Engineering Commons^™

Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan

Turkish Journal of Electrical Engineering and Computer Sciences

Learning a robust and invariant representation of various unwanted factors in sign language recognition (SLR) applications is essential. One of the factors that might degrade the sign recognition performance is the lack of signer diversity in the training datasets, causing a dependence on the singer’s identity during representation learning. Consequently, capturing signer-specific features hinders the generalizability of SLR systems. This study proposes a feature disentanglement framework comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network based on adversarial training to learn a signer-independent sign language representation that might enhance the recognition of signs. We aim to …

Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou

Turkish Journal of Electrical Engineering and Computer Sciences

Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node …

Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning (DL) models have performed tremendously well in image classification. This good performance can be attributed to the availability of massive data in most domains. However, some domains are known to have few datasets, especially the health sector. This makes it difficult to develop domain-specific high-performing DL algorithms for these fields. The field of health is critical and requires accurate detection of diseases. In the United States Gastrointestinal diseases are prevalent and affect 60 to 70 million people. Ulcerative colitis, polyps, and esophagitis are some gastrointestinal diseases. Colorectal polyps is the third most diagnosed malignancy in the world. This …

Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel control framework for the collaboration of an aerial robot and a ground vehicle that is connected via a taut tether is proposed. The framework is based on a leader-follower paradigm. The leader follows a desired trajectory while the motion of the follower is controlled by an admittance controller using an extended state observer to estimate the tether force. Additionally, a velocity estimator is also incorporated to accurately assess the leader’s velocity. An essential feature of our system is its adaptability, enabling role switching between the robots when needed. Furthermore, the synchronization performance of the robots …

Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, vision systems have become essential in the development of advanced driver assistance systems or autonomous vehicles. Although deep learning methods have been the center of focus in recent years to develop fast and reliable obstacle detection solutions, they face difficulties in complex and unknown environments where objects of varying types and shapes are present. In this study, a novel non-AI approach is presented for finding the ground-line and detecting the obstacles in roads using v-disparity data. The main motivation behind the study is that the ground-line estimation errors cause greater deviations at the output. Hence, a novel …

Flexible Biosensors For Food Pathogen Detection, Sonatan Biswas, Md Shariful Islam, Fei Jia, Yunteng Cao, Yanbin Li, Changyong Cao

Biological and Agricultural Engineering Faculty Publications and Presentations

Food contamination poses a significant threat to public health, the economy, and human health worldwide, occurring at any stage of the food supply chain, from farm to fork. Efficient and effective real-time monitoring methods for the early identification and rapid detection of pathogen contamination are critical to preventing possible food safety issues. In the past decade, flexible electrochemical biosensors have rapidly expanded in the detection of foodborne pathogens, owing to their ability to function well at biological interfaces that may be soft, intrinsically curvy, irregular, or deformable. The most important features of flexible sensors are their flexibility, multifunctionality, low cost, …

Adsorption-Type Aluminium-Based Direct Lithium Extraction: The Effect Of Heat, Salinity And Lithium Content, Yasaman Boroumand, Amir Razmjou

Research outputs 2022 to 2026

Conventional lithium production through solar evaporation is considered a time-consuming procedure, taking a substantial 12 to 18 months with significant environmental impacts such as aquifer depletion and damaging the basin's complex hydrological system. Direct Lithium Extraction (DLE) has emerged as a promising alternative for lithium extraction from brines, offering reduced environmental impact. Although adsorption-type DLE with aluminium-based adsorbents is the sole commercial technology of DLE, a debate persists concerning its Technology Readiness Level (TRL), which challenges the prevailing notion that adsorption-type DLE undeniably reaches a TRL of 9. Within this narrative, we propose that adsorption is capable of attaining its …

An Integrated Resource Planning Proposal For Tucson Electric Power, Valeria Bernal

Master's Projects and Capstones

An integrated resource plan (IRP) is crucial for utilities to determine the most cost-efficient energy resources while considering system reliability, environmental impact, and regulatory requirements. VitalsparK developed an IRP for Tucson Electric Power (TEP) to transition its current 70% thermal and 30% renewable energy portfolio, emitting 740 grams of CO2 per kWh, toward carbon neutrality by 2050. The proposed plan involves retiring existing infrastructure, adding 8 GW of renewable and storage capacity, and incorporating 2.5 GW of net-zero natural gas power plants. VitalsparK presented two scenarios: the Reference (REF) Case, which focuses on the least-cost portfolio to meet demand through …

Extreme Image Transformations Improve Latent Representations In Machines, Girik Malik, Ennio Mingolla

MODVIS Workshop

Shuffling pixels in an image helps machines to learn a more robust object representation. To probe the strategies used by humans and machines for object recognition, we introduce Extreme Image Transformations (EITs). Machines rely heavily on exploiting low-level features like color and texture, so their performance degrades on out-of-distribution and adversarial inputs. Humans depend on high-level features like shapes and contours, making them relatively robust to image distortions. EITs systematically shuffle the pixels in an image, parameterized by the size of grids, probability of shuffle and binary block movement, distorting the structure of objects at both local and global levels. …

The Academic System Influence On Instructional Change: A Conceptual Systems Dynamics Model Of Faculty Motivation To Adopt Research-Based Instructional Strategies (Rbis), Juan M. Cruz Bohorquez, Stephanie G. Adams, Flor Angela Bravo

Henry M. Rowan College of Engineering Departmental Research

Many universities have implemented initiatives to drive instructional change, yet their success has often been limited due to a lack of recognition of academia as a complex dynamic system. This paper explores how the interconnected and dynamic nature of academic systems influences faculty motivation to adopt instructional innovations, such as project-based learning (PBL) and small group collaborations (SGCs). We present a Conceptual Systems Dynamics Model (CSDM) that illustrates these interconnections, demonstrating how systemic factors create feedback loops that either reinforce or hinder faculty motivation, as well as other related factors. These loops, represented as Causal Loop Diagrams (CLDs), were derived …

Can Smart Supply Chain Bring Agility And Resilience For Enhanced Sustainable Business Performance?, Mahak Sharma, Rose Antony, Ashu Sharma, Tugrul Daim

Engineering and Technology Management Faculty Publications and Presentations

Purpose

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

Design/methodology/approach

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices …

Learning Proximal Operators With Gaussian Process And Adaptive Quantization In Distributed Optimization, Aldo Duarte Vera Tudela

LSU Doctoral Dissertations

In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a further decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Integrating Gaussian processes (GP) as a learning component to the Alternating Direction Method of Multipliers (ADMM) has proven effective in learning each agent's local proximal operator to …

Residential Ders In Service-Oriented Load Participation: Enhancing Grid Flexibility, Zhongkai Zeng

Dissertations and Theses

Amidst concerns about power consumption during peak periods and potential grid instability, the role of Distributed Energy Resource (DER) aggregation comes into consideration. Smart electric water heaters with remote capabilities and energy storage offer load reduction capabilities that can help maintain grid stability and manage residential energy consumption. DERs address challenges posed by stochastic renewable energy generation and fossil fuel power plant emissions, playing a contributing role in load shifting and enhancing grid flexibility by participating in energy management programs.

However, high unenrollment rates in demand response programs, notably programs that use direct load control, persist due to customer dissatisfaction. …

Facilitation In Pattern Motion Perception Of Self-Operated Stimuli Explained By Adaptive Contrast Normalization, Fulvio Missoni, Francesca Peveri, Andrea Canessa, Giulia Sedda, Vittorio Sanguineti, Silvio P. Sabatini

MODVIS Workshop

Movement can affect the way we make sense of complex visual information. To investigate this issue, we designed an experiment to assess changes of plaid motion perception threshold after a period of sensorimotor contingency experience. We found that movement training facilitates combination of elementary motion cues into a global motion percept. No changes in perceptual thresholds are observed in a passive visual condition. A Bayesian model suggested a reduction, after training, of the cross-talk between two gratings with unbalanced contrasts in corresponding sensory channels. To test plausible neural mechanisms for active reduction of cross-talk in cortical representation of complex visual …

Redeveloping System Noise Temperature Test Capabilities For Dss-17 Using The Moon As A Noise Source, Emily R. Walter

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Engineering at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Emily R. Walter on May 16, 2024.

Band Gap Tuning Of Perovskite Solar Cells For Enhancing The Efficiency And Stability: Issues And Prospects, Md Helal Miah, Mayeen Uddin Khandaker, Md Bulu Rahman, Mohammad Nur-E-Alam, Mohammad Aminul Islam

Research outputs 2022 to 2026

The intriguing optoelectronic properties, diverse applications, and facile fabrication techniques of perovskite materials have garnered substantial research interest worldwide. Their outstanding performance in solar cell applications and excellent efficiency at the lab scale have already been proven. However, owing to their low stability, the widespread manufacturing of perovskite solar cells (PSCs) for commercialization is still far off. Several instability factors of PSCs, including the intrinsic and extrinsic instability of perovskite materials, have already been identified, and a variety of approaches have been adopted to improve the material quality, stability, and efficiency of PSCs. In this review, we have comprehensively presented …

Design Of An Integrated System For The Protection Of Patient Health Information In Medical Images, Manikandan V

Theses and Dissertations

Electronic clinical data such as Patient Health Information (PHI) is stored by adapting the Digital Imaging and Communications in Medicine (DICOM) standard to build an integrated healthcare system where medical images from various sources can be interlinked. The healthcare industry poses a threat from hackers, and the information fetched by hackers provides more money than the other information stolen. This thesis deals with designing and analysing encryption algorithms, key generation mechanisms, and information-hiding schemes for protecting PHI.

Sensitive multimedia information of all forms is encrypted, with a key, before storage and transmission to protect it from illegal use and manipulation …

Investigating Small Drinking Water System Technical Capacity To Treat For Pfas, Chloe J. Yoder, Kaycie Lane

Department of Civil and Environmental Engineering: Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) presents technical challenges in small systems where advanced drinking water treatment implementation is difficult. Publicly available data were used to examine technical treatment capacity for PFAS in the US, using Nebraska as a pilot. Of 1312 PWSs in Nebraska, 441 have technologies capable of removing PFAS from drinking water. Reverse osmosis was the most common treatment technology in Nebraska with 277 total systems using this technology with, 194 PWSs with RO serving populations of <= 100 people. Fifty-two PWSs had granular activated carbon, 47 had ion exchange and 62 had ultraviolet, with UV being primarily used for disinfection. We found PWSs had different technology deployment methods, several systems had “significant deficiencies” reported in management and operation evaluations, and age and previous water quality violations were not correlated to treatment evaluations. The developed methodology models utilizing publicly available data for contaminants across the US.

Barriers To Mental Health Treatment Among U.S. Army Aviation Personnel, Aric James Raus

Doctoral Dissertations and Projects

Safe and effective Army aviation operations require a clear focus from all involved. Yet, after more than two decades of U.S. combat aviation operations, little is known about the barriers experienced by aviators when considering mental health evaluation and treatment. An extensive literature review found no published studies examining mental health treatment hesitance among Army Aviation personnel or the perceived acceptability of self-help treatment options. This study identifies the relationships between age, gender, and aviation career specialty on the self-disclosed instrumental, attitudinal, and stigma-based barriers to care among U.S. Army aviation personnel. Additionally, the research determines relationships between the population’s …

Modeling Synergistic Effects Of Integrin And Tgf-Beta Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Biology and Medicine Through Mathematics Conference

No abstract provided.

Enhancing Electrical Network Vulnerability Assessment With Machine Learning And Deep Learning Techniques, M Mishkatur Rahman, Ayman Sajjad Akash, Harun Pirim, Chau Le, Trung Le, Om Prakash Yadav

Northeast Journal of Complex Systems (NEJCS)

This research utilizes advanced machine learning techniques to evaluate node vul-
nerability in power grid networks. Utilizing the SciGRID and GridKit datasets, con-
sisting of 479, 16,167 nodes and 765, 20,539 edges respectively, the study employs
K-nearest neighbor and median imputation methods to address missing data. Cen-
trality metrics are integrated into a single comprehensive score for assessing node
criticality, categorizing nodes into four centrality levels informative of vulnerability.
This categorization informs the use of traditional machine learning (including XG-
Boost, SVM, Multilayer Perceptron) and Graph Neural Networks in the analysis.
The study not only benchmarks the capabilities of these …

Explaining The Staircase Gelb Illusion, Simultaneous Contrast, And Perceptual Fading Of Stabilized Images With A Neural Model Driven By Fixational Eye Movements, Michael E. Rudd

MODVIS Workshop

A neural model of lightness computation driven by fixational eye movements is described and used to simulate various lightness phenomenon, including the Staircase Gelb illusion and its variants, simultaneous contrast, the Chevreul illusion, and perceptual fading of stabilized images. The model provides a precise account of the lightness matches from several experiments, with an overall error of only 1.5%. In the model, spatial maps of transient ON and OFF cell activations—produced as the eyes traverse the visual scene—are sorted by eye movement direction in visual cortex. At a subsequent processing stage, the activations within these maps are summed across space …

Effects Of A Wi-Fi Link On The Performance Of A Path Following Autonomous Ground Vehicle, Anthony Iwejuo, Austin Cagle, Billy Kihei, Ph.D.

Symposium of Student Scholars

As vehicles become more automated and connected, the future of safe and efficient travel will be dependent on efficient wireless networks. Artificial intelligence (AI) demands high power resources and computing resources that can be resource-intensive for mobile robotic systems. A new paradigm involving the remote computing of A.I. can enable robotics that are built lighter and more power efficient. In this study, we compare a locally run artificial intelligence algorithm for autonomous ground vehicle navigation against remote computation through various wireless links to highlight the need for low-latency access to remote computing resources over Wi-Fi network calls. Our findings show …

A Robust Decision-Making Model For Medical Supplies Via Selecting Appropriate Unmanned Aerial Vehicle, Amira Salam, Mai Mohamed, Rui Yong, Jun Ye

Neutrosophic Systems with Applications

Recently, Unmanned Aerial Vehicles (UAVs) have been used in many fields, including the field of health care, especially in delivering the necessary medical equipment and supplies, due to the many advantages they have compared to other traditional methods and the presence of different types of UAVs, to improve healthcare and provide it with the medical supplies and equipment necessary to save the lives of patients. Choosing the appropriate UAV for a specific situation represents a problem facing decision-makers, which is considered a multi-criteria decision-making problem. Since the decision-making process is cumbersome and complex, and deals with uncertainty and ambiguity. In …

An Innovative Approach On Yao’S Three-Way Decision Model Using Intuitionistic Fuzzy Sets For Medical Diagnosis, Wajid Ali, Tanzeela Shaheen, Iftikhar Ul Haq, Florentin Smarandache, Hamza Ghazanfar Toor, Faiza Asif

Neutrosophic Systems with Applications

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a …

Dense Video Description Method Based On Multi-Modal Fusion In Transformer Network, Xiang Li, Haifeng Sang

Journal of System Simulation

Abstract: In order to solve the problems that most of the current dense video description models use twostage methods, which have low efficiency, ignore audio and semantic information, and have incomplete description results, a multi-modal and semantic information fusion dense video description method was proposed. An adaptive R(2+1)D network was proposed to extract visual features, a semantic detector was designed to generate semantic information, audio features were added to supplement it, a multi-scale deformable attention module was established, and a parallel prediction head was applied to accelerate the convergence rate and improve the accuracy of the model. The experimental results …

Approach Guardrail Transition Retrofit To Existing Buttresses & Bridge Rails, Scott Rosenbaugh, Robert W. Bielenberg, Chen Fang, Ronald K. Faller, Cody S. Stolle

Nebraska Department of Transportation: Research Reports

The Nebraska Department of Transportation (NDOT) frequently applies roadway overlays to the surface of bridges to extend the bridge’s lifespan. To minimize repair costs, NDOT does not desire to replace or alter any bridge rails with adequate structural capacity and height. Bridge rails installed to NCHRP Report 350 or MASH standards are likely to remain in place, though their effective heights would be reduced by the overlay. This creates a problem of attaching new, 31-in. tall approach guardrail transitions (AGTs) to existing concrete bridge rails and buttressess (after an overlay) that were not designed for such connections and the resulting …

Research On Simulation Model Of Double-Layer Expansion Design Of Expressway, Jiandong Qiu, Yi Tang, Yuxiong Ji, Heng Liu, Junsha Luo

Journal of System Simulation

Abstract: Aiming at the problems that the traditional traffic simulation technology has insufficient evaluation accuracy and little application effect in the three-dimensional composite expansion scenario of expressway, a simulation model construction method for double-layer expansion design of expressway was proposed. The reconstruction and expansion project of Shenzhen Jihe Expressway is selected as the research object, the three simulation model modeling elements, including road network facilities, traffic demand data, and driving behavior model parameters, are sorted out, and the technical process of simulation modeling is proposed. The whole road network including key infrastructure such as interchange, toll station, ramp up and …

A Graph Neural Network Visual Slam Algorithm For Large-Angle View Motion, Jinhui Liu, Mengyuan Chen, Pengpeng Han, Hebao Chen, Yukun Zhang

Journal of System Simulation

Abstract: Aimed at the difficulty of feature point extraction in mobile robots with drastic changes in illumination or sparse texture scenes under large-angle view motion, difficulty in matching features at extreme angles leads to large errors in Epipolar Geometry calculations, a fusion of an improved graph neural network based visual SLAM algorithm (GNN-SLAM) is proposed. The priori location estimation feature extraction network is proposed to achieve fast and uniform detection and description of image feature points by a priori location estimation and to construct real and accurate feature point information. The graph attention mechanism feature matching network is proposed to …

Implementation And Numerical Simulation On Object-Oriented Elastic-Plastic Finite Element Method Based On Python, Henghui Li, Yingxiong Xiao

Journal of System Simulation

Abstract: With the continuous expansion of the application fields of finite element methods, higher requirements are put forward for the scalability of finite element methods. In order to overcome the defects of the traditional finite element methods, a simple and easily extensible object-oriented elasticplastic finite element program framework is proposed based on Python. Combined with the characteristics of Python, we design some finite element classes such as the pre-processing class, the post-processing class, the linear solution class, the stress integration class and the analysis class. By applying the resulting framework to several typical elastic-plastic mechanical problems and comparing the results …