The definition of asymmetric training in artificial …

A Tool-Supported Metamodel For Program Bugfix Analysis In Empirical Software Engineering, Manal Zneit

Theses and Dissertations

This thesis describes a software modeling approach aimed at addressing empirical studies in software engineering. We build a metamodel that provides an overview of the taxonomy of program bugfixes in deep learning programs. For modeling purposes, we present a prototype tool that is an implementation of the model-driven techniques presented.

Generative Design Of Stable Semiconductor Materials Using Deep Learning And Density Functional Theory, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Indika Perera, Jianjun Hu

Faculty Publications

Semiconductor device technology has greatly developed in complexity since discovering the bipolar transistor. In this work, we developed a computational pipeline to discover stable semiconductors by combining generative adversarial networks (GAN), classifiers, and high-throughput first-principles calculations. We used CubicGAN, a GAN-based algorithm for generating cubic materials and developed a classifier to screen the semiconductors and studied their stability using first principles. We found 12 stable AA’ MH₆ semiconductors in the F-43m space group including BaNaRhH₆, BaSrZnH₆, BaCsAlH₆, SrTlIrH₆, KNaNiH₆, NaYRuH₆, CsKSiH₆, CaScMnH₆, YZnMnH …

Abm Simulation Model Of A Pandemic For Optimizing Vaccination Strategy, Gibeom Park

Theses and Dissertations

This study presents a process-oriented hybrid model for individuals' immune responses and interactions involving vaccination to describe the trend of contagious disease and estimate the future societal cost. The model considers "recovery" as a non-absorbing state and incorporates various infection stage states including two symptomatic states. To model contagiousness to be consistent with the current pandemic and include that the spread of a disease depends on the mobility of people, we developed an Agent-Based Simulator that fitted to the particular model used in this study and can test various what-if scenarios. We improved the simulator considerably by appying data structures …

Evaluating The Variable Stride Algorithm In The Identification Of Diabetic Retinopathy, Ying Zheng, Brian Danaher, Matthew Brown

Beyond: Undergraduate Research Journal

An experiment was performed to investigate a modified pooling method for use in convolutional neural networks for image recognition. This algorithm–Variable Stride–allows the user to segment an image and change the amount of subsampling in each region. This control allows for the user to maintain a higher amount of data retention in more important regions of the image, while more aggressively subsampling the less important regions to increase training speed. Three Variable Stride methods were compared to the preexisting pooling algorithms, Maximum Pool and Average Pool, in three different network configurations tasked with classifying Diabetic Retinopathy images between its early …

A Multi-Dimensional Matrix Pencil-Based Channel Prediction Method For Massive Mimo With Mobility, Weidong Li, Haifan Yin, Ziao Qin, Yandi Cao, Mérouane Debbah

Machine Learning Faculty Publications

This paper addresses the mobility problem in massive multiple-input multiple-output systems, which leads to significant performance losses in the practical deployment of the fifth generation mobile communication networks. We propose a novel channel prediction method based on multi-dimensional matrix pencil (MDMP), which estimates the path parameters by exploiting the angular-frequency-domain and angular-timedomain structures of the wideband channel. The MDMP method also entails a novel path pairing scheme to pair the delay and Doppler, based on the super-resolution property of the angle estimation. Our method is able to deal with the realistic constraint of time-varying path delays introduced by user movements, …

React E-Commerce Application & Google Cloud Devops, Hemanth Panditi

Masters Projects

The “CIS 693” project consists of an electronic commerce React application and a developmental operations pipeline that was built in Google Cloud. Over the duration of the applied computer science program and popular trends in technology, there has been an emphasis on cloud computing, serverless technology/microservice architecture, containerization, and distributed computing in general. The cloud is an important and necessary platform to work from because it provides a central location with access to these tools, useful documentation, and informative demonstrations. The projects for previous classes revolved around similar topics as it is relevant in today’s context. The courses offered a …

Green Approach For Iron Oxide Nanoparticles Synthesis: Application In Antimicrobial And Anticancer- An Updated Review, Norul Aini Zakariya, Wan Hafizah W. Jusof, Shahnaz Majeed

Karbala International Journal of Modern Science

Cancer and microbial infections create numerous challenges nowadays. Chemotherapy agents cause severe side effects, while microbial infections, especially multidrug-resistant bacterial strains hard to treat with available antibiotics. Therefore, this review provides an overview of the green synthesis of Iron oxide nanoparticles (IONPs) with their physicochemical properties and mechanism of action . The IONPs causes cytotoxicity and antimicrobial activity by causing oxidative distress through the production of Reactive Oxygen Species (ROS). The IONPs as an anticancer and antimicrobial agent may help to overcome the limitation of conventional treatments but needs toxicity evaluation before usage in clinical applications.

A High Yield Method For Protoplast Isolation And Ease Detection Of Rol B And C Genes In The Hairy Roots Of Cauliflower (Brassica Oleracea L.) Inoculated With Agrobacterium Rhizogenes, Qutaiba Shuaib Al-Nema, Ghazwan Qasim Hasan, Omar Abdulazeez Alhamd

Karbala International Journal of Modern Science

Protoplasts represent a unique experimental system for the circulation and formation of genetically modified plants. Here, protoplasts were isolated from genetically modified hairy root tissues of Brassica oleracea L. induced by the Agrobacterium rhizogenes strain (ATCC13332). The concentration of enzyme solutions utilized for protoplast isolation was 1.5 % Cellulase YC and 0.1 % Pectolyase Y23 in 13% mannitol solution, which resulted in high efficiency of isolation within 8 hours, in which the protoplast yield was 2 × 104 cells ml-1 and the percentage of viability was 72%. Each protoplast has one nucleus with a nucleation of 48%. A polymerase chain …

Tapioca Starch In The Sol-Gel Synthesis Of Cobalt Ferrites With Divalent Cation Substitutions, Anuchit Hunyek, Chitnarong Sirisathitkul, Krit Koyvanich

Karbala International Journal of Modern Science

An aqueous solution of tapioca starch was successfully used as a chelating agent in the sol-gel synthesis of Co0.7Me0.3Fe2O4, where Me denotes Co, Mn, Cu, Ni, or Zn. The hysteresis loops of all sintered ferrites revealed ferrimagnetic properties. The saturation magnetization was reduced in Co0.7Cu0.3Fe2O4 and Co0.7Ni0.3Fe2O4 because of the ion substitutions with smaller magnetic moments. Interestingly, Co0.7Cu0.3Fe2O4 exhibited the highest saturation magnetization and the lowest coercive field. This result demonstrates the value addition of local agricultural products in controlling nanoparticle formation during sol-gel synthesis.