Engineering Commons^™

A Radial Basis Function Neural Network Algorithm For The Simultaneous Retrieval Of Two Meteorological Parameters From Solar Radiation, Nicholas W. Nzala, Nicolausi Ssebiyonga, Dennis Muyimbwa, Taddeo Ssenyonga

Tanzania Journal of Science

Local meteorological parameters are key in understanding the frequency of occurrence of extreme weather conditions such as floods, and droughts, among others. In this study, we present a method for simultaneous retrieval of two weather parameters. The method is based on already measured monthly average values of weather parameters from 2011 to 2016, which were used to train a Feed-forward radial basis function neural network (RBFNN) to obtain a fast and accurate method to compute global solar radiation for specified weather parameters pair. In inverse modelling, a multidimensional unconstrained non-linear optimization was employed to retrieve the weather parameters pair. The …

Engineering Of Functionalized Carbon Nano-Onions Embedded Bsa Nanocomposite Fibers For Stimuli-Responsive Drug Release, Ramiro Manuel Velasco Delgadillo, Narsimha Mamidi

Research Symposium

Background: Advanced drug delivery systems (DDSs) have received enormous attention in biomedical applications due to their pharmacodynamic and pharmacokinetic drug properties. For the present study, poly 4-hydroxyphenyl methacrylate (PHPMA)/CNOs (f-CNOs) inserted bovine serum albumin (BSA) nanofibers were prepared for stimuli-responsive release of Doxorubicin (DOX). Temperature and pH would be altered to study the release of DOX in acidic microenvironments.

Methods: PHPMA were coupled with COOH-CNOs via ester coupling via the sonochemical method to produce PHPMA-CNOs (f-CNOs). Then, f-CNOs/DOX embedded BSA nanofibers were prepared at room temperature using Forcespinning. UV spectra of DOX-loaded nanofibers were studied to investigate the …

Engineered Exosomes For The Multimodal Imaging Directed Photo-Immunotherapy Of Colorectal Cancer, Deepak S. Chauhan, Meena Jaggi, Subhash C. Chauhan, Murali M. Yallapu

Research Symposium

Background: Rio Grande Valley experience severe cancer health disparity. A novel therapeutic modality may serve as better therapeutic option. Nanohybrids endowed with multifunctionality, longer circulation time, large surface area have emerged as an active preference for cancer research. However, rising concern of nanomaterials toxicity and scalability issues has slowed their translation to clinics. Exosomes (Exo) are endogenous endocytic origin 40-100 nm vesicles found in various body fluids, which in comparison to synthetic nanoparticles, are biodegradable, highly biocompatible as well as immunocompatible in nature. Although bulk isolation of exosomes from human body fluids is still a problem and engineering of exosomes …

Biocidal Properties Of Hybrid Nanonanomaterial, Chandrasekaran Karthikeyan, Kokkarachedu Varaprasad

Research Symposium

Background: Cancer is one of the essential unpredictable diseases worldwide; simultaneously, complicated issues created are by the human health system. Especially, breast cancer is the most commonly occurring cancer in women and is increasing remarkably in developing countries. It is a leading cause of cancer death in women, and breast cancer incidence rates are growing globally. To diagnose and treat cancer cells, different methods such as Radiation Therapy, Surgery, and Chemotherapy. These methods are high risk, more side effects, and high costs. The advanced healthcare material was developed to overcome this problem, inexpensive tools, and diagnosis of less-toxic drugs with …

A 3d Printed Microneedle System For Transdermal Drug Delivery Of Anticancer Drugs, Md Jasim Uddin, Tanvir Ahmed, Dennis Douroumis

Research Symposium

Background: Transdermal delivery of drugs is an attractive alternative to the conventional route of administration as oral delivery. The hypodermic injections are painful and less patient compliance. Microneedles (MNs) are micron-sized, minimally invasive needles to deliver a wide range of molecules (e.g., small, DNA, vaccines etc.) to the upper portion of the dermis in a sustained and controlled manner, without causing any pain. The introduction of 3D printing technologies in the fabrication of MN will promote one-step manufacturing tools and scale-up for the delivery devices of anticancer drugs.

Methods: The 3D printed MN (3DMN) arrays were fabricated using Stereolithography (SLA), …

The Santa Clara, 2023-09-29, Santa Clara University

The Santa Clara

No abstract provided.

Using T-Distributed Stochastic Neighbor Embedding For Visualization And Segmentation Of 3d Point Clouds Of Plants, Heli̇n Dutağaci

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, the use of t-SNE is proposed to embed 3D point clouds of plants into 2D space for plant characterization. It is demonstrated that t-SNE operates as a practical tool to flatten and visualize a complete 3D plant model in 2D space. The perplexity parameter of t-SNE allows 2D rendering of plant structures at various organizational levels. Aside from the promise of serving as a visualization tool for plant scientists, t-SNE also provides a gateway for processing 3D point clouds of plants using their embedded counterparts in 2D. In this paper, simple methods were proposed to perform semantic …

Dynamic Deep Neural Network Inference Via Adaptive Channel Skipping, Meixia Zou, Xiuwen Li, Jinzheng Fang, Hong Wen, Weiwei Fang

Turkish Journal of Electrical Engineering and Computer Sciences

Deep neural networks have recently made remarkable achievements in computer vision applications. However, the high computational requirements needed to achieve accurate inference results can be a significant barrier to deploying DNNs on resource-constrained computing devices, such as those found in the Internet-of-things. In this work, we propose a fresh approach called adaptive channel skipping (ACS) that prioritizes the identification of the most suitable channels for skipping and implements an efficient skipping mechanism during inference. We begin with the development of a new gating network model, ACS-GN, which employs fine-grained channel-wise skipping to enable input-dependent inference and achieve a desirable balance …

Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük

Turkish Journal of Electrical Engineering and Computer Sciences

Intent detection and slot filling are two crucial subtasks of a text-based goal-oriented dialogue system. In a goal-oriented dialogue system, users interact with the system to complete a goal (or to fulfill their intent) and provide the necessary information (slot values) to achieve that goal. Therefore, a user?s text input includes information about the user?s intent and contains required slot values. Recently, joint models that simultaneously detect the intent and extract the slots are proposed to benefit from the interaction between the two tasks. The proposed methods are usually tested using benchmark data sets in English such as ATIS and …

Transforming Temporal-Dynamic Graphs Into Time-Series Data For Solving Event Detection Problems, Kutay Taşci, Fuat Akal

Turkish Journal of Electrical Engineering and Computer Sciences

Event detection on temporal-dynamic graphs aims at detecting significant events based on deviations from the normal behavior of the graphs. With the widespread use of social media, many real-world events manifest as social media interactions, making them suitable for modeling as temporal-dynamic graphs. This paper presents a workflow for event detection on temporal-dynamic graphs using graph representation learning. Our workflow leverages generated embeddings of a temporal-dynamic graph to reframe the problem as an unsupervised time-series anomaly detection task. We evaluated our workflow on four distinct real-world social media datasets and compared our results with the related work. The results show …

Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a spiking neural network (SNN) has been proposed for recognizing the digits written on the LCD screen of an experimental setup. The convergence of the learning algorithm has been ensured by using sliding mode control (SMC) theory and the Lyapunov stability method for the adaptation of the network parameters. The spike response model (SRM) has been utilized in the design of the SNN. The performance of the proposed learning scheme has been evaluated both on the experimental data and on the MNIST dataset. The simulated and experimental results of the SNN structure have been compared with the …

A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Dyslexia is a learning disorder, characterized by impairment in the ability to read, spell, and decode letters. It is vital to detect dyslexia in earlier stages to reduce its effects. However, diagnosing dyslexia is a time-consuming and costly process. In this paper, we propose a machine-learning model that predicts whether a Turkish-speaking child has dyslexia using his/her audio records. Therefore, our model can be easily used by smart phones and work as a warning system such that children who are likely to be dyslexic according to our model can seek an examination by experts. In order to train and evaluate, …

Direct Pore-Based Identification For Fingerprint Matching Process, Vedat Delican, Behçet Uğur Töreyi̇n, Ege Çeti̇n, Ayli̇n Yalçin Saribey

Turkish Journal of Electrical Engineering and Computer Sciences

Fingerprints are one of the most important scientific proof instruments in solving forensic cases. Identification in fingerprints consists of three levels based on the flow direction of the papillary lines at the first level, the minutiae points at the second level, and the pores at the third level. The inadequacy of existing imaging systems in detecting fingerprints and the lack of pore details at the desired level limit the widespread use of third-level identification. The fact that fingerprints with images based on pores in the unsolved database are not subjected to any evaluation criteria and remain in the database reveals …

Vulnerable Road User Safety: Data Collection, Analysis, And Countermeasures, Anahita Kakhani

Theses and Dissertations

The safety of pedestrians and bicyclists (vulnerable road users) has become a paramount global concern, especially with a 53% and 31% surge in related crashes over the past decade in the U.S. Despite transportation agencies implementing various safety measures to address this issue, the number of severe injuries among these road users continues to climb annually. This underscores the urgent need for innovative methodologies and technologies to pinpoint the factors compromising their safety. To do so, this study aimed to introduce and employ techniques and countermeasures to gain deeper insight into risks faced by vulnerable road users. This study includes …

The Role Of Nanofluids In Renewable Energy Engineering, M. M. Bhatti, K. Vafai, Sara I. Abdelsalam

Basic Science Engineering

No abstract provided.

Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer

Turkish Journal of Electrical Engineering and Computer Sciences

Although the standard k-nearest neighbor (KNN) algorithm has been used widely for classification in many different fields, it suffers from various limitations that abate its classification ability, such as being influenced by the distribution of instances, ignoring distances between the test instance and its neighbors during classification, and building a single/weak learner. This paper proposes a novel algorithm, called stepwise dynamic nearest neighbor (SDNN), which can effectively handle these problems. Instead of using a fixed parameter k like KNN, it uses a dynamic neighborhood strategy according to the data distribution and implements a new voting mechanism, called stepwise voting. Experimental …

Cognitive Load Detection Using Ci-Ssa For Eeg Signal Decomposition And Nature-Inspired Feature Selection, Jammisetty Yedukondalu, Lakhan Dev Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive load detection is eminent during the mental assignment of neural activity because it indicates how the brain reacts to stimuli. The level of cognitive load experienced during mental arithmetic tasks can be determined using an electroencephalogram (EEG). The EEG data were collected from publicly available datasets, namely, mental arithmetic task (MAT) and simultaneous task workload (STEW). The first phase comprises decomposing the electroencephalogram (EEG) signal into intrinsic mode functions (IMFs) using circulant singular spectrum analysis (Ci-SSA). In the second phase, entropy-based features were evaluated using IMFs. After that, the extracted features were fed to nature-inspired feature selection algorithms: genetic …

Adaptive Octree Meshes For Simulation Of Extracellular Electrophysiology, Christopher Bc Girard, Dong Song

Engineering Faculty Articles and Research

Objective. The interaction between neural tissues and artificial electrodes is crucial for understanding and advancing neuroscientific research and therapeutic applications. However, accurately modeling this space around the neurons rapidly increases the computational complexity of neural simulations. Approach. This study demonstrates a dynamically adaptive simulation method that greatly accelerates computation by adjusting spatial resolution of the simulation as needed. Use of an octree structure for the mesh, in combination with the admittance method for discretizing conductivity, provides both accurate approximation and ease of modification on-the-fly. Main results. In tests of both local field potential estimation and multi-electrode stimulation, dynamically adapted meshes …

L(D)-Tyrosine-Mediated One-Step Chiral Graphene Production For Chirality-Dependent Sensing, Fnu Pranav, Ali Ashraf, Meena Jaggi, Subhash C. Chauhan, Murali M. Yallapu

Research Symposium

Background: Chirality has been the most iconic phenomenon that occurred in nature. The idea of mirror-image asymmetry associated with the biological entity is still unsolved The emergence of 2D layered nanomaterials which have already shown amazing properties and a wide range of applications, especially in the areas of sensing.Amino acids enantiomers have similar physical and chemical properties however their physiological responses get changed based on the enantiomers. For example, L from amino acids helps body in protein formation, and generation of biological signals etc. whereas the D-form may cause toxic effects. We have developed a novel and facile synthesis method …

Modeling Leaf-Level Transpiration: Exploring The Consequences Of Assumed Saturated Vapor Pressure In Leaves, Danlyn L. Brennan

Dissertations and Theses

Understanding the dynamics of water transport through leaf intercellular airspaces (IAS) and its impact on transpiration is crucial for accurate predictions of plant water use and ecosystem response to changing climates. This study investigates the implications of assuming undersaturation of water vapor in the IAS for transpiration predictions and explores potential modifications to standard modeling approaches.

A dynamic 1D soil-plant-atmosphere continuum using a stomatal optimization model (SPAC-SOT) framework was used to simulate the response of tree species, P. edulis, to prolonged drought and varying environmental conditions. Comparisons between two model assumptions (saturated vs. undersaturated IAS) reveal notable differences in …

Design And Characterization Of 2.4ghz Antennas For Wireless Sensor Applications, Luis Zogby Brennan

Dissertations and Theses

Wireless sensor networks benefit greatly from advances in circuit integration and miniaturization. However, antennas are bound to specific geometries both in terms of fundamental limits and their response to immediate surroundings. As such, various successful techniques for antenna miniaturization must still be carefully tested and characterized as part of the design process of a sensor system. The work presented here fully characterizes a number of miniaturized 2.4GHz antennas and successfully integrates designs into a sensor system using the highly integrated Single Chip Micro Mote (SCµM), which uses a crystal-less radio design resulting in the requirement of only a …

Asymmetric Electrode-Electrolyte Interfaces For High-Performance Rechargeable Lithium-Sulfur Batteries, Jia Chou, Ya-Hui Wang, Wen-Peng Wang, Sen Xin, Yu-Guo Guo

Journal of Electrochemistry

With a high cell-level specific energy and a low cost, lithium-sulfur (Li-S) battery has been intensively studied as one of the most promising candidates for competing the next-generation energy storage campaign. Currently, the practical use of Li-S battery is hindered by the rapidly declined storage performance during battery operation, as caused by irreversible loss of electroactive sulfide species at the cathode, dendrite formation at the anode and parasitic reactions at the electrode-electrolyte interface due to unfavorable cathode-anode crosstalk. In this perspective, we propose to stabilize the Li-S electrochemistry, and improve the storage performance of battery by designing asymmetric electrode-electrolyte interfaces …

Advanced Processing Techniques For Electrospun Nanofibers: Investigating Annealing And Laser Zone-Drawing Effects On Material Characteristics, Matthew D. Flamini

Theses and Dissertations

Electrospun nanofibers hold potential for a wide range of commercial and scientific applications; however, their properties must be optimized through post-processing treatments to achieve optimal performance. This dissertation investigates the effects of annealing and laser zone-drawing on electrospun nanofiber properties. Annealing polycaprolactone nanofibers at 70°C results in the highest rate of crystallization and molecular alignment, impacting long-term stability and mechanical properties. A multivariate linear model incorporating crystallinity and molecular alignment predicts the material properties resulting from annealing under different conditions. Laser zone-drawing experiments reveal that polylactide fiber thinning under laser irradiation primarily occurs due to drawing rather than ablation. Steady-state …

The Wings Program And The Compliance Program, Sarah Nilsson

Publications

No abstract provided.

Hydrophobicity Optimization Of Cathode Catalyst Layer For Proton Exchange Membrane Fuel Cell, Hao-Jie Chen, Mei-Hua Tang, Sheng-Li Chen

Journal of Electrochemistry

Hydrophobicity of the cathode catalyst layers (CCLs) crucially determines the performance of proton exchange membrane fuel cells (PEMFCs) by affecting the transports of oxygen and liquid water. In this regard, polytetrafluoroethylene (PTFE) is usually used as a hydrophobic additive to facilitate the oxygen and water transports in CCLs. So far, there remains lacking systematic effort to optimize the addition methods of PTFE in CCLs and the mechanisms behind. In this work, the effects of the approaches for PTFE addition and the distribution of PTFE on the mass transport of oxygen and the proton conduction in CCLs were studied by using …

Dependence Of Heat Transfer Model On The Structure Of Electrically Coil-Heated Microelectrodes, Ju Li, Sen Yang, Jian-Jun Sun

Journal of Electrochemistry

Electrically heated microelectrodes have gained much attention in electroanalytical chemistry in recent years. It has been shown that the promotion of mass transport and reaction kinetics at high-temperatures often results in increased current signals. However, there is no study about the heat transfer inner the microelectrodes which is necessary for the design and operation for microsensors. This report introduces a finite element software (COMSOL) to analyze the factors that influence the surface temperature (T_s), which is crucial for the heating ability of micro-disk electrodes with coils. Distances between the electrode surface and the bottom of the heated copper …

Teaching To Develop Perspective, Skills, Confidence, And Identity As Problem-Solving Engineers, Russell Kirk Pirlo

Research and Reflection on Learning and Teaching in Higher Education

The “core” of an engineering degree program typically comprises the concepts, equations, and technical skills needed, as well as their practical application to common problems of the profession. This core is then divided into the “content” that must be covered in each course. It is widely recognized, however, that successful individuals do not thrive as professionals on content alone. Thus, there is significant and increasing emphasis across higher education to “educate the whole person.” These efforts aim to develop “deep” qualities like grit, critical thinking, perseverance, learning from failure, valuing diversity, teamwork, leadership, curiosity, recognizing opportunity, creating value, and acting …

Privacy-Preserving Federated Learning, Dumindu Samaraweera

Math Department Colloquium Series

AI's applicability across diverse fields is hindered by data sensitivity, privacy concerns, and limited training data availability. Federated Learning (FL) addresses this challenge by enabling collaborative machine learning while preserving data privacy. FL allows clients to engage in model training with their local data, avoiding centralized storage. However, even with FL, security threats persist, jeopardizing model integrity and client data privacy. In this presentation, we will explore our latest findings in this area of research, safeguarding sensitive data from attacks through techniques like secure multiparty computation, homomorphic encryption, and differential privacy within the FL framework, enhancing data protection, and expanding …

Analysing Child Sexual Abuse Activities In The Dark Web Based On An Efficient Csam Detection Algorithm, Vuong Ngo, Christina Thorpe, Susan Mckeever

Articles

Abstract: Child sexual abuse material (CSAM) activities are prevalent on the Dark Web to evade detection, posing a global challenge for law enforcement. Our objective is to analyze CSAM discussions in this concealed space using a Support Vector Machine model, achieving an accuracy of 87.6%. Across eight forums, approximately 28.4% of posts contained CSAM, with victim ages most commonly reported as 12, 14, 13, and 11 years old for YouTube, Skype, Instagram, and Facebook, respectively. Additionally, in forums discussing boys, the most frequently mentioned nationalities in CSAM posts were English, German, and American, accounting for 12%, 7.8%, and 6% of …

Developing A Smart And Sustainable Public Transportation System: A Case Study In Camden, New Jersey, Zahra Vafakhah

Theses and Dissertations

The transportation sector is a major contributor to air pollution and Greenhouse Gas (GHG) emissions. As a significant source of emissions, public transportation presents an opportunity for mitigation through electrification. However, transitioning to an electric bus fleet necessitates substantial investments in bus procurement and charging infrastructure. To address the associated costs, this study introduces a mixed-integer linear mathematical model developed to optimize the location of on-route fast charging stations within bus networks. The central objective of this optimization formulation is to minimize the overall cost of establishing the charging infrastructure. The study employs a real-world case study focusing on a …