Physical Sciences and Mathematics Commons^™

Chm110 Principles Of Chemistry Lecture Slides, Leah S. Cohen

Open Educational Resources

These modified slides contain information from the first ten chapters from the General, Organic, and Biochemistry: connecting Chemistry to Your Life textbook by Blei & Odian.

Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, the rapid growth of the Internet of Things (IoT) has raised concerns about the security and reliability of IoT systems. Anomaly detection is vital for recognizing potential risks and ensuring the optimal functionality of IoT networks. However, traditional anomaly detection methods often lack transparency and interpretability, hindering the understanding of their decisions. As a solution, Explainable Artificial Intelligence (XAI) techniques have emerged to provide human-understandable explanations for the decisions made by anomaly detection models. In this study, we present a comprehensive survey of XAI-based anomaly detection methods for IoT. We review and analyze various XAI techniques, including …

Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek

Turkish Journal of Electrical Engineering and Computer Sciences

This survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English …

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 …

Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …

05.20.2024 Orsp Connect, Liz Williamson

ORED Newsletter

NIH RPPR Update (Research Performance Progress Report)

A Computational Framework For Consciousness: Integrating Quantum Mechanics And Integrated Information Theory, Allie Ellis

Undergraduate Honors Theses

Integrated Information Theory (IIT) provides a rigorous mathematical framework for consciousness, defining it by a system’s intrinsic causal power, quantified by the integrated information (Φ). A central obstacle to testing IIT is the prohibitive computational complexity of calculating Φ, which scales exponentially with system size. This work investigates whether efficient computational techniques from quantum information theory, specifically tensor network contractions, can be adapted to approximate key structural properties of IIT without directly computing the full Φ. We developed a classical model of 8-node networks with binary states, characterized by their Transition Probability Matrices (TPMs). For these systems, we constructed corresponding …

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 …

Generalizing Parkinson’S Disease Detection Using Keystroke Dynamics: A Self-Supervised Approach, Luca Giancardo

Faculty, Staff and Student Publications

Objective: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability.

Materials and methods: We propose a new type of self-supervised loss combining Barlow Twins loss, which attempts to create similar feature representations with reduced …

Employing Digital Pcr For Enhanced Detection Of Perinatal Toxoplasma Gondii Infection: A Cross-Sectional Surveillance And Maternal-Infant Outcomes Study In El Salvador, Mary K. Lynn, Marvin Stanley Rodriguez Aquino, Pamela Michelle Cornejo Rivas, Xiomara Miranda, David F. Torres-Romero, Hanson Cowan, Madeleine M. Meyer, Willber D. Castro-Godoy, Mufaro Kanyangarara Ph.D., Stella Coker Watson Self Ph.D., Ms, Berry A. Campbell, Melissa Nolan Ph.D., Mph

Faculty Publications

Toxoplasma gondii is a parasitic infection that can be transmitted in utero, resulting in fetal chorioretinitis and other long-term neurological outcomes. If diagnosed early, pregnancy-safe chemotherapeutics can prevent vertical transmission. Unfortunately, diagnosis of acute, primary infection among pregnant women remains neglected, particularly in low-and-middle-income countries. Clinically actionable diagnosis is complex due to the commonality of infection during childhood and early adulthood which spawn long-last antibody titers and historically unreliable direct molecular diagnostics. The current study employed a cross-sectional T. gondii perinatal surveillance study using digital PCR, a next generation molecular diagnostic platform, and a maternal-fetal outcomes survey to ascertain …

Perspective—Surface-Display Techniques In Electrochemical Biosensor Designs For Health Monitoring, Courtney J. Weber, Megan D. Whisonant, Olivia M. Clay, Olja Simoska

Faculty Publications

Enzymatic and microbial electrochemical biosensors integrate enzymes and microorganisms as biological recognition elements into the sensor design and functionality. Enzyme-based sensors offer high sensitivity and selectivity for target analyte detection. However, these have limited stability necessary for continuous analyte monitoring. Contrarily, microbe-based electrochemical sensors provide a means for continuous analyte sensing but are associated with challenges related to analyte selectivity in complex samples. To address these limitations, surface-display methods, which bind enzymes to microbial surfaces, enhance biosensor selectivity and sensitivity. This perspective outlines the application of surface-display techniques, offering a promising avenue for health monitoring.

Brain Science And Brain-Inspired Intelligence In Intelligent Era, Xu Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

With intelligence technology as the core technology and intelligent computing power as the productive force, the intelligent era has once again pushed brain science to the forefront of world science and technology. Brain science is the science that studies the nature and rule of cognition and intelligence of human, animal, and machine. A comprehensive analysis of the structure and functional connection rule of the nervous system will eventually draw the functional connectivity map of the brain. In the past decade, neuroscience research has been committed to systematically analyzing the types of neurons and neural structural connections of the nervous system, …

Some Reflections On Developing Trend Of Gravimetry In China, Heping Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

With the development of modern science and technology, gravimetry is growing vigorously and is increasingly becoming an interdisciplinary subject that is closely related to many others such as geology, fundamental physics, geodynamics, hydrology, oceanography, and astronomy. It is now a key subject in giving service to demands in national strategy and fundamental researches in geoscience such as fiducial surveying and mapping, resource exploration, military security, and hazard monitoring. Therefore, owning the core gravimetric techniques is one of the pivots which reflect national core competitiveness. This study first briefly overviews the history and actuality of the growth of gravimetry subject in …

Technology Innovation Is The Key To Future Space Science Missions, Ji Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Space science is one of the important space activities of China together with space technology and space application. Although it is a space program aimed at scientific discovery and breakthrough, with the development of technology and the increasing number of achievements received in the past, space science missions require more and more technological innovation to achieve their goals. This study first reviews the development trend of space science missions since their birth, then analyzes the cultivation process of space science mission proposals with technological innovation and the responsibilities of the chief scientist leading such tasks, and finally analyzes and proposes …

Promoting Ecosystem Based Marine Management Through A Marine Ecological Classification And Zoning System, Wenhai Lu, Xiao Li, Meng Cui

Bulletin of Chinese Academy of Sciences (Chinese Version)

Ecosystem based ocean management is an important means of building marine ecological civilization. The current marine ecological classification and zoning in China comprehensively sorts out the types and natural geographical characteristics of marine ecosystems, divided the Chinese seas and adjacent waters into several levels of ecological spatial units according to different scales, effectively characterizes the geographical distribution features of marine biological communities and their habitats, and provides effective support for ecosystem based marine management. This study analyzed the practical significance of marine ecological classification and zoning. Based on a review of the development of marine ecological classification and zoning, this …

Winning Battle For Key And Core Technologies In Emerging Fields—Inspiration Based On 863 Program Related Projects, Guangzu Bai, Li Li, Hongfei Meng, Qiang Wang, Xiaoyang Cao, Anrong Liu, Bo Cheng, Mimi Zhan, Jing Li, Leiei Cui, Xiangwan Du

Bulletin of Chinese Academy of Sciences (Chinese Version)

Emerging technology fields have become the main battleground for strategic competition among major powers today, with key and core technologies serving as crucial approach in shaping a nation’s international competitive advantage. This study, from the perspective of national strategy, profoundly understands the significant importance of winning the key and core technology battle in emerging fields. Based on this understanding, it starts with a comparison between the implementation background of the 863 Program and the current reality. It systematically summarizes valuable experiences from projects aimed at advancing key and core technologies in emerging fields, and puts forward reflections and suggestions for …

Analysing An Imbalanced Stroke Prediction Dataset Using Machine Learning Techniques, Viswapriya Subramaniyam Elangovan, Rajeswari Devarajan, Osamah I. Khalaf, Mhd Saeed Sharif, Wael Elmedany

Karbala International Journal of Modern Science

A stroke is a medical condition characterized by the rupture of blood vessels within the brain which can lead to brain damage. various symptoms may be exhibited when the brain's supply of blood and essential nutrients is disrupted. To forecast the possibility of brain stroke occurring at an early stage using Machine Learning and Deep Learning is the main objective of this study. Timely detection of the various warning signs of a stroke can significantly reduce its severity. This paper performed a comprehensive analysis of features to enhance stroke prediction effectiveness. A reliable dataset for stroke prediction is taken from …

Potential Enhancement Of Microbial Disinfection Using Oxygen Enriched Cold Atmospheric-Pressure Argon (Ar/O2) Plasma Jet, Waleed O. Younis, Mahmoud M. Berekaa, Mostafa A. Ellbban, Abdel-Sattar S. Gadallah, Jamal Q. Almarashi, Abdel-Aleam H. Mohamed

Karbala International Journal of Modern Science

Oxygen activated cold-atmospheric-pressure-argon plasma jet (APPJ) has gained prominence over the regular argon plasma especially in disinfection and decontamination. As an objective of the current research, an oxygen-enriched argon system was built, where plasma produced through a vessel metallic tube that is introduced into alumina one. A sinusoidal high voltage signal of 25 kHz was used to generate plasma jet. Potential impact of oxygen enriched APP jet (Ar/O₂) in decontamination of different microbial cells was observed. For examination, suspension of each tested microbe was placed in contact with plasma jet nearly 10 mm away from the jet nozzle …

A Potential Of Watercress Nasturtium Officinale Bioactive Compounds In Inhibiting Infectious Myonecrosis Virus (Imnv) By Targeting Rna-Dependent Rna Polymerase (Rdrp) Virus From Several Countries: In Silico Approach, Qurrota A’Yunin, Fatchiyah Fatchiyah, Maftuch Maftuch, Feri Eko Hermanto, Muhammad Hermawan Widyananda, Narendra Santika Hartana, Muhaimin Rifa’I, Yoga Dwi Jatmiko

Karbala International Journal of Modern Science

Infectious myonecrosis virus (IMNV) disease causes mass mortality and decreased shrimp production. The RdRp region projects to the interior, where it may function in transcription. The focus of this study was to determine the effect of amino acid polymorphisms from several countries on the structure of RdRp and identify the potential of watercress in inhibiting IMNV by targeting the RdRp protein of IMNV through an in silico approach. The results showed that the structure of the IMNV RdRp protein from Indonesia was similar to Mexico, and the protein structure from India_QDN was identical to India_QIL. Ligand binding affinity values showed …

Extraction Of Morphometric Features The Shape Of Mangrove Leaves Based On Digital Images And Classification Using The Support Vector Machine, Ishak Ariawan, Della Ayu Lestari, Luthfi Anzani, Tri Yanti, Cakra Rahardjo, M. Saleh, Sahril Angga Permana, Dea Aisyah Rusmawati

Karbala International Journal of Modern Science

At present, several botanists still rely on the use of manual estimating methods to assess the carbon content in mangrove. However, these methods have been reported to be extremely time-consuming, showing the need to develop a system for prediction. An effective solution lies in the creation of an artificial intelligence application, which can provide rapid and cost-effective results. In constructing this application, careful consideration must be given to the selection of parameters or attributes. Species is an essential parameter for the assessment of carbon content, but its determination has proven to be challenging due to the similarities of mangrove. The …

Ethylene-Forming Enzyme Kinetics And Ethylene Biosynthesis For Commercial And Medical Use, Amala Clawson

Undergraduate Theses and Capstone Projects

Ethylene is the organic compound that serves as the raw material for polyethylene and other chemical polymers used in the manufacturing of plastic products. Traditional methods used to obtain ethylene are associated with significant carbon emissions that are harmful to the environment. Despite these negative environmental impacts, the utility of ethylene in commercial and medical industries has led researchers to investigate potential pathways for ethylene biosynthesis in recent decades. Previous studies have identified an ethylene-forming enzyme (EFE) that is involved in ethylene biosynthesis in many microorganisms. Researchers have explored biochemical properties of EFE and strategies for maximizing enzyme expression and …

Pod-Ifying Mass Media: An Exploration Of Journalistic Integrity In Podcasting, Sam Graham

Undergraduate Theses and Capstone Projects

Podcasting is a rapidly growing form of media that has expanded into nearly every genre of consumption from news to comedy to sports. It operates similarly to on-demand television or television streaming, though its reach has the potential to be much greater due to its on-demand structure. In past studies, audio has been found to be one of the most effective mediums of communication. As a result, it is my belief that the medium has the ability to shape the perceptions of large groups of people, and specific niches, leading them to opinions that are at times inaccurate, misguided, or …

Recognizing Traps And Frightening Wolves: Foxes And Lions As A Representative Of Machiavellian Political Ideology In Shakespeare’S Comedies, Grace Powell

Undergraduate Theses and Capstone Projects

While William Shakespeare’s plays and sonnets have been the subject of literary discourse for centuries, one topic that has been less traversed is the connection between his Comedies and Niccolò Machiavelli’s political ideologies. This project will explore references of lions and foxes in Shakespeare’s Comedies and the leaders and monarchs within them to determine how beliefs about Machiavelli’s political ideology influenced Shakespeare’s literature and became symbols for leadership and power. This will be important for gaining historical context on Machiavellian political discourse and how it was represented in the contemporary dramatic literature of William Shakespeare. I closely examined Shakespeare’s Comedies …

Evaluating The Impact Of Wildfires On Mixed Conifer Forest Regeneration And The Effectiveness Of Usfs Management Strategies On Restoring Ecosystem Services, Wyatt Farino

Master's Projects and Capstones

Wildfires are increasing in frequency, duration, and severity across Western North America. 20,438,720 acres (20.1%) of California has burned at least once since 2010. Projections suggest a statewide increase in burned area between 36% and 74% by 2085, with some forested areas in Northern California exceeding 100% in all modeled scenarios. Fire regimes have deviated far from their historical norm, significantly increasing the risk of type conversion from forest to other ecosystems. Californians rely on the myriad of ecosystem services produced by these forests to meet their basic needs. Access to these fundamental services will be severely reduced if appropriate …

Assessing The Use Of Regenerative Agriculture In California Almonds As Climate Change Resilience, Skyler M. Seamons

Master's Projects and Capstones

The agriculture sector is responsible for 10% of the United States’ greenhouse gas emissions. In turn, anthropogenic climate change threatens crops. With its Mediterranean climate, California is the country’s largest agricultural-producing state. Many California crops are at risk due to increasing temperatures and changed precipitation patterns. This paper investigates regenerative farming techniques as a tool to protect California crops from a changing climate. Almonds are used as a case study to analyze the soil management practices, finances, and policies underlying regenerative agriculture in California. A literature review and comparative analysis are used to compare regenerative and conventional soil management practices …

An Inventory Of Tidal Marsh Restoration Opportunities In Humboldt Bay And Their Impact On Greenhouse Gas Emissions, Nicholas Rowlands

Master's Projects and Capstones

Blue carbon ecosystems like tidal marshes, mangroves, and seagrass are efficient carbon sinks that release minimal methane under saline conditions. However, coastal wetlands globally are under threat, and on the U.S. West Coast some 85% of historic tidal wetlands have been lost. As such, there is increasing interest in their restoration as a necessary climate mitigation strategy. This GIS analysis identifies potential tidal marsh restoration sites in Humboldt Bay, California, and estimates the post-restoration greenhouse gas benefits. An elevation-based model of Humboldt Bay’s full estuary extent developed by West Coast researchers was combined with data from the California Aquatic Resources …

U.S. International Climate Finance: An Analysis Of Historical Shortfalls And A Proposal For More Equitable Distribution, Maria-Cristina Kealey

Master's Projects and Capstones

Least-developed countries experienced 69% of deaths from climate disasters over the past 50 years despite comprising only 13% of the world’s population. Low-income and climate vulnerable nations around the world are suffering disproportionately as wealthy, high-emitting countries, such as the U.S., profit from the climate crisis. This research provides a comprehensive overview of past U.S. contributions to international climate finance efforts, assesses the climate finance deficit globally and specifically for developing countries, and proposes a more equitable share of U.S. funding from a quantitative and restorative climate justice approach. The primary analyses included quantifying the U.S. share of global greenhouse …