bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clam Shell Powder as Cement Substitution in Concrete Production
Authors: Abdul Malek A S , Jakaria S Z , Wan Putera Shah W M F I , Mohd Zuki S S , Mohammad Azmi M A , Shahidan S , Mohd Yusof N 
Published: February 2025

Abstract
In this era of rapid development, cement is used extensively in the building sector, resulting in a growing need for cement. This also causes the cost of cement to rise over time, and as a result, the cost of building construction also rises. In addition, the cement production industry is one of the most significant contributors to greenhouse gases. Clamshells are a kind of food waste whose breakdown requires a lengthy time. As a result, one of the methods to limit the disposal of this food waste is by substituting this material for cement in the production of concrete, due to the silica concentration of this clamshell being identical to that of cement. The research objective is to evaluate the compressive strength of concrete mixed with different percentages (5%, 10%, and 15%) of Clam Shell Powder as cement replacement. In addition, OPC and CSP’s chemical composition and microstructure are determined using X-ray fluorescence and Scanning Electronic Microscopy. This research aims to determine if clam shell powder is a suitable substitute for cement. It can be concluded that substituting 5% of cement with CSP gave concrete with similar design strength at 28 days due to CaO content found in CSP is comparable to that found in cement. It was observed that concrete with CSP increases the durability of concrete.
Utilizing mode shape curvature and artificial neural networks for structural damage assessment in beam-like structures
Authors: Hakim S J S , Mhaya A M , Noh M S M , Paknahad M , Tami H , Alshalif A F 
Published: February 2025

Abstract
Damage within a structure refers to changes in both its geometric and material characteristics, resulting in a drop in the stiffness that impacts the structure’s performance adversely. This decrease in stiffness causes alterations in modal parameters, including natural frequencies and mode shapes. Utilizing modal analysis allows for the extraction of modal frequencies and mode shapes, facilitating the analysis of mode shape curvature to detect structural damage. In recent years, artificial neural networks (ANNs) have achieved significant application, mainly for their exceptional capability in pattern recognition, which proves invaluable for identifying structural damage. This article proposes a novel method based on mode shape curvature and ANNs for detecting damage in beam-like structures. Experimental study is conducted to analysis damaged and undamaged structural modal behaviours. A feed-forward neural network with two hidden layers, trained on damage indices from mode shape data, is used to accurately pinpoint damage locations within the structure. The proposed approach for damage detection is validated and proves its ability to precisely pinpoint the location of damage. The results of this study demonstrate that ANNs trained with modal curvatures hold significant promise for identifying structural damage, enabling early detection in beam-like structures and contributing to ensuring their safe operation.
Evaluation of arch bridges using Finite element model updating
Authors: Kurniawan M , Syarif F , Setiawan P R , Ahmadi H , Putri C R 
Published: February 2025

Abstract
The arch bridge at the Islamic University of Riau is the main transportation access to the Faculty of Communication Sciences. Initially, the bridge was designed with a 16-meter span, but it’s currently only 13 meters long due to unexpected changes. Additionally, the bridge’s placement has shifted, affecting its load distribution and foundation due to soil accumulation. This study aims to evaluate the arch bridge’s Finite element (FE) model after updating it. To achieve this, Structural health monitoring systems (SHMS) will be used to assess the structural elements’ durability. One method being utilized is Finite element model updating (FEMU), which aims to improve the accuracy of the model by comparing field measurement data with numerical simulation results. The data obtained from the G-Link 200 USB accelerometer is processed using the ARTeMIS, FEMtools, and MATLAB programs to display the structural modal parameters. The results and discussions of this study indicate that the updated parameters mainly relate to the elastic modulus of the bridge structure. It’s concluded that the updated model, based on natural frequency and mode shape, illustrates that the bridge is still capable of operating normally. This is evidenced by a difference of 0.5885 Hz between the actual and theoretical frequency, indicating that the bridge has not diminished in its capacity.
Evaluating Productivity, Safety and Barriers in Modular Construction System Implementation
Authors: Sarbini N N , Wee Z Y , Thong J W 
Published: February 2025

Abstract
The implementation of modular construction systems in Malaysia is still low as compared to other countries, although it has proven to speed up the construction process. In this matter, this study focused on the productivity and safety that modular construction could offer. Besides, the barrier on the modular construction system implementation in Malaysia is also evaluated. This study employs a mixed research technique, combining a comprehensive literature review and a questionnaire distributed to the respondents via online forms. The analysis utilizes the Fuzzy Delphi method to reach consensus among respondents on the productivity and safety of the modular construction system. The barriers are also evaluated for consensus among the respondents. The findings indicate that modular construction systems have indeed improved site management, reduced construction time, and offered significant advantages in mitigating the risk of accidents and injuries, as supported by consensus. The main barriers to the adoption of modular construction systems include technical challenges and regulatory factors. Conversely, aspects such as supply, demand, industrial attitude, and process are not considered significant barriers. This research contributes to improve the modular construction system implementation in the Malaysian construction industry.
Sustainable Concrete Solution: Utilizing Palm Oil Fuel Ash and Metakaolin in Coconut Shell Aggregate Lightweight Concrete
Authors: Abu Bakar M N R , Ismail M H , Che Rahim N A N , George A F 
Published: February 2025

Abstract
The adoption of sustainable materials in the manufacturing of concrete has received considerable attention in recent years due to the environmental issues linked to conventional cement production. The objective of this study is to examine how the inclusion of palm oil fuel ash (POFA) and metakaolin (MK) as substitutes for cement affects the mechanical characteristics of lightweight concrete (LWC) that incorporates coconut shell as a partial substitute for coarse aggregate. The proportion utilised for MK and coconut shell remained constant, with 10% and 50% substitution, respectively. However, the proportion of POFA varied, ranging from 5% to 20% with increments of 5%. The study concluded that including 5% of POFA in coconut shell LWC resulted in the highest compressive strength with an increase of 68.55%, flexural strength with an increase of 39.29% while the split tensile strength was 32.18% and the lastly, was the lowest water absorption which 3.75% at 28 days of concrete age. Nevertheless, the slump value decreases as the percentage of POFA substance increases.
Site Selection Study of Siren Early Warning System for Community Preparedness due to Potential Dam Calamity: Case Study of Kg Batu Melintang, Jeli, Kelantan
Authors: Mamat Ahmad Fadhli , Amin Mohammad Faiq Md , Mahmood Jaini , Hamid Mohamad Amirul Hafiz Abd , Hussain Mohd. Ramzi Mohd. , Tukiman Izawati , Muda Rahsidi Sabri 
Published: February 2025

Abstract
Effective early warning systems (EWS) for dam disasters rely heavily on the strategic placement of sirens to ensure comprehensive coverage and timely alerts. This study investigates the criteria and methodologies for optimizing siren placement, utilizing Geographic Information System (GIS) technology and multi-criteria decision analysis. By integrating data on population density, geographic features, and flood hydrodynamics, the study identifies optimal siren locations to maximize effectiveness. Population data from recent census reports, geographic data from topographic maps and satellite imagery, and disaster simulation data were analysed to determine high-risk areas and prioritize siren placement. The results demonstrate that strategic placement of sirens with standard coverage radius of up to 1 kilometre can significantly enhance early warning capabilities, even in areas prone to flooding, provided they are strategically placed in densely populated zones. The findings highlight the importance of data-driven site selection in improving disaster preparedness and risk management strategies, ultimately contributing to more effective early warning systems that safeguard lives and property in vulnerable communities.
Effect of organic amendments based on date palm residues on barley crop (Hordeum vulgare L.) in an oasian environment: case of the Oued Righ region, Algeria.
Authors: Tirichine A , Abid A , Hafouda L , Sbih M , Gommeaux M , Boumaraf B , Moussa M , Marin B , Le Guyader E , Kavvadias V , Morvan X 
Published: February 2025

Abstract
The Saharan soils are known to be poor in organic matter and mineral elements essential to plants. In this context, the field trial has been conducted in the experimental station of the National Institute of Agronomic Research of Algeria (INRAA) of Sidi Mehdi Touggourt in order to improve soil agronomic suitability of the region’s palm groves and increase yields. The trial examined the effect of five treatments, including an unamended control and four combinations of organic amendments and/or chemical fertilizer (compost, biochar + compost, biochar + fertilizer and fertilizer alone) on some growth and yield parameters of the barley crop (number of tillers per plant, plant height, and grain yield). A randomized experimental design with three repetitions was used. For all studied parameters, the biochar + fertilizer treatment ranked first compared to the other treatments. In terms of grain yields, it exceeded 51 qt/ha followed by fertilizer treatment (49.9 qt/ha). The compost amendment gave a yield of 36.6 qt/ha. The biochar + compost treatment and the control (cultivated without amendment) were the last with yields of 30.8qt/ha and 27.7 qt/ha, respectively. The statistical study revealed significant to very highly significant differences between treatments depending on the parameters.
Repeat gravity observation using CG5 relative gravimeter since 2014 measurements of A10 absolute gravimeter in Bandung and Blora, Indonesia
Authors: Wahyudi E J , Setianingsih  
Published: February 2025

Abstract
Since 2014 micro-gravity measurements using portable absolute gravimeter A10 and relative gravimeter Scintrex CG-5 at Bandung and Blora, we continue to monitor gravity value at several cities in Java Island, Indonesia. Repeat observation from 2014 to 2024 activities conducted by team from FTTM Geophysics Exploration Laboratory. From this activities, several studies (such as: field camp geophysics, undergraduate final projects, and magister thesis) that using gravity data can be conducted. The studies mainly used to monitor hidrology variation and structural modeling in the subsurface. Repeat gravity observation during ten years (2014 to 2024) cover several cities such as: Bandung, Kebumen, Yogyakarta, Klaten, Blora, Ngawi, Madiun, and Ponorogo. Next study in several cities can be proposed to repeat the observation in several area such as: Nganjuk, Magetan, Pacitan, Sragen, Karanganyar, Wates, Purworejo, Banyumas, Cilacap, Banjar, Ciamis, and Garut. Time-lapse microgravity studies already cover the area in the several vilages in Blora, three Kecamatan of Kota Madiun, several Kecamatan of Ngawi (baseline-survey), and Bandung (since 2010 to 2021). From this work, several gravity values from reference benchmark (BM) shows small changes with standard deviation less then 20 microGal (16 refference stations), while 8 stations provide standard deviation in the range 20 to 82 microGal, and 2 other stations shows higher standard deviation up to 126 microGal.
Interception of Meratus and Java Trends Structures as Controlling the Emergence of the Purwodadi Mud Volcano Complex
Authors: Novianto Ardian , Hidayat Wahyu , Bintarto Bambang 
Published: February 2025

Abstract
The geological phenomena of mud volcano and eternal flame in Purwodadi and its surroundings are geological events that are often the subject of research. The concept of disaster (geohazard) is one of the concerns, especially related to infrastructure development for regional development, especially in Grobogan District (Purwodadi). The distribution pattern of mud volcano on the surface such as Bledug Kuwu, Bledug Ramesan Medang, Bledug Cangkring, Bledug Banjar Lor, Bledug Krewek, Bledug Kesonggo needs to be interpreted to predict the possibility of mudflow occurrence in other places due to infrastructure development. The pattern of mud volcano occurrence is interpreted to be controlled by the geological structure affecting the area. The confluence of structures between the stresses that produce the Meratus pattern and the Java Pattern is interpreted as a weak zone that serves as a mud release path to the surface. This research aims to identify the pattern and development of structures in the study area based on gravity data to reduce potential geohazard in infrastructure development on the surface. Structural analysis was conducted using the gravity method and enhancement data processing using the derivative method. Analysis of subsurface structural patterns based on gravity processing will be validated with seismic data and geological structures on the surface. This combination of analysis is used to interpret the pattern and development of structures that control the emergence of mud volcanoes or mud diapirs that can cause geohazards in infrastructure development. The analysis results based on several methods show that the emergence of the mud volcano phenomenon in the study area is interpreted to occur at the intersection between two major structural patterns, namely the Meratus pattern and the Java pattern. This intersection produces a weak zone that serves as a pathway for mud to escape from the underlying ellisonal basin to the surface as a mud volcano. The distribution pattern of this structural intersection zone becomes a geohazard-prone area so that it can be used in planning infrastructure development on the surface.
Assessment of Seismic Vulnerability and Shear Wave Velocity Estimation Using the Horizontal-to-Vertical Spectral Ratio (HVSR) Method in Umbul Niti Geothermal Manifestations, Jatimulyo Village, South Lampung
Authors: Prabowo Satria Bagus , Wulandari Rizki , Putri Intan Andriani , Nathania Edlyn Yoadan , Nugraha Purwaditya , Sitio Yogi Y. Ch. 
Published: February 2025

Abstract
The discovery of geothermal manifestations in 2021 in Umbul Niti, Jatimulyo Village, South Lampung Regency, reveals significant potential for geotourism development, which can help reduce poverty. However, this potential is accompanied by an unstable zone due to a fault, increasing earthquake risks. Additionally, population growth and the presence of the Sumatera Institute of Technology (ITERA) pose development challenges related to population density and potential losses. Therefore, investigating soil characteristics based on natural frequency (f
0), amplification (A
0), and shear wave velocity at depths of 0-30 meters (

V
s

30

) is crucial for development planning and earthquake risk evaluation through seismic vulnerability values (Kg
). The Horizontal to Vertical Spectral Ratio (HVSR) method was used, revealing f
0 values from 3.876 Hz to 23.695 Hz, indicating sediment thickness variations from thick to very thin, dominated by very thin layers with very low amplification. The f
0 results, correlating with geothermal areas, show the same anomaly contrast as previous studies with 3D gravity model results and residual magnetic anomalies. Additionally, the Particle Swarm Optimization (PSO) method was used to obtain

V
s

30

variations, ranging from hard to soft soil, with the lowest

V
s

30

values near the manifestation. The seismic vulnerability index was generally low, indicating a low earthquake disaster risk in the study area. The cross-section results identified three faults in cross-section A-A’ and two faults in cross-section B-B’, corresponding with the forward modeling in the magnetic method. This research is expected to contribute positively to geotourism development, particularly in planning and disaster risk mitigation. These findings highlight the need for careful planning and risk mitigation to leverage geotourism potential while managing seismic risks. Although the seismic vulnerability index is generally low, some medium risk zones were detected, emphasizing the importance of integrating geotourism development with comprehensive risk management strategies to ensure sustainable geotourism development and community resilience.
Stress Inversion and Fault Instability Analysis of Seram-Buru Region
Authors: Saputra Rifky Wahyu , Diputra Adi Syahwal Ganda , Sahara David Prambudi , Surya Tri Satrio Cahya , Sharfina Nadira Putri , Kusumawati Dian 
Published: February 2025

Abstract
The Eastern Indonesia is situated at the convergence of the Alpine-Himalayan orogenic belt and the Circum-Pacific belt, where the convergence of three tectonic plates generates an area of significant geological complexity and neotectonic activity. This research aims to ascertain the stress regime influencing the Seram-Buru area and its implications on fault instability within the region. The study area encompasses the islands of Seram and Buru, Maluku, utilizing earthquake catalogs and focal mechanism data obtained from the International Seismological Center (ISC) and the Global Centroid Moment Tensor (GCMT), spanning the recording period from January 1st, 1964, to March 31st, 2024, comprising a total of 5198 earthquake catalog entries and 449 focal mechanism data points. Processing involves seismicity analysis of the area, followed by spatial data clustering utilizing a density-based spatial clustering algorithm. Subsequently, stress regime inversion is performed for each clustered area, culminating in an analysis of tectonic instability within the region. The clustering analysis categorizes the data into 5 clusters deemed to correlate well with the neotectonic conditions of the research area, namely shallow subduction earthquakes, intra-subduction earthquakes, and shallow fault-related earthquakes. The results of stress inversion reveal variable shape ratios ranging from 0.5051 to 0.7506, with friction coefficients ranging from 0.3 to 0.85. Sigma 1 exhibits a compressive NE-SW stress regime with a predominantly horizontal plunge, whereas Sigma 3 displays a NW-SE trending stress regime with a predominantly vertical plunge, aligning with the focal mechanism tendencies indicative of uplift faults.
Analysis of the Hypocenter-Epicenter Distribution Based on Volcanic Earthquake of Mount Agung Along January – December 2018 Using the Coupled Velocity-Hypocenter Method and Structural Deformation.
Authors: Nadirah Farah Jihan , Suparman Yasa , Hapsoro Cahyo Aji , Sutrisno  
Published: February 2025

Abstract
The eruption of Mount Agung in November 2017 became one of the largest eruptions in Indonesia. Therefore, after the eruption period, Mount Agung experienced an increase in activity in the year 2018. One of the challenges to warn and alert the citizen about the danger of eruptions is to monitor volcanic activity caused by volcanoes. Monitoring the level of volcanic activity can be conduted by determining the distribution of the hypocenter of the earthquake. In this study, the hypocenter distortion of the earthquake was determined using the Coupled Velocity-Hypocenter method with 2D and 3D plotting. This method produces outputs such as the hipocenter coordinates, the local 1-D velocity model of the P wave, as well as the correction of the station. This model gives the information about the structure of the Earth’s layers through the seismic wave. Based on the calculations that have been [revealed], the distribution of the hippocenter is centered in the southwestern direction of the summit of Mount Agung with a depth range of 1-10 km. This location is associated to the presence of intrusion of magma that forms the dyke resulting in many points of volcanic earthquakes due to magma movement. The type of explosive Mount Agung eruption can affect the structure of Mount Agung as a result of a massive eruption. The deformation of the structures that occurred resulted in changes in the structure of the Earth’s surface, which is it could affect the lava flow path that could be hazardous if there were civilian settlements. This has become one of the key factors in addition to determining the location of the earthquake source, monitoring of structural deformation also needs to be conducted.
Lithology Prediction Using Convolutional Neural Network Algoritm Study Case Poseidon Field Australia Basin
Authors: Komara Eki , Nugraha Muhammad Faiz , Utama Widya , Garini Sherly Ardhya 
Published: February 2025

Abstract
Convolutional Neural Network (CNN) method is one of a machine learning algorithm that is adapted from the the way of human brain works and is used to facilitate the processing of large amounts of data. The CNN method predicts the lithology of a well with well log data, there are Gamma-Ray Logs, Density Logs, Neutron Porosity Logs, and DT Logs. The CNN model is formed by several layers, such as 2 Convolutional Layers, 2 Dense Layers, 0.5 Dropout Layers, and 256 Dense Nodes. Contrary outcomes are observed in predictions that were previously generated utilizing 10 input parameters from Poseidon2, Poseidon North, Well Proteus1, and Poseidon1 data. The lithology frequency of Claystone and Siltstone is the dominant type based on the data from Poseidon2, Poseidon North, and Proteus1 Wells. The Poseidon1 Well data mostly consists of Claystone lithological frequency. The trained model utilizes data from the Poseidon2, Poseidon North, and Proteus1 wells, which exhibit lithology distinct from that of the Poseidon1 Wells. Consequently, the model is limited to predicting lithology based solely on log types that align with the training data.. The amount of 3730 initial data from the Poseidon2, Poseidon North, and Proteus1 wells were entered and trained which later became the CNN model and then tested the 820 new data. The accuracy of the lithology prediction was done by comparing the actual facies with the predicted facies which had an accuracy of 87.9% at the Poseidon2, Poseidon North, and Proteus1 wells. The resulting RMSE value is 1.4. As a result, the CNN method can predict the lithology according to the original facies and identify the lithology of the Poseidon1 well as a target at a depth of 4620 m to 4660 m with Claystone lithology. CNN method can also predict thin layers such as Ferruginous Calcilutite and Altered Volcanic. The input section of the CNN method is required to use well report data that matches the depth data.