Engineering Commons^™

Sustainable Hospitals Lighting Design Optimization To Enhance Patient Well-Being, Merna R. Ashac, Rania F. Ismail, Nasreen Fathy Abdelsalam

Mansoura Engineering Journal

This research investigates the critical role of lighting design in hospitals environments, focusing on its impact on patient outcomes and environmental sustainability. By integrating energy-efficient LEDs and natural light, the study aims to enhance patient well-being and staff performance. To achieve this, the research explores aligning artificial lighting with circadian rhythms to improve both patient outcomes and staff performance. Using mixed-methods approach, the research includes a literature review, case studies, and analysis using DIALux simulation software. The literature review achieves a framework for sustainable, human-centric lighting, while case studies provide practical insights into effective designs in patient rooms. DIALux simulations …

Evaluating Machine Learning Techniques For Breast Cancer Detection: A Comprehensive Review, Owen Kresse, Youssef Kamel Kamel Hassan Rezk, Alaaelddin Ibrahim Said, Rana Hossameldin Mousa, Merna Adel Abdelrahman Ibrahim, Ahmed Fathy Sweed, Tomas Pegorari, Pablo Nakasato, Ainhoa Osa-Sanchez, Itxasne Del Barrio, Francesc Serra Crespí, Keltse Santisteban Ortiz, Naiara Melián Eguia, Mohamed Elsharkawy, Ibrahim Abdelhalim, Begonya Garcia-Zapirain, Ayman El-Baz

Mansoura Engineering Journal

Breast cancer is considered one of the most common types of cancer among women. significant amount of effort done in early detection to increase survival chance since early detection is a challenging task especially in certain breast cancer conditions or using inefficient imaging modalities AI demonstrated significant potential in breast cancer detection algorithms including convolutional neural networks (CNNs) and Transformers, which have achieved highly accurate results but they have some limitations, such as the large amounts of data required for training as CNNs rely on local features, while Transformers focus on global features However, recent research has proposed hybrid models …

Photocatalytic Production Of Hydrogen From Sodium Borohydride Using Tio2/Mwcnt, Ahmed S . Sewerky, Ibrahim Gar Al Alm Rashed, M.M. El-Halwany, Mohamed R. Elmarghany

Mansoura Engineering Journal

In this research, a novel photocatalyst composed of titanium dioxide TiO2 supported on multi-walled carbon nanotubes (MWCNTs) was synthesized using the sol-gel method to produce hydrogen H2 from the hydrolysis of sodium borohydride NaBH4. The TiO2/MWCNT composite’s photocatalytic activity was examined under ultraviolet (UV) light irradiation, with UV lamps used as the source. The experiments were repeated at different temperatures and varying catalyst doses to analyze their effects on H2 generation. The synthesized photocatalyst was characterized through structural, morphological, and compositional studies using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDX). The findings reveal that …

The Impact Of Direct Emergency Policies Of Corona Pandemic On The Education Process Affecting Economic Labor Productivity, Shimaa Mohammed Hamdy Derbala, Usama Helmy Mohmmed

Mansoura Engineering Journal

This research examines the impacts of immediate emergency policies of the Corona Virus pandemic on the education process at Minya University; Egypt; along with impacts on economic labor productivity. It hypothesizes that academic performance of graduates during the pandemic declined, including impacts on employment, quality of labor, and economic productivity.The research reviews experiences of Malaysia, KSA, Kuwait, and Egypt in managing the education process during the pandemic. Two questionnaires were used, to analyze students’ satisfaction with the experience of distant teaching/learning, and to analyze workers’ satisfaction with the efficiency of economic labor productivity during the pandemic. SPSS Non …

Survey: A Study On Image Encryption Using Dna In Bioinformatics, Rana M. Zaki, Zaed S. Mahdi, Matheel E. Abdulmunim

Journal of Soft Computing and Computer Applications

One area of study between computer science and biology is bioinformatics, which deals with methods for collecting, processing, storing, and evaluating biological data. Sequences of RiboNucleic Acid (RNA), DeoxyriboNucleic Acid (DNA), and proteins make up biological data, which has a wide range of uses in domains such as feature extraction, data segmentation, data security, and more. In cryptography, DNA sequences are used as data carriers, enhancing the unique properties of biomolecules. This approach involves using DNA sequences to enhance the security of confidential data that must be transmitted over networks or stored securely. Several DNA-based security techniques have been developed, …

New Feature Selection Using Principal Component Analysis, Zaid Mundher Radeef, Soukaena Hassan Hashem, Ekhlas Khalaf Gbashi

Journal of Soft Computing and Computer Applications

Dimensionality reduction techniques streamline machine learning by reducing data complexity, improving model accuracy, and cutting computational costs. They remove noise and irrelevant features, making models faster and more efficient. These techniques also enhance data visualization and interpretation by condensing data into manageable, insightful dimensions. Ultimately, dimensionality reduction leads to simpler, more interpretable models without sacrificing critical information, making it a cornerstone of efficient data analysis and machine learning applications. Theoretically, feature extraction tends to create new features that encapsulate more information by combining multiple existing features, resulting in more concentrated and informative features. In contrast, feature selection involves choosing a …

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 …

Improved Rapidly-Exploring Random Tree Using Firefly Algorithm For Robot Path Planning, Dena Kadhim Muhsen, Firas Abdulrazzaq Raheem, Yuhanis Yusof, Ahmed T. Sadiq, Faiz Al Alawy

Journal of Soft Computing and Computer Applications

In robotics, efficient path planning makes robots work independently and move through changing environments over time. This study combines the Rapidly-exploring Random Tree (RRT) architecture with the Firefly Algorithm (FA) to make robot’s path-planning better. The proposed ERRT-FA, which stands for "Enhanced RRT with Firefly Algorithm", generates better routes using Firefly social habits. Plan routes using Firefly social habits can effectively aid in exploring configuration space. The role of the FA is to enhance the RRT algorithm by providing an optimized exploration of the search space, ultimately leading to optimizing the path found by the RRT algorithm and better paths …

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 …

Optimizing Bioethanol Production From Solanum Torvum (Devil's Thorn): An Evaluation Of Conversion Efficiency And Invasive Plant Management Potential, Jaya Ashwin D S, Navaneeth K, Abhay Mahesh Baadkar, Supriya S Sundar, Bhoomika B J

Manipal Journal of Science and Technology

Solanum torvum, commonly known as the Devil’s thorn, is an invasive species present in India that causes negative ecological consequences. However, given its abundance and high starch content in the plant, it could be utilized as a potential feedstock for sustainable biofuel production. We aim to explore the feasibility of bioethanol production from S. torvum and its potential as a means of managing this invasive species. The study will take on a comprehensive approach, including techniques for optimizing starch extraction and improving its accessibility. Fermentation with suitable strains of microorganisms, and analysis of bioethanol yield. In addition, the study will …

Genetic Algorithm-Based Design Solution Of An Area Lighting Scheme - A Case Study, Prabhat Mishra, Arnab Ganguly, Amartya Roy, Mihir Kumar Manna, Abhik Hazra

Manipal Journal of Science and Technology

In this paper, a Genetic Algorithm (GA)-based approach is taken for the lighting design of a specified area. The design of an area lighting scheme primarily depends upon the application of that area and accordingly target values of lighting design parameters are to be decided from relevant BIS (Bureau of Indian Standard) lighting codes. There are several design variables, viz., light distribution, aiming of the luminaire, pole spacing, luminaire mounting height, grid dimension over the field, etc. The task of a lighting designer is to achieve the target design parameters through a suitable combination of set design variables and design …

Field Oriented Control (Foc) Of Permanent Magnet Synchronous Motor (Pmsm) Applied In Electric Vehicle (Ev), Unnikrishnan P C, Delgin Saji, Ashwini M, Georgee Cleetus, Joshua Andrews Chandy

Manipal Journal of Science and Technology

Synchronous motors are the most commonly used steady-state three-phase AC motors in electrical systems. The synchronous speed of these motors remains constant, being equal to the supply frequency and its rotational period corresponding to the integral number of AC cycles. So, these motors are mainly used to improve the power factor in power systems.

The paper focuses on field-oriented control of a permanent magnet synchronous motor to effectively control its speed and torque. AC motors only have stator currents, so separate control mechanisms such as vector controls are required to control the motor’s operation. Field-oriented control is the most commonly …

Contingency Analysis On Transmission Line Of Ieee 9 Bus System, Padmashree K S

Manipal Journal of Science and Technology

Ensuring power system security poses a significant challenge for engineers in the field. Conducting security assessments is crucial as it provides insight into the system's condition in the event of a contingency. The widely employed contingency analysis technique serves to anticipate the impact of outages, such as equipment failures or transmission line disruptions, enabling pre-emptive measures to maintain system reliability. However, analyzing each contingency offline is arduous due to the extensive number of system components, with only select contingencies posing severe threats to the system. Computing performance indices for every scenario is a step in the contingency selection process, which …

An Energy-Efficient Clustering Technique Of Heterogeneous And Homogeneous Wireless Sensor Networks, Ahmad Alkhayyat, Rohit Sharma

NJF Intelligent Engineering Journal

The technology of wireless sensor networks (WSN) has recently gained widespread recognition as an emerging one. A WSN consists of a set of sensors powered by batteries. Inaccessible locations usually make it difficult to replace or recharge sensors' batteries. These networks are plagued by energy consumption, which is the main problem. The clustering algorithms are remarkably effective in dealing with such problems in this regard. As a result, this technique appears to help reduce node energy consumption, which ultimately increases the network's lifespan. Heterogeneous and homogeneous clustering algorithms exist. In homogeneous clustering algorithms, all nodes have the same technical characteristics, …

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.

New Forced Convection Flow Of Nanofluid Within A Partially Filled Porous~Straight Channel, Ammar I. Alsabery, Ali Sahib Abosinee

NJF Intelligent Engineering Journal

This study specifically examines how the movement and dispersion of nanoparticles affect heat transfer in a linear channel that contains a partially porous medium. The existing body of literature is lacking a comprehensive understanding of the convective heat transfer of nanofluids in porous channels. This presents an open research topic that demands further investigation. The porous channel is modelled using Finite Element Method (FEM) for steady flow. The assumption of thermal equilibrium model is made between the solid phases and nanofluid. The non-uniform distribution of nanoparticles within the channel is postulated. Consequently, the equation for the distribution of volume fraction …

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 …

Comparative Analysis Of Nature-Inspired Optimization Algorithms: Applications, Challenges And Future Directions, Prerna Mann

NJF Intelligent Engineering Journal

With the proliferation of data generation, the process of achieving optimal solutions is getting more complex. It is becoming increasingly clear that intelligent metaheuristics algorithms are the way to go for solving these complicated optimisation problems, particularly when faced with several restrictions. The development of effective methods for dealing with these optimisation challenges has prompted the creation of numerous new algorithms. These algorithms are either improving their ability to handle problems in many domains or are investigating new contexts in which they could be useful. The field is advancing at a quick pace, leaving many in the dark about its …

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. …

Strategic Site Selection For Bio-Lng Plant In Indonesia: A Multi-Criteria Scoring Method Approach, Edma Nadhif Oktariani, Yuliusman Yuliusman

Journal of Materials Exploration and Findings

In Indonesia, the energy sector is still predominantly reliant on fossil fuels, with renewable energy, including liquefied biomethane (Bio-LNG), playing a limited role. Nonetheless, Indonesia has significant potential for Bio-LNG development due to its abundant organic waste resources such as Palm Oil Mill Effluent (POME) from palm oil mills. Having approximately 891 Palm Oil Mills in Indonesia and being spread mostly in Sumatra, this study aims to select a strategic location for a Bio-LNG plant that can enhance logistical efficiency and economic viability for the plant. This study uses Multi-Criteria Decision Making (MCDM) methodologies to assess potential sites based on …

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 …

Inspection Program Effectiveness Key Performance Indicator For Pressurized Static Equipment Integrity At Offshore Platform, Teuku Ahmad Haekal, Johny Wahyuadi Soedarsono, Badrul Munir, Muhammad Yudi Masduky Sholihin

Journal of Materials Exploration and Findings

One of the key challenges in asset integrity management system at offshore platform is the lack of visibility regarding performance issues and program effectiveness. Without proper performance measurement systems, it becomes difficult to address positive or negative trends promptly and for management to stay informed about the status and the impact of the inspection program. Therefore, Key Performance Indicator (KPI) is needed to measure inspection program effectiveness to prevent undesirable equipment failures that could lead to Loss of Primary Containment (LOPC) or Process Safety Event (PSE). The developed KPI is the ratio of the number of non-leak inspection findings with …

A Comparative Study Of Conventional And Statistically Active Corrosion Methods For Corrosion Growth Assessment Of A 24-Inch Gas Pipeline, Rudi Rinaldi, Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

Component failures in oil and gas pipelines can have fatal consequences, leading to operational downtimes and environmental damage. Knowledge of the corrosion growth rate is fundamental to pipeline integrity management, as it is essential for risk assessment and decisions related to asset management. This article aimed to compare two approaches for the corrosion growth estimation of the 24-inch offshore gas pipeline: the conventional method versus the Statistically Active Corrosion (SAC) method. This article is based on the in-line inspection (ILI) results of two consecutive assessments from 2020 to 2023 of the entire 73 km of the pipeline. The results show …

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, …

Development Of A Spray Pipe Evaporator For Application On Unproductive Salt Farm Land In Indonesia, Srie Muljani, Ketut Sumada, Alfian Rizki Pradana, Caecilia Pujiastuti

ASEAN Journal of Community Engagement

This article discusses the development of a prototype spray pipe evaporator and its efficiency in producing salt in Indonesia. Due to the length of the salt harvesting season in Indonesia, many salt farmers have closed their business doors, leaving many salt ponds abandoned. The spray pipe evaporator prototype was designed to produce a brine solution with a salinity of 23–24 Be from seawater, which has a salinity of 2.5–3.5 Be, in less than 3 days. This is faster than the conventional process of a brine solution salinity of 24 Be. The prototype spray pipe evaporator was assessed in a 20 …

Hybrid Solar-Rainwater Harvesting System With Mini Turbine Integration For Enhanced Energy Generation, Shamanth Showri N R, Sathvik V. Koushik Mr., Shreya C R, Samarth S

Manipal Journal of Science and Technology

Uniting the sun's rays with the fluidity of water, the combination of solar and waterpower creates a potent force for renewable energy, lighting the way to a greener tomorrow. The proposed hybrid system combines modified solar panels with integrated rainwater collection channels, a central collection point, and mini turbines for electricity generation. Through experimental testing and simulations, the feasibility and effectiveness of the hybrid system are evaluated, demonstrating its potential to maximize energy output in regions with abundant sunlight and rainfall. The results indicate that the hybrid solar rainwater harvesting system offers a promising solution for sustainable energy generation, with …