bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing Machine Learning to Determine User Interface Elements in Agricultural Mobile Location-Based Services
Authors: Osman Mohamad Jahidi , Idris Nurul Hawani , Mohd Salleh Mohd Radhie , Majid Zulkepli , Ismail Zamri , Othman Nurain 
Published: December 2024

Abstract
The evolution of mobile location-based technology revolutionizes user experiences, providing personalized services and seamless navigation. This transformation influences how individuals interact with information and surroundings, enhancing daily life’s connectivity and convenience. However, creating interactive mobile location-based user interfaces (UI) for diverse users, especially in lower-middle-income countries, poses a significant challenge. Overcoming barriers to technology adoption within this diverse user group necessitates strategic planning to prevent exacerbating the digital divide. It is imperative to comprehend farmers’ preferences and requirements, especially in the context of user interface design. This study aims to determine preferred UI elements using machine learning based on respondents’ demographic characteristics. This investigation examines the user interface preferences of chili farmers in reporting pest and disease incidents through the implementation of a machine learning algorithm. Data was acquired through surveys and field experiments involving specified user interface elements for reporting chili crop issues in Batu Pahat and Johor Bahru. The findings of this study were analyzed using the Random Forest (RF) and Support Vector Machine (SVM) algorithms, and it shows that the image icon and radio button were the respondents’ preferences in stating the name of the disease. Based on the overall accuracy and kappa values, Random Forest is the more effective model for making predictions in this study. The findings support the transition of Malaysian farmers towards becoming intelligent farmers when designing the UI based on the demographic characteristics of farmers, aligning with the objectives of the Shared Prosperity Vision 2030 and endorsing the National Agrofood Policy 2021-2030 (NAP2.0). Additionally, this initiative aligns with the Food and Agriculture Organization of the United Nations (FAO) efforts to digitize farmers, including smallholders.
Semantic segmentation of high resolution imagery using U-Net for classification of sugarcane age in parts of Lumajang Jember Regency
Authors: Jatmiko R H , Rosyadi R I , Yusdipriantono M , Dewi A L F , Dariansyah T A , Afwani M Z , Lestari F N , Raharja M A E 
Published: December 2024

Abstract
Sugar cane mapping at a lower cost and time is an important need for farmers and the sugar industry. Semantic image segmentation with U-Net offers a potential solution to overcome this problem. This research uses high resolution Google Satellite imagery to examine the area around the Jatiroto Sugar Factory in Jember Regency, East Java Province. The aim of this research is to carry out semantic segmentation on high resolution images using U-Net to determine the age classification of sugarcane. The results showed that U-Net was able to achieve sugarcane age classification accuracy of 83.6%. Disturbances in the form of differences in recording and contrast of image mosaic results result in the learning curve experiencing overfitting. Image segmentation reveals the presence of new objects beyond the training data, necessitating future development related to the findings of visual interpretation, field data, and segmentation data. In conclusion, U-Net shows promising potential for sugarcane age classification in Google Satellite imagery. Further research is needed to improve accuracy and overcome the various obstacles encountered.
Visualization of urban growth modelling land use change using cellular automata
Authors: Bhattacharya Apratim , Paul Prabir K. , Khatua Aniruddha , Aithal Bharath H. 
Published: December 2024

Abstract
The phenomenon of urbanization, which is driven by a significant growth in population, leads to the expansion of cities at the cost of reducing Land Cover areas. The necessity of monitoring and predicting urban growth trends lies in the establishment and maintenance of sustainability. The objective of this work is to utilize the Spatial Lag Model to analyze the urban growth pattern of the Asansol-Durgapur region. The aim is to investigate the interconnections between the factors contributing to urban growth. Additionally, The Cellular Automata-based SLEUTH model will be employed to forecast the likelihood of future growth in the region. The accurate modeling and prediction of urban areas necessitate the consideration of multiple variables and the utilization of big datasets, hence posing a significant challenge to researchers. The research reveals that the existence of multimodal infrastructure, such as well-connected roads, highways, and railroads, that offer convenient accessibility, along with neighbourhood development and, the presence of vacant lands in the vicinity, has a crucial role in driving population migration toward urban regions, hence contributing to urban expansion. These results aid in developing policy measures and sustainable actions to mitigate urbanization’s anthropogenic effects. Integrating machine learning with the models and continuous data updates are recommended for better urban growth predictions.
Reviewing the versioning in 3D city model to track building history and progress
Authors: Idris Nabila Husna , Azri Suhaibah , Ujang Uznir 
Published: December 2024

Abstract
Managing information regarding building history and progress poses significant challenges, particularly in contexts such as construction, renovation, or demolition within urban environments. This study reviews the importance and application of versioning as a solution to address these challenges. Versioning offers a systematic approach to documenting changes over time, facilitating the tracking of building evolution. In the context of 3D city models, versioning provides advantages such as enhanced visualization and analysis capabilities, enabling stakeholders to better understand the development trajectory of urban landscapes. Versioning serves multiple crucial functions within the realm of 3D city models. Firstly, it enables the depiction of temporal information, aligning with the model’s time dimension and delineating key events such as generation, modification, or destruction. Additionally, versioning acts as a vital backup and recovery mechanism, affording users the ability to revert to primary iterations should issues arise. Moreover, it plays a pivotal role in ensuring rigorous quality control, necessitating thorough examination and approval of each model iteration before progression. This study aims to delve into the significance and practicality of versioning within the context of 3D city models, employing CityGML and CityJSON formats for comparative analysis. By scrutinizing the benefits and limitations of versioning across these data models, the research sheds light on its nuanced implications. Furthermore, it surveys prior research endeavors utilizing versioning and temporal data in 3D city model applications, offering insights into existing methodologies and their efficacy. Ultimately, the investigation reveals the complexities associated with implementing versioning, particularly within the CityGML framework, attributed to its intricate schema.
Building footprint extraction from aerial imagery through semantic segmentation techniques
Authors: Teo Tee-Ann , Chen Pei-Cheng 
Published: December 2024

Abstract
The extraction of building footprints from aerial images is crucial for creating detailed topographic maps. Leveraging advancements in artificial intelligence, particularly deep learning, presents a promising avenue for enhancing the automation of this extraction process. This study aims to establish a methodology that employs deep learning semantic segmentation technology to detect and reconstruct building footprints from digital aerial images. The methodology encompasses several key steps: generating true-ortho images from multi-view aerial images, constructing dataset for building regions, employing deep learning semantic segmentation, and regularizing the detected building footprints. The test area is located in Hsinchu, Taiwan. The experiment utilizes 25cm aerial true-ortho images for building region detection through the TransUNet semantic segmentation method. An additional data covering approximately 7km2 was utilized as an independent check region. The precision and recall metrics for building detection achieved 90% and 91%, respectively. Post-boundary regularization, the extraction of building footprints from the identified building regions was successfully executed. This proposed scheme shows the efficacy of automatically extracting building footprints by integrating aerial orthoimagery with deep learning technology, significantly benefiting the creation of precise topographic maps.
Estimation of elephant home range in Endau-Rompin (Peta) National Park using geospatial approach
Authors: Mohd Salleh Nurul Anisah , Hassan Noordyana , Tarmidi Mohamad Zakri 
Published: December 2024

Abstract
The tropical rainforest coverage is decreasing has caused wildlife habitat lost. Instead of that, the wildlife especially elephants have lack source of food. Due to that, the elephants tend to go to the areas near the forest and human settlements. This problem has contributed to the occurrences of human-elephant conflict. To overcome this problem, the estimation of elephant home range is crucial as one of the approaches in establishment of wildlife corridor. To estimate the elephant home range in Endau-Rompin National Park (Peta), the habitat suitability model was utilized. The factors that characterise the elephant home range has been identified based on weighted overlay analysis based on the literature review. The parameters involve are Digital Elevation Model (DEM) data, Normal Difference Vegetation Index (NDVI), proximity to river, Land Surface Temperature (LST), Slope and land use and land cover (LULC). Buffer analysis is used to identify surrounding geographic features. Results shows that LULC was the highest weight (30 %) as influence on elephant habitat suitability. While proximity to river, slope and NDVI were weighted with 20%. The habitat suitability has shown the elephant home range of year 2018 to 2020 was increasing. As a conclusion, the weighted overlay can identify the factors that gives effects to elephant home range. However, lack of detailed information for each environmental variables on how the factors would affects.
Potential applications of remote sensing and Earth observation approaches to monitor mangrove ecosystem services: A review
Authors: Roslani Muhammad Akmal , Ismail Mohd Hasmadi , Kamarudin Norizah 
Published: December 2024

Abstract
Remote sensing technologies offer significant potential for monitoring mangrove ecosystems, which serve as invaluable hubs of biodiversity and providers of crucial ecosystem services (ESs). In the face of mounting threats from human activities and climate change, effective monitoring becomes paramount to safeguarding their health and the services they offer. Remote sensing and Earth observation techniques present exceptional opportunities for monitoring mangrove ecosystems and their ESs. Despite the successful use of remote sensing and Earth observation-based technologies in mapping and monitoring mangrove ecosystems, few studies have been undertaken to utilize them for assessing mangrove ESs. This paper explores the vast potential of remote sensing and Earth observation in monitoring mangrove ecosystems and assessing their ESs. Through a comprehensive review and discussion of relevant scientific literature, researchers also have employed various sensors to study carbon stocks, species diversity, biomass, and related topics. These findings provide a set of values data essential for protecting, preserving, and conserving these ecosystems and their resources, thereby facilitating better management, planning, and policymaking. By leveraging these technologies, policymakers, scientists, and conservationists can make informed decisions to conserve mangrove ecosystems and ensure their long-term viability.
Community-based mobile crack monitoring for landslide inventory
Authors: Jekop Advero Reyes , Idris Nurul Hawani , Ishak Mohamad Hafis Izran 
Published: December 2024

Abstract
Landslides are a common natural disaster that can cause significant damage and loss of life. In Malaysia, the current methods for monitoring and mapping landslides are mainly based on satellite imagery and field surveys. There is a lack of targeted platforms to engage communities in landslide monitoring within their neighbourhoods, with the existing platforms not specifically focusing on involving communities in landslide monitoring. Therefore, this study aims to propose a community-based crack monitoring mobile app for landslide inventory. The objectives included 1) identifying suitable data and information for a community to report landslide activities within the neighbourhood and 2) developing a mobile application for monitoring structural cracks for landslide inventory. The methodology involved five phases: planning, analysis, design, system development, and system evaluation. The findings highlighted the lack of targeted platforms for community engagement in landslide monitoring, proposing a friendly mobile application for the community to report landslides in their area. The application includes several key modules, such as user registration and authentication, data submission and retrieval, and mapping and visualisation. This study offers significant benefits by enhancing public awareness and participation, timely reporting of potential landslide risks, and practical mitigation efforts, ultimately minimising the impact of landslides and saving lives.
Assessment of sustainable geothermal potential in Patigi region, North-Central Nigeria
Authors: Salaudeen S. A. , Adagunodo T. A. , Sunmonu L. A. , Suleman K. O. , Ayanbisi O. W. , Oladapo O. F. 
Published: December 2024

Abstract
This study examines the geothermal potential in the Patigi region of Nigeria to address local and national power challenges. The study area and its environs are currently experiencing a power outage for the past three years. As energy is one of the most vital factors that facilitate development in a region or country at large.Aeromagnetic data were utilised to determine the geothermal potential, which could be added to the energy mix to boost the energy supply in the region. The geothermal parameters that were established from the study are the Curie point depth, geothermal gradient, and heat flow. The residual map was segmented into nine overlapping spectral blocks, and the logarithm of spectral energies was plotted against wave number. From these plots, the centroid depth (Z0) and the depth to the top boundary (Zt) were derived to calculate the Curie point depth (CPD), geothermal gradient (GG), and heat flow (HF). The results indicated that the Curie point depth values ranged from 34.09 km to 55.19 km, with an average of 41.87 km. The geothermal gradient values varied from 10.51 to 17.01 °C/km, averaging 14.13 °C/km. The heat flow values spanned from 26.27 to 42.53 mW/m², with an average of 35.32 mW/m². The deepest Curie point depth was observed in the central and northeastern parts of the study area, while shallower depths were found in other parts. Geothermal and heat flow contour maps highlighted hotspots in the southeastern and eastern regions, including Kusoji, Rogun, Ekopapo-Yagi, Etsufu, Sankwafuji, Momba, Koro, and Rodun. These hotspots are deemed suitable for geothermal energy exploitation, potentially addressing the power challenges in the study area and throughout Nigeria.Developing geothermal energy resources in Nigeria can significantly help achieve sustainable development goals 7, 9, 11, and 13. It could also enhance a reduction of unemployment and poverty in Nigeria.
Greener Technology of Producing Polyhydroxyalkanoate using Anthracene as Carbon Source
Authors: Akinwumi A.R. , Nwinyi O.C. , Ayeni A.O. , Mohan S.V. 
Published: December 2024

Abstract
The study investigated the potential of Bacillus cereus AAR-1 (OQ999178) to simultaneously degrade anthracene, a toxic environmental pollutant, and produce polyhydroxyalkanoate (PHA), an eco-friendly and sustainable biopolymer. Using a Taguchi L16 (4*3) array for optimization, it was found that a 10% seed inoculum, grown for 8 days in a minimal salt medium containing 400 ppm of anthracene and 2 g/L of NH4Cl as carbon and nitrogen sources, respectively, maximized anthracene degradation and PHA accumulation by B. cereus AAR-1. The bacterial biomass had a colony count of 1 x 106 cfu/ml and produced 286 mg/L of biopolymer, as extracted using a hypochlorite-chloroform solvent method. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed the biopolymer as PHA. This study identifies a key hydrocarbon-degrading bacterium at a municipal dumpsite, which plays a significant role in environmental biotechnology by supporting cleaner and greener technologies. This contribution aligns with the goals of SDG 12 and 14.
Environmental Impact of Pre-occupational radon level measurements in medical imaging facilities of a tertiary hospital in south-west Nigeria
Authors: Aremu A. A. , Oni O. M. , Oladipo A. E. , Oladapo O. O. , Obafemi Y. D. , Oniha M. I. , Babarimisa I. O. , James U. E. 
Published: December 2024

Abstract
Radiation facilities are placed in an enclosed environment to prevent scattered radiation from getting out of the room, by so doing the rooms foil gas exchange from the outdoor environment, thereby increasing the radon concentration in the indoor air. This study aimed at estimating the occupational radon exposure level in medical facility room in order to estimate the radiological risk in such environment. RAD7 electronic device was used to measure the indoor radon concentration in the five proposed rooms in the newly built Radiology department of a University Teaching Hospital while a digital thermometer was used to measure the ambient temperature. The radon concentrations ranged between 12.09 Bq/m3 and 58.52 Bq/m3. The ultrasound room has the least average value of 12.09 Bqm−3 and the Fluoroscopy room has the maximum average value of 58.52 Bqm−3. The radon level translated into the effective dose, working level and excess life-time cancer risk for any worker staying for a period of nine hours per day, over a year. Fluoroscopy facility was estimated to present the highest annual absorbed dose and annual effective dose with 0.73 mSvy−1 and 0.8858 mSv y−1, respectively. The mean radon concentration for the five rooms was 41.96Bq/m3. The calculated annual effective dose rate and the mean annual absorbed dose rate to the lung within the radiation facilities rooms were 0.529 mSvy−1 and 0.6350 mSv y−1, respectively. The indoor radon concentrations measured and the effective dose value of 200 Bq/m3 and 1 mSvy−1 respectively is below the reference limit set by International Commission Radiation Protection (ICRP) Agency. This implies that the radiation facility rooms are in conformity with international best practices and this is in agreement with SDG 3 (Good Health and well –being)
Effective Sustainable Vector Control of Anopheles gambiae in Ota
Authors: Adedoyin E. D. , Cleanclay W. D. , Iheagwam F. N. 
Published: December 2024

Abstract
This study investigates the resistance status of Anopheles gambiae in Ota to malathion, fenitrothion, alphacypermethrin, and deltamethrin, and its implications for sustainable vector control and public health. Female larvae and pupae were collected from breeding sites in Atan and Nestle areas using the standard dipping method and reared to adulthood (2-5 days old, non-blood-fed). These adult mosquitoes were then assessed for responsiveness to malathion (5%), fenitrothion (1%), deltamethrin (0.05%), and alphacypermethrin (0.05%) following World Health Organization standard protocols. Genotypic analysis of knockdown resistance (kdr) alleles in the resistant mosquito population was conducted using polymerase chain reaction. The mortality rate of the mosquitoes to malathion and fenitrothion (100%) exposure was higher than alphacypermethrin (11.8%) and deltamethrin (12.5%). Contrary, the 50% and 95% knockdown time thresholds of alphacypermethrin (1.47 ×108 and 2.57×108 min) and deltamethrin (190.12 and 319.53 min) were higher than malathion (52.86 and 84.02 min) and fenitrothion (53.35 and 90.71 min). The kdr allele frequency was 100% for alphacypermethrin resistance and 23.5% for deltamethrin. This study shows the high efficacy of malathion and fenitrothion for mosquito control and potential resistance to alphacypermethrin and deltamethrin in Ota. Robust mosquito surveillance and resistance profiling on a large scale is required in Ota for effective sustainable vector management and malaria eradication promoting good health and wellbeing.
Sustainable Role of Terminalia catappa Extract for Maintaining Antioxidant Activities in Wistar Rats
Authors: Iheagwam F.N , Adedoyin E.D 
Published: December 2024

Abstract
Oxidative stress is linked to various diseases, including cancer and cardiovascular disorders, due to the imbalance between reactive oxygen species and the body’s antioxidant defenses. The use of natural antioxidants presents a sustainable approach to mitigating oxidative damage, aligning with Sustainable Development Goals 3 and 12. This study evaluates the impact of repeated oral administration of Terminalia catappa aqueous extract (AETC) on antioxidant activities in Wistar rats over 28 days. The enzymatic activities and non-enzymatic concentration of endogenous antioxidants were investigated in the plasma and tissues at the end of the experiment. Results indicated increased renal superoxide dismutase, hepatic peroxidase, erythrocyte and renal glutathione-S-transferase activities. Hepatic reduced glutathione concentration was increased while plasma and renal malondialdehyde concentrations were reduced. These results emphasise AETC’s tissue-specific antioxidant effects and its potential as a protective agent against oxidative damage, consolidating the ethnobotanical use of Terminalia catappa leaves as a tonic for health-improving benefits promoting good health in addition to advocating for ecofriendly and sustainable health solutions. Further elucidatation of AETC antioxidant mechanisms and optimisation of its therapeutic applications is required.