Digital Commons Network^™

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 4 [2025], Número 2 (Issue 2), Cristo Leon, Romano Ponce-Díaz Phd, Ivan Avila Gonzalez Phd, James Lipuma Dr., Bruce G. Bukiet, Ricardo Victoria-Uribe, Nazario Robles-Bastida, Chris Birmingham, Ximena Diaz Santillan, Edgar Francisco Vázquez Martínez He, Jorge Prieto Terrones, Juan Carlos C. González Vidal S, Edgar Meritano, Laura Magela Garcés Ramírez

Journal of Roleplaying Studies and STEAM

En una sesión de juego por medio del registro lingüístico se organiza la escena, se orienta la manera de nombrar las tareas, se distribuyen los roles actanciales, se establecen la expectativas; por lo tanto, se establece una puesta en escena. De tal forma, las prácticas lúdicas y ficcionales se configuran a partir de nuestra mirada del mundo e irremediablemente también reconfiguran esa misma mirada. El ser y el estar en un espacio es la especificidad mediática fundamental de los juegos de rol; dicho de otra manera, en los sistemas de juego de rol dentro de sus universos narrativos, en su …

A Digital Twin Framework For Real-Time Energy Optimization: A Simulated Case Study Of The Podium Office Building, New Cairo, Egypt, Maha Fawzy Aly Anber

Mansoura Engineering Journal

The growing demand for smarter and more energy-efficient buildings has led to increasing interest in digital twin (DT) technology for building operation and management. This paper presents a DT framework developed to improve the energy performance of the Podium Office Building in Cairo Festival City, New Cairo, Egypt. A detailed EnergyPlus model, supported by Python-based tools (eppy and pyEnergyPlus), was used to test three HVAC control strategies: a baseline fixed schedule, a real-time DT-informed strategy, and a predictive optimization approach. By integrating local climate data and realistic occupancy patterns, the study assesses energy savings, CO₂ reductions, and indoor comfort improvements. …

3d-Dnn Ion-Eg Model Applications For Ionospheric Characterization Over Egypt: Mans Cors Case Study Of Vtec Variability And Nmf2/Hmf2 Mapping (2020-2024), Ismail Zaher, Zaki Zeidan, Mostafa Rabah, Mahmoud El-Mewafi

Mansoura Engineering Journal

This study introduces an operational evaluation of a deep learning–driven ionospheric modeling system tailored for Egypt, designed to overcome the limitations of conventional empirical approaches in data-sparse regions. The 3D-DNN Ion-EG model was trained on 737,110 COSMIC-2 radio occultation profiles (2020–2024), integrating spatial temporal coordinates with geophysical drivers to generate high-resolution threedimensional electron density distributions. Validation against the MANS CORS station (Mansoura University) demonstrated strong predictive skill (R2 = 0.9337; r = 0.970) under independent testing. Performance analysis across diverse geophysical regimes confirmed the model’s advantage in capturing storm-time and solar-driven disturbances, surpassing empirical models that perform best only under …

Enhancement Of Punching Shear Strength Capacity Of Interior Slab-Column Connections In Flat Slabs By Using Continuous Stirrups, Heba A. Dahroug, Hamed S. Askar, Mohamed E. El-Zoughiby, Mohamed H. Matthana

Mansoura Engineering Journal

The failure caused by punching shear is considered very dangerous because it happens suddenly. So, many researches have presented various methods to enhance the punching shear capacity by adding shear reinforcement like, vertical shear studs, stirrups or other means. In this study continuous stirrups is used as a shear reinforcement system. An experimental test includes four interior slab-column joints, of normal strength concrete, and an analytical study had been carried out to examine the efficiency of the proposed reinforcement system. The finite element analysis had been carried out by using computer program ABAQUS-V13.0 .The final results showed that, using continuous …

Pressure Field Estimation From 2d-Piv Measurements: A Case Study Of Fish Suction-Feeding, Jensine C. Coggin, Duvall Dickerson-Evans, Erin E. Hackett, Roi Gurka

Physics and Engineering Science

Particle image velocimetry (PIV) flow measurements are common practice in laboratory settings in a wide variety of fields involving fluid dynamics, including biology, physics, engineering, and medicine. Dynamic fluid pressure is a notoriously difficult property to measure non-intrusively, yet its variation is a driving flow force and critical to model correctly. Techniques have been developed to estimate the pressure from velocity and velocity gradient measurements. Here, we highlight a novel application of boundary conditions when applying such pressure estimation techniques based on two-dimensional PIV data; the novel method is especially relevant to problems with complex boundary conditions. As such, it …

Parameter Identification Of A Pi Controller For A Wind Energy Conversion System Based On Dfig, Mariam Hesham, Dina S. M. Osheba, Mahmoud M. Khater

Mansoura Engineering Journal

In this work, three methods are proposed to identify parameters of PI controllers used for wind energy conversion systems based on DFIG. Mathematical model of generator and grid side system is depicted. Three tuning methods; bode-plot, pole-placement, and MATLAB tuner are used for grid side and rotor side converter controllers’ design. Wind turbine system with PI controller parameters obtained using the mentioned method is investigated via MATLAB/SIMULINK under three different scenarios. The wind system is subjected to step wind speed change, random wind speed, and sever symmetrical voltage dip in the grid. The handled comparison illustrates that the pole-placement tuning …

Using Machine Learning To Predict Women At Risk Having A Child With Congenital Heart Defects, Amany M. Abdo Prof., Asmaa M. Mosallam Ms., Laila M. Abdelhamid Assoc.Prof.

Information Systems

Congenital heart defects (CHD) are heart malformations present at birth, affecting heart function and circulation, and are a leading cause of infant mortality. CHD can result from genetic, environmental, and maternal health factors, making early detection essential. Early diagnosis allows for timely intervention, reducing risks like heart failure or stroke. In countries like Egypt, CHD often remains undiagnosed due to limited healthcare resources. Artificial intelligence (AI) can improve early detection by analyzing risk factors. This study presents a predictive model for CHD using maternal and paternal health factors. Data was collected from 571 families: 260 with a CHD-affected child and …

Exploring Math Word Problem Generation With Llms, Trung Hieu Vuong

Master's Theses

Math Word Problem (MWP) is an important building block for learning math. This type of problem is particularly useful for younger audiences because solving it involves two simultaneous skill sets: reading comprehension and mathematical reasoning. With publicly available large language models (LLMs), generating additional MWPs is readily achievable. While researchers have started using LLMs as MWP facilitators, there still exists a gap in studies about the diversity of MWPs generated by unmodified, publicly accessible LLMs. For that reason, our study focused on two goals: (1) to evaluate the diversity of MWPs generated by publicly available LLMs when provided with examples …

Current Trends In Industrial Gas Furnace Control And Monitoring Systems, Utkir Uktam O'Gli Kholmanov

Chemical Technology, Control and Management

This paper presents a critical review of modern control methods applied to industrial gas-fired furnaces. Conventional PID controllers and their advanced modifications, including Advanced Process Control (APC) and cascade control schemes, are analyzed alongside Model Predictive Control (MPC) approaches. In addition, intelligent control algorithms—such as fuzzy logic and neuro-fuzzy systems (Fuzzy, ANFIS)—are examined. The study also considers advanced sensing technologies, including Tunable Diode Laser Absorption Spectroscopy (TDLAS), acoustic pyrometry, and infrared pyrometers, as well as digital twins and CFD-based modeling techniques. Particular attention is given to a comparative evaluation of control strategies based on key performance criteria, including energy efficiency, …

Development And Evaluation Of A Smart Vacuum-Assisted Suspension System For Transtibial Prostheses, Zahraa Kathem Ali, Wajdi Sadik Aboud

Al-Bahir

A prosthetic socket is essential for achieving comfort, gait symmetry, and overall satisfaction for amputees. Effective suspension systems are crucial for securely attaching prostheses, thereby optimizing comfort, functional performance, and long-term limb health. This study aimed to develop and evaluate an intelligent vacuum-assisted suspension system for transtibial prostheses to improve socket fit, gait stability, and reduce residual limb movement. The system integrates force-sensitive resistors (FSRs) and an inertial measurement unit (MPU6050) with accelerometer and gyroscope sensors, continuously monitoring interface pressure and limb motion. Real-time data from these sensors dynamically adjusts vacuum pressure based on the user's gait pattern .Quantitative gait …

Folding Architecture “Origami Art-Inspired” Applicability To Sustainable Architecture- Biomuseo As A Case Study, Vitta A. Ibrahim

Mansoura Engineering Journal

The growing need for sustainable architectural solutions in the contemporary era underscores the necessity for interactive architectural applications that can adapt to changing requirements. In architecture, folding systems refer to three-dimensional, foldable structural forms that create unique spatial configurations and possess a wide range of capabilities. Drawing inspiration from origami techniques, this study emphasizes the role of folding systems in generating innovative spatial designs. The research problem arises from the fact that the built environment is a significant contributor to greenhouse gas emissions and energy consumption, necessitating the implementation of smart solutions. The goal of this study is to identify …

Developing A Vietnamese Text Summarization Large Language Model On Limited Hardware, Tin Pho

Master's Theses

Text summarization models have achieved significant growth during the last few years because of major Large Language Model (LLM) technological advancements. The application of LLMs are widely used in news distribution (TL;DR news), translation tools (DeepL Translate), or virtual assistants (ChatGPT, DeepSeek, Claude, etc.). However, the progress has not yet reached all languages equally. The Vietnamese language is used by more than 90 million people, but the language is not as highly developed for LLM as it has many homophones, five different tones that affect meaning of words, and irregular grammar compared to other languages (e.g. English, Spanish, etc.). Also, …

Supply Chain Network Based On Blockchain And Intelligent Agent, Hiba Hamdi Hassan, Rana Fareed Ghani

Journal of Soft Computing and Computer Applications

In agricultural supply chains, the complexity and indeterminacy pose serious challenges to traceability, reliability and confidence today. This challenge is especially acute in the olive oil industry where adulteration, wrong labeling, and uneven chemical quality threaten the actual well-being of producers and consumers. The project aims to design a blockchain-based hybrid architecture with intelligent agents (FNNs) to enhance transparency, reliability and responsiveness in the olive oil supply chain. The Blockchain component enables a completely open, tamper-proof ledger to be built in a very decentralized way and preserved as an archive of every account of its transactions. The intelligent agents contribute …

Intelligent Extensible Markup Language Encryption Using Type-2 Fuzzy Logic, Faiez Musa Lahmood Alrufaye, Seham Ahmed Hashem

Journal of Soft Computing and Computer Applications

Financial and commercial institutions increasingly rely on Extensible Markup Language (XML) files as a standard means of exchanging data. However, this extensive use has created serious security challenges due to the fact that these files contain sensitive information such as bank card numbers and expiration dates. Relying on traditional full file encryption methods achieves a high degree of security, but it causes problems related to the large file sizes that consume memory and the long encryption and decryption times, which reduces the efficiency of systems when dealing with a large number of daily transactions. Methods based on Type-1 Fuzzy Logic …

Enhanced Generative Convolutional Networks: A Hybrid Algorithm For Refinement Video Classification, Dalal Thair Mahjoub, Hala Bahjat Abdulwahab, Kesra Nermend

Journal of Soft Computing and Computer Applications

Video classification is a vital area of research due to the growing volume of video content in various applications. Accurate category across various resolutions poses challenges, which include adapting to scaling, resizing, and compression. Therefore, this paper introduces an innovative Generative Convolutional Network (GCN) set of rules tailored for multi-resolution video classes. The proposed GCN model utilizes Convolutional Neural Networks (CNNs) combined with generative modeling to enhance the extraction of functions across varying video resolutions, which is crucial for maintaining class robustness in the face of common video adjustments, such as scaling, resizing, and compression. In contrast, traditional fashions frequently …

Review Of Video Steganography By Using Deep Learning Methods: Datasets, Techniques, And Evaluations, Noor Fahem Sahib, Soukaena Hassan Hashem, Ekhlas Falih Naser

Journal of Soft Computing and Computer Applications

The growing prevalence of cyber threats, including fraud and attacks, has intensified the demand for secure methods of safeguarding confidential information exchanged between users. As telecommunications increasingly rely on multimedia data, video steganography has become a prominent technique to address these concerns. By embedding sensitive data within video files, this approach enhances protection against unauthorized access and common internet-based attacks, offering a robust layer of security in an era of escalating digital risks. With the introduction of Deep Learning (DL) steganography methods recently, video steganography can be defined as a rapidly developing subject within information security. This study provides a …

Real-Time Hand Gesture Recognition System For Abductees Rescue Using Deep Learning Techniques, Aws Saood Mohamed, Nidaa Flaih Hassan, Abeer Salim Jamil

Journal of Soft Computing and Computer Applications

Hand gesture recognition is a challenging problem in computer vision, particularly in terms of security surveillance applications. This study presents the first efficient system for abduction-related hand gesture real-time detection based on deep learning. The most critical problem is to detect and recognize hand gestures in real surveillance conditions and to be computationally effective for real-time multi-hand tracking in various lighting situations while allowing reliable surveillance beyond the 1–4 meters limitation. The proposed system consists of three main parts: The adaptive hand tracking algorithm, which has been used to create the Abductees-Rescue dataset. Introduced pose estimation You Only Look Once …

Hate Speech Detection Using Optimized Feature Representation Via Spiral-Grey Wolf Optimizer-Based Machine Learning Approaches, Noor S. Farhan, Matheel E. Abdulmunim, Hasanen S. Abdullah

Journal of Soft Computing and Computer Applications

Hate speech detection is crucial as social media diversifies. This research present a lightweight, scalable system using traditional machine learning methods along with a new approach called Spiral-Grey Wolf Optimizer (S-GWO).

S-GWO effectively selects key features that consider both meaning and content from the Term Frequency Inverse Document Frequency (TF-IDF) space, leading to high-quality representation without excessive computing power.

The propoused system was tested on Arabic and another English datasets using six machine learning methods: SVM, RF, LR, KNN, NB, and SGD. It achieved 92% accuracy and F1 score on the Arabic dataset, while reaching 100% accuracy on the English …

Visualizing The Effect Of Process Pause On Virus Entrapment During Constant Flux Virus Filtration, Wenbo Xu, Xianghong Qian, Hironobu Shirataki, Daniel Straus, Sumith Ranil Wickramasinghe

Biomedical Engineering Faculty Publications and Presentations

Virus filtration is an essential unit operation used to validate clearance of adventitious virus during the manufacture of biopharmaceutical products such as monoclonal antibodies. Obtaining at least a 10,000-fold reduction in virus particles in the permeate is challenging as monoclonal antibodies are about half the size of the virus particles. Minute virus of mice, FDA-recommended model adventitious virus, was labeled with a fluorescent dye. Laser scanning confocal microscopy was used to determine the location of virus entrapment within the virus filtration membrane. Three different hollow fiber membranes made of regenerated cellulose and polyvinylidene fluoride were tested. Feed streams consisted of …

A Proposed Model For Assessing The Impact Of Sustainable Practices On The Affordability Of Affordable Housing In Egypt Using Ahp, Ayman M Zakaria Eraqi, Omnia Nagy Abd El-Hafez, Amany Nagy Abd El-Hafez

HBRC Journal

Amid rising inflation and a housing crisis in Egypt, this research develops a model to assess the affordability of sustainable housing for low- and middle-income groups by integrating environmental, social, and economic sustainability criteria. The research methodology used Analytic Hierarchy Process (AHP) to evaluate the relative weights of sustainability criteria in housing projects. Based on their impact on construction costs, these criteria were classified by experts into five main groups: Design Criteria (preliminary studies, initial cost, environmental planning), Neighborhood Criteria (location, design, management), Social and Cultural Criteria (privacy and safety), Natural Resource Sustainability (water, energy), Housing Unit Criteria (design and …

Key Technical Difficulties, Challenges, And Prospects Of Geologic Co2 Sequestration In Saline Aquifers, Wei Hengfei, Shi Junjie, Nie Xiaodong, Fang Jie, Chen Jing, Zhao Yue, Sun Dawei, Li Xin, Zhang Yong, Guo Pei

Coal Geology & Exploration

Background and Method Carbon capture and storage (CCS) technology represents the primary technical direction for large-scale carbon emission reduction. Among various CCS techniques, geologic CO₂ sequestration in saline aquifers holds great potential, establishing it as a major technique for future carbon storage. Based on a review of the current status of research on global geologic CO₂ sequestration in saline aquifers, this study comprehensively analyzed the technical difficulties, challenges, and prospects of this technology, focusing on the dilemma of the application of this technology under complex geological conditions in China. Results and Conclusions A huge gap in both the …

Compression Forming Of Basic Oxygen Furnace Slag-Gypsum Blocks: Performance Enhancement And Environmental Assessment, Fengyi Zhang

Student Works (2020-2029)

The construction industry plays a crucial role in global development but faces significant environmental challenges, particularly CO2 emissions from cement production. Gypsum blocks provide a sustainable alternative to traditional cement concrete blocks. However, the low mechanical strength and water resistance of gypsum materials limit the widespread adoption of gypsum-based materials in the construction industry. This study initially produced gypsum-based blocks using compression forming, adding supplementary cementitious materials (SCMs), and subjecting accelerated carbonation curing (ACC). It was found that compression forming addressed the shortcomings of traditional block manufacturing (high energy consumption and long production time), and the addition of SCMs generated …

Automatic Guitar Transcription Of Polyphonic Music, Ritwik Patil

Master's Theses

Transcribing guitar music automatically is a complex task due to polyphonic overlap, tuning variations, and diverse playing techniques. Current transcription systems focus on identifying note pitches and timing while ignoring performance techniques that describe how the notes are played, treating guitar recordings as generic polyphonic audio and producing MIDI-like outputs that lose important information about articulation and style. To address these challenges, we propose an end-to-end transformer model for automatic guitar transcription. The system uses a T5-based encoder-decoder architecture that processes the Constant-Q Transform (CQT) of stereo audio input. The stereo representation helps separate individual guitar parts within a mix …

Spatial Distribution And Source-Sink Matching Of Stationary Co2 Emissions In Zhejiang Province, Zhu Qianlin, Chen Dongbao, Liu Hanxiao, Lu Shijian, Chen Fu

Coal Geology & Exploration

Objective Carbon capture, utilization, and storage (CCUS) is supposed to become an essential technology for the consumption of fossil fuels under the background of achieving carbon neutrality. Delving into the spatial distribution of regional CO₂ stationary sources and the source-sink matching characteristics will contribute to more rational decision-making in CCUS deployment and promote the development of carbon sequestration technology. Methods This study investigated the spatial distribution of CO₂ stationary sources in Zhejiang Province and, using the carbon emission factor method, assessed their CO₂ emissions based on their scales. Furthermore, it analyzed the geological features of both onshore …

Physical Simulation Experiments On 4d Visualization Of Dynamic Methane Diffusion And Adsorption In Low-Porosity And Low-Permeability Coals, Liu Tong, Jiao Baizhuo, Lin Baiquan, Sang Shuxun, Yang Wei, Liu Shiqi, Liu Ting, Li He, Yang Mingxing

Coal Geology & Exploration

Objective and Method The diffusivity of methane (CH₄) in coal seams significantly influences the surface extraction of coalbed methane (CBM) and underground gas drainage. However, the visualized characterization of the diffusion and migration processes of CH₄ in coals remains challenging. To address this issue, this study systematically demonstrated the similarity between krypton (Kr) and CH₄ in their adsorption and diffusion behavior in coals. Utilizing Kr—a gas with high X-ray attenuation—as a tracer substitute for CH₄, this study achieved the transparent observation of the dynamic gas migration process in low-porosity, low-permeability, and heterogeneous coals using …

Efektivitas Dan Keberterimaan Madcom Noise Protection Sebagai Alat Pelindung Pendengaran Berbasis Perlindungan Ganda, Ahmad Athif Wahyu Ramadhan, Yamtana Yamtana, Naris Dyah Prasetyawati, Sigid Sudaryanto

National Journal of Occupational Health and Safety

Industrial environments often generate high noise levels due to the continuous operation of machinery and production equipment. Persistent exposure to workplace noise exceeding the Threshold Limit Value (TLV) can lead to noise-induced hearing loss. According to the World Health Organization, an estimated 430 million people worldwide require rehabilitation for hearing impairment, with 109.4 million of these cases occurring in Southeast and Central Asia. As a critical component of Occupational Health and Safety (OHS) management, noise control is often implemented using Hearing Protection Devices (HPDs). This study aims to evaluate the effectiveness of an earplug-earmuff combination, developed as Madcom Noise Protection, …

Green Ai-Enhanced Deep Learning Model For Breast Cancer Detection And Classification In Mammography Images: Bc-Net-512, Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy

Mansoura Engineering Journal

This study champions a sustainable approach for developing a Deep Learning (DL) model for medical image analysis, specifically focusing on breast cancer (BC) detection in mammograms. By prioritizing low-computing algorithms to achieve high diagnostic accuracy while minimizing the model's environmental footprint, that aligns with the principles of Green AI. In this paper, an innovative architecture called BC-Net-512 was constructed for the classification of BC mammography. It is composed of lightweight Convolutional Neural Network (CNN) blocks for texture, density, and structure feature extraction and detection, a thin, fully connected layer for learning complex patterns and correlations in the extracted features, and …

Quantitative Evaluation Of Tunnel Rock Mass Integrity Based On Mwd Technology, Zhang Kunmu, Peng Hao, Liang Ming, Han Yu, Song Guanxian

Journal of China & Foreign Highway

In tunnel construction,the quantitative evaluation of rock mass integrity heavily relies on information from the exposed face,and there are challenges when drilling data is used for integrity evaluation.To this end,this study introduced a novel method for quantitative evaluation of rock mass integrity during drilling,integrating numerical statistics with machine learning.A substantial dataset of digital drilling data was collected,covering three common types of rock mass integrity:relatively intact,relatively fractured,and fractured.Subsequently,a high-performance random forest model for the classification of rock mass integrity was developed through data preprocessing and hyperparameter optimization.The interpretability of the model ’s predictive results was enhanced using Shapley additive explanations (SHAP …

Object Detection And Tracking Based On Fusion Of Radar And Camera On Highway Side, Zeng Yongqiang, Zhang Yonghua, Zhao Hui, Liu Xin, Xu Mingsheng, Shen Jianwei, Hu Zhiwei, Chen Zhenquan

Journal of China & Foreign Highway

Camera is the most widely used sensor in intelligent transportation systems (ITS),but the decline of detection and positioning accuracy caused by target occlusion and external environment interference has always been an important factor restricting the development of ITS.In order to solve this problem,a multi-mode fusion target detection and tracking method based on millimeter-wave radar (MWR ) and camera on highway side was designed.Compared with cameras,high-resolution MWR had better measurement accuracy and weather robustness,serving as a better complement to camera perception.The proposed method used the center point-based radar and camera fusion algorithm for target detection and adopted the greedy algorithm for …

Impact Of Ethanol On The Evolution Of One-Step Synthesized Gold Nanoplates And Nanostars And Their Effects On Raman Signal Enhancement, Ananda Fania, Nonni Soraya Sambudi, Kirana Yuniati Putri, Yuliati Herbani, Affi Nur Hidayah

Makara Journal of Science

Gold nanoplates and nanostars were synthesized from a gold metal salt solution (HAuCl₄) using a one-step synthesis method of ultraviolet C (UVC) light irradiation. The gold salt solution was mixed with ethanol in 6 mL with the following ratios: (1.5:4.5, 3:3, and 4.5:1.5), and subsequently irradiated with UVC light. Changes in localized surface plasmon resonance (LSPR) shifts were observed in real time at 30-min intervals for 2 h. The synthesis process produces gold nanoplates. While gold nanostars were synthesized from a solution of gold salt combined with ethanol, ascorbic acid, and AgNO₃, maintaining a consistent ratio …