bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management and controlling of processes in the field of energy saving on the basis of Industry 4.0
Authors: Kuzmynchuk Nataliia , Fedorenko Irina , Kutsenko Tetiana , Aloshyn Serhii 
Published: December 2024

Abstract
Improving the energy saving system requires implementing particular management style based on controlling tools aimed at developing energy-efficient solutions and taking reasonable decisions that will ensure competitiveness of industrial enterprises. The aim of this study is to provide a two-component assessment of the level at which industrial enterprises are ready to implement innovative technologies in the field of energy saving in the context of Industry 4.0 using analytical and instrumental support of the management and controlling system. Analyzing the impact of innovation potential of industrial enterprises grouped by the values of innovation potential indicators on the level of their competitiveness has been carried out within the groups taken. The impact of innovation potential components on competitiveness level has been determined only for industrial enterprises of the third group. The defined correlation-regression model for industrial enterprises of the third group contributes to determining the influence of innovation potential components on the level of competitiveness. It has been proven that application of this approach makes it possible to solve a critical task of accelerating the development of Industry 4.0 technologies towards energy saving automation and digitalization, in particular, it has significantly increased the interest of industrial enterprises in transformational changes. It has also been substantiated that improving the energy saving system at industrial enterprises with the use of controlling tools allows for creative transition to Industry 4.0, which determines the current development trend of automating the energy resource management and digitizing the production processes.
Green Building Implementation in Campus Settings
Authors: Herzanita Ayu , Trisno Lestari Rini , Prautama Dewi Atri , Airunnisa Virginia Nur , Fairuz Insyirah Amirah 
Published: December 2024

Abstract
Many universities have declared themselves as green campuses to integrate sustainable development into education. One effort to implement a green campus is by improving infrastructure to be more environmentally friendly through the construction of green building. This study aims to identify the green building elements that have been implemented at the Faculty of Engineering Building at Pancasila University (FTUP). The green building elements that will be identified are appropriate site development, energy efficiency and conservation, water conservation, material resources and cycle, indoor health and comfort, and building environment management. Data collection methods are carried out by observation, interviews and archive analysis. Data analysis is conducted descriptively. The results of the study indicate that the elements that have been applied include appropriate site development, energy efficiency and conservation, material resources and cycle, and indoor health and comfort. There needs to be an increase in the implementation of green buildings so that the target of a green campus will be achieved.
Features of Reflectance Spectroscopy and Geochemistry Towards REE Mineralization in Weathered Granitic Clays
Authors: Nugraha A A S , Syafrizal  , Hede A N H 
Published: December 2024

Abstract
The rising global demand for rare earth elements (REEs) has intensified exploration efforts, particularly in regions like Indonesia with significant REE potential. This study explores the use of reflectance spectroscopy for rapid identification of REE-bearing clay minerals derived from weathered granite in West Kalimantan. Clay samples from distinct weathering horizons were analyzed using X-ray diffraction (XRD), inductively coupled plasma mass spectrometry (ICP-MS), and reflectance spectroscopy. XRD confirmed the presence of kaolinite, dickite, gibbsite, and quartz, indicating their formation as weathering products of the host granite. While ICP-MS revealed that REE concentrations in the clay samples were lower than in the host rock, this observation suggests that the REE enrichment process within the clay minerals may still be ongoing or influenced by specific local geochemical conditions. Reflectance spectroscopy identified key clay minerals based on their characteristic absorption features in the shortwave infrared (SWIR) region. However, direct detection of REE-related absorption features was challenging due to the likely low concentrations and potential masking by iron oxides. This study highlights the potential of reflectance spectroscopy as a valuable tool for initial screening and identification of clay minerals in REE exploration, particularly when combined with other analytical techniques. Further research focusing on enhancing spectral analysis methods and targeting areas with potentially higher REE concentrations will be crucial in maximizing the effectiveness of this technique for REE resource discovery.
Application of Source Independent Full Waveform Inversion to Land Seismic Data: A Case Study of Donggi Field, Indonesia
Authors: Winardhi Sonny , Saputra Sigalingging Asido , Dinanto Ekkal 
Published: December 2024

Abstract
Full-waveform inversion (FWI) is a data-fitting process based on seismic full-wavefield modeling that provides high-resolution images of subsurface geological structures from observed field data. However, its applicability to real-world scenarios, particularly in land data, is limited due to several factors. These factors include the lack of modeling of strong surface waves, converted waves, phase dispersion, near-surface weathering layer distortion, and wave phenomena such as attenuation energy and distortion because of complex geology. Additionally, the source wavelet information is often missing for land surveys, and recorded waveforms can vary significantly due to spatially variant shot characteristics such as source charge size, shot depth, and hole pattern, as well as the distortion caused by the near-surface weathering layer. In this study, we address the main challenges of seismic data with a low signal-to-noise ratio and an unknown correct source wavelet. To solve for the unknown source wavelet, we use a source-independent objective function and perform several preprocessing techniques on the seismic input to improve the signal-to-noise ratio without significantly changing the amplitude. We use velocity analysis data as a prior model to reduce the non-linear problem. We demonstrate the effectiveness of our technique by applying it to land seismic data from the Donggi Basin in Indonesia, and our results show that the velocity model improves and has a better correlation with well-log data.
Evaluation of Depth Dependent Seismic Anisotropy within Limited Offset on Vertical Transverse Isotropy Media: Deep Water Reservoir Case Study
Authors: Oktariena Madaniya , Triyoso W , Fatkhan  , Sukmono S , Septama E , Wardaya P D , Murdianto B S 
Published: December 2024

Abstract
Hydrocarbon bearing sediment in deep water reservoirs are uniquely characterized by the body of water being an additional weight on the top of vertical sedimentary layering. While large aerial extent of deep water reservoirs is known for their ability to contain substantial amount of reserves, they come with technical difficulties mainly in acquisition and imaging aspect. Deep water seismic imaging more often than not suffers from the hockey stick effect found in the long offset. At the same time, the presence of hockey stick in seismic long offset could be utilized as a tool to extract anisotropy information from seismic data. However, the deep target level requires a rather long offset in seismic data to be able in capturing a proper hockey stick condition. This research intends to evaluate seismic anisotropy behaviour in various depth level within a limited offset range instead of the commonly used very long offset. Seismic related anisotropy (η) is extracted from travel time error as a delta to the isotropic travel time. The extracted anisotropy η is to be plotted against several known VTI travel time approximation in order to identified the equation that most fitted to the deep water real data condition. Several depth levels are to be analysed as an attempt to capture depth related variation in multi reservoir scenarios. Observation is conducted on PMBG Seismic Gather around several well location as point of validation. The result shows indication of seismic anisotropy degree variation within progressed depth that could be concluded as depth dependant behaviour. The fact that the observed area has a typical character of weak anisotropy which only has a small impact on seismic data encourages a possibility to delineate anisotropy from seismic data with a certain treatment. Analysis on limited range offset seismic promotes the utilization of old vintage seismic data for seismic anisotropy extraction that contribute to the vision of using a new insight on the existing data as part of enhanced oil recovery strategies.
A High Resolution of Terrain Gravity of Bandung Area
Authors: Gunawan I , Prasetyo N , Alawiyah S 
Published: December 2024

Abstract
The Bandung basin spans around 30 km by 60 km and is encircled by mountains. Therefore, the gravity due to terrain variations has significantly contributed to the area’s Complete Bouguer Anomaly (CBA). In this study, we have applied a high resolution of terrain gravity (TG) using the block of rectangular prisms with 100 m x 100 m x 10 m dimensions. The investigation includes up to 70 km x 100 km terrain areas where the data was obtained from the shuttle radar topography mission digital elevation model (SRTM DEM). The results show that the southern region has about 20 mGal TG higher than the northern region due to more and higher mountain variation. Our investigation also found that the reasonable terrain areas included in the calculation must be at least 40 km wider from the outer gravity stations to get less than one mGal change in the 5 km terrain area width change. This result gives a good overview of the terrain effect on gravity calculation and interpretation, especially in the Bandung area.
The Early Study for Nature-Inspired Algorithms in Geophysical Modeling Based on Gravity Method: Prototype Bat Algorithm in 3D Gravity Inversion
Authors: Prasetyo Nugroho , Alawiyah Susanti , Ufaira Aprina Patria , Gunawan Indra 
Published: December 2024

Abstract
The physical properties of the subsurface are a crucial consideration in various geoscientific analyses. Geophysical methods offer insights into the distribution of subsurface physical properties, with varying approximations based on these properties. One approach to developing a subsurface model is inverse modeling, a technique that converts data into models. However, new approaches are needed for gravity inversion methods to obtain models with reduced ambiguity. Stochastic inversion techniques are commonly used to avoid local optima that can occur in gravity data modeling due to the underdetermined nature of the model parameters. Nonetheless, a key constraint of this approach is selecting a range of model parameters that accurately represent the geological conditions. To address this issue, the Bat Algorithm is applied as a meta-heuristic method to stochastic inversion techniques. This method emulates the behavior of microbats in randomly searching for prey in the model space. Through simultaneous communication, all microbats aim to locate the best solution within a global search topology, thereby avoiding the entrapment of local optima. This study aims to develop a novel approach to 3D modeling of gravity data through inversion methods. A 3D grid of stacked rectangular prisms serves as the density model, with perturbation achieved through manipulation of the 3D array index as a density grid. Synthetic testing demonstrates a success rate of over 85% for single and multi-layer array models with a density body in the center of the mesh grid. The random distribution of density originates from the bat’s propagation of the Bat Algorithm in finding the best model. The suggested technique displays potential for expansion towards the modeling of gravity data with greater complexity, including its practical application in field data analyses.
Spreadsheets for Geothermal Resource Classification Based on United Nation Framework Classification (UNFC) and Jailolo Geothermal Field Case Study
Authors: Pratama A B , Pratama H B , Ma’fu A A 
Published: December 2024

Abstract
The United Nations Framework Classification (UNFC) is a resource classification method developed by the United Nations Economic Commission for Europe (UNECE) in collaboration with the International Geothermal Association (IGA). UNFC assesses and classifies geothermal resources based on three aspects: socio-economic factors, project feasibility, and geological knowledge. This uniformity in resource classification, assessment, and comparison is significant for global communication regarding geothermal resources. Implementing UNFC in Indonesia will impact the development and financing of this renewable energy. This paper presents the development of a Microsoft Excel spreadsheet for characterizing geothermal fields in Indonesia using the UNFC classification standard, applied to a specific geothermal field. The spreadsheet categorizes socio-economic factors into axis-E, project feasibility into axis-F, and geological knowledge into axis-G. Case studies were conducted in the Jailolo Geothermal Field, located in Halmahera Regency, North-Maluku Province. The field is at an early stage of development and is included in the government’s drilling program agenda. However, the feasibility of extraction by a defined development project cannot be evaluated due to limited technical data, although site-specific geological studies and exploration activities have identified the potential for an individual deposit with sufficient confidence to warrant drilling or testing. Based on geological studies, the estimated quantities associated with the potential deposit are a low-confidence estimate of 75 MW. The field is categorized as E3.2 for socio-economic aspects, F3.1 for feasibility of extraction based on maturity studies, and G4 for geological studies.
Correlation between N-SPT value and shear wave velocity for clayey soil
Authors: Nurcahyo W D , Prassetyo S H , Simangunsong G M 
Published: December 2024

Abstract
Shear wave velocity (Vs) is an important parameter for tunnel design to evaluate seismic site classification and earthquake hazard at a site. Unfortunately, determining in situ shear wave velocity for large areas is expensive and takes a long time. To overcome these problems, a correlation between the standard penetration test (N-SPT) and Vs is made in order to facilitate predicting Vs from the N-SPT value. N-SPT data were obtained from a total of 41 boreholes ranging from 40 to 85 m in depth. Shear wave velocity was obtained from seismic downhole tests and seismic refraction. The correlation between N-SPT and Vs in this study has a coefficient of regression (R
2) value of 0.901. The correlation in this study is validated using normal consistency ratio, comparison between Vs predicted and Vs measured and a scaled error percent graph. The correlation in this study can be used as a predictor to estimate shear wave velocity for initial design before a survey is conducted.
Effect of core material on random vibration behaviour of foam-based laminated sandwich panels using a modified layerwise theory
Authors: Momeni Saman , Zabihollah Abolghassem 
Published: December 2024

Abstract
This study investigates the vibration response of foam-based laminated sandwich panels (FLSP) under random loading. A modified layerwise displacement theory is employed to account for the varying material properties of the layers throughout the thickness. The dynamic behavior of the FLSP is analyzed using random input excitation, focusing on the impact of different foam materials on the random vibration characteristics. Additionally, the effects of the thickness of both composite and foam sections are examined. Key random parameters, including mean, standard deviation, variance, and autocorrelation, are determined for various core materials. A proof-of-concept experimental setup was developed to validate the proposed modified layerwise theory, demonstrating its effectiveness in random vibration analysis of FLSPs. The results indicate that as the softness of the core material increases, the natural frequency of the FLSP decreases. Conversely, higher core stiffness correlates with increased response parameters in random vibration, including mean value, standard deviation, and variance. Furthermore, FLSPs with stiffer core materials exhibit a higher signal correlation compared to those with softer cores.
Does administrative divisions adjustment affect polluting industries dependence? Evidence from township-town merge in China
Authors: Zheng Xiaodan , Li Shangpu , Li Junwen , Sun Yihong 
Published: December 2024

Abstract
Land distribution is intricately linked to economic quality and sustainable growth, influenced by administrative division adjustment (ADA), which can be categorized into various forms, with the township–town merge (TTM) reform being the most common. This study evaluates the effect of TTM on local governments’ dependence on polluting industries from a fiscal decentralization angle, using the differences-in-differences model with transaction data from China’s land market. Findings reveal that TTM increases local governments’ dependence on polluting industries, especially in districts/counties with weaker economic conditions before the COVID-19 pandemic. Evidence also highlights a notable boundary effect of TTM, though its impact is minimal in districts/counties at provincial borders due to their potentially lower public investment inclination. TTM also increases the decentralization level of districts/counties, thus explaining the increase in local government’s dependence on polluting industries. The empirical results have confirmed such a mechanism. However, top-down supervision limits the effect of the reform to a certain extent. This conclusion offers fresh policy insights for leveraging land supply mechanisms to advance environmental governance in centralized developing nations through the lens of ADA.
Optimizing differential privacy in a federated learning framework: strategies for dynamic clipping and privacy allocation
Authors: Liang Zhaoxian , Chen Yonghong 
Published: December 2024

Abstract
Differential privacy has garnered significant attention for its ability to protect the privacy of parameters uploaded in federated learning. Two key factors in differential privacy, threshold clipping and the privacy budget, determine the amount of noise added to the data to achieve privacy protection. However, traditional differential privacy approaches do not account for the unique dynamic characteristics of the federated learning process, often resulting in trade-offs between privacy protection and model performance. To address this limitation, this study proposes a federated learning framework that combines dynamic threshold clipping and adaptive privacy budgeting. By adjusting these parameters in response to the changes during training, our method applies privacy protection more precisely without compromising model performance. The framework effectively balances privacy preservation and model accuracy by dynamically adapting to the training process and data distribution. Experimental results demonstrate that our approach significantly outperforms traditional differential privacy-based federated learning algorithms.
Concrete sleeper crack detection based on image saliency
Authors: Wu Qingjin , An Xiaoxue , Li Liming 
Published: December 2024

Abstract
Concrete sleepers are crucial infrastructure in railway construction and operation. Sleeper cracks may cause the structural damage or functional failure of sleepers, endangering railway operation safety. A third-order residual crack saliency detection network (R3Net-CSD) model is constructed based on ConvNeXt for detecting concrete sleeper cracks in track inspection images. This model can accurately extract the saliency features of rail sleeper crack images. It first uses ConvNeXt to form the backbone network and a block module to form the first residual, followed by a spatial pyramid (dilated convolution group-based spatial pyramid) module based on the anti-residual structure and the dilated convolution group to form the second residual. Finally, it uses a saliency residual (significance residual) module to form the third residual. Simultaneously, combined with a multilevel joint loss function supervision strategy for supervised learning, the R3Net-CSD model fully utilizes the low-level edge information and high-level semantic information of cracks. By using the images collected by a hand-pushed rail inspection vehicle, a dataset of rail sleeper cracks is manually constructed and the developed model is experimentally validated. A large number of experiments demonstrate that the R3Net-CSD model achieves the best results in multiple indicators, including an average absolute error (mean absolute error) of 0.0082, an average accuracy (average precision) of 0.9764, and an area under the curve value of 0.9995. By combining the calculation method of crack geometric parameters, the quantitative indicators of crack length and width are obtained, with a detection accuracy of 0.1 mm. This research provides a new solution for crack detection in concrete sleepers and the measurement of geometric parameters.
Adhesive thickness effect upon the CFRP plate-concrete interface bond behaviours
Authors: Xiong Huixia , Zhang Qian , Guo Shihui 
Published: December 2024

Abstract
Bonding behavior at the interface between concrete and carbon fiber reinforced polymer (CFRP) is very important for the FRP efficiency in concrete structure strengthening. Influences of the adhesive thickness upon BP is rarely studied in the previous literature. In this paper, based upon testing data of 8 single shear specimens, a finite element (FE) method is investigated to analyze debonding in CFRP-concrete interface. By analyzing the specimen failure mode, the FRP strain distributions along bond length, and ultimate bearing capacity (UBC), influences of adhesive thickness on bonding behavior were investigated. Our data prove that the adhesive thickness has significant effects upon bonding behaviors between concrete and CFRP interface. With an increment of adhesive thickness, bond strength increases and reaches the maximum at 3 mm. If the adhesive thickness is > 3 mm, bond strength of the low-grade concrete specimen is reduced. However, the high-grade concrete specimen bond strength continues to increase, but the rate of increase decreases.