Balance Method Research Articles

Unlocking the power of optimized data balancing ratios: a new frontier in tackling imbalanced datasets

Data balancing methods eliminate the problem of imbalanced class distributions, which often lead to the majority class being well-learned while the minority class remains underrepresented, negatively affecting classification performance. This study applies data balancing to the healthcare domain, a critical field where classification success directly impacts human life. The primary aim is to introduce novel balancing methods while addressing the previously overlooked problem of optimizing data balancing ratios. Six healthcare datasets were used: Wisconsin Diagnostic Breast Cancer (WDBC), Wisconsin Prognostic Breast Cancer (WPBC), Z-Alizadeh Sani, Kidney, Diabetes, and Stroke, all characterized by significant diseases and imbalanced class distributions. Six balancing methods were tested, including synthetic minority oversampling technique (SMOTE), adaptive synthetic sampling (ADASYN), support vector machine-SMOTE (SVM-SMOTE), Borderline-SMOTE, cubic interpolation, and quadratic interpolation, with interpolation-based methods being adapted to this domain for the first time. The critical factor in data balancing is identifying the optimal ratio that maximizes classification performance. In this study, particle swarm optimization (PSO), whale optimization algorithm (WOA), and Optuna optimization methods were used to optimize balancing ratios via a custom-designed fitness function that simultaneously optimizes classification accuracy and resource consumption. Classification was conducted for three scenarios: full balance, optimized balance, and imbalance, using support vector machine (SVM), random forest (RF), and ensemble learning (EL) classifiers, allowing for extensive analysis. Each combination of balancing methods, classifiers, and optimization techniques was separately analyzed using metrics such as accuracy, precision, recall, F1-score, time, central processing unit (CPU) usage, and memory usage. As a result, the combination that optimally balances classification accuracy and resource consumption was determined for each dataset, providing both comprehensive analysis and insights into the impact of balancing ratio optimization on diagnostic success in health care.

Modified Solution–Diffusion Model Incorporating Rotational Kinetic Energy in Pressure Retarded Osmosis

Pressure-retarded osmosis (PRO) is a process that allows the production of mechanical energy from the chemical potential difference between two solutions of different concentrations separated by a semi-permeable membrane. One of the main obstacles for this technology to be commercially competitive is the difference between the theoretical power density and the experimental power density due to negative factors like ICP. Analytical models facilitate the analysis of the relationships between system parameters and thus facilitate the optimization of components. In general, PRO has traditionally been explained through the solution–diffusion model, where the flow of water through the membrane depends on a diffusivity factor, the concentration gradient, and the hydraulic pressure gradient. This paper focuses on developing a modified solution–diffusion model that includes means to control the ICP through rotational kinetic energy. An energy balance method for obtaining a solution diffusion-based model is explained, and an analytical model is obtained. Finally, said model is verified through simulations with parameters reported in the literature to obtain insight on the required dimensions for a prototype. It was found that a turning radius of 0.5 m and an angular speed of less than 3000 rev/min could generate enough kinetic energy to compensate for ICP losses in a PRO scenario. Also, the results suggest that bigger concentration differences could benefit more of this technology, as they require almost the same energy as smaller concentration differences but allow for more energy extraction.

Research on Rotor Dynamic Characteristics of High Speed Aviation Piston Pump

The high-speed aviation piston pump plays a vital role in hydraulic systems in the aviation field. Extremely complex force situations happen during running operations due to the coupling between multiple components, as a result of the overall dynamic characteristics being complex and changeable, which brings great difficulties and challenges to its performance optimization. Taking the high-speed aviation piston pump as the research object, a mechanical balance equation of the piston based on the dynamic balance method was proposed. The reaction force of the swashplate and the influence of rotational speed and outlet pressure on it were modeled. Through the balance of the system and the component subsystem, the load of the support bearing of the piston pump under different working conditions is analyzed, as well as the influence of the rotational speed and the outlet pressure on the bearing stiffness by the quasi-static method. In addition, the discrete model of the piston pump spindle and the discrete model of the rotor system are established. The accuracy of the model is verified by the finite element method. The maximum error of the spindle discrete model is 6.13%, and the maximum error of the rotor system discrete model is 15.28%. The transfer matrix analysis shows that the working condition parameters have little effect on the critical speed of the spindle and rotor system, and the outlet pressure has a more significant effect than the speed. The research results provide a theoretical basis and analysis method for the dynamic analysis and structural optimization of the high-speed aviation piston pump.

Giant Pacific octopus optimizer based on fitness-distance balance and natural survival method to solve time-cost-quality-labor trade-off problem in construction projects

ABSTRACT To successfully arrange, execute, monitor, and complete a project, a project manager must play a key role in project management. The utilization of technology and artificial intelligence in the engineering industry has grown absolutely essential and guarantees that each nation’s socioeconomic development needs are accomplished. This study proposes the Giant Pacific Octopus Optimizer Based on Fitness-Distance Balance and Natural Survivor Method to tackle the challenge of optimizing the optimal combination of time, cost, quality, and labor tradeoff in the construction industry. The Natural Survivor Method and Fitness Distance Balance selection techniques, along with the Tournament Selection technique, are used in this research to redesign and further enhance the mechanism of the Giant Pacific Octopus Optimizer, which enhances the convergence time by rapidly transitioning from random selection to best candidate selection. The results of Giant Pacific Octopus Optimizer Based on Fitness-Distance Balance and Natural Survivor Method were compared with many well-known, comparable algorithms to demonstrate the viability and effectiveness of the proposed model through case study of construction management, Friedman test, Wilcoxon Signed Rank test, Indicators evaluation and Stability analysis. Based on the results obtained, a robust model that is superior to the evaluated models was developed in this research.

A Method to Handle Unbalanced Systems in Branch Current-Based State Estimators

The undergoing energy transition to a sustainable future requires, among other things, the application of demand side management (DSM) techniques to maintain grid stability and allow a smooth performance. To successfully implement DSM strategies, near real-time monitoring of the grid is required. This can be achieved through a distribution system state estimator (DSSE). Conventional approaches to state estimation (SE) typically rely on the assumption of a balanced reference bus, which is reasonable for transmission systems but may not be applicable to low-voltage distribution networks, even more with significant distributed generation (DG) penetration. To address this problem, a branch current-based low-voltage DSSE for unbalanced three-phase systems is developed. The algorithm incorporates a virtual bus to account for highly unbalanced systems, enabling it to obtain a more accurate estimation of the grid state. The proposed method is compared to the conventional balanced reference bus method through multiple simulations under different load conditions in the IEEE European low-voltage test feeder.

Dynamic Characteristics and Periodic Stability Analysis of Rotor System with Squeeze Film Damper Under Base Motions

Inertial loads induced by base motion excitation introduce significant complexities in equilibrium point determination and linearization of systems incorporating squeeze film dampers (SFDs). The coupled effects of base motion excitation and SFD characteristics on periodic stability have received limited attention in previous investigations. This study investigates the dynamic characteristics and periodic stability of a rotor system with SFD subjected to base motion excitation. A finite element model of the rotor-SFD-support system under non-inertial motion is established. The periodic responses are solved using the harmonic balance method with alternating frequency/time technique (HB-AFT) and the arc-length continuation algorithm incorporating the predictor–corrector method, while system stability is analyzed using Floquet theory and the Newmark method. A systematic parametric study is conducted to investigate the effects of base motion parameters, mass unbalance, and SFD parameters on the system’s periodic response. Results demonstrate that base pitching motion enhances system stability, suppresses bistable responses and jump phenomena, and reduces unstable vibration regions. However, under specific parameter combinations, pitching motion can trigger secondary Hopf bifurcations, leading to quasi-periodic and chaotic motions, among other complex nonlinear behaviors. This research provides theoretical foundations for stability-oriented design optimization of rotor systems with SFDs under base motion excitation.

Improvements in the vertical-laser alignment method for joule balance

A vacuum-compatible vertical-laser alignment method based on an oil mirror and an air-spaced lens is used to measure and compensate for the vertical deviation angle of the laser beams in a joule balance. This paper reports improvements in this alignment method regarding the focal-plane positioning error, off-axis error of the lens, tradeoff of oil mirror parameters, and measurement resolution. Dual spot coincidence is used to locate the lens focal plane, and the optimal collimation region in the Gaussian beam of the laser source is located, which is regarded as a parallel light source. An observation mechanism is designed to realize the online detection of the lens off-axis distance, and the optimal area for balancing the influence of the angular error of the corner cube and the lens off-axis distance is preliminarily obtained. The performance parameters of silicone oil are balanced, and the measurement resolution is improved from three perspectives. The sealing performance of the chamber for containing silicone oil is also verified experimentally. Furthermore, through an experiment, the measurement accuracy of the vertical-laser alignment method is preliminarily verified.

OPTIMALISASI KINERJA TEKNIS PENGELOLAAN DAERAH IRIGASI SALURAN INDUK MADIUN KABUPATEN MADIUN

Ulo Secondary Canal which has an irrigation area of 1,352 ha is one of the secondary canals in the Madiun Main Canal. Ulo Secondary Canal is supplied by three dams namely Semawur Dam, Jati Dam and Gondrok Dam which are located in Madiun Regency. The Madiun Main Canal Irrigation Area has been rehabilitated in 2019, and has been completed in 2022. The Madiun Main Irrigation Channel area is still in need of water. The methods used to calculate water requirements are Climatology Method, FJ. Mock Method, and Water Balance Method. From the calculation, it is known that the condition before rehabilitation, the value of water availability cannot fulfill agricultural water needs in the Ulo Secondary Canal area. In conditions before rehabilitation, the supply from Jati Dam is 18% with a value between 0.43 m3/s - 0.72 m3/s, coupled with water withdrawal at the Semawur Dam intake of 0.06 m3/s and water withdrawal at the Gondrok Dam intake of 0.07 m3/s. The existing water availability can only fulfill the needs of the cropping pattern of paddy (20%) - crops (40%) - crops (45%), with the smallest residual discharge value of 0.09 m3/s in April III. After rehabilitation, the supply value of Jati Dam is 15% with a value between 2.17 m3/s - 2.72 m3/s, with water withdrawal at the Semawur Dam intake of 0.06 m3/s and water withdrawal at the Gondrok Dam intake of 0.07 m3/s.The percentage value after rehabilitation is smaller than before rehabilitation but the value of water supply is bigger. Based on these conditions, several alternative cropping patterns are planned, such as Paddy (100%) - Crops (100%) - Crops (100%), Paddy (100%) - Paddy (100%) - Crops (100%) and Paddy (100%) - Paddy (100%) - Paddy (100%) with a profit amounting to IDR 6,415,515,780.00 in conditions before rehabilitation and after rehabilitation, on alternative III with a cropping pattern of paddy (100%) - paddy (100%) - paddy (100%) obtained the highest profit amounting to IDR 62,144,490,720.00.

Intraoperative Tranexamic Acid Infusion Reduces Perioperative Blood Loss in Pediatric Limb-Salvage Surgeries: A Double-Blinded Randomized Placebo-Controlled Trial.

Limb-salvage surgery for malignant bone tumors can be associated with considerable perioperative blood loss. The aim of this randomized controlled trial was to assess the safety and efficacy of the intraoperative infusion of tranexamic acid (TXA) in children and adolescents undergoing limb-salvage surgery. All participants were <18 years of age at the time of surgery and diagnosed with a malignant bone tumor of the femur that was treated with resection and reconstruction with a megaprosthesis. Exclusion criteria included anatomic locations other than the femur, reconstruction with a vascularized fibular graft, and a previous history of deep venous thrombosis, coagulopathy, or renal dysfunction. Participants were randomly allocated to either the TXA group (a preoperative loading dose infusion of 10 mg/kg of TXA followed by a continuous infusion of 5 mg/kg/hr until the end of surgery) or the placebo group (the same dosage but with TXA substituted with an infusion of normal saline solution). Intraoperative and perioperative blood loss were calculated with use of the hemoglobin balance method. Perioperative blood loss at postoperative day 1 and at discharge from the hospital were calculated. The total volumes of blood transfused intraoperatively and postoperatively were recorded. A statistical comparison between the groups was performed for blood loss and blood transfusion as well as for possible independent variables other than TXA, including age, body mass index, histopathologic diagnosis, tumor volume, preoperative hemoglobin level, type of resection, and the duration of surgery. A total of 48 participants, with a mean age of 12.5 ± 3.44 years (range, 5 to 18 years) and a male-to-female ratio of 1.18, were included. All participants were Egyptians by race and ethnicity. There were no minor or major drug-related adverse events. There was no significant difference between the groups with respect to intraoperative blood loss (p = 0.0616) or transfusion requirements (p = 0.812), but there was a significant difference in perioperative blood loss at postoperative day 1 (p = 0.0144) and at discharge from the hospital (p = 0.0106) and in perioperative blood transfusion (p = 0.023). TXA can be safely infused intraoperatively in children and adolescents undergoing limb-salvage surgery, and it contributes significantly to the reduction of perioperative blood loss and transfusion requirements. Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.

An improved soft voting-based machine learning technique to detect breast cancer utilizing effective feature selection and SMOTE-ENN class balancing

Breast cancer is the primary cause of death among women globally, and it is becoming more prevalent. Early detection and precise diagnosis of breast cancer can reduce the disease’s mortality rate. Recent advances in machine learning have benefited in this regard. However, if the dataset contains duplicate or irrelevant features, machine learning-based algorithms are unable to give the intended results. To address this issue, a series of effective strategies such as the Robust Scaler is used for data scaling, Synthetic Minority Over-sampling Technique-Edited Nearest Neighbor (SMOTE-ENN) is utilized for class balancing, and Boruta and Coefficient-Based Feature Selection (CBFS) methods are employed for feature selection. For more accurate and reliable breast cancer classification, this study proposes a soft voting-based ensemble model that harnesses the capabilities of three diverse classifiers: Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). To show the efficiency of the proposed ensemble model, it is compared with its base classifiers using the Wisconsin Diagnosis Breast Cancer Dataset (WDBC). The results of the experiment revealed that the soft voting classifier achieved high scores with an accuracy of 99.42%, precision of 100.0%, recall of 98.41%, F1 score of 99.20%, and AUC of 1.0 when it is trained on optimal features obtained from the CBFS method. However, with tenfold cross-validation (10-FCV), it shows a mean accuracy score of 99.34%. A comprehensive analysis of the results revealed that the suggested technique outperformed the existing state-of-the-art methods due to the efficient data preprocessing, feature selection, and ensemble methods.

System response tracking based on the Runge–Kutta method and the incremental harmonic balance method

System response tracking based on the Runge–Kutta method and the incremental harmonic balance method

Halogen Emissions from Coal-Fired Power Plants in China: Evolutions, Driving Forces, and Future Trends.

Atmospheric halogens, including fluorine (F), chlorine (Cl), bromine (Br), and iodine(I), significantly impact atmospheric chemistry and climate change. Containing all types of halogens, coal fired power plants (CFPPs) are among the major anthropogenic sources of atmospheric halogens. However, comprehensive estimates of halogen emissions from CFPPs in China remain limited, despite significant advancements in scale and pollution control. This study developed a detailed emissions inventory for all halogens from CFPPs using multisource data and the mass balance method, analyzing their spatiotemporal variations, driving forces, and future trends under climate goals. Results showed fluctuating halogen emissions from 2018 to 2022, with F, Cl, Br, and I reaching 6,875.7 t, 24,872.4 t, 1,127.9 t, and 476.7 t in 2022, respectively. Emissions were predominately concentrated in key coal resource areas and high-energy-consuming regions. Increased coal consumption was the primary driver of emissions growth, while improvements in pollution control and power generation technology contributed to reductions. Under air pollution control and climate goals, halogen emissions are expected to peak before 2030 and decline rapidly thereafter, with near-elimination by 2050. Combining strict air pollutants and carbon control technologies would offer the greatest reduction potential.

Investigating nonlinear dynamic properties of an inertial sensor with rotational velocity-dependent rigidity

This study investigates the nonlinear dynamics of a system with frequency-dependent stiffness using a MEMS-based capacitive inertial sensor as a case study. The sensor is positioned directly on a rotating component of a machine and consists of a microbeam clamped at both ends by fixed supports with a fixed central proof mass. The nonlinear behavior is determined by electrostatic forces, axial and bending motion coupling, and frequency-dependent stiffness. The numerical Galerkin approach is employed for discretization of the coupled differential equations in spatial coordinates. To obtain the sensor response as a function of frequency, a continuation arc-length method based on weak formulation energy balance method is used. This approach uses a physical gradient descent learning based method to obtain unknown coefficients of the considered response. The presented method computes the periodic steady-state solution of the design by considering different frequency contents within the response, including different harmonics of the response expansion. However, the primary and secondary resonances at various harmonic frequencies within the response can be predicted. In this article, the dynamic behavior of the design is investigated by testing different levels of shaft acceleration and different bias voltages. The purpose of the evaluation is to determine the frequency-dependent stiffness of the accelerometer for different levels of shaft speed, taking into account various sensor geometric parameters. The analysis demonstrates the behavior of the sensors under different conditions, particularly highlighting the nonlinearity of the sensor, which causes primary and secondary resonances in the first, second, and third harmonic responses of the accelerometer, especially at higher bias voltages. Fast Fourier analyses indicated that the transversal vibration amplitude of the structure in the second and third harmonies are so considerable that cannot be neglected. The mathematical method used in this study can be applied by researchers and engineers in the design of such sensors to effectively create these devices.

PROBLEMS OF ENVIRONMENTAL SECURITY AND WATER SUPPLY NEEDS IN THE CENTRAL ASIAN REGION

he last decade in the Central Asian region has been characterized by a steady trend of increasing fresh water needs due to the expansion of agricultural activities and the growth of population consumption. At the same time, the growth of consumption is ensured exclusively by increasing the anthropogenic load on available water resources, which causes a multiple increase in the risks of environmental disasters and problems with water supply and ensuring water security of the countries of the region. The article uses the method of complex assessment (balance method) of assessing the level of water resources availability in the context of countries, content analysis of regulation of water use of transboundary rivers, factor analysis of the growth of regulation of water flows of the main rivers (Amu Darya and Syr Darya basins, hereinafter abbreviated as BAM) and project analysis of the growth of anthropogenic pressure on the resource base of the region. The study notes that the uncoordinated use of water resources for national development and projects to overcome the environmental problems of shallowing of the Aral Sea only lead to an aggravation of the situation. The conclusions are based on the assessment of projects and strategies for overcoming the environmental catastrophe of the Aral Sea and the construction of new artificial water drainage infrastructure in the countries of the lower reaches of transboundary rivers.

Magnetization and Anisotropy of Magnetic Susceptibility of a Liquid Crystal Doped with Chlorophylls a, b and Carotenoids.

The magnetization and anisotropy of magnetic susceptibility of a 5CB nematic liquid crystal doped three extracts containing chlorophylls a and b and carotenoids in different weight percentage has been studied. The extracts have been dissolved in the liquid crystal matrix at a concentration of 2%. The magnetic susceptibility of the substances has been measured by the Faraday-Curie balance method. The field σ(H) and temperature Δχ(T) dependences of molar magnetizations σ and anisotropy of magnetic susceptibility Δχ for the investigated objects have been obtained. The divergence of the σ(H) dependences for the extracts dissolved in the liquid crystal matrix and in acetone has been found. The growth of the Δχ values in the Δχ(T) dependence with an increase in the weight percentage of chlorophylls in the extracts has been established. The influence of molecules of the dopants on the anisotropy of magnetic susceptibility has been evaluated with allowance for the π-electron currents in the conjugated systems of the benzene rings and in the porphyrin nuclei of chlorophylls, as well as in chemical bonds of the aliphatic fragments.

Comprehensive Analysis and Emission Reduction Pathway of GHG Emissions at a Wastewater Treatment Plant in Suzhou

Taking a sewage treatment plant in Suzhou City, Jiangsu Province, as an example, the greenhouse gas （GHG） emissions generated in the sewage treatment system were calculated using the carbon balance method and the emission factor method. The environmental impacts and economic aspects of different treatment units in wastewater treatment plants were analyzed using life cycle assessment, cost-benefit analysis, and data envelopment analysis models, and emission reduction pathways were proposed. The results indicated that the total GHG emissions （in terms of CO2） from a certain municipal wastewater treatment plant in Suzhou were 6 653.08 kg·（104 m3）-1, with direct and indirect GHG emissions accounting for 29.22% and 74%, respectively. The reuse of treated effluent achieved a reduction of 3.3% in emissions. The biological treatment phase and the sludge treatment phase were the main impact stages for GHG emissions at a certain wastewater treatment plant in Suzhou, where the high-power equipment, specifically the blowers used in the biological treatment phase, and the use of polymeric ferric sulfate agents in the sludge treatment phase were the primary factors contributing to GHG emissions. Life cycle assessment analysis revealed that electricity consumption, direct CO2 emissions, pollutant concentration in the effluent, and the use of chemical agents at wastewater treatment plants had negative impacts on global warming, atmospheric acidification, and eutrophication of water bodies. Calculations indicated that for every 10 000 m3 of wastewater treated, the sewage treatment plant achieved a net benefit of 13 630 RMB. However, from April to May 2023, the scale efficiency of the sewage treatment plant was less than 1. This indicates that during this period, the proportion of output increase was less than that of input increase, demonstrating an irrational structure of input-output. After June, through enhancing the overall operational load, advancing technical improvements, and management efforts, the optimization of scale efficiency was achieved. A sewage treatment plant in Suzhou could achieve the goal of being "green and low-carbon" by installing high-efficiency pumps and fans, utilizing solar photovoltaic and water source heat pump systems, and making process improvements.

Patterns and Drivers of Surface Energy Flux in the Alpine Meadow Ecosystem in the Qilian Mountains, Northwest China.

Alpine meadows are vital ecosystems on the Qinghai-Tibet Plateau, significantly contributing to water conservation and climate regulation. This study examines the energy flux patterns and their driving factors in the alpine meadows of the Qilian Mountains, focusing on how the meteorological variables of net radiation (Rn), air temperature, vapor pressure deficit (VPD), wind speed (U), and soil water content (SWC) influence sensible heat flux (H) and latent heat flux (LE). Using the Bowen ratio energy balance method, we monitored energy changes during the growing and non-growing seasons from 2022 to 2023. The annual average daily Rn was 85.29 W m-2, with H, LE, and G accounting for 0.56, 0.71, and -0.32 of Rn, respectively. Results show that Rn is the main driver of both H and LE, highlighting its crucial role in turbulent flux variations. Additionally, a negative correlation was found between air temperature and H, suggesting that high temperatures may suppress H. A significant positive correlation was observed between soil moisture and LE, further indicating that moist soil conditions enhance LE. In conclusion, this study demonstrates the impact of climate change on energy distribution in alpine meadows and calls for further research on the ecosystem's dynamic responses to changing climate conditions.

Optimization of drying parameters and texture properties of winter jujube slices by radio frequency combined with hot air.

In order to improve the drying quality of winter jujube slices and find the best drying process parameters, RF + HA (radio frequency combined hot air) drying technology was used in this study to study the effects of plate spacing, RF application time, and RF interval time on the quality of winter jujube slices. Vitamin C (VC) content, red and green value (a*), and drying rate (DR) were used as quality indexes, and the changing trend of texture properties was analyzed. According to the conclusion of the single-factor experiment, the orthogonal experiment is carried out, and the parameters of each factor in the orthogonal experiment are optimized by the comprehensive balance method and matrix analysis method. The results showed as follows: (1) Plate spacing, RF application, and interval time all significantly affected the drying properties in the single-factor test (p < 0.05). The VC content of winter jujube slices increased and then decreased with the increase in the three factors. (2) In the orthogonal test, the order of influence of each factor on the quality of the winter jujube tablet is plate spacing > RF interval time > RF application time. The optimum RF heat treatment parameters are plate spacing of 100 mm, RF application time of 3 min, and RF interval time of 2 min. Under these conditions, the VC content of the winter jujube slices was 258.35 mg/100 g, a* was -9.47 and the DR was 0.64 g/min. (3) RF + HA has more advantages in shortening drying time and maintaining shape, reducing hardness by 12.6 ~ 18.7% and crispiness by 13.8 ~ 20.4%, the microstructure of jujube slices shows a regular honeycomb shape. The research results provide a new drying combination mechanism and process optimization scheme for improving the drying technology of winter jujube slices in industrial production.

Application of an adaptive observer for the detection and location of pipeline leak

Leakages in hydrocarbon transport pipelines are a recurring problem. Their real-time diagnosis is a priority task. Timely resolution of leaks helps avoid human casualties, environmental harm, and infrastructure damage. This work focuses on simulating the hydrodynamic behavior along a pipeline to enable timely leak detection and localization through a novel computational tool. The proposed mathematical model identifies discrepancies between the mass and momentum equations and an adaptive observer’s estimation, which considers the leaking fluid like a system perturbation. The flow volume balance method confirms the existence of a leakage. A fluid quantifier estimates the total leaked volume during the detection period. The estimation error between the measured and estimated variables for the adaptive observer approximates the leakage location. The developed software was validated by comparing the results with a real leak scenario in a 20-inch diameter, 15 km long liquefied petroleum gas pipeline. The results demonstrate the tool’s feasibility for real-time leak detection, localization, and quantification, showcasing its potential for addressing recurring pipeline leaks.

Sustainable Urban Cultural Heritage Policy in the City of Yogyakarta, Indonesia

This study investigates the preservation of urban heritage in Yogyakarta, Indonesia, exploring the delicate balance between conserving cultural heritage and fostering modern urban development. In the face of rapid urbanization and globalization, Yogyakarta’s rich Javanese heritage encounters significant challenges in maintaining its historical and cultural assets while accommodating contemporary needs. This research underscores the importance of urban heritage—including historical, cultural, and architectural elements—in preserving the identity of metropolitan areas. The primary aim of this study is to analyse Yogyakarta’s policy on cultural preservation, focusing on the city government’s strategies to harmonize heritage conservation with urban development. The methodology employed includes Focus Group Discussions with local leaders, interviews with academics, analysis of government policies, on-site observations, and media content analysis. The findings indicate that Yogyakarta’s approach to cultural heritage management represents a distinctive model within Indonesia, successfully integrating heritage preservation with economic growth and cultural identity. This approach emphasizes the crucial roles of the community and government in safeguarding heritage and traditions. The study proposes a balanced method of development and conservation, presenting Yogyakarta’s model as a potential guide for other cities. This model highlights the value of community involvement and the significance of cultural heritage in enriching contemporary and future societal contexts.