Computer Sciences Commons^™

Green Intellectual Capital And Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?, Ayman Wael Al-Khatib, Ahmed Shuhaiber

All Works

In light of global environmental concerns growing, environmental awareness within firms has become more important than before, and many scholars and researchers have argued the importance of environmental management in promoting sustainable organizational performance, especially in the context of supply chains. Thus, the current study aimed at identifying the impact of the components of green intellectual capital (green human capital, green structural capital, green relational capital) on green supply chain performance in the manufacturing sector in Jordan, as well as identifying the moderating role of big data analytics capabilities. To achieve this aim, we developed a conceptual model of Structural …

Mathematical Models Yield Insights Into Cnns: Applications In Natural Image Restoration And Population Genetics, Ryan Cecil

Electronic Theses and Dissertations

Due to a rise in computational power, machine learning (ML) methods have become the state-of-the-art in a variety of fields. Known to be black-box approaches, however, these methods are oftentimes not well understood. In this work, we utilize our understanding of model-based approaches to derive insights into Convolutional Neural Networks (CNNs). In the field of Natural Image Restoration, we focus on the image denoising problem. Recent work have demonstrated the potential of mathematically motivated CNN architectures that learn both `geometric' and nonlinear higher order features and corresponding regularizers. We extend this work by showing that not only can geometric features …

Bot-Mgat: A Transfer Learning Model Based On A Multi-View Graph Attention Network To Detect Social Bots, Eiman Alothali, Motamen Salih, Kadhim Hayawi, Hany Alashwal

All Works

Twitter, as a popular social network, has been targeted by different bot attacks. Detecting social bots is a challenging task, due to their evolving capacity to avoid detection. Extensive research efforts have proposed different techniques and approaches to solving this problem. Due to the scarcity of recently updated labeled data, the performance of detection systems degrades when exposed to a new dataset. Therefore, semi-supervised learning (SSL) techniques can improve performance, using both labeled and unlabeled examples. In this paper, we propose a framework based on the multi-view graph attention mechanism using a transfer learning (TL) approach, to predict social bots. …

Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead

Art Faculty Articles and Research

We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.

System Dynamics Modeling For Traumatic Brain Injury: Mini-Review Of Applications, Erin S. Kenzie, Elle L. Parks, Nancy Carney, Wayne Wakeland

Complex Systems Faculty Publications and Presentations

Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery …

Computational Imaging For Shape Understanding, Yuqi Ding

LSU Doctoral Dissertations

Geometry is the essential property of real-world scenes. Understanding the shape of the object is critical to many computer vision applications. In this dissertation, we explore using computational imaging approaches to recover the geometry of real-world scenes. Computational imaging is an emerging technique that uses the co-designs of image hardware and computational software to expand the capacity of traditional cameras. To tackle face recognition in the uncontrolled environment, we study 2D color image and 3D shape to deal with body movement and self-occlusion. Especially, we use multiple RGB-D cameras to fuse the varying pose and register the front face in …

A Smartwatch Step-Counting App For Older Adults: Development And Evaluation Study, George Boateng, Curtis L. Petersen, David Kotz, Karen L. Fortuna, Rebecca Masutani, John A. Batsis

Dartmouth Scholarship

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have …

Purifications Of Iraqi Petroleum Using Ceramic Ball Nano Cobalt Nickel Ferrite Filter, Huda Jabbar, Enas Muhi, Tahseen Hussien

Karbala International Journal of Modern Science

Iraqi petroleum, especially from the Al-Ahdab, has a big problem resulting from its high percentage of heavy metals. In this paper, heavy metals were reduced or removed from Iraqi petroleum using a Ceramic Ball Nano Cobalt Nickel Ferrite Filter (BCNF), synthesized by combining kaolin and palm frond in a 30% ratio with Co0.8Ni0.2Fe2O4 nanoparticles in a various ratios (5, 10, 15, and 20%). The sol-gel technique prepared Co0.8Ni0.2Fe2O4 nanoparticles. The structure and magnetic properties of the material are described using X-RD, FT-IR, and VSM techniques. In addition, the water ab-sorption ratio and apparent porosity were assessed. The results show that …

Studying The Physical And Biological Characteristics Of Denture Base Resin Pmma Reinforced With Zro2 And Tio2 Nanoparticles, Fatin A. Asim, Entessar H.A. Al-Mosaweb, Wafaa A. Hussain

Karbala International Journal of Modern Science

Polymethyl methacrylate (PMMA) suffers from poor mechanical properties that limit its application in the bio-medical field. In this study, PMMA was reinforced with zirconium dioxide (ZrO2) and titanium dioxide (TiO2) nanopar-ticles; subsequently, the hardness, porosity, biocompatibility, bacterial adhesion, and colonization of the reinforced PMMA with various oxide nanoparticles were characterized. The results of this study indicated that reinforced material inhibits bacterial growth and decreases bacterial adhesion by decreasing porosity and increasing PMMA hardness. Based on the findings, 3 wt% PMMA-ZrO2 and 3 wt% PMMA-ZrO2 -TiO2 composites significantly inhibited bacterial growth and adherence while maintaining hemolysis PT and INR and enhancing …

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 …