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Journal of Science Education for Students with Disabilities

Publication rights to works is granted to Journal of Science Education for Students with Disabilities, however, full copyright for works published in this journal is retained by the author(s). The author(s) may post their works online in an institutional repository, on their University departmental website, or on their own personal websites.

Memf-Net: A Mega-Ensemble Of Multi-Feature Cnns For Classification Of Breast Histopathological Images, Alaa Hussein Abdulaal, Ali H. Abdulwahhab, Aqeel Majeed Breesam, Zahra Hasan Oleiwi, Riyam Ali Yassin, Morteza Valizadeh, Saja Nafea Mohsin

Iraqi Journal for Computer Science and Mathematics

Pathological anatomical images play a pivotal role in diagnosing diseases, notably breast cancer, which affects women globally. These images, obtained through biopsies or post-mortem examinations, are preserved to maintain their structural integrity. Software tools, like computer-aided diagnosis, aid doctors in early detection and treatment planning, contributing to reduced mortality rates. In this context, convolutional neural networks (CNNs) have emerged as valuable tools for diagnosing benign and malignant breast cancers. This paper introduces a Mega Ensemble Net method, leveraging multi-scale combination features on the breast histopathology dataset. Three fine-tuned deep learning models, namely ResNet-18, ResNet-34, and ResNet-50, are integrated into this …

Retracted: Capsule Network Model For Detecting Spoofing Attack In The Internet Of Medical Things (Iomt), Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Mansour Obeidat, Rami Shehab

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) has transformed healthcare delivery through real-time monitoring and data exchange. However, this integration of smart medical devices has also introduced critical cybersecurity threats, particularly spoofing attacks, which can compromise patient safety and system reliability. Conventional Intrusion Detection Systems (IDS) often fail to address IoMT-specific challenges such as class imbalance, computational constraints, and the need for real-time adaptability. This study proposes a Capsule Network (CapsNet)-based IDS that leverages spatial dependency modeling and hierarchical feature relationships to detect spoofing attacks in IoMT environments. Using the CICIoMT2024 dataset, we implemented a binary classification framework where spoofing instances …

Complexity Study Of Knowledge And Public Observation, Avijeet Ghosh

Doctoral Theses

Automated planning has been a steady branch of research in the field of Artificial Intelligence. A very interesting branch of such planning studies is epistemic planning. Epistemic plans are such plans where the attained goal revolves around knowledge of some intelligent agents. One of the more popular modeling techniques and underlying language to handle knowledge of intelligent agents is provided by dynamic epistemic logic (DEL). It uses Kripke models that have possible states of truth and relations to model knowledge. It also uses a similar technique to model actions or events that update the knowledge state. Since DEL deals with …

September 3, 2025 General Faculty Minutes, University Of South Carolina

Faculty Senate

No abstract provided.

Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz

Chemical Technology, Control and Management

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …

Optimizing Beer Fermentation Through Intelligent Control, Azizbek Nodirbekovich Yusupbekov, Mirjalol Yusupov

Chemical Technology, Control and Management

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

Long-Range Quantum Entanglement In Dielectric Mu-Near-Zero Metamaterials, Olivia Mello, Larissa Vertchenko, Seth Nelson, Adrien Debacq, Durdu Guney, Eric Mazur, Michaël Lobet

Michigan Tech Publications

Entanglement is paramount in quantum information processing. Many quantum systems suffer from spatial decoherence in distances over a wavelength and cannot be sustained over short time periods due to dissipation. However, long range solutions are required for the development of quantum information processing on chip. Photonic reservoirs mediating the interactions between qubits and their environment are suggested. Recent research takes advantage of extended wavelength inside near-zero refractive index media to solve the long-range problem along with less sensitivity on the position of quantum emitters. However, those recent proposals use plasmonic epsilon near-zero waveguides that are intrinsically lossy. Here, we propose …

Moderated Identity Politics: Muslim Voters And Religious Depolarization In North Maluku’S 2024 Gubernatorial Election, Aji Deni, Marno Wance, Muhtar Muhtar

Jurnal Wacana Politik

This study examines religious polarization in North Maluku, proposing moderated identity politics and a hybrid representation model to explain post-conflict electoral behavior. It highlights local leaders who strategically balance identity appeals with cross-group alliances, integrating structural and agential factors to advance electoral theory and offer a replicable model for mitigating identity-based conflict in plural Indonesian regions. Using a mixed-methods sequential explanatory design, quantitative data were first collected from 100 proportionally sampled respondents. Subsequently, in-depth qualitative interviews were conducted with 17 key informants. Data triangulation, comparing survey results with interview findings, ensured consistency and strengthened the validity of the research conclusions. …

Performance Analysis Of Flapping-Foil Energy Harvesters Under Shear-Flow Conditions, Maqusud Alam, Bubryur Kim, Shehnaz Akhtar, Sujeen Song, Zengshun Chen, Jinwoo An

Civil Engineering Faculty Publications

Flapping-foil energy harvesters represent a promising technology for extracting energy from fluid flows, although their performance under shear-flow conditions is poorly understood. To address this research gap, we investigated the impact of power-law shear flow on the performance of flapping-foil energy harvesters. We conducted numerical simulations at different Reynolds numbers (Re = 1000, 50 000, and 500 000) under uniform-flow and shear-flow conditions. Based on the results, shear flow minimally affected the power outputs at Re = 1000 and 50 000, where viscous forces dominate the flow dynamics. However, at Re = 500 000, shear flow significantly reduced the …

Characterizing Problematic Images In Retracted Scientific Articles, João Phillipe Cardenuto, Daniel Moreira, Anderson Rocha

Computer Science: Faculty Publications and Other Works

This cross-sectional study analyzed retracted articles flagged for problematic image manipulation (e.g., image duplication) in the Retraction Watch Database (56,716 entries as of October 4, 2024). We focused on entries containing the term image in the retraction reason (8002 entries) and further refined the dataset to those discussed on PubPeer (2078 after duplicate removal) to gain more detailed insights into the image problems. Data extracted included figure types (eg, microscopy, gel blot), the context of image misuse (eg, within-article, between-article), and the type of manipulation (e.g., duplication, splicing). The study highlights the prevalence of gel blot images and between-article image …

Algorithms For The Synthesis Of Adaptive Control Systems Based On The Speed-Gradient Method, Oxunjon Boborayimov

Chemical Technology, Control and Management

This paper discusses the synthesis algorithms for adaptive control systems based on the speed-gradient method. Adaptive control systems with implicit reference and adjustable models are synthesized using speed-gradient techniques, which reduce the requirements for the main control loop structure and the completeness of measurement data. Stable adaptive decentralized control algorithms are developed for a class of interconnected systems with nonlinear local dynamics and uncertainties, ensuring the stability of individual subsystems and the overall system while accounting for their interactions. To incorporate inter-subsystem interactions into the overall control law, an adaptation algorithm based on the speed-gradient method is introduced. A synthesis …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

Research And Development Of Intelligent Measurement Systems, Odil Abdujalilovich Jumaev, Mahmudov Giyosjon Baqoyevich

Chemical Technology, Control and Management

The article discusses modern methods for developing intelligent measuring systems. Intelligent measuring systems are systems based on intelligent technologies that not only accurately measure physical or chemical quantities, but also have the ability to self-analyze, diagnose and make management decisions. The article comprehensively examines the architecture, components of such systems, the organization of their software and hardware, the relationship of sensors and artificial intelligence algorithms. It also analyzes the practical application and prospects of intelligent measuring systems in such areas as industry, medicine, energy, ecology, transport.

Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov

Chemical Technology, Control and Management

This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …

Algorithms For Assessing Soil Salinity Levels Based On Remote Sensing Imagery, Bobomurod Mamitjonovich Tojiboev

Chemical Technology, Control and Management

This article investigates methods for assessing soil salinity levels based on satellite (remote sensing) imagery and their calculation algorithms. Determining the degree of salinity plays a crucial role in the rational use of land resources and increasing agricultural efficiency. The study analyzes indices for determining soil salt content using remote sensing technologies, particularly multispectral images obtained from satellite systems such as Landsat and Sentinel (for example, SI - Salinity Index, NDVI - Normalized Difference Vegetation Index, and others). Furthermore, algorithms are developed based on these indices that enable automatic determination of salinity assessments. Artificial intelligence, machine learning, and geographic information …

Synthesis Of A Control System For Thermal Energy Facilities Using The Quantum Photon Spin Method, Isomiddin Siddikov, N.S Yakubova

Chemical Technology, Control and Management

Increasing energy efficiency and reducing fuel consumption in the process of generating electricity and heat at thermal power plants is one of the urgent tasks. Such systems operate under conditions of random changes in external and internal influences, as well as measurement uncertainties, which reduce the quality of control. In order to overcome this problem, it was proposed to develop an intelligent control system using the quantum photon-spin method to control technological units of thermal power plants. In the proposed approach, a multi-dimensional heating boiler device was taken as a control object, and the simulation modeling of the control system …

Multimodel And Multidiagnostic Ensemble-Based Deep Convective Area Forecast For Aviation Operations Using The Global Unified Model And Korean Integrated Model, Yi-June Park, Jung-Hoon Kim, Dan-Bi Lee, Hyun-Joo Choi, Soo-Hyun Kim, Matthias Steiner, Seung Hee Kim

Institute for ECHO Articles and Research

To provide safe and efficient guidance for aircraft operation to avoid deep convective areas (DCAs) in Korea and broader East Asia, we developed a multimodel and multidiagnostic ensemble (MMDE)-based forecast system. This system utilizes two global numerical weather prediction (NWP) models based on the Unified Model (UM) and the Korean Integrated Model (KIM) operated by the Korea Meteorological Administration. To predict hazardous weather conditions, we defined DCAs using ground-based radar mosaic data where the 15-dBZ echo-top height exceeds flight level (FL) 250 (about z = 6.5 km) and FL350 (about z = 9 km). For predictors, we employed a …

Re: Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan (Fsp): Bres No. 120 – Bonanza Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Classifying Compact Radio Emission In Nearby Galaxies: A 10 Ghz Study Of Active Galactic Nuclei, Supernovae, Anomalous Microwave Emission, And Star-Forming Regions, Kristen C. Dage, Eric W. Koch, Evangelia Tremou, Kwangmin Oh, Susmita Sett, Cosima Eibensteiner, Sean T. Linden, Angiraben D. Mahida, Eric J. Murphy, Liliana E. Rivera Sandoval

Physics & Astronomy Faculty Publications

We present 115 compact radio point sources in three galaxies, NGC 5474, NGC 4631, and M51, taken in the most extended (A-)configuration of the Karl G. Jansky Very Large Array at 10 GHz. Several of these compact radio point sources have diffuse counterparts identified in previous multiband studies of resolved radio continuum emission. We find compact counterparts to eight star forming regions, four anomalous microwave emission candidates, and one supernova remnant (SN 2011dh). Nine of the compact radio sources match X-ray counterparts, the majority of which are background galaxies. These AGN are all within the D25 (isophotal diameter) of the …

High-Capacity, Reversible, And Energy-Efficient Water Vapor Sorption By Hierarchical Micro-To-Macroporous Carbon Aerogels From Polybenzoxazine And Polybenzodiazine, Vaibhav A. Edlabadkar, Rushi U. Soni, Stephen Y. Owusu, A. B.M.Shaheen Ud Doulah, Nicholas Leventis, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

Quantitative, reversible water vapor sorption is in rising demand for applications ranging from home appliances to atmospheric water harvesting. However, most sorbents suffer from low water-uptake capacities, nonreusability, and especially high regeneration temperatures. This study addresses this challenge by introducing polybenzoxazine- (PBO) and polybenzodiazine-derived (PBDAZ) carbon aerogels as reversible high-capacity desiccants. PBO and PBDAZ aerogels were prepared from structurally related monomers via HCl-catalyzed ring opening polymerization. Both types of aerogels were first aromatized at 200–240 °C under air or O2 and then were carbonized at 800 °C under Ar. These as-prepared carbon aerogels were further etched at 1000 °C under …

Leslie Combs And His Life In Chaos, Stanley C. Krippner

Journal of Conscious Evolution

The purpose of this contribution is to review what Leslie Combs described as his “Life in Chaos” and our interaction over the years. Beginning with our meeting at the founding of the Society for Chaos Theory in Psychology in 1991, this tribute traces his journey from early educational challenges to his emergence as a pioneering theorist in consciousness studies. It highlights our decades-long collaboration in the study of dreams, creativity, and the evolution of consciousness, celebrating his enduring legacy as both a brilliant psychologist and a cherished friend.

Keywords: Allan Leslie Combs, Stanley Krippner, chaos theory, systems theory, consciousness …

The Road To A Raisin In The Sun: The Hansberry Family Of Floster, Mississippi, And Its Link To Alcorn A&M; College, J. Janice Coleman

Journal of Mississippi History

No abstract provided.

Retracted: Automated Diagnosis Of Orthopedic Patients With Vertebral Column Disorders Using Advanced Mathematical Modeling, Chen Feng, Zhenhua Sun, Xinheng Dai, Hongli Wen

Iraqi Journal for Computer Science and Mathematics

Orthopedic disorders are multifactorial, making accurate diagnosis a significant challenge. This study introduces a novel method for classifying patients into three categories—normal, disc herniation, and spondylolisthesis—using biomechanical parameters derived from diagnostic datasets. To enhance classification accuracy, two meta-heuristic optimization algorithms—the Zebra Optimization Algorithm (ZOA) and Chaos Game Optimization (CGO)—are integrated with Adaptive Boosting (ADAC) and Light Gradient Boosting Machine (LGBM) classifiers. The experimental results reveal that ZOA significantly improves model performance, particularly in the ADAC classifier. The baseline ADAC model achieved a mean accuracy of 0.916, which increased to 0.952 after optimization with ZOA (referred to as the ADZO model). …

Deep Learning And Texture Analysis For Lung And Colon Cancer Predicting, Mohamed M. Neamah, Laith A. Al-Ani, Loay E. George

Iraqi Journal for Computer Science and Mathematics

Cancer remains a major cause of death worldwide, with lung and colon (LC) cancers presenting significant challenges to healthcare systems due to their high rates of occurrence and mortality. Early and precise diagnosis is essential for better patient outcomes. This research utilizes recent advances in deep learning (DL) and texture analysis (TA) to create a reliable predictive model for detecting LC cancer through histopathological images (HPI). A hybrid method is proposed that combines a gray-level co-occurrence matrix (GLCM) for extracting texture features with an adaptive modified EfficientNet B2 model (AM-EfficientNet B2) for deep feature extraction. These features are used to …

Retracted: Software Engineering-Oriented Text Generation And Analysis Using Gpt-2, Nadia Mahmood Hussien, Aumama Mohammed Farhan, Yasmin Makki Mohialden, Qabas Abdal Zahraa Jabbar, Shahbaa Mohammed Abdulmaged, Asmaa Hatem Arif

Iraqi Journal for Computer Science and Mathematics

The research focuses on developing an improved system for generating and analyzing text by combining GPT-2, LSTM, and CNN models to address challenges in automated content creation for software engineering tasks. The system targets specific applications such as requirements engineering, software documentation, and code comment generation. It generates 150-token text samples based on over 100 user-provided prompts. These generated texts are first processed through an LSTM layer to capture semantic meaning, then passed through a CNN module to extract syntactic and semantic features. All outputs are stored in structured CSV files to support future analysis. Evaluation results demonstrate positive impacts …

Application Of Active Fault-Tolerant Control With Hardware Redundancy In Variable Frequency Drives Of Ac Induction Motors, Zuhair A. Alqarni

Yanbu Journal of Engineering and Science

Fault-tolerant control (FTC) techniques have the potential to significantly enhance the dependability of voltage source inverters (VSI) and are becoming popular. This study presents an innovative fault tolerance approach for designing a very dependable induction motor drive (IMD) that incorporates both analytical (active) and hardware redundancies. The created model aims to enhance fault tolerance against the current sensor, speed sensor, and IGBT switch failures in the inverter module. The Active Fault Tolerant Control System (AFTCS) has been applied to the speed sensor to detect any faults in the sensor. If a fault is detected, the system will replace the defective …

Phenotypic And Genetic Associations Between Cardiovascular Disease Subtypes And Alzheimer's Disease, Aili Toyli, Chen Zhao, Kuan-Jui Su, Hui Shen, Hong-Wen Deng, Qing-Hui Chen, Qiuying Sha, Weihua Zhou

Michigan Tech Publications

BACKGROUND: Cardiovascular disease (CVD) and Alzheimer's disease (AD) are major public health concerns that share overlapping risk factors and potential mechanistic pathways. While vascular contributions to cognitive decline are well-documented, the specific relationships between AD and different CVD subtypes remain poorly understood. METHODS: We examined associations between AD and 11 CVD subtypes using logistic regression models in two large biobanks: the UK Biobank (n = 502,133) and the All of Us Research Program (n = 287,011). Models were adjusted for demographic, lifestyle, and clinical covariates. We also explored genetic overlap between AD and CVD traits through colocalization of significant single …

Che 489-001: Process Dynamics And Control, Sagnik Basuray

Chemical and Materials Engineering Syllabi

No abstract provided.

Phen 603-101: Pharmaceutical Processing And Manufacturing, Piero Armenante

Chemical and Materials Engineering Syllabi

No abstract provided.