Digital Commons Network^™

Pause For A Cybersecurity Cause: Assessing The Influence Of A Waiting Period On User Habituation In Mitigation Of Phishing Attacks, Amy Antonucci

CCAC Theses and Dissertations

Social engineering costs organizations billions of dollars a year. Social engineering exploits the weakest link of information security systems, the people who are using them. Phishing is a form of social engineering in which the perpetrator depends on the victim’s instinctual thinking towards an email designed to create a fear or excitement response. It is well-documented in literature that users continue to click on phishing emails costing them and their employers significant monetary resources and data loss. Training does not appear to mitigate the effects of phishing much; other solutions are necessary to mitigate phishing.

Kahneman introduced the concepts of …

A Study Of Factors That Influence Symbol Selection On Augmentative And Alternative Communication Devices For Individuals With Autism Spectrum Disorder, William Todd Dauterman

CCAC Theses and Dissertations

According to the American Academy of Pediatrics (AAP), 1 in 59 children are diagnosed with Autism Spectrum Disorder (ASD) each year. Given the complexity of ASD and how it is manifested in individuals, the execution of proper interventions is difficult. One major area of concern is how individuals with ASD who have limited communication skills are taught to communicate using Augmentative and Alternative Communication devices (AAC). AACs are portable electronic devices that facilitate communication by using audibles, signs, gestures, and picture symbols. Traditionally, Speech-Language Pathologists (SLPs) are the primary facilitators of AAC devices and help establish the language individuals with …

Enhancing Stability And Antioxidant Efficacy Of Fisetin By Encapsulating As Β-Cyclodextrin Inclusion Complex With Porous Polylactic Acid Film From Breath Figure, Charasphat Preuksarattanawut, Warinyupa Mangmee, Munchumas Prousoontorn, Ekasit Nisarattanaporn, Krisana Siraleartmukul

Journal of Metals, Materials and Minerals

This research aims to investigate the scope of fisetin (FIT)/β-cyclodextrin (β-CD) inclusion complexes with the ratios of 1:2 and 2:1 mole by means of freeze-drying, kneading and physical mixing methods (controlled process). Moreover, the complex compounds are analyzed by Fourier-Transform Infrared Spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC). The results show that the most suitable preparation method of fisetin (FIT)/β-CD complex is the freeze-drying method with the fisetin (FIT) to β-CD ratio at 1:2. The emission of FIT/β-CD was investigated and it is found that the emission rate of freeze-dried FIT/β-CD in 1:2 ratio by freeze-drying method is lower than …

Sustainable Valorization Of Sugarcane Leaves For Succinic Acid And Biochar Production, Nuttaporn Chokesawatanakit, Pasakorn Jutakridsada, Khanita Kamwilaisak

Journal of Metals, Materials and Minerals

The leaves of sugarcane (Saccharum officinarum) are agricultural waste that is burnt before harvesting. This project aims to find an alternative way to increase the value of sugarcane leaves and decrease air pollution by using the leaves as raw material to produce succinic acid and biochar. Reducing sugars were extracted from the leaves by H2SO4 hydrolysis. The sugars were then fermented by Yarrowia lipolytica TBRC 4417 to produce succinic acid. The solid residue was used as the raw material for biochar production by pyrolysis. The effects of pyrolysis temperature (350, 400, and 450℃) and nitrogen gas flow rate (5, 10, …

New Views On The Ingenious Applications Of Ag Nanoparticles As A Sensor For Antibiotic Detection And As A Potent Antimicrobial Agent, Keyur Bhatt, Anita Kongor, Mohd Atharb, Vinod Jain

Journal of Metals, Materials and Minerals

Nanotechnology uses exceptional approaches for the control of bacterial infections which uncovers the potential function of bio-systems at nano-scale level. Compared to silver ions, silver nanoparticles possess enhanced physicochemical stability and low bio-toxicity properties. The intrinsic chemical framework of silver nanoparticles is prone to exhibit a significant chemistry when used as sensor and as therapeutic. Nowadays, silver is used in (nano-) medicine, in the form of nanoparticles to optimize its therapeutic property for controlling infections caused by multidrug-resistant bacteria. Exclusive use of antibiotics as medicines and its discharge from the body of the infected person or animals into the sewage …

Facile Purification Of Locally Mined Gypsum And Its Use For Preparing Nano-Hemihydrates, Luqman Ayodeji Adams, Enobong Essien, Taiwo Aiyeloro, Stella Oseyomon, John Makanjuola

Journal of Metals, Materials and Minerals

Gypsum has a wide range of applications, in interior decorations, building construction, supplements or implants in orthopaedics to mention a few. However, in many developing countries including Nigeria, there is still a large-scale importation despite huge available natural deposits. In this study, a facile method to purify locally-mined gypsum has been explored based on the mineral retrograde solubility in water. The purified gypsum was investigated for its elemental composition in comparison to the crude sample and a commercially obtained medical-grade gypsum using X-ray fluorescence (XRF). The results showed that the purified gypsum contained 94.05% CaSO4 compared with the crude which …

Efficiency Of 2-Dodecylaminopyridine For The Liquid-Liquid Extraction Of Gold(Iii) From Succinic Acid Medium, Umrao Shep, Rucha Pawar, Balasaheb Arbad

Journal of Metals, Materials and Minerals

Extractive recovery of gold(III) from succinic acid solution with high molecular weight amine: 2-dodecylaminopyridine (2-DDAP) as a new extractant in xylene has been investigated. Extraction data indicates that 5 × 10-4 mol⋅L-1 2-DDAP is a very efficient and fast extractant. Gold(III) can be effectively extracted (D = 414.16) with 2-DDAP from 0.04 M succinic acid solution. The equilibrium of gold(III) from aqueous phase of succinic acid with 2-DDAP is achieved within 60 sec. The extraction of gold(III) with 2-DDAP proceed at the interface according to ion pair formation mechanism. The best stripping solution from among the studied ones is the …

Effect Of Dc Power On The Thickness, Hardness And Adhesion Strength Of Ti-51 At% Ni Coated Ti/Tin, Ishiaka Shaibu Arudi, Esah Hamzah, Muhammad Azizi Mat Yajid, Bushroa Abdul Razak

Journal of Metals, Materials and Minerals

The coating of Ti/TiN was successfully deposited on Ti-51 at% Ni substrates by using direct current (DC) magnetron sputtering technique and the effect of different sputtering power on the thickness, surface hardness and adhesion strength of the coatings were studied. The microstructural characterization was carried out using scanning electron microscope (SEM), energy-dispersive X-ray (EDX) and X-ray diffractometer (XRD). The coating thicknesses were detected and measured using SEM. The surface hardness test was performed using microhardness tester, and the adhesion strength was carried out by scratch testing. The results showed that the TiN crystallites growth orientation, thickness, surface hardness and adhesion …

Developments Of Biodegradable Polymer Based On Polylactic Acid (Pla) With Natural Color Extracts For Packaging Film Applications, Worraphol Nansu, Passarawan Chaiwut, Sukunya Ross, Gareth Ross, Nungruthai Suphrom, Sararat Mahasaranon

Journal of Metals, Materials and Minerals

This research was interested in the use of natural colorants to replace hazardous synthetic pigments in the plastic polymer industry. The natural colors were selected from local plants indigenous to southeast Asia, which were Hibiscus sabdariffa roselle calyx (RS) and Caesapinia sappan Linn heartwood (SP). Natural colorant extracts were used as additives in poly(lactic acid ) (PLA). These were manufactured using a twin screws extruder and blow film extruder to obtain biodegradable thin films for use as packaging materials. Biodegradable films were characterized by color index, light barrier properties, water vapor transmission (WVTR), morphology, mechanical and chemical properties. The results …

Raman Signal Enhancement Of Low-Cost Metal Sheet Sers With Gold Decoration, Nampueng Pangpaiboon, Kawinphob Phetnam, Sukon Kalasung, Chanunthorn Chananonawathorn, Viyapol Patthanasettakul, Mati Horprathum, Pitak Eiamchai, Noppadon Nuntawong, Saksorn Limwichean

Journal of Metals, Materials and Minerals

Surface Enhance Raman Spectroscopy (SERS) is a sensitive surface creating plasmonic resonance for the Raman scattering. SERS is considered as a powerful technique to enhance the Raman signal, when quantity of sample is limited. Recently, our lab team has discovered a low-cost SERS template fabrication, laser-engraving method, which is suitable with gold nanoparticles decoration. In this work, two different materials, zinc and copper, are used as metal sheet SERS substrate. Gold nanoparticles sputtered with 270 s of sputtering time are used as decorated noble metal. FE-SEM images illustrate the nano-in-microstructure of the engraved metal sheets. The decorated Au nanoparticles are …

Development Of Chemical Methods For Oligonucleotide Purification, Paramagnetic Labeling And Synthesis Of Dna-Based Advanced Materials, Muhan He

Legacy Theses & Dissertations (2009 - 2024)

This thesis describes a chemical method for alternative oligonucleotide purification that is non-chromatographic and gel-free and allows to routinely synthesize and purify long functional RNA strands. The purification of long RNAs is based on the bio-orthogonal inverse electron demand Diels-Alder (IEDDA) chemistry between trans-cyclooctene (TCO) and tetrazine (Tz). Target oligonucleotide strands are selectively tagged with Tz and can be captured and purified from the failure sequences with immobilized TCO. RNA strands are synthesized on solid support through a photolabile linker to avoid the loss of Tz tag. Purity of the isolated oligonucleotides was evaluated using gel electrophoresis, HPLC and mass …

Mixed Carrier Communication For Sixth-Generation Networks :, Ahmed Fahmy Mahmoud Hussein

Legacy Theses & Dissertations (2009 - 2024)

Recently, research on sixth-generation (6G) wireless networks has gained significant interest. By 2030, it is expected that 6G will introduce revolutionary applications and services. Thus, 6G is likely to expand across all available spectrum, including terahertz (THz) and optical frequency bands. Although 5G will offer a massive upgrade to the spectrum, the technology does not provide solutions to support a vast multitude of services and devices simultaneously.Motivated by the heterogeneity of wireless technologies, devices, and services, the Mixed Carrier Communication (MCC) concept is introduced for the first time. MCC is a novel concept that supports the 6G vision by enabling …

Intrabodies Reveal Critical Steps Involved In Ricin's Interactions With The Ribosome, Timothy Francis Czajka

Legacy Theses & Dissertations (2009 - 2024)

Ricin is a highly lethal protein toxin derived from the seeds of the castor plant, Ricinus communis. It is a Type II ribosome inactivating protein (RIP), meaning it is a heterodimer with one subunit, ricin toxin B (RTB), that mediates cell surface attachment and intracellular trafficking and a second subunit, ricin toxin A (RTA), that irreversibly shuts down protein synthesis in the cytosol. During trafficking, RTA and RTB necessarily separate in the endoplasmic reticulum, wherein RTA unfolds and translocates into the cytosol where it refolds into an enzymatically active conformation. RTA is remarkably fast acting and efficient, with few molecules …

Deformation Manifold Learning Model For Multi Walled Carbon Nanotubes, Shashank S. Pathrudkar

Dissertations, Master's Theses and Master's Reports

Two-Dimensional (2D) materials are being studied widely by researchers due to their superior material properties over the bulk materials. Since the isolation of graphene in 2004, graphene has gained popularity amongst the 2D materials community. Graphene when rolled into sheets form Carbon Nanotubes (CNTs) which possess excellent mechanical and electrical properties. Concentric stacks of CNTs yield Multi-walled Carbon Nanotubes (MWCNTs) which are superior to CNTs in certain aspects. It has been well established that the deformation of CNTs and MWCNTs change their mechanical and electrical properties significantly. This has opened doors for CNTs into numerous applications and also piqued the …

Understanding The Weather- And Soil-Related Variability In Agricultural Water Footprints: Case Study Of Maize And Soybeans Grown In The St. Joseph Watershed, Karleigh M. Krieg

Dissertations, Master's Theses and Master's Reports

Introduced in 2002, the water footprint is a valuable tool for understanding the consumption of freshwater resources. The traditional approach to quantifying the water footprint is to sum the green, blue, and gray water footprint components. The green water footprint is the volume of water that comes from precipitation, is stored in the soil, and used by vegetation. The blue water footprint is the volume of surface or ground water that is withdrawn and applied to cultivated lands via irrigation. These components are based on the evapotranspiration of green and blue water resources, respectively. The gray water footprint is the …

Clustering Ensemble Selection Based On The Extended Jaccard Measure, Hajar Khalili, Mohsen Rabbani, Ebrahim Akbari

Turkish Journal of Electrical Engineering and Computer Sciences

Clustering ensemble selection has shown high efficiency in the improvement of the quality of clustering solutions. This technique comprises two important metrics: diversity and quality. It has been empirically proved that ensembles of higher effectiveness can be achieved through taking into consideration the diversity and quality simultaneously. However, the relationships between these two metrics in base clusterings have remained uncertain. This paper suggests a new hierarchical selection algorithm using a diversity/quality measure based on the Jaccard similarity measure. In the proposed algorithm, the selection of the subsets of the clustering partitions is done based on their diversity measures. The proposed …

Exploring The Attention Process Differentiation Of Attention Deficit Hyperactivity Disorder (Adhd) Symptomatic Adults Using Artificial Intelligence Onelectroencephalography (Eeg) Signals, Gökhan Güney, Esra Kisacik, Canan Kalaycioğlu, Görkem Saygili

Turkish Journal of Electrical Engineering and Computer Sciences

Attention deficit and hyperactivity disorder (ADHD) onset in childhood and its symptoms can last up till adulthood. Recently, electroencephalography (EEG) has emerged as a tool to investigate the neurophysiological connection of ADHD and the brain. In this study, we investigated the differentiation of attention process of healthy subjects with or without ADHD symptoms under visual continuous performance test (VCPT). In our experiments, artificial neural network (ANN) algorithm achieved 98.4% classification accuracy with 0.98 sensitivity when P2 event related potential (ERP) was used. Additionally, our experimental results showed that fronto-central channels were the most contributing. Overall, we conclude that the attention …

Evaluation Of Mother Wavelets On Steady-State Visually-Evoked Potentials Fortriple-Command Brain-Computer Interfaces, Ebru Sayilgan, Yilmaz Kemal Yüce, Yalçin İşler

Turkish Journal of Electrical Engineering and Computer Sciences

Wavelet transform (WT) is an important tool to analyze the time-frequency structure of a signal. The WT relies on a prototype signal that is called the mother wavelet. However, there is no single universal wavelet that fits all signals. Thus, the selection of mother wavelet function might be challenging to represent the signal to achieve the optimum performance. There are some studies to determine the optimal mother wavelet for other biomedical signals; however, there exists no evaluation for steady-state visually-evoked potentials (SSVEP) signals that becomes very popular among signals manipulated for brain-computer interfaces (BCIs) recently. This study aims to explore, …

Sleep Staging With Deep Structured Neural Net Using Gabor Layer And Dataaugmentation, Ali Erfani Sholeyan, Fereidoun Nowshiravan Rahatabad, Kamal Setaredan

Turkish Journal of Electrical Engineering and Computer Sciences

Slow wave sleep (SWS) and rapid eye movement (REM) are two of the most important sleep stages that are considered in many studies. Detection of these two sleep stages will help researchers in many applications to detect sleeprelated diseases and disorders and also in many fields of neuroscience studies such as cognitive impairment and memory consolidation. Since manual sleep staging is time-consuming, subjective, and expensive; designing an efficient automatic sleep scoring system will overcome some of these difficulties. Many studies have proposed automatic sleep staging systems with different methods. In recent years, deep learning methods show their potential in different …

Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, hybrid methods are proposed for feature selection and classification of gene expression datasets. In the proposed genetic algorithm/support vector machine (GA-SVM) and genetic algorithm/k nearest neighbor (GA-KNN) hybrid methods, genetic algorithm is improved using Pearson's correlation coefficient, Relief-F, or mutual information. Crossover and selection operations of the genetic algorithm are specialized. Eight different gene expression datasets are used for classification process. The classification performances of the proposed methods are compared with the traditional GA-KNN and GA-SVM wrapper methods and other studies in the literature. Classification results demonstrate that higher accuracy rates are obtained with the proposed methods …

Presentation Attack Detection For Face Recognition Using Remotephotoplethysmography And Cascaded Fusion, Mehmet Fati̇h Gündoğar, Çi̇ğdem Eroğlu Erdem

Turkish Journal of Electrical Engineering and Computer Sciences

Spoofing (presentation) attacks are important threats for face recognition and authentication systems, which try to deceive them by presenting an image or video of a different subject, or by using a 3D mask. Remote (non-contact) photoplethysmography (rPPG) is useful for liveness detection using a facial video by estimating the heart-rate of the subject. In this paper, we first compare the presentation attack detection performance of three different rPPG-based heart rate estimation methods on four datasets (3DMAD, Replay-Attack, Replay-Mobile, and MSU-MFSD). We also present a cascaded fusion system, which utilizes a multistage ensemble of classifiers using rPPG, motion-based (including head-pose, eye-gaze …

A Hybrid Convolutional Neural Network Approach For Feature Selection Anddisease Classification, Prajna Paramita Debata, Puspanjali Mohapatra

Turkish Journal of Electrical Engineering and Computer Sciences

: Many researchers have analyzed the high dimensional gene expression data for disease classification using several conventional and machine learning-based approaches, but still there exists some issues which make this task nontrivial. Due to the growing complexities of the unstructured data, the researchers focus on the deep learning approach, which is the latest form of machine learning algorithm. In the presented work, a kernel-based Fisher score (KFS) approach is implemented to extract the notable genes, and an improvised chaotic Jaya (CJaya) algorithm optimized convolutional neural network (CJaya-CNN) model is applied to classify high dimensional gene expression or microarray data. This …

Malignant Skin Melanoma Detection Using Image Augmentation By Oversamplingin Nonlinear Lower-Dimensional Embedding Manifold, Olusola Oluwakemi Abayomi-Alli, Robertas Damasevicius, Sanjay Misra, Rytis Maskeliunas, Adebayo Abayomi-Alli

Turkish Journal of Electrical Engineering and Computer Sciences

The continuous rise in skin cancer cases, especially in malignant melanoma, has resulted in a high mortality rate of the affected patients due to late detection. Some challenges affecting the success of skin cancer detection include small datasets or data scarcity problem, noisy data, imbalanced data, inconsistency in image sizes and resolutions, unavailability of data, reliability of labeled data (ground truth), and imbalance of skin cancer datasets. This study presents a novel data augmentation technique based on covariant Synthetic Minority Oversampling Technique (SMOTE) to address the data scarcity and class imbalance problem. We propose an improved data augmentation model for …

Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A brain tumor is an abnormal growth of a mass or cell in the brain. Early diagnosis of the tumor significantly increases the chances of successful treatment. Artificial intelligence-based systems can detect the tumor in early stages. In this way, it could be possible to detect a tumor and resolve this problem that may endanger human life early. In the study, the partial correlation-based channel selection formula was presented that allowed the selection of the most prominent feature that differs from the other studies in the literature. Additionally, the multi-channel convolution structure was proposed for the feature network phase of …

A Deep Transfer Learning Based Model For Automatic Detection Of Covid-19from Chest X-Rays, Prateek Chhikara, Prakhar Gupta, Prabhjot Singh, Tarunpreet Bhatia

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning in medical imaging has revolutionized the way we interpret medical data, as high computational devices' capabilities are far more than their creators. With the pandemic causing havoc for the second straight year, the findings in our paper will allow researchers worldwide to use and create state-of-the-art models to detect affected persons before it reaches the R number. The paper proposes an automated diagnostic tool using the deep learning models on chest x-rays as an input to reach a point where we surpass this pandemic (COVID-19 disease). A deep transfer learning-based model for automatic detection of COVID-19 from chest …

Deep Learning-Based Covid-19 Detection System Using Pulmonary Ct Scans, Rajit Nair, Adi Alhudhaif, Deepika Koundal, Rumi Iqbal Doewes, Preeti Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

One of the most significant pandemics has been raised in the form of Coronavirus disease 2019 (COVID19). Many researchers have faced various types of challenges for finding the accurate model, which can automatically detect the COVID-19 using computed pulmonary tomography (CT) scans of the chest. This paper has also focused on the same area, and a fully automatic model has been developed, which can predict the COVID-19 using the chest CT scans. The performance of the proposed method has been evaluated by classifying the CT scans of community-acquired pneumonia (CAP) and other non-pneumonia. The proposed deep learning model is based …

Classification Of P300 Based Brain Computer Interface Systems Using Longshort-Term Memory (Lstm) Neural Networks With Feature Fusion, Ali̇ Osman Selvi̇, Abdullah Feri̇koğlu, Derya Güzel

Turkish Journal of Electrical Engineering and Computer Sciences

Enabling to obtain brain activation signs, electroencephalography is currently used in many applications as a medical diagnostic method. Brain-computer interface (BCI) applications are developed to facilitate the lives of individuals who have not lost their brain functions yet have lost their motor and communication abilities. In this study, a BCI system is proposed to make classification using Bi-directional long short term memory (Bi-LSTM) neural networks. In the designed system, spectral entropy method including instantaneous frequency change of signal is used as feature fusion. In the study, electroencephalography (EEG) data of 10 participants are collected with Emotiv EPOC+ device using 2x2 …

Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap

Turkish Journal of Electrical Engineering and Computer Sciences

As per 2016 updates by World Health Organization (WHO) on cancer disease, gliomas are categorized and further treated based on genomic mutations. The imaging modalities support a complimentary but immediate noninvasive diagnosis of cancer based on genetic mutations. Our aim is to train a deep convolutional neural network for isocitrate dehydrogenase (IDH) genotyping of glioma by auto-extracting the most discriminative features from magnetic resonance imaging (MRI) volumes. MR imaging data of total 217 patients were obtained from The Cancer Imaging Archives (TCIA) of high and low-grade gliomas. A 3-pathway convolutional neural network was trained for IDH classification. The multipath neural …

Leukocyte Classification Based On Feature Selection Using Extra Trees Classifier: Atransfer Learning Approach, Diana Baby, Sujitha Juliet Devaraj, Jude Hemanth, Anishin Raj M M

Turkish Journal of Electrical Engineering and Computer Sciences

The criticality of investigating the white blood cell (WBC) count cannot be underestimated, as white blood cells are an important component of the body's defence system. From helping to diagnose hidden infections to insinuating the presence of comorbidities like immunodeficiency, an accurate white blood cell count can contribute significantly to shape a physician?s assessment. The manual process performed by the pathologists for the classification of WBCs is a time consuming and tedious task, which is further disadvantaged by a lack of accuracy. This study concentrates on the automatic detection and classification of WBC without data augmentation into four subtypes such …

Improved Cell Segmentation Using Deep Learning In Label-Free Optical Microscopyimages, Aydin Ayanzadeh, Özden Yalçin Özuysal, Devri̇m Pesen Okvur, Sevgi̇ Önal, Behçet Uğur Töreyi̇n, Devri̇m Ünay

Turkish Journal of Electrical Engineering and Computer Sciences

The recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the …