Digital Commons Network^™

Achieving Urban Resilience Strategies For Cities, Rehab Abdelfatah Abdel Aziz. Mahmoud

Mansoura Engineering Journal

The concept of the Resilient City is a relatively recent addition to urban planning discussions, gaining global attention due to the increasing need for cities to withstand urban, social, and environmental challenges. Urban resilience, alongside adaptability, plays a vital role in addressing these dynamic transformations. This research investigates how to implement urban resilience strategies to effectively respond to ongoing changes and sudden crises, such as terrorist attacks and natural disasters like floods, earthquakes, and hurricanes. The research identifies a critical gap in the absence of a comprehensive theoretical framework for evaluating the success of urban resilience strategies within cities’ planning …

Development Of A Hybrid Methodology Of Deep Learning And Machine Learning For Lung Nodule Detection In Medical Computed Tomography Images, Zaed S. Mahdi, Rana M. Zaki, Alaa Kadhim Farhan, Negar Majma

Journal of Soft Computing and Computer Applications

Deep learning and machine learning play an important role in the medical field, helping doctors make accurate, fast and effective diagnosis. Despite the progress achieved in the use of modern technologies in detecting cancerous nodes, current studies still suffer from some challenges and limitations that must be addressed to obtain high efficiency in identifying cancerous nodes. These challenges include using image pre-processing, combining deep learning and machine learning techniques, and constantly adapting to clinical changes, in order to address this. A hybrid methodology has been proposed for detecting cancerous nodules in the lung in medical Computed Tomography (CT) images. It …

Enhancing Image Classification Using A Convolutional Neural Network Model, Zena M. Saadi, Ahmed T. Sadiq, Omar Z. Akif, Marwa M. Eid

Journal of Soft Computing and Computer Applications

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as …

Foreword From Editor - 16th Edition: Toward An Inclusive Community Engagement, Yandi Andri Yatmo

ASEAN Journal of Community Engagement

This edition of AJCE defines and elaborates on the idea of inclusive community engagement as a means to involve the community in a meaningful process. ‘Inclusive’ refers to the principles of encompassing everyone, all individuals and groups alike, regardless of their identity, background, characteristics, needs, and perspectives, thereby ensuring that all voices are represented (Hodkinson, 2011). This practice extends beyond individuals with disabilities and embodies broader ideas of equality. Inclusive engagement plays a crucial part in fostering a constructive dialog that incorporates diverse perspectives within a community. Such engagements prioritize community participation in the decision-making process that affects their well-being …

Exploring Student Satisfaction In Learning With Podcast Applications: A Qualitative Study Based On Open-Ended Questions, Indah Permatasari, Peny Meliaty Hutabarat, Erni Adelina

Jurnal Vokasi Indonesia

This study aims to explore student satisfaction with the use of podcasts as a learning medium in the Non-News Radio Production course. A qualitative approach was used, with three open-ended questions posed to students: (1) What different experiences did you have when listening to the course material via podcast?(2) Did listening to the course material through podcasts help you focus on understanding the material? And why? And (3) provide your opinion on the Adapto podcast material shared during the Non-News Radio Production course in the 4th semester. The data obtained was thematically analyzed to identify the main emerging themes. The …

2024 Scholarly Productivity Report, Missouri University Of Science And Technology

Civil, Architectural and Environmental Engineering Scholarly Productivity Reports

No abstract provided.

Optimized Thyroid Disease Classification Using Nature-Inspired Algorithms: Gwo & Woa, Sayan Mondal

NJF Intelligent Engineering Journal

Recently, there has been an upsurge in the number of cases of thyroid disease. Thyroid function is essential for metabolism, making the early diagnosis of thyroid dysfunction an urgent matter. The issue of class imbalance has not been thoroughly examined, even though there are multiple publications on the topic of thyroid disease detection. Furthermore, the binary-class problem has been the primary emphasis of previous research. This study intends to address these concerns by using the suggested strategy, which takes into account ten distinct thyroid illnesses. In order to choose the best features from the Thyroid dataset, this research proposes two …

A Predictive Iot And Cloud Framework For Smart Healthcare Monitoring Using Integrated Deep Learning Model, Preeti Rani, Umesh Chandra Garjola, Haider Abbas

NJF Intelligent Engineering Journal

The researchers developed a deep learning-based smart healthcare monitoring system based on IoT and cloud technology. The proposed system integrates IoT sensors for real-time collection of physiological data, such as ECG, blood pressure, and heart rate, with cloud computing for secure storage and advanced analytics. Utilizing the Bi-LSTM model with fuzzy inference systems (FIS), the framework enhances the accuracy and efficiency of heart disease prediction. According to the evaluation, the model performs better in terms of accuracy, precision, recall, and F1 score than traditional LSTM and FLSTM models. By enabling early detection and personalized interventions, the system aims to reduce …

Real-Time Congestion Control And Load Optimization In Cloud-Manets Using Predictive Algorithms, Preeti Rani, Mohammed Hussien Falaah

NJF Intelligent Engineering Journal

Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.

A Predictive Framework Combining Iot And Machine Learning Regression Models For Smart Precision Farming, Kusum Yadav, Nesreen Abdou El-Hadiede

NJF Intelligent Engineering Journal

In this paper, the Internet of Things (IoT) and machine learning algorithms that incorporate regressor are integrated to improve precision agriculture. Data from Internet of Things sensors like temperature sensors, humidity sensors, and soil sensors can be collected and analysed using machine learning algorithms like Support Vector Machines (SVMs) and Multilayer Perceptrons (MLPs). By using the proposed system, crop yield will be optimised, resource usage will be minimised, and the environmental impact of agriculture will be reduced. A comparison of predictive accuracy and error metrics, such as RMSE, demonstrated the effectiveness of automated monitoring, predicting crop health issues, and implementing …

Single-Step Synthesis Of Activated Carbon From Arabica Spent Coffee Ground Using K2co3 As Activator Agent, Ghina Ivana Mieldan, Yuliusman Yuliusman

Journal of Materials Exploration and Findings

Activated carbon is a nanomaterial that is often used as an effective adsorbent. Activated carbon raw materials can use biomass, such as coffee grounds, which can be found along with the growth of public interest in coffee drinks. Chemical activators are used for activation to increase biomass carbon's adsorption capacity. Using K₂CO₃ activator to increase the specific surface area of activated carbon is more harmless than KOH. The use of spent coffee grounds as carbon source and food additive K₂CO₃ as an activator can make food-grade activated carbon that can be used for food. …

Effect Of Alkyd And Polyester Resin Compositions On Corrosion Resistance, Blistering, And Adhesion In Utilization Of Oily Sludge As Anti-Rust Coating Material, Gerets Land Kakalang, Yohanes David Kristianto, Johny Wahyuadi Mudaryoto

Journal of Materials Exploration and Findings

Oil sludge is a waste derived from upstream and downstream activities of the oil and gas industry which is estimated at 10,000 tonnes generated from all PERTAMINA downstream activities spread across various fields, processing units and depots throughout Indonesia. Oil sludge has the same characteristics as asphalt, where asphalt in previous studies can be used as an anti-rust coating, so that the handling of oily sludge can be topped up by reusing and having its own added value. The purpose of this research is to utilise waste oily sludge as an alternative anti-rust coating material and compare alkyd resin and …

Comparative Analysis Of Risk-Based And Time-Based Inspection Application In Hydrocarbon And Chemical Industries: A Review, Azizar Azizar, Nofrijon Sofyan

Journal of Materials Exploration and Findings

RBI and TBI strategies are comparatively reviewed in terms of their contribution to maintaining asset integrity for asset owners in the hydrocarbon and chemical industries. The objective is to assess various methods on a cost-efficient and risk-managed operational safety basis. It utilizes common industry standards such as API 580 for RBI, and API 510, API 570, and API 653 for TBI, and also case studies and literature analysis. The analysis of data was conducted to examine how each approach deals with inspection planning and decision-making. They suggest that RBI's risk-based prioritization strategy leads to more effective management of high-risk assets, …

Portable Personal Air Monitor, Samreen Zabiulla, T Jaya Soumya, Vaishnavi N, Pronama Biswas, Belaguppa Manjunath Ashwin Desai

Manipal Journal of Science and Technology

Cities around the globe are facing ever-increasing challenges to air quality, posing serious risks to public health due to high levels of particulate matter and various pollutants. Addressing these challenges requires a multifaceted strategy, including strict regulations, sustainable urban planning, and adopting cleaner technologies. To tackle these issues, we developed a portable personal air monitor designed to effectively assess environmental conditions. This innovative device incorporates a range of sensors and a filtration system to measure concentrations of different pollutants. What sets it apart is its unique design inspired by the human lung, utilizing a diaphragm vacuum pump to mimic the …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Black Soldier Fly Larvae (Bsfl) Bioconversion For Circular Economy: A Study In Polaman Village, Siswo Sumardiono, Rizka Amalia, Syaikha Butsaina Dhiya’Ulhaq, Nurika Nazilatul Ilmi, Hermawan Dwi Ariyanto

ASEAN Journal of Community Engagement

Conventional organic waste management methods often lead to environmental degradation and underutilization of valuable resources. In rural areas, such as Polaman Village, limited awareness and inefficient disposal systems exacerbate these issues, thus necessitating innovative and sustainable solutions. This study explores black soldier fly larvae (BSFL) bioconversion as a community-based solution for organic waste management, addresses environmental challenges, and promotes economic empowerment by converting waste into valuable by-products. The study employed a mixed-methods approach, beginning with baseline assessments of waste generation and existing management practices to identify community needs. Educational workshops and hands-on training sessions introduced BSFL bioconversion techniques to local …

Green Design Of Plant Based Pharmaceutical Drugs: Example Of A Wound Healing Topical Cream With Plectranthus Bojeri (Benth) Hedge Lamiaceae Extract, Helga Rim Farasoa, Marie Louise Razafindravao, Rojo Fanambinantsoa Andriamiarantsoa, Gerard Cecilien Raboanary, Jean Marie Razafindrakoto, Voahangy Ramanandraibe Vestalys

Journal of Bioresource Management

To ensure the perennity of natural resources, the valorisation process of herbal pharmaceuticals must be assessed for sustainability from the very beginning of its design. No specific tools have been developed for this particular field so far. We demonstrate in this study that existing green design tools can be adapted to evaluate plant-based products manufacturing process. As the example of a topical cream using Plectranthus bojeri (Benth) Hedge LAMIACEAE extract was considered, we first confirmed the traditional use of this plant for wound healing. It acts by accelerating the re-epithelialisation phase. Using the Vermeer Cosmolife version 0.24 software tool the …

Forecasting Air Pollution Driven By Vehicle Growth, Public Transport, Industry, And Household Waste, Chandra Harjono, Ludy Gianto, Rachmattullah Sidik, Dyah Lestari Widaningrum

Journal of Environmental Science and Sustainable Development

Jakarta, Indonesia's bustling capital, is grappling with escalating air pollution levels attributed to a confluence of socio-economic and infrastructural factors. This study employs Vensim modelling to project PM2.5 pollution trends through 2040, analysing the dynamic interplay among major contributors: increased vehicular emissions, industrial activities, public transportation deficiencies, and waste management inefficiencies. Materials and Methods: The method that will be used in this air pollution analysis is to integrate empirical data spanning three years to construct a predictive model underpinned by a robust causal loop diagram that elucidates the relationships between system variables and air quality. The results of this paper …

Assessing The Environmental Impact Of Municipal Solid Waste, Ojo Oluwayinka Florence, Olaniyan Olatunji Sunday, Akolade Adebola Saheed, Alabi Oluwaseyi Omotayo, Olaomotito Precious Adesope, Adebayo Kehinde John

Journal of Environmental Science and Sustainable Development

Municipal solid waste (MSW) management presents significant environmental challenges, especially with increasing urbanization and population growth. This study assesses the environmental impacts of MSW, focusing on waste composition, management practices, and their effects on air, water, and soil quality. The primary objective is to evaluate how MSW contributes to environmental degradation and to explore strategies for mitigating these impacts. A hypothesis was developed that optimizing waste composition through proper sorting and treatment can reduce the environmental footprint of MSW management by at least 10% in terms of leachate production and greenhouse gas emissions. Samples were collected using a randomized sampling …

Road Safety Assessment For Accident And Non-Accident Cases Supporting Sustainable Development Goals 2030, Brian Nararya Nugraha, Sekar Warangi Nurcahyati, Hizkia Adhikaratma, Martha Leni Siregar

Journal of Environmental Science and Sustainable Development

Halving the number of global deaths and injuries from road traffic accidents is one target of the Sustainable Development Goals 2030, which is still a challenging problem in Indonesia. However, the majority of research on this topic uses accident-based methods, which limits the safety analysis. Two road safety assessment methods are used to close the gap, with the addition of non-accident-based methods such as Road Safety Audits (RSA). The Margonda Raya Road, which is categorised as a traffic accident blackspot, was selected for the case study. For this, a field survey of the road segment is carried out. To minimise …

Online Learning Transition: An Analysis Of Proactive Institutional Assistance In Reducing Difficulties During The Covid-19 Pandemic, Mohammed Yahya Alghamdi

BAU Journal - Science and Technology

The COVID-19 pandemic caused major changes in the education system, with a shift to online learning, and experience has shown that transitioning from face-to-face instruction is difficult. This study involved 80 academic staff members from Al-Baha University in Saudi Arabia to learn about the benefits, limitations, and institutional support of online education in the setting of an epidemic. The study answers two primary questions: The first study question was, What difficulties did instructors face when they switched to online instruction? While the second research question was, How did institutional support influence the transition to online instruction? The study’s research methodology …

Cropsync: Ai-Powered Sustainable Crop Management, Ziad Doughan, Ibrahim Mneimneh, Zouheir Nakouzi, Noor Al Khaib, Samer Damaj, Jamal Chaaban, Hamza Mrad, Sari Itani

BAU Journal - Science and Technology

CropSync is a smart agriculture system that uses AI and IoT technologies to enable sustain- able crop management and precision farming. The system aims to address the challenges faced by the agriculture sector, such as increasing food production to meet global population demands while minimizing environmental impact. CropSync integrates sensors, cameras, and cloud-based analytics to provide farmers with real-time insights and recommendations for optimizing crop cul- tivation. The system upholds engineering professional and ethical standards, considering broader social, environmental, and economic implications. From a social perspective, CropSync improves food security and enhances farmers’ livelihoods through increased productivity and efficient re- …

Metakaolin-Based Geopolymer Concrete; Synthesis, Development And Characterization, Heba Fouad

Theses and Dissertations

Geopolymers are rendered as an essential sustainable replacement to the widely used Ordinary Portland Cement (OPC) which causes immense carbon dioxide emissions, hence a detrimental impact on society’s health and the environment. Geopolymers are three-dimensional networks of polymerized tetrahedral silicate and aluminate in the form of Q4(4Al), Q4(3Al) and Q4(2Al) which act as the principal binding phase in concrete. Past research has reported the synthesis of geopolymers from different aluminosilicates precursors, their characterization, and their wide range properties. However, previous studies still have not properly investigated effective range of synthesis ratios for a particular source material, optimum curing regimes, short- …

Liquid-Cooled Thermoelectric Modules: Potential For Efficient Water Harvesting Through Air Condensation, Bowo Yuli Prasetyo, Aindri Yuliane, Parisya Premiera Rosulindo, Fujen Wang

Makara Journal of Technology

Water is one of the essential natural resources for the sustaining life of all beings on this planet. In general, groundwater is used to meet daily needs, although the availability of this water source becomes a major concern, particularly in some areas with limited access to it. Air condensation is a solution for providing water in such areas. This study aims to explore the potential of utilizing the thermoelectric technology as an alternative solution for water provision. An experiment is conducted using a system consisting of single liquid-cooled thermoelectric cooling devices/modules (TECs). Three types/variants of TECs with different cooling capacities …

Quantitative Analysis Of Machine Learning Model Performance And The Need To Consider Explainability, Vishnu S. Pendyala

Open Educational Resources

This presentation, titled "Quantitative analysis of Machine Learning model performance and the need to consider explainability," delves into various metrics used for evaluating machine learning models. It thoroughly examines fundamental classification metrics like accuracy, precision, recall, and F-score, while also discussing more advanced measures such as the Kappa Statistic and Matthews Correlation Coefficient (MCC), particularly highlighting their relevance in scenarios with imbalanced datasets. The presentation underscores the importance of model accuracy in real-world applications and briefly introduces regression metrics like R-squared and F-statistic. Additionally, it addresses challenges related to data imbalance and fairness in ML models, stressing the critical need …

Experimental Insights Into Friction Losses Of Post-Tensioned Precast Full-Scale Girders, Mostafa Serry

Theses and Dissertations

The use of post-tensioning in construction has revolutionized the construction industry and made way for several construction and structural applications that were unattainable before. One of the most important topics that are synonymous with the use of post-tensioning is the matter of accurately calculating the short-term and long-term losses that arise in pre-stress. One of the prominent types of losses is the friction losses that occur during the jacking of the concrete elements due to its impact on structural integrity and longevity.

The thesis examines this critical aspect of friction losses in post-tensioned concrete structures. The study focuses on full-scale, …

A Quantitative Approach To Evaluating Multi-Event Resilience In Oil Pipeline Incidents, Labiba N. Asha, Nita Yodo, Ying Huang

Industrial Engineering Faculty Publications and Presentations

This study introduces a quantitative approach to evaluating the resilience of oil pipeline systems against various natural and physical disruptions. Resilience is increasingly essential in critical infrastructure to ensure continuous operations and minimize disruption impacts. However, existing quantitative methods often need specific time-dependent data, making measuring resilience in pipeline infrastructure challenging. To address this gap, this paper proposed a comprehensive framework by integrating the existing incident database with key features of assessing failure probabilities based on historical events and developing multi-event resilience indicators based on system performance under various disruptions. The methodology employs event tree analysis to quantify the probabilities …

Mathematical Model Of Control Of A Pumping Unit Used In The Technological Process Of Wastewater Treatment, Nodira Batirdjanovna Alimova Dsc, Professor, Aziza Ruzimamamovna Khaitova

Technical science and innovation

Strict environmental and health regulations, as well as the cost-effectiveness of wastewater treatment processes, have made control technology an important priority in the wastewater treatment industry. Control strategies operate on input variables (setpoint values) by choosing the values they should take to influence the evolution of state variables so that output variables (controllable variables) achieve desired values. The object is a pumping unit used in wastewater treatment technology, and its mathematical model is a set of structures reflecting the characteristics of the simulated processes. The main parameters in mathematical models are temperature and vibration level during pump operation, coordinates of …

Application Of Satellite Interferometry To Tailings Damages To Determine Their Stability, Mukhlisa Khasanovna Rakhimova

Technical science and innovation

In our country and abroad, the construction of special alluvial hydraulic structures - tailings storage facilities - is being carried out on a large scale for storing waste from the mineral enrichment process, the operation of which requires ensuring and observing strict technological control, failure of which leads to serious accidents and even disasters. Tailings dams play a critical role in the mining and metallurgy industry by providing safe storage of production waste. However, their stability and safety are a constant concern. Satellite interferometry (InSAR) is an innovative technology that can effectively monitor deformations and changes in the condition of …

Enriched Microbial Consortia From Natural Environments Reveal Core Groups Of Microbial Taxa Able To Degrade Terephthalate And Terphthalamide, Laura G. Schaerer, Sulihat Aloba, Emily Wood, Allison Olson, Isabel B. A. Valencia, Rebecca Ong, Stephen Techtmann

Michigan Tech Publications

Millions of tons of polyethylene terephthalate (PET) are produced each year, however only ~30% of PET is currently recycled in the United States. Improvement of PET recycling and upcycling practices is an area of ongoing research. One method for PET upcycling is chemical depolymerization (through hydrolysis or aminolysis) into aromatic monomers and subsequent biodegradation. Hydrolysis depolymerizes PET into terephthalate, while aminolysis yields terephthalamide. Aminolysis, which is catalyzed with strong bases, yields products with high osmolality, which is inhibitory to optimal microbial growth. Additionally, terephthalamide, may be antimicrobial and its biodegradability is presently unknown. In this study, microbial communities were enriched …