Engineering Commons^™

An Integrated Geophysical Approach For Estimating The Depth Of Mineral Potential In Some Part Of Basement Complex Terrain Southwestern Nigeria, Hamid Titilope Oladunjoye, Joseph Coker, Niyi-Ola Adebisi, Omolara Abosede Adenuga, Sofiat Adetomilola Adekoya, Aderemi Alabi, Abisola Akinmoladun

Al-Bahir

Effective mineral exploration in a basement complex necessitates precise delineation of overburden thickness and mineral potential within the Basement Complex terrain. This study examined the subsurface geology and assesses the abundance of prospective mineral deposits within the study area The objective of the study was to outline the overburden thickness and infer mineral potential using integrated ground magnetic and electrical resistivity geophysical methods. The electrical resistivity method unraveled the litho-stratigraphic sequence as surmised from geo-electric layers. Consequently, the mineralization of the basement delineated was characterized by the magnetic method. The acquired data were processed using WINRESIST and Oasis Montaj respectively. …

Examining The Impact Of Stress On Collegiate Flight Students, Shivanee D. Cannon-Patron

Beyond: Undergraduate Research Journal

Stress may negatively affect the timely completion of a student pilot's flight training. A student pilot influenced by stress may be subject to what is known as "falling behind the aircraft," a condition that constantly requires minor interventions from their flight instructor. This lack of situational awareness and decreased performance may inadvertently cause the student pilot to repeat the flight lesson, increasing the time spent in the training course.

Investigating The Properties Of Eco-Bricks Composed Of Sawdust, Bamboo, And Varying Composition Of Sugarcane Bagasse Ash And Portland Cement, Wilfred Victor C. Marasigan, Julia Sophia Antonia S. Encarnacion, Czyrus Michael A. Bajeta, Alijah F. Gonzales, Juan Carlo T. Gumangan

Sinaya: A Philippine Journal for Senior High School Teachers and Students

With the construction industry contributing nearly 40% of global greenhouse gas emissions, there is a growing need for innovative and sustainable building materials. This research investigates a new eco-friendly concrete brick incorporating sugarcane bagasse ash (SCBA), sawdust, and bamboo fibers. Three eco-brick mixtures, each containing 2% bamboo fiber and 10% sawdust by weight but with varying proportions of Portland cement (PC) and SCBA, were tested against a standard brick for compressive strength, flexural strength, and water absorption. The optimal mixture, with 2% bamboo fiber by weight, 10% sawdust by weight, 85% PC, and 15% SCBA, exhibits compressive and flexural strength …

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 4 [2025], Número 1 (Issue 1), Ivan Ávila González Phd, Cristo Leon, Romano Ponce-Díaz Phd, Diogo A. Camelo, Alfonso Rincón Vaquero, Edgar Ávila González, Daira Pando Tamayo, Michelle Llado-Wrzos, Leonid Moyzhes, Andrea A. Echeverría Barrios

Journal of Roleplaying Studies and STEAM

La cultura es un diálogo constante con el pasado, el presente y el futuro. Todos nuestros objetos culturales son el resultado causal de las personas que estuvieron antes que nosotros, se actualizan en nuestro proceder en el presente y, les proyectamos al futuro con la esperanza de que aporten algo positivo a las generaciones que estarán delante de nosotros; de tal forma, este Volumen 4 [2025], número 1 (Issue 2) es el resultado directo de la labor de los editores fundadores Mauricio Rangel Jiménez, Miguel Angel Bastarrachea Magnani y todas aquellas personas que trabajaron antes que nosotros para que existiera …

Cutting-Edge Methods For Analyzing Student Behavior In Educational Settings: A Review, Shatha Talib Rashid, Hasanen S. Abdullah

Journal of Soft Computing and Computer Applications

The ability to predict students' performance in educational settings like schools and universities is crucial. A key objective of this effort is to increase academic outcomes and prevent dropout rates, among other benefits. Automating student activities, encouraged by information collected from any technology-based learning tool, has an important role in the process here. Those big quantities of information ought to be completely studied theoretically and processed for gaining worthy insights concerning a student's background as well as interacting with scientific missions, facilitating the development of advanced ways and algorithms to predict students' performance. The current study reviews several contemporary mechanisms …

Blockchain-Based Physical Election Votes Digitally Secure Transfer, Mohanad A. Mohammed, Hala B. Abdul Wahab

Journal of Soft Computing and Computer Applications

Responsibility for maintaining election transparency over time and ensuring democratic values intact is held by the Iraqi Independent High Electoral Commission (IHEC). However, transferring physical election votes from election centers is a critical duty, where many challenges appear regarding accountability and security measures. This study proposes a system that utilizes blockchain technology to solve any challenges or difficulties and ensure an effective and improved election process by providing its highest trustworthiness and legitimacy and ensuring a decentralized security process. This system offers unique blockchain characteristics such as immutability, decentralization, and transparency, providing an extra level of security to the data …

Modern Face Recgognition Systems: A Review Of Methods And Empirical Findings, Zahraa Naji Razoqi, Raheem Ogla, Abdul Monem S. Rahma

Journal of Soft Computing and Computer Applications

The face recognition system is a biometric technique that replaces traditional passwords and personal identification. This research is dedicated to presenting a study of some facial recognition systems. Since it is unlikely to replicate and is more stable over time, the domain of facial feature extraction has proven to be more effective in attaining exact facial recognition, which is important, especially in intelligent security surveillance systems. Face recognition systems encounter several challenges, primarily related to pose variations, illumination conditions, and occlusions such as hair, glasses, and so on. To address these challenges, enhance performance, and boost the accuracy and speed …

Arson Event Detection Using Yolov9, Ali Abbas Abbod, Matheel E. Abdulmunimb, Ismail A. Mageed

Journal of Soft Computing and Computer Applications

Detecting event anomalies is crucial for surveillance systems, as it enables the identification of occurrences in videos, both temporally and spatially. It can identify deviations from patterns without requiring human oversight by learning from past information to distinguish normal behavior and pinpoint irregularities. Early detection of arson fires is critical to mitigating damage, public safety, property, and the environment, as well as saving lives and aiding in law enforcement investigations. The objective of this study is to evaluate a system for detecting events using the You Only Look Once version 9 (YOLOv9) model in surveillance videos with a focus on …

Enhancing Cybersecurity Based On Blockchain Technology: A Systematic Review, Sarah Mohammed Shareef, Rehab Flaih Hassan

Journal of Soft Computing and Computer Applications

Cybersecurity is a crucial component of the security system that guards against unauthorized access to digital transactions. Blockchain is a decentralized ledger used to securely exchange digital currencies and conduct trades and transactions. Blockchain technology has led to significant changes in electronic transactions. The enormous potential is being exploited in many areas such as financial services, real estate, supply chain, and the Internet of Things. Despite being a security system, it has suffered from security threats to sensitive data. Phishing and 51% attacks can circumvent blockchain security, highlighting the need for thorough user education and awareness. Additionally, blockchains based on …

Predicting Earthquake Location Using Convolutional Neural Network-Attention Mechanism Approach, Mohammed A. Jaleel Shaneen, Suhad M. Kadhem

Journal of Soft Computing and Computer Applications

In seismically active areas, earthquake prediction is essential for minimizing potential damages and preserving lives. However, precise forecasts are complicated to achieve because of seismic events’ complex and unpredictable nature. The current study presents an advanced prediction approach to address such issues, combining Convolutional Neural Networks (CNNs) and Attention Mechanism (AM). The primary goal is to improve the accuracy of the earthquake predictions and the generalizability across various mainland Chinese regions. AM layer emphasizes significant features for improving the prediction performance, whereas CNNs are utilized to extract spatial features of seismic data. The efficiency and effectiveness of the proposed approach …

Comparative Analysis Of Loss Of Control Definitions, Owen D. Poborsky

Journal of Aviation Technology and Engineering

“Loss of control” (LOC) is a broad term in aviation used to describe an event or series of events that resulted in an accident or incident of an aircraft. Many definitions of LOC exist for aircraft while maneuvering on the ground and in the air. The purpose of this study is to synthesize the numerous LOC definitions found in the literature and from government and rulemaking organizations to better understand the importance of airspeed awareness as it relates to LOC events at low altitudes. Furthermore, emphasis shall be placed specifically on flight training within general aviation, as significant LOC statistical …

E-Taxi Technology: Assessing Operational Benefits And Sustainability In Modern Aviation, Arthur C. Dela Peña

Journal of Aviation Technology and Engineering

This study evaluates the operational benefits and sustainability impacts of electrically driven landing gear systems (e-taxi technology) in the aviation industry, focusing on the Philippine context. The objective was to assess improvements in fuel savings, emissions reductions, and maintenance costs associated with e-taxi systems. Using a mixed-methods approach, data were collected through interviews with airline operators, and secondary data were collected from industry reports. Results showed that e-taxi systems reduced taxiing time by 15–22%, fuel consumption by 150–180 kg per flight, and engine wear by 10–14%. Carbon emissions were reduced by 472–566 kg per flight, while noise levels decreased by …

A Machine Learning-Driven Framework For Real Time Detection And Prevention Of Replica Node Attacks In Wireless Sensor Networks, Maram Pavani, Tanguturi Sharani, Amutha Jeevakumari S A

Northeast Journal of Complex Systems (NEJCS)

Mobile devices and wireless sensor networks (WSNs) are increasingly vulnerable to security threats such as unauthorized access and replica node attacks. Mobile devices face risks from replication and anomalous behavior, while attackers compromise WSNs by cloning legitimate nodes, thus threatening network integrity. Traditional security mechanisms often fall short in detecting such sophisticated threats, especially in resource-constrained environments. This research proposes a dual-component security system. A Machine Learning-Based Intrusion Detection System (IDS) for WSNs leverages Graph Neural Networks (GNNs) to detect replica nodes through structural network analysis and applies Federated Learning to preserve data privacy. The Sequential Probability Ratio Test (SPRT) …

Thermal Rheological Properties Of Heat-Moisture Modified And Its Application In Multigrain Cookies, Thi Huyen Trang, Li Xianghong, Miao Jinxu, Wang Faxiang, Liu Yongle, Li Shuang

Food and Machinery

［Objective］ To develop low -burden,high -nutrient functional baked foods.［Methods］ A single -factor experimental design is employed,with rapid visco analyzer,rheometer,and differential scanning calorimeter to analyze the physicochemical properties of heat -moisture modified wheat flour.The cookie formula is optimized based on sensory evaluation.［Results］ Heat -moisture treatment significantly enhances the pasting stability and resistant starch content of wheat flour.The optimal auxiliary ingredient formula is 50 g of heat-moisture modified wheat flour,20 g of oat flour,10 g of mung bean flour,and 6 g of resistant dextrin powder.Compared with the control group,the cookies made from the experimental formula show a significantly lower digestibility,with a glycemic …

Intelligent Intrusion Detection In Clustered Wireless Sensor Networks: A Dynamic Clustering And Machine Learning-Based Approach, Abdullah R. Abdulwahhab, Mohd Fadzli Mohd Salleh, Muhammad Firdaus Akb, Mohammed Najm Abdullah

Iraqi Journal for Computer Science and Mathematics

Traditional Intrusion Detection Systems (IDS) designed for more conventional network infrastructures are often ill-equipped to handle the unique challenges WSNs pose, leading to significant gaps in security and resilience. This paper introduces an Intelligent Intrusion Detection System (IIDS) explicitly tailored for clustered WSNs to address these critical challenges. The proposed IIDS integrates dynamic clustering with advanced machine learning algorithms to create a robust and adaptive security solution capable of real-time threat detection and mitigation. The dynamic clustering mechanism is designed to continuously monitor and respond to changes in sensor node network topology and energy levels, ensuring that energy consumption is …

Non-Overlapping Patch-Based Pre-Trained Cnn For Breast Cancer Classification, Lamyaa Sabeeh Ashour, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Putra Sumari, Ahmed Kateb Jumaah Al-Nussairi, Sura Abdulateef Al-Shammari, Sarah Thabit Abdulmunem

Iraqi Journal for Computer Science and Mathematics

Breast cancer (BC) significantly impacts women's mortality rates and requires early detection to improve survival chances and enable appropriate treatment. Thus, a computer-aided system with high performance can speed up this process. A convolutional neural network (CNN) is considered sensitive to insufficient, noisy data. It cannot achieve high performance, however, restricted access to high-quality medical data, stemming from stringent confidentiality and privacy issues, is a considerable obstacle to the successful training of deep learning models. The current study aims to develop a remarkable, influential model for BC classification whilst considering modern pre-trained models ResNet50, AlexNet, InceptionV3 and VGG16 for extracting …

Retracted: Navigating The Complexities And Artificial Intelligence Of Internet Of Things Security Claims, Tamara Saad Mohamed, Saad Mohammed Khalifah

Iraqi Journal for Computer Science and Mathematics

The term ``Internet of Things'' (IoT) describes a system that allows everyday objects to communicate with one another and with controlled systems, servers, and other linked devices through a variety of connectivity constructions by means of embedded software, sensor technology, electronics, and connections. Data from the Internet of Things (IoT) will be sent to the servers over the internet from a variety of sensors, nods, and collectors. Governments, medical facilities, consumers, and corporations all make use of IoT devices. approximately, More than 65 billion Internet of Things devices are expected to be in operation by 2024. The proliferation of IoT …

Topological Indices For The Resize Graph Of (G2(3)), Manar Musab Ftekhan, Ali Abd Aubad

Iraqi Journal for Computer Science and Mathematics

Indexes of topological play a crucial role in mathematical chemistry and network theory, providing valuable insights into the structural properties of graphs. In this study, we investigate the Resize graph of G₂(3), a significant algebraic structure arising from the exceptional Lie group (G₂) over the finite field F₃. We compute several well-known topological indices, including the Zagreb indices, Wiener index, and Randić index, to analyze the graph's connectivity and complexity. Our results reveal intricate relationships between the algebraic structure of G₂(3) and its graphical properties, offering a deeper understanding of its combinatorial …

Machine Learning Algorithms To Detect Cyber-Attack In The Internet Of Things Platform, Maad Kamal Al-Anni, Rafah M. Almuttairi, Ammar A. Al-Hamadani, Khamis A. Zidan, Husam Ibrahiem Husain Alsaadi, Ghaidaa A. Al-Sultany

Iraqi Journal for Computer Science and Mathematics

In response to escalating cyber threats in Internet of Things (IoT) networks, this research investigates several traffic classification techniques by using benchmark datasets, such as CICIoT2023. This dataset was exclusively used to test the effectiveness of the proposed system, which aims to enhance the data processing for machine learning algorithms amid increasingly complex cyber threats. To prepare the naturally unstructured and raw dataset for analysis, Linear Discriminant Analysis (LDA) is applied for dimensionality reduction. The processed data and attributes are then fed into the proposed Fuzzy-Integrated Relevance Vector Machine Classifier (FIRVM), which is implemented in Python 3.10⁺ using the …

Evaluating The Physiological Effects Of A Spacesuit While Performing Cpr, Marielle Lenehan

Beyond: Undergraduate Research Journal

Limited research exists on the challenges of performing cardiopulmonary resuscitation (CPR) while wearing a spacesuit/pressure suit; but, during a space mission or following spacecraft egress, astronauts may need to perform Basic Life Support (BLS) on a crewmember. BLS consists of CPR and External Chest Compressions (ECC). In an emergency, astronauts may not have time to remove their intravehicular (IVA) spacesuits/pressure suits or wait for their heart rates to return to resting conditions and, therefore, would have to perform CPR while physically exerted. This study sought to evaluate the physiological exertion on rescuer performance while performing ECCs over 6 minutes while …

Exploring The Interplay Between Economic Growth And Sustainable Development: A Complex Systems Approach To Gsdp And Sdgs In Indian States, Rosewine Joy, Helen Josephine, Divya D, Midhun Raj

Northeast Journal of Complex Systems (NEJCS)

Pursuing Sustainable Development Goals (SDGs) necessitates aligning business and management practices on a global scale. This paper delves into the intricate dynamics between Gross State Domestic Product (GSDP) and SDGs across diverse states in India, offering nuanced insights to policymakers, businesses, and stakeholders. This paper explores the dynamic relationship between Gross State Domestic Product (GSDP) and the Sustainable Development Goals (SDGs) in the context of India's diverse states by applying modern machine learning techniques such as XG boost, Decision trees, and K mean clustering. The study delves into how economic growth influences the progress towards SDGs. The research integrates complex …

Orchestrating Complexity: The Art Of Virtual Leadership In System Modelling, Vijay Kumar Sonawane, Bipllab Roy, Purnendu Bikash Acharjee, Indu Pv

Northeast Journal of Complex Systems (NEJCS)

This paper explores the dynamics of virtual leadership within global remote work environments, focusing on the application of complex system modelling to understand and enhance leadership efficacy. The application of computational modelling has been a regular feature in economics, science and technology fields, however its application in virtual leadership with linkage to sport leadership appears to be a novel concept. Adopting a multidisciplinary approach, this paper incorporates Game Theory as a conceptual framework to make the leadership model more relevant and applicable that can offer simpler understanding of complex play of leadership drivers. The model incorporates five key leadership dimensional …

Leveraging Usage Of Ai In Education: Knowledge, Attitude And Behavioral Analysis On Students, Bipllab Roy, Purnendu Bikash Acharjee, Rohit Kumar Sharma, Ruptaheen Kramsapi, Shruti P

Northeast Journal of Complex Systems (NEJCS)

The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how …

Control Strategies In Wind Energy Systems: A Comprehensive Overview, Abeer Awad, Mohamed Al Hasheem

Future Engineering Journal

This paper reviews different control methods used in wind energy systems to improve how they work and connect to the power grid. It covers simple control methods like Proportional-Integral (PI) controllers, as well as more advanced ones like Sliding Mode Control and intelligent controls such as fuzzy logic and neural networks. The strengths and weaknesses of each method are discussed, focusing on how well they handle changes in wind and load, keep power quality high, and stay stable. Challenges like system complexity and unpredictable wind are also explained. The paper ends by suggesting that future work should focus on combining …

A Hybrid Ai-Based Framework For Real-Time Epileptic Seizure Detection In Intracranial Eeg Signals Using Brain-Computer Interfaces, Ahmed, M. Salaheldin Dr., Manal Abdel Wahed Prof., Neven Saleh

Future Engineering Journal

Epilepsy is a serious neurological disorder that can significantly impact an individual's quality of life. This study proposes a novel method for the detection and mitigation of epileptic seizures through the integration of artificial intelligence (AI) and a brain-computer interface (BCI) system. Statistical features were extracted from intracranial electroencephalography (IEEG) signals using a multi-resolution decomposition technique and used to train five classification algorithms: support vector machines (SVM), k-nearest neighbors (KNN), Naïve Bayes (NB), artificial neural networks (ANN), and long short-term memory (LSTM). The model demonstrated strong performance, achieving classification accuracies of 98.28% (SVM), 93.88% (KNN), 95.73% (NB), 95.73% (ANN), and …

Review Of Energy Storage Systems For Optimal Planning And Operation Of Microgrid Resources, Ibrahim M. Ibrahim Dr., Walid A. Omran Prof., Almoataz Y. Abdelaziz Prof.

Future Engineering Journal

Energy storage systems (ESSs) play a central role in microgrid (MG) research and are widely used in related studies. This is due to the many applications of ESSs that enhance the performance of MGs. These include power quality applications and energy management applications. This paper presents a literature review of various studies that address the use of ESSs in microgrid (MG) systems to perform functions aimed at enhancing overall performance. These studies are classified into two main categories: planning and operational planning, with the MG being either grid-connected or islanded in each case. Finally, the optimization techniques used to obtain …

Exploring Sustainable Practices In Educational Buildings During The Project Lifecycle In Egypt, Abdallah Awny, Youssef A. Awad, Hosam Hegazy, Ibrahim Mahdi

Future Engineering Journal

Sustainable construction approaches are essential for mitigating environmental concerns and enhancing energy efficiency in educational facilities. This research examines sustainability solutions in Egyptian educational institutions, concentrating on the design, building, and operating stages. The study combines quantitative and qualitative assessments from a survey of 66 industry experts, evaluating essential sustainability criteria like energy efficiency, water conservation, material sustainability, and operating expenses. Statistical methods, such as the Relative Importance Index (RII) and correlation analysis, were used to assess the relevance and interrelations among sustainability factors. The findings reveal that energy efficiency (RII: 0.82) and the promotion of health and well-being (RII: …

Centralized, Decentralized And Hybrid Wastewater Management Approaches – Gap Study, Zeyad Kadry, Ahmed M. Ebid Dr., Ibrahim Mahdi

Future Engineering Journal

This literature review highlights advancements in wastewater management, emphasizing hybrid systems that integrate centralized and decentralized approaches. It underscores the cost-effectiveness and scalability of decentralized wastewater management (DWWM) for small urban and rural areas, despite higher land and capital needs. Optimization frameworks utilizing advanced computational tools, such as genetic algorithms and GIS, have proven effective in reducing costs and enhancing resource recovery, with decision-support frameworks tailored for rural planning. The integration of synergistic technologies like vertical farming and photovoltaic energy enhances the sustainability and resilience of decentralized systems in urban contexts. Additionally, innovative treatment methods, including nano-disinfection and advanced coagulation, …

Retraction Notice: Enhancing Project Tracking Through Microsoft Power Platform Automation: A Case-Based Study Using Power Bi

AUIQ Technical Engineering Science

Reason for Retraction:

The authors have disclosed that the article includes confidential and proprietary data, specifically within one of the figures (Figure 9), which was published without authorization from the data-owning organization. This constitutes a violation of publishing ethics as defined by the Committee on Publication Ethics (COPE) and necessitates formal retraction.

Boundary Value Problems Associated With Morse-Novikov Cohomology Groups Of Riemannian Manifolds With Boundary, Qusay S. A. Al-Zamil, Mohammed Y. Abass

Iraqi Journal for Computer Science and Mathematics

In this paper, we provide an affirmative response to the following question: if Morse-Novikov cohomology groups of M with non-empty boundary ∂M do not vanish, then what topological or analytical(geometrical) constraints can be enforced to ensure that the equation 𝖽θω=η is solvable for any non-trivialprescribed [η] in absolute Hθk(M) or relative Hθk(M,∂M) Morse-Novikov cohomology groups?. Where 𝖽θω=𝖽ω+θ∧ω and 0≠[θ]∈HdR1(M) for any ω∈ …